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PURPOSE: To evaluate the relative diagnostic yield of clinical germline genomic tests in a diverse pediatric cancer population. PATIENTS AND METHODS: The KidsCanSeq study enrolled pediatric cancer patients across six sites in Texas. Germline analysis included both exome sequencing and a therapy-focused pediatric cancer gene panel. The results were categorized by participants demographics, the presence of pathogenic or likely pathogenic (P/LP) variants, and variants of uncertain significance (VUS) in cancer predisposition genes (CPGs). Pediatric actionable CPGs were defined as those with cancer surveillance recommendations during childhood. RESULTS: Cancer P/LP variants were reported by at least one platform in 103 of 578 (17.8%) participants of which 76 were dominant cancer genes (13.1%) with no significant differences by self-described race or Hispanic ethnicity. However, the proportion of participants with VUS was greater in Asian and African American participants (P = .0029). Diagnostic yield was 16.6% for exome versus 8.5% for panel (P < .0001) with 42 participants with concordant germline results. Exome-only results included P/LP variants in 30 different CPGs in 54 participants, whereas panel-only results included seven participants with a copy number or structural P/LP variants in CPGs. There was no significant difference in diagnostic yield limited to pediatric actionable CPGs (P = .6171). CONCLUSION: Approximately 18% of a diverse pediatric cancer population had germline diagnostic findings with 50% of P/LP variants reported by only one platform because of CPGs not on the targeted panel and copy number variants (CNVs)/rearrangements not reported by exome. Although diagnostic yields were similar in this diverse population, increases in VUS results were observed in Asian and African American populations. Given the clinical significance of CNVs/rearrangements in this cohort, detection is critical to optimize germline analysis of pediatric cancer populations.
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Sequenciamento do Exoma , Mutação em Linhagem Germinativa , Neoplasias , Humanos , Criança , Neoplasias/genética , Neoplasias/diagnóstico , Texas , Masculino , Feminino , Pré-Escolar , Adolescente , Sequenciamento do Exoma/métodos , Exoma/genética , Lactente , Predisposição Genética para Doença , Células GerminativasRESUMO
BACKGROUND: Obstructive lung disease (OLD) is increasingly prevalent among persons living with HIV (PLWH). However, the role of proteases in HIV-associated OLD remains unclear. METHODS: We combined proteomics and peptidomics to comprehensively characterize protease activities. We combined mass spectrometry (MS) analysis on bronchoalveolar lavage fluid (BALF) peptides and proteins from PLWH with OLD (n = 25) and without OLD (n = 26) with a targeted Somascan aptamer-based proteomic approach to quantify individual proteases and assess their correlation with lung function. Endogenous peptidomics mapped peptides to native proteins to identify substrates of protease activity. Using the MEROPS database, we identified candidate proteases linked to peptide generation based on binding site affinities which were assessed via z-scores. We used t-tests to compare average forced expiratory volume in 1 s per predicted value (FEV1pp) between samples with and without detection of each cleaved protein and adjusted for multiple comparisons by controlling the false discovery rate (FDR). FINDINGS: We identified 101 proteases, of which 95 had functional network associations and 22 correlated with FEV1pp. These included cathepsins, metalloproteinases (MMP), caspases and neutrophil elastase. We discovered 31 proteins subject to proteolytic cleavage that associate with FEV1pp, with the top pathways involved in small ubiquitin-like modifier mediated modification (SUMOylation). Proteases linked to protein cleavage included neutrophil elastase, granzyme, and cathepsin D. INTERPRETATIONS: In HIV-associated OLD, a significant number of proteases are up-regulated, many of which are involved in protein degradation. These proteases degrade proteins involved in cell cycle and protein stability, thereby disrupting critical biological functions.
