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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Identification of integrated proteomics and transcriptomics signature of alcohol-associated liver disease using machine learning

Distinguishing between alcohol-associated hepatitis (AH) and alcohol-associated cirrhosis (AC) remains a diagnostic challenge. In this study, we used machine learning with transcriptomics and proteomics data from liver tissue and peripheral mononuclear blood cells (PBMCs) to classify patients with alcohol-associated liver disease. The conditions in the study were AH, AC, and healthy controls. We processed 98 PBMC RNAseq samples, 55 PBMC proteomic samples, 48 liver RNAseq samples, and 53 liver proteomic samples. First, we built separate classification and feature selection pipelines for transcriptomics and proteomics data. The liver tissue models were validated in independent liver tissue datasets. Next, we built integrated gene and protein expression models that allowed us to identify combined gene-protein biomarker panels. For liver tissue, we attained 90% nested-cross validation accuracy in our dataset and 82% accuracy in the independent validation dataset using transcriptomic data. We attained 100% nested-cross validation accuracy in our dataset and 61% accuracy in the independent validation dataset using proteomic data. For PBMCs, we attained 83% and 89% accuracy with transcriptomic and proteomic data, respectively. The integration of the two data types resulted in improved classification accuracy for PBMCs, but not liver tissue. We also identified the following gene-protein matches within the gene-protein biomarker panels: CLEC4M-CLC4M, GSTA1-GSTA2 for liver tissue and SELENBP1-SBP1 for PBMCs. In this study, machine learning models had high classification accuracy for both transcriptomics and proteomics data, across liver tissue and PBMCs. The integration of transcriptomics and proteomics into a multi-omics model yielded improvement in classification accuracy for the PBMC data. The set of integrated gene-protein biomarkers for PBMCs show promise toward developing a liquid biopsy for alcohol-associated liver disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Robust surfactant-assisted one-pot sample preparation for label-free single-cell and nanoscale proteomics

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk cells. However, such bulk measurement obscures cell to cell heterogeneity, precluding proteome profiling of single cells and small numbers of cells of interest. To address this issue, in recent 5 years there are a surge of small sample preparation methods developed for robust effective collection and processing of single cells and small numbers of cells for in-depth MS-based proteome profiling. Based on their broad accessibility, they can be categorized into two types: specific device- and standard PCR tube- or multi-well plate-based methods. Herein we describe the detailed protocol of our recently developed, easily adoptable, Surfactant-assisted One-Pot (SOP) sample preparation coupled with MS method termed SOP-MS for label-free single-cell and nanoscale proteomics. SOP-MS capitalizes on the combination of a MS-compatible surfactant, DDM (n-Dodecyl-ß-D-maltoside), and standard low-bind PCR tube or multi-well plate for ‘all-in-one’ one-pot sample preparation without sample transfer. With its robust and convenient features, SOP-MS can be readily implemented in any MS laboratory for single-cell and nanoscale proteomics. With further improvements in MS detection sensitivity and sample throughput, we believe that SOP-MS could open an avenue for single-cell proteomics with broad applicability in the biological and biomedical research.

Single-cell proteomics, nanoscale proteomics, SOP-↗
DOE OSTI2022

Determining protein polarization proteome-wide using physical dissection of individual Stentor coeruleus cells

Cellular components are non-randomly arranged with respect to the shape and polarity of the whole cell. Patterning within cells can extend down to the level of individual proteins and mRNA. But how much of the proteome is actually localized with respect to cell polarity axes? Proteomics combined with cellular fractionation has shown that most proteins localize to one or more organelles but does not tell us how many proteins have a polarized localization with respect to the large-scale polarity axes of the intact cell. Genome-wide localization studies in yeast found that only a few percent of proteins have a localized position relative to the cell polarity axis defined by sites of polarized cell growth. Here, we describe an approach for analyzing protein distribution within a cell with a visibly obvious global patterning - the giant ciliate Stentor coeruleus. Ciliates, including Stentor, have highly polarized cell shapes with visible surface patterning. A Stentor cell is roughly 2mmlong, allowing a ‘‘proteomic dissection’’ in which microsurgery is used to separate cellular fragments along the anterior-posterior axis, followed by comparative proteomic analysis. In our analysis, 25% of the proteome, including signaling proteins, centrin/SFI proteins, and GAS2 orthologs, shows a polarized location along the cell’s anterior-posterior axis. We conclude that a large proportion of all proteins are polarized with respect to global cell polarity axes and that proteomic dissection provides a simple and effective approach for spatial proteomics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Spatial top-down proteomics for the functional characterization of human kidney

