Acquiring and Analyzing Data Independent Acquisition Proteomics Experiments without Spectrum Libraries

Targeting glutamine metabolism improves sarcoma response to radiation therapy in vivo

Diverse tumor metabolic phenotypes are influenced by the environment and genetic lesions. Whether these phenotypes extend to rhabdomyosarcoma (RMS) and how they might be leveraged to design new therapeutic approaches remains an open question. Thus, we utilized a Pax7Cre-ER-T2/+; NrasLSL-G12D/+; p53fl/fl (P7NP) murine model of sarcoma with mutations that most frequently occur in human embryonal RMS. To study metabolism, we infuse 13C-labeled glucose or glutamine into mice with sarcomas and show that sarcomas consume more glucose and glutamine than healthy muscle tissue. However, we reveal a marked shift from glucose consumption to glutamine metabolism after radiation therapy (RT). In addition, we show that inhibiting glutamine, either through genetic deletion of glutaminase (Gls1) or through pharmacological inhibition of glutaminase, leads to significant radiosensitization in vivo. This causes a significant increase in overall survival for mice with Gls1-deficient compared to Gls1-proficient sarcomas. Finally, Gls1-deficient sarcomas post-RT elevate levels of proteins involved in natural killer cell and interferon alpha/gamma responses, suggesting a possible role of innate immunity in the radiosensitization of Gls1-deficient sarcomas. Thus, our results indicate that glutamine contributes to radiation response in a mouse model of RMS.

Glycoproteomic and proteomic analysis of Burkholderia cenocepacia reveals glycosylation events within FliF and MotB are dispensable for motility

Across the Burkholderia genus O-linked protein glycosylation is highly conserved. While the inhibition of glycosylation has been shown to be detrimental for virulence in Burkholderia cepacia complex species, such as Burkholderia cenocepacia, little is known about how specific glycosylation sites impact protein functionality. Within this study, we sought to improve our understanding of the breadth, dynamics, and requirement for glycosylation across the B. cenocepacia O-glycoproteome. Assessing the B. cenocepacia glycoproteome across different culture media using complementary glycoproteomic approaches, we increase the known glycoproteome to 141 glycoproteins. Leveraging this repertoire of glycoproteins, we quantitively assessed the glycoproteome of B. cenocepacia using Data-Independent Acquisition (DIA) revealing the B. cenocepacia glycoproteome is largely stable across conditions with most glycoproteins constitutively expressed. Examination of how the absence of glycosylation impacts the glycoproteome reveals that the protein abundance of only five glycoproteins (BCAL1086, BCAL2974, BCAL0525, BCAM0505, and BCAL0127) are altered by the loss of glycosylation. Assessing ΔfliF (ΔBCAL0525), ΔmotB (ΔBCAL0127), and ΔBCAM0505 strains, we demonstrate the loss of FliF, and to a lesser extent MotB, mirror the proteomic effects observed in the absence of glycosylation in ΔpglL. While both MotB and FliF are essential for motility, we find loss of glycosylation sites in MotB or FliF does not impact motility supporting these sites are dispensable for function. Combined this work broadens our understanding of the B. cenocepacia glycoproteome supporting that the loss of glycoproteins in the absence of glycosylation is not an indicator of the requirement for glycosylation for protein function.

IMPORTANCE

Burkholderia cenocepacia is an opportunistic pathogen of concern within the Cystic Fibrosis community. Despite a greater appreciation of the unique physiology of B. cenocepacia gained over the last 20 years a complete understanding of the proteome and especially the O-glycoproteome, is lacking. In this study, we utilize systems biology approaches to expand the known B. cenocepacia glycoproteome as well as track the dynamics of glycoproteins across growth phases, culturing media and in response to the loss of glycosylation. We show that the glycoproteome of B. cenocepacia is largely stable across conditions and that the loss of glycosylation only impacts five glycoproteins including the motility associated proteins FliF and MotB. Examination of MotB and FliF shows, while these proteins are essential for motility, glycosylation is dispensable. Combined this work supports that B. cenocepacia glycosylation can be dispensable for protein function and may influence protein properties beyond stability.

Comprehensive Prostate Fluid-Based Spectral Libraries for Enhanced Protein Detection in Urine

Biofluids contain molecules in circulation and from nearby organs that can be indicative of disease states. Characterizing the proteome of biofluids with DIA-MS is an emerging area of interest for biomarker discovery; yet, there is limited consensus on DIA-MS data analysis approaches for analyzing large numbers of biofluids. To evaluate various DIA-MS workflows, we collected urine from a clinically heterogeneous cohort of prostate cancer patients and acquired data in DDA and DIA scan modes. We then searched the DIA data against urine spectral libraries generated using common library generation approaches or a library-free method. We show that DIA-MS doubles the sample throughput compared to standard DDA-MS with minimal losses to peptide detection. We further demonstrate that using a sample-specific spectral library generated from individual urines maximizes peptide detection compared to a library-free approach, a pan-human library, or libraries generated from pooled, fractionated urines. Adding urine subproteomes, such as the urinary extracellular vesicular proteome, to the urine spectral library further improves the detection of prostate proteins in unfractionated urine. Altogether, we present an optimized DIA-MS workflow and provide several high-quality, comprehensive prostate cancer urine spectral libraries that can streamline future biomarker discovery studies of prostate cancer using DIA-MS.

NCI Cancer Research Data Commons: Resources to Share Key Cancer Data

Since 2014, the NCI has launched a series of data commons as part of the Cancer Research Data Commons (CRDC) ecosystem housing genomic, proteomic, imaging, and clinical data to support cancer research and promote data sharing of NCI-funded studies. This review describes each data commons (Genomic Data Commons, Proteomic Data Commons, Integrated Canine Data Commons, Cancer Data Service, Imaging Data Commons, and Clinical and Translational Data Commons), including their unique and shared features, accomplishments, and challenges. Also discussed is how the CRDC data commons implement Findable, Accessible, Interoperable, Reusable (FAIR) principles and promote data sharing in support of the new NIH Data Management and Sharing Policy. See related articles by Brady et al., p. 1384, Pot et al., p. 1396, and Kim et al., p. 1404.

Removal of Exogenous Stimuli Reveals a Canalization of Circadian Physiology in a Vertically Migrating Copepod

Diel rhythms are observed across taxa and are important for maintaining synchrony between the environment and organismal physiology. A striking example of this is the diel vertical migration undertaken by zooplankton, some of which, such as the 5 mm-long copepod Pleuromamma xiphias (P. xiphias), migrate hundreds of meters daily between the surface ocean and deeper waters. Some of the molecular pathways that underlie the expressed phenotype at different stages of this migration are entrained by environmental variables (e.g., day length and food availability), while others are regulated by internal clocks. We identified a series of proteomic biomarkers that vary across ocean DVM and applied them to copepods incubated in 24 h of darkness to assess circadian control. The dark-incubated copepods shared some proteomic similarities to the ocean-caught copepods (i.e., increased abundance of carbohydrate metabolism proteins at night). Shipboard-incubated copepods demonstrated a clearer distinction between night and day proteomic profiles, and more proteins were differentially abundant than in the in situ copepods, even in the absence of the photoperiod and other environmental cues. This pattern suggests that there is a canalization of rhythmic diel physiology in P. xiphias that reflects likely circadian clock control over diverse molecular pathways.