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Infecções por HIV , Peptídeo Hidrolases , Proteômica , Humanos , Proteômica/métodos , Masculino , Infecções por HIV/enzimologia , Infecções por HIV/metabolismo , Pessoa de Meia-Idade , Feminino , Peptídeo Hidrolases/metabolismo , Adulto , Líquido da Lavagem Broncoalveolar/química , Doença Pulmonar Obstrutiva Crônica/metabolismo , Doença Pulmonar Obstrutiva Crônica/enzimologia , Doença Pulmonar Obstrutiva Crônica/diagnósticoRESUMO
Mass spectrometry (MS)-based metaproteomics is used to identify and quantify proteins in microbiome samples, with the frequently used methodology being Data-Dependent Acquisition mass spectrometry (DDA-MS). However, DDA-MS is limited in its ability to reproducibly identify and quantify lower abundant peptides and proteins. To address DDA-MS deficiencies, proteomics researchers have started using Data-Independent Acquisition Mass Spectrometry (DIA-MS) for reproducible detection and quantification of peptides and proteins. We sought to evaluate the reproducibility and accuracy of DIA-MS metaproteomic measurements relative to DDA-MS using a mock community of known taxonomic composition. Artificial microbial communities of known composition were analyzed independently in three laboratories using DDA- and DIA-MS acquisition methods. DIA-MS yielded more protein and peptide identifications than DDA-MS in each laboratory. In addition, the protein and peptide identifications were more reproducible in all laboratories and provided an accurate quantification of proteins and taxonomic groups in the samples. We also identified some limitations of current DIA tools when applied to metaproteomic data, highlighting specific needs to improve DIA tools enabling analysis of metaproteomic datasets from complex microbiomes. Ultimately, DIA-MS represents a promising strategy for MS-based metaproteomics due to its large number of detected proteins and peptides, reproducibility, deep sequencing capabilities, and accurate quantitation.
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Alternative cleavage and polyadenylation within introns (intronic APA) generate shorter mRNA isoforms; however, their physiological significance remains elusive. In this study, we developed a comprehensive workflow to analyze intronic APA profiles using the mammalian target of rapamycin (mTOR)-regulated transcriptome as a model system. Our investigation revealed two contrasting effects within the transcriptome in response to fluctuations in cellular mTOR activity: an increase in intronic APA for a subset of genes and a decrease for another subset of genes. The application of this workflow to RNA-seq data from The Cancer Genome Atlas demonstrated that this dichotomous intronic APA pattern is a consistent feature in transcriptomes across both normal tissues and various cancer types. Notably, our analyses of protein length changes resulting from intronic APA events revealed two distinct phenomena in proteome programming: a loss of functional domains due to significant changes in protein length or minimal alterations in C-terminal protein sequences within unstructured regions. Focusing on conserved intronic APA events across 10 different cancer types highlighted the prevalence of the latter cases in cancer transcriptomes, whereas the former cases were relatively enriched in normal tissue transcriptomes. These observations suggest potential, yet distinct, roles for intronic APA events during pathogenic processes and emphasize the abundance of protein isoforms with similar lengths in the cancer proteome. Furthermore, our investigation into the isoform-specific functions of JMJD6 intronic APA events supported the hypothesis that alterations in unstructured C-terminal protein regions lead to functional differences. Collectively, our findings underscore intronic APA events as a discrete molecular signature present in both normal tissues and cancer transcriptomes, highlighting the contribution of APA to the multifaceted functionality of the cancer proteome.
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As a leading global cause of musculoskeletal-related disability, osteoarthritis (OA) represents a public health urgency. Understanding of disease pathogenesis has advanced substantially in the past decade, yet no disease-modifying therapeutics have advanced to the clinic. To address this challenge, the CARE-AP (Cartilage Repair strategies to alleviate Arthritis Pain) collaborative research team was convened to bring together relevant multidisciplinary expertise and perspectives from across the VA research community nationwide. The first CARE-AP Annual Research Symposium took place (virtually) in February 2022 with roughly 90 participants. A number of innovative and therapeutic strategies were discussed, including siRNA approaches coupled with novel nanoparticle-based delivery systems, cellular engineering approaches to develop reparative cells that can probe the joint environment and respond to disease-specific cues, and novel biofabrication techniques to improve tissue engineering and effect "biological joint replacement." In addition, challenges and advances in rehabilitation approaches, imaging outcomes, and clinical studies were presented, which were integrated into a framework of recommendations for running "preclinical trials" to improve successful clinical translation.
