Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand the dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune, and clinical markers of microbiomes from four body sites in 86 participants over 6 years. We found that microbiome stability and individuality are body-site specific and heavily influenced by the host. The stool and oral microbiome are more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. We identify individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlate across body sites, suggesting systemic dynamics influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals show altered microbial stability and associations among microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune and clinical markers of microbiomes from four body sites in 86 participants over six years. We found that microbiome stability and individuality are body-site-specific and heavily influenced by the host. The stool and oral microbiome were more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. Also, we identified individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlated across body sites, suggesting systemic coordination influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals showed altered microbial stability and associations between microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Study Highlights

The stability of the human microbiome varies among individuals and body sites.Highly individualized microbial genera are more stable over time.At each of the four body sites, systematic interactions between the environment, the host and bacteria can be detected.Individuals with insulin resistance have lower microbiome stability, a more diversified skin microbiome, and significantly altered host-microbiome interactions.

Multi-omics microsampling for the profiling of lifestyle-associated changes in health

Current healthcare practices are reactive and use limited physiological and clinical information, often collected months or years apart. Moreover, the discovery and profiling of blood biomarkers in clinical and research settings are constrained by geographical barriers, the cost and inconvenience of in-clinic venepuncture, low sampling frequency and the low depth of molecular measurements. Here we describe a strategy for the frequent capture and analysis of thousands of metabolites, lipids, cytokines and proteins in 10 μl of blood alongside physiological information from wearable sensors. We show the advantages of such frequent and dense multi-omics microsampling in two applications: the assessment of the reactions to a complex mixture of dietary interventions, to discover individualized inflammatory and metabolic responses; and deep individualized profiling, to reveal large-scale molecular fluctuations as well as thousands of molecular relationships associated with intra-day physiological variations (in heart rate, for example) and with the levels of clinical biomarkers (specifically, glucose and cortisol) and of physical activity. Combining wearables and multi-omics microsampling for frequent and scalable omics may facilitate dynamic health profiling and biomarker discovery.

Dynamic lipidome alterations associated with human health, disease and ageing

Lipids can be of endogenous or exogenous origin and affect diverse biological functions, including cell membrane maintenance, energy management and cellular signalling. Here, we report >800 lipid species, many of which are associated with health-to-disease transitions in diabetes, ageing and inflammation, as well as cytokine-lipidome networks. We performed comprehensive longitudinal lipidomic profiling and analysed >1,500 plasma samples from 112 participants followed for up to 9 years (average 3.2 years) to define the distinct physiological roles of complex lipid subclasses, including large and small triacylglycerols, ester- and ether-linked phosphatidylethanolamines, lysophosphatidylcholines, lysophosphatidylethanolamines, cholesterol esters and ceramides. Our findings reveal dynamic changes in the plasma lipidome during respiratory viral infection, insulin resistance and ageing, suggesting that lipids may have roles in immune homoeostasis and inflammation regulation. Individuals with insulin resistance exhibit disturbed immune homoeostasis, altered associations between lipids and clinical markers, and accelerated changes in specific lipid subclasses during ageing. Our dataset based on longitudinal deep lipidome profiling offers insights into personalized ageing, metabolic health and inflammation, potentially guiding future monitoring and intervention strategies.

Protein Coronas on Functionalized Nanoparticles Enable Quantitative and Precise Large-Scale Deep Plasma Proteomics

Background

The wide dynamic range of circulating proteins coupled with the diversity of proteoforms present in plasma has historically impeded comprehensive and quantitative characterization of the plasma proteome at scale. Automated nanoparticle (NP) protein corona-based proteomics workflows can efficiently compress the dynamic range of protein abundances into a mass spectrometry (MS)-accessible detection range. This enhances the depth and scalability of quantitative MS-based methods, which can elucidate the molecular mechanisms of biological processes, discover new protein biomarkers, and improve comprehensiveness of MS-based diagnostics.

Methods

Investigating multi-species spike-in experiments and a cohort, we investigated fold-change accuracy, linearity, precision, and statistical power for the using the Proteograph™ Product Suite, a deep plasma proteomics workflow, in conjunction with multiple MS instruments.

Results

We show that NP-based workflows enable accurate identification (false discovery rate of 1%) of more than 6,000 proteins from plasma (Orbitrap Astral) and, compared to a gold standard neat plasma workflow that is limited to the detection of hundreds of plasma proteins, facilitate quantification of more proteins with accurate fold-changes, high linearity, and precision. Furthermore, we demonstrate high statistical power for the discovery of biomarkers in small- and large-scale cohorts.

Conclusions

The automated NP workflow enables high-throughput, deep, and quantitative plasma proteomics investigation with sufficient power to discover new biomarker signatures with a peptide level resolution.

Functionally distinct BMP1 isoforms show an opposite pattern of abundance in plasma from non-small cell lung cancer subjects and controls

Advancements in deep plasma proteomics are enabling high-resolution measurement of plasma proteoforms, which may reveal a rich source of novel biomarkers previously concealed by aggregated protein methods. Here, we analyze 188 plasma proteomes from non-small cell lung cancer subjects (NSCLC) and controls to identify NSCLC-associated protein isoforms by examining differentially abundant peptides as a proxy for isoform-specific exon usage. We find four proteins comprised of peptides with opposite patterns of abundance between cancer and control subjects. One of these proteins, BMP1, has known isoforms that can explain this differential pattern, for which the abundance of the NSCLC-associated isoform increases with stage of NSCLC progression. The presence of cancer and control-associated isoforms suggests differential regulation of BMP1 isoforms. The identified BMP1 isoforms have known functional differences, which may reveal insights into mechanisms impacting NSCLC disease progression.

