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Tsantilas KA, Merrihew GE, Robbins JE, Johnson RS, Park J, Plubell DL, Huang E, Riffle M, Sharma V, MacLean BX, Eckels J, Wu CC, Bereman MS, Spencer SE, Hoofnagle AN, MacCoss MJ. A framework for quality control in quantitative proteomics. bioRxiv 2024:2024.04.12.589318. [PMID: 38645098 PMCID: PMC11030400 DOI: 10.1101/2024.04.12.589318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow from planning to analysis. We share real-world case studies applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at protein and peptide-level allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis using Skyline, longitudinal QC metrics using AutoQC, and server-based data deposition using PanoramaWeb. We propose that this integrated approach to QC be used as a starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible.
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Vicente JJ, Wagenbach M, Decarreau J, Zelter A, MacCoss MJ, Davis TN, Wordeman L. The kinesin motor Kif9 regulates centriolar satellite positioning and mitotic progression. bioRxiv 2024:2024.04.03.587821. [PMID: 38617353 PMCID: PMC11014612 DOI: 10.1101/2024.04.03.587821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Centrosomes are the principal microtubule-organizing centers of the cell and play an essential role in mitotic spindle function. Centrosome biogenesis is achieved by strict control of protein acquisition and phosphorylation prior to mitosis. Defects in this process promote fragmentation of pericentriolar material culminating in multipolar spindles and chromosome missegregation. Centriolar satellites, membrane-less aggrupations of proteins involved in the trafficking of proteins toward and away from the centrosome, are thought to contribute to centrosome biogenesis. Here we show that the microtubule plus-end directed kinesin motor Kif9 localizes to centriolar satellites and regulates their pericentrosomal localization during interphase. Lack of Kif9 leads to aggregation of satellites closer to the centrosome and increased centrosomal protein degradation that disrupts centrosome maturation and results in chromosome congression and segregation defects during mitosis. Our data reveal roles for Kif9 and centriolar satellites in the regulation of cellular proteostasis and mitosis.
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Wu CC, Tsantilas KA, Park J, Plubell D, Sanders JA, Naicker P, Govender I, Buthelezi S, Stoychev S, Jordaan J, Merrihew G, Huang E, Parker ED, Riffle M, Hoofnagle AN, Noble WS, Poston KL, Montine TJ, MacCoss MJ. Mag-Net: Rapid enrichment of membrane-bound particles enables high coverage quantitative analysis of the plasma proteome. bioRxiv 2024:2023.06.10.544439. [PMID: 38617345 PMCID: PMC11014469 DOI: 10.1101/2023.06.10.544439] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Membrane-bound particles in plasma are composed of exosomes, microvesicles, and apoptotic bodies and represent ~1-2% of the total protein composition. Proteomic interrogation of this subset of plasma proteins augments the representation of tissue-specific proteins, representing a "liquid biopsy," while enabling the detection of proteins that would otherwise be beyond the dynamic range of liquid chromatography-tandem mass spectrometry of unfractionated plasma. We have developed an enrichment strategy (Mag-Net) using hyper-porous strong-anion exchange magnetic microparticles to sieve membrane-bound particles from plasma. The Mag-Net method is robust, reproducible, inexpensive, and requires <100 μL plasma input. Coupled to a quantitative data-independent mass spectrometry analytical strategy, we demonstrate that we can collect results for >37,000 peptides from >4,000 plasma proteins with high precision. Using this analytical pipeline on a small cohort of patients with neurodegenerative disease and healthy age-matched controls, we discovered 204 proteins that differentiate (q-value < 0.05) patients with Alzheimer's disease dementia (ADD) from those without ADD. Our method also discovered 310 proteins that were different between Parkinson's disease and those with either ADD or healthy cognitively normal individuals. Using machine learning we were able to distinguish between ADD and not ADD with a mean ROC AUC = 0.98 ± 0.06.
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Affiliation(s)
- Christine C. Wu
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Jea Park
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Deanna Plubell
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Justin A. Sanders
- Department of Computer Science, University of Washington, Seattle, WA, USA
| | | | | | | | | | | | - Gennifer Merrihew
- Department of Computer Science, University of Washington, Seattle, WA, USA
| | - Eric Huang
- Department of Computer Science, University of Washington, Seattle, WA, USA
| | - Edward D. Parker
- Vision Core Lab, Department of Ophthalmology, University of Washington, Seattle, WA, USA
| | - Michael Riffle
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Andrew N. Hoofnagle
- Department of Lab Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - William S. Noble
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Department of Computer Science, University of Washington, Seattle, WA, USA
| | - Kathleen L. Poston
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto CA, USA
| | | | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
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4
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Moradian A, Goonatilleke E, Lin TT, Hatten-Beck M, Emrick M, Schepmoes AA, Fillmore TL, MacCoss MJ, Sechi S, Sobhani K, Little R, Kabytaev K, van Eyk JE, Qian WJ, Hoofnagle AN. Interlaboratory Comparison of Antibody-Free LC-MS/MS Measurements of C-peptide and Insulin. Clin Chem 2024:hvae034. [PMID: 38549041 DOI: 10.1093/clinchem/hvae034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 01/29/2024] [Indexed: 05/01/2024]
Abstract
BACKGROUND The enhanced precision and selectivity of liquid chromatography-tandem mass spectrometry (LC-MS/MS) makes it an attractive alternative to certain clinical immunoassays. Easily transferrable work flows could help facilitate harmonization and ensure high-quality patient care. We aimed to evaluate the interlaboratory comparability of antibody-free multiplexed insulin and C-peptide LC-MS/MS measurements. METHODS The laboratories that comprise the Targeted Mass Spectrometry Assays for Diabetes and Obesity Research (TaMADOR) consortium verified the performance of a validated peptide-based assay (reproducibility, linearity, and lower limit of the measuring interval [LLMI]). An interlaboratory comparison study was then performed using shared calibrators, de-identified leftover laboratory samples, and reference materials. RESULTS During verification, the measurements were precise (2.7% to 3.7%CV), linear (4 to 15 ng/mL for C-peptide and 2 to 14 ng/mL for insulin), and sensitive (LLMI of 0.04 to 0.10 ng/mL for C-peptide and 0.03 ng/mL for insulin). Median imprecision across the 3 laboratories was 13.4% (inter-quartile range [IQR] 11.6%) for C-peptide and 22.2% (IQR 20.9%) for insulin using individual measurements, and 10.8% (IQR 8.7%) and 15.3% (IQR 14.9%) for C-peptide and insulin, respectively, when replicate measurements were averaged. Method comparison with the University of Missouri reference method for C-peptide demonstrated a robust linear correlation with a slope of 1.044 and r2 = 0.99. CONCLUSIONS Our results suggest that combined LC-MS/MS measurements of C-peptide and insulin are robust and adaptable and that standardization with a reference measurement procedure could allow accurate and precise measurements across sites, which could be important to diabetes research and help patient care in the future.
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Affiliation(s)
- Annie Moradian
- Precision Biomarker Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Elisha Goonatilleke
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
| | - Tai-Tu Lin
- Integrative Omics, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
| | - Maya Hatten-Beck
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
| | - Michelle Emrick
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
| | - Athena A Schepmoes
- Integrative Omics, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
| | - Thomas L Fillmore
- Integrative Omics, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Salvatore Sechi
- Division of Diabetes, Endocrinology, & Metabolic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Kimia Sobhani
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Randie Little
- Department of Pathology and Anatomical Sciences, University of Missouri School of Medicine, Columbia, MO, United States
| | - Kuanysh Kabytaev
- Department of Pathology and Anatomical Sciences, University of Missouri School of Medicine, Columbia, MO, United States
| | - Jennifer E van Eyk
- Precision Biomarker Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Advanced Clinical Biosystems Research Institute, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Wei-Jun Qian
- Integrative Omics, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
| | - Andrew N Hoofnagle
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
- Department of Medicine, Kidney Research Institute, University of Washington, Seattle, WA, United States
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5
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Bailey LRJ, Bugg D, Reichardt IM, Ortaç CD, Nagle A, Gunaje J, Martinson A, Johnson R, MacCoss MJ, Sakamoto T, Kelly DP, Regnier M, Davis JM. MBNL1 Regulates Programmed Postnatal Switching Between Regenerative and Differentiated Cardiac States. Circulation 2024. [PMID: 38426339 DOI: 10.1161/circulationaha.123.066860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 02/05/2024] [Indexed: 03/02/2024]
Abstract
BACKGROUND Discovering determinants of cardiomyocyte maturity is critical for deeply understanding the maintenance of differentiated states and potentially reawakening endogenous regenerative programs in adult mammalian hearts as a therapeutic strategy. Forced dedifferentiation paired with oncogene expression is sufficient to drive cardiac regeneration, but elucidation of endogenous developmental regulators of the switch between regenerative and mature cardiomyocyte cell states is necessary for optimal design of regenerative approaches for heart disease. MBNL1 (muscleblind-like 1) regulates fibroblast, thymocyte, and erythroid differentiation and proliferation. Hence, we examined whether MBNL1 promotes and maintains mature cardiomyocyte states while antagonizing cardiomyocyte proliferation. METHODS MBNL1 gain- and loss-of-function mouse models were studied at several developmental time points and in surgical models of heart regeneration. Multi-omics approaches were combined with biochemical, histological, and in vitro assays to determine the mechanisms through which MBNL1 exerts its effects. RESULTS MBNL1 is coexpressed with a maturation-association genetic program in the heart and is regulated by the MEIS1/calcineurin signaling axis. Targeted MBNL1 overexpression early in development prematurely transitioned cardiomyocytes to hypertrophic growth, hypoplasia, and dysfunction, whereas loss of MBNL1 function increased cardiomyocyte cell cycle entry and proliferation through altered cell cycle inhibitor transcript stability. Moreover, MBNL1-dependent stabilization of estrogen-related receptor signaling was essential for maintaining cardiomyocyte maturity in adult myocytes. In accordance with these data, modulating MBNL1 dose tuned the temporal window of neonatal cardiac regeneration, where increased MBNL1 expression arrested myocyte proliferation and regeneration and MBNL1 deletion promoted regenerative states with prolonged myocyte proliferation. However, MBNL1 deficiency was insufficient to promote regeneration in the adult heart because of cell cycle checkpoint activation. CONCLUSIONS Here, MBNL1 was identified as an essential regulator of cardiomyocyte differentiated states, their developmental switch from hyperplastic to hypertrophic growth, and their regenerative potential through controlling an entire maturation program by stabilizing adult myocyte mRNAs during postnatal development and throughout adulthood. Targeting loss of cardiomyocyte maturity and downregulation of cell cycle inhibitors through MBNL1 deletion was not sufficient to promote adult regeneration.
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Affiliation(s)
- Logan R J Bailey
- Laboratory Medicine and Pathology, University of Washington, Seattle.(L.R.J.B., D.B., C.D.O., J.G., A.M., J.M.D.)
- Molecular and Cellular Biology, University of Washington, Seattle. (L.R.J.B.)
- Medical Scientist Training Program, University of Washington, Seattle. (L.R.J.B.)
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle. (L.R.J.B., D.B., I.M.R., C.D.O., A.N., J.G., A.M., M.R.)
| | - Darrian Bugg
- Laboratory Medicine and Pathology, University of Washington, Seattle.(L.R.J.B., D.B., C.D.O., J.G., A.M., J.M.D.)
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle. (L.R.J.B., D.B., I.M.R., C.D.O., A.N., J.G., A.M., M.R.)
| | - Isabella M Reichardt
- Bioengineering, University of Washington, Seattle. (I.M.R., A.N., M.R., J.M.D.)
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle. (L.R.J.B., D.B., I.M.R., C.D.O., A.N., J.G., A.M., M.R.)
| | - C Dessirée Ortaç
- Laboratory Medicine and Pathology, University of Washington, Seattle.(L.R.J.B., D.B., C.D.O., J.G., A.M., J.M.D.)
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle. (L.R.J.B., D.B., I.M.R., C.D.O., A.N., J.G., A.M., M.R.)
| | - Abigail Nagle
- Bioengineering, University of Washington, Seattle. (I.M.R., A.N., M.R., J.M.D.)
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle. (L.R.J.B., D.B., I.M.R., C.D.O., A.N., J.G., A.M., M.R.)
| | - Jagadambika Gunaje
- Laboratory Medicine and Pathology, University of Washington, Seattle.(L.R.J.B., D.B., C.D.O., J.G., A.M., J.M.D.)
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle. (L.R.J.B., D.B., I.M.R., C.D.O., A.N., J.G., A.M., M.R.)
| | - Amy Martinson
- Laboratory Medicine and Pathology, University of Washington, Seattle.(L.R.J.B., D.B., C.D.O., J.G., A.M., J.M.D.)
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle. (L.R.J.B., D.B., I.M.R., C.D.O., A.N., J.G., A.M., M.R.)
| | - Richard Johnson
- Genome Sciences, University of Washington, Seattle. (R.J., M.J.M.)
| | | | - Tomoya Sakamoto
- Cardiovascular Institute, Medicine, University of Pennsylvania, Philadelphia (T.S., D.P.K.)
| | - Daniel P Kelly
- Cardiovascular Institute, Medicine, University of Pennsylvania, Philadelphia (T.S., D.P.K.)
| | - Michael Regnier
- Bioengineering, University of Washington, Seattle. (I.M.R., A.N., M.R., J.M.D.)
- Center for Translational Muscle Research, University of Washington, Seattle. (M.R., J.M.D.)
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle. (L.R.J.B., D.B., I.M.R., C.D.O., A.N., J.G., A.M., M.R.)
| | - Jennifer M Davis
- Laboratory Medicine and Pathology, University of Washington, Seattle.(L.R.J.B., D.B., C.D.O., J.G., A.M., J.M.D.)
- Bioengineering, University of Washington, Seattle. (I.M.R., A.N., M.R., J.M.D.)
- Center for Translational Muscle Research, University of Washington, Seattle. (M.R., J.M.D.)
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6
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Lombardi RL, Ramsey JS, Mahoney JE, MacCoss MJ, Heck ML, Slupsky CM. Longitudinal Transcriptomic, Proteomic, and Metabolomic Response of Citrus sinensis to Diaphorina citri Inoculation of Candidatus Liberibacter asiaticus. J Proteome Res 2024. [PMID: 38373055 DOI: 10.1021/acs.jproteome.3c00485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
Huanglongbing (HLB) is a fatal citrus disease that is currently threatening citrus varieties worldwide. One putative causative agent, Candidatus Liberibacter asiaticus (CLas), is vectored by Diaphorina citri, known as the Asian citrus psyllid (ACP). Understanding the details of CLas infection in HLB disease has been hindered by its Candidatus nature and the inability to confidently detect it in diseased trees during the asymptomatic stage. To identify early changes in citrus metabolism in response to inoculation of CLas using its natural psyllid vector, leaves from Madam Vinous sweet orange (Citrus sinensis (L.) Osbeck) trees were exposed to CLas-positive ACP or CLas-negative ACP and longitudinally analyzed using transcriptomics (RNA sequencing), proteomics (liquid chromatography-tandem mass spectrometry; data available in Dryad: 10.25338/B83H1Z), and metabolomics (proton nuclear magnetic resonance). At 4 weeks postexposure (wpe) to psyllids, the initial HLB plant response was primarily to the ACP and, to a lesser extent, the presence or absence of CLas. Additionally, analysis of 4, 8, 12, and 16 wpe identified 17 genes and one protein as consistently differentially expressed between leaves exposed to CLas-positive ACP versus CLas-negative ACP. This study informs identification of early detection molecular targets and contributes to a broader understanding of vector-transmitted plant pathogen interactions.