Interactome dynamics during heat stress signal transmission and reception

Among evolved molecular mechanisms, cellular stress response to altered environmental conditions to promote survival is among the most fundamental. The presence of stress-induced unfolded or misfolded proteins and molecular registration of these events constitute early steps in cellular stress response. However, what stress-induced changes in protein conformations and protein-protein interactions within cells initiate stress response and how these features are recognized by cellular systems are questions that have remained difficult to answer, requiring new approaches. Quantitative in vivo chemical cross-linking coupled with mass spectrometry (qXL-MS) is an emerging technology that provides new insight on protein conformations, protein-protein interactions and how the interactome changes during perturbation within cells, organelles, and even tissues. In this work, qXL-MS and quantitative proteome analyses were applied to identify significant time-dependent interactome changes that occur prior to large-scale proteome abundance remodeling within cells subjected to heat stress. Interactome changes were identified within minutes of applied heat stress, including stress-induced changes in chaperone systems as expected due to altered functional demand. However, global analysis of all interactome changes revealed the largest significant enrichment in the gene ontology molecular function term of RNA binding. This group included more than 100 proteins among multiple components of protein synthesis machinery, including mRNA binding, spliceosomes, and ribosomes. These interactome data provide new conformational insight on the complex relationship that exists between transcription, translation and cellular stress response mechanisms. Moreover, stress-dependent interactome changes suggest that in addition to conformational stabilization of RNA-binding proteins, adaptation of RNA as interacting ligands offers an additional fitness benefit resultant from generally lower RNA thermal stability. As such, RNA ligands also serve as fundamental temperature sensors that signal stress through decreased conformational regulation of their protein partners as was observed in these interactome dynamics.

High-Throughput Acoustic Ejection Mass Spectrometry with Adjustable Signal Durations

High-throughput mass spectrometry (MS) has witnessed rapid advancements and has found extensive applications across various disciplines. It enables the fast and accurate analysis of large sample sets, delivering a 10-fold or greater enhancement in analytical throughput when compared to conventional LC-MS methods. However, the signal duration in these high-throughput MS technologies is typically confined to a narrow range, presenting challenges for workflows demanding prolonged signal durations. In this study, we introduce a method that enables precise modulation of the signal duration on an acoustic ejection mass spectrometry (AEMS) system while ensuring high signal reproducibility. This flexibility allows for simultaneous and precise analysis of a significantly greater number of MS/MS transitions in high-throughput MS environments. Additionally, it offers a unique approach for parameter optimization and method development with minimal sample volume requirements. This advancement enhances the efficiency of MS-based analyses across diverse applications and facilitates broader utilization of MS technologies in high-throughput settings, including data-dependent acquisition (DDA) and data-independent acquisition (DIA).

Comprehensive insights into the impact of bacterial indole-3-acetic acid on sensory preferences in Drosophila melanogaster

Several bacteria of environmental and clinical origins, including some human-associated strains secrete a cross-kingdom signaling molecule indole-3-acetic acid (IAA). IAA is a tryptophan (trp) derivative mainly known for regulating plant growth and development as a hormone. However, the nutritional sources that boost IAA secretion in bacteria and the impact of secreted IAA on non-plant eukaryotic hosts remained less explored. Here, we demonstrate significant trp-dependent IAA production in Pseudomonas juntendi NEEL19 when provided with ethanol as a carbon source in liquid cultures. IAA was further characterized to modulate the odor discrimination, motility and survivability in Drosophila melanogaster. A detailed analysis of IAA-fed fly brain proteome using high-resolution mass spectrometry showed significant (fold change, ± 2; p ≤ 0.05) alteration in the proteins governing neuromuscular features, audio-visual perception and energy metabolism as compared to IAA-unfed controls. Sex-wise variations in differentially regulated proteins were witnessed despite having similar visible changes in chemo perception and psychomotor responses in IAA-fed flies. This study not only revealed ethanol-specific enhancement in trp-dependent IAA production in P. juntendi, but also showed marked behavioral alterations in flies for which variations in an array of proteins governing odor discrimination, psychomotor responses, and energy metabolism are held responsible. Our study provided novel insights into disruptive attributes of bacterial IAA that can potentially influence the eukaryotic gut-brain axis having broad environmental and clinical implications.

Mag-Net: Rapid enrichment of membrane-bound particles enables high coverage quantitative analysis of the plasma proteome

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.

A critical evaluation of ultrasensitive single-cell proteomics strategies

Success of mass spectrometry characterization of the proteome of single cells allows us to gain a greater understanding than afforded by transcriptomics alone but requires clear understanding of the tradeoffs between analytical throughput and precision. Recent advances in mass spectrometry acquisition techniques, including updated instrumentation and sample preparation, have improved the quality of peptide signals obtained from single cell data. However, much of the proteome remains uncharacterized, and higher throughput techniques often come at the expense of reduced sensitivity and coverage, which diminish the ability to measure proteoform heterogeneity, including splice variants and post-translational modifications, in single cell data analysis. Here, we assess the growing body of ultrasensitive single-cell approaches and their tradeoffs as researchers try to balance throughput and precision in their experiments.

Computational approaches to identify sites of phosphorylation

Due to their oftentimes ambiguous nature, phosphopeptide positional isomers can present challenges in bottom-up mass spectrometry-based workflows as search engine scores alone are often not enough to confidently distinguish them. Additional scoring algorithms can remedy this by providing confidence metrics in addition to these search results, reducing ambiguity. Here we describe challenges to interpreting phosphoproteomics data and review several different approaches to determine sites of phosphorylation for both data-dependent and data-independent acquisition-based workflows. Finally, we discuss open questions regarding neutral losses, gas-phase rearrangement, and false localization rate estimation experienced by both types of acquisition workflows and best practices for managing ambiguity in phosphosite determination.

Global Release of Translational Repression Across Plasmodium's Host-to-Vector Transmission Event

Malaria parasites must be able to respond quickly to changes in their environment, including during their transmission between mammalian hosts and mosquito vectors. Therefore, before transmission, female gametocytes proactively produce and translationally repress mRNAs that encode essential proteins that the zygote requires to establish a new infection. This essential regulatory control requires the orthologues of DDX6 (DOZI), LSM14a (CITH), and ALBA proteins to form a translationally repressive complex in female gametocytes that associates with many of the affected mRNAs. However, while the release of translational repression of individual mRNAs has been documented, the details of the global release of translational repression have not. Moreover, the changes in spatial arrangement and composition of the DOZI/CITH/ALBA complex that contribute to translational control are also not known. Therefore, we have conducted the first quantitative, comparative transcriptomics and DIA-MS proteomics of Plasmodium parasites across the host-to-vector transmission event to document the global release of translational repression. Using female gametocytes and zygotes of P. yoelii, we found that nearly 200 transcripts are released for translation soon after fertilization, including those with essential functions for the zygote. However, we also observed that some transcripts remain repressed beyond this point. In addition, we have used TurboID-based proximity proteomics to interrogate the spatial and compositional changes in the DOZI/CITH/ALBA complex across this transmission event. Consistent with recent models of translational control, proteins that associate with either the 5' or 3' end of mRNAs are in close proximity to one another during translational repression in female gametocytes and then dissociate upon release of repression in zygotes. This observation is cross-validated for several protein colocalizations in female gametocytes via ultrastructure expansion microscopy and structured illumination microscopy. Moreover, DOZI exchanges its interaction from NOT1-G in female gametocytes to the canonical NOT1 in zygotes, providing a model for a trigger for the release of mRNAs from DOZI. Finally, unenriched phosphoproteomics revealed the modification of key translational control proteins in the zygote. Together, these data provide a model for the essential translational control mechanisms used by malaria parasites to promote their efficient transmission from their mammalian host to their mosquito vector.