Enhanced Competition at the Nano-Bio Interface Enables Comprehensive Characterization of Protein Corona Dynamics and Deep Coverage of Proteomes

Introducing engineered nanoparticles (NPs) into a biofluid such as blood plasma leads to the formation of a selective and reproducible protein corona at the particle-protein interface, driven by the relationship between protein-NP affinity and protein abundance. This enables scalable systems that leverage protein-nano interactions to overcome current limitations of deep plasma proteomics in large cohorts. Here the importance of the protein to NP-surface ratio (P/NP) is demonstrated and protein corona formation dynamics are modeled, which determine the competition between proteins for binding. Tuning the P/NP ratio significantly modulates the protein corona composition, enhancing depth and precision of a fully automated NP-based deep proteomic workflow (Proteograph). By increasing the binding competition on engineered NPs, 1.2-1.7× more proteins with 1% false discovery rate are identified on the surface of each NP, and up to 3× more proteins compared to a standard plasma proteomics workflow. Moreover, the data suggest P/NP plays a significant role in determining the in vivo fate of nanomaterials in biomedical applications. Together, the study showcases the importance of P/NP as a key design element for biomaterials and nanomedicine in vivo and as a powerful tuning strategy for accurate, large-scale NP-based deep proteomic studies.

Abstract 6339: Deep plasma proteomics at scale enabling proteogenomic analyses in a lung cancer (NSCLC) study

Our ~20,000 genes encode over one million protein variants, given alternative splice forms, allelic variation, and protein modification. Though large-scale genomics studies have expanded our understanding of biology, similarly, scaled deep and untargeted proteomics studies of biofluids have remained impractical due to complex workflows. To address this need, we have previously described Proteograph࣪, a novel platform that leverages the protein-corona interactions of nanoparticles for deep and untargeted proteomic sampling at scale.

Using Proteograph࣪ in a non-small cell lung cancer (NSCLC) cohort, we previously conducted a deep interrogation of plasma from 141 subjects: 61 early-stage NSCLC subjects and 80 non-cancer controls. We identified 2,499 plasma proteins, with 1,992 present in ≥ 25% of the samples. Leveraging this data, we created a biomarker classifier distinguishing NSCLC from controls with area under the receiver operating characteristic curve of 0.911. In this study, we now re-analyze the data with the more sensitive DIA-NN software to enhance protein depth while preserving the accuracy of the classifier. In addition, to show the added value of our platform in combination with genomic data, we integrate previously sequenced exome data with our proteomic data to build a multi-modal proteogenomic deep learning classifier. Our results outline proteogenomic workflows for robust biomarker discovery and cohort subtyping.

The Proteograph࣪ platform interrogates the plasma proteome at previously impractical combinations of scale, depth and coverage, and enables the development of improved classification models and the study of proteogenomics.

1Blume et al. Nat. Comm. (2020)

Citation Format: Mahdi Zamanighomi, Harendra Guturu, Jian Wang, Amir Alavi, Tristan Brown, Daniel Hornburg, Moaraj Hasan, Shadi Ferdosi, Khatereh Motamedchaboki, Margaret Donovan, Theodore Platt, Ryan Benz, Asim Siddiqui, Serafim Batzoglou. Deep plasma proteomics at scale enabling proteogenomic analyses in a lung cancer (NSCLC) study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6339.

Global, distinctive, and personal changes in molecular and microbial profiles by specific fibers in humans

Dietary fibers act through the microbiome to improve cardiovascular health and prevent metabolic disorders and cancer. To understand the health benefits of dietary fiber supplementation, we investigated two popular purified fibers, arabinoxylan (AX) and long-chain inulin (LCI), and a mixture of five fibers. We present multiomic signatures of metabolomics, lipidomics, proteomics, metagenomics, a cytokine panel, and clinical measurements on healthy and insulin-resistant participants. Each fiber is associated with fiber-dependent biochemical and microbial responses. AX consumption associates with a significant reduction in LDL and an increase in bile acids, contributing to its observed cholesterol reduction. LCI is associated with an increase in Bifidobacterium. However, at the highest LCI dose, there is increased inflammation and elevation in the liver enzyme alanine aminotransferase. This study yields insights into the effects of fiber supplementation and the mechanisms behind fiber-induced cholesterol reduction, and it shows effects of individual, purified fibers on the microbiome.

Amyloid-like aggregating proteins cause lysosomal defects in neurons via gain-of-function toxicity

Using cryo-ET, cell biology, and proteomics, this study shows that aggregating proteins impair the autophagy-lysosomal pathway in neurons by sequestering a subunit of the AP-3 adaptor complex.

The autophagy-lysosomal pathway is impaired in many neurodegenerative diseases characterized by protein aggregation, but the link between aggregation and lysosomal dysfunction remains poorly understood. Here, we combine cryo-electron tomography, proteomics, and cell biology studies to investigate the effects of protein aggregates in primary neurons. We use artificial amyloid-like β-sheet proteins (β proteins) to focus on the gain-of-function aspect of aggregation. These proteins form fibrillar aggregates and cause neurotoxicity. We show that late stages of autophagy are impaired by the aggregates, resulting in lysosomal alterations reminiscent of lysosomal storage disorders. Mechanistically, β proteins interact with and sequester AP-3 μ1, a subunit of the AP-3 adaptor complex involved in protein trafficking to lysosomal organelles. This leads to destabilization of the AP-3 complex, missorting of AP-3 cargo, and lysosomal defects. Restoring AP-3μ1 expression ameliorates neurotoxicity caused by β proteins. Altogether, our results highlight the link between protein aggregation, lysosomal impairments, and neurotoxicity.

Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring

Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.

Loss of full-length hnRNP R isoform impairs DNA damage response in motoneurons by inhibiting Yb1 recruitment to chromatin

Neurons critically rely on the functions of RNA-binding proteins to maintain their polarity and resistance to neurotoxic stress. HnRNP R has a diverse range of post-transcriptional regulatory functions and is important for neuronal development by regulating axon growth. Hnrnpr pre-mRNA undergoes alternative splicing giving rise to a full-length protein and a shorter isoform lacking its N-terminal acidic domain. To investigate functions selectively associated with the full-length hnRNP R isoform, we generated a Hnrnpr knockout mouse (Hnrnprtm1a/tm1a) in which expression of full-length hnRNP R was abolished while production of the truncated hnRNP R isoform was retained. Motoneurons cultured from Hnrnprtm1a/tm1a mice did not show any axonal growth defects but exhibited enhanced accumulation of double-strand breaks and an impaired DNA damage response upon exposure to genotoxic agents. Proteomic analysis of the hnRNP R interactome revealed the multifunctional protein Yb1 as a top interactor. Yb1-depleted motoneurons were defective in DNA damage repair. We show that Yb1 is recruited to chromatin upon DNA damage where it interacts with γ-H2AX, a mechanism that is dependent on full-length hnRNP R. Our findings thus suggest a novel role of hnRNP R in maintaining genomic integrity and highlight the function of its N-terminal acidic domain in this context.

A DMS Shotgun Lipidomics Workflow Application to Facilitate High-Throughput, Comprehensive Lipidomics

Differential mobility spectrometry (DMS) is highly useful for shotgun lipidomic analysis because it overcomes difficulties in measuring isobaric species within a complex lipid sample and allows for acyl tail characterization of phospholipid species. Despite these advantages, the resulting workflow presents technical challenges, including the need to tune the DMS before every batch to update compensative voltages settings within the method. The Sciex Lipidyzer platform uses a Sciex 5500 QTRAP with a DMS (SelexION), an LC system configured for direction infusion experiments, an extensive set of standards designed for quantitative lipidomics, and a software package (Lipidyzer Workflow Manager) that facilitates the workflow and rapidly analyzes the data. Although the Lipidyzer platform remains very useful for DMS-based shotgun lipidomics, the software is no longer updated for current versions of Analyst and Windows. Furthermore, the software is fixed to a single workflow and cannot take advantage of new lipidomics standards or analyze additional lipid species. To address this multitude of issues, we developed Shotgun Lipidomics Assistant (SLA), a Python-based application that facilitates DMS-based lipidomics workflows. SLA provides the user with flexibility in adding and subtracting lipid and standard MRMs. It can report quantitative lipidomics results from raw data in minutes, comparable to the Lipidyzer software. We show that SLA facilitates an expanded lipidomics analysis that measures over 1450 lipid species across 17 (sub)classes. Lastly, we demonstrate that the SLA performs isotope correction, a feature that was absent from the original software.

Identification of covalent modifications regulating immune signaling complex composition and phenotype

Cells signal through rearrangements of protein communities governed by covalent modifications and reversible interactions of distinct sets of proteins. A method that identifies those post‐transcriptional modifications regulating signaling complex composition and functional phenotypes in one experimental setup would facilitate an efficient identification of novel molecular signaling checkpoints. Here, we devised modifications, interactions and phenotypes by affinity purification mass spectrometry (MIP‐APMS), comprising the streamlined cloning and transduction of tagged proteins into functionalized reporter cells as well as affinity chromatography, followed by MS‐based quantification. We report the time‐resolved interplay of more than 50 previously undescribed modification and hundreds of protein–protein interactions of 19 immune protein complexes in monocytes. Validation of interdependencies between covalent, reversible, and functional protein complex regulations by knockout or site‐specific mutation revealed ISGylation and phosphorylation of TRAF2 as well as ARHGEF18 interaction in Toll‐like receptor 2 signaling. Moreover, we identify distinct mechanisms of action for small molecule inhibitors of p38 (MAPK14). Our method provides a fast and cost‐effective pipeline for the molecular interrogation of protein communities in diverse biological systems and primary cells.

A genome-wide atlas of co-essential modules assigns function to uncharacterized genes

A central question in the post-genomic era is how genes interact to form biological pathways. Measurements of gene dependency across hundreds of cell lines have been used to cluster genes into 'co-essential' pathways, but this approach has been limited by ubiquitous false positives. In the present study, we develop a statistical method that enables robust identification of gene co-essentiality and yields a genome-wide set of functional modules. This atlas recapitulates diverse pathways and protein complexes, and predicts the functions of 108 uncharacterized genes. Validating top predictions, we show that TMEM189 encodes plasmanylethanolamine desaturase, a key enzyme for plasmalogen synthesis. We also show that C15orf57 encodes a protein that binds the AP2 complex, localizes to clathrin-coated pits and enables efficient transferrin uptake. Finally, we provide an interactive webtool for the community to explore our results, which establish co-essentiality profiling as a powerful resource for biological pathway identification and discovery of new gene functions.