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Affiliation(s)
- Rachel L Lombardi
- Department of Food Science and Technology, University of California Davis, Davis, California 95616, United States
| | - John S Ramsey
- Agricultural Research Service, Emerging Pests and Pathogens Research Unit, Ithaca, New York 14853, United States
| | - Jaclyn E Mahoney
- Boyce Thompson Institute for Plant Research, Ithaca, New York 14853, United States
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Michelle L Heck
- Agricultural Research Service, Emerging Pests and Pathogens Research Unit, Ithaca, New York 14853, United States
- Plant Pathology and Plant Microbe Biology Section, School of Integrative Plant Science, Cornell University, Ithaca, New York 14853, United States
| | - Carolyn M Slupsky
- Department of Food Science and Technology, University of California Davis, Davis, California 95616, United States
- Department of Nutrition, University of California Davis, Davis, California 95616, United States
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7
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Vázquez Torres S, Leung PJY, Venkatesh P, Lutz ID, Hink F, Huynh HH, Becker J, Yeh AHW, Juergens D, Bennett NR, Hoofnagle AN, Huang E, MacCoss MJ, Expòsit M, Lee GR, Bera AK, Kang A, De La Cruz J, Levine PM, Li X, Lamb M, Gerben SR, Murray A, Heine P, Korkmaz EN, Nivala J, Stewart L, Watson JL, Rogers JM, Baker D. De novo design of high-affinity binders of bioactive helical peptides. Nature 2024; 626:435-442. [PMID: 38109936 PMCID: PMC10849960 DOI: 10.1038/s41586-023-06953-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 12/07/2023] [Indexed: 12/20/2023]
Abstract
Many peptide hormones form an α-helix on binding their receptors1-4, and sensitive methods for their detection could contribute to better clinical management of disease5. De novo protein design can now generate binders with high affinity and specificity to structured proteins6,7. However, the design of interactions between proteins and short peptides with helical propensity is an unmet challenge. Here we describe parametric generation and deep learning-based methods for designing proteins to address this challenge. We show that by extending RFdiffusion8 to enable binder design to flexible targets, and to refining input structure models by successive noising and denoising (partial diffusion), picomolar-affinity binders can be generated to helical peptide targets by either refining designs generated with other methods, or completely de novo starting from random noise distributions without any subsequent experimental optimization. The RFdiffusion designs enable the enrichment and subsequent detection of parathyroid hormone and glucagon by mass spectrometry, and the construction of bioluminescence-based protein biosensors. The ability to design binders to conformationally variable targets, and to optimize by partial diffusion both natural and designed proteins, should be broadly useful.
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Affiliation(s)
- Susana Vázquez Torres
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Graduate Program in Biological Physics, Structure and Design, University of Washington, Seattle, WA, USA
| | - Philip J Y Leung
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Graduate Program in Molecular Engineering, University of Washington, Seattle, WA, USA
| | - Preetham Venkatesh
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Graduate Program in Biological Physics, Structure and Design, University of Washington, Seattle, WA, USA
| | - Isaac D Lutz
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | - Fabian Hink
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Huu-Hien Huynh
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Jessica Becker
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Andy Hsien-Wei Yeh
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - David Juergens
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Graduate Program in Molecular Engineering, University of Washington, Seattle, WA, USA
| | - Nathaniel R Bennett
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Graduate Program in Molecular Engineering, University of Washington, Seattle, WA, USA
| | - Andrew N Hoofnagle
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Eric Huang
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Marc Expòsit
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Graduate Program in Molecular Engineering, University of Washington, Seattle, WA, USA
| | - Gyu Rie Lee
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Asim K Bera
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Alex Kang
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Joshmyn De La Cruz
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Paul M Levine
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Xinting Li
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Mila Lamb
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Stacey R Gerben
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Analisa Murray
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Piper Heine
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Elif Nihal Korkmaz
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Jeff Nivala
- School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
- Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA
| | - Lance Stewart
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Joseph L Watson
- Department of Biochemistry, University of Washington, Seattle, WA, USA.
- Institute for Protein Design, University of Washington, Seattle, WA, USA.
| | - Joseph M Rogers
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark.
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA, USA.
- Institute for Protein Design, University of Washington, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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8
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Saul MC, Litkowski EM, Hadad N, Dunn AR, Boas SM, Wilcox JAL, Robbins JE, Wu Y, Philip VM, Merrihew GE, Park J, De Jager PL, Bridges DE, Menon V, Bennett DA, Hohman TJ, MacCoss MJ, Kaczorowski CC. Hippocampus Glutathione S Reductase Potentially Confers Genetic Resilience to Cognitive Decline in the AD-BXD Mouse Population. bioRxiv 2024:2024.01.09.574219. [PMID: 38260300 PMCID: PMC10802440 DOI: 10.1101/2024.01.09.574219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Alzheimer's disease (AD) is a prevalent and costly age-related dementia. Heritable factors account for 58-79% of variation in late-onset AD, but substantial variation remains in age-of- onset, disease severity, and whether those with high-risk genotypes acquire AD. To emulate the diversity of human populations, we utilized the AD-BXD mouse panel. This genetically diverse resource combines AD genotypes with multiple BXD strains to discover new genetic drivers of AD resilience. Comparing AD-BXD carriers to noncarrier littermates, we computed a novel quantitative metric for resilience to cognitive decline in the AD-BXDs. Our quantitative AD resilience trait was heritable and genetic mapping identified a locus on chr8 associated with resilience to AD mutations that resulted in amyloid brain pathology. Using a hippocampus proteomics dataset, we nominated the mitochondrial glutathione S reductase protein (GR or GSHR) as a resilience factor, finding that the DBA/2J genotype was associated with substantially higher GR abundance. By mapping protein QTLs (pQTLs), we identified synaptic organization and mitochondrial proteins coregulated in trans with a cis-pQTL for GR. We found four coexpression modules correlated with the quantitative resilience score in aged 5XFAD mice using paracliques, which were related to cell structure, protein folding, and postsynaptic densities. Finally, we found significant positive associations between human GSR transcript abundance in the brain and better outcomes on AD-related cognitive and pathology traits in the Religious Orders Study/Memory and Aging project (ROSMAP). Taken together, these data support a framework for resilience in which neuronal antioxidant pathway activity provides for stability of synapses within the hippocampus.
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9
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Yakabi K, Berson E, Montine KS, Bendall SC, MacCoss MJ, Poston KL, Montine TJ. Human cerebrospinal fluid single exosomes in Parkinson's and Alzheimer's diseases. bioRxiv 2023:2023.12.22.573124. [PMID: 38187636 PMCID: PMC10769431 DOI: 10.1101/2023.12.22.573124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Exosomes are proposed to be important in the pathogenesis of prevalent neurodegenerative diseases. We report the first application of solid-state technology to perform multiplex analysis of single exosomes in human cerebrospinal fluid (CSF) obtained from the lumbar sac of people diagnosed with Alzheimer's disease dementia (ADD, n=30) or Parkinson's disease dementia (PDD, n=30), as well as age-matched health controls (HCN, n=30). Single events were captured with mouse monoclonal antibodies to one of three different tetraspanins (CD9, CD63, or CD81) or with mouse (M) IgG control, and then probed with fluorescently labeled antibodies to prion protein (PrP) or CD47 to mark neuronal or presynaptic origin, as well as ADD- and PDD-related proteins: amyloid beta (Aβ), tau, α-synuclein, and Apolipoprotein (Apo) E. Data were collected only from captured events that were within the size range of 50 to 200 nm. Exosomes were present at approximately 100 billion per mL human CSF and were similarly abundant for CD9+ and CD81+ events, but CD63+ were only 22% to 25% of CD9+ (P<0.0001) or CD81+ (P<0.0001) events. Approximately 24% of CSF exosomes were PrP+, while only 2% were CD47+. The vast majority of exosomes were surface ApoE+, and the number of PrP-ApoE+ (P<0.001) and PrP+ApoE+ (P<0.01) exosomes were significantly reduced in ADD vs. HCN for CD9+ events only. Aβ, tau, and α-synuclein were not detected on the exosome surface or in permeabilized cargo. These data provide new insights into single exosome molecular features and highlight reduction in the CSF concentration of ApoE+ exosomes in patients with ADD.
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10
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Montine KS, Berson E, Phongpreecha T, Huang Z, Aghaeepour N, Zou JY, MacCoss MJ, Montine TJ. Understanding the molecular basis of resilience to Alzheimer's disease. Front Neurosci 2023; 17:1311157. [PMID: 38192507 PMCID: PMC10773681 DOI: 10.3389/fnins.2023.1311157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 12/04/2023] [Indexed: 01/10/2024] Open
Abstract
The cellular and molecular distinction between brain aging and neurodegenerative disease begins to blur in the oldest old. Approximately 15-25% of observations in humans do not fit predicted clinical manifestations, likely the result of suppressed damage despite usually adequate stressors and of resilience, the suppression of neurological dysfunction despite usually adequate degeneration. Factors during life may predict the clinico-pathologic state of resilience: cardiovascular health and mental health, more so than educational attainment, are predictive of a continuous measure of resilience to Alzheimer's disease (AD) and AD-related dementias (ADRDs). In resilience to AD alone (RAD), core features include synaptic and axonal processes, especially in the hippocampus. Future focus on larger and more diverse cohorts and additional regions offer emerging opportunities to understand this counterforce to neurodegeneration. The focus of this review is the molecular basis of resilience to AD.
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Affiliation(s)
| | - Eloïse Berson
- Department of Pathology, Stanford University, Stanford, CA, United States
- Department of Anesthesiology, Stanford University, Stanford, CA, United States
| | - Thanaphong Phongpreecha
- Department of Pathology, Stanford University, Stanford, CA, United States
- Department of Anesthesiology, Stanford University, Stanford, CA, United States
| | - Zhi Huang
- Department of Pathology, Stanford University, Stanford, CA, United States
- Department of Biomedical Data Science, Stanford University, Stanford, CA, United States
| | - Nima Aghaeepour
- Department of Anesthesiology, Stanford University, Stanford, CA, United States
- Department of Biomedical Data Science, Stanford University, Stanford, CA, United States
| | - James Y. Zou
- Department of Biomedical Data Science, Stanford University, Stanford, CA, United States
- Department of Computer Science, Stanford University, Stanford, CA, United States
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Thomas J. Montine
- Department of Pathology, Stanford University, Stanford, CA, United States
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11
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Pharaoh G, Kamat V, Kannan S, Stuppard RS, Whitson J, Martín-Pérez M, Qian WJ, MacCoss MJ, Villén J, Rabinovitch P, Campbell MD, Sweet IR, Marcinek DJ. The mitochondrially targeted peptide elamipretide (SS-31) improves ADP sensitivity in aged mitochondria by increasing uptake through the adenine nucleotide translocator (ANT). GeroScience 2023; 45:3529-3548. [PMID: 37462785 PMCID: PMC10643647 DOI: 10.1007/s11357-023-00861-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 06/23/2023] [Indexed: 07/28/2023] Open
Abstract
Aging muscle experiences functional decline in part mediated by impaired mitochondrial ADP sensitivity. Elamipretide (ELAM) rapidly improves physiological and mitochondrial function in aging and binds directly to the mitochondrial ADP transporter ANT. We hypothesized that ELAM improves ADP sensitivity in aging leading to rescued physiological function. We measured the response to ADP stimulation in young and old muscle mitochondria with ELAM treatment, in vivo heart and muscle function, and compared protein abundance, phosphorylation, and S-glutathionylation of ADP/ATP pathway proteins. ELAM treatment increased ADP sensitivity in old muscle mitochondria by increasing uptake of ADP through the ANT and rescued muscle force and heart systolic function. Protein abundance in the ADP/ATP transport and synthesis pathway was unchanged, but ELAM treatment decreased protein s-glutathionylation incuding of ANT. Mitochondrial ADP sensitivity is rapidly modifiable. This research supports the hypothesis that ELAM improves ANT function in aging and links mitochondrial ADP sensitivity to physiological function. ELAM binds directly to ANT and ATP synthase and ELAM treatment improves ADP sensitivity, increases ATP production, and improves physiological function in old muscles. ADP (adenosine diphosphate), ATP (adenosine triphosphate), VDAC (voltage-dependent anion channel), ANT (adenine nucleotide translocator), H+ (proton), ROS (reactive oxygen species), NADH (nicotinamide adenine dinucleotide), FADH2 (flavin adenine dinucleotide), O2 (oxygen), ELAM (elamipretide), -SH (free thiol), -SSG (glutathionylated protein).
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Affiliation(s)
- Gavin Pharaoh
- Department of Radiology, University of Washington, Seattle, WA, 98195, USA
| | - Varun Kamat
- Department of Medicine, University of Washington, Seattle, WA, 98195, USA
| | - Sricharan Kannan
- Department of Radiology, University of Washington, Seattle, WA, 98195, USA
| | - Rudolph S Stuppard
- Department of Radiology, University of Washington, Seattle, WA, 98195, USA
| | - Jeremy Whitson
- Department of Biology, High Point University, High Point, NC, 27268, USA
| | - Miguel Martín-Pérez
- Department of Cell Biology, Physiology and Immunology, University of Barcelona, 08028, Barcelona, Spain
| | - Wei-Jun Qian
- Integrative Omics Group, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA
| | - Judit Villén
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA
| | - Peter Rabinovitch
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, 98195, USA
| | - Matthew D Campbell
- Department of Radiology, University of Washington, Seattle, WA, 98195, USA
| | - Ian R Sweet
- Department of Medicine, University of Washington, Seattle, WA, 98195, USA
| | - David J Marcinek
- Department of Radiology, University of Washington, Seattle, WA, 98195, USA.
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, 98109, USA.
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12
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Matthews I, Birnbaum A, Gromova A, Huang AW, Liu K, Liu EA, Coutinho K, McGraw M, Patterson DC, Banks MT, Nobles AC, Nguyen N, Merrihew GE, Wang L, Baeuerle E, Fernandez E, Musi N, MacCoss MJ, Miranda HC, La Spada AR, Cortes CJ. Skeletal muscle TFEB signaling promotes central nervous system function and reduces neuroinflammation during aging and neurodegenerative disease. Cell Rep 2023; 42:113436. [PMID: 37952157 PMCID: PMC10841857 DOI: 10.1016/j.celrep.2023.113436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/12/2023] [Accepted: 10/28/2023] [Indexed: 11/14/2023] Open
Abstract
Skeletal muscle has recently arisen as a regulator of central nervous system (CNS) function and aging, secreting bioactive molecules known as myokines with metabolism-modifying functions in targeted tissues, including the CNS. Here, we report the generation of a transgenic mouse with enhanced skeletal muscle lysosomal and mitochondrial function via targeted overexpression of transcription factor E-B (TFEB). We discovered that the resulting geroprotective effects in skeletal muscle reduce neuroinflammation and the accumulation of tau-associated pathological hallmarks in a mouse model of tauopathy. Muscle-specific TFEB overexpression significantly ameliorates proteotoxicity, reduces neuroinflammation, and promotes transcriptional remodeling of the aged CNS, preserving cognition and memory in aged mice. Our results implicate the maintenance of skeletal muscle function throughout aging in direct regulation of CNS health and disease and suggest that skeletal muscle originating factors may act as therapeutic targets against age-associated neurodegenerative disorders.
