Global, in situ analysis of the structural proteome in individuals with Parkinson's disease to identify a new class of biomarker.

Parkinson's disease (PD) is a prevalent neurodegenerative disease for which robust biomarkers are needed. Because protein structure reflects function, we tested whether global, in situ analysis of protein structural changes provides insight into PD pathophysiology and could inform a new concept of structural disease biomarkers. Using limited proteolysis-mass spectrometry (LiP-MS), we identified 76 structurally altered proteins in cerebrospinal fluid (CSF) of individuals with PD relative to healthy donors. These proteins were enriched in processes misregulated in PD, and some proteins also showed structural changes in PD brain samples. CSF protein structural information outperformed abundance information in discriminating between healthy participants and those with PD and improved the discriminatory performance of CSF measures of the hallmark PD protein α-synuclein. We also present the first analysis of inter-individual variability of a structural proteome in healthy individuals, identifying biophysical features of variable protein regions. Although independent validation is needed, our data suggest that global analyses of the human structural proteome will guide the development of novel structural biomarkers of disease and enable hypothesis generation about underlying disease processes.

Biomarker Candidates for Tumors Identified from Deep-Profiled Plasma Stem Predominantly from the Low Abundant Area.

The plasma proteome has the potential to enable a holistic analysis of the health state of an individual. However, plasma biomarker discovery is difficult due to its high dynamic range and variability. Here, we present a novel automated analytical approach for deep plasma profiling and applied it to a 180-sample cohort of human plasma from lung, breast, colorectal, pancreatic, and prostate cancers. Using a controlled quantitative experiment, we demonstrate a 257% increase in protein identification and a 263% increase in significantly differentially abundant proteins over neat plasma. In the cohort, we identified 2732 proteins. Using machine learning, we discovered biomarker candidates such as STAT3 in colorectal cancer and developed models that classify the diseased state. For pancreatic cancer, a separation by stage was achieved. Importantly, biomarker candidates came predominantly from the low abundance region, demonstrating the necessity to deeply profile because they would have been missed by shallow profiling.

Different syngeneic tumors show distinctive intrinsic tumor-immunity and mechanisms of actions (MOA) of anti-PD-1 treatment.

Cancers are immunologically heterogeneous. A range of immunotherapies target abnormal tumor immunity via different mechanisms of actions (MOAs), particularly various tumor-infiltrate leukocytes (TILs). We modeled loss of function (LOF) in four common anti-PD-1 antibody-responsive syngeneic tumors, MC38, Hepa1-6, CT-26 and EMT-6, by systematical depleting a series of TIL lineages to explore the mechanisms of tumor immunity and treatment. CD8+-T-cells, CD4+-T-cells, Treg, NK cells and macrophages were individually depleted through either direct administration of anti-marker antibodies/reagents or using DTR (diphtheria toxin receptor) knock-in mice, for some syngeneic tumors, where specific subsets were depleted following diphtheria toxin (DT) administration. These LOF experiments revealed distinctive intrinsic tumor immunity and thus different MOAs in their responses to anti-PD-1 antibody among different syngeneic tumors. Specifically, the intrinsic tumor immunity and the associated anti-PD-1 MOA were predominately driven by CD8+ cytotoxic TILs (CTL) in all syngeneic tumors, excluding Hepa1-6 where CD4+ Teff TILs played a key role. TIL-Treg also played a critical role in supporting tumor growth in all four syngeneic models as well as M2-macrophages. Pathway analysis using pharmacodynamic readouts of immuno-genomics and proteomics on MC38 and Hepa1-6 also revealed defined, but distinctive, immune pathways of activation and suppression between the two, closely associated with the efficacy and consistent with TIL-pharmacodynamic readouts. Understanding tumor immune-pathogenesis and treatment MOAs in the different syngeneic animal models, not only assists the selection of the right model for evaluating new immunotherapy of a given MOA, but also can potentially help to understand the potential disease mechanisms and strategize optimal immune-therapies in patients.

Urine Proteomics for Noninvasive Monitoring of Biomarkers in Bronchopulmonary Dysplasia.

