A compendium of multi-omics data illuminating host responses to lethal human virus infections.

Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death. Here, we present experimental methods and multi-omics data capture approaches representing the global host response to infection generated from 45 individual experiments involving human viruses from the Orthomyxoviridae, Filoviridae, Flaviviridae, and Coronaviridae families. Analogous experimental designs were implemented across human or mouse host model systems, longitudinal samples were collected over defined time courses, and global multi-omics data (transcriptomics, proteomics, metabolomics, and lipidomics) were acquired by microarray, RNA sequencing, or mass spectrometry analyses. For comparison, we have included transcriptomics datasets from cells treated with type I and type II human interferon. Raw multi-omics data and metadata were deposited in public repositories, and we provide a central location linking the raw data with experimental metadata and ready-to-use, quality-controlled, statistically processed multi-omics datasets not previously available in any public repository. This compendium of infection-induced host response data for reuse will be useful for those endeavouring to understand viral disease pathophysiology and network biology.

FLAG-KRAS4B as a Model System for KRAS4B Proteoform and PTM Evaluation by Mass Spectrometry.

Prior analysis of intact and modified protein forms (proteoforms) of KRAS4B isolated from cell lines and tumor samples by top-down mass spectrometry revealed the presence of novel posttranslational modifications (PTMs) and potential evidence of context-specific KRAS4B modifications. However, low endogenous proteoform signal resulted in ineffective characterization, making it difficult to visualize less abundant PTMs or perform follow-up PTM validation using standard proteomic workflows. The NCI RAS Initiative has developed a model system, whereby KRAS4B bearing an N-terminal FLAG tag can be stably expressed within a panel of cancer cell lines. Herein, we present a method for combining immunoprecipitation with complementary proteomic methods to directly analyze N-terminally FLAG-tagged KRAS4B proteoforms and PTMs. We provide detailed protocols for FLAG-KRAS4B purification, proteoform analysis by targeted top-down LC-MS/MS, and validation of abundant PTMs by bottom-up LC-MS/MS with example results.

Quantitative proteomics analysis reveals an important role of the transcriptional regulator UidR in the bacterial biofilm formation of Aeromonas hydrophila.

Introduction: Bacterial biofilm is a well-known characteristic that plays important roles in diverse physiological functions, whereas the current intrinsic regulatory mechanism of its formation is still largely unknown. Methods: In the present study, a label-free based quantitative proteomics technology was conducted to compare the differentially expressed proteins (DEPs) between ΔuidR and the wild-type strain in the biofilm state. Results: The results showed that the deletion of gene uidR encoding a TetR transcriptional regulator significantly increased the biofilm formation in Aeromonas hydrophila. And there was a total of 220 DEPs, including 120 up-regulated proteins and 100 down-regulated proteins between ΔuidR and the wild-type strain based on the quantitative proteomics. Bioinformatics analysis suggested that uidR may affect bacterial biofilm formation by regulating some related proteins in glyoxylic acid and dicarboxylic acid pathway. The expressions of selected proteins involved in this pathway were further confirmed by q-PCR assay, and the results was in accordance with the quantitative proteomics data. Moreover, the deletion of four genes (AHA_3063, AHA_3062, AHA_4140 and aceB) related to the glyoxylic acid and dicarboxylic acid pathway lead to a significant decrease in the biofilm formation. Discussion: Thus, the results indicated that uidR involved in the regulatory of bacterial biofilm formation, and it may provide a potential target for the drug development and a new clue for the prevention of pathogenic A. hydrophila in the future.

Data-Independent Acquisition-Based Quantitative Proteomic Analysis Reveals Potential Salivary Biomarkers of Primary Sjögren's Syndrome.