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Affiliation(s)
- Ian Matthews
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90007, USA
| | - Allison Birnbaum
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90007, USA
| | - Anastasia Gromova
- Department of Pathology and Laboratory Medicine, UCI Institute for Neurotherapeutics, University of California, Irvine, Irvine, CA 92697, USA
| | - Amy W Huang
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90007, USA
| | - Kailin Liu
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90007, USA
| | - Eleanor A Liu
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90007, USA
| | - Kristen Coutinho
- Comprehensive Diabetes Center, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Megan McGraw
- Department of Cell, Developmental and Integrative Biology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Dalton C Patterson
- Department of Cell, Developmental and Integrative Biology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Macy T Banks
- Department of Cell, Developmental and Integrative Biology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Amber C Nobles
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Nhat Nguyen
- Department of Pathology and Laboratory Medicine, UCI Institute for Neurotherapeutics, University of California, Irvine, Irvine, CA 92697, USA
| | - Gennifer E Merrihew
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Lu Wang
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA
| | - Eric Baeuerle
- Department of Pharmacology, University of Texas Health San Antonio, San Antonio, TX 78229, USA; Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, TX 78229, USA; Geriatric Research, Education and Clinical Center, South Texas Veterans Health Care Network, San Antonio, TX 78229, USA
| | - Elizabeth Fernandez
- Department of Pharmacology, University of Texas Health San Antonio, San Antonio, TX 78229, USA; Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, TX 78229, USA; Geriatric Research, Education and Clinical Center, South Texas Veterans Health Care Network, San Antonio, TX 78229, USA
| | - Nicolas Musi
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Helen C Miranda
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA; Department of Neurosciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA; RNA Center, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Albert R La Spada
- Department of Pathology and Laboratory Medicine, UCI Institute for Neurotherapeutics, University of California, Irvine, Irvine, CA 92697, USA; Department of Neurology and Department of Biological Chemistry, UCI Institute for Neurotherapeutics, University of California, Irvine, Irvine, CA 92697, USA.
| | - Constanza J Cortes
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90007, USA.
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13
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Heil L, Damoc E, Arrey TN, Pashkova A, Denisov E, Petzoldt J, Peterson AC, Hsu C, Searle BC, Shulman N, Riffle M, Connolly B, MacLean BX, Remes PM, Senko MW, Stewart HI, Hock C, Makarov AA, Hermanson D, Zabrouskov V, Wu CC, MacCoss MJ. Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data-Independent Acquisition. J Proteome Res 2023; 22:3290-3300. [PMID: 37683181 PMCID: PMC10563156 DOI: 10.1021/acs.jproteome.3c00357] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Indexed: 09/10/2023]
Abstract
We evaluate the quantitative performance of the newly released Asymmetric Track Lossless (Astral) analyzer. Using data-independent acquisition, the Thermo Scientific Orbitrap Astral mass spectrometer quantifies 5 times more peptides per unit time than state-of-the-art Thermo Scientific Orbitrap mass spectrometers, which have long been the gold standard for high-resolution quantitative proteomics. Our results demonstrate that the Orbitrap Astral mass spectrometer can produce high-quality quantitative measurements across a wide dynamic range. We also use a newly developed extracellular vesicle enrichment protocol to reach new depths of coverage in the plasma proteome, quantifying over 5000 plasma proteins in a 60 min gradient with the Orbitrap Astral mass spectrometer.
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Affiliation(s)
- Lilian
R. Heil
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Eugen Damoc
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | - Tabiwang N. Arrey
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | - Anna Pashkova
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | - Eduard Denisov
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | - Johannes Petzoldt
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | | | - Chris Hsu
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Brian C. Searle
- Pelotonia
Institute for Immuno-Oncology, The Ohio
State University Comprehensive Cancer Center, Columbus, Ohio 43210, United States
- Department
of Biomedical Informatics, The Ohio State
University, Columbus, Ohio 43210, United States
| | - Nicholas Shulman
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Michael Riffle
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Brian Connolly
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Brendan X. MacLean
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Philip M. Remes
- Thermo
Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Michael W. Senko
- Thermo
Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Hamish I. Stewart
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | - Christian Hock
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | | | - Daniel Hermanson
- Thermo
Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Vlad Zabrouskov
- Thermo
Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Christine C. Wu
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Michael J. MacCoss
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
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14
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Huang Z, Merrihew GE, Larson EB, Park J, Plubell D, Fox EJ, Montine KS, Keene CD, Latimer CS, Zou JY, MacCoss MJ, Montine TJ. Unveiling Resilience to Alzheimer's Disease: Insights From Brain Regional Proteomic Markers. Neurosci Insights 2023; 18:26331055231201600. [PMID: 37810186 PMCID: PMC10557413 DOI: 10.1177/26331055231201600] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 08/31/2023] [Indexed: 10/10/2023] Open
Abstract
Studying proteomics data of the human brain could offer numerous insights into unraveling the signature of resilience to Alzheimer's disease. In our previous study with rigorous cohort selection criteria that excluded 4 common comorbidities, we harnessed multiple brain regions from 43 research participants with 12 of them displaying cognitive resilience to Alzheimer's disease. Based on the previous findings, this work focuses on 6 proteins out of the 33 differentially expressed proteins associated with resilience to Alzheimer's disease. These proteins are used to construct a decision tree classifier, enabling the differentiation of 3 groups: (i) healthy control, (ii) resilience to Alzheimer's disease, and (iii) Alzheimer's disease with dementia. Our analysis unveiled 2 important regional proteomic markers: Aβ peptides in the hippocampus and PA1B3 in the inferior parietal lobule. These findings underscore the potential of using distinct regional proteomic markers as signatures in characterizing the resilience to Alzheimer's disease.
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Affiliation(s)
- Zhi Huang
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Eric B Larson
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jea Park
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Deanna Plubell
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Edward J Fox
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Kathleen S Montine
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - C Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Caitlin S Latimer
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - James Y Zou
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Thomas J Montine
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
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15
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Heil LR, Remes PM, Canterbury JD, Yip P, Barshop WD, Wu CC, MacCoss MJ. Dynamic Data-Independent Acquisition Mass Spectrometry with Real-Time Retrospective Alignment. Anal Chem 2023; 95:11854-11858. [PMID: 37527417 PMCID: PMC10517878 DOI: 10.1021/acs.analchem.3c00903] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/03/2023]
Abstract
Data-independent acquisition (DIA) mass spectrometry has grown in popularity in recent years, because of the reproducibility and quantitative rigor of a systematic tandem mass spectrometry (MS/MS) sampling method. However, traditional DIA methods may spend valuable instrument time acquiring MS/MS spectra with no usable information in them, affecting sensitivity and quantitative performance. We developed a DIA strategy that dynamically adjusts the MS/MS windows during the chromatographic separation. The method focuses MS/MS acquisition on the most relevant mass range at each point in time─increasing the quantitative sensitivity by increasing the time spent on each DIA window. We demonstrate an improved lower limit of quantification, on average, without sacrificing the number of peptides detected.
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Affiliation(s)
- Lilian R Heil
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Philip M Remes
- Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Jesse D Canterbury
- Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Ping Yip
- Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - William D Barshop
- Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Christine C Wu
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
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16
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Li Y, Dou Y, Da Veiga Leprevost F, Geffen Y, Calinawan AP, Aguet F, Akiyama Y, Anand S, Birger C, Cao S, Chaudhary R, Chilappagari P, Cieslik M, Colaprico A, Zhou DC, Day C, Domagalski MJ, Esai Selvan M, Fenyö D, Foltz SM, Francis A, Gonzalez-Robles T, Gümüş ZH, Heiman D, Holck M, Hong R, Hu Y, Jaehnig EJ, Ji J, Jiang W, Katsnelson L, Ketchum KA, Klein RJ, Lei JT, Liang WW, Liao Y, Lindgren CM, Ma W, Ma L, MacCoss MJ, Martins Rodrigues F, McKerrow W, Nguyen N, Oldroyd R, Pilozzi A, Pugliese P, Reva B, Rudnick P, Ruggles KV, Rykunov D, Savage SR, Schnaubelt M, Schraink T, Shi Z, Singhal D, Song X, Storrs E, Terekhanova NV, Thangudu RR, Thiagarajan M, Wang LB, Wang JM, Wang Y, Wen B, Wu Y, Wyczalkowski MA, Xin Y, Yao L, Yi X, Zhang H, Zhang Q, Zuhl M, Getz G, Ding L, Nesvizhskii AI, Wang P, Robles AI, Zhang B, Payne SH. Proteogenomic data and resources for pan-cancer analysis. Cancer Cell 2023; 41:1397-1406. [PMID: 37582339 PMCID: PMC10506762 DOI: 10.1016/j.ccell.2023.06.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 11/15/2022] [Accepted: 06/27/2023] [Indexed: 08/17/2023]
Abstract
The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.
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Affiliation(s)
- Yize Li
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Yongchao Dou
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | | | - Yifat Geffen
- Broad Institute of MIT and Harvard, Cambridge, MA 02141, USA
| | - Anna P Calinawan
- Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - François Aguet
- Broad Institute of MIT and Harvard, Cambridge, MA 02141, USA
| | - Yo Akiyama
- Broad Institute of MIT and Harvard, Cambridge, MA 02141, USA
| | - Shankara Anand
- Broad Institute of MIT and Harvard, Cambridge, MA 02141, USA
| | - Chet Birger
- Broad Institute of MIT and Harvard, Cambridge, MA 02141, USA
| | - Song Cao
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA
| | | | | | - Marcin Cieslik
- Department of Computational Medicine & Bioinformatics, Department of Pathology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Antonio Colaprico
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Daniel Cui Zhou
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Corbin Day
- Department of Biology, Brigham Young University, Provo, UT 84602, USA
| | | | - Myvizhi Esai Selvan
- Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - David Fenyö
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Steven M Foltz
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA
| | | | - Tania Gonzalez-Robles
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10016, USA; Department of Medicine, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Zeynep H Gümüş
- Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - David Heiman
- Broad Institute of MIT and Harvard, Cambridge, MA 02141, USA
| | | | - Runyu Hong
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Yingwei Hu
- Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA
| | - Eric J Jaehnig
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jiayi Ji
- Tisch Cancer Institute and Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Wen Jiang
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Lizabeth Katsnelson
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10016, USA
| | | | - Robert J Klein
- Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jonathan T Lei
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Wen-Wei Liang
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Yuxing Liao
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Caleb M Lindgren
- Department of Biology, Brigham Young University, Provo, UT 84602, USA
| | - Weiping Ma
- Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Lei Ma
- ICF, Rockville, MD 20850, USA
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Fernanda Martins Rodrigues
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Wilson McKerrow
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10016, USA
| | | | - Robert Oldroyd
- Department of Biology, Brigham Young University, Provo, UT 84602, USA
| | | | - Pietro Pugliese
- Department of Sciences and Technologies, University of Sannio, Benevento 82100, Italy
| | - Boris Reva
- Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Paul Rudnick
- Spectragen Informatics, Bainbridge Island, WA 98110, USA
| | - Kelly V Ruggles
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, USA; Department of Medicine, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Dmitry Rykunov
- Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sara R Savage
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Michael Schnaubelt
- Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA
| | - Tobias Schraink
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10016, USA; Department of Medicine, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Zhiao Shi
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | | | - Xiaoyu Song
- Tisch Cancer Institute and Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Erik Storrs
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Nadezhda V Terekhanova
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA
| | | | | | - Liang-Bo Wang
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Joshua M Wang
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Ying Wang
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Bo Wen
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yige Wu
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Matthew A Wyczalkowski
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Yi Xin
- ICF, Rockville, MD 20850, USA
| | - Lijun Yao
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Xinpei Yi
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Hui Zhang
- Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA
| | - Qing Zhang
- Broad Institute of MIT and Harvard, Cambridge, MA 02141, USA
| | | | - Gad Getz
- Broad Institute of MIT and Harvard, Cambridge, MA 02141, USA; Cancer Center and Department of Pathology, Mass. General Hospital, Boston, MA 02114, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Li Ding
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA; Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63130, USA; Department of Genetics, Washington University in St. Louis, St. Louis, MO 63130, USA
| | | | - Pei Wang
- Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ana I Robles
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA.
| | - Bing Zhang
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
| | - Samuel H Payne
- Department of Biology, Brigham Young University, Provo, UT 84602, USA.
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17
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Heil LR, Damoc E, Arrey TN, Pashkova A, Denisov E, Petzoldt J, Peterson AC, Hsu C, Searle BC, Shulman N, Riffle M, Connolly B, MacLean BX, Remes PM, Senko MW, Stewart HI, Hock C, Makarov AA, Hermanson D, Zabrouskov V, Wu CC, MacCoss MJ. Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data Independent Acquisition. bioRxiv 2023:2023.06.03.543570. [PMID: 37398334 PMCID: PMC10312564 DOI: 10.1101/2023.06.03.543570] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
We evaluate the quantitative performance of the newly released Asymmetric Track Lossless (Astral) analyzer. Using data independent acquisition, the Thermo Scientific™ Orbitrap™ Astral™ mass spectrometer quantifies 5 times more peptides per unit time than state-of-the-art Thermo Scientific™ Orbitrap™ mass spectrometers, which have long been the gold standard for high resolution quantitative proteomics. Our results demonstrate that the Orbitrap Astral mass spectrometer can produce high quality quantitative measurements across a wide dynamic range. We also use a newly developed extra-cellular vesicle enrichment protocol to reach new depths of coverage in the plasma proteome, quantifying over 5,000 plasma proteins in a 60-minute gradient with the Orbitrap Astral mass spectrometer.
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Affiliation(s)
- Lilian R. Heil
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Eugen Damoc
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | - Tabiwang N. Arrey
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | - Anna Pashkova
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | - Eduard Denisov
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | - Johannes Petzoldt
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | | | - Chris Hsu
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Brian C. Searle
- Pelotonia Institute for Immuno-Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio 43210, United States
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio 43210, United States
| | - Nicholas Shulman
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Michael Riffle
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Brian Connolly
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Brendan X. MacLean
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Philip M. Remes
- Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Michael W. Senko
- Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Hamish I. Stewart
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | - Christian Hock
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | | | - Daniel Hermanson
- Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Vlad Zabrouskov
- Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Christine C. Wu
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
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18
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Huynh HH, Kuch K, Orquillas A, Forrest K, Barahona-Carrillo L, Keene D, Henderson VW, Wagner AD, Poston KL, Montine TJ, Lin A, Tian L, MacCoss MJ, Emrick MA, Hoofnagle AN. Metrologically Traceable Quantification of 3 Apolipoprotein E Isoforms in Cerebrospinal Fluid. Clin Chem 2023; 69:734-745. [PMID: 37279935 PMCID: PMC10320014 DOI: 10.1093/clinchem/hvad056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 04/14/2023] [Indexed: 06/08/2023]
Abstract
BACKGROUND APOE genotype is associated with Alzheimer disease. Thus, the concentration of apolipoprotein E (apoE) isoforms in cerebrospinal fluid (CSF) could be altered in dementia. However, conflicting results have been obtained in different studies. Carefully validated and standardized assays could improve the interpretation of research findings, allow their replication in other laboratories, and generalize their application. METHODS To evaluate this hypothesis, we aimed to develop, validate, and standardize a new measurement procedure using LC-MS/MS. Purified recombinant apoE protein standards (E2, E3, E4) were thoroughly characterized and used to assign the concentration of a matrix-matched calibration material that contained each apoE isoform, which ensured the metrological traceability of results. RESULTS The assay of each isoform in human CSF was precise (≤11%CV) and of moderate throughput (approximately 80 samples per day). It demonstrated good linearity and parallelism for lumbar CSF, ventricular CSF, and bovine CSF. The use of an SI-traceable matrix-matched calibrator enabled precise and accurate measurements. There was no association observed between total apoE concentration and the number of Ɛ4 alleles in a cohort of 322 participants. However, the concentration of each isoform was significantly different in heterozygotes, with E4 > E3 > E2. Isoform concentrations were associated with cognitive and motor symptoms but contributed negligibly to a predictive model of cognitive impairment that included established CSF biomarkers. CONCLUSIONS Our method simultaneously measures each apoE isoform in human CSF with excellent precision and accuracy. A secondary matrix-matched material has been developed and is available to other laboratories to improve interlaboratory agreement.
