Proteomics analysis of deep fascia in acute compartment syndrome.

Acute compartment syndrome (ACS) is a syndrome in which local circulation is affected due to increased pressure within the compartment. We previously found in patients with calf fractures, the pressure of fascial compartment could be sharply reduced upon the appearance of tension blisters. Deep fascia, as the important structure for compartment, might play key role in this process. Therefore, the aim of the present study was to examine the differences in gene profile in deep fascia tissue in fracture patients of the calf with or without tension blisters, and to explore the role of fascia in pressure improvement in ACS. Patients with lower leg fracture were enrolled and divided into control group (CON group, n = 10) without tension blister, and tension blister group (TB group, n = 10). Deep fascia tissues were collected and LC-MS/MS label-free quantitative proteomics were performed. Genes involved in fascia structure and fibroblast function were further validated by Western blot. The differentially expressed proteins were found to be mainly enriched in pathways related to protein synthesis and processing, stress fiber assembly, cell-substrate adhesion, leukocyte mediated cytotoxicity, and cellular response to stress. Compared with the CON group, the expression of Peroxidasin homolog (PXDN), which promotes the function of fibroblasts, and Leukocyte differentiation antigen 74 (CD74), which enhances the proliferation of fibroblasts, were significantly upregulated (p all <0.05), while the expression of Matrix metalloproteinase-9 (MMP9), which is involved in collagen hydrolysis, and Neutrophil elastase (ELANE), which is involved in elastin hydrolysis, were significantly reduced in the TB group (p all <0.05), indicating fascia tissue underwent microenvironment reconstruction during ACS. In summary, the ACS accompanied by blisters is associated with the enhanced function and proliferation of fibroblasts and reduced hydrolysis of collagen and elastin. The adaptive alterations in the stiffness and elasticity of the deep fascia might be crucial for pressure release of ACS.

Labeled-free quantitative proteomic analysis of cervical squamous cell carcinoma identifies potential protein biomarkers.

Background: Cervical cancer remains a prevalent cancer among women, and reliance on surgical and radio-chemical therapies can irreversibly affect patients' life span and quality of life. Thus, early diagnosis and further exploration into the pathogenesis of cervical cancer are crucial. Mass spectrometry technology is widely applied in clinical practice and can be used to further investigate the protein alterations during the onset of cervical cancer. Methods: Employing labeled-free quantitative proteomics technology and bioinformatics tools, we analyzed and compared the differential protein expression profiles between normal cervical squamous cell tissues and cervical squamous cell cancer tissues. GEPIA is an online website for analyzing the RNA sequencing expression data of tumor and normal tissue data from the TCGA and the GTEx databases. This approach aided in identifying qualitative and quantitative changes in key proteins related to the progression of cervical cancer. Results: Compared to normal samples, a total of 562 differentially expressed proteins were identified in cervical cancer samples, including 340 up-regulated and 222 down-regulated proteins. Gene ontology functional annotation, and KEGG pathway, and enrichment analysis revealed that the differentially expressed proteins mainly participated in metabolic pathways, spliceosomes, regulation of the actin cytoskeleton, and focal adhesion signaling pathways. Specifically, desmoplakin (DSP), protein phosphatase 1, regulatory (inhibitor) subunit 13 like (PPP1R13L) and ANXA8 may be involved in cervical tumorigenesis by inhibiting apoptotic signal transmission. Moreover, we used GEPIA database to validate the expression of DSP, PPP1R13L and ANXA8 in human cancers and normal cervix. Conclusion: In this study, we identified 562 differentially expressed proteins, and there were three proteins expressed higher in the cervical cancer tissues. The functions and signaling pathways of these differentially expressed proteins lay a theoretical foundation for elucidating the molecular mechanisms of cervical cancer.

PowerNovo: de novo peptide sequencing via tandem mass spectrometry using an ensemble of transformer and BERT models.