Background: The Human Proteome Project has credibly detected nearly 93% of the roughly 20,000 proteins which are predicted by the human genome. However, the proteome is enigmatic, where alterations in amino acid sequences from polymorphisms and alternative splicing, errors in translation, and post-translational modifications result in a proteome depth estimated at several million unique proteoforms. Recently mass spectrometry has been demonstrated in several landmark efforts mapping the human proteoform landscape in bulk analyses. Herein, we developed an integrated workflow for characterizing proteoforms from human tissue in a spatially resolved manner by coupling laser capture microdissection, nanoliter-scale sample preparation, and mass spectrometry imaging. Results: Using healthy human kidney sections as the case study, we focused our analyses on the major functional tissue units including glomeruli, tubules, and medullary rays. After laser capture microdissection, these isolated functional tissue units were processed with microPOTS (microdroplet processing in one-pot for trace samples) for sensitive top-down proteomics measurement. This provided a quantitative database of 616 proteoforms that was further leveraged as a library for mass spectrometry imaging with near-cellular spatial resolution over the entire section. Notably, several mitochondrial proteoforms were found to be differentially abundant between glomeruli and convoluted tubules, and further spatial contextualization was provided by mass spectrometry imaging confirming unique differences identified by microPOTS, and further expanding the field-of-view for unique distributions such as enhanced abundance of a truncated form (1-74) of ubiquitin within cortical regions. Conclusions: We developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Where of the 20 differentially abundant proteoforms identified as discriminate between tubules and glomeruli by microPOTS, the vast majority of tubular proteoforms were of mitochondrial origin (8 of 10) where discriminate proteoforms in glomeruli were primarily hemoglobin subunits (9 of 10). These trends were also identified within ion images demonstrating spatially resolved characterization of proteoforms that has the potential to reshape discovery-based proteomics because the proteoforms are the ultimate effector of cellular functions. Applications of this technology have the potential to unravel etiology and pathophysiology of disease states, informing on biologically active proteoforms, which remodel the proteomic landscape in chronic and acute disorders.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Proteomes reveal metabolic capabilities of Yarrowia lipolytica for biological upcycling of polyethylene into high-value chemicals

ABSTRACT Polyolefins derived from plastic wastes are recalcitrant for biological upcycling. However, chemical depolymerization of polyolefins can generate depolymerized plastic (DP) oil, comprising of a complex mixture of saturated, unsaturated, even, and odd hydrocarbons suitable for biological conversion. While DP oil contains a rich carbon and energy source, it is inhibitory to cells. Understanding and harnessing robust metabolic capabilities of microorganisms to upcycle the hydrocarbons in DP oil, both naturally and unnaturally occurring, into high-value chemicals are limited. Here, we discovered that an oleaginous yeast, Yarrowia lipolytica, undergoing short-term adaptation to DP oil robustly utilized a wide range of hydrocarbons for cell growth and production of citric acid and neutral lipids. When growing on hydrocarbons, Y. lipolytica partitioned into planktonic and oil-bound cells with each exhibiting distinct proteomes and amino acid distributions invested in establishing these proteomes. Significant proteome reallocation toward energy and lipid metabolism, belonging to 2 of the 23 Eukaryotic Orthologous Groups classes C and I, enabled robust growth of Y. lipolytica on hydrocarbons, with n-hexadecane as the preferential substrate. This investment was even higher for growth on DP oil where classes C and I were ranked one and two, respectively, and many associated proteins and pathways were expressed and upregulated including the hydrocarbon degradation pathway, Krebs cycle, glyoxylate shunt and, unexpectedly, propionate metabolism. However, a reduction in proteome allocation for protein biosynthesis, at the expense of the observed increase toward energy and lipid metabolisms, might have caused the inhibitory effect of DP oil on cell growth. IMPORTANCE Sustainable processes for biological upcycling of plastic wastes in a circular bioeconomy are needed to promote decarbonization and reduce environmental pollution due to increased plastic consumption, incineration, and landfill storage. Strain characterization and proteomic analysis revealed the robust metabolic capabilities of Yarrowia lipolytica to upcycle polyethylene into high-value chemicals. Significant proteome reallocation toward energy and lipid metabolisms was required for robust growth on hydrocarbons with n-hexadecane as the preferential substrate. However, an apparent over-investment in these same categories to utilize complex depolymerized plastic (DP) oil came at the expense of protein biosynthesis, limiting cell growth. Taken together, this study elucidates how Y. lipolytica activates its metabolism to utilize DP oil and establishes Y. lipolytica as a promising host for the upcycling of plastic wastes.