DIA-Based Quantitative Proteomics in the Flower Buds of Two Malus sieversii (Ledeb.) M. Roem Subtypes at Different Overwintering Stages

Malus sieversii is considered the ancestor of the modern cultivated apple, with a high value for apple tolerance breeding. Despite studies on the temperature adaptability of M. sieversii carried out at a physiological response and the genome level, information on the proteome changes of M. sieversii during dormancy is limited, especially about the M. sieversii subtypes. In this study, a DIA-based approach was employed to screen and identify differential proteins involved in three overwintering periods of flower buds in two M. sieversii subtypes (Malus sieversii f. luteolus, GL; Malus sieversii f. aromaticus, HC) with different overwintering adaptabilities. The proteomic analysis revealed that the number of the down-regulated differential expression proteins (DEPs) was obviously higher than that of the up-regulated DEPs in the HC vs. GL groups, especially at the dormancy stage and dormancy-release stage. Through functional classification of those DEPs, the majority of the DEPs in the HC vs. GL groups were associated with protein processing in the endoplasmic reticulum, oxidative phosphorylation, starch and sucrose metabolism and ribosomes. Through WGCNA analysis, tricarboxylic acid cycle and pyruvate metabolism were highly correlated with the overwintering stages; oxidative phosphorylation and starch and sucrose metabolism were highly correlated with the Malus sieversii subtypes. This result suggests that the down-regulation of DEPs, which are predominantly enriched in these pathways, could potentially contribute to the lower cold tolerance observed in HC during overwintering stage.

Nontargeted Plasma Proteomic Analysis of Renal Disease and Pulmonary Hypertension in Patients with Sickle Cell Disease

Sickle cell disease (SCD) is characterized by red blood cell sickling, vaso-occlusion, hemolytic anemia, damage to multiple organ systems, and, as a result, shortened life expectancy. Sickle cell disease nephropathy (SCDN) and pulmonary hypertension (pHTN) are common and frequently co-occurring complications of SCD; both are associated with markedly accelerated mortality. To identify candidate circulating biomarkers of SCDN and pHTN, we used mass spectrometry to quantify the relative abundance of >1000 proteins in plasma samples from 189 adults with SCD from the Outcome Modifying Genes in SCD (OMG-SCD) cohort (ProteomeXchange identifier PXD048716). Forty-four proteins were differentially abundant in SCDN, most significantly cystatin-C and collagen α-1(XVIII) chain (COIA1), and 55 proteins were dysregulated in patients with SCDN and pHTN, most significantly insulin-like growth factor-binding protein 6 (IBP6). Network analysis identified a module of 133 coregulated proteins significantly associated with SCDN, that was enriched for extracellular matrix proteins, insulin-like growth factor binding proteins, cell adhesion proteins, EGF-like calcium binding proteins, and several cadherin family members. Collectively, these data provide a comprehensive understanding of plasma protein changes in SCDN and pHTN which validate numerous studies of chronic kidney disease and suggest shared profiles of protein disruption in kidney dysfunction and pHTN among SCD patients.

Robust, Precise, and Deep Proteome Profiling Using a Small Mass Range and Narrow Window Data-Independent-Acquisition Scheme

In recent years, a plethora of different data-independent acquisition methods have been developed for proteomics to cover a wide range of requirements. Current deep proteome profiling methods rely on fractionations, elaborate chromatography, and mass spectrometry setups or display suboptimal quantitative precision. We set out to develop an easy-to-use one shot DIA method that achieves high quantitative precision and high proteome coverage. We achieve this by focusing on a small mass range of 430-670 m/z using small isolation windows without overlap. With this new method, we were able to quantify >9200 protein groups in HEK lysates with an average coefficient of variance of 3.2%. To demonstrate the power of our newly developed narrow mass range method, we applied it to investigate the effect of PGC-1α knockout on the skeletal muscle proteome in mice. Compared to a standard data-dependent acquisition method, we could double proteome coverage and, most importantly, achieve a significantly higher quantitative precision, as compared to a previously proposed DIA method. We believe that our method will be especially helpful in quantifying low abundant proteins in samples with a high dynamic range. All raw and result files are available at massive.ucsd.edu (MSV000092186).

Combining FAIMS based glycoproteomics and DIA proteomics reveals widespread proteome alterations in response to glycosylation occupancy changes in Neisseria gonorrhoeae

Protein glycosylation is increasingly recognized as a common protein modification across bacterial species. Within the Neisseria genus O-linked protein glycosylation is conserved yet closely related Neisseria species express O-oligosaccharyltransferases (PglOs) with distinct targeting activities. Within this work, we explore the targeting capacity of different PglOs using Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) fractionation and Data-Independent Acquisition (DIA) to allow the characterization of the impact of changes in glycosylation on the proteome of Neisseria gonorrhoeae. We demonstrate FAIMS expands the known glycoproteome of wild type N. gonorrhoeae MS11 and enables differences in glycosylation to be assessed across strains expressing different pglO allelic chimeras with unique substrate targeting activities. Combining glycoproteomic insights with DIA proteomics, we demonstrate that alterations within pglO alleles have widespread impacts on the proteome of N. gonorrhoeae. Examination of peptides known to be targeted by glycosylation using DIA analysis supports alterations in glycosylation occupancy occurs independently of changes in protein levels and that the occupancy of glycosylation is generally low on most glycoproteins. This work thus expands our understanding of the N. gonorrhoeae glycoproteome and the roles that pglO allelic variation may play in governing genus-level protein glycosylation.

Multispecies Benchmark Analysis for LC-MS/MS Validation and Performance Evaluation in Bottom-Up Proteomics

We present an instrument-independent benchmark procedure and software (LFQ_bout) for the validation and comparative evaluation of the performance of LC-MS/MS and data processing workflows in bottom-up proteomics. The procedure enables a back-to-back comparison of common and emerging workflows, e.g., diaPASEF or ScanningSWATH, and evaluates the impact of arbitrary and inadequately documented settings or black-box data processing algorithms. It enhances the overall performance and quantification accuracy by recognizing and reporting common quantification errors.