Objective As primary Sj?gren's syndrome (pSS) primarily affects the salivary glands, saliva can serve as an indicator of the glands' pathophysiology and the disease's status. This study aims to illustrate the salivary proteomic profiles of pSS patients and identify potential candidate biomarkers for diagnosis.Methods The discovery set contained 49 samples (24 from pSS and 25 from age- and gender-matched healthy controls [HCs]) and the validation set included 25 samples (12 from pSS and 13 from HCs). Totally 36 pSS patients and 38 HCs were centrally randomized into the discovery set or to the validation set at a 2:1 ratio. Unstimulated whole saliva samples from pSS patients and HCs were analyzed using a data-independent acquisition (DIA) strategy on a 2D LC?HRMS/MS platform to reveal differential proteins. The crucial proteins were verified using DIA analysis and annotated using gene ontology (GO) and International Pharmaceutical Abstracts (IPA) analysis. A prediction model for SS was established using random forests.Results A total of 1,963 proteins were discovered, and 136 proteins exhibited differential representation in pSS patients. The bioinformatic research indicated that these proteins were primarily linked to immunological functions, metabolism, and inflammation. A panel of 19 protein biomarkers was identified by ranking order based on P-value and random forest algorichm, and was validated as the predictive biomarkers exhibiting good performance with area under the curve (AUC) of 0.817 for discovery set and 0.882 for validation set.Conclusions The candidate protein panel discovered may aid in pSS diagnosis. Salivary proteomic analysis is a promising non-invasive method for prognostic evaluation and early and precise treatments for pSS patients. DIA offers the best time efficiency and data dependability and may be a suitable option for future research on the salivary proteome.

Quantitative Pattern of hPTMs by Mass Spectrometry-Based Proteomics with Implications for Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is known for its aggressive nature, and TNBC management is currently challenging due to the lack of effective targets. Despite the importance of histone post-translational modifications (hPTMs) in breast cancer, their associations with molecular subtypes of breast cancer, especially TNBC, are poorly understood. In this study, a combination of untargeted and targeted proteomics approaches, supplemented by a derivatization method, was applied to breast cancer cells and tissue samples. Untargeted proteomics of eight breast cancer cell lines belonging to different molecular subtypes revealed 36 modified peptides with 12 lysine modification sites in histone H3, and the most frequently reported top 5 histone H3 methylation and acetylation sites were covered. Then, targeted proteomics was carried out to quantify the total 20 target hPTMs at the covered modification sites (i.e., mono-, di-, trimethylation, and acetylation for each site), indicating the difficulty in distinguishing TNBC cells from normal cells. Subsequently, the analysis in TNBC patients revealed significant expression differences in 4 specific hPTMs (H3K14ac, H3K27me1, H3K36me2, and H3K36me3) between TNBC and adjacent normal tissue samples. These unique hPTM patterns allowed for the differentiation of TNBC from normal cases. This finding provides promising implications for advancing targeted treatment strategies for TNBC in the future.

The development of a novel zeolite-based assay for efficient and deep plasma proteomic profiling.

Plasma proteins are considered the most informative source of biomarkers for disease diagnosis and monitoring. Mass spectrometry (MS)-based proteomics has been applied to identify biomarkers in plasma, but the complexity of the plasma proteome and the extremely large dynamic range of protein abundances in plasma make the clinical application of plasma proteomics highly challenging. We designed and synthesized zeolite-based nanoparticles to deplete high-abundance plasma proteins. The resulting novel plasma proteomic assay can measure approximately 3000 plasma proteins in a 45 min chromatographic gradient. Compared to those in neat and depleted plasma, the plasma proteins identified by our assay exhibited distinct biological profiles, as validated in several public datasets. A pilot investigation of the proteomic profile of a hepatocellular carcinoma (HCC) cohort identified 15 promising protein features, highlighting the diagnostic value of the plasma proteome in distinguishing individuals with and without HCC. Furthermore, this assay can be easily integrated with all current downstream protein profiling methods and potentially extended to other biofluids. In conclusion, we established a robust and efficient plasma proteomic assay with unprecedented identification depth, paving the way for the translation of plasma proteomics into clinical applications.

The 37TrillionCells initiative for improving global healthcare via cell-based interception and precision medicine: focus on neurodegenerative diseases.