Nano-Bio Interactions in Cancer: From Therapeutics Delivery to Early Detection

Understanding the interactions between nanomaterials and biological systems plays a pivotal role in enhancing the efficacy of nanomedicine and advancing the disease diagnosis. The nanoparticle-protein corona, an active biomolecular layer, is formed around nanoparticles (NPs) upon mixing with biological fluid. The surface layer which consists of rapidly exchanged biomolecules is called the "soft" corona. The inner layer which is more stable and tightly packed is called the "hard" corona. It has been suggested that the NP-protein corona has a decisive effect on the in vivo fate of nanomedicine upon intravenously administration into the mouse. Furthermore, the features of the NP-protein corona make it a powerful platform to enrich low-abundance proteins from serum/plasma for downstream mass-spectrometry (MS)-based proteomics for biomarker discovery and disease diagnosis.Herein, we summarize our recent work on the development of nanomedicine and disease detection from the level of nano-bio interactions between nanoparticles and biological systems. Nanomedicine has made substantial progress over the past two decades. However, the significant enhancement of overall patient survival by nanomedicine remains a challenge due to the lack of a deep understanding of nano-bio interactions in the clinical setting. The pharmacokinetic effect of the protein corona on PEGylated NPs during blood circulation indicated that the adsorbed apolipoproteins could prolong the circulation time of NPs. This mechanistic understanding of the protein corona (active biomolecule) formed around polymeric NPs offered insights into enhancing the efficacy of nanomedicine from the biological interactions point of view. Moreover, we discuss the basic rationale for developing bioresponsive cancer nanomedicine by exploiting the pathophysiological environment around the tumor, typically the pH, reactive oxygen species (ROS), and redox-responsive supramolecular motifs based on synthetic amphiphilic polymers. The protein corona in vivo determines the biological fate of NPs, whereas it opens a new avenue to enrich low abundant proteins in a biospecimen ex vivo to render them "visible" for downstream analytical workflows, such as MS-based proteomics. Blood serum/plasma, due to easy accessibility and great potential to uncover and monitor physiological and pathological changes in health and disease, has remained a major source of detecting protein biomarker candidates. Inspired by the features of the NP-protein corona, a Proteograph platform, which integrates multi-NP-protein coronas with MS for large-scale efficient and deep proteome profiling has been developed. Finally, we conclude this Account with a better understanding of nano-bio interactions to accelerate the nanomedicine translation and how MS-based proteomics can boost our understanding of the corona composition and facilitate the identification of disease biomarkers.

Molecular Choreography of Acute Exercise

Acute physical activity leads to several changes in metabolic, cardiovascular, and immune pathways. Although studies have examined selected changes in these pathways, the system-wide molecular response to an acute bout of exercise has not been fully characterized. We performed longitudinal multi-omic profiling of plasma and peripheral blood mononuclear cells including metabolome, lipidome, immunome, proteome, and transcriptome from 36 well-characterized volunteers, before and after a controlled bout of symptom-limited exercise. Time-series analysis revealed thousands of molecular changes and an orchestrated choreography of biological processes involving energy metabolism, oxidative stress, inflammation, tissue repair, and growth factor response, as well as regulatory pathways. Most of these processes were dampened and some were reversed in insulin-resistant participants. Finally, we discovered biological pathways involved in cardiopulmonary exercise response and developed prediction models revealing potential resting blood-based biomarkers of peak oxygen consumption.

Dietary Intake Regulates the Circulating Inflammatory Monocyte Pool

Caloric restriction is known to improve inflammatory and autoimmune diseases. However, the mechanisms by which reduced caloric intake modulates inflammation are poorly understood. Here we show that short-term fasting reduced monocyte metabolic and inflammatory activity and drastically reduced the number of circulating monocytes. Regulation of peripheral monocyte numbers was dependent on dietary glucose and protein levels. Specifically, we found that activation of the low-energy sensor 5'-AMP-activated protein kinase (AMPK) in hepatocytes and suppression of systemic CCL2 production by peroxisome proliferator-activator receptor alpha (PPARα) reduced monocyte mobilization from the bone marrow. Importantly, we show that fasting improves chronic inflammatory diseases without compromising monocyte emergency mobilization during acute infectious inflammation and tissue repair. These results reveal that caloric intake and liver energy sensors dictate the blood and tissue immune tone and link dietary habits to inflammatory disease outcome.

The MEK5-ERK5 Kinase Axis Controls Lipid Metabolism in Small-Cell Lung Cancer

Small-cell lung cancer (SCLC) is an aggressive form of lung cancer with dismal survival rates. While kinases often play key roles driving tumorigenesis, there are strikingly few kinases known to promote the development of SCLC. Here, we investigated the contribution of the MAPK module MEK5-ERK5 to SCLC growth. MEK5 and ERK5 were required for optimal survival and expansion of SCLC cell lines in vitro and in vivo. Transcriptomics analyses identified a role for the MEK5-ERK5 axis in the metabolism of SCLC cells, including lipid metabolism. In-depth lipidomics analyses showed that loss of MEK5/ERK5 perturbs several lipid metabolism pathways, including the mevalonate pathway that controls cholesterol synthesis. Notably, depletion of MEK5/ERK5 sensitized SCLC cells to pharmacologic inhibition of the mevalonate pathway by statins. These data identify a new MEK5-ERK5-lipid metabolism axis that promotes the growth of SCLC. SIGNIFICANCE: This study is the first to investigate MEK5 and ERK5 in SCLC, linking the activity of these two kinases to the control of cell survival and lipid metabolism.

A longitudinal big data approach for precision health

Precision health relies on the ability to assess disease risk at an individual level, detect early preclinical conditions and initiate preventive strategies. Recent technological advances in omics and wearable monitoring enable deep molecular and physiological profiling and may provide important tools for precision health. We explored the ability of deep longitudinal profiling to make health-related discoveries, identify clinically relevant molecular pathways and affect behavior in a prospective longitudinal cohort (n = 109) enriched for risk of type 2 diabetes mellitus. The cohort underwent integrative personalized omics profiling from samples collected quarterly for up to 8 years (median, 2.8 years) using clinical measures and emerging technologies including genome, immunome, transcriptome, proteome, metabolome, microbiome and wearable monitoring. We discovered more than 67 clinically actionable health discoveries and identified multiple molecular pathways associated with metabolic, cardiovascular and oncologic pathophysiology. We developed prediction models for insulin resistance by using omics measurements, illustrating their potential to replace burdensome tests. Finally, study participation led the majority of participants to implement diet and exercise changes. Altogether, we conclude that deep longitudinal profiling can lead to actionable health discoveries and provide relevant information for precision health.