Full Mass Range ΦSDM Orbitrap Mass Spectrometry for DIA Proteome Analysis

Optimizing data-independent acquisition methods for proteomics applications often requires balancing spectral resolution and acquisition speed. Here, we describe a real-time full mass range implementation of the phase-constrained spectrum deconvolution method (ΦSDM) for Orbitrap mass spectrometry that increases mass resolving power without increasing scan time. Comparing its performance to the standard enhanced Fourier transformation signal processing revealed that the increased resolving power of ΦSDM is beneficial in areas of high peptide density and comes with a greater ability to resolve low-abundance signals. In a standard 2 h analysis of a 200 ng HeLa digest, this resulted in an increase of 16% in the number of quantified peptides. As the acquisition speed becomes even more important when using fast chromatographic gradients, we further applied ΦSDM methods to a range of shorter gradient lengths (21, 12, and 5 min). While ΦSDM improved identification rates and spectral quality in all tested gradients, it proved particularly advantageous for the 5 min gradient. Here, the number of identified protein groups and peptides increased by >15% in comparison to enhanced Fourier transformation processing. In conclusion, ΦSDM is an alternative signal processing algorithm for processing Orbitrap data that can improve spectral quality and benefit quantitative accuracy in typical proteomics experiments, especially when using short gradients.

Acquisition and Analysis of DIA-Based Proteomic Data: A Comprehensive Survey in 2023

Data-independent acquisition (DIA) mass spectrometry (MS) has emerged as a powerful technology for high-throughput, accurate, and reproducible quantitative proteomics. This review provides a comprehensive overview of recent advances in both the experimental and computational methods for DIA proteomics, from data acquisition schemes to analysis strategies and software tools. DIA acquisition schemes are categorized based on the design of precursor isolation windows, highlighting wide-window, overlapping-window, narrow-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation-enhanced DIA methods. For DIA data analysis, major strategies are classified into spectrum reconstruction, sequence-based search, library-based search, de novo sequencing, and sequencing-independent approaches. A wide array of software tools implementing these strategies are reviewed, with details on their overall workflows and scoring approaches at different steps. The generation and optimization of spectral libraries, which are critical resources for DIA analysis, are also discussed. Publicly available benchmark datasets covering global proteomics and phosphoproteomics are summarized to facilitate performance evaluation of various software tools and analysis workflows. Continued advances and synergistic developments of versatile components in DIA workflows are expected to further enhance the power of DIA-based proteomics.

Hippocampus Glutathione S Reductase Potentially Confers Genetic Resilience to Cognitive Decline in the AD-BXD Mouse Population

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.

In-Depth Proteome Profiling of Small Extracellular Vesicles Isolated from Cancer Cell Lines and Patient Serum

Extracellular vesicle (EV) secretion has been observed in many types of both normal and tumor cells. EVs contain a variety of distinctive cargoes, allowing tumor-derived serum proteins in EVs to act as a minimally invasive method for clinical monitoring. We have undertaken a comprehensive study of the protein content of the EVs from several cancer cell lines using direct data-independent analysis. Several thousand proteins were detected, including many classic EV markers such as CD9, CD81, CD63, TSG101, and Syndecan-1, among others. We detected many distinctive cancer-specific proteins, including several known markers used in cancer detection and monitoring. We further studied the protein content of EVs from patient serum for both normal controls and pancreatic cancer and hepatocellular carcinoma. The EVs for these studies have been isolated by various methods for comparison, including ultracentrifugation and CD9 immunoaffinity column. Typically, 500-1000 proteins were identified, where most of them overlapped with the EV proteins identified from the cell lines studied. We were able to identify many of the cell-line EV protein markers in the serum EVs, in addition to the large numbers of proteins specific to pancreatic and HCC cancers.

Exploring immunoregulatory properties of a phenolic-enriched maple syrup extract through integrated proteomics and in vitro assays

Our laboratory has established a comprehensive program to investigate the phytochemical composition and nutritional/medicinal properties of phenolic-enriched maple syrup extract (MSX). Previous studies support MSX's therapeutic potential in diverse disease models, primarily through its anti-inflammatory effects. We recently demonstrated MSX's ability to regulate inflammatory signaling pathways and modulate inflammatory markers and proteins in a lipopolysaccharide (LPS)-induced peritonitis mouse model. However, MSX's immunoregulatory properties remain unknown. Herein, we investigated MSX's immunoregulatory properties for the first time using an integrated approach, combining data-dependent acquisition (DDA) and data-independent acquisition (DIA) strategies in a proteomic analysis of spleen tissue collected from the aforementioned peritonitis mouse model. Additionally, we conducted immune cell activation assays using macrophages and T lymphocytes. The DIA analysis unveiled a distinctive expression pattern involving three proteins-Krt83, Thoc2, and Vps16-which were present in both the control and MSX-treated groups but absent in the LPS-induced model group. Furthermore, proteins Ppih and Dpp9 exhibited significant reductions in the MSX-treated group. Ingenuity pathway analysis indicated that MSX may modulate several critical signaling pathways, exerting a suppressive effect on immune responses in various cell types involved in both innate and adaptive immunity. Our in vitro cell assays supported findings from the proteomics, revealing that MSX significantly reduced the levels of interleukin-1 beta (IL-1β) and tumor necrosis factor-alpha (TNF-α) in LPS-stimulated human macrophage cells, as well as the levels of IL-2 in anti-CD3/anti-CD28-induced Jurkat T cells. Taken together, our investigations provide evidence that MSX exerts immune regulatory effects that impact both innate and adaptive immunity, which adds to the data supporting MSX's development as a functional food.

Comparative proteomics analysis of kidney in chicken infected by infectious bronchitis virus

The gamma coronavirus infectious bronchitis virus (IBV) is known to cause an acute and highly contagious infectious disease in poultry. Here, this study aimed to investigate the impact of virulent or avirulent IBV infection on the avian host by conducting proteomics with data-independent acquisition mass spectrometry (DIA-MS) in the kidneys of IBV-infected chickens. The results revealed 267, 489, and 510 differentially expressed proteins (DEPs) in the chicken kidneys at 3, 5, and 7 days postinfection (dpi), respectively, when infected with the GD17/04 strain, which is a highly nephrogenic strain and belongs to the 4/91 genotype. In contrast, the attenuated 4/91 vaccine resulted in the identification of 144, 175, and 258 DEPs at 3, 5, and 7 dpi, respectively. Functional enrichment analyses indicated distinct expression profiles between the 2 IBV strains. Upon GD17/04 infection, metabolic pathways respond initially in the early stage (3 dpi) and immune-related signaling pathways respond in the middle and late stages (5 and 7 dpi). The 4/91 vaccine elicited a completely opposite response compared to the GD17/04 infection. Among all DEPs, 62 immune-related DEPs were focused on and found to be mainly enriched in the type I interferon (IFN-I) signaling pathway and involved in humoral and cellular immunity. Notably, key molecules in the IFN-I signaling pathway including MDA5, LGP2, and TBK1 may serve as regulatory targets of IBV. Overall, this study highlights similarities and discrepancies in the patterns of protein expression at different stages of infection with virulent and avirulent IBV strains, with the IFN-I signaling pathway emerging as a critical response to IBV infection.