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Affiliation(s)
- Huu-Hien Huynh
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
| | - Kellie Kuch
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
| | - Allen Orquillas
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA, United States
| | - Katrina Forrest
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
| | - Lili Barahona-Carrillo
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
| | - Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
| | - Victor W Henderson
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA, United States
- Department of Neurology and Neurological Science, Stanford University School of Medicine, Stanford, CA, United States
| | - Anthony D Wagner
- Department of Psychology, Stanford University, Stanford, CA, United States
| | - Kathleen L Poston
- Department of Neurology and Neurological Science, Stanford University School of Medicine, Stanford, CA, United States
| | - Thomas J Montine
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, United States
| | - Amy Lin
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, United States
| | - Lu Tian
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, United States
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Michelle A Emrick
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
| | - Andrew N Hoofnagle
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
- Department of Medicine, University of Washington, Seattle, WA, United States
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19
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Huang Z, Merrihew GE, Larson EB, Park J, Plubell D, Fox EJ, Montine KS, Latimer CS, Dirk Keene C, Zou JY, MacCoss MJ, Montine TJ. Brain proteomic analysis implicates actin filament processes and injury response in resilience to Alzheimer's disease. Nat Commun 2023; 14:2747. [PMID: 37173305 PMCID: PMC10182086 DOI: 10.1038/s41467-023-38376-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Accepted: 04/27/2023] [Indexed: 05/15/2023] Open
Abstract
Resilience to Alzheimer's disease is an uncommon combination of high disease burden without dementia that offers valuable insights into limiting clinical impact. Here we assessed 43 research participants meeting stringent criteria, 11 healthy controls, 12 resilience to Alzheimer's disease and 20 Alzheimer's disease with dementia and analyzed matched isocortical regions, hippocampus, and caudate nucleus by mass spectrometry-based proteomics. Of 7115 differentially expressed soluble proteins, lower isocortical and hippocampal soluble Aβ levels is a significant feature of resilience when compared to healthy control and Alzheimer's disease dementia groups. Protein co-expression analysis reveals 181 densely-interacting proteins significantly associated with resilience that were enriched for actin filament-based processes, cellular detoxification, and wound healing in isocortex and hippocampus, further supported by four validation cohorts. Our results suggest that lowering soluble Aβ concentration may suppress severe cognitive impairment along the Alzheimer's disease continuum. The molecular basis of resilience likely holds important therapeutic insights.
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Affiliation(s)
- Zhi Huang
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Gennifer E Merrihew
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA
| | - Eric B Larson
- Department of Medicine, University of Washington, Seattle, WA, 98195, USA
| | - Jea Park
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA
| | - Deanna Plubell
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA
| | - Edward J Fox
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Kathleen S Montine
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Caitlin S Latimer
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, 98195, USA
| | - C Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, 98195, USA
| | - James Y Zou
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, 94305, USA.
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA.
| | - Thomas J Montine
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
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20
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Merrihew GE, Park J, Plubell D, Searle BC, Keene CD, Larson EB, Bateman R, Perrin RJ, Chhatwal JP, Farlow MR, McLean CA, Ghetti B, Newell KL, Frosch MP, Montine TJ, MacCoss MJ. A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer's disease. Sci Data 2023; 10:206. [PMID: 37059743 PMCID: PMC10104800 DOI: 10.1038/s41597-023-02057-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 03/08/2023] [Indexed: 04/16/2023] Open
Abstract
Alzheimer's disease (AD) is a looming public health disaster with limited interventions. Alzheimer's is a complex disease that can present with or without causative mutations and can be accompanied by a range of age-related comorbidities. This diverse presentation makes it difficult to study molecular changes specific to AD. To better understand the molecular signatures of disease we constructed a unique human brain sample cohort inclusive of autosomal dominant AD dementia (ADD), sporadic ADD, and those without dementia but with high AD histopathologic burden, and cognitively normal individuals with no/minimal AD histopathologic burden. All samples are clinically well characterized, and brain tissue was preserved postmortem by rapid autopsy. Samples from four brain regions were processed and analyzed by data-independent acquisition LC-MS/MS. Here we present a high-quality quantitative dataset at the peptide and protein level for each brain region. Multiple internal and external control strategies were included in this experiment to ensure data quality. All data are deposited in the ProteomeXchange repositories and available from each step of our processing.
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Affiliation(s)
- Gennifer E Merrihew
- Department of Genome Sciences, University of Washington, Seattle, Washington, 98195, USA
| | - Jea Park
- Department of Genome Sciences, University of Washington, Seattle, Washington, 98195, USA
| | - Deanna Plubell
- Department of Genome Sciences, University of Washington, Seattle, Washington, 98195, USA
| | - Brian C Searle
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio, 43210, USA
| | - C Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, 98195, USA
| | - Eric B Larson
- Department of Medicine, University of Washington, Seattle, Washington, 98195, USA
| | - Randall Bateman
- Department of Neurology, Washington University School of Medicine, 660 South Euclid Avenue, Box 8111, St. Louis, Missouri, 63110, USA
| | - Richard J Perrin
- Department of Pathology, Washington University School of Medicine, 660 South Euclid Avenue, Box 8111, St. Louis, Missouri, 63110, USA
| | - Jasmeer P Chhatwal
- Massachusetts General Hospital, Department of Neurology, Harvard Medical School, 15 Parkman St, Suite 835, Boston, Massachusetts, 02114, USA
| | - Martin R Farlow
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA
| | - Catriona A McLean
- Department of Anatomical Pathology, Alfred Health, Melbourne, VIC, 3004, Australia
| | - Bernardino Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA
| | - Kathy L Newell
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA
| | - Matthew P Frosch
- C.S. Kubik Laboratory for Neuropathology, and Massachusetts Alzheimer Disease Research Center, Massachusetts General Hospital, Boston, Massachusetts, 02114, USA
| | - Thomas J Montine
- Department of Pathology, Stanford University, Stanford, CA, 94305, USA.
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, Washington, 98195, USA.
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21
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Bailey LRJ, Bugg D, Reichardt IM, Ortaç CD, Gunaje J, Johnson R, MacCoss MJ, Sakamoto T, Kelly DP, Regnier M, Davis JM. MBNL1 regulates programmed postnatal switching between regenerative and differentiated cardiac states. bioRxiv 2023:2023.03.16.532974. [PMID: 36993225 PMCID: PMC10055038 DOI: 10.1101/2023.03.16.532974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Discovering determinants of cardiomyocyte maturity and the maintenance of differentiated states is critical to both understanding development and potentially reawakening endogenous regenerative programs in adult mammalian hearts as a therapeutic strategy. Here, the RNA binding protein Muscleblind-like 1 (MBNL1) was identified as a critical regulator of cardiomyocyte differentiated states and their regenerative potential through transcriptome-wide control of RNA stability. Targeted MBNL1 overexpression early in development prematurely transitioned cardiomyocytes to hypertrophic growth, hypoplasia, and dysfunction, whereas loss of MBNL1 function increased cardiomyocyte cell cycle entry and proliferation through altered cell cycle inhibitor transcript stability. Moreover, MBNL1-dependent stabilization of the estrogen-related receptor signaling axis was essential for maintaining cardiomyocyte maturity. In accordance with these data, modulating MBNL1 dose tuned the temporal window of cardiac regeneration, where enhanced MBNL1 activity arrested myocyte proliferation, and MBNL1 deletion promoted regenerative states with prolonged myocyte proliferation. Collectively these data suggest MBNL1 acts as a transcriptome-wide switch between regenerative and mature myocyte states postnatally and throughout adulthood.
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22
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Abstract
Mammalian cells have about 30,000-fold more protein molecules than mRNA molecules, which has major implications in the development of proteomics technologies. We review strategies that have been helpful for counting billions of protein molecules by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and suggest that these strategies can benefit single-molecule methods, especially in mitigating the challenges of the wide dynamic range of the proteome.
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Affiliation(s)
- Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
| | - Javier Antonio Alfaro
- International Centre for Cancer Vaccine Science, University of Gdańsk, Gdańsk, Poland.
- Department of Biochemistry and Microbiology, University of Victoria, Victoria, British Columbia, Canada.
- School of Informatics, University of Edinburgh, Edinburgh, UK.
| | - Danielle A Faivre
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Christine C Wu
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Meni Wanunu
- Department of Physics, Northeastern University, Boston, MA, USA
| | - Nikolai Slavov
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA.
- Parallel Squared Technology Institute, Watertown, MA, USA.
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23
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Gatto L, Aebersold R, Cox J, Demichev V, Derks J, Emmott E, Franks AM, Ivanov AR, Kelly RT, Khoury L, Leduc A, MacCoss MJ, Nemes P, Perlman DH, Petelski AA, Rose CM, Schoof EM, Van Eyk J, Vanderaa C, Yates JR, Slavov N. Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments. Nat Methods 2023; 20:375-386. [PMID: 36864200 PMCID: PMC10130941 DOI: 10.1038/s41592-023-01785-3] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 01/24/2023] [Indexed: 03/04/2023]
Abstract
Analyzing proteins from single cells by tandem mass spectrometry (MS) has recently become technically feasible. While such analysis has the potential to accurately quantify thousands of proteins across thousands of single cells, the accuracy and reproducibility of the results may be undermined by numerous factors affecting experimental design, sample preparation, data acquisition and data analysis. We expect that broadly accepted community guidelines and standardized metrics will enhance rigor, data quality and alignment between laboratories. Here we propose best practices, quality controls and data-reporting recommendations to assist in the broad adoption of reliable quantitative workflows for single-cell proteomics. Resources and discussion forums are available at https://single-cell.net/guidelines .
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Affiliation(s)
- Laurent Gatto
- Computational Biology and Bioinformatics Unit, de Duve Institute, Université Catholique de Louvain, Brussels, Belgium
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Juergen Cox
- Max Planck Institute of Biochemistry, Martinsried, Germany
| | | | - Jason Derks
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA
| | - Edward Emmott
- Centre for Proteome Research, Department of Biochemistry and Systems Biology, University of Liverpool, Liverpool, UK
| | - Alexander M Franks
- Department of Statistics and Applied Probability, University of California Santa Barbara, Santa Barbara, CA, USA
| | - Alexander R Ivanov
- Department of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, USA
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA
| | - Luke Khoury
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA
| | - Andrew Leduc
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA
| | | | - Peter Nemes
- Department of Chemistry and Biochemistry, University of Maryland, College Park, MD, USA
| | - David H Perlman
- Merck Exploratory Science Center, Merck Sharp & Dohme Corp., Cambridge, MA, USA
| | - Aleksandra A Petelski
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA
- Parallel Squared Technology Institute, Watertown, MA, USA
| | - Christopher M Rose
- Department of Microchemistry, Proteomics and Lipidomics, Genentech Inc., South San Francisco, CA, USA
| | - Erwin M Schoof
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | | | - Christophe Vanderaa
- Computational Biology and Bioinformatics Unit, de Duve Institute, Université Catholique de Louvain, Brussels, Belgium
| | - John R Yates
- Departments of Molecular Medicine and Neurobiology, the Scripps Research Institute, La Jolla, CA, USA
| | - Nikolai Slavov
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA.
- Parallel Squared Technology Institute, Watertown, MA, USA.
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24
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Kertesz-Farkas A, Nii Adoquaye Acquaye FL, Bhimani K, Eng JK, Fondrie WE, Grant C, Hoopmann MR, Lin A, Lu YY, Moritz RL, MacCoss MJ, Noble WS. The Crux Toolkit for Analysis of Bottom-Up Tandem Mass Spectrometry Proteomics Data. J Proteome Res 2023; 22:561-569. [PMID: 36598107 DOI: 10.1021/acs.jproteome.2c00615] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The Crux tandem mass spectrometry data analysis toolkit provides a collection of algorithms for analyzing bottom-up proteomics tandem mass spectrometry data. Many publications have described various individual components of Crux, but a comprehensive summary has not been published since 2014. The goal of this work is to summarize the functionality of Crux, focusing on developments since 2014. We begin with empirical results demonstrating our recently implemented speedups to the Tide search engine. Other new features include a new score function in Tide, two new confidence estimation procedures, as well as three new tools: Param-medic for estimating search parameters directly from mass spectrometry data, Kojak for searching cross-linked mass spectra, and DIAmeter for searching data independent acquisition data against a sequence database.
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Affiliation(s)
- Attila Kertesz-Farkas
- Department of Data Analysis and Artificial Intelligence and Laboratory on AI for Computational Biology, Faculty of Computer Science, HSE University, 20 Myasnitskaya ulitsa, Moscow 101000, Russia
| | - Frank Lawrence Nii Adoquaye Acquaye
- Department of Data Analysis and Artificial Intelligence and Laboratory on AI for Computational Biology, Faculty of Computer Science, HSE University, 20 Myasnitskaya ulitsa, Moscow 101000, Russia
| | - Kishankumar Bhimani
- Department of Data Analysis and Artificial Intelligence and Laboratory on AI for Computational Biology, Faculty of Computer Science, HSE University, 20 Myasnitskaya ulitsa, Moscow 101000, Russia
| | - Jimmy K Eng
- Proteomics Resource, University of Washington, 850 Republican Street, Seattle, Washington 98109-4725, United States
| | - William E Fondrie
- Talus Bioscience550 17th Avenue, Seattle, Washington 98122, United States
| | - Charles Grant
- Department of Genome Sciences, University of Washington3720 15th Avenue NE, Seattle, Washington 98195, United States
| | - Michael R Hoopmann
- Insititute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - Andy Lin
- Department of Genome Sciences, University of Washington3720 15th Avenue NE, Seattle, Washington 98195, United States
| | - Yang Y Lu
- Department of Genome Sciences, University of Washington3720 15th Avenue NE, Seattle, Washington 98195, United States
| | - Robert L Moritz
- Insititute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington3720 15th Avenue NE, Seattle, Washington 98195, United States
| | - William Stafford Noble
- Department of Genome Sciences, University of Washington3720 15th Avenue NE, Seattle, Washington 98195, United States.,Paul G. Allen School of Computer Science and Engineering, University of Washington185 E Stevens Way NE, Seattle, Washington 98195-2350, United States
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25
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Basisty N, Shulman N, Wehrfritz C, Marsh AN, Shah S, Rose J, Ebert S, Miller M, Dai DF, Rabinovitch PS, Adams CM, MacCoss MJ, MacLean B, Schilling B. TurnoveR: A Skyline External Tool for Analysis of Protein Turnover in Metabolic Labeling Studies. J Proteome Res 2023; 22:311-322. [PMID: 36165806 PMCID: PMC10066879 DOI: 10.1021/acs.jproteome.2c00173] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
In spite of its central role in biology and disease, protein turnover is a largely understudied aspect of most proteomic studies due to the complexity of computational workflows that analyze in vivo turnover rates. To address this need, we developed a new computational tool, TurnoveR, to accurately calculate protein turnover rates from mass spectrometric analysis of metabolic labeling experiments in Skyline, a free and open-source proteomics software platform. TurnoveR is a straightforward graphical interface that enables seamless integration of protein turnover analysis into a traditional proteomics workflow in Skyline, allowing users to take advantage of the advanced and flexible data visualization and curation features built into the software. The computational pipeline of TurnoveR performs critical steps to determine protein turnover rates, including isotopologue demultiplexing, precursor-pool correction, statistical analysis, and generation of data reports and visualizations. This workflow is compatible with many mass spectrometric platforms and recapitulates turnover rates and differential changes in turnover rates between treatment groups calculated in previous studies. We expect that the addition of TurnoveR to the widely used Skyline proteomics software will facilitate wider utilization of protein turnover analysis in highly relevant biological models, including aging, neurodegeneration, and skeletal muscle atrophy.