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Objective: To identify factors contributing to sex-differences in OA risk by evaluating the short-term effect of high-fat (HF) diet on sex-specific changes in cartilage cell proliferation, ribosomal biogenesis, and targeted extra-cellular and cellular protein abundance. Materials and methods: Knee cartilage was harvested to the subchondral bone from 20-week-old female and male C57BL/6J mice fed a low-fat or HF diet for 4 weeks and labeled with deuterium oxide for 1, 3, 5, 7, 15, or 21 days. Deuterium enrichment was quantified in isolated DNA and RNA to measure cell proliferation and ribosomal biogenesis, respectively. Protein concentration was measured using targeted high resolution accurate mass spectrometry. Results: HF diet increased the maximal deuterium incorporation into DNA from approximately 40 to 50%, albeit at a slower rate. These findings, which were magnified in female versus male mice, indicate a greater number of proliferating cells with longer half-lives under HF diet conditions. HF diet caused distinct sex-dependent effects on deuterium incorporation into RNA, increasing the fraction of ribosomes undergoing biogenesis in male mice and doubling the rate of ribosome biogenesis in female mice. HF diet altered cartilage protein abundance similarly in both sexes, except for matrilin-3, which was more abundant in HF versus LF conditions in female mice only. Overall, HF diet treatment had a stronger effect than sex on cartilage protein abundance, with most changes involving extracellular matrix and matrix-associated proteins. Conclusions: Short-term HF diet broadly altered cartilage matrix protein abundance, while sex-dependent effects primarily involved differences in cell proliferation and ribosomal biogenesis.
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Background: Obstructive lung disease (OLD) is increasingly prevalent among persons living with HIV (PLWH). However, the role of proteases in HIV-associated OLD remains unclear. Methods: We combined proteomics and peptidomics to comprehensively characterize protease activities. We combined mass spectrometry (MS) analysis on bronchoalveolar lavage fluid (BALF) peptides and proteins from PLWH with OLD (n=25) and without OLD (n=26) with a targeted Somascan aptamer-based proteomic approach to quantify individual proteases and assess their correlation with lung function. Endogenous peptidomics mapped peptides to native proteins to identify substrates of protease activity. Using the MEROPS database, we identified candidate proteases linked to peptide generation based on binding site affinities which were assessed via z-scores. We used t-tests to compare average forced expiratory volume in 1 second per predicted value (FEV1pp) between samples with and without detection of each cleaved protein and adjusted for multiple comparisons by controlling the false discovery rate (FDR). Findings: We identified 101 proteases, of which 95 had functional network associations and 22 correlated with FEV1pp. These included cathepsins, metalloproteinases (MMP), caspases and neutrophil elastase. We discovered 31 proteins subject to proteolytic cleavage that associate with FEV1pp, with the top pathways involved in small ubiquitin-like modifier mediated modification (SUMOylation). Proteases linked to protein cleavage included neutrophil elastase, granzyme, and cathepsin D. Interpretations: In HIV-associated OLD, a significant number of proteases are up-regulated, many of which are involved in protein degradation. These proteases degrade proteins involved in cell cycle and protein stability, thereby disrupting critical biological functions.