One of the main burdens in the treatment of diseases is imputable to the delay between the appearance of molecular dysfunctions in the first affected disease cells and their presence in sufficient number for detection in specific tissues or organs. This delay obviously plays in favor of disease progression to an extent that makes efficient treatments difficult, as they arrive too late. The development of a novel medical strategy, termed cell-based interception and precision medicine, seeks to identify dysfunctional cells early, when tissue damages are not apparent and symptoms not yet present, and develop therapies to treat diseases early. Central to this strategy is the use of single-cell technologies that allow detection of molecular changes in cells at the time of phenotypical bifurcation from health to disease. In this article we describe a general procedure to support such an approach applied to neurodegenerative disorders. This procedure combines four components directed towards highly complementary objectives: 1) a high-performance single-cell proteomics (SCP) method (Detect), 2) the development of disease experimental cell models and predictive computational models of cell trajectories (Understand), 3) the discovery of specific targets and personalized therapies (Cure), and 4) the creation of a community of collaborating laboratories to accelerate the development of this novel medical paradigm (Collaborate). A global initiative named 37TrillionCells (37TC) was launched to advance the development of cell-based interception and precision medicine.

Enrichment, Characterization, and Proteomic Profiling of Small Extracellular Vesicles Derived from Human Limbal Mesenchymal Stromal Cells and Melanocytes.

Limbal epithelial progenitor cells (LEPC) rely on their niche environment for proper functionality and self-renewal. While extracellular vesicles (EV), specifically small EVs (sEV), have been proposed to support LEPC homeostasis, data on sEV derived from limbal niche cells like limbal mesenchymal stromal cells (LMSC) remain limited, and there are no studies on sEVs from limbal melanocytes (LM). In this study, we isolated sEV from conditioned media of LMSC and LM using a combination of tangential flow filtration and size exclusion chromatography and characterized them by nanoparticle tracking analysis, transmission electron microscopy, Western blot, multiplex bead arrays, and quantitative mass spectrometry. The internalization of sEV by LEPC was studied using flow cytometry and confocal microscopy. The isolated sEVs exhibited typical EV characteristics, including cell-specific markers such as CD90 for LMSC-sEV and Melan-A for LM-sEV. Bioinformatics analysis of the proteomic data suggested a significant role of sEVs in extracellular matrix deposition, with LMSC-derived sEV containing proteins involved in collagen remodeling and cell matrix adhesion, whereas LM-sEV proteins were implicated in other cellular bioprocesses such as cellular pigmentation and development. Moreover, fluorescently labeled LMSC-sEV and LM-sEV were taken up by LEPC and localized to their perinuclear compartment. These findings provide valuable insights into the complex role of sEV from niche cells in regulating the human limbal stem cell niche.

Giant Virus Global Proteomics Innovation: Comparative Evaluation of In-Gel and In-Solution Digestion Methods.

With their unusually large genome and particle sizes, giant viruses (GVs) defy the conventional definition of viruses. Although most GVs isolated infect unicellular protozoans, such as amoeba, studies in the last decade have established their much wider prevalence infecting most eukaryotic supergroups and some giant viral families with the potential to be human pathogens. Their complexity, almost autonomous life cycle, and enigmatic evolution necessitate the study of GVs. The accurate assessment of GV proteome is a veritable challenge. We have compared the coverage of global protein identification using different methods for GVs isolated in Mumbai, Mimivirus Bombay (MVB), Powai Lake Megavirus (PLMV), and Kurlavirus (KV), along with two previously studied GVs, Acanthamoeba polyphaga Mimivirus (APMV) and Marseillevirus (MV). Our study shows that the simultaneous use of in-gel and in-solution digestion methods can significantly increase the coverage of protein identification in the global proteome analysis of purified GV particles. Combining the two methods of analyses, we identified an additional 72 proteins in APMV and 114 in MV compared with what have been previously reported. Similarly, proteomes of MVB, PLMV, and KV were analyzed, and a total of 242 proteins in MVB, 287 proteins in PLMV, and 174 proteins in KV were identified. Our results suggest that a combined methodology of in-gel and in-solution methods is more efficient and opens up new avenues for innovation in global proteome analysis of GVs. Future planetary health research on GVs can benefit from consideration of a broader range of proteomics methodologies as illustrated by the present study.

Decoding the ubiquitin landscape by cutting-edge ubiquitinomic approaches.

Functional consequences of protein ubiquitination have gone far beyond the degradation regulation as was initially imagined during its discovery 40 years back. The state-of-the-art has revealed the plethora of signaling pathways that are largely regulated by ubiquitination process in eukaryotes. To no surprise, ubiquitination is often dysregulated in many human diseases, including cancer, neurodegeneration and infection. Hence it has become a major focus with high-gain research value for many investigators to unravel new proteoforms, that are the targets of this ubiquitination modification. Despite many biochemical or proteomic approaches available for ubiquitination detection, mass-spectrometry stood out to be the most efficient and transformative technology to read this complex modification script. Here in this review, we have discussed how different ubiquitin codes can be decoded qualitatively and quantitatively following various sequential proteomic approaches to date reported and indicated the current limitations with scope for improvements.