The primary objective of analyzing the data obtained in a mass spectrometry-based proteomic experiment is peptide and protein identification, or correct assignment of the tandem mass spectrum to one amino acid sequence. Comparison of empirical fragment spectra with the theoretical predicted one or matching with the collected spectra library are commonly accepted strategies of proteins identification and defining of their amino acid sequences. Although these approaches are widely used and are appreciably efficient for the well-characterized model organisms or measured proteins, they cannot detect novel peptide sequences that have not been previously annotated or are rare. This study presents PowerNovo tool for de novo sequencing of proteins using tandem mass spectra acquired in a variety of types of mass analyzers and different fragmentation techniques. PowerNovo involves an ensemble of models for peptide sequencing: model for detecting regularities in tandem mass spectra, precursors, and fragment ions and a natural language processing model, which has a function of peptide sequence quality assessment and helps with reconstruction of noisy sequences. The results of testing showed that the performance of PowerNovo is comparable and even better than widely utilized PointNovo, DeepNovo, Casanovo, and Novor packages. Also, PowerNovo provides complete cycle of processing (pipeline) of mass spectrometry data and, along with predicting the peptide sequence, involves the peptide assembly and protein inference blocks.

Extracellular matrix remodelling pathway in peripheral blood mononuclear cells from severe COVID-19 patients: an explorative study.

There is a reciprocal relationship between extracellular matrix (ECM) remodelling and inflammation that could be operating in the progression of severe COVID-19. To explore the immune-driven ECM remodelling in COVID-19, we in this explorative study analysed these interactions in hospitalised COVID-19 patients. RNA sequencing and flow analysis were performed on peripheral blood mononuclear cells. Inflammatory mediators in plasma were measured by ELISA and MSD, and clinical information from hospitalised COVID-19 patients (N=15) at admission was included in the analysis. Further, we reanalysed two publicly available datasets: (1) lung tissue RNA-sequencing dataset (N=5) and (2) proteomics dataset from PBCM. ECM remodelling pathways were enriched in PBMC from COVID-19 patients compared to healthy controls. Patients treated at the intensive care unit (ICU) expressed distinct ECM remodelling gene profiles compared to patients in the hospital ward. Several markers were strongly correlated to immune cell subsets, and the dysregulation in the ICU patients was positively associated with plasma levels of inflammatory cytokines and negatively associated with B-cell activating factors. Finally, our analysis of publicly accessible datasets revealed (i) an augmented ECM remodelling signature in inflamed lung tissue compared to non-inflamed tissue and (ii) proteomics analysis of PBMC from severe COVID-19 patients demonstrated an up-regulation in an ECM remodelling pathway. Our results may suggest the presence of an interaction between ECM remodelling, inflammation, and immune cells, potentially initiating or perpetuating pulmonary pathology in severe COVID-19.

Mosquitocidal toxin-like islands in Bacillus thuringiensis S2160-1 revealed by complete-genome sequence and MS proteomic analysis.

Here, we present the whole genome sequence of Bt S2160-1, a potential alternative to the mosquitocidal model strain, Bti. One chromosome genome and four mega-plasmids were contained in Bt S2160-1, and 13 predicted genes encoding predicted insecticidal crystal proteins were identified clustered on one plasmid pS2160-1p2 containing two pathogenic islands (PAIs) designed as PAI-1 (Cry54Ba, Cry30Ea4, Cry69Aa-like, Cry50Ba2-like, Cry4Ca1-like, Cry30Ga2, Cry71Aa-like, Cry72Aa-like, Cry70Aa-like, Cyt1Da2-like and Vpb4C1-like) and PAI-2 (Cyt1Aa-like, and Tpp80Aa1-like). The clusters appear to represent mosquitocidal toxin islands similar to pathogenicity islands. Transcription/translation of 10 of the 13 predicted genes was confirmed by whole-proteome analysis using LTQ-Orbitrap LC-MS/MS. In summary, the present study identified the existence of a mosquitocidal toxin island in Bacillus thuringiensis, and provides important genomic information for understanding the insecticidal mechanism of B. thuringiensis.

Integrative multi-omics analysis unravels the host response landscape and reveals a serum protein panel for early prognosis prediction for ARDS.