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Airway microbiota are known to contribute to lung diseases, such as cystic fibrosis (CF), but their contributions to pathogenesis are still unclear. To improve our understanding of host-microbe interactions, we have developed an integrated analytical and bioinformatic mass spectrometry (MS)-based metaproteomics workflow to analyze clinical bronchoalveolar lavage (BAL) samples from people with airway disease. Proteins from BAL cellular pellets were processed and pooled together in groups categorized by disease status (CF vs. non-CF) and bacterial diversity, based on previously performed small subunit rRNA sequencing data. Proteins from each pooled sample group were digested and subjected to liquid chromatography tandem mass spectrometry (MS/MS). MS/MS spectra were matched to human and bacterial peptide sequences leveraging a bioinformatic workflow using a metagenomics-guided protein sequence database and rigorous evaluation. Label-free quantification revealed differentially abundant human peptides from proteins with known roles in CF, like neutrophil elastase and collagenase, and proteins with lesser-known roles in CF, including apolipoproteins. Differentially abundant bacterial peptides were identified from known CF pathogens (e.g., Pseudomonas), as well as other taxa with potentially novel roles in CF. We used this host-microbe peptide panel for targeted parallel-reaction monitoring validation, demonstrating for the first time an MS-based assay effective for quantifying host-microbe protein dynamics within BAL cells from individual CF patients. Our integrated bioinformatic and analytical workflow combining discovery, verification, and validation should prove useful for diverse studies to characterize microbial contributors in airway diseases. Furthermore, we describe a promising preliminary panel of differentially abundant microbe and host peptide sequences for further study as potential markers of host-microbe relationships in CF disease pathogenesis.IMPORTANCEIdentifying microbial pathogenic contributors and dysregulated human responses in airway disease, such as CF, is critical to understanding disease progression and developing more effective treatments. To this end, characterizing the proteins expressed from bacterial microbes and human host cells during disease progression can provide valuable new insights. We describe here a new method to confidently detect and monitor abundance changes of both microbe and host proteins from challenging BAL samples commonly collected from CF patients. Our method uses both state-of-the art mass spectrometry-based instrumentation to detect proteins present in these samples and customized bioinformatic software tools to analyze the data and characterize detected proteins and their association with CF. We demonstrate the use of this method to characterize microbe and host proteins from individual BAL samples, paving the way for a new approach to understand molecular contributors to CF and other diseases of the airway.
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Líquido da Lavagem Broncoalveolar , Fibrose Cística , Proteômica , Espectrometria de Massas em Tandem , Fluxo de Trabalho , Humanos , Fibrose Cística/microbiologia , Proteômica/métodos , Líquido da Lavagem Broncoalveolar/microbiologia , Líquido da Lavagem Broncoalveolar/química , Interações entre Hospedeiro e Microrganismos/genética , Microbiota/genética , Lavagem Broncoalveolar , Biologia Computacional/métodos , MasculinoRESUMO
The upper respiratory tract (URT) is home to a diverse range of microbial species. Respiratory infections disturb the microbial flora in the URT, putting people at risk of secondary infections. The potential dangers and clinical effects of bacterial and fungal coinfections with SARS-CoV-2 support the need to investigate the microbiome of the URT using clinical samples. Mass spectrometry (MS)-based metaproteomics analysis of microbial proteins is a novel approach to comprehensively assess the clinical specimens with complex microbial makeup. The coronavirus that causes severe acute respiratory syndrome (SARS-CoV-2) is responsible for the COVID-19 pandemic resulting in a plethora of microbial coinfections impeding therapy, prognosis, and overall disease management. In this chapter, the corresponding workflows for MS-based shotgun proteomics and metaproteomic analysis are illustrated.
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COVID-19 , Coinfecção , Proteômica , SARS-CoV-2 , Humanos , COVID-19/virologia , COVID-19/complicações , Proteômica/métodos , Coinfecção/microbiologia , Coinfecção/virologia , SARS-CoV-2/isolamento & purificação , Microbiota , Infecções Respiratórias/microbiologia , Infecções Respiratórias/virologia , Infecções Respiratórias/diagnóstico , Espectrometria de Massas/métodos , Proteoma/análise , Sistema Respiratório/microbiologia , Sistema Respiratório/metabolismo , Sistema Respiratório/virologiaRESUMO
Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification, and prioritization of microbial proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant [to generate peptide-spectral matches (PSMs) and quantification], PepQuery2 (to verify the quality of PSMs), Unipept (for taxonomic and functional annotation), and MSstatsTMT (for statistical analysis). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies. IMPORTANCE: Clinical metaproteomics has immense potential to offer functional insights into the microbiome and its contributions to human disease. However, there are numerous challenges in the metaproteomic analysis of clinical samples, including handling of very large protein sequence databases for sensitive and accurate peptide and protein identification from mass spectrometry data, as well as taxonomic and functional annotation of quantified peptides and proteins to enable interpretation of results. To address these challenges, we have developed a novel clinical metaproteomics workflow that provides customized bioinformatic identification, verification, quantification, and taxonomic and functional annotation. This bioinformatic workflow is implemented in the Galaxy ecosystem and has been used to characterize diverse clinical sample types, such as nasopharyngeal swabs and bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness and availability for use by the research community via analysis of residual fluid from cervical swabs.