Global O-glycoproteome enrichment and analysis enabled by a combinatorial enzymatic workflow.

A comprehensive analysis of site-specific protein O-glycosylation is hindered by the absence of a consensus O-glycosylation motif, the diversity of O-glycan structures, and the lack of a universal enzyme that cleaves attached O-glycans. Here, we report the development of a robust O-glycoproteomic workflow for analyzing complex biological samples by combining four different strategies: removal of N-glycans, complementary digestion using O-glycoprotease (IMPa) with/without another protease, glycopeptide enrichment, and mass spectrometry with fragmentation of glycopeptides using stepped collision energy. Using this workflow, we cataloged 474 O-glycopeptides on 189 O-glycosites derived from 79 O-glycoproteins from human plasma. These data revealed O-glycosylation of several abundant proteins that have not been previously reported. Because many of the proteins that contained unannotated O-glycosylation sites have been extensively studied, we wished to confirm glycosylation at these sites in a targeted fashion. Thus, we analyzed selected purified proteins (kininogen-1, fetuin-A, fibrinogen, apolipoprotein E, and plasminogen) in independent experiments and validated the previously unknown O-glycosites.

N-glycoproteomic analyses of human intestinal enteroids, varying in histo-blood group geno- and phenotypes, reveal a wide repertoire of fucosylated glycoproteins.

Human noroviruses, globally the main cause of viral gastroenteritis, show strain specific affinity for histo-blood group antigens (HBGA) and can successfully be propagated ex vivo in human intestinal enteroids (HIEs). HIEs established from jejunal stem cells of individuals with different ABO, Lewis and secretor geno- and phenotypes, show varying susceptibility to such infections. Using bottom-up glycoproteomic approaches we have defined and compared the N-linked glycans of glycoproteins of seven jejunal HIEs. Membrane proteins were extracted, trypsin digested, and glycopeptides enriched by hydrophilic interaction liquid chromatography and analyzed by nanoLC-MS/MS. The Byonic software was used for glycopeptide identification followed by hands-on verifications and interpretations. Glycan structures and attachment sites were identified from MS2 spectra obtained by higher-energy collision dissociation through analysis of diagnostic saccharide oxonium ions (B-ions), stepwise glycosidic fragmentation of the glycans (Y-ions), and peptide sequence ions (b- and y-ions). Altogether 694 unique glycopeptides from 93 glycoproteins were identified. The N-glycans encompassed pauci- and oligomannose, hybrid- and complex-type structures. Notably, polyfucosylated HBGA-containing glycopeptides of the four glycoproteins tetraspanin-8, carcinoembryonic antigen-related cell adhesion molecule 5, sucrose-isomaltase and aminopeptidase N were especially prominent and were characterized in detail and related to donor ABO, Lewis and secretor types of each HIE. Virtually no sialylated N-glycans were identified for these glycoproteins suggesting that terminal sialylation was infrequent compared to fucosylation and HBGA biosynthesis. This approach gives unique site-specific information on the structural complexity of N-linked glycans of glycoproteins of human HIEs and provides a platform for future studies on the role of host glycoproteins in gastrointestinal infectious diseases.

Proteomic insights into paediatric cancer: Unravelling molecular signatures and therapeutic opportunities.

Survival rates in some paediatric cancers have improved greatly over recent decades, in part due to the identification of diagnostic, prognostic and predictive molecular signatures, and the development of risk-directed therapies. However, other paediatric cancers have proved difficult to treat, and there is an urgent need to identify novel biomarkers that reveal therapeutic opportunities. The proteome is the total set of expressed proteins present in a cell or tissue at a point in time, and is vastly more dynamic than the genome. Proteomics holds significant promise for cancer research, as proteins are ultimately responsible for cellular phenotype and are the target of most anticancer drugs. Here, we review the discoveries, opportunities and challenges of proteomic analyses in paediatric cancer, with a focus on mass spectrometry (MS)-based approaches. Accelerating incorporation of proteomics into paediatric precision medicine has the potential to improve survival and quality of life for children with cancer.