BACKGROUND: The multidimensional biological mechanisms underpinning acute respiratory distress syndrome (ARDS) continue to be elucidated, and early biomarkers for predicting ARDS prognosis are yet to be identified. METHODS: We conducted a multicenter observational study, profiling the 4D-DIA proteomics and global metabolomics of serum samples collected from patients at the initial stage of ARDS, alongside samples from both disease control and healthy control groups. We identified 28-day prognosis biomarkers of ARDS in the discovery cohort using the LASSO method, fold change analysis, and the Boruta algorithm. The candidate biomarkers were validated through parallel reaction monitoring (PRM) targeted mass spectrometry in an external validation cohort. Machine learning models were applied to explore the biomarkers of ARDS prognosis. RESULTS: In the discovery cohort, comprising 130 adult ARDS patients (mean age 72.5, 74.6% male), 33 disease controls, and 33 healthy controls, distinct proteomic and metabolic signatures were identified to differentiate ARDS from both control groups. Pathway analysis highlighted the upregulated sphingolipid signaling pathway as a key contributor to the pathological mechanisms underlying ARDS. MAP2K1 emerged as the hub protein, facilitating interactions with various biological functions within this pathway. Additionally, the metabolite sphingosine 1-phosphate (S1P) was closely associated with ARDS and its prognosis. Our research further highlights essential pathways contributing to the deceased ARDS, such as the downregulation of hematopoietic cell lineage and calcium signaling pathways, contrasted with the upregulation of the unfolded protein response and glycolysis. In particular, GAPDH and ENO1, critical enzymes in glycolysis, showed the highest interaction degree in the protein-protein interaction network of ARDS. In the discovery cohort, a panel of 36 proteins was identified as candidate biomarkers, with 8 proteins (VCAM1, LDHB, MSN, FLG2, TAGLN2, LMNA, MBL2, and LBP) demonstrating significant consistency in an independent validation cohort of 183 patients (mean age 72.6 years, 73.2% male), confirmed by PRM assay. The protein-based model exhibited superior predictive accuracy compared to the clinical model in both the discovery cohort (AUC: 0.893 vs. 0.784; Delong test, P < 0.001) and the validation cohort (AUC: 0.802 vs. 0.738; Delong test, P = 0.008). INTERPRETATION: Our multi-omics study demonstrated the potential biological mechanism and therapy targets in ARDS. This study unveiled several novel predictive biomarkers and established a validated prediction model for the poor prognosis of ARDS, offering valuable insights into the prognosis of individuals with ARDS.

An integrated comparative genomics, subtractive proteomics and immunoinformatics framework for the rational design of a Pan-Salmonella multi-epitope vaccine.

Salmonella infections pose a significant global public health concern due to the substantial expenses associated with monitoring, preventing, and treating the infection. In this study, we explored the core proteome of Salmonella to design a multi-epitope vaccine through Subtractive Proteomics and immunoinformatics approaches. A total of 2395 core proteins were curated from 30 different isolates of Salmonella (strain NZ CP014051 was taken as reference). Utilizing the subtractive proteomics approach on the Salmonella core proteome, Curlin major subunit A (CsgA) was selected as the vaccine candidate. csgA is a conserved gene that is related to biofilm formation. Immunodominant B and T cell epitopes from CsgA were predicted using numerous immunoinformatics tools. T lymphocyte epitopes had adequate population coverage and their corresponding MHC alleles showed significant binding scores after peptide-protein based molecular docking. Afterward, a multi-epitope vaccine was constructed with peptide linkers and Human Beta Defensin-2 (as an adjuvant). The vaccine could be highly antigenic, non-toxic, non-allergic, and have suitable physicochemical properties. Additionally, Molecular Dynamics Simulation and Immune Simulation demonstrated that the vaccine can bind with Toll Like Receptor 4 and elicit a robust immune response. Using in vitro, in vivo, and clinical trials, our findings could yield a Pan-Salmonella vaccine that might provide protection against various Salmonella species.