INTRODUCTION: Current techniques to diagnose and/or monitor critically ill neonates with bronchopulmonary dysplasia (BPD) require invasive sampling of body fluids, which is suboptimal in these frail neonates. We tested our hypothesis that it is feasible to use noninvasively collected urine samples for proteomics from extremely low gestational age newborns (ELGANs) at risk for BPD to confirm previously identified proteins and biomarkers associated with BPD. METHODS: We developed a robust high-throughput urine proteomics methodology that requires only 50 µL of urine. We utilized the methodology with a proof-of-concept study validating proteins previously identified in invasively collected sample types such as blood and/or tracheal aspirates on urine collected within 72 h of birth from ELGANs (gestational age [26 ± 1.2] weeks) who were admitted to a single Neonatal Intensive Care Unit (NICU), half of whom eventually developed BPD (n = 21), while the other half served as controls (n = 21). RESULTS: Our high-throughput urine proteomics approach clearly identified several BPD-associated changes in the urine proteome recapitulating expected blood proteome changes, and several urinary proteins predicted BPD risk. Interestingly, 16 of the identified urinary proteins are known targets of drugs approved by the Food and Drug Administration. CONCLUSION: In addition to validating numerous proteins, previously found in invasively collected blood, tracheal aspirate, and bronchoalveolar lavage, that have been implicated in BPD pathophysiology, urine proteomics also suggested novel potential therapeutic targets. Ease of access to urine could allow for sequential proteomic evaluations for longitudinal monitoring of disease progression and impact of therapeutic intervention in future studies.

FLEXIQuant-LF to quantify protein modification extent in label-free proteomics data.

Improvements in LC-MS/MS methods and technology have enabled the identification of thousands of modified peptides in a single experiment. However, protein regulation by post-translational modifications (PTMs) is not binary, making methods to quantify the modification extent crucial to understanding the role of PTMs. Here, we introduce FLEXIQuant-LF, a software tool for large-scale identification of differentially modified peptides and quantification of their modification extent without knowledge of the types of modifications involved. We developed FLEXIQuant-LF using label-free quantification of unmodified peptides and robust linear regression to quantify the modification extent of peptides. As proof of concept, we applied FLEXIQuant-LF to data-independent-acquisition (DIA) data of the anaphase promoting complex/cyclosome (APC/C) during mitosis. The unbiased FLEXIQuant-LF approach to assess the modification extent in quantitative proteomics data provides a better understanding of the function and regulation of PTMs. The software is available at https://github.com/SteenOmicsLab/FLEXIQuantLF.

Tau PTM Profiles Identify Patient Heterogeneity and Stages of Alzheimer's Disease.

To elucidate the role of Tau isoforms and post-translational modification (PTM) stoichiometry in Alzheimer's disease (AD), we generated a high-resolution quantitative proteomics map of 95 PTMs on multiple isoforms of Tau isolated from postmortem human tissue from 49 AD and 42 control subjects. Although Tau PTM maps reveal heterogeneity across subjects, a subset of PTMs display high occupancy and frequency for AD, suggesting importance in disease. Unsupervised analyses indicate that PTMs occur in an ordered manner, leading to Tau aggregation. The processive addition and minimal set of PTMs associated with seeding activity was further defined by analysis of size-fractionated Tau. To summarize, features in the Tau protein critical for disease intervention at different stages of disease are identified, including enrichment of 0N and 4R isoforms, underrepresentation of the C terminus, an increase in negative charge in the proline-rich region (PRR), and a decrease in positive charge in the microtubule binding domain (MBD).

MassIVE.quant: a community resource of quantitative mass spectrometry-based proteomics datasets.

MassIVE.quant is a repository infrastructure and data resource for reproducible quantitative mass spectrometry-based proteomics, which is compatible with all mass spectrometry data acquisition types and computational analysis tools. A branch structure enables MassIVE.quant to systematically store raw experimental data, metadata of the experimental design, scripts of the quantitative analysis workflow, intermediate input and output files, as well as alternative reanalyses of the same dataset.

Phosphorylation of ACTN4 Leads to Podocyte Vulnerability and Proteinuric Glomerulosclerosis.