Cross-link assisted spatial proteomics to map sub-organelle proteomes and membrane protein topologies.

The functions of cellular organelles and sub-compartments depend on their protein content, which can be characterized by spatial proteomics approaches. However, many spatial proteomics methods are limited in their ability to resolve organellar sub-compartments, profile multiple sub-compartments in parallel, and/or characterize membrane-associated proteomes. Here, we develop a cross-link assisted spatial proteomics (CLASP) strategy that addresses these shortcomings. Using human mitochondria as a model system, we show that CLASP can elucidate spatial proteomes of all mitochondrial sub-compartments and provide topological insight into the mitochondrial membrane proteome. Biochemical and imaging-based follow-up studies confirm that CLASP allows discovering mitochondria-associated proteins and revising previous protein sub-compartment localization and membrane topology data. We also validate the CLASP concept in synaptic vesicles, demonstrating its applicability to different sub-cellular compartments. This study extends the scope of cross-linking mass spectrometry beyond protein structure and interaction analysis towards spatial proteomics, and establishes a method for concomitant profiling of sub-organelle and membrane proteomes.

Blood-Based Multiomics-Guided Detection of a Precancerous Pancreatic Tumor.

Over a decade ago, longitudinal multiomics analysis was pioneered for early disease detection and individually tailored precision health interventions. However, high sample processing costs, expansive multiomics measurements along with complex data analysis have made this approach to precision/personalized medicine impractical. Here we describe in a case report, a more practical approach that uses fewer measurements, annual sampling, and faster decision making. We also show how this approach offers promise to detect an exceedingly rare and potentially fatal condition before it fully manifests. Specifically, we describe in the present case report how longitudinal multiomics monitoring (LMOM) helped detect a precancerous pancreatic tumor and led to a successful surgical intervention. The patient, enrolled in an annual blood-based LMOM since 2018, had dramatic changes in the June 2021 and 2022 annual metabolomics and proteomics results that prompted further clinical diagnostic testing for pancreatic cancer. Using abdominal magnetic resonance imaging, a 2.6 cm lesion in the tail of the patient's pancreas was detected. The tumor fluid from an aspiration biopsy had 10,000 times that of normal carcinoembryonic antigen levels. After the tumor was surgically resected, histopathological findings confirmed it was a precancerous pancreatic tumor. Postoperative omics testing indicated that most metabolite and protein levels returned to patient's 2018 levels. This case report illustrates the potentials of blood LMOM for precision/personalized medicine, and new ways of thinking medical innovation for a potentially life-saving early diagnosis of pancreatic cancer. Blood LMOM warrants future programmatic translational research with the goals of precision medicine, and individually tailored cancer diagnoses and treatments.

Dynamics of CD44+ bovine nucleus pulposus cells with inflammation.

Intervertebral Disc (IVD) degeneration has been associated with a chronic inflammatory response, but knowledge on the contribution of distinct IVD cells, namely CD44, to the progression of IVD degeneration remains elusive. Here, bovine nucleus pulposus (NP) CD44 cells were sorted and compared by gene expression and proteomics with the negative counterpart. NP cells were then stimulated with IL-1b (10 ng/ml) and dynamics of CD44 gene and protein expression was analyzed upon pro-inflammatory treatment. The results emphasize that CD44 has a multidimensional functional role in IVD metabolism, ECM synthesis and production of neuropermissive factors. CD44 widespread expression in NP was partially associated with CD14 and CD45, resulting in the identification of distinct cell subsets. In conclusion, this study points out CD44 and CD44-based cell subsets as relevant targets in the modulation of the IVD pro-inflammatory/degenerative cascade.

High-throughput proteomic analysis of chronic inflammatory skin diseases: Psoriasis and atopic dermatitis.