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Affiliation(s)
- Nathan Basisty
- Buck Institute for Research on Aging, Novato, California 94945, United States
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, Maryland 21224, United States
| | - Nicholas Shulman
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Cameron Wehrfritz
- Buck Institute for Research on Aging, Novato, California 94945, United States
| | - Alexandra N Marsh
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Samah Shah
- Buck Institute for Research on Aging, Novato, California 94945, United States
| | - Jacob Rose
- Buck Institute for Research on Aging, Novato, California 94945, United States
| | - Scott Ebert
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, Rochester, Minnesota 55905, United States
- Emmyon, Inc., Rochester, Minnesota 55902, United States
| | - Matthew Miller
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, Rochester, Minnesota 55905, United States
- Medical Scientist Training Program, University of Iowa, Iowa City, Iowa 52242, United States
| | - Dao-Fu Dai
- Department of Pathology, University of Iowa, Iowa City, Iowa 52242, United States
| | - Peter S Rabinovitch
- Department of Pathology, University of Washington, Seattle, Washington 98195, United States
| | - Christopher M Adams
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, Rochester, Minnesota 55905, United States
- Emmyon, Inc., Rochester, Minnesota 55902, United States
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Brendan MacLean
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Birgit Schilling
- Buck Institute for Research on Aging, Novato, California 94945, United States
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26
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Hoopmann MR, Shteynberg DD, Zelter A, Riffle M, Lyon AS, Agard DA, Luan Q, Nolen BJ, MacCoss MJ, Davis TN, Moritz RL. Improved Analysis of Cross-Linking Mass Spectrometry Data with Kojak 2.0, Advanced by Integration into the Trans-Proteomic Pipeline. J Proteome Res 2023; 22:647-655. [PMID: 36629399 PMCID: PMC10234491 DOI: 10.1021/acs.jproteome.2c00670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Fragmentation ion spectral analysis of chemically cross-linked proteins is an established technology in the proteomics research repertoire for determining protein interactions, spatial orientation, and structure. Here we present Kojak version 2.0, a major update to the original Kojak algorithm, which was developed to identify cross-linked peptides from fragment ion spectra using a database search approach. A substantially improved algorithm with updated scoring metrics, support for cleavable cross-linkers, and identification of cross-links between 15N-labeled homomultimers are among the newest features of Kojak 2.0 presented here. Kojak 2.0 is now integrated into the Trans-Proteomic Pipeline, enabling access to dozens of additional tools within that suite. In particular, the PeptideProphet and iProphet tools for validation of cross-links improve the sensitivity and accuracy of correct cross-link identifications at user-defined thresholds. These new features improve the versatility of the algorithm, enabling its use in a wider range of experimental designs and analysis pipelines. Kojak 2.0 remains open-source and multiplatform.
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Affiliation(s)
| | | | - Alex Zelter
- Department of Biochemistry, University of Washington, Seattle, WA, USA 98195
| | - Michael Riffle
- Department of Biochemistry, University of Washington, Seattle, WA, USA 98195
| | - Andrew S. Lyon
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA 94143
| | - David A. Agard
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA 94143
| | - Qing Luan
- Department of Chemistry and Biochemistry, University of Oregon, Eugene, OR, USA 97403
| | - Brad J. Nolen
- Department of Chemistry and Biochemistry, University of Oregon, Eugene, OR, USA 97403
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA 98195
| | - Trisha N. Davis
- Department of Biochemistry, University of Washington, Seattle, WA, USA 98195
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27
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Pharaoh G, Kamat V, Kannan S, Stuppard RS, Whitson J, Martin-Perez M, Qian WJ, MacCoss MJ, Villen J, Rabinovitch P, Campbell MD, Sweet IR, Marcinek DJ. Elamipretide Improves ADP Sensitivity in Aged Mitochondria by Increasing Uptake through the Adenine Nucleotide Translocator (ANT). bioRxiv 2023:2023.02.01.525989. [PMID: 36778398 PMCID: PMC9915686 DOI: 10.1101/2023.02.01.525989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Aging muscle experiences functional decline in part mediated by impaired mitochondrial ADP sensitivity. Elamipretide (ELAM) rapidly improves physiological and mitochondrial function in aging and binds directly to the mitochondrial ADP transporter ANT. We hypothesized that ELAM improves ADP sensitivity in aging leading to rescued physiological function. We measured the response to ADP stimulation in young and old muscle mitochondria with ELAM treatment, in vivo heart and muscle function, and compared protein abundance, phosphorylation, and S-glutathionylation of ADP/ATP pathway proteins. ELAM treatment increased ADP sensitivity in old muscle mitochondria by increasing uptake of ADP through the ANT and rescued muscle force and heart systolic function. Protein abundance in the ADP/ATP transport and synthesis pathway was unchanged, but ELAM treatment decreased protein s-glutathionylation incuding of ANT. Mitochondrial ADP sensitivity is rapidly modifiable. This research supports the hypothesis that ELAM improves ANT function in aging and links mitochondrial ADP sensitivity to physiological function. Abstract Figure
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Affiliation(s)
- Gavin Pharaoh
- Department of Radiology, University of Washington, Seattle, Washington, 98195, USA
| | - Varun Kamat
- Department of Medicine, University of Washington, Seattle, Washington, 98195, USA
| | - Sricharan Kannan
- Department of Radiology, University of Washington, Seattle, Washington, 98195, USA
| | - Rudolph S. Stuppard
- Department of Radiology, University of Washington, Seattle, Washington, 98195, USA
| | - Jeremy Whitson
- Department of Biology, High Point University, High Point, NC, 27268, USA
| | - Miguel Martin-Perez
- Department of Cell Biology, Physiology and Immunology, University of Barcelona, Barcelona, 08028, Spain
| | - Wei-Jun Qian
- Integrative Omics Group, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA
| | - Judit Villen
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA
| | - Peter Rabinovitch
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, 98195, USA
| | - Matthew D. Campbell
- Department of Radiology, University of Washington, Seattle, Washington, 98195, USA
| | - Ian R. Sweet
- Department of Medicine, University of Washington, Seattle, Washington, 98195, USA
| | - David J. Marcinek
- Department of Radiology, University of Washington, Seattle, Washington, 98195, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, 98109, USA
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28
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Martinez TF, Lyons-Abbott S, Bookout AL, De Souza EV, Donaldson C, Vaughan JM, Lau C, Abramov A, Baquero AF, Baquero K, Friedrich D, Huard J, Davis R, Kim B, Koch T, Mercer AJ, Misquith A, Murray SA, Perry S, Pino LK, Sanford C, Simon A, Zhang Y, Zipp G, Bizarro CV, Shokhirev MN, Whittle AJ, Searle BC, MacCoss MJ, Saghatelian A, Barnes CA. Profiling mouse brown and white adipocytes to identify metabolically relevant small ORFs and functional microproteins. Cell Metab 2023; 35:166-183.e11. [PMID: 36599300 PMCID: PMC9889109 DOI: 10.1016/j.cmet.2022.12.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 09/19/2022] [Accepted: 12/06/2022] [Indexed: 01/05/2023]
Abstract
Microproteins (MPs) are a potentially rich source of uncharacterized metabolic regulators. Here, we use ribosome profiling (Ribo-seq) to curate 3,877 unannotated MP-encoding small ORFs (smORFs) in primary brown, white, and beige mouse adipocytes. Of these, we validated 85 MPs by proteomics, including 33 circulating MPs in mouse plasma. Analyses of MP-encoding mRNAs under different physiological conditions (high-fat diet) revealed that numerous MPs are regulated in adipose tissue in vivo and are co-expressed with established metabolic genes. Furthermore, Ribo-seq provided evidence for the translation of Gm8773, which encodes a secreted MP that is homologous to human and chicken FAM237B. Gm8773 is highly expressed in the arcuate nucleus of the hypothalamus, and intracerebroventricular administration of recombinant mFAM237B showed orexigenic activity in obese mice. Together, these data highlight the value of this adipocyte MP database in identifying MPs with roles in fundamental metabolic and physiological processes such as feeding.
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Affiliation(s)
- Thomas F Martinez
- Department of Pharmaceutical Sciences, Department of Biological Chemistry, Chao Family Comprehensive Cancer Center, University of California, Irvine, Irvine, CA, USA
| | | | - Angie L Bookout
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Eduardo V De Souza
- Centro de Pesquisas em Biologia Molecular e Funcional (CPBMF) and Instituto Nacional de Ciência e Tecnologia em Tuberculose (INCT-TB), Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre, Brazil; Programa de Pós-Graduação em Biologia Celular e Molecular, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul 90616-900, Brazil; Clayton Foundation Laboratories for Peptide Biology, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Cynthia Donaldson
- Clayton Foundation Laboratories for Peptide Biology, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Joan M Vaughan
- Clayton Foundation Laboratories for Peptide Biology, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Calvin Lau
- Clayton Foundation Laboratories for Peptide Biology, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Ariel Abramov
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Arian F Baquero
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Karalee Baquero
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Dave Friedrich
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Justin Huard
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Ray Davis
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Bong Kim
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Ty Koch
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Aaron J Mercer
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Ayesha Misquith
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Sara A Murray
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Sakara Perry
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Lindsay K Pino
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Alex Simon
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Yu Zhang
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Garrett Zipp
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA
| | - Cristiano V Bizarro
- Centro de Pesquisas em Biologia Molecular e Funcional (CPBMF) and Instituto Nacional de Ciência e Tecnologia em Tuberculose (INCT-TB), Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre, Brazil; Programa de Pós-Graduação em Biologia Celular e Molecular, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul 90616-900, Brazil
| | - Maxim N Shokhirev
- Razavi Newman Integrative Genomics and Bioinformatics Core, Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | - Brian C Searle
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Alan Saghatelian
- Clayton Foundation Laboratories for Peptide Biology, Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Christopher A Barnes
- Novo Nordisk Research Center Seattle, Inc., Seattle, WA, USA; Velia Therapeutics, Inc., San Diego, CA, USA.
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29
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Saxton MW, Perry BW, Evans Hutzenbiler BD, Trojahn S, Gee A, Brown AP, Merrihew GE, Park J, Cornejo OE, MacCoss MJ, Robbins CT, Jansen HT, Kelley JL. Serum plays an important role in reprogramming the seasonal transcriptional profile of brown bear adipocytes. iScience 2022; 25:105084. [PMID: 36317158 PMCID: PMC9617460 DOI: 10.1016/j.isci.2022.105084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 06/30/2022] [Accepted: 09/01/2022] [Indexed: 11/19/2022] Open
Abstract
Understanding how metabolic reprogramming happens in cells will aid the progress in the treatment of a variety of metabolic disorders. Brown bears undergo seasonal shifts in insulin sensitivity, including reversible insulin resistance in hibernation. We performed RNA-sequencing on brown bear adipocytes and proteomics on serum to identify changes possibly responsible for reversible insulin resistance. We observed dramatic transcriptional changes, which depended on both the cell and serum season of origin. Despite large changes in adipocyte gene expression, only changes in eight circulating proteins were identified as related to the seasonal shifts in insulin sensitivity, including some that have not previously been associated with glucose homeostasis. The identified serum proteins may be sufficient for shifting hibernation adipocytes to an active-like state. Hibernation in grizzly bears is marked by insulin resistance Bear adipocytes were stimulated with active and hibernating bear blood serum Serum elicited dramatic gene expression responses related to insulin signaling Eight serum proteins were implicated in driving this transcriptional response
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Affiliation(s)
- Michael W. Saxton
- School of Biological Sciences, Washington State University, Pullman, WA 99163, USA
| | - Blair W. Perry
- School of Biological Sciences, Washington State University, Pullman, WA 99163, USA
| | | | - Shawn Trojahn
- School of Biological Sciences, Washington State University, Pullman, WA 99163, USA
| | - Alexia Gee
- School of Biological Sciences, Washington State University, Pullman, WA 99163, USA
| | - Anthony P. Brown
- School of Biological Sciences, Washington State University, Pullman, WA 99163, USA
| | | | - Jea Park
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Omar E. Cornejo
- School of Biological Sciences, Washington State University, Pullman, WA 99163, USA
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Charles T. Robbins
- School of Biological Sciences, Washington State University, Pullman, WA 99163, USA
- School of the Environment, Washington State University, Pullman, WA 99163, USA
| | - Heiko T. Jansen
- Department of Integrative Physiology and Neuroscience, Washington State University, Pullman, WA 99163, USA
| | - Joanna L. Kelley
- School of Biological Sciences, Washington State University, Pullman, WA 99163, USA
- Corresponding author
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30
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Reiter KH, Zelter A, Janowska MK, Riffle M, Shulman N, MacLean BX, Tamura K, Chambers MC, MacCoss MJ, Davis TN, Guttman M, Brzovic PS, Klevit RE. Cullin-independent recognition of HHARI substrates by a dynamic RBR catalytic domain. Structure 2022; 30:1269-1284.e6. [PMID: 35716664 PMCID: PMC9444911 DOI: 10.1016/j.str.2022.05.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 04/15/2022] [Accepted: 05/24/2022] [Indexed: 11/27/2022]
Abstract
RING-between-RING (RBR) E3 ligases mediate ubiquitin transfer through an obligate E3-ubiquitin thioester intermediate prior to substrate ubiquitination. Although RBRs share a conserved catalytic module, substrate recruitment mechanisms remain enigmatic, and the relevant domains have yet to be identified for any member of the class. Here we characterize the interaction between the auto-inhibited RBR, HHARI (AriH1), and its target protein, 4EHP, using a combination of XL-MS, HDX-MS, NMR, and biochemical studies. The results show that (1) a di-aromatic surface on the catalytic HHARI Rcat domain forms a binding platform for substrates and (2) a phosphomimetic mutation on the auto-inhibitory Ariadne domain of HHARI promotes release and reorientation of Rcat for transthiolation and substrate modification. The findings identify a direct binding interaction between a RING-between-RING ligase and its substrate and suggest a general model for RBR substrate recognition.
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Affiliation(s)
- Katherine H Reiter
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
| | - Alex Zelter
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
| | - Maria K Janowska
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
| | - Michael Riffle
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
| | - Nicholas Shulman
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Brendan X MacLean
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Kaipo Tamura
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Matthew C Chambers
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Trisha N Davis
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
| | - Miklos Guttman
- Department of Medicinal Chemistry, University of Washington, Seattle, WA 98195, USA
| | - Peter S Brzovic
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
| | - Rachel E Klevit
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.