Design of experiments approach for systematic optimization of a single-shot diaPASEF plasma proteomics workflow applicable for high-throughput

PURPOSE

Plasma is an abundant source of protein biomarkers. Mass spectrometry (MS) is an effective means to measure a large number of proteins in a single run. The recent development of data-independent acquisition with parallel accumulation and serial fragmentation (diaPASEF) on a trapped ion mobility spectrometer (TIMS) affords deep proteomic coverage with short liquid chromatography gradients. In this work, we utilized a process optimization approach, design of experiments (DoE), to maximize precursor identification for a plasma proteomic diaPASEF workflow.

EXPERIMENTAL DESIGN

A partial factorial design was used to screen 11 sample preparation factors and six diaPASEF MS acquisition factors. Selected factors were optimized using the response surface method.

RESULTS

Three important sample preparation factors and the two important MS acquisition factors were identified in the screening experiments and were selected for separate optimization experiments. The optimal parameters were compared to our standard plasma proteomics workflows using either a 1-h or overnight trypsin digestion. The optimized method outperformed the 1-h digestion, and it was similar in performance to the overnight digestion, however, the optimized method could be completed in a day.

CONCLUSION AND CLINICAL RELEVANCE

We have used DoE to report an optimized plasma proteomics workflow for diaPASEF, however, established methods are already highly optimized, and resources may be better spent on running samples than comprehensive optimization.

An Updated Guide to the Identification, Quantitation, and Imaging of the Crustacean Neuropeptidome

Crustaceans serve as a useful, simplified model for studying peptides and neuromodulation, as they contain numerous neuropeptide homologs to mammals and enable electrophysiological studies at the single-cell and neural circuit levels. Crustaceans contain well-defined neural networks, including the stomatogastric ganglion, oesophageal ganglion, commissural ganglia, and several neuropeptide-rich organs such as the brain, pericardial organs, and sinus glands. As existing mass spectrometry (MS) methods are not readily amenable to neuropeptide studies, there is a great need for optimized sample preparation, data acquisition, and data analysis methods. Herein, we present a general workflow and detailed methods for MS-based neuropeptidomic analysis of crustacean tissue samples and circulating fluids. In conjunction with profiling, quantitation can also be performed with isotopic or isobaric labeling. Information regarding the localization patterns and changes of peptides can be studied via mass spectrometry imaging. Combining these sample preparation strategies and MS analytical techniques allows for a multi-faceted approach to obtaining deep knowledge of crustacean peptidergic signaling pathways.

Unraveling the mechanism of centromere inactivation in human aging

Aging involves a range of genetic, epigenetic, and physiological alterations. A key characteristic of aged cells is the loss of global heterochromatin, accompanied by a reduction in canonical histone levels. In this study, we track the fate of centromeres during aging in human cells. Our findings reveal that the centromeric histone H3 variant CENP-A is downregulated in aged cells, in a p53-dependent manner. We observe repression of centromeric noncoding transcription through an epigenetic mechanism via recruitment of a lysine-specific demethylase 1 (LSD1/KDM1A) to centromeres. This suppression results in defective de novo CENP-A loading at aging centromeres. By dual inhibition of p53 and LSD1/KDM1A in aged cells, we mitigate the reduction in centromeric proteins and centromeric transcripts, leading to mitotic rejuvenation of these cells. These results offer insights into a novel mechanism for centromeric inactivation during aging and provide potential strategies to reactivate centromeres.

Recent advances in mass spectrometry-based methods to investigate reversible cysteine oxidation

The post-translational modification of cysteine to diverse oxidative states is understood as a critical cellular mechanism to combat oxidative stress. To study the role of cysteine oxidation, cysteine enrichments and subsequent analysis via mass spectrometry are necessary. As such, technologies and methods are rapidly developing for sensitive and efficient enrichments of cysteines to further explore its role in signaling pathways. In this review, we analyze recent developments in methods to miniaturize cysteine enrichments, analyze the underexplored disulfide bound redoxome, and quantify site-specific cysteine oxidation. We predict that further development of these methods will improve cysteine coverage across more diverse organisms than those previously studied and elicit novel roles cysteines play in stress response.

Q-RAI data-independent acquisition for lipidomic quantitative profiling

Untargeted lipidomics has been increasingly adopted for hypothesis generation in a biological context or discovery of disease biomarkers. Most of the current liquid chromatography mass spectrometry (LC-MS) based untargeted methodologies utilize a data dependent acquisition (DDA) approach in pooled samples for identification and MS-only acquisition for semi-quantification in individual samples. In this study, we present for the first time an untargeted lipidomic workflow that makes use of the newly implemented Quadrupole Resolved All-Ions (Q-RAI) acquisition function on the Agilent 6546 quadrupole time-of-flight (Q-TOF) mass spectrometer to acquire MS2 spectra in data independent acquisition (DIA) mode. This is followed by data processing and analysis on MetaboKit, a software enabling DDA-based spectral library construction and extraction of MS1 and MS2 peak areas, for reproducible identification and quantification of lipids in DIA analysis. This workflow was tested on lipid extracts from human plasma and showed quantification at MS1 and MS2 levels comparable to multiple reaction monitoring (MRM) targeted analysis of the same samples. Analysis of serum from Ceramide Synthase 2 (CerS2) null mice using the Q-RAI DIA workflow identified 88 lipid species significantly different between CerS2 null and wild type mice, including well-characterized changes previously associated with this phenotype. Our results show the Q-RAI DIA as a reliable option to perform simultaneous identification and reproducible relative quantification of lipids in exploratory biological studies.

The regulatory landscape of the yeast phosphoproteome

The cellular ability to react to environmental fluctuations depends on signaling networks that are controlled by the dynamic activities of kinases and phosphatases. Here, to gain insight into these stress-responsive phosphorylation networks, we generated a quantitative mass spectrometry-based atlas of early phosphoproteomic responses in Saccharomyces cerevisiae exposed to 101 environmental and chemical perturbations. We report phosphosites on 59% of the yeast proteome, with 18% of the proteome harboring a phosphosite that is regulated within 5 min of stress exposure. We identify shared and perturbation-specific stress response programs, uncover loss of phosphorylation as an integral early event, and dissect the interconnected regulatory landscape of kinase-substrate networks, as we exemplify with target of rapamycin signaling. We further reveal functional organization principles of the stress-responsive phosphoproteome based on phosphorylation site motifs, kinase activities, subcellular localizations, shared functions and pathway intersections. This information-rich map of 25,000 regulated phosphosites advances our understanding of signaling networks.

An Optimized and High-Throughput Method for Histone Propionylation and Data-Independent Acquisition Analysis for the Identification and Quantification of Histone Post-translational Modifications

Histones are DNA binding proteins that allow for packaging of the DNA into the nucleus. They are abundantly present across the genome and thus serve as a major site of epigenetic regulation through the use of post-translational modifications (PTMs). Aberrations in histone expression and modifications have been implicated in a variety of human diseases and thus are a major focus of disease etiology studies. A well-established method for studying histones and PTMs is through the chemical derivatization of isolated histones followed by liquid chromatography and mass spectrometry analysis. Using such an approach has allowed for a swath of discoveries to be found, leading to novel therapeutics such as histone deacetylase (HDAC) inhibitors that have already been applied in the clinic. However, with the rapid improvement in instrumentation and data analysis pipelines, it remains important to temporally re-evaluate the established protocols to improve throughput and ensure data quality. Here, we optimized the histone derivatization procedure to increase sample throughput without compromising peptide quantification. An implemented spike-in standard peptide further serves as a quality control to evaluate the propionylation and digestion efficiencies as well as reproducibility in chromatographic retention and separation. Last, the application of various data-independent acquisition (DIA) strategies was explored to ensure low variation between runs. The output of this study is a newly optimized derivatization protocol and mass spectrometry method that maintains high identification and quantification of histone PTMs while increasing sample throughput.