Cross-Platform Comparison of Untargeted and Targeted Lipidomics Approaches on Aging Mouse Plasma

Lipidomics – the global assessment of lipids – can be performed using a variety of mass spectrometry (MS)-based approaches. However, choosing the optimal approach in terms of lipid coverage, robustness and throughput can be a challenging task. Here, we compare a novel targeted quantitative lipidomics platform known as the Lipidyzer to a conventional untargeted liquid chromatography (LC)-MS approach. We find that both platforms are efficient in profiling more than 300 lipids across 11 lipid classes in mouse plasma with precision and accuracy below 20% for most lipids. While the untargeted and targeted platforms detect similar numbers of lipids, the former identifies a broader range of lipid classes and can unambiguously identify all three fatty acids in triacylglycerols (TAG). Quantitative measurements from both approaches exhibit a median correlation coefficient (r) of 0.99 using a dilution series of deuterated internal standards and 0.71 using endogenous plasma lipids in the context of aging. Application of both platforms to plasma from aging mouse reveals similar changes in total lipid levels across all major lipid classes and in specific lipid species. Interestingly, TAG is the lipid class that exhibits the most changes with age, suggesting that TAG metabolism is particularly sensitive to the aging process in mice. Collectively, our data show that the Lipidyzer platform provides comprehensive profiling of the most prevalent lipids in plasma in a simple and automated manner.

The hemicellulose-degrading enzyme system of the thermophilic bacterium Clostridium stercorarium: comparative characterisation and addition of new hemicellulolytic glycoside hydrolases

BACKGROUND

The bioconversion of lignocellulosic biomass in various industrial processes, such as the production of biofuels, requires the degradation of hemicellulose. Clostridium stercorarium is a thermophilic bacterium, well known for its outstanding hemicellulose-degrading capability. Its genome comprises about 50 genes for partially still uncharacterised thermostable hemicellulolytic enzymes. These are promising candidates for industrial applications.

RESULTS

To reveal the hemicellulose-degrading potential of 50 glycoside hydrolases, they were recombinantly produced and characterised. 46 of them were identified in the secretome of C. stercorarium cultivated on cellobiose. Xylanases Xyn11A, Xyn10B, Xyn10C, and cellulase Cel9Z were among the most abundant proteins. The secretome of C. stercorarium was active on xylan, β-glucan, xyloglucan, galactan, and glucomannan. In addition, the recombinant enzymes hydrolysed arabinan, mannan, and galactomannan. 20 enzymes are newly described, degrading xylan, galactan, arabinan, mannan, and aryl-glycosides of β-d-xylose, β-d-glucose, β-d-galactose, α-l-arabinofuranose, α-l-rhamnose, β-d-glucuronic acid, and N-acetyl-β-d-glucosamine. The activities of three enzymes with non-classified glycoside hydrolase (GH) family modules were determined. Xylanase Xyn105F and β-d-xylosidase Bxl31D showed activities not described so far for their GH families. 11 of the 13 polysaccharide-degrading enzymes were most active at pH 5.0 to pH 6.5 and at temperatures of 57-76 °C. Investigation of the substrate and product specificity of arabinoxylan-degrading enzymes revealed that only the GH10 xylanases were able to degrade arabinoxylooligosaccharides. While Xyn10C was inhibited by α-(1,2)-arabinosylations, Xyn10D showed a degradation pattern different to Xyn10B and Xyn10C. Xyn11A released longer degradation products than Xyn10B. Both tested arabinose-releasing enzymes, Arf51B and Axh43A, were able to hydrolyse single- as well as double-arabinosylated xylooligosaccharides.

CONCLUSIONS

The obtained results lead to a better understanding of the hemicellulose-degrading capacity of C. stercorarium and its involved enzyme systems. Despite similar average activities measured by depolymerisation tests, a closer look revealed distinctive differences in the activities and specificities within an enzyme class. This may lead to synergistic effects and influence the enzyme choice for biotechnological applications. The newly characterised glycoside hydrolases can now serve as components of an enzyme platform for industrial applications in order to reconstitute synthetic enzyme systems for complete and optimised degradation of defined polysaccharides and hemicellulose.

Proteomics and C9orf72 neuropathology identify ribosomes as poly-GR/PR interactors driving toxicity

Proteomics and neuropathological validation show that aberrant poly-GR/PR proteins in C9orf72 ALS/FTD bind STAU2 and ribosomes and inhibit translation.