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31
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Huynh HH, Forrest K, Becker JO, Emrick MA, Miller GD, Moncrieffe D, Cowan DA, Thomas A, Thevis M, MacCoss MJ, Hoffstrom B, Byers PH, Eichner D, Hoofnagle AN. A Targeted Liquid Chromatography-Tandem Mass Spectrometry Method for Simultaneous Quantification of Peptides from the Carboxyl-terminal Region of Type III Procollagen, Biomarkers of Collagen Turnover. Clin Chem 2022; 68:1281-1291. [PMID: 35906802 DOI: 10.1093/clinchem/hvac119] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 06/10/2022] [Indexed: 11/12/2022]
Abstract
BACKGROUND The development of analytical approaches to help reduce the risk of growth hormone (GH) doping is important to fair competition and the health of athletes. However, the reliable detection of GH use remains challenging. The identification of novel biomarkers of GH administration could lead to a better understanding of the physiological response to GH, more sensitive detection of the illicit use of GH in sport, and better management of patients treated for GH disorders. METHODS We developed a targeted liquid chromatography-tandem mass spectrometry method to simultaneously quantify the carboxyl-terminal propeptide of type III procollagen (P-III-CP) and type III collagen degradation products in human serum. Following proteolysis, we instituted a simple acid precipitation step to reduce digested sample complexity before peptide immunoenrichment, which improved the recovery of one target peptide from serum. We evaluated the concentration of each biomarker at different age ranges and after GH administration in healthy participants. RESULTS The assay was linear over an estimated concentration range of 0.3 to1.0 nM and 0.1 to 0.4 nM for each surrogate peptide of P-III-CP and collagen fragments, respectively. Intra-day and inter-day coefficients of variation were ≤15%. Biomarker concentrations appeared to vary with age and to reflect age-specific collagen turnover. Moreover, their concentrations changed after GH administration. CONCLUSIONS Our method quantifies the proteins belonging to the family of P-III-CP and type III collagen degradation products in human serum, which could be used to detect GH administration in athletes and better understand diseases involving GH therapy or altered type III collagen turnover.
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Affiliation(s)
- Huu-Hien Huynh
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Katrina Forrest
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Jessica O Becker
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Michelle A Emrick
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Geoffrey D Miller
- Sports Medicine Research and Testing Laboratory, Salt Lake City, UT, USA
| | - Danielle Moncrieffe
- Drug Control Centre, Department of Analytical, Environmental and Forensic Science, King's College London, London, UK.,Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK
| | - David A Cowan
- Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK
| | - Andreas Thomas
- Center for Preventive Doping Research (ZePraeDo), Institute of Biochemistry, German Sport University, Cologne, Germany
| | - Mario Thevis
- Center for Preventive Doping Research (ZePraeDo), Institute of Biochemistry, German Sport University, Cologne, Germany
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Ben Hoffstrom
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Peter H Byers
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
| | - Daniel Eichner
- Sports Medicine Research and Testing Laboratory, Salt Lake City, UT, USA
| | - Andrew N Hoofnagle
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
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32
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Kirkwood KI, Pratt BS, Shulman N, Tamura K, MacCoss MJ, MacLean BX, Baker ES. Utilizing Skyline to analyze lipidomics data containing liquid chromatography, ion mobility spectrometry and mass spectrometry dimensions. Nat Protoc 2022; 17:2415-2430. [PMID: 35831612 DOI: 10.1038/s41596-022-00714-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 04/21/2022] [Indexed: 12/26/2022]
Abstract
Lipidomics studies suffer from analytical and annotation challenges because of the great structural similarity of many of the lipid species. To improve lipid characterization and annotation capabilities beyond those afforded by traditional mass spectrometry (MS)-based methods, multidimensional separation methods such as those integrating liquid chromatography, ion mobility spectrometry, collision-induced dissociation and MS (LC-IMS-CID-MS) may be used. Although LC-IMS-CID-MS and other multidimensional methods offer valuable hydrophobicity, structural and mass information, the files are also complex and difficult to assess. Thus, the development of software tools to rapidly process and facilitate confident lipid annotations is essential. In this Protocol Extension, we use the freely available, vendor-neutral and open-source software Skyline to process and annotate multidimensional lipidomic data. Although Skyline ( https://skyline.ms/skyline.url ) was established for targeted processing of LC-MS-based proteomics data, it has since been extended such that it can be used to analyze small-molecule data as well as data containing the IMS dimension. This protocol uses Skyline's recently expanded capabilities, including small-molecule spectral libraries, indexed retention time and ion mobility filtering, and provides a step-by-step description for importing data, predicting retention times, validating lipid annotations, exporting results and editing our manually validated 500+ lipid library. Although the time required to complete the steps outlined here varies on the basis of multiple factors such as dataset size and familiarity with Skyline, this protocol takes ~5.5 h to complete when annotations are rigorously verified for maximum confidence.
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Affiliation(s)
- Kaylie I Kirkwood
- Department of Chemistry, North Carolina State University, Raleigh, NC, USA
| | - Brian S Pratt
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Nicholas Shulman
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Kaipo Tamura
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Brendan X MacLean
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Erin S Baker
- Department of Chemistry, North Carolina State University, Raleigh, NC, USA. .,Comparative Medicine Institute, North Carolina State University, Raleigh, NC, USA.
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33
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Peng D, Kakani EG, Mameli E, Vidoudez C, Mitchell SN, Merrihew GE, MacCoss MJ, Adams K, Rinvee TA, Shaw WR, Catteruccia F. A male steroid controls female sexual behaviour in the malaria mosquito. Nature 2022; 608:93-97. [PMID: 35794471 PMCID: PMC9352575 DOI: 10.1038/s41586-022-04908-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 05/25/2022] [Indexed: 11/09/2022]
Abstract
Insects, unlike vertebrates, are widely believed to lack male-biased sex steroid hormones1. In the malaria mosquito Anopheles gambiae, the ecdysteroid 20-hydroxyecdysone (20E) appears to have evolved to both control egg development when synthesized by females2 and to induce mating refractoriness when sexually transferred by males3. Because egg development and mating are essential reproductive traits, understanding how Anopheles females integrate these hormonal signals can spur the design of new malaria control programs. Here we reveal that these reproductive functions are regulated by distinct sex steroids through a sophisticated network of ecdysteroid-activating/inactivating enzymes. We identify a male-specific oxidized ecdysteroid, 3-dehydro-20E (3D20E), which safeguards paternity by turning off female sexual receptivity following its sexual transfer and activation by dephosphorylation. Notably, 3D20E transfer also induces expression of a reproductive gene that preserves egg development during Plasmodium infection, ensuring fitness of infected females. Female-derived 20E does not trigger sexual refractoriness but instead licenses oviposition in mated individuals once a 20E-inhibiting kinase is repressed. Identifying this male-specific insect steroid hormone and its roles in regulating female sexual receptivity, fertility and interactions with Plasmodium parasites suggests the possibility for reducing the reproductive success of malaria-transmitting mosquitoes.
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Affiliation(s)
- Duo Peng
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Evdoxia G Kakani
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.,Verily Life Sciences, South San Francisco, CA, USA
| | - Enzo Mameli
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.,Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | | | - Sara N Mitchell
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.,Verily Life Sciences, South San Francisco, CA, USA
| | | | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Kelsey Adams
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Tasneem A Rinvee
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - W Robert Shaw
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Flaminia Catteruccia
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA. .,Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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34
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Burnum-Johnson KE, Conrads TP, Drake RR, Herr AE, Iyengar R, Kelly RT, Lundberg E, MacCoss MJ, Naba A, Nolan GP, Pevzner PA, Rodland KD, Sechi S, Slavov N, Spraggins JM, Van Eyk JE, Vidal M, Vogel C, Walt DR, Kelleher NL. New Views of Old Proteins: Clarifying the Enigmatic Proteome. Mol Cell Proteomics 2022; 21:100254. [PMID: 35654359 PMCID: PMC9256833 DOI: 10.1016/j.mcpro.2022.100254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/09/2022] [Accepted: 05/27/2022] [Indexed: 11/23/2022] Open
Abstract
All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide a >10 years of projection for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we describe a next generation of approaches to define, quantify, and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade.
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Affiliation(s)
- Kristin E Burnum-Johnson
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA.
| | - Thomas P Conrads
- Inova Women's Service Line, Inova Health System, Falls Church, Virginia, USA
| | - Richard R Drake
- Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Amy E Herr
- Department of Bioengineering, University of California, Berkeley, California, USA
| | - Ravi Iyengar
- Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah, USA
| | - Emma Lundberg
- Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Alexandra Naba
- Department of Physiology and Biophysics, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Garry P Nolan
- Department of Pathology, Stanford University, Stanford, California, USA
| | - Pavel A Pevzner
- Department of Computer Science and Engineering, University of California at San Diego, San Diego, California, USA
| | - Karin D Rodland
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Salvatore Sechi
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Nikolai Slavov
- Department of Bioengineering, Northeastern University, Boston, Massachusetts, USA
| | - Jeffrey M Spraggins
- Department of Cell and Developmental Biology, Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA
| | - Jennifer E Van Eyk
- Advanced Clinical Biosystems Institute in the Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Marc Vidal
- Department of Genetics, Harvard University, Cambridge, Massachusetts, USA
| | - Christine Vogel
- New York University Center for Genomics and Systems Biology, New York University, New York, New York, USA
| | - David R Walt
- Department of Pathology, Harvard Medical School, Brigham and Women's Hospital, Wyss Institute at Harvard University, Boston, Massachusetts, USA
| | - Neil L Kelleher
- Department of Chemistry, Northwestern University, Evanston, Illinois, USA.
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35
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Endicott SJ, Monovich AC, Huang EL, Henry EI, Boynton DN, Beckmann LJ, MacCoss MJ, Miller RA. Lysosomal targetomics of ghr KO mice shows chaperone-mediated autophagy degrades nucleocytosolic acetyl-coA enzymes. Autophagy 2022; 18:1551-1571. [PMID: 34704522 PMCID: PMC9298451 DOI: 10.1080/15548627.2021.1990670] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Mice deficient in GHR (growth hormone receptor; ghr KO) have a dramatic lifespan extension and elevated levels of hepatic chaperone-mediated autophagy (CMA). Using quantitative proteomics to identify protein changes in purified liver lysosomes and whole liver lysates, we provide evidence that elevated CMA in ghr KO mice downregulates proteins involved in ribosomal structure, translation initiation and elongation, and nucleocytosolic acetyl-coA production. Following up on these initial proteomics findings, we used a cell culture approach to show that CMA is necessary and sufficient to regulate the abundance of ACLY and ACSS2, the two enzymes that produce nucleocytosolic (but not mitochondrial) acetyl-coA. Inhibition of CMA in NIH3T3 cells has been shown to lead to aberrant accumulation of lipid droplets. We show that this lipid droplet phenotype is rescued by knocking down ACLY or ACSS2, suggesting that CMA regulates lipid droplet formation by controlling ACLY and ACSS2. This evidence leads to a model of how constitutive activation of CMA can shape specific metabolic pathways in long-lived endocrine mutant mice.Abbreviations: CMA: chaperone-mediated autophagy; DIA: data-independent acquisition; ghr KO: growth hormone receptor knockout; GO: gene ontology; I-WAT: inguinal white adipose tissue; KFERQ: a consensus sequence resembling Lys-Phe-Glu-Arg-Gln; LAMP2A: lysosomal-associated membrane protein 2A; LC3-I: non-lipidated MAP1LC3; LC3-II: lipidated MAP1LC3; PBS: phosphate-buffered saline; PI3K: phosphoinositide 3-kinase.
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Affiliation(s)
| | | | - Eric L. Huang
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Evelynn I. Henry
- Program in Cellular and Molecular Biology, University of Michigan, Ann Arbor, MI, USA,Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA
| | - Dennis N. Boynton
- College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI, USA
| | - Logan J. Beckmann
- College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI, USA
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Richard A. Miller
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA,Geriatrics Center, University of Michigan, Ann Arbor, MI, USA,CONTACT Richard A. Miller Department of Pathology, University of Michigan, Ann Arbor, MI, USA
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36
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Whitson JA, Johnson R, Wang L, Bammler TK, Imai SI, Zhang H, Fredrickson J, Latorre-Esteves E, Bitto A, MacCoss MJ, Rabinovitch PS. Age-related disruption of the proteome and acetylome in mouse hearts is associated with loss of function and attenuated by elamipretide (SS-31) and nicotinamide mononucleotide (NMN) treatment. GeroScience 2022; 44:1621-1639. [PMID: 35416576 PMCID: PMC9213586 DOI: 10.1007/s11357-022-00564-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Accepted: 04/04/2022] [Indexed: 11/04/2022] Open
Abstract
We analyzed the effects of aging on protein abundance and acetylation, as well as the ability of the mitochondrial-targeted drugs elamipretide (SS-31) and nicotinamide mononucleotide (NMN) to reverse aging-associated changes in mouse hearts. Both drugs had a modest effect on restoring the abundance and acetylation of proteins that are altered with age, while also inducing additional changes. Age-related increases in protein acetylation were predominantly in mitochondrial pathways such as mitochondrial dysfunction, oxidative phosphorylation, and TCA cycle signaling. We further assessed how these age-related changes associated with diastolic function (Ea/Aa) and systolic function (fractional shortening under higher workload) measurements from echocardiography. These results identify a subset of protein abundance and acetylation changes in muscle, mitochondrial, and structural proteins that appear to be essential in regulating diastolic function in old hearts.
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Affiliation(s)
- Jeremy A Whitson
- Department of Biology, Davidson College, 405 N Main St, Davidson, NC, 28035, USA
| | - Richard Johnson
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, WA, 98195, USA
| | - Lu Wang
- Department of Environmental & Occupational Health Sciences, University of Washington, 4225 Roosevelt Way NE, Seattle, WA, 98105, USA
| | - Theo K Bammler
- Department of Environmental & Occupational Health Sciences, University of Washington, 4225 Roosevelt Way NE, Seattle, WA, 98105, USA
| | - Shin-Ichiro Imai
- Department of Developmental Biology, Washington University School of Medicine, 660 South Euclid Avenue, St. Louis, MO, 63110, USA
| | - Huiliang Zhang
- Department of Pharmacology and Toxicology, University of Arkansas for Medical Sciences, 4301 W Markham St, Little Rock, AR, 72205, USA
| | - Jeanne Fredrickson
- Department of Pathology, University of Washington, 1959 NE Pacific St, Seattle, WA, 98195, USA
| | - Elena Latorre-Esteves
- Department of Pathology, University of Washington, 1959 NE Pacific St, Seattle, WA, 98195, USA
| | - Alessandro Bitto
- Department of Pathology, University of Washington, 1959 NE Pacific St, Seattle, WA, 98195, USA
| | - Michael J MacCoss
- Department of Pathology, University of Washington, 1959 NE Pacific St, Seattle, WA, 98195, USA
| | - Peter S Rabinovitch
- Department of Pathology, University of Washington, 1959 NE Pacific St, Seattle, WA, 98195, USA.
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37
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Heil LR, Fondrie WE, McGann CD, Federation AJ, Noble WS, MacCoss MJ, Keich U. Building Spectral Libraries from Narrow-Window Data-Independent Acquisition Mass Spectrometry Data. J Proteome Res 2022; 21:1382-1391. [PMID: 35549345 DOI: 10.1021/acs.jproteome.1c00895] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Advances in library-based methods for peptide detection from data-independent acquisition (DIA) mass spectrometry have made it possible to detect and quantify tens of thousands of peptides in a single mass spectrometry run. However, many of these methods rely on a comprehensive, high-quality spectral library containing information about the expected retention time and fragmentation patterns of peptides in the sample. Empirical spectral libraries are often generated through data-dependent acquisition and may suffer from biases as a result. Spectral libraries can be generated in silico, but these models are not trained to handle all possible post-translational modifications. Here, we propose a false discovery rate-controlled spectrum-centric search workflow to generate spectral libraries directly from gas-phase fractionated DIA tandem mass spectrometry data. We demonstrate that this strategy is able to detect phosphorylated peptides and can be used to generate a spectral library for accurate peptide detection and quantitation in wide-window DIA data. We compare the results of this search workflow to other library-free approaches and demonstrate that our search is competitive in terms of accuracy and sensitivity. These results demonstrate that the proposed workflow has the capacity to generate spectral libraries while avoiding the limitations of other methods.