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Biologia Computacional , Proteômica , Fluxo de Trabalho , Proteômica/métodos , Humanos , Biologia Computacional/métodos , Interações entre Hospedeiro e Microrganismos , Espectrometria de Massas , Microbiota/genética , Líquido da Lavagem Broncoalveolar/microbiologia , Líquido da Lavagem Broncoalveolar/química , Proteínas de Bactérias/genéticaRESUMO
OBJECTIVE: Metabolic processes are intricately linked to the resolution of innate inflammation and tissue repair, two critical steps for treating post-traumatic osteoarthritis (PTOA). Based on lipolytic and immunoregulatory actions of norepinephrine, we hypothesized that intra-articular ß-adrenergic receptor (ßAR) stimulation would suppress PTOA-associated inflammation in the infrapatellar fat pad (IFP) and synovium. DESIGN: We used the ßAR agonist isoproterenol to perturb intra-articular metabolism 3.5 weeks after applying a non-invasive single-load compression injury to knees of 12-week-old male and female mice. We examined the acute effects of intra-articular isoproterenol treatment relative to saline on IFP histology, multiplex gene expression of synovium-IFP tissue, synovial fluid metabolomics, and mechanical allodynia. RESULTS: Injured knees developed PTOA pathology characterized by heterotopic ossification, articular cartilage loss, and IFP atrophy and fibrosis. Isoproterenol suppressed the upregulation of pro-fibrotic genes and downregulated the expression of adipose genes and pro-inflammatory genes (Adam17, Cd14, Icam1, Csf1r, and Casp1) in injured joints of female (but not male) mice. Analysis of published single-cell RNA-seq data identified elevated catecholamine-associated gene expression in resident-like synovial-IFP macrophages after injury. Injury substantially altered synovial fluid metabolites by increasing amino acids, peptides, sphingolipids, phospholipids, bile acids, and dicarboxylic acids, but these changes were not appreciably altered by isoproterenol. Intra-articular injection of either isoproterenol or saline increased mechanical allodynia in female mice, whereas neither substance affected male mice. CONCLUSIONS: Acute ßAR activation altered synovial-IFP transcription in a sex and injury-dependent manner, suggesting that women with PTOA may be more sensitive than men to treatments targeting sympathetic neural signaling pathways.
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Agonistas Adrenérgicos beta , Isoproterenol , Animais , Feminino , Masculino , Camundongos , Isoproterenol/farmacologia , Agonistas Adrenérgicos beta/farmacologia , Modelos Animais de Doenças , Fatores Sexuais , Membrana Sinovial/metabolismo , Tecido Adiposo/metabolismo , Mediadores da Inflamação/metabolismo , Receptores Adrenérgicos beta/metabolismo , Injeções Intra-Articulares , Traumatismos do Joelho/complicações , Traumatismos do Joelho/metabolismo , Osteoartrite do Joelho/metabolismo , Osteoartrite do Joelho/etiologia , Cartilagem Articular/metabolismo , Cartilagem Articular/efeitos dos fármacos , Cartilagem Articular/patologia , Camundongos Endogâmicos C57BLRESUMO
Access to genomic sequencing (GS) and resulting recommendations have not been well described in pediatric oncology. GS results may provide a cancer predisposition syndrome (CPS) diagnosis that warrants screening and specialist visits beyond cancer treatment, including testing or surveillance for family members. The Texas KidsCanSeq (KCS) Study evaluated implementation of GS in a diverse pediatric oncology population. We conducted semi-structured interviews (n = 20) to explore experiences of KCS patients' families around learning about a CPS diagnosis and following up on recommended care. We used qualitative content analysis to develop themes and subthemes across families' descriptions of their experiences accessing care and to understand which factors presented barriers and/or facilitators. We found participants had difficulty differentiating which follow-up care recommendations were made for their child's current cancer treatment versus the CPS. In families' access to follow-up care for CPS, organizational factors were crucial: travel time and distance were common hardships, while coordination of care to streamline multiple appointments with different providers helped facilitate CPS care. Financial factors also impacted families' access to CPS-related follow-up care: having financial assistance and insurance were facilitators for families, while costs and lack of insurance posed as barriers for patients who lost coverage during transitions from pediatric to adult care, and for adult family members who had no coverage. Factors related to beliefs and perceptions, specifically perceiving the risk as less salient to them and feeling overwhelmed with the patient's cancer care, presented barriers to follow-up care primarily for family members. Regarding social factors, competing life priorities made it difficult for families to access follow-up care, though having community support alleviated these barriers. We suggest interventions to improve coordination of cancer treatment and CPS-related care and adherence to surveillance protocols for families as children age, such as care navigators and integrating longitudinal genetic counseling into hereditary cancer centers.