Frontotemporal dementia and amyotrophic lateral sclerosis patients with C9orf72 mutation show cytoplasmic poly-GR and poly-PR aggregates. Short poly-(Gly-Arg) and poly-(Pro-Arg) (poly-GR/PR) repeats localizing to the nucleolus are toxic in various model systems, but no interactors have been validated in patients. Here, the neuronal interactomes of cytoplasmic GFP-(GR)₁₄₉ and nucleolar (PR)₁₇₅-GFP revealed overlapping RNA-binding proteins, including components of stress granules, nucleoli, and ribosomes. Overexpressing the poly-GR/PR interactors STAU1/2 and YBX1 caused cytoplasmic aggregation of poly-GR/PR in large stress granule–like structures, whereas NPM1 recruited poly-GR into the nucleolus. Poly-PR expression reduced ribosome levels and translation consistent with reduction of synaptic proteins detected by proteomics. Surprisingly, truncated GFP-(GR)₅₃, but not GFP-(GR)₁₄₉, localized to the nucleolus and reduced ribosome levels and translation similar to poly-PR, suggesting that impaired ribosome biogenesis may be driving the acute toxicity observed in vitro. In patients, only ribosomes and STAU2 co-aggregated with poly-GR/PR. Partial sequestration of ribosomes may chronically impair protein synthesis even in the absence of nucleolar localization and contribute to pathogenesis.

Why is it so difficult to measure glucagon-like peptide-1 in a mouse?

AIMS/HYPOTHESIS

In humans, glucagon-like peptide-1 (GLP-1) is rapidly degraded by dipeptidyl peptidase-4 to a relatively stable metabolite, GLP-1(9-36)NH₂, which allows measurement of GLP-1 secretion. However, little is known about the kinetics of the GLP-1 metabolite in mice. We hypothesised that the GLP-1 metabolite is rapidly degraded in this species by neutral endopeptidase(s) (NEP[s]).

METHODS

We administered glucose, mixed meal or water orally to 256 mice, and took blood samples before and 2, 6, 10, 20, 30, 60 or 90 min after stimulation. To study the metabolism of the GLP-1 metabolite, i.v. GLP-1(9-36)NH₂ (800 fmol) or saline (154 mmol/l NaCl) was administered to 160 mice, some of which had a prior injection of a selective NEP 24.11 ± inhibitor (candoxatril, 5 mg/kg) or saline. Blood was collected before and 1, 2, 4 and 12 min after GLP-1/saline injection. Plasma GLP-1 levels were analysed using a customised single-site C-terminal ELISA, two different two-site ELISAs and MS.

RESULTS

GLP-1 secretion profiles after oral glucose administration differed markedly when assayed by C-terminal ELISA compared with sandwich ELISAs, with the former showing a far higher peak value and AUC. In mice injected with GLP-1(9-36)NH₂, immunoreactive GLP-1 plasma levels peaked at approximately 75 pmol/l at 1 min when measured with sandwich ELISAs, returning to baseline (~20 pmol/l) after 12 min, but remained elevated using the C-terminal ELISA (~90 pmol/l at 12 min). NEP 24.11 inhibition by candoxatril significantly attenuated GLP-1(9-36)NH₂ degradation in vivo and in vitro. MS identified GLP-1 fragments consistent with NEP 24.11 degradation.

CONCLUSIONS/INTERPRETATION

In mice, the GLP-1 metabolite is eliminated within a few minutes owing to endoproteolytic cleavage by NEP 24.11. Therefore, accurate measurement of GLP-1 secretion in mice requires assays for NEP 24.11 metabolites. Conventional sandwich ELISAs are inadequate because of endoproteolytic cleavage of the dipeptidyl peptidase-4-generated metabolite.

C9ORF72 interaction with cofilin modulates actin dynamics in motor neurons

Intronic hexanucleotide expansions in C9ORF72 are common in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia, but it is unknown whether loss of function, toxicity by the expanded RNA or dipeptides from non-ATG-initiated translation are responsible for the pathophysiology. We determined the interactome of C9ORF72 in motor neurons and found that C9ORF72 was present in a complex with cofilin and other actin binding proteins. Phosphorylation of cofilin was enhanced in C9ORF72-depleted motor neurons, in patient-derived lymphoblastoid cells, induced pluripotent stem cell-derived motor neurons and post-mortem brain samples from ALS patients. C9ORF72 modulates the activity of the small GTPases Arf6 and Rac1, resulting in enhanced activity of LIM-kinases 1 and 2 (LIMK1/2). This results in reduced axonal actin dynamics in C9ORF72-depleted motor neurons. Dominant negative Arf6 rescues this defect, suggesting that C9ORF72 acts as a modulator of small GTPases in a pathway that regulates axonal actin dynamics.

TDP-43 loss of function inhibits endosomal trafficking and alters trophic signaling in neurons

Nuclear clearance of TDP-43 into cytoplasmic aggregates is a key driver of neurodegeneration in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD), but the mechanisms are unclear. Here, we show that TDP-43 knockdown specifically reduces the number and motility of RAB11-positive recycling endosomes in dendrites, while TDP-43 overexpression has the opposite effect. This is associated with delayed transferrin recycling in TDP-43-knockdown neurons and decreased β2-transferrin levels in patient CSF Whole proteome quantification identified the upregulation of the ESCRT component VPS4B upon TDP-43 knockdown in neurons. Luciferase reporter assays and chromatin immunoprecipitation suggest that TDP-43 represses VPS4B transcription. Preventing VPS4B upregulation or expression of its functional antagonist ALIX restores trafficking of recycling endosomes. Proteomic analysis revealed the broad reduction in surface expression of key receptors upon TDP-43 knockdown, including ErbB4, the neuregulin 1 receptor. TDP-43 knockdown delays the surface delivery of ErbB4. ErbB4 overexpression, but not neuregulin 1 stimulation, prevents dendrite loss upon TDP-43 knockdown. Thus, impaired recycling of ErbB4 and other receptors to the cell surface may contribute to TDP-43-induced neurodegeneration by blocking trophic signaling.