BACKGROUND: Genetic mutations in α-actinin-4 (ACTN4)-an important actin crosslinking cytoskeletal protein that provides structural support for kidney podocytes-have been linked to proteinuric glomerulosclerosis in humans. However, the effect of post-translational modifications of ACTN4 on podocyte integrity and kidney function is not known. METHODS: Using mass spectrometry, we found that ACTN4 is phosphorylated at serine (S) 159 in human podocytes. We used phosphomimetic and nonphosphorylatable ACTN4 to comprehensively study the effects of this phosphorylation in vitro and in vivo. We conducted x-ray crystallography, F-actin binding and bundling assays, and immunofluorescence staining to evaluate F-actin alignment. Microfluidic organ-on-a-chip technology was used to assess for detachment of podocytes simultaneously exposed to fluid flow and cyclic strain. We then used CRISPR/Cas9 to generate mouse models and assessed for renal injury by measuring albuminuria and examining kidney histology. We also performed targeted mass spectrometry to determine whether high extracellular glucose or TGF-ß levels increase phosphorylation of ACTN4. RESULTS: Compared with the wild type ACTN4, phosphomimetic ACTN4 demonstrated increased binding and bundling activity with F-actin in vitro. Phosphomimetic Actn4 mouse podocytes exhibited more spatially correlated F-actin alignment and a higher rate of detachment under mechanical stress. Phosphomimetic Actn4 mice developed proteinuria and glomerulosclerosis after subtotal nephrectomy. Moreover, we found that exposure to high extracellular glucose or TGF-ß stimulates phosphorylation of ACTN4 at S159 in podocytes. CONCLUSIONS: These findings suggest that increased phosphorylation of ACTN4 at S159 leads to biochemical, cellular, and renal pathology that is similar to pathology resulting from human disease-causing mutations in ACTN4. ACTN4 may mediate podocyte injury as a consequence of both genetic mutations and signaling events that modulate phosphorylation.

Combining Precursor and Fragment Information for Improved Detection of Differential Abundance in Data Independent Acquisition.

In bottom-up, label-free discovery proteomics, biological samples are acquired in a data-dependent (DDA) or data-independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance and lead to false positive or false negative conclusions.We hypothesized that the combined use of MS1 and MS2 quantitative signals could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2-combined method increased the coverage of known activated pathways.Since recent technological developments continue to increase the quality of MS1 signals (e.g. using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.

Systematic Comparison of Strategies for the Enrichment of Lysosomes by Data Independent Acquisition.

In mammalian cells, the lysosome is the main organelle for the degradation of macromolecules and the recycling of their building blocks. Correct lysosomal function is essential, and mutations in every known lysosomal hydrolase result in so-called lysosomal storage disorders, a group of rare and often fatal inherited diseases. Furthermore, it is becoming more and more apparent that lysosomes play also decisive roles in other diseases, such as cancer and common neurodegenerative disorders. This leads to an increasing interest in the proteomic analysis of lysosomes for which enrichment is a prerequisite. In this study, we compared the four most common strategies for the enrichment of lysosomes using data-independent acquisition. We performed centrifugation at 20,000 × g to generate an organelle-enriched pellet, two-step sucrose density gradient centrifugation, enrichment by superparamagnetic iron oxide nanoparticles (SPIONs), and immunoprecipitation using a 3xHA tagged version of the lysosomal membrane protein TMEM192. Our results show that SPIONs and TMEM192 immunoprecipitation outperform the other approaches with enrichment factors of up to 118-fold for certain proteins relative to whole cell lysates. Furthermore, we achieved an increase in identified lysosomal proteins and a higher reproducibility in protein intensities for label-free quantification in comparison to the other strategies.

Surpassing 10 000 identified and quantified proteins in a single run by optimizing current LC-MS instrumentation and data analysis strategy.

Comprehensive proteome quantification is crucial for a better understanding of underlying mechanisms of diseases. Liquid chromatography mass spectrometry (LC-MS) has become the method of choice for comprehensive proteome quantification due to its power and versatility. Even though great advances have been made in recent years, full proteome coverage for complex samples remains challenging due to the high dynamic range of protein expression. Additionally, when studying disease regulatory proteins, biomarkers or potential drug targets are often low abundant, such as for instance kinases and transcription factors. Here, we show that with improvements in chromatography and data analysis the single shot proteome coverage can go beyond 10 000 proteins in human tissue. In a testis cancer study, we quantified 11 200 proteins using data independent acquisition (DIA). This depth was achieved with a false discovery rate of 1% which was experimentally validated using a two species test. We introduce the concept of hybrid libraries which combines the strength of direct searching of DIA data as well as the use of large project-specific or published DDA data sets. Remarkably deep proteome coverage is possible using hybrid libraries without the additional burden of creating a project-specific library. Within the testis cancer set, we found a large proportion of proteins in an altered expression (in total: 3351; 1453 increased in cancer). Many of these proteins could be linked to the hallmarks of cancer. For example, the complement system was downregulated which helps to evade the immune response and chromosomal replication was upregulated indicating a dysregulated cell cycle.