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Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, which are usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification and prioritization of microbial and host proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant (to generate peptide-spectral matches (PSMs) and quantification), PepQuery2 (to verify the quality of PSMs), and Unipept and MSstatsTMT (for taxonomy and functional annotation). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies.
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Objective: To develop an imaging mass cytometry method for identifying complex cell phenotypes, inter-cellular interactions, and population changes in the synovium and infrapatellar fat pad (IFP) of the mouse knee following a non-invasive compression injury. Design: Fifteen male C57BL/6 mice were fed a high-fat diet for 8 weeks prior to random assignment to sham, 0.88 âmm, or 1.7 âmm knee compression displacement at 24 weeks of age. 2-weeks after loading, limbs were prepared for histologic and imaging mass cytometry analysis, focusing on myeloid immune cell populations in the synovium and IFP. Results: 1.7 âmm compression caused anterior cruciate ligament (ACL) rupture, development of post-traumatic osteoarthritis, and a 2- to 3-fold increase in cellularity of synovium and IFP tissues compared to sham or 0.88 âmm compression. Imaging mass cytometry identified 11 myeloid cell subpopulations in synovium and 7 in IFP, of which approximately half were elevated 2 weeks after ACL injury in association with the vasculature. Notably, two monocyte/macrophage subpopulations and an MHC IIhi population were elevated 2-weeks post-injury in the synovium but not IFP. Vascular and immune cell interactions were particularly diverse in the synovium, incorporating 8 unique combinations of 5 myeloid cell populations, including a monocyte/macrophage population, an MHC IIhi population, and 3 different undefined F4/80+ myeloid populations. Conclusions: Developing an imaging mass cytometry method for the mouse enabled us to identify a diverse array of synovial and IFP vascular-associated myeloid cell subpopulations. These subpopulations were differentially elevated in synovial and IFP tissues 2-weeks post injury, providing new details on tissue-specific immune regulation.
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Hemoglobin (Hb) adducts are widely used in human biomonitoring due to the high abundance of hemoglobin in human blood, its reactivity toward electrophiles, and adducted protein stability for up to 120 days. In the present paper, we compared three methods of analysis of hemoglobin adducts: mass spectrometry of derivatized N-terminal Val adducts, mass spectrometry of N-terminal adducted hemoglobin peptides, and limited proteolysis mass spectrometry . Blood from human donors was incubated with a selection of contact allergens and other electrophiles, after which hemoglobin was isolated and subjected to three analysis methods. We found that the FIRE method was able to detect and reliably quantify N-terminal adducts of acrylamide, acrylic acid, glycidic acid, and 2,3-epoxypropyl phenyl ether (PGE), but it was less efficient for 2-methyleneglutaronitrile (2-MGN) and failed to detect 1-chloro-2,4-dinitrobenzene (DNCB). By contrast, bottom-up proteomics was able to determine the presence of adducts from all six electrophiles at both the N-terminus and reactive hemoglobin side chains. Limited proteolysis mass spectrometry, studied for four contact allergens (three electrophiles and a metal salt), was able to determine the presence of covalent hemoglobin adducts with one of the three electrophiles (DNCB) and coordination complexation with the nickel salt. Together, these approaches represent complementary tools in the study of the hemoglobin adductome.