Oxyntomodulin Identified as a Marker of Type 2 Diabetes and Gastric Bypass Surgery by Mass-spectrometry Based Profiling of Human Plasma

Low-abundance regulatory peptides, including metabolically important gut hormones, have shown promising therapeutic potential. Here, we present a streamlined mass spectrometry-based platform for identifying and characterizing low-abundance regulatory peptides in humans. We demonstrate the clinical applicability of this platform by studying a hitherto neglected glucose- and appetite-regulating gut hormone, namely, oxyntomodulin. Our results show that the secretion of oxyntomodulin in patients with type 2 diabetes is significantly impaired, and that its level is increased by more than 10-fold after gastric bypass surgery. Furthermore, we report that oxyntomodulin is co-distributed and co-secreted with the insulin-stimulating and appetite-regulating gut hormone glucagon-like peptide-1 (GLP-1), is inactivated by the same protease (dipeptidyl peptidase-4) as GLP-1 and acts through its receptor. Thus, oxyntomodulin may participate with GLP-1 in the regulation of glucose metabolism and appetite in humans. In conclusion, this mass spectrometry-based platform is a powerful resource for identifying and characterizing metabolically active low-abundance peptides.

Evidence of Extrapancreatic Glucagon Secretion in Man

Glucagon is believed to be a pancreas-specific hormone, and hyperglucagonemia has been shown to contribute significantly to the hyperglycemic state of patients with diabetes. This hyperglucagonemia has been thought to arise from α-cell insensitivity to suppressive effects of glucose and insulin combined with reduced insulin secretion. We hypothesized that postabsorptive hyperglucagonemia represents a gut-dependent phenomenon and subjected 10 totally pancreatectomized patients and 10 healthy control subjects to a 75-g oral glucose tolerance test and a corresponding isoglycemic intravenous glucose infusion. We applied novel analytical methods of plasma glucagon (sandwich ELISA and mass spectrometry-based proteomics) and show that 29-amino acid glucagon circulates in patients without a pancreas and that glucose stimulation of the gastrointestinal tract elicits significant hyperglucagonemia in these patients. These findings emphasize the existence of extrapancreatic glucagon (perhaps originating from the gut) in man and suggest that it may play a role in diabetes secondary to total pancreatectomy.

η-Secretase processing of APP inhibits neuronal activity in the hippocampus

Alzheimer disease (AD) is characterized by the accumulation of amyloid plaques, which are predominantly composed of amyloid-β peptide. Two principal physiological pathways either prevent or promote amyloid-β generation from its precursor, β-amyloid precursor protein (APP), in a competitive manner. Although APP processing has been studied in great detail, unknown proteolytic events seem to hinder stoichiometric analyses of APP metabolism in vivo. Here we describe a new physiological APP processing pathway, which generates proteolytic fragments capable of inhibiting neuronal activity within the hippocampus. We identify higher molecular mass carboxy-terminal fragments (CTFs) of APP, termed CTF-η, in addition to the long-known CTF-α and CTF-β fragments generated by the α- and β-secretases ADAM10 (a disintegrin and metalloproteinase 10) and BACE1 (β-site APP cleaving enzyme 1), respectively. CTF-η generation is mediated in part by membrane-bound matrix metalloproteinases such as MT5-MMP, referred to as η-secretase activity. η-Secretase cleavage occurs primarily at amino acids 504-505 of APP695, releasing a truncated ectodomain. After shedding of this ectodomain, CTF-η is further processed by ADAM10 and BACE1 to release long and short Aη peptides (termed Aη-α and Aη-β). CTFs produced by η-secretase are enriched in dystrophic neurites in an AD mouse model and in human AD brains. Genetic and pharmacological inhibition of BACE1 activity results in robust accumulation of CTF-η and Aη-α. In mice treated with a potent BACE1 inhibitor, hippocampal long-term potentiation was reduced. Notably, when recombinant or synthetic Aη-α was applied on hippocampal slices ex vivo, long-term potentiation was lowered. Furthermore, in vivo single-cell two-photon calcium imaging showed that hippocampal neuronal activity was attenuated by Aη-α. These findings not only demonstrate a major functionally relevant APP processing pathway, but may also indicate potential translational relevance for therapeutic strategies targeting APP processing.

The Impact II, a Very High-Resolution Quadrupole Time-of-Flight Instrument (QTOF) for Deep Shotgun Proteomics

Hybrid quadrupole time-of-flight (QTOF) mass spectrometry is one of the two major principles used in proteomics. Although based on simple fundamentals, it has over the last decades greatly evolved in terms of achievable resolution, mass accuracy, and dynamic range. The Bruker impact platform of QTOF instruments takes advantage of these developments and here we develop and evaluate the impact II for shotgun proteomics applications. Adaption of our heated liquid chromatography system achieved very narrow peptide elution peaks. The impact II is equipped with a new collision cell with both axial and radial ion ejection, more than doubling ion extraction at high tandem MS frequencies. The new reflectron and detector improve resolving power compared with the previous model up to 80%, i.e. to 40,000 at m/z 1222. We analyzed the ion current from the inlet capillary and found very high transmission (>80%) up to the collision cell. Simulation and measurement indicated 60% transfer into the flight tube. We adapted MaxQuant for QTOF data, improving absolute average mass deviations to better than 1.45 ppm. More than 4800 proteins can be identified in a single run of HeLa digest in a 90 min gradient. The workflow achieved high technical reproducibility (R2 > 0.99) and accurate fold change determination in spike-in experiments in complex mixtures. Using label-free quantification we rapidly quantified haploid against diploid yeast and characterized overall proteome differences in mouse cell lines originating from different tissues. Finally, after high pH reversed-phase fractionation we identified 9515 proteins in a triplicate measurement of HeLa peptide mixture and 11,257 proteins in single measurements of cerebellum—the highest proteome coverage reported with a QTOF instrument so far.