1-alkenes↗
DOE OSTI2023

Evaluating Linear Ion Trap for MS3-Based Multiplexed Single-Cell Proteomics

There is a growing demand to develop high-throughput and high-sensitivity mass spectrometry methods for single-cell proteomics. The commonly used isobaric labeling-based multiplexed single-cell proteomics approach suffers from distorted protein quantification due to co-isolated interfering ions during MS/MS fragmentation, also known as ratio compression. We reasoned that the use of MS3-based quantification could mitigate ratio compression and provide better quantification. However, previous studies indicated reduced proteome coverages in the MS3 method, likely due to long duty cycle time and ion losses during multilevel ion selection and fragmentation. Here, in this paper, we described an improved MS acquisition method for MS3-based single-cell proteomics by employing a linear ion trap to measure reporter ions. We demonstrated that linear ion trap can increase the proteome coverages for single-cell-level peptides with even higher gain obtained via the MS3 method. The optimized real-time search MS3 method was further applied to study the immune activation of single macrophages. Among a total of 126 single cells studied, over 1200 and 1000 proteins were quantifiable when at least 50 and 75% nonmissing data were required, respectively. Our evaluation also revealed several limitations of the low-resolution ion trap detector for multiplexed single-cell proteomics and suggested experimental solutions to minimize their impacts on single-cell analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Coupling Microdroplet-Based Sample Preparation, Multiplexed Isobaric Labeling, and Nanoflow Peptide Fractionation for Deep Proteome Profiling of the Tissue Microenvironment

There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity in a cell-type-specific manner to better understand and predict the function of complex biological systems such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverage due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (microdroplet processing in one pot for trace samples), multiplexed isobaric labeling, and a nanoflow peptide fractionation approach. The integrated workflow allowed us to maximize proteome coverage of laser-isolated tissue samples containing nanogram levels of proteins. We demonstrated that the deep spatial proteomics platform can quantify more than 5000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 μm2) and differentiate unique protein abundance patterns in pancreas. Furthermore, the use of the microPOTS chip eliminated the requirement for advanced microfabrication capabilities and specialized nanoliter liquid handling equipment, making it more accessible to proteomic laboratories.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Facile One-Pot Nanoproteomics for Label-Free Proteome Profiling of 50–1000 Mammalian Cells

Recent advances in sample preparation enable label-free MS-based proteome profiling of small numbers of mammalian cells. However, specific devices are often required to downscale sample processing volume from the standard 50-200 µL to sub-µL for effective nanoproteomics, which greatly impedes the implementation of current nanoproteomics methods by broad proteomics research community. Here we report a facile one-pot nanoproteomics method termed SOPs-MS (Surfactant-assisted One-Pot sample processing at the standard volume coupled with MS) for convenient proteome profiling of 50-1000 mammalian cells. Building upon our recent development of SOP-MS for label-free single-cell proteomics at low µL volume (Commun Bio 2021, 4, 265), we have systematically evaluated its processing volume at 10-200 µL using 100 human cells for robust reproducible nanoproteomic analysis. The processing volume of 50 µL which is in the range of volume for standard proteomics sample preparation, has been selected for easy sample handling with benchtop micropipette. Using the commonly accessible LC-MS platform, SOPs-MS allows for reliable label-free quantification of ~1200-2700 protein groups from 50-1000 MCF10A cells. When applied to small subpopulations of mouse colon crypt cells, SOPs-MS can reveal distinct protein signatures between any two subpopulation cells with identification of ~1500-2500 protein groups for each subpopulation. SOPs-MS may pave the way for routine deep proteome profiling of small numbers of cells as well as low-input samples.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Spatially Resolved Mass Spectrometry at the Single Cell: Recent Innovations in Proteomics and Metabolomics

