Enriched protein screening of human bone marrow mesenchymal stromal cell secretions reveals MFAP5 and PENK as novel IL-10 modulators.
Milwid Jack M,Elman Jessica S,Li Matthew,Shen Keyue,Manrai Arjun,Gabow Aaron,Yarmush Joshua,Jiao Yunxin,Fletcher Anne,Lee Jungwoo,Cima Michael J,Yarmush Martin L,Parekkadan Biju
Molecular therapy : the journal of the American Society of Gene Therapy
The secreted proteins from a cell constitute a natural biologic library that can offer significant insight into human health and disease. Discovering new secreted proteins from cells is bounded by the limitations of traditional separation and detection tools to physically fractionate and analyze samples. Here, we present a new method to systematically identify bioactive cell-secreted proteins that circumvent traditional proteomic methods by first enriching for protein candidates by differential gene expression profiling. The bone marrow stromal cell secretome was analyzed using enriched gene expression datasets in combination with potency assay testing. Four proteins expressed by stromal cells with previously unknown anti-inflammatory properties were identified, two of which provided a significant survival benefit to mice challenged with lethal endotoxic shock. Greater than 85% of secreted factors were recaptured that were otherwise undetected by proteomic methods, and remarkable hit rates of 18% in vitro and 9% in vivo were achieved.
Genomic transcriptional profiling identifies a candidate blood biomarker signature for the diagnosis of septicemic melioidosis.
Pankla Rungnapa,Buddhisa Surachat,Berry Matthew,Blankenship Derek M,Bancroft Gregory J,Banchereau Jacques,Lertmemongkolchai Ganjana,Chaussabel Damien
BACKGROUND:Melioidosis is a severe infectious disease caused by Burkholderia pseudomallei, a Gram-negative bacillus classified by the National Institute of Allergy and Infectious Diseases (NIAID) as a category B priority agent. Septicemia is the most common presentation of the disease with a 40% mortality rate even with appropriate treatments. Better diagnostic tests are therefore needed to improve therapeutic efficacy and survival rates. RESULTS:We have used microarray technology to generate genome-wide transcriptional profiles (>48,000 transcripts) from the whole blood of patients with septicemic melioidosis (n = 32), patients with sepsis caused by other pathogens (n = 31), and uninfected controls (n = 29). Unsupervised analyses demonstrated the existence of a whole blood transcriptional signature distinguishing patients with sepsis from control subjects. The majority of changes observed were common to both septicemic melioidosis and sepsis caused by other infections, including genes related to inflammation, interferon-related genes, neutrophils, cytotoxic cells, and T-cells. Finally, class prediction analysis identified a 37 transcript candidate diagnostic signature that distinguished melioidosis from sepsis caused by other organisms with 100% accuracy in a training set. This finding was confirmed in 2 independent validation sets, which gave high prediction accuracies of 78% and 80%, respectively. This signature was significantly enriched in genes coding for products involved in the MHC class II antigen processing and presentation pathway. CONCLUSIONS:Blood transcriptional patterns distinguish patients with septicemic melioidosis from patients with sepsis caused by other pathogens. Once confirmed in a large scale trial this diagnostic signature might constitute the basis of a differential diagnostic assay.
Development of a Bioinformatics Framework for Identification and Validation of Genomic Biomarkers and Key Immunopathology Processes and Controllers in Infectious and Non-infectious Severe Inflammatory Response Syndrome.
Tong Dong Ling,Kempsell Karen E,Szakmany Tamas,Ball Graham
Frontiers in immunology
Sepsis is defined as dysregulated host response caused by systemic infection, leading to organ failure. It is a life-threatening condition, often requiring admission to an intensive care unit (ICU). The causative agents and processes involved are multifactorial but are characterized by an overarching inflammatory response, sharing elements in common with severe inflammatory response syndrome (SIRS) of non-infectious origin. Sepsis presents with a range of pathophysiological and genetic features which make clinical differentiation from SIRS very challenging. This may reflect a poor understanding of the key gene inter-activities and/or pathway associations underlying these disease processes. Improved understanding is critical for early differential recognition of sepsis and SIRS and to improve patient management and clinical outcomes. Judicious selection of gene biomarkers suitable for development of diagnostic tests/testing could make differentiation of sepsis and SIRS feasible. Here we describe a methodologic framework for the identification and validation of biomarkers in SIRS, sepsis and septic shock patients, using a 2-tier gene screening, artificial neural network (ANN) data mining technique, using previously published gene expression datasets. Eight key hub markers have been identified which may delineate distinct, core disease processes and which show potential for informing underlying immunological and pathological processes and thus patient stratification and treatment. These do not show sufficient fold change differences between the different disease states to be useful as primary diagnostic biomarkers, but are instrumental in identifying candidate pathways and other associated biomarkers for further exploration.