Side-chain to main-chain hydrogen bonding controls the intrinsic backbone dynamics of the amyloid precursor protein transmembrane helix

Many transmembrane helices contain serine and/or threonine residues whose side chains form intrahelical H-bonds with upstream carbonyl oxygens. Here, we investigated the impact of threonine side-chain/main-chain backbonding on the backbone dynamics of the amyloid precursor protein transmembrane helix. This helix consists of a N-terminal dimerization region and a C-terminal cleavage region, which is processed by γ-secretase to a series of products. Threonine mutations within this transmembrane helix are known to alter the cleavage pattern, which can lead to early-onset Alzheimer's disease. Circular dichroism spectroscopy and amide exchange experiments of synthetic transmembrane domain peptides reveal that mutating threonine enhances the flexibility of this helix. Molecular dynamics simulations show that the mutations reduce intrahelical amide H-bonding and H-bond lifetimes. In addition, the removal of side-chain/main-chain backbonding distorts the helix, which alters bending and rotation at a diglycine hinge connecting the dimerization and cleavage regions. We propose that the backbone dynamics of the substrate profoundly affects the way by which the substrate is presented to the catalytic site within the enzyme. Changing this conformational flexibility may thus change the pattern of proteolytic processing.

The Q Exactive HF, a Benchtop mass spectrometer with a pre-filter, high-performance quadrupole and an ultra-high-field Orbitrap analyzer

The quadrupole Orbitrap mass spectrometer (Q Exactive) made a powerful proteomics instrument available in a benchtop format. It significantly boosted the number of proteins analyzable per hour and has now evolved into a proteomics analysis workhorse for many laboratories. Here we describe the Q Exactive Plus and Q Exactive HF mass spectrometers, which feature several innovations in comparison to the original Q Exactive instrument. A low-resolution pre-filter has been implemented within the injection flatapole, preventing unwanted ions from entering deep into the system, and thereby increasing its robustness. A new segmented quadrupole, with higher fidelity of isolation efficiency over a wide range of isolation windows, provides an almost 2-fold improvement of transmission at narrow isolation widths. Additionally, the Q Exactive HF has a compact Orbitrap analyzer, leading to higher field strength and almost doubling the resolution at the same transient times. With its very fast isolation and fragmentation capabilities, the instrument achieves overall cycle times of 1 s for a top 15 to 20 higher energy collisional dissociation method. We demonstrate the identification of 5000 proteins in standard 90-min gradients of tryptic digests of mammalian cell lysate, an increase of over 40% for detected peptides and over 20% for detected proteins. Additionally, we tested the instrument on peptide phosphorylation enriched samples, for which an improvement of up to 60% class I sites was observed.

Deep proteomic evaluation of primary and cell line motoneuron disease models delineates major differences in neuronal characteristics

The fatal neurodegenerative disorders amyotrophic lateral sclerosis and spinal muscular atrophy are, respectively, the most common motoneuron disease and genetic cause of infant death. Various in vitro model systems have been established to investigate motoneuron disease mechanisms, in particular immortalized cell lines and primary neurons. Using quantitative mass-spectrometry-based proteomics, we compared the proteomes of primary motoneurons to motoneuron-like cell lines NSC-34 and N2a, as well as to non-neuronal control cells, at a depth of 10,000 proteins. We used this resource to evaluate the suitability of murine in vitro model systems for cell biological and biochemical analysis of motoneuron disease mechanisms. Individual protein and pathway analysis indicated substantial differences between motoneuron-like cell lines and primary motoneurons, especially for proteins involved in differentiation, cytoskeleton, and receptor signaling, whereas common metabolic pathways were more similar. The proteins associated with amyotrophic lateral sclerosis also showed distinct differences between cell lines and primary motoneurons, providing a molecular basis for understanding fundamental alterations between cell lines and neurons with respect to neuronal pathways with relevance for disease mechanisms. Our study provides a proteomics resource for motoneuron research and presents a paradigm of how mass-spectrometry-based proteomics can be used to evaluate disease model systems.

The backbone dynamics of the amyloid precursor protein transmembrane helix provides a rationale for the sequential cleavage mechanism of γ-secretase

The etiology of Alzheimer's disease depends on the relative abundance of different amyloid-β (Aβ) peptide species. These peptides are produced by sequential proteolytic cleavage within the transmembrane helix of the 99 residue C-terminal fragment of the amyloid precursor protein (C99) by the intramembrane protease γ-secretase. Intramembrane proteolysis is thought to require local unfolding of the substrate helix, which has been proposed to be cleaved as a homodimer. Here, we investigated the backbone dynamics of the substrate helix. Amide exchange experiments of monomeric recombinant C99 and of synthetic transmembrane domain peptides reveal that the N-terminal Gly-rich homodimerization domain exchanges much faster than the C-terminal cleavage region. MD simulations corroborate the differential backbone dynamics, indicate a bending motion at a diglycine motif connecting dimerization and cleavage regions, and detect significantly different H-bond stabilities at the initial cleavage sites. Our results are consistent with the following hypotheses about cleavage of the substrate: First, the GlyGly hinge may precisely position the substrate within γ-secretase such that its catalytic center must start proteolysis at the known initial cleavage sites. Second, the ratio of cleavage products formed by subsequent sequential proteolysis could be influenced by differential extents of solvation and by the stabilities of H-bonds at alternate initial sites. Third, the flexibility of the Gly-rich domain may facilitate substrate movement within the enzyme during sequential proteolysis. Fourth, dimerization may affect substrate processing by decreasing the dynamics of the dimerization region and by increasing that of the C-terminal part of the cleavage region.