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Affiliation(s)
- Lilian R Heil
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105, United States
| | - William E Fondrie
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105, United States
| | - Christopher D McGann
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105, United States
| | - Alexander J Federation
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105, United States
| | - William S Noble
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105, United States.,Paul G. Allen School for Computer Science and Engineering, University of Washington, Seattle, Washington 98105, United States
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105, United States
| | - Uri Keich
- School of Mathematics and Statistics, University of Sydney, Sydney, NSW 2006, Australia
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38
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Phipps WS, Smith KD, Yang HY, Henderson CM, Pflaum H, Lerch ML, Fondrie WE, Emrick MA, Wu CC, MacCoss MJ, Noble WS, Hoofnagle AN. Tandem Mass Spectrometry-Based Amyloid Typing Using Manual Microdissection and Open-Source Data Processing. Am J Clin Pathol 2022; 157:748-757. [PMID: 35512256 PMCID: PMC9071319 DOI: 10.1093/ajcp/aqab185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 09/20/2021] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVES Standard implementations of amyloid typing by liquid chromatography-tandem mass spectrometry use capabilities unavailable to most clinical laboratories. To improve accessibility of this testing, we explored easier approaches to tissue sampling and data processing. METHODS We validated a typing method using manual sampling in place of laser microdissection, pairing the technique with a semiquantitative measure of sampling adequacy. In addition, we created an open-source data processing workflow (Crux Pipeline) for clinical users. RESULTS Cases of amyloidosis spanning the major types were distinguishable with 100% specificity using measurements of individual amyloidogenic proteins or in combination with the ratio of λ and κ constant regions. Crux Pipeline allowed for rapid, batched data processing, integrating the steps of peptide identification, statistical confidence estimation, and label-free protein quantification. CONCLUSIONS Accurate mass spectrometry-based amyloid typing is possible without laser microdissection. To facilitate entry into solid tissue proteomics, newcomers can leverage manual sampling approaches in combination with Crux Pipeline and related tools.
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Affiliation(s)
- William S Phipps
- Department of Laboratory Medicine and Pathology, Seattle, WA, USA
| | - Kelly D Smith
- Department of Laboratory Medicine and Pathology, Seattle, WA, USA
- Department of Medicine, Seattle, WA, USA
| | - Han-Yin Yang
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Clark M Henderson
- Department of Laboratory Medicine and Pathology, Seattle, WA, USA
- Seagen, Bothel, WA, USA
| | - Hannah Pflaum
- Department of Laboratory Medicine and Pathology, Seattle, WA, USA
- Seattle Children’s Hospital, Seattle, WA, USA
| | - Melissa L Lerch
- Department of Laboratory Medicine and Pathology, Seattle, WA, USA
| | - William E Fondrie
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Christine C Wu
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - William S Noble
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Andrew N Hoofnagle
- Department of Laboratory Medicine and Pathology, Seattle, WA, USA
- Department of Medicine, Seattle, WA, USA
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39
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Plubell DL, Käll L, Webb-Robertson BJM, Bramer LM, Ives A, Kelleher NL, Smith LM, Montine TJ, Wu CC, MacCoss MJ. Putting Humpty Dumpty Back Together Again: What Does Protein Quantification Mean in Bottom-Up Proteomics? J Proteome Res 2022; 21:891-898. [PMID: 35220718 PMCID: PMC8976764 DOI: 10.1021/acs.jproteome.1c00894] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Bottom-up proteomics provides peptide measurements and has been invaluable for moving proteomics into large-scale analyses. Commonly, a single quantitative value is reported for each protein-coding gene by aggregating peptide quantities into protein groups following protein inference or parsimony. However, given the complexity of both RNA splicing and post-translational protein modification, it is overly simplistic to assume that all peptides that map to a singular protein-coding gene will demonstrate the same quantitative response. By assuming that all peptides from a protein-coding sequence are representative of the same protein, we may miss the discovery of important biological differences. To capture the contributions of existing proteoforms, we need to reconsider the practice of aggregating protein values to a single quantity per protein-coding gene.
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Affiliation(s)
- Deanna L. Plubell
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195 USA
| | - Lukas Käll
- Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 17121, Solna, Sweden
| | | | - Lisa M. Bramer
- Pacific Northwest National Laboratory, Richland, WA 99352
| | - Ashley Ives
- Proteomics Center of Excellence & Departments of Chemistry and Molecular Biosciences, Northwestern University, Evanston, IL 60208
| | - Neil L. Kelleher
- Proteomics Center of Excellence & Departments of Chemistry and Molecular Biosciences, Northwestern University, Evanston, IL 60208
| | - Lloyd M. Smith
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706
| | | | - Christine C. Wu
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195 USA
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195 USA
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40
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Stillman M, Lautz JD, Johnson RS, MacCoss MJ, Smith SEP. Activity dependent dissociation of the Homer1 interactome. Sci Rep 2022; 12:3207. [PMID: 35217690 PMCID: PMC8881602 DOI: 10.1038/s41598-022-07179-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 02/09/2022] [Indexed: 11/12/2022] Open
Abstract
Neurons encode information by rapidly modifying synaptic protein complexes, which changes the strength of specific synaptic connections. Homer1 is abundantly expressed at glutamatergic synapses, and is known to alter its binding to metabotropic glutamate receptor 5 (mGlu5) in response to synaptic activity. However, Homer participates in many additional known interactions whose activity-dependence is unclear. Here, we used co-immunoprecipitation and label-free quantitative mass spectrometry to characterize activity-dependent interactions in the cerebral cortex of wildtype and Homer1 knockout mice. We identified a small, high-confidence protein network consisting of mGlu5, Shank2 and 3, and Homer1–3, of which only mGlu5 and Shank3 were significantly reduced following neuronal depolarization. We identified several other proteins that reduced their co-association in an activity-dependent manner, likely mediated by Shank proteins. We conclude that Homer1 dissociates from mGlu5 and Shank3 following depolarization, but our data suggest that direct Homer1 interactions in the cortex may be more limited than expected.
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Affiliation(s)
- Mason Stillman
- Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, WA, USA.,Dartmouth-Hitchcock Medical Center Psychiatry Residency Program, Dartmouth, NH, USA
| | - Jonathan D Lautz
- Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, WA, USA
| | - Richard S Johnson
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Stephen E P Smith
- Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, WA, USA. .,Department of Pediatrics, University of Washington, Seattle, WA, USA. .,Graduate Program in Neuroscience, University of Washington, Seattle, WA, USA.
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41
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Riffle M, Hoopmann MR, Jaschob D, Zhong G, Moritz RL, MacCoss MJ, Davis TN, Isoherranen N, Zelter A. Discovery and Visualization of Uncharacterized Drug-Protein Adducts Using Mass Spectrometry. Anal Chem 2022; 94:3501-3509. [PMID: 35184559 PMCID: PMC8892443 DOI: 10.1021/acs.analchem.1c04101] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
![]()
Drugs are often metabolized
to reactive intermediates that form
protein adducts. Adducts can inhibit protein activity, elicit immune
responses, and cause life-threatening adverse drug reactions. The
masses of reactive metabolites are frequently unknown, rendering traditional
mass spectrometry-based proteomics approaches incapable of adduct
identification. Here, we present Magnum, an open-mass search algorithm
optimized for adduct identification, and Limelight, a web-based data
processing package for analysis and visualization of data from all
existing algorithms. Limelight incorporates tools for sample comparisons
and xenobiotic-adduct discovery. We validate our tools with three
drug/protein combinations and apply our label-free workflow to identify
novel xenobiotic-protein adducts in CYP3A4. Our new methods and software
enable accurate identification of xenobiotic-protein adducts with
no prior knowledge of adduct masses or protein targets. Magnum outperforms
existing label-free tools in xenobiotic-protein adduct discovery,
while Limelight fulfills a major need in the rapidly developing field
of open-mass searching, which until now lacked comprehensive data
visualization tools.
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Affiliation(s)
- Michael Riffle
- Department of Biochemistry, University of Washington, Seattle, Washington 98195, United States
| | | | - Daniel Jaschob
- Department of Biochemistry, University of Washington, Seattle, Washington 98195, United States
| | - Guo Zhong
- Department of Pharmaceutics, University of Washington, Seattle, Washington 98195, United States
| | - Robert L Moritz
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Trisha N Davis
- Department of Biochemistry, University of Washington, Seattle, Washington 98195, United States
| | - Nina Isoherranen
- Department of Pharmaceutics, University of Washington, Seattle, Washington 98195, United States
| | - Alex Zelter
- Department of Biochemistry, University of Washington, Seattle, Washington 98195, United States
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42
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Guitart-Mampel M, Urquiza P, Carnevale Neto F, Anderson JR, Hambardikar V, Scoma ER, Merrihew GE, Wang L, MacCoss MJ, Raftery D, Peffers MJ, Solesio ME. Mitochondrial Inorganic Polyphosphate (polyP) Is a Potent Regulator of Mammalian Bioenergetics in SH-SY5Y Cells: A Proteomics and Metabolomics Study. Front Cell Dev Biol 2022; 10:833127. [PMID: 35252194 PMCID: PMC8892102 DOI: 10.3389/fcell.2022.833127] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 01/21/2022] [Indexed: 01/04/2023] Open
Abstract
Inorganic polyphosphate (polyP) is an ancient, ubiquitous, and well-conserved polymer which is present in all the studied organisms. It is formed by individual subunits of orthophosphate which are linked by structurally similar bonds and isoenergetic to those found in ATP. While the metabolism and the physiological roles of polyP have already been described in some organisms, including bacteria and yeast, the exact role of this polymer in mammalian physiology still remains poorly understood. In these organisms, polyP shows a co-localization with mitochondria, and its role as a key regulator of the stress responses, including the maintenance of appropriate bioenergetics, has already been demonstrated by our group and others. Here, using Wild-type (Wt) and MitoPPX (cells enzymatically depleted of mitochondrial polyP) SH-SY5Y cells, we have conducted a comprehensive study of the status of cellular physiology, using proteomics and metabolomics approaches. Our results suggest a clear dysregulation of mitochondrial physiology, especially of bioenergetics, in MitoPPX cells when compared with Wt cells. Moreover, the effects induced by the enzymatic depletion of polyP are similar to those present in the mitochondrial dysfunction that is observed in neurodegenerative disorders and in neuronal aging. Based on our findings, the metabolism of mitochondrial polyP could be a valid and innovative pharmacological target in these conditions.
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Affiliation(s)
| | - Pedro Urquiza
- Department of Biology, Rutgers University, Camden, NJ, United States
| | - Fausto Carnevale Neto
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, United States
| | - James R. Anderson
- Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Vedangi Hambardikar
- Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, United States
| | - Ernest R. Scoma
- Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, United States
| | - Gennifer E. Merrihew
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Lu Wang
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, United States
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, United States
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United States
| | - Mandy J. Peffers
- Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Maria E. Solesio
- Department of Biology, Rutgers University, Camden, NJ, United States
- Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, United States
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43
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Cohen ZR, Kessenich BL, Hazra A, Nguyen J, Johnson RS, MacCoss MJ, Lalic G, Black RA, Keller SL. Prebiotic Membranes and Micelles Do Not Inhibit Peptide Formation During Dehydration. Chembiochem 2022; 23:e202100614. [PMID: 34881485 PMCID: PMC8957845 DOI: 10.1002/cbic.202100614] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 12/07/2021] [Indexed: 02/06/2023]
Abstract
Cycles of dehydration and rehydration could have enabled formation of peptides and RNA in otherwise unfavorable conditions on the early Earth. Development of the first protocells would have hinged upon colocalization of these biopolymers with fatty acid membranes. Using atomic force microscopy, we find that a prebiotic fatty acid (decanoic acid) forms stacks of membranes after dehydration. Using LC-MS-MS (liquid chromatography-tandem mass spectrometry) with isotope internal standards, we measure the rate of formation of serine dipeptides. We find that dipeptides form during dehydration at moderate temperatures (55 °C) at least as fast in the presence of decanoic acid membranes as in the absence of membranes. Our results are consistent with the hypothesis that protocells could have formed within evaporating environments on the early Earth.
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Affiliation(s)
- Zachary R. Cohen
- Department of Chemistry, University of Washington – Seattle, Seattle, Washington 98195-1700, USA, Astrobiology Program, University of Washington – Seattle, Seattle, Washington 98195, USA
| | - Brennan L. Kessenich
- Department of Chemistry, University of Washington – Seattle, Seattle, Washington 98195-1700, USA
| | - Avijit Hazra
- Department of Chemistry, University of Washington – Seattle, Seattle, Washington 98195-1700, USA
| | - Julia Nguyen
- Department of Chemistry, University of Washington – Seattle, Seattle, Washington 98195-1700, USA
| | - Richard S. Johnson
- Department of Genome Sciences, University of Washington – Seattle, Seattle, Washington 98195, USA
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington – Seattle, Seattle, Washington 98195, USA
| | - Gojko Lalic
- Department of Chemistry, University of Washington – Seattle, Seattle, Washington 98195-1700, USA
| | - Roy. A. Black
- Department of Chemistry, University of Washington – Seattle, Seattle, Washington 98195-1700, USA
| | - Sarah L. Keller
- Department of Chemistry, University of Washington – Seattle, Seattle, Washington 98195-1700, USA, Astrobiology Program, University of Washington – Seattle, Seattle, Washington 98195, USA
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44
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Zhao X, Golic FT, Harrison BR, Manoj M, Hoffman EV, Simon N, Johnson R, MacCoss MJ, McIntyre LM, Promislow DEL. The metabolome as a biomarker of aging in Drosophila melanogaster. Aging Cell 2022; 21:e13548. [PMID: 35019203 PMCID: PMC8844127 DOI: 10.1111/acel.13548] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 11/12/2021] [Indexed: 12/15/2022] Open
Abstract
Many biomarkers have been shown to be associated not only with chronological age but also with functional measures of biological age. In human populations, it is difficult to show whether variation in biological age is truly predictive of life expectancy, as such research would require longitudinal studies over many years, or even decades. We followed adult cohorts of 20 Drosophila Genetic Reference Panel (DGRP) strains chosen to represent the breadth of lifespan variation, obtain estimates of lifespan, baseline mortality, and rate of aging, and associate these parameters with age‐specific functional traits including fecundity and climbing activity and with age‐specific targeted metabolomic profiles. We show that activity levels and metabolome‐wide profiles are strongly associated with age, that numerous individual metabolites show a strong association with lifespan, and that the metabolome provides a biological clock that predicts not only sample age but also future mortality rates and lifespan. This study with 20 genotypes and 87 metabolites, while relatively small in scope, establishes strong proof of principle for the fly as a powerful experimental model to test hypotheses about biomarkers and aging and provides further evidence for the potential value of metabolomic profiles as biomarkers of aging.