Analysis of 1508 Plasma Samples by Capillary-Flow Data-Independent Acquisition Profiles Proteomics of Weight Loss and Maintenance.

Comprehensive, high throughput analysis of the plasma proteome has the potential to enable holistic analysis of the health state of an individual. Based on our own experience and the evaluation of recent large-scale plasma mass spectrometry (MS) based proteomic studies, we identified two outstanding challenges: slow and delicate nano-flow liquid chromatography (LC) and irreproducibility of identification of data-dependent acquisition (DDA). We determined an optimal solution reducing these limitations with robust capillary-flow data-independent acquisition (DIA) MS. This platform can measure 31 plasma proteomes per day. Using this setup, we acquired a large-scale plasma study of the diet, obesity and genes dietary (DiOGenes) comprising 1508 samples. Proving the robustness, the complete acquisition was achieved on a single analytical column. Totally, 565 proteins (459 identified with two or more peptide sequences) were profiled with 74% data set completeness. On average 408 proteins (5246 peptides) were identified per acquisition (319 proteins in 90% of all acquisitions). The workflow reproducibility was assessed using 34 quality control pools acquired at regular intervals, resulting in 92% data set completeness with CVs for protein measurements of 10.9%.The profiles of 20 apolipoproteins could be profiled revealing distinct changes. The weight loss and weight maintenance resulted in sustained effects on low-grade inflammation, as well as steroid hormone and lipid metabolism, indicating beneficial effects. Comparison to other large-scale plasma weight loss studies demonstrated high robustness and quality of biomarker candidates identified. Tracking of nonenzymatic glycation indicated a delayed, slight reduction of glycation in the weight maintenance phase. Using stable-isotope-references, we could directly and absolutely quantify 60 proteins in the DIA.In conclusion, we present herein the first large-scale plasma DIA study and one of the largest clinical research proteomic studies to date. Application of this fast and robust workflow has great potential to advance biomarker discovery in plasma.

Comparison of Protein Quantification in a Complex Background by DIA and TMT Workflows with Fixed Instrument Time.

Label-free quantification (LFQ) and isobaric labeling quantification (ILQ) are among the most popular protein quantification workflows in discovery proteomics. Here, we compared the TMT SPS/MS3 10-plex workflow to a label free single shot data-independent acquisition (DIA) workflow on a controlled sample set. The sample set consisted of ten samples derived from 10 biological replicates of mouse cerebelli spiked with the UPS2 protein standard in five different concentrations. For a fair comparison, we matched the instrument time for the two workflows. The LC-MS data were acquired at two facilities to assess interlaboratory reproducibility. Both methods resulted in a high proteome coverage (>5000 proteins) with low missing values on protein level (<2%). The TMT workflow led to 15-20% more identified proteins and a slightly better quantitative precision, whereas the quantitative accuracy was better for the DIA method. The quantitative performance was benchmarked by the number of true positives (UPS2 proteins) within the top 100 candidates. TMT and DIA showed a similar performance. The quantitative performance of the DIA data stayed in a similar range when searching the spectra against a fasta database directly, instead of using a project-specific library. Our experiments also demonstrated that both workflows are readily transferrable between facilities.

Multisystem Analysis of Mycobacterium tuberculosis Reveals Kinase-Dependent Remodeling of the Pathogen-Environment Interface.