Temporally resolved proteomics identifies nidogen-2 as a cotarget in pancreatic cancer that modulates fibrosis and therapy response.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by increasing fibrosis, which can enhance tumor progression and spread. Here, we undertook an unbiased temporal assessment of the matrisome of the highly metastatic KPC (Pdx1-Cre, LSL-KrasG12D/+, LSL-Trp53R172H/+) and poorly metastatic KPflC (Pdx1-Cre, LSL-KrasG12D/+, Trp53fl/+) genetically engineered mouse models of pancreatic cancer using mass spectrometry proteomics. Our assessment at early-, mid-, and late-stage disease reveals an increased abundance of nidogen-2 (NID2) in the KPC model compared to KPflC, with further validation showing that NID2 is primarily expressed by cancer-associated fibroblasts (CAFs). Using biomechanical assessments, second harmonic generation imaging, and birefringence analysis, we show that NID2 reduction by CRISPR interference (CRISPRi) in CAFs reduces stiffness and matrix remodeling in three-dimensional models, leading to impaired cancer cell invasion. Intravital imaging revealed improved vascular patency in live NID2-depleted tumors, with enhanced response to gemcitabine/Abraxane. In orthotopic models, NID2 CRISPRi tumors had less liver metastasis and increased survival, highlighting NID2 as a potential PDAC cotarget.

Changes in the Proteome of the Circle of Willis during Aging Reveal Signatures of Vascular Disease.

Approximately 70% of all strokes occur in patients over 65 years old, and stroke increases the risk of developing dementia. The circle of Willis (CoW), the ring of arteries at the base of the brain, links the intracerebral arteries to one another to maintain adequate cerebral perfusion. The CoW proteome is affected in cerebrovascular and neurodegenerative diseases, but changes related to aging have not been described. Here, we report on a quantitative proteomics analysis comparing the CoW from five young (2-3-month-old) and five aged male (18-20-month-old) mice using gene ontology (GO) enrichment, ingenuity pathway analysis (IPA), and iPathwayGuide tools. This revealed 242 proteins that were significantly dysregulated with aging, among which 189 were upregulated and 53 downregulated. GO enrichment-based analysis identified blood coagulation as the top biological function that changed with age and integrin binding and extracellular matrix constituents as the top molecular functions. Consistent with these findings, iPathwayGuide-based impact analysis revealed associations between aging and the complement and coagulation, platelet activation, ECM-receptor interaction, and metabolic process pathways. Furthermore, IPA analysis revealed the enrichment of 97 canonical pathways that contribute to inflammatory responses, as well as 59 inflammation-associated upstream regulators including 39 transcription factors and 20 cytokines. Thus, aging-associated changes in the CoW proteome in male mice demonstrate increases in metabolic, thrombotic, and inflammatory processes.

Proteomic analysis of Rana sylvatica reveals differentially expressed proteins in liver in response to anoxia, dehydration or freezing stress.

Ectothermic animals that live in seasonally cold regions must adapt to seasonal variation and specific environmental conditions. During the winter, some amphibians hibernate on land and encounter limited environmental water, deficient oxygen, and extremely low temperatures that can cause the whole body freezing. These stresses trigger physiological and biochemical adaptations in amphibians that allow them to survive. Rana sylvatica, commonly known as the wood frog, shows excellent freeze tolerance. They can slow their metabolic activity to a near halt and endure freezing of 65-70% of their total body water as extracellular ice during hibernation, returning to normal when the temperatures rise again. To investigate the molecular adaptations of freeze-tolerant wood frogs, a comprehensive proteomic analysis was performed on frog liver tissue after anoxia, dehydration, or freezing exposures using a label-free LC-MS/MS proteomic approach. Quantitative proteomic analysis revealed that 87, 118, and 86 proteins were significantly upregulated in dehydrated, anoxic, and frozen groups, suggesting potential protective functions. The presence of three upregulated enzymes, glutathione S-transferase (GST), aldolase (ALDOA), and sorbitol dehydrogenase (SORD), was also validated. For all enzymes, the specific enzymatic activity was significantly higher in the livers of frozen and anoxic groups than in the controls. This study reveals that GST, ALDOA, and SORD might participate in the freeze tolerance mechanism by contributing to regulating cellular detoxification and energy metabolism.