The correlations between the serum expression of miR-206 and the severity and prognosis of sepsis.
Liang Guiwen,Wu Yao,Guan Yuwen,Dong Yansong,Jiang Lan,Mao Guomin,Wu Ruo,Huang Zhongwei,Jiang Haiyan,Qi Lei,Tang Jianzhong
Annals of palliative medicine
BACKGROUND:An accurate assessment of the severity and prognosis of sepsis, especially septic shock, is vital for the tailored treatment of this condition. miRNA participates in the inflammatory response and cell apoptosis and regulates inflammation-related signaling pathways. Immune disorders often accompany sepsis. Since serum miRNA expression is superior to traditional biological markers in terms of sensitivity and specificity, its role in the assessment of sepsis has increasingly been recognized. METHODS:Serum miRNAs were extracted from septic patients and healthy individuals by using the ultracentrifugation method. The differential expressions of miRNAs in the serum samples were detected by high-throughput sequencing technology. The differentially expressed miRNAs between the two groups were analyzed by bioinformatics. The quantitative polymerase chain reaction real-time polymerase chain reaction (qRT-PCR) was used to amplify the sample size to verify the results and to screen the highly-expressed miR206 in septic patients. Subsequently, serum samples were collected from 63 septic patients, and 30 patients with septic shock and qRT-PCR were performed to analyze the expression of miR-206. These 93 patients were divided into the miR-206 low-expression group and miR-206 high-expression group according to miR206 expression level. The potential correlations between the miR-206 expression and the clinical data were analyzed by using SPSS 25.0. RESULTS:Serum miRNA expression significantly differed between septic patients and healthy individuals. High-throughput sequencing results showed that, compared with those in healthy individuals, 29 miRNA molecules were down-regulated, and 25 molecules were up-regulated in the serum samples of septic patients. qRT-PCR identified the significantly up-regulated miR-206 in septic patients. qRT-PCR also showed significantly higher miR-206 expression levels in patients with septic shock than in septic patients. Furthermore, we observed a significantly longer prothrombin time and activated partial thromboplastin time, and significantly higher SOFA score, APACHE-II score, and in-hospital mortality rate. miR-206 was positively correlated with SOFA sore and APACHE-II score. CONCLUSIONS:Serum miR-206 expression is positively correlated with the severity and prognosis of sepsis. Thus, it may be a potential biomarker for assessing the severity and prognosis of sepsis, although the specific mechanism warrants further investigations.
Genome-wide expression profiling in pediatric septic shock.
Wong Hector R
For nearly a decade, our research group has had the privilege of developing and mining a multicenter, microarray-based, genome-wide expression database of critically ill children (≤10 y of age) with septic shock. Using bioinformatic and systems biology approaches, the expression data generated through this discovery-oriented, exploratory approach have been leveraged for a variety of objectives, which are reviewed here. Fundamental observations include widespread repression of gene programs corresponding to the adaptive immune system and biologically significant differential patterns of gene expression across developmental age groups. The data have also identified gene expression-based subclasses of pediatric septic shock having clinically relevant phenotypic differences. The data have also been leveraged for the discovery of novel therapeutic targets, as well as for the discovery and development of novel stratification and diagnostic biomarkers. Almost a decade of genome-wide expression profiling in pediatric septic shock is now demonstrating tangible results. The studies have progressed from an initial discovery-oriented and exploratory phase to a new phase in which the data are being translated and applied to address several areas of clinical need.
Single-cell deconstruction of post-sepsis skeletal muscle and adipose tissue microenvironments.