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Dinitroclorobenzeno , Hemoglobinas , Humanos , Hemoglobinas/análise , Espectrometria de MassasRESUMO
INTRODUCTION: Continuous advances in mass spectrometry (MS) technologies have enabled deeper and more reproducible proteome characterization and a better understanding of biological systems when integrated with other 'omics data. Bioinformatic resources meeting the analysis requirements of increasingly complex MS-based proteomic data and associated multi-omic data are critically needed. These requirements included availability of software that would span diverse types of analyses, scalability for large-scale, compute-intensive applications, and mechanisms to ease adoption of the software. AREAS COVERED: The Galaxy ecosystem meets these requirements by offering a multitude of open-source tools for MS-based proteomics analyses and applications, all in an adaptable, scalable, and accessible computing environment. A thriving global community maintains these software and associated training resources to empower researcher-driven analyses. EXPERT OPINION: The community-supported Galaxy ecosystem remains a crucial contributor to basic biological and clinical studies using MS-based proteomics. In addition to the current status of Galaxy-based resources, we describe ongoing developments for meeting emerging challenges in MS-based proteomic informatics. We hope this review will catalyze increased use of Galaxy by researchers employing MS-based proteomics and inspire software developers to join the community and implement new tools, workflows, and associated training content that will add further value to this already rich ecosystem.
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Proteômica , Humanos , Biologia Computacional/métodos , Espectrometria de Massas/métodos , Proteômica/métodos , SoftwareRESUMO
Exogenous compounds and metabolites derived from therapeutics, microbiota, or environmental exposures directly interact with endogenous metabolic pathways, influencing disease pathogenesis and modulating outcomes of clinical interventions. With few spectral library references, the identification of covalently modified biomolecules, secondary metabolites, and xenobiotics is a challenging task using global metabolomics profiling approaches. Numerous liquid chromatography-coupled mass spectrometry (LC-MS) small molecule analytical workflows have been developed to curate global profiling experiments for specific compound groups of interest. These workflows exploit shared structural moiety, functional groups, or elemental composition to discover novel and undescribed compounds through nontargeted small molecule discovery pipelines. This Review introduces the concept of structure-oriented LC-MS discovery methodology and aims to highlight common approaches employed for the detection and characterization of covalently modified biomolecules, secondary metabolites, and xenobiotics. These approaches represent a combination of instrument-dependent and computational techniques to rapidly curate global profiling experiments to detect putative ions of interest based on fragmentation patterns, predictable phase I or phase II metabolic transformations, or rare elemental composition. Application of these methods is explored for the detection and identification of novel and undescribed biomolecules relevant to the fields of toxicology, pharmacology, and drug discovery. Continued advances in these methods expand the capacity for selective compound discovery and characterization that promise remarkable insights into the molecular interactions of exogenous chemicals with host biochemical pathways.
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Espectrometria de Massas em Tandem , Xenobióticos , Cromatografia Líquida , Descoberta de Drogas , Exposição AmbientalRESUMO
Leptin is a proinflammatory adipokine that contributes to obesity-associated osteoarthritis (OA), especially in women. However, the extent to which leptin causes knee OA separate from the effect of increased body weight is not clear. We hypothesized that leptin is necessary to induce knee OA in obese female rats but not sufficient to induce knee OA in lean rats lacking systemic metabolic inflammation. The effect of obesity without leptin signaling was modeled by comparing female lean Zucker rats to pair fed obese Zucker rats, which possess mutant fa alleles of the leptin receptor gene. The effect of leptin without obesity was modeled in female F344BN F1 hybrid rats by systemically administering recombinant rat leptin versus saline for 23 weeks via osmotic pumps. Primary OA outcomes included cartilage histopathology and subchondral bone micro-computed tomography. Secondary outcomes included targeted cartilage proteomics, serum inflammation, and synovial fluid inflammation following an acute intra-articular challenge with interleukin-1ß (IL-1ß). Compared to lean Zucker rats, obese Zucker rats developed more severe tibial osteophytes and focal cartilage lesions in the medial tibial plateau, with modest changes in proximal tibial epiphysis