Common characteristics in the pathogenesis of psoriasis (PS) and atopic dermatitis (AD) have been presumed, but only a few studies have clearly supported this. The current aim was to find possible similarities and differences in protein expression patterns between these two major chronic inflammatory skin diseases. High-throughput tandem mass spectrometry proteomic analysis was performed using full thickness skin samples from adult PS patients, AD patients and healthy subjects. We detected a combined total of 3045 proteins in the three study groups. According to principal component analysis, there was significant overlap between the proteomic profiles of PS and AD, and both clearly differed from that of healthy skin. The following validation of selected proteins with western blot analysis showed similar tendencies in expression levels and produced statistically significant results. The expression of periostin (POSTN) was consistently high in AD and very low or undetectable in PS (5% FDR corrected p < 0.001), suggesting POSTN as a potential biomarker to distinguish these diseases. Immunohistochemistry further confirmed higher POSTN expression in AD compared to PS skin. Overall, our findings support the concept that these two chronic skin diseases might share considerably more common mechanisms in pathogenesis than has been suspected thus far.

Proteomic biomarkers in seminal plasma as predictors of reproductive potential in azoospermic men.

Introduction: Azoospermia, characterized by an absence of sperm in the ejaculate, represents the most severe form of male infertility. While surgical sperm retrieval in obstructive azoospermia (OA) is successful in the majority of cases, patients with non-obstructive azoospermia (NOA) show retrieval rates of only about 50% and thus frequently have unnecessary surgery. Surgical intervention could be avoided if patients without preserved spermatogenesis are identified preoperatively. This prospective study aimed to discover biomarkers in seminal plasma that could be employed for a non-invasive differential diagnosis of OA/NOA in order to rationalize surgery recommendations and improve success rates. Methods: All patients signed written informed consent, underwent comprehensive andrological evaluation, received human genetics to exclude relevant pathologies, and patients with azoospermia underwent surgical sperm retrieval. Using label-free LC-MS/MS, we compared the proteomes of seminal plasma samples from fertile men (healthy controls (HC), n=8) and infertile men diagnosed with 1) OA (n=7), 2) NOA with successful sperm retrieval (mixed testicular atrophy (MTA), n=8), and 3) NOA without sperm retrieval (Sertoli cell-only phenotype (SCO), n=7). Relative abundance changes of two candidate markers of sperm retrieval, HSPA2 and LDHC, were confirmed by Western Blot. Results: We found the protein expression levels of 42 proteins to be significantly down-regulated (p ≤ 0.05) in seminal plasma from SCO NOA patients relative to HC whereas only one protein was down-regulated in seminal plasma from MTA patients. Analysis of tissue and cell expression suggested that the testis-specific proteins LDHC, PGK2, DPEP3, and germ-cell enriched heat-shock proteins HSPA2 and HSPA4L are promising biomarkers of spermatogenic function. Western blotting revealed a significantly lower abundance of LDHC and HSPA2 in the seminal plasma of men with NOA (SCO and MTA) compared to controls. Discussion: The results indicate that certain testis-specific proteins when measured in seminal plasma, could serve as indicators of the presence of sperm in the testis and predict the success of sperm retrieval. Used in conjunction with conventional clinical assessments, these proteomic biomarkers may assist in the non-invasive diagnosis of idiopathic male infertility.

Impact of inflammatory preconditioning on murine microglial proteome response induced by focal ischemic brain injury.

Preconditioning with lipopolysaccharide (LPS) induces neuroprotection against subsequent cerebral ischemic injury, mainly involving innate immune pathways. Microglia are resident immune cells of the central nervous system (CNS) that respond early to danger signals through memory-like differential reprogramming. However, the cell-specific molecular mechanisms underlying preconditioning are not fully understood. To elucidate the distinct molecular mechanisms of preconditioning on microglia, we compared these cell-specific proteomic profiles in response to LPS preconditioning and without preconditioning and subsequent transient focal brain ischemia and reperfusion, - using an established mouse model of transient focal brain ischemia and reperfusion. A proteomic workflow, based on isolated microglia obtained from mouse brains by cell sorting and coupled to mass spectrometry for identification and quantification, was applied. Our data confirm that LPS preconditioning induces marked neuroprotection, as indicated by a significant reduction in brain infarct volume. The established brain cell separation method was suitable for obtaining an enriched microglial cell fraction for valid proteomic analysis. The results show a significant impact of LPS preconditioning on microglial proteome patterns by type I interferons, presumably driven by the interferon cluster regulator proteins signal transducer and activator of transcription1/2 (STAT1/2).