Biological systems are composed of heterogeneous populations of cells that intercommunicate to form a functional living tissue. Biological function varies greatly across populations of cells, as each single cell has a unique transcriptome, proteome, and metabolome that translates to functional differences within single species and across kingdoms. Over the past decade, substantial advancements in our ability to characterize omic profiles on a single cell level have occurred, including in multiple spectroscopic and mass spectrometry (MS)-based techniques. Of these technologies, spatially resolved mass spectrometry approaches, including mass spectrometry imaging (MSI), have shown the most progress for single cell proteomics and metabolomics. For example, reporter-based methods using heavy metal tags have allowed for targeted MS investigation of the proteome at the subcellular level, and development of technologies such as laser ablation electrospray ionization mass spectrometry (LAESI-MS) now mean that dynamic metabolomics can be performed in situ. In this Perspective, we showcase advancements in single cell spatial metabolomics and proteomics over the past decade and highlight important aspects related to high-throughput screening, data analysis, and more which are vital to the success of achieving proteomic and metabolomic profiling at the single cell scale. Finally, using this broad literature summary, we provide a perspective on how the next decade may unfold in the area of single cell MS-based proteomics and metabolomics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ~2500 proteins and precise quantification of ~1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A seed-like proteome in oil-rich tubers

There are numerous examples of plant organs or developmental stages that are desiccation-tolerant and can withstand extended periods of severe water loss. One prime example are seeds and pollen of many spermatophytes. However, in some plants, also vegetative organs can be desiccation-tolerant. One example are the tubers of yellow nutsedge ( Cyperus esculentus ), which also store large amounts of lipids similar to seeds. Interestingly, the closest known relative, purple nutsedge ( Cyperus rotundus ), generates tubers that do not accumulate oil and are not desiccation-tolerant. We generated nanoLC-MS/MS-based proteomes of yellow nutsedge in five replicates of four stages of tuber development and compared them to the proteomes of roots and leaves, yielding 2257 distinct protein groups. Our data reveal a striking upregulation of hallmark proteins of seeds in the tubers. A deeper comparison to the tuber proteome of the close relative purple nutsedge ( C. rotundus ) and a previously published proteome of Arabidopsis seeds and seedlings indicates that indeed a seed-like proteome was found in yellow but not purple nutsedge. This was further supported by an analysis of the proteome of a lipid droplet-enriched fraction of yellow nutsedge, which also displayed seed-like characteristics. One reason for the differences between the two nutsedge species might be the expression of certain transcription factors homologous to ABSCISIC ACID INSENSITIVE3, WRINKLED1, and LEAFY COTYLEDON1 that drive gene expression in Arabidopsis seed embryos.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Carrier-assisted One-pot Sample Preparation for Targeted Proteomics Analysis of Small Numbers of Human Cells

Protein analysis of small numbers of human cells is primarily achieved by targeted proteomics with antibody-based immunoassays, which have inherent limitations (e.g., low multiplex and unavailability of antibodies for new proteins). Mass spectrometry (MS)-based targeted proteomics has emerged as an alternative because it is antibody-free, high multiplex, and has high specificity and quantitation accuracy. Recent advances in MS instrumentation make MS-based targeted proteomics possible for multiplexed quantification of highly abundant proteins in single cells. However, there is a technical challenge for effective processing of single cells with minimal sample loss for MS analysis. To address this issue, we have recently developed a convenient protein carrier-assisted one-pot sample preparation coupled with liquid chromatography (LC) - selected reaction monitoring (SRM) termed cLC-SRM for targeted proteomics analysis of small numbers of human cells. This method capitalizes on using the combined excessive exogenous protein as a carrier and low-volume one-pot processing to greatly reduce surface adsorption losses as well as high-specificity LC-SRM to effectively address the increased dynamic concentration range due to the addition of exogeneous carrier protein. Its utility has been demonstrated by accurate quantification of most moderately abundant proteins in small numbers of cells (e.g., 10-100 cells) and highly abundant proteins in single cells. The easy-to-implement features and no need for specific devices make this method readily accessible to most proteomics laboratories. In this study, we have provided a detailed protocol for cLC-SRM analysis of small numbers of human cells including cell sorting, cell lysis and digestion, LC-SRM analysis, and data analysis. Further improvements in detection sensitivity and sample throughput are needed towards targeted single-cell proteomics analysis. We anticipate that cLC-SRM will be broadly applied to biomedical research and systems biology with the potential of facilitating precision medicine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Surfactant-assisted one-pot sample preparation for label-free single-cell proteomics