trabecular bone structure. In contrast, exogenous leptin treatment, which increased plasma leptin sixfold without altering body weight, caused mild generalized cartilage fibrillation and reduced Safranin O staining compared to vehicle-treated animals. Leptin also significantly increased subchondral and trabecular bone volume and bone mineral density in the proximal tibia. Cartilage metabolic and antioxidant enzyme protein levels were substantially elevated with leptin deficiency and minimally suppressed with leptin treatment. In contrast, leptin treatment induced greater changes in systemic and local inflammatory mediators compared to leptin receptor deficiency, including reduced serum IL-6 and increased synovial fluid IL-1ß. In conclusion, rat models that separately elevate leptin or body weight develop distinct OA-associated phenotypes, revealing how obesity increases OA pathology through both leptin-dependent and independent pathways. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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During the COVID-19 pandemic, impaired immunity and medical interventions resulted in cases of secondary infections. The clinical difficulties and dangers associated with secondary infections in patients necessitate the exploration of their microbiome. Metaproteomics is a powerful approach to study the taxonomic composition and functional status of the microbiome under study. In this study, the mass spectrometry (MS)-based data of nasopharyngeal swab samples from COVID-19 patients was used to investigate the metaproteome. We have established a robust bioinformatics workflow within the Galaxy platform, which includes (a) generation of a tailored database of the common respiratory tract pathogens, (b) database search using multiple search algorithms, and (c) verification of the detected microbial peptides. The microbial peptides detected in this study, belong to several opportunistic pathogens such as Streptococcus pneumoniae, Klebsiella pneumoniae, Rhizopus microsporus, and Syncephalastrum racemosum. Microbial proteins with a role in stress response, gene expression, and DNA repair were found to be upregulated in severe patients compared to negative patients. Using parallel reaction monitoring (PRM), we confirmed some of the microbial peptides in fresh clinical samples. MS-based clinical metaproteomics can serve as a powerful tool for detection and characterization of potential pathogens, which can significantly impact the diagnosis and treatment of patients.
Assuntos
COVID-19 , Coinfecção , Humanos , COVID-19/diagnóstico , Pandemias , Peptídeos , NasofaringeRESUMO
BACKGROUND: 'Omics methods have empowered scientists to tackle the complexity of microbial communities on a scale not attainable before. Individually, omics analyses can provide great insight; while combined as "meta-omics", they enhance the understanding of which organisms occupy specific metabolic niches, how they interact, and how they utilize environmental nutrients. Here we present three integrative meta-omics workflows, developed in Galaxy, for enhanced analysis and integration of metagenomics, metatranscriptomics, and metaproteomics, combined with our newly developed web-application, ViMO (Visualizer for Meta-Omics) to analyse metabolisms in complex microbial communities. RESULTS: In this study, we applied the workflows on a highly efficient cellulose-degrading minimal consortium enriched from a biogas reactor to analyse the key roles of uncultured microorganisms in complex biomass degradation processes. Metagenomic analysis recovered metagenome-assembled genomes (MAGs) for several constituent populations including Hungateiclostridium thermocellum, Thermoclostridium stercorarium and multiple heterogenic strains affiliated to Coprothermobacter proteolyticus. The metagenomics workflow was developed as two modules, one standard, and one optimized for improving the MAG quality in complex samples by implementing a combination of single- and co-assembly, and dereplication after binning. The exploration of the active pathways within the recovered MAGs can be visualized in ViMO, which also provides an overview of the MAG taxonomy and quality (contamination and completeness), and information about carbohydrate-active enzymes (CAZymes), as well as KEGG annotations and pathways, with counts and abundances at both mRNA and protein level. To achieve this, the metatranscriptomic reads and metaproteomic mass-spectrometry spectra are mapped onto predicted genes from the metagenome to analyse the functional potential of MAGs, as well as the actual expressed proteins and functions of the microbiome, all visualized in ViMO. CONCLUSION: Our three workflows for integrative meta-omics in combination with ViMO presents a progression in the analysis of 'omics data, particularly within Galaxy, but also beyond. The optimized metagenomics workflow allows for detailed reconstruction of microbial community consisting of MAGs with high quality, and thus improves analyses of the metabolism of the microbiome, using the metatranscriptomics and metaproteomics workflows.