Tuberculosis is the leading killer among infectious diseases worldwide. Increasing multidrug resistance has prompted new approaches for tuberculosis drug development, including targeted inhibition of virulence determinants and of signaling cascades that control many downstream pathways. We used a multisystem approach to determine the effects of a potent small-molecule inhibitor of the essential Mycobacterium tuberculosis Ser/Thr protein kinases PknA and PknB. We observed differential levels of phosphorylation of many proteins and extensive changes in levels of gene expression, protein abundance, cell wall lipids, and intracellular metabolites. The patterns of these changes indicate regulation by PknA and PknB of several pathways required for cell growth, including ATP synthesis, DNA synthesis, and translation. These data also highlight effects on pathways for remodeling of the mycobacterial cell envelope via control of peptidoglycan turnover, lipid content, a SigE-mediated envelope stress response, transmembrane transport systems, and protein secretion systems. Integrated analysis of phosphoproteins, transcripts, proteins, and lipids identified an unexpected pathway whereby threonine phosphorylation of the essential response regulator MtrA decreases its DNA binding activity. Inhibition of this phosphorylation is linked to decreased expression of genes for peptidoglycan turnover, and of genes for mycolyl transferases, with concomitant changes in mycolates and glycolipids in the cell envelope. These findings reveal novel roles for PknA and PknB in regulating multiple essential cell functions and confirm that these kinases are potentially valuable targets for new antituberculosis drugs. In addition, the data from these linked multisystems provide a valuable resource for future targeted investigations into the pathways regulated by these kinases in the M. tuberculosis cell.IMPORTANCE Tuberculosis is the leading killer among infectious diseases worldwide. Increasing drug resistance threatens efforts to control this epidemic; thus, new antitubercular drugs are urgently needed. We performed an integrated, multisystem analysis of Mycobacterium tuberculosis responses to inhibition of its two essential serine/threonine protein kinases. These kinases allow the bacterium to adapt to its environment by phosphorylating cellular proteins in response to extracellular signals. We identified differentially phosphorylated proteins, downstream changes in levels of specific mRNA and protein abundance, and alterations in the metabolite and lipid content of the cell. These results include changes previously linked to growth arrest and also reveal new roles for these kinases in regulating essential processes, including growth, stress responses, transport of proteins and other molecules, and the structure of the mycobacterial cell envelope. Our multisystem data identify PknA and PknB as promising targets for drug development and provide a valuable resource for future investigation of their functions.

Costs of life - Dynamics of the protein inventory of Staphylococcus aureus during anaerobiosis.

Absolute protein quantification was applied to follow the dynamics of the cytoplasmic proteome of Staphylococcus aureus in response to long-term oxygen starvation. For 1,168 proteins, the majority of all expressed proteins, molecule numbers per cell have been determined to monitor the cellular investments in single branches of bacterial life for the first time. In the presence of glucose the anaerobic protein pattern is characterized by increased amounts of glycolytic and fermentative enzymes such as Eno, GapA1, Ldh1, and PflB. Interestingly, the ferritin-like protein FtnA belongs to the most abundant proteins during anaerobic growth. Depletion of glucose finally leads to an accumulation of different enzymes such as ArcB1, ArcB2, and ArcC2 involved in arginine deiminase pathway. Concentrations of 29 exo- and 78 endometabolites were comparatively assessed and have been integrated to the metabolic networks. Here we provide an almost complete picture on the response to oxygen starvation, from signal transduction pathways to gene expression pattern, from metabolic reorganization after oxygen depletion to beginning cell death and lysis after glucose exhaustion. This experimental approach can be considered as a proof of principle how to combine cell physiology with quantitative proteomics for a new dimension in understanding simple life processes as an entity.

FLEXITau: Quantifying Post-translational Modifications of Tau Protein in Vitro and in Human Disease.

Tauopathies, including Alzheimer's disease (AD), are associated with the aggregation of modified microtubule associated protein tau. This pathological state of tau is often referred to as "hyperphosphorylated". Due to limitations in technology, an accurate quantitative description of this state is lacking. Here, a mass spectrometry-based assay, FLEXITau, is presented to measure phosphorylation stoichiometry and provide an unbiased quantitative view of the tau post-translational modification (PTM) landscape. The power of this assay is demonstrated by measuring the state of hyperphosphorylation from tau in a cellular model for AD pathology, mapping, and calculating site occupancies for over 20 phosphorylations. We further employ FLEXITau to define the tau PTM landscape present in AD post-mortem brain. As shown in this study, the application of this assay provides mechanistic understanding of tau pathology that could lead to novel therapeutics, and we envision its further use in prognostic and diagnostic approaches for tauopathies.

Quantitative prediction of genome-wide resource allocation in bacteria.