A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline

Here, we present a standardized, "off-the-shelf" proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high throughput and scalability. This integrated pipeline streamlines a fully automated sample preparation platform, a data-independent acquisition (DIA) coupled with high-field asymmetric waveform ion mobility spectrometer (FAIMS) interface, and an optimized library-free DIA database search strategy. Our systematic evaluation of FAIMS-DIA showing single compensation voltage (CV) at -35 V not only yields the deepest proteome coverage but also best correlates with DIA without FAIMS. Our in-depth comparison of direct-DIA database search engines shows that Spectronaut outperforms others, providing the highest quantifiable proteins. Next, we apply three common DIA strategies in characterizing human induced pluripotent stem cell (iPSC)-derived neurons and show single-shot mass spectrometry (MS) using single-CV (-35 V)-FAIMS-DIA results in >9,000 quantifiable proteins with <10% missing values, as well as superior reproducibility and accuracy compared with other existing DIA methods.

Elucidating the cellular determinants of targeted membrane protein degradation by lysosome-targeting chimeras

Targeted protein degradation can provide advantages over inhibition approaches in the development of therapeutic strategies. Lysosome-targeting chimeras (LYTACs) harness receptors, such as the cation-independent mannose 6-phosphate receptor (CI-M6PR), to direct extracellular proteins to lysosomes. In this work, we used a genome-wide CRISPR knockout approach to identify modulators of LYTAC-mediated membrane protein degradation in human cells. We found that disrupting retromer genes improved target degradation by reducing LYTAC recycling to the plasma membrane. Neddylated cullin-3 facilitated LYTAC-complex lysosomal maturation and was a predictive marker for LYTAC efficacy. A substantial fraction of cell surface CI-M6PR remains occupied by endogenous M6P-modified glycoproteins. Thus, inhibition of M6P biosynthesis increased the internalization of LYTAC-target complexes. Our findings inform design strategies for next-generation LYTACs and elucidate aspects of cell surface receptor occupancy and trafficking.

The fitness cost of spurious phosphorylation

The fidelity of signal transduction requires the binding of regulatory molecules to their cognate targets. However, the crowded cell interior risks off-target interactions between proteins that are functionally unrelated. How such off-target interactions impact fitness is not generally known, but quantifying this is required to understand the constraints faced by cell systems as they evolve. Here, we use the model organism S. cerevisiae to inducibly express tyrosine kinases. Because yeast lacks bona fide tyrosine kinases, most of the resulting tyrosine phosphorylation is spurious. This provides a suitable system to measure the impact of artificial protein interactions on fitness. We engineered 44 yeast strains each expressing a tyrosine kinase, and quantitatively analysed their phosphoproteomes. This analysis resulted in ~30,000 phosphosites mapping to ~3,500 proteins. Examination of the fitness costs in each strain revealed a strong correlation between the number of spurious pY sites and decreased growth. Moreover, the analysis of pY effects on protein structure and on protein function revealed over 1000 pY events that we predict to be deleterious. However, we also find that a large number of the spurious pY sites have a negligible effect on fitness, possibly because of their low stoichiometry. This result is consistent with our evolutionary analyses demonstrating a lack of phosphotyrosine counter-selection in species with bona fide tyrosine kinases. Taken together, our results suggest that, alongside the risk for toxicity, the cell can tolerate a large degree of non-functional crosstalk as interaction networks evolve.

Advances in proteomics: characterization of the innate immune system after birth and during inflammation

Proteomics is the characterization of the protein composition, the proteome, of a biological sample. It involves the large-scale identification and quantification of proteins, peptides, and post-translational modifications. This review focuses on recent developments in mass spectrometry-based proteomics and provides an overview of available methods for sample preparation to study the innate immune system. Recent advancements in the proteomics workflows, including sample preparation, have significantly improved the sensitivity and proteome coverage of biological samples including the technically difficult blood plasma. Proteomics is often applied in immunology and has been used to characterize the levels of innate immune system components after perturbations such as birth or during chronic inflammatory diseases like rheumatoid arthritis (RA) and inflammatory bowel disease (IBD). In cancers, the tumor microenvironment may generate chronic inflammation and release cytokines to the circulation. In these situations, the innate immune system undergoes profound and long-lasting changes, the large-scale characterization of which may increase our biological understanding and help identify components with translational potential for guiding diagnosis and treatment decisions. With the ongoing technical development, proteomics will likely continue to provide increasing insights into complex biological processes and their implications for health and disease. Integrating proteomics with other omics data and utilizing multi-omics approaches have been demonstrated to give additional valuable insights into biological systems.

Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data-Independent Acquisition

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.

Rapid and in-depth proteomic profiling of small extracellular vesicles for ultralow samples

The integration of robust single-pot, solid-phase-enhanced sample preparation with powerful liquid chromatography-tandem mass spectrometry (LC-MS/MS) is routinely used to define the extracellular vesicle (EV) proteome landscape and underlying biology. However, EV proteome studies are often limited by sample availability, requiring upscaling cell cultures or larger volumes of biofluids to generate sufficient materials. Here, we have refined data independent acquisition (DIA)-based MS analysis of EV proteome by optimizing both protein enzymatic digestion and chromatography gradient length (ranging from 15 to 44 min). Our short 15 min gradient length can reproducibly quantify 1168 (from as little as 500 pg of EV peptides) to 3882 proteins groups (from 50 ng peptides), including robust quantification of 22 core EV marker proteins. Compared to data-dependent acquisition, DIA achieved significantly greater EV proteome coverage and quantification of low abundant protein species. Moreover, we have achieved optimal magnetic bead-based sample preparation tailored to low quantities of EVs (0.5 to 1 µg protein) to obtain sufficient peptides for MS quantification of 1908-2340 protein groups. We demonstrate the power and robustness of our pipeline in obtaining sufficient EV proteomes granularity of different cell sources to ascertain known EV biology. This underscores the capacity of our optimised workflow to capture precise and comprehensive proteome of EVs, especially from ultra-low sample quantities (sub-nanogram), an important challenge in the field where obtaining in-depth proteome information is essential.