Integrated serum proteomic and N-glycoproteomic characterization of dengue patients.

Dengue fever is a mosquito-borne viral disease caused by the dengue virus (DENV). It poses a public health threat globally and, while most people with dengue have mild symptoms or are asymptomatic, approximately 5% of affected individuals develop severe disease and need hospital care. However, knowledge of the molecular mechanisms underlying dengue infection and the interaction between the virus and its host remains limited. In the present study, we performed a quantitative proteomic and N-glycoproteomic analysis of serum from 19 patients with dengue and 11 healthy people. The results revealed distinct proteomic and N-glycoproteomic landscapes between the two groups. Notably, we report for the first time the changes in the serum N glycosylation pattern following dengue infection and provide abundant information on glycoproteins, glycosylation sites, and intact N-glycopeptides using recently developed site-specific glycoproteomic approaches. Furthermore, a series of key functional pathways in proteomic and N-glycoproteomic were identified. Collectively, our findings significantly improve understanding of host and DENV interactions and the general pathogenesis and pathology of DENV, laying a foundation for functional studies of glycosylation and glycan structures in dengue infection.

Changes in cerebrospinal fluid proteome of patients with tick-borne encephalitis.

Tick-borne encephalitis (TBE) is one of the main diseases transmitted by ticks, the incidence of which is increasing. Moreover, its diagnosis and therapy are often long and difficult according to nonspecific symptoms and complex etiology. This study aimed to observe changes in the proteome of cerebrospinal fluid from TBE patients. Cerebrospinal fluid (CSF) of TBE patients (n = 20) and healthy individuals (n = 10) was analyzed using a proteomic approach (QExactiveHF-Orbitrap mass spectrometer) and zymography. Obtained results show that in CSF of TBE patients, the top-upregulated proteins are involved in pro-inflammatory reaction (interleukins), as well as antioxidant/protective response (peroxiredoxins, heat shock proteins). Moreover, changes in the proteome of CSF are not only the result of this disease development, but they can also be an indicator of its course. This mainly applies to proteins involved in proteolysis including serpins and metalloproteinases, whose activity is proportional to the length of patients' convalescence. The obtained proteomic data strongly direct attention to the changes caused by the development of TBE to antioxidant, pro-inflammatory, and proteolytic proteins, knowledge about which can significantly contribute to faster and more accurate diagnosis of various clinical forms of TBE.

The antioxidant effects of butylated hydroxytoluene on cryopreserved goat sperm from a proteomic perspective.

At present, there are few reports about the proteomics changes provoked by butylated hydroxytoluene (BHT) supplementation on cryopreserved semen in mammals. Thus, we aimed to evaluate the effects of different concentrations of BHT on goat sperm and to investigate the proteomics changes of adding BHT to cryopreserved goat (Capra hircus) sperm. Firstly, semen samples were collected from four goats, and frozen in the basic extenders containing different concentrations of BHT (0.5 mM, 1.0 mM, 2.0 mM) and a control without BHT, respectively. After thawing, the protective effects of dose-dependent replenished BHT to the freezing medium on post-thaw sperm motility, integrities of plasma membrane and acrosome, reactive oxygen species levels were confirmed, with 0.5 mM BHT being the best (B group) as compared to the control (without BHT, C group). Afterwards, TMT-based quantitative proteomic technique was performed to profile proteome of the goat sperm between C group and B group. Parallel reaction monitoring was used to confirm reliability of the data. Overall, 2,476 proteins were identified and quantified via this approach. Comparing the C and B groups directly (C vs. B), there were 17 differentially abundant proteins (DAPs) po-tentially associated with sperm characteristics and functions were identified, wherein three were upregulated and 14 were downregulated, respectively. GO annotation analysis demonstrated the potential involvement of the identified DAPs in metabolic process, multi-organism process, reproduction, reproductive process, and cellular process. KEGG enrichment analysis further indicated their potential roles in renin-angiotensin system and glutathione metabolism pathways. Together, this novel study clearly shows that BHT can effectively improve quality parameters and fertility potential of post-thawed goat sperm at the optimal concentration, and its cryoprotection may be realized through regulation of sperm metabolism and antioxidative capability from the perspective of sperm proteomic modification.