Predicting resource allocation between cell processes is the primary step towards decoding the evolutionary constraints governing bacterial growth under various conditions. Quantitative prediction at genome-scale remains a computational challenge as current methods are limited by the tractability of the problem or by simplifying hypotheses. Here, we show that the constraint-based modeling method Resource Balance Analysis (RBA), calibrated using genome-wide absolute protein quantification data, accurately predicts resource allocation in the model bacterium Bacillus subtilis for a wide range of growth conditions. The regulation of most cellular processes is consistent with the objective of growth rate maximization except for a few suboptimal processes which likely integrate more complex objectives such as coping with stressful conditions and survival. As a proof of principle by using simulations, we illustrated how calibrated RBA could aid rational design of strains for maximizing protein production, offering new opportunities to investigate design principles in prokaryotes and to exploit them for biotechnological applications.

Advancing Urinary Protein Biomarker Discovery by Data-Independent Acquisition on a Quadrupole-Orbitrap Mass Spectrometer.

The promises of data-independent acquisition (DIA) strategies are a comprehensive and reproducible digital qualitative and quantitative record of the proteins present in a sample. We developed a fast and robust DIA method for comprehensive mapping of the urinary proteome that enables large scale urine proteomics studies. Compared to a data-dependent acquisition (DDA) experiments, our DIA assay doubled the number of identified peptides and proteins per sample at half the coefficients of variation observed for DDA data (DIA = ∼8%; DDA = ∼16%). We also tested different spectral libraries and their effects on overall protein and peptide identifications and their reproducibilities, which provided clear evidence that sample type-specific spectral libraries are preferred for reliable data analysis. To show applicability for biomarker discovery experiments, we analyzed a sample set of 87 urine samples from children seen in the emergency department with abdominal pain. The whole set was analyzed with high proteome coverage (∼1300 proteins/sample) in less than 4 days. The data set revealed excellent biomarker candidates for ovarian cyst and urinary tract infection. The improved throughput and quantitative performance of our optimized DIA workflow allow for the efficient simultaneous discovery and verification of biomarker candidates without the requirement for an early bias toward selected proteins.

MStern Blotting-High Throughput Polyvinylidene Fluoride (PVDF) Membrane-Based Proteomic Sample Preparation for 96-Well Plates.

We describe a 96-well plate compatible membrane-based proteomic sample processing method, which enables the complete processing of 96 samples (or multiples thereof) within a single workday. This method uses a large-pore hydrophobic PVDF membrane that efficiently adsorbs proteins, resulting in fast liquid transfer through the membrane and significantly reduced sample processing times. Low liquid transfer speeds have prevented the useful 96-well plate implementation of FASP as a widely used membrane-based proteomic sample processing method. We validated our approach on whole-cell lysate and urine and cerebrospinal fluid as clinically relevant body fluids. Without compromising peptide and protein identification, our method uses a vacuum manifold and circumvents the need for digest desalting, making our processing method compatible with standard liquid handling robots. In summary, our new method maintains the strengths of FASP and simultaneously overcomes one of the major limitations of FASP without compromising protein identification and quantification.

First description of small proteins encoded by spRNAs in Methanosarcina mazei strain Gö1.

In Methanosarcina mazei several small RNAs have been identified containing a small putative open reading frame (sORF) and thus classified as spRNAs. Here, we report on the first detection of three small proteins in M. mazei encoded by spRNAs using LC-MS/MS analysis of total protein extracts of cells grown under various stress conditions. Each spRNA shows high conservation in Methanosarcina species with regard to the sORF and the flanking non-coding RNA regions, moreover the predicted RNA structures are as well highly conserved. Characterizing the respective transcript levels in response to several stress conditions by northern blots demonstrated an enormous decrease of spRNA36 and spRNA44 during stationary growth (to less than 5%), and a significant increase of spRNA36 (2.5-fold) in response to nitrogen limitation. spRNA41, however, was only detected by RNA-Seq approaches. Quantification of the small proteins by LC-MS/MS using synthetic stable isotope labeled oligopeptides as standards indicated that the concentration of oligopetide36 and 41 in mid exponential phase is induced under nitrogen limitation, which in case of oligopeptide36 is in accordance with its transcript level. The relative amount of the three oligopeptides did not change upon entering stationary growth phase, even though the transcript levels decreased dramatically. Additional production of the oligopeptides in M. mazei did not result in any evident phenotype under standard or nitrogen limiting growth conditions. However, overall the transcript levels of several genes involved in carbon metabolism or in heat shock response were reduced 2-3 fold due to the overproduction, though no sORF specific change was observed. Based on our findings we hypothesize that oligopeptide36 might have a regulatory function in nitrogen metabolism by modulating the activity of a yet unknown target protein involved in the central nitrogen metabolism.