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Affiliation(s)
- Xiaqing Zhao
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
| | - Forrest T. Golic
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
| | - Benjamin R. Harrison
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
| | - Meghna Manoj
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
| | - Elise V. Hoffman
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
| | - Neta Simon
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
| | - Richard Johnson
- Department of Genome Sciences University of Washington School of Medicine Seattle US
| | - Michael J. MacCoss
- Department of Genome Sciences University of Washington School of Medicine Seattle US
| | - Lauren M. McIntyre
- Genetics Institute University of Florida Gainesville USA
- Department of Molecular Genetics and Microbiology University of Florida Gainesville USA
| | - Daniel E. L. Promislow
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
- Department of Biology University of Washington Seattle US
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45
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Hubbard EE, Heil LR, Merrihew GE, Chhatwal JP, Farlow MR, McLean CA, Ghetti B, Newell KL, Frosch MP, Bateman RJ, Larson EB, Keene CD, Perrin RJ, Montine TJ, MacCoss MJ, Julian RR. Does Data-Independent Acquisition Data Contain Hidden Gems? A Case Study Related to Alzheimer's Disease. J Proteome Res 2022; 21:118-131. [PMID: 34818016 PMCID: PMC8741752 DOI: 10.1021/acs.jproteome.1c00558] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
One of the potential benefits of using data-independent acquisition (DIA) proteomics protocols is that information not originally targeted by the study may be present and discovered by subsequent analysis. Herein, we reanalyzed DIA data originally recorded for global proteomic analysis to look for isomerized peptides, which occur as a result of spontaneous chemical modifications to long-lived proteins. Examination of a large set of human brain samples revealed a striking relationship between Alzheimer's disease (AD) status and isomerization of aspartic acid in a peptide from tau. Relative to controls, a surprising increase in isomer abundance was found in both autosomal dominant and sporadic AD samples. To explore potential mechanisms that might account for these observations, quantitative analysis of proteins related to isomerization repair and autophagy was performed. Differences consistent with reduced autophagic flux in AD-related samples relative to controls were found for numerous proteins, including most notably p62, a recognized indicator of autophagic inhibition. These results suggest, but do not conclusively demonstrate, that lower autophagic flux may be strongly associated with loss of function in AD brains. This study illustrates that DIA data may contain unforeseen results of interest and may be particularly useful for pilot studies investigating new research directions. In this case, a promising target for future investigations into the therapy and prevention of AD has been identified.
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Affiliation(s)
- Evan E. Hubbard
- Department of Chemistry, University of California, Riverside, California 92521, United States
| | - Lilian R. Heil
- Department of Genome Sciences, University of Washington, Seattle, Washington, 98195, United States
| | - Gennifer E. Merrihew
- Department of Genome Sciences, University of Washington, Seattle, Washington, 98195, United States
| | - Jasmeer P. Chhatwal
- Harvard Medical School, Massachusetts General Hospital, Department of Neurology, 15 Parkman St, Suite 835, Boston MA 02114
| | - Martin R. Farlow
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, 46202
| | | | - Bernardino Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202
| | - Kathy L. Newell
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202
| | - Matthew P. Frosch
- C.S. Kubik Laboratory for Neuropathology, and Massachusetts Alzheimer Disease Research Center, Massachusetts General Hospital, Boston, MA 02114
| | - Randall J. Bateman
- Department of Neurology, Washington University School of Medicine, 660 South Euclid Avenue, Box 8111, St. Louis, 63110, Missouri, USA
| | - Eric B. Larson
- Kaiser Permanente Washington Health Research Institute and Department of Medicine, University of Washington, Seattle WA
| | - C. Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, 98195, United States
| | - Richard J. Perrin
- Department of Pathology and Immunology, Department of Neurology, Washington University School of Medicine, Saint Louis, Missouri 63110, United States
| | - Thomas J. Montine
- Department of Pathology, Stanford University, Stanford, CA, 94305, United States
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, Washington, 98195, United States
| | - Ryan R. Julian
- Department of Chemistry, University of California, Riverside, California 92521, United States,corresponding author:
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46
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Ramsey JS, Ammar ED, Mahoney JE, Rivera K, Johnson R, Igwe DO, Thannhauser TW, MacCoss MJ, Hall DG, Heck M. Host Plant Adaptation Drives Changes in Diaphorina citri Proteome Regulation, Proteoform Expression, and Transmission of ' Candidatus Liberibacter asiaticus', the Citrus Greening Pathogen. Phytopathology 2022; 112:101-115. [PMID: 34738832 DOI: 10.1094/phyto-06-21-0275-r] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The Asian citrus psyllid (Diaphorina citri) is a pest of citrus and the primary insect vector of the bacterial pathogen, 'Candidatus Liberibacter asiaticus' (CLas), which is associated with citrus greening disease. The citrus relative Murraya paniculata (orange jasmine) is a host plant of D. citri but is more resistant to CLas compared with all tested Citrus genotypes. The effect of host switching of D. citri between Citrus medica (citron) and M. paniculata plants on the acquisition and transmission of CLas was investigated. The psyllid CLas titer and the proportion of CLas-infected psyllids decreased in the generations after transfer from CLas-infected citron to healthy M. paniculata plants. Furthermore, after several generations of feeding on M. paniculata, pathogen acquisition (20 to 40% reduction) and transmission rates (15 to 20% reduction) in psyllids transferred to CLas-infected citron were reduced compared with psyllids continually maintained on infected citron. Top-down (difference gel electrophoresis) and bottom-up (shotgun MS/MS) proteomics methods were used to identify changes in D. citri protein expression resulting from host plant switching between Citrus macrophylla and M. paniculata. Changes in expression of insect metabolism, immunity, and cytoskeleton proteins were associated with host plant switching. Both transient and sustained feeding on M. paniculata induced distinct patterns of protein expression in D. citri compared with psyllids reared on C. macrophylla. The results point to complex interactions that affect vector competence and may lead to strategies to control the spread of citrus greening disease.
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Affiliation(s)
- John S Ramsey
- U.S. Department of Agriculture-Agricultural Research Service-Emerging Pests and Pathogens Research Unit, Ithaca, NY
| | - El-Desouky Ammar
- U.S. Department of Agriculture-Agricultural Research Service, USHRL-SIRU, Fort Pierce, FL
| | | | - Keith Rivera
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
| | | | - David O Igwe
- Cornell University College of Agriculture and Life Sciences-Plant Pathology and Plant Microbe Biology, Ithaca, NY
| | - Theodore W Thannhauser
- U.S. Department of Agriculture-Agricultural Research Service-Plant, Soil, and Nutrition Research Unit, Ithaca, NY
| | | | - David G Hall
- U.S. Department of Agriculture-Agricultural Research Service, USHRL-SIRU, Fort Pierce, FL
| | - Michelle Heck
- U.S. Department of Agriculture-Agricultural Research Service-Emerging Pests and Pathogens Research Unit, Ithaca, NY
- Cornell University College of Agriculture and Life Sciences-Plant Pathology and Plant Microbe Biology, Ithaca, NY
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47
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Abstract
![]()
Skyline Batch is
a newly developed Windows forms application that
enables the easy and consistent reprocessing of data with Skyline.
Skyline has made previous advances in this direction; however, none
enable seamless automated reprocessing of local and remote files.
Skyline keeps a log of all of the steps that were taken in the document;
however, reproducing these steps takes time and allows room for human
error. Skyline also has a command-line interface, enabling it to be
run from a batch script, but using the program in this way requires
expertise in editing these scripts. By formalizing the workflow of
a highly used set of batch scripts into an intuitive and powerful
user interface, Skyline Batch can reprocess data stored in remote
repositories just by opening and running a Skyline Batch configuration
file. When run, a Skyline Batch configuration downloads all necessary
remote files and then runs a four-step Skyline workflow. By condensing
the steps needed to reprocess the data into one file, Skyline Batch
gives researchers the opportunity to publish their processing along
with their data and other analysis files. These easily run configuration
files will greatly increase the transparency and reproducibility of
published work. Skyline Batch is freely available at https://skyline.ms/batch.url.
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Affiliation(s)
- Alexandra N Marsh
- Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Vagisha Sharma
- Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Surya K Mani
- Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Olga Vitek
- Khoury College of Computer Sciences, Northeastern University, Boston, Massachusetts 02115, United States
| | - Michael J MacCoss
- Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Brendan X MacLean
- Genome Sciences, University of Washington, Seattle, Washington 98195, United States
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48
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Kirkwood KI, Christopher MW, Burgess JL, Littau SR, Foster K, Richey K, Pratt BS, Shulman N, Tamura K, MacCoss MJ, MacLean BX, Baker ES. Development and Application of Multidimensional Lipid Libraries to Investigate Lipidomic Dysregulation Related to Smoke Inhalation Injury Severity. J Proteome Res 2021; 21:232-242. [PMID: 34874736 DOI: 10.1021/acs.jproteome.1c00820] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The implication of lipid dysregulation in diseases, toxic exposure outcomes, and inflammation has brought great interest to lipidomic studies. However, lipids have proven to be analytically challenging due to their highly isomeric nature and vast concentration ranges in biological matrices. Therefore, multidimensional techniques such as those integrating liquid chromatography, ion mobility spectrometry, collision-induced dissociation, and mass spectrometry (LC-IMS-CID-MS) have been implemented to separate lipid isomers as well as provide structural information and increased identification confidence. These data sets are however extremely large and complex, resulting in challenges for data processing and annotation. Here, we have overcome these challenges by developing sample-specific multidimensional lipid libraries using the freely available software Skyline. Specifically, the human plasma library developed for this work contains over 500 unique lipids and is combined with adapted Skyline functions such as indexed retention time (iRT) for retention time prediction and IMS drift time filtering for enhanced selectivity. For comparison with other studies, this database was used to annotate LC-IMS-CID-MS data from a NIST SRM 1950 extract. The same workflow was then utilized to assess plasma and bronchoalveolar lavage fluid (BALF) samples from patients with varying degrees of smoke inhalation injury to identify lipid-based patient prognostic and diagnostic markers.
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Affiliation(s)
- Kaylie I Kirkwood
- Department of Chemistry, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Michael W Christopher
- Department of Chemistry, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Jefferey L Burgess
- Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona 85721, United States
| | - Sally R Littau
- Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona 85721, United States
| | - Kevin Foster
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Karen Richey
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Brian S Pratt
- Arizona Burn Center, Valleywise Health, Phoenix, Arizona 85008, United States
| | - Nicholas Shulman
- Arizona Burn Center, Valleywise Health, Phoenix, Arizona 85008, United States
| | - Kaipo Tamura
- Arizona Burn Center, Valleywise Health, Phoenix, Arizona 85008, United States
| | - Michael J MacCoss
- Arizona Burn Center, Valleywise Health, Phoenix, Arizona 85008, United States
| | - Brendan X MacLean
- Arizona Burn Center, Valleywise Health, Phoenix, Arizona 85008, United States
| | - Erin S Baker
- Department of Chemistry, North Carolina State University, Raleigh, North Carolina 27695, United States.,Comparative Medicine Institute, North Carolina State University, Raleigh, North Carolina 27695, United States
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49
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Steele-Ogus MC, Johnson RS, MacCoss MJ, Paredez AR. Identification of Actin Filament-Associated Proteins in Giardia lamblia. Microbiol Spectr 2021; 9:e0055821. [PMID: 34287056 PMCID: PMC8552679 DOI: 10.1128/spectrum.00558-21] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Accepted: 06/17/2021] [Indexed: 11/20/2022] Open
Abstract
The deep-branching protozoan parasite Giardia lamblia is the causative agent of the intestinal disease giardiasis. Consistent with its proposed evolutionary position, many pathways are minimalistic or divergent, including its actin cytoskeleton. Giardia is the only eukaryote known to lack all canonical actin-binding proteins. Previously, our lab identified a number of noncanonical Giardia lamblia actin (GlActin) interactors; however, these proteins appeared to interact only with monomeric or globular actin (G-actin) rather than with filamentous actin (F-actin). To identify F-actin interactors, we used a chemical cross-linker to preserve native interactions followed by an anti-GlActin antibody, protein A affinity chromatography, and liquid chromatography coupled to mass spectrometry. We found 46 putative actin interactors enriched under the conditions favoring F-actin. Data are available via ProteomeXchange with identifier PXD026067. None of the proteins identified contain known actin-interacting motifs, and many lacked conserved domains. Each potential interactor was then tagged with the fluorescent protein mNeonGreen and visualized in live cells. We categorized the proteins based on their primary localization; localizations included ventral disc, marginal plate, nuclei, flagella, plasma membrane, and internal membranes. One protein from each of the six categories was colocalized with GlActin using immunofluorescence microscopy. We also co-immunoprecipitated one protein from each category and confirmed three of the six potential interactions. Most of the localization patterns are consistent with previously demonstrated GlActin functions, but the ventral disc represents a new category of actin interactor localization. These results suggest a role for GlActin in ventral disc function, which has previously been controversial. IMPORTANCE Giardia lamblia is an intestinal parasite that colonizes the small intestine and causes diarrhea, which can lead to dehydration and malnutrition. Giardia actin (GlActin) has a conserved role in Giardia cells, despite being a highly divergent protein with none of the conserved regulators found in model organisms. Here, we identify and localize 46 interactors of polymerized actin. These putative interactors localize to a number of places in the cell, underlining GlActin's importance in multiple cellular processes. Surprisingly, eight of these proteins localize to the ventral disc, Giardia's host attachment organelle. Since host attachment is required for infection, proteins involved in this process are an appealing target for new drugs. While treatments for Giardia exist, drug resistance is becoming more common, resulting in a need for new treatments. Giardia and human systems are highly dissimilar, thus drugs specifically tailored to Giardia proteins would be less likely to have side effects.
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Affiliation(s)
| | - Richard S. Johnson
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
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50
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Woodall NB, Weinberg Z, Park J, Busch F, Johnson RS, Feldbauer MJ, Murphy M, Ahlrichs M, Yousif I, MacCoss MJ, Wysocki VH, El-Samad H, Baker D. De novo design of tyrosine and serine kinase-driven protein switches. Nat Struct Mol Biol 2021; 28:762-770. [PMID: 34518698 PMCID: PMC8601088 DOI: 10.1038/s41594-021-00649-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 07/26/2021] [Indexed: 02/07/2023]
Abstract
Kinases play central roles in signaling cascades, relaying information from the outside to the inside of mammalian cells. De novo designed protein switches capable of interfacing with tyrosine kinase signaling pathways would open new avenues for controlling cellular behavior, but, so far, no such systems have been described. Here we describe the de novo design of two classes of protein switch that link phosphorylation by tyrosine and serine kinases to protein-protein association. In the first class, protein-protein association is required for phosphorylation by the kinase, while in the second class, kinase activity drives protein-protein association. We design systems that couple protein binding to kinase activity on the immunoreceptor tyrosine-based activation motif central to T-cell signaling, and kinase activity to reconstitution of green fluorescent protein fluorescence from fragments and the inhibition of the protease calpain. The designed switches are reversible and function in vitro and in cells with up to 40-fold activation of switching by phosphorylation.
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Affiliation(s)
- Nicholas B Woodall
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Zara Weinberg
- Department of Biochemistry & Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - Jesslyn Park
- Department of Biochemistry & Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - Florian Busch
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, USA
- Resource for Native Mass Spectrometry Guided Structural Biology, The Ohio State University, Columbus, OH, USA
| | - Richard S Johnson
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Michael Murphy
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Maggie Ahlrichs
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Issa Yousif
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Vicki H Wysocki
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, USA
- Resource for Native Mass Spectrometry Guided Structural Biology, The Ohio State University, Columbus, OH, USA
| | - Hana El-Samad
- Department of Biochemistry & Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
- Institute for Protein Design, University of Washington, Seattle, WA, USA.
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