Multi-scale signaling and tumor evolution in high-grade gliomas.

Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas.

Proteomic Analysis of In Vitro Plant Tissues (Coffea canephora): A Case of Study.

Since the term proteomics was coined by Marc Wilkins in 1994, there has been an explosion in the number of articles reporting the use of the proteomics technique. As the layers of biological organization and their regulation increase, the complexity of living beings increases. Thus, we go from the genome to tissues, cells, cellular compartments, and phenotypes and the complexity of the tools used to study this complexity also increases. Unlike the genome study, in the case of the proteome, we have a more complex panorama. We have a spatial and temporal proteome. Proteomics helps to answer complex biological questions since proteins' function depends on their molecular structure, subcellular localization, and posttranslational modifications. In this protocol, we describe a methodology to extract proteins using different methods, separating proteins by electrophoresis in double-dimensional gels and analyzing the gels using specialized software that allows obtaining information on the number and abundance of the proteins from the gels.

Exploring the Alternative Proteome with OpenProt and Mass Spectrometry.

Proteogenomics has revealed the translation of unannotated open reading frames (ORFs) present in mRNAs and in noncoding RNAs (ncRNAs). OpenProt annotates all ORFs with a minimum of 30 codons in the transcriptome of several species and displays many functional features associated with the corresponding proteins. Two types of proteins are annotated: reference or canonical proteins which are proteins already annotated in UniProt, RefSeq, or Ensembl and noncanonical proteins. Noncanonical proteins form two groups: predicted novel isoforms that display a significant level of homology with a reference protein and alternative proteins that are new proteins with no significant homology to known proteins. This chapter describes how to check whether a gene and/or transcript contains multiple open reading frames and how to use OpenProt databases for the detection of alternative proteins and novel isoforms by mass spectrometry-based proteomics.

Identification of Novel Bacterial Microproteins Encoded by Small Open Reading Frames Using a Computational Proteogenomics Workflow.

Genome annotation has historically ignored small open reading frames (smORFs), which encode a class of proteins shorter than 100 amino acids, collectively referred to as microproteins. This cutoff was established to avoid thousands of false positives due to limitations of pure genomics pipelines. Proteogenomics, a computational approach that combines genomics, transcriptomics, and proteomics, makes it possible to accurately identify these short sequences by overlaying different levels of omics evidence. In this chapter, we showcase the use of µProteInS, a bioinformatics pipeline developed for the identification of unannotated microproteins encoded by smORFs in bacteria. The workflow covers all the steps from quality control and transcriptome assembly to the scoring and post-processing of mass spectrometry data. Additionally, we provide an example on how to apply the pipeline's machine learning method to identify high-confidence spectra and pinpoint the most reliable identifications from large datasets.

Understanding PTM Cross Talk Through a Visualization Tool, PTMViz.

The advancement of sequencing technologies has expanded our understanding of biological complexity through mechanisms such as allelic variations, alternative splicing of RNA, degradation of RNA by microRNAs, and posttranslational modifications (PTMs). In this chapter, we describe a method, PTMViz, for analyzing proteoforms identified by mass spectrometry. This interactive platform provides differential abundance analysis and visualization of protein and posttranslational modifications. We describe the detailed steps to prepare mass spectrometry database search results into the necessary format for PTMViz, how to set up the experimental conditions for differential abundance analysis, and the visualization of the results. The application is freely available at https://github.com/ByrumLab/PTMViz .

Integrating HexNAcQuest with Glycoproteomics Data Analysis Software to Distinguish HexNAc Isomers on Peptides.

Recently, HexNAcQuest was developed to help distinguish peptides modified by HexNAc isomers, more specifically O-linked ß-N-acetylglucosamine (O-GlcNAc) and O-linked α-N-acetylgalactosamine (O-GalNAc, Tn antigen). To facilitate its usage (particularly for datasets from glycoproteomics studies), herein we present a detailed protocol. It describes example cases and procedures for which users might need to use HexNAcQuest to distinguish these two modifications.