Translating Senotherapeutic Interventions into the Clinic with Emerging Proteomic Technologies

Cellular senescence is a state of irreversible growth arrest with profound phenotypic changes, including the senescence-associated secretory phenotype (SASP). Senescent cell accumulation contributes to aging and many pathologies including chronic inflammation, type 2 diabetes, cancer, and neurodegeneration. Targeted removal of senescent cells in preclinical models promotes health and longevity, suggesting that the selective elimination of senescent cells is a promising therapeutic approach for mitigating a myriad of age-related pathologies in humans. However, moving senescence-targeting drugs (senotherapeutics) into the clinic will require therapeutic targets and biomarkers, fueled by an improved understanding of the complex and dynamic biology of senescent cell populations and their molecular profiles, as well as the mechanisms underlying the emergence and maintenance of senescence cells and the SASP. Advances in mass spectrometry-based proteomic technologies and workflows have the potential to address these needs. Here, we review the state of translational senescence research and how proteomic approaches have added to our knowledge of senescence biology to date. Further, we lay out a roadmap from fundamental biological discovery to the clinical translation of senotherapeutic approaches through the development and application of emerging proteomic technologies, including targeted and untargeted proteomic approaches, bottom-up and top-down methods, stability proteomics, and surfaceomics. These technologies are integral for probing the cellular composition and dynamics of senescent cells and, ultimately, the development of senotype-specific biomarkers and senotherapeutics (senolytics and senomorphics). This review aims to highlight emerging areas and applications of proteomics that will aid in exploring new senescent cell biology and the future translation of senotherapeutics.

A Multipathway Phosphopeptide Standard for Rapid Phosphoproteomics Assay Development

Recent advances in methodology have made phosphopeptide analysis a tractable problem for many proteomics researchers. There are now a wide variety of robust and accessible enrichment strategies to generate phosphoproteomes while free or inexpensive software tools for quantitation and site localization have simplified phosphoproteome analysis workflow tremendously. As a research group under the Association for Biomolecular Resource Facilities umbrella, the Proteomics Standards Research Group has worked to develop a multipathway phosphopeptide standard based on a mixture of heavy-labeled phosphopeptides designed to enable researchers to rapidly develop assays. This mixture contains 131 mass spectrometry vetted phosphopeptides specifically chosen to cover as many known biologically interesting phosphosites as possible from seven different signaling networks: AMPK signaling, death and apoptosis signaling, ErbB signaling, insulin/insulin-like growth factor-1 signaling, mTOR signaling, PI3K/AKT signaling, and stress (p38/SAPK/JNK) signaling. Here, we describe a characterization of this mixture spiked into a HeLa tryptic digest stimulated with both epidermal growth factor and insulin-like growth factor-1 to activate the MAPK and PI3K/AKT/mTOR pathways. We further demonstrate a comparison of phosphoproteomic profiling of HeLa performed independently in five labs using this phosphopeptide mixture with data-independent acquisition. Despite different experimental and instrumentation processes, we found that labs could produce reproducible, harmonized datasets by reporting measurements as ratios to the standard, while intensity measurements showed lower consistency between labs even after normalization. Our results suggest that widely available, biologically relevant phosphopeptide standards can act as a quantitative "yardstick" across laboratories and sample preparations enabling experimental designs larger than a single laboratory can perform. Raw data files are publicly available in the MassIVE dataset MSV000090564.

Exploring molecular dynamic indicators associated with reproductive performance of Bos indicus cattle in blood plasma samples through data-independent acquisition mass spectrometry

Improving reproductive performance of cattle is of paramount importance for sustainable dairy farming. Poor reproduction performance (RP) hinders the genetic improvement of important Bos indicus cattle breeds. It is well known that incorporation of molecular information along with conventional breeding method is far better than use of conventional method alone for the genetic improvement of reproductive performance traits in cattle. Therefore, the present study sought to investigate the plasma proteome of the Deoni cows in cyclical (n = 6) and pregnant (n = 6) reproductive phases with varying reproductive performance (high and low). High-throughput data independent acquisition (DIA) based proteomics was performed to understand corresponding proteome. We identified a total of 430 plasma proteins. Among cyclic cows, twenty proteins were differentially regulated in low RP as compared to high RP. BARD1 and AFP proteins were observed upregulated in cyclical cows whose upregulation reported to affect reproductive performance in cattle. Among the pregnant cows, thirty-five proteins were differentially regulated, including the downregulation of FGL2 and ZNFX1 that modulates the maternal immune response mechanism which is required for successful implantation of the embryo. Also, proteins such as AHSG, CLU and SERPINA6 were upregulated in the pregnant cows whose upregulation reported to reduced reproductive performance. The results of this study will be helpful in establishing a framework for future research on the aspect of improving reproductive performance in Bos indicus cattle breeds. SIGNIFICANCE: The Indian subcontinent is the center of domestication for Bos indicus cattle breeds and they are known for their disease resistance, heat tolerance, ability to survive in low input regime and harsh climatic conditions. In recent times, population of many important Bos indicus breeds including Deoni cattle is declining due to various factors, especially due to reproductive performance. Traditional breeding methods are not sufficient enough to understand and improve the reproductive performance traits in important Bos indicus cattle breeds. Proteomics approach is a promising technology to understand the complex biological factors which leads to poor reproductive performance in cattle. The present study utilized DIA based LC- MS/MS analysis to identify the plasma proteins associated with reproductive performance in cyclical and pregnant cows. This study if improved further, can be used to develop potential protein markers associated with reproductive performance which is useful for the selection and genetic improvement of important Bos indicus breeds.

Dynamic Data-Independent Acquisition Mass Spectrometry with Real-Time Retrospective Alignment

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.

Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data Independent Acquisition

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.

Comparison of Quantitative Mass Spectrometric Methods for Drug Target Identification by Thermal Proteome Profiling

Thermal proteome profiling (TPP) provides a powerful approach to studying proteome-wide interactions of small therapeutic molecules and their target and off-target proteins, complementing phenotypic-based drug screens. Detecting differences in thermal stability due to target engagement requires high quantitative accuracy and consistent detection. Isobaric tandem mass tags (TMTs) are used to multiplex samples and increase quantification precision in TPP analysis by data-dependent acquisition (DDA). However, advances in data-independent acquisition (DIA) can provide higher sensitivity and protein coverage with reduced costs and sample preparation steps. Herein, we explored the performance of different DIA-based label-free quantification approaches compared to TMT-DDA for thermal shift quantitation. Acute myeloid leukemia cells were treated with losmapimod, a known inhibitor of MAPK14 (p38α). Label-free DIA approaches, and particularly the library-free mode in DIA-NN, were comparable of TMT-DDA in their ability to detect target engagement of losmapimod with MAPK14 and one of its downstream targets, MAPKAPK3. Using DIA for thermal shift quantitation is a cost-effective alternative to labeled quantitation in the TPP pipeline.

nf-encyclopedia: A Cloud-Ready Pipeline for Chromatogram Library Data-Independent Acquisition Proteomics Workflows

Data-independent acquisition (DIA) mass spectrometry methods provide systematic and comprehensive quantification of the proteome; yet, relatively few open-source tools are available to analyze DIA proteomics experiments. Fewer still are tools that can leverage gas phase fractionated (GPF) chromatogram libraries to enhance the detection and quantification of peptides in these experiments. Here, we present nf-encyclopedia, an open-source NextFlow pipeline that connects three open-source tools, MSConvert, EncyclopeDIA, and MSstats, to analyze DIA proteomics experiments with or without chromatogram libraries. We demonstrate that nf-encyclopedia is reproducible when run on either a cloud platform or a local workstation and provides robust peptide and protein quantification. Additionally, we found that MSstats enhances protein-level quantitative performance over EncyclopeDIA alone. Finally, we benchmarked the ability of nf-encyclopedia to scale to large experiments in the cloud by leveraging the parallelization of compute resources. The nf-encyclopedia pipeline is available under a permissive Apache 2.0 license; run it on your desktop, cluster, or in the cloud: https://github.com/TalusBio/nf-encyclopedia.