Large numbers of cells are generally required for quantitative global proteome profiling due to surface adsorption losses associated with sample processing. Such bulk measurement obscures important cell-to-cell variability (cell heterogeneity) and makes proteomic profiling impossible for rare cell populations (e.g., circulating tumor cells (CTCs)). Here we report a surfactant-assisted one-pot sample preparation coupled with mass spectrometry (MS) method termed SOP-MS for label-free global single-cell proteomics. SOP-MS capitalizes on the combination of a MS-compatible nonionic surfactant, n-Dodecyl-β-D-maltoside, and hydrophobic surface-based low-bind tubes or multi-well plates for ‘all-in-one’ one-pot sample preparation. This ‘all-in-one’ method including elimination of all sample transfer steps maximally reduces surface adsorption losses for effective processing of single cells, thus improving detection sensitivity for single-cell proteomics. This method allows convenient label-free quantification of hundreds of proteins from single human cells and ~1200 proteins from small tissue sections (close to ~20 cells). When applied to a patient CTC-derived xenograft (PCDX) model at the single-cell resolution, SOP-MS can reveal distinct protein signatures between primary tumor cells and early metastatic lung cells, which are related to the selection pressure of anti-tumor immunity during breast cancer metastasis. The approach paves the way for routine, precise, quantitative single-cell proteomics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Thiol redox proteomics: Characterization of thiol-based post-translational modifications

Redox post-translational modifications on cysteine thiols (redox PTMs) have profound effects on protein structure and function, thus enabling regulation of various biological processes. Redox proteomics approaches aim to characterize the landscape of redox PTMs at the systems level. These approaches facilitate studies of condition-specific, dynamic processes implicating redox PTMs and have furthered our understanding of redox signaling and regulation. Mass spectrometry (MS) is a powerful tool for such analyses which has been demonstrated by significant advances in redox proteomics during the last decade. A group of well-established approaches involves the initial blocking of free thiols followed by selective reduction of oxidized PTMs and subsequent enrichment for downstream detection. Alternatively, novel chemoselective probe-based approaches have been developed for various redox PTMs. Direct detection of redox PTMs without any enrichment has also been demonstrated given the sensitivity of contemporary MS instruments. This review discusses the general principles behind different analytical strategies and covers recent advances in redox proteomics. Several applications of redox proteomics are also highlighted to illustrate how large-scale redox proteomics data can lead to novel biological insights.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

MARLOWE: An Untargeted Proteomics, Statistical Approach to Taxonomic Classification for Forensics

General proteomics research for fundamental science typically addresses laboratory- or patient-derived samples of known origin and composition. However, in a few research areas, such as environmental proteomics, clinical identification of infectious organisms, archeology, art/cultural history, and forensics, attributing the origin of a protein-containing sample to the organisms that produced it is a central focus. A small number of groups have approached this problem and developed software tools for taxonomic characterization and/or identification using bottom-up proteomics. Most such tools identify peptides via database search, and many rely on organism-specific peptides as markers. Our group recently introduced MARLOWE, a software tool for taxonomic characterization of unknown samples based on de novo peptide identification and signal-erosion-resistant strong peptides, which are shared peptides distributed in a taxonomy-dependent manner. In the current work, we further characterize the utility of MARLOWE using publicly available proteomics data from forensically-relevant samples. MARLOWE characterizes samples based on their protein profile, and returns ranked organism lists of potential contributors and taxonomic scores based on shared strong peptides between organisms. Overall, the correct characterization rate ranges between 44 and 100%, depending on the sample type and data acquisition parameters (with lower numbers associated with lower-quality data sets). MARLOWE demonstrates successful characterization of true contributors and close relatives, and provides sufficient specificity to distinguish certain microbial species. MARLOWE demonstrates its ability to provide insight into potential taxonomic sources for a wide range of sample types without prior assumptions about sample contents. As a result, this approach can find utility in forensic science and also broadly in bioanalytical applications that utilize proteomics approaches for taxonomic characterization.