Cho Dong Seong,Schmitt Rebecca E,Dasgupta Aneesha,Ducharme Alexandra M,Doles Jason D
Journal of cachexia, sarcopenia and muscle
BACKGROUND:Persistent loss of skeletal muscle mass and function as well as altered fat metabolism are frequently observed in severe sepsis survivors. Studies examining sepsis-associated tissue dysfunction from the perspective of the tissue microenvironment are scarce. In this study, we comprehensively assessed transcriptional changes in muscle and fat at single-cell resolution following experimental sepsis induction. METHODS:Skeletal muscle and visceral white adipose tissue from control mice or mice 1 day or 1 month following faecal slurry-induced sepsis were used. Single cells were mechanically and enzymatically prepared from whole tissue, and viable cells were further isolated by fluorescence activated cell sorting. Droplet-based single-cell RNA-sequencing (scRNA-seq; 10× Genomics) was used to generate single-cell gene expression profiles of thousands of muscle and fat-resident cells. Bioinformatics analyses were performed to identify and compare individual cell populations in both tissues. RESULTS:In skeletal muscle, scRNA-seq analysis classified 1438 single cells into myocytes, endothelial cells, fibroblasts, mesenchymal stem cells, macrophages, neutrophils, T-cells, B-cells, and dendritic cells. In adipose tissue, scRNA-seq analysis classified 2281 single cells into adipose stem cells, preadipocytes, endothelial cells, fibroblasts, macrophages, dendritic cells, B-cells, T-cells, NK cells, and gamma delta T-cells. One day post-sepsis, the proportion of most non-immune cell populations was decreased, while immune cell populations, particularly neutrophils and macrophages, were highly enriched. Proportional changes of endothelial cells, neutrophils, and macrophages were validated using faecal slurry and cecal ligation and puncture models. At 1 month post-sepsis, we observed persistent enrichment/depletion of cell populations and further uncovered a cell-type and tissue-specific ability to return to a baseline transcriptomic state. Differential gene expression analyses revealed key genes and pathways altered in post-sepsis muscle and fat and highlighted the engagement of infection/inflammation and tissue damage signalling. Finally, regulator analysis identified gonadotropin-releasing hormone and Bay 11-7082 as targets/compounds that we show can reduce sepsis-associated loss of lean or fat mass. CONCLUSIONS:These data demonstrate persistent post-sepsis muscle and adipose tissue disruption at the single-cell level and highlight opportunities to combat long-term post-sepsis tissue wasting using bioinformatics-guided therapeutic interventions.
Continuous evaluation of changes in the serum proteome from early to late stages of sepsis caused by Klebsiella pneumoniae.
Raju M Swathi,V Jahnavi,Kamaraju Ratnakar S,Sritharan Venkataraman,Rajkumar Karthik,Natarajan Sumathi,Kumar Anil D,Burgula Sandeepta
Molecular medicine reports
Serum protein profiles of patients with bacterial sepsis from the day of diagnosis until recovery/mortality were compared from early to late stages in response to severe sepsis using two dimensional electrophoresis. The proteins exhibiting changes during the course of sepsis (20‑28 day mortality) were selected and identified by matrix‑assisted laser desorption ionization‑time of flight‑tandem mass spectrometry. Among the proteins identified, haptoglobin (Hp), transthyretin (TTR), orosomucoid 1/α1 acid glycoprotein (ORM1), α1 antitrypsin (A1AT), serum amyloid A (SAA) and S100A9 exhibited differential expression patterns between survivors (S; n=6) and non‑survivors (NS; n=6), particularly during the early stages of sepsis. Expression factors (EFs), taken as the ratio between the NS and S during early stages, showed ratios of Hp, 0.39 (P≤0.012); TTR, 3.96 (P≤0.03); ORM1, 0.69 (P≤0.79); A1AT, 0.92 (P≤0.87) and SAA, 0.69 (P≤0.01). S100A9, an acute phase protein, exhibited an EF ratio of 1.68 (P≤0.004) during the end stages of sepsis. A delayed rise in levels was observed in Hp, A1AT, ORM1, S100A9 and SAA, whereas TTR levels increased during the early stages of sepsis in NS. Analysis of inflammatory responses in the early stages of sepsis revealed increased mRNA expression in leukocytes of interleukin (IL)‑6 (EF, 2.50), IL‑10 (EF, 1.70) and prepronociceptin (EF, 1.6), which is a precursor for nociceptin in NS compared with S, and higher Toll‑like receptor‑4 (EF, 0.30) levels in S compared with NS. Therefore, a weaker acute phase response in the early stages of sepsis in NS, combined with an inefficient inflammatory response, may contribute to sepsis mortality.