Advanced mass spectrometry workflows for accurate quantification of trace-level host cell proteins in drug products: Benefits of FAIMS separation and gas-phase fractionation DIA

Therapeutic monoclonal antibodies (mAb) production relies on multiple purification steps before release as a drug product (DP). A few host cell proteins (HCPs) may co-purify with the mAb. Their monitoring is crucial due to the considerable risk they represent for mAb stability, integrity, and efficacy and their potential immunogenicity. Enzyme-linked immunosorbent assays (ELISA) commonly used for global HCP monitoring present limitations in terms of identification and quantification of individual HCPs. Therefore, liquid chromatography tandem mass spectrometry (LC-MS/MS) has emerged as a promising alternative. Challenging DP samples show an extreme dynamic range requiring high performing methods to detect and reliably quantify trace-level HCPs. Here, we investigated the benefits of adding high-field asymmetric ion mobility spectrometry (FAIMS) separation and gas phase fractionation (GPF) prior to data independent acquisition (DIA). FAIMS LC-MS/MS analysis allowed the identification of 221 HCPs among which 158 were reliably quantified for a global amount of 880 ng/mg of NIST mAb Reference Material. Our methods have also been successfully applied to two FDA/EMA approved DPs and allowed digging deeper into the HCP landscape with the identification and quantification of a few tens of HCPs with sensitivity down to the sub-ng/mg of mAb level.

Innovative workflow for the identification of cathepsin K cleavage sites in type I collagen

Since the late 1990s, cathepsin K cleavage sites in type I collagen have been extensively studied due to its ability to release bone resorption biomarkers such as CTX and NTX. However, gel-based methods and N-sequencing used in these studies lack sensitivity, especially for small to medium peptides. In this work, we propose a degradomics mass spectrometry-based workflow that combines protein digestion, Nano-LC-UDMSE, and several software tools to identify cathepsin K cleavage sites. This workflow not only identified previously known cleavage sites, but also discovered new ones. Multiple cleavage hotspots were found and described in type I α1 and type I α2 collagen, many of which coincided with pyridinoline crosslinks, known to stabilize the triple helix. Our results allowed us to establish a chronology of digestion and conclude that cathepsin K preferentially cleaves the extremities of type I collagen before the helical part. We also found that cathepsin K preferentially cleaves amino acid residues with long and hydrophobic lateral chains at the beginning of digestion, whereas no preferred amino acid residues were identified later in the digestion. In conclusion, our workflow successfully identified new cleavage sites and can be easily applied to other proteins or proteases.

Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform

Liquid chromatography (LC) coupled with data-independent acquisition (DIA) mass spectrometry (MS) has been increasingly used in quantitative proteomics studies. Here, we present a fast and sensitive approach for direct peptide identification from DIA data, MSFragger-DIA, which leverages the unmatched speed of the fragment ion indexing-based search engine MSFragger. Different from most existing methods, MSFragger-DIA conducts a database search of the DIA tandem mass (MS/MS) spectra prior to spectral feature detection and peak tracing across the LC dimension. To streamline the analysis of DIA data and enable easy reproducibility, we integrate MSFragger-DIA into the FragPipe computational platform for seamless support of peptide identification and spectral library building from DIA, data-dependent acquisition (DDA), or both data types combined. We compare MSFragger-DIA with other DIA tools, such as DIA-Umpire based workflow in FragPipe, Spectronaut, DIA-NN library-free, and MaxDIA. We demonstrate the fast, sensitive, and accurate performance of MSFragger-DIA across a variety of sample types and data acquisition schemes, including single-cell proteomics, phosphoproteomics, and large-scale tumor proteome profiling studies.

Organism-wide, cell-type-specific secretome mapping of exercise training in mice

There is a significant interest in identifying blood-borne factors that mediate tissue crosstalk and function as molecular effectors of physical activity. Although past studies have focused on an individual molecule or cell type, the organism-wide secretome response to physical activity has not been evaluated. Here, we use a cell-type-specific proteomic approach to generate a 21-cell-type, 10-tissue map of exercise training-regulated secretomes in mice. Our dataset identifies >200 exercise training-regulated cell-type-secreted protein pairs, the majority of which have not been previously reported. Pdgfra-cre-labeled secretomes were the most responsive to exercise training. Finally, we show anti-obesity, anti-diabetic, and exercise performance-enhancing activities for proteoforms of intracellular carboxylesterases whose secretion from the liver is induced by exercise training.

Recent progress in quantitative phosphoproteomics

INTRODUCTION

Protein phosphorylation is a critical post-translational modification involved in the regulation of numerous cellular processes from signal transduction to modulation of enzyme activities. Knowledge of dynamic changes of phosphorylation levels during biological processes, under various treatments or between healthy and disease models is fundamental for understanding the role of each phosphorylation event. Thereby, LC-MS/MS based technologies in combination with quantitative proteomics strategies evolved as a powerful strategy to investigate the function of individual protein phosphorylation events.

AREAS COVERED

State-of-the-art labeling techniques including stable isotope and isobaric labeling provide precise and accurate quantification of phosphorylation events. Here, we review the strengths and limitations of recent quantification methods and provide examples based on current studies, how quantitative phosphoproteomics can be further optimized for enhanced analytic depth, dynamic range, site localization, and data integrity. Specifically, reducing the input material demands is key to a broader implementation of quantitative phosphoproteomics, not least for clinical samples.

EXPERT OPINION

Despite quantitative phosphoproteomics is one of the most thriving fields in the proteomics world, many challenges still have to be overcome to facilitate even deeper and more comprehensive analyses as required in the current research, especially at single cell levels and in clinical diagnostics.

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

2019 Association of Biomolecular Resource Facilities Multi-Laboratory Data-Independent Acquisition Proteomics Study

Despite the advantages of fewer missing values by collecting fragment ion data on all analytes in the sample as well as the potential for deeper coverage, the adoption of data-independent acquisition (DIA) in proteomics core facility settings has been slow. The Association of Biomolecular Resource Facilities conducted a large interlaboratory study to evaluate DIA performance in proteomics laboratories with various instrumentation. Participants were supplied with generic methods and a uniform set of test samples. The resulting 49 DIA datasets act as benchmarks and have utility in education and tool development. The sample set consisted of a tryptic HeLa digest spiked with high or low levels of 4 exogenous proteins. Data are available in MassIVE MSV000086479. Additionally, we demonstrate how the data can be analyzed by focusing on 2 datasets using different library approaches and show the utility of select summary statistics. These data can be used by DIA newcomers, software developers, or DIA experts evaluating performance with different platforms, acquisition settings, and skill levels.