Bacteria↗
DOE OSTI2020

Proteomic Characterization of Damaged Single Hairs Recovered after an Explosion for Protein-Based Human Identification

Evidence recovery is challenging where an explosion has occurred. Though hair evidence may be sufficiently robust to be recovered at the site, forensic analysis underutilizes the matrix by relying on morphological analysis. Where DNA is compromised, particularly in hair, protein-based human identification presents a promising alternative. Detection of amino acid polymorphisms in hair proteins as genetically variant peptides (GVPs) permits the inference of individualizing single nucleotide polymorphisms for identification. However, an explosive blast may damage hair proteins and compromise GVP identification. This work evaluates effects of an explosive blast on the hair proteome and GVP identification, investigates microscopy as a predictor of proteome profiling success in recovered hairs to improve analysis throughput, and quantifies discriminative power in damaged hairs. The proteomics dataset has been deposited into the ProteomeXchange Consortium (PXD017427). With the exception of degradation in keratins K75, K80, K40, and keratin-associated protein KAP10-11 as markers of hair cuticular damage, corroborated by scanning electron microscopic analysis, minimal hair proteome degradation following explosion allowed successful proteome profiling of single hairs regardless of morphological damage. Finally, GVP identification remained independent of explosion conditions, permitting similar discriminative power between exploded and undamaged hairs. These findings lend greater confidence to GVP analysis in one-inch hairs for forensic identification and provide information about hair protein localization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Data from a multi-year targeted proteomics study of a longitudinal birth cohort of type 1 diabetes

The deployment of liquid chromatography-mass spectrometry-based plasma proteomics experiments in a large cohort is sparse, leading to a lack of data available for benchmarking, method development or validation. Comprised of 6,426 plasma analyses, The Environmental Determinants of Diabetes in the Young (TEDDY) proteomics validation study constitutes one of the largest targeted proteomics experiments in the literature to date. The proteomics data from this study were generated over the course of 2.5 years from over 900 study subjects, each providing up to 29 longitudinal samples. The data also includes 916 quality control samples. The targeted mass spectrometry assay was comprised of 694 peptides mapping to 167 proteins and the panel was measured in each subject and QC sample. The targeted proteomic dataset presented here can be used as a resource for new computational method development, such as for batch correction, as well as for benchmarking and comparing the performance of different methods/tools.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Proteomic Analysis of Methanococcus voltae Grown in the Presence of Mineral and Nonmineral Sources of Iron and Sulfur

Iron sulfur (Fe-S) proteins are essential and ubiquitous across all domains of life, yet the mechanisms underpinning assimilation of iron (Fe) and sulfur (S) and biogenesis of Fe-S clusters are poorly understood. This is particularly true for anaerobic methanogenic archaea, which are known to employ more Fe-S proteins than other prokaryotes. Here, we utilized a deep proteomics analysis of Methanococcus voltae A3 cultured in the presence of either synthetic pyrite (FeS 2 ) or aqueous forms of ferrous iron and sulfide to elucidate physiological responses to growth on mineral or nonmineral sources of Fe and S. The liquid chromatography-mass spectrometry (LCMS) shotgun proteomics analysis included 77% of the predicted proteome. Through a comparative analysis of intra- and extracellular proteomes, candidate proteins associated with FeS 2 reductive dissolution, Fe and S acquisition, and the subsequent transport, trafficking, and storage of Fe and S were identified. The proteomic response shows a large and balanced change, suggesting that M. voltae makes physiological adjustments involving a range of biochemical processes based on the available nutrient source. Among the proteins differentially regulated were members of core methanogenesis, oxidoreductases, membrane proteins putatively involved in transport, Fe-S binding ferredoxin and radical S-adenosylmethionine proteins, ribosomal proteins, and intracellular proteins involved in Fe-S cluster assembly and storage. This work improves our understanding of ancient biogeochemical processes and can support efforts in biomining of minerals. Clusters of iron and sulfur are key components of the active sites of enzymes that facilitate microbial conversion of light or electrical energy into chemical bonds. The proteins responsible for transporting iron and sulfur into cells and assembling these elements into metal clusters are not well understood. Using a microorganism that has an unusually high demand for iron and sulfur, we conducted a global investigation of cellular proteins and how they change based on the mineral forms of iron and sulfur. Understanding this process will answer questions about life on early earth and has application in biomining and sustainable sources of energy.

59 BASIC BIOLOGICAL SCIENCES↗