Differential protein expression in patients with urosepsis.
Yang Xu-Kai,Wang Nan,Yang Cheng,Wang Yang-Min,Che Tuan-Jie
Chinese journal of traumatology = Zhonghua chuang shang za zhi
PURPOSE:Urosepsis in adults comprises approximately 25% of all sepsis cases, and is due to complicated urinary tract infections in most cases. However, its mechanism is not fully clarified. Urosepsis is a very complicated disease with no effective strategy for early diagnosis and treatment. This study aimed to identify possible target-related proteins involved in urosepsis using proteomics and establish possible networks using bioinformatics. METHODS:Fifty patients admitted to the Urology Unit of Lanzhou General PLA (Lanzhou, China), from October 2012 to October 2015, were enrolled in this study. The patients were further divided into shock and matched-pair non-shock groups. 2-DE technique, mass spectrometry and database search were used to detect differentially expressed proteins in serum from the two groups. RESULTS:Six proteins were found at higher levels in the shock group compared with non-shock individuals, including serum amyloid A-1 protein (SAA1), apolipoprotein L1 (APOL1), ceruloplasmin (CP), haptoglobin (HP), antithrombin-III (SERPINC1) and prothrombin (F2), while three proteins showed lower levels, including serotransferrin (TF), transthyretin (TTR) and alpha-2-macroglobulin (A2M). CONCLUSION:Nine proteins were differentially expressed between uroseptic patients (non-shock groups) and severe uroseptic patients (shock groups), compared with non-shock groups, serum SAA1, APOL1,CP, HP, SERPINC1and F2 at higher levels, while TF, TTR and A2M at lower levels in shock groups.these proteins were mainly involved in platelet activation, signaling and aggregation, acute phase protein pathway, lipid homeostasis, and iron ion transport, deserve further research as potential candidates for early diagnosis and treatment. (The conclusion seems too simple and vague, please re-write it. You may focus at what proteins have been expressed and introduce more detail about its significance.).
Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Pediatric Sepsis.
Xie Kexin,Kong Shan,Li Fuxing,Zhang Yulin,Wang Jing,Zhao Weidong
Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Sepsis is an extremely common health issue with a considerable mortality rate in children. Our understanding about the pathogenic mechanisms of sepsis is limited. The aim of this study was to identify the differential expression genes (DEGs) in pediatric sepsis through comprehensive analysis, and to provide specific insights for the clinical sepsis therapies in children. MATERIAL AND METHODS Three pediatric gene expression profiles (GSE25504, GSE26378, GSE26440) were downloaded from the Gene Expression Omnibus (GEO) database. The difference expression genes (DEGs) between pediatric sepsis and normal control group were screened with the GEO2R online tool. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were performed. Cytoscape with CytoHubba were used to identify the hub genes. Finally, NetworkAnalyst was used to construct the targeted microRNAs (miRNAs) of the hub genes. RESULTS Totally, 160 overlapping upward genes and 61 downward genes were identified. In addition, 5 KEGG pathways, including hematopoietic cell lineage, Staphylococcus aureus infection, starch and sucrose metabolism, osteoclast differentiation, and tumor necrosis factor (TNF) signaling pathway, were significantly enriched using a database for labeling, visualization, and synthetic discovery. In combination with the results of the protein-protein interaction (PPI) network and CytoHubba, 9 hub genes including ITGAM, TLR8, IL1ß, MMP9, MPO, FPR2, ELANE, SPI1, and C3AR1 were selected. Combined with DEG-miRNAs visualization, 5 miRNAs, including has-miR-204-5p, has-miR-211-5p, has-miR-590-5p, and has-miR-21-5p, were predicted as possibly the key miRNAs. CONCLUSIONS Our findings will contribute to identification of potential biomarkers and novel strategies for pediatric sepsis treatment.
Platelet gene expression and function in patients with COVID-19.
Manne Bhanu Kanth,Denorme Frederik,Middleton Elizabeth A,Portier Irina,Rowley Jesse W,Stubben Chris,Petrey Aaron C,Tolley Neal D,Guo Li,Cody Mark,Weyrich Andrew S,Yost Christian C,Rondina Matthew T,Campbell Robert A
There is an urgent need to understand the pathogenesis of coronavirus disease 2019 (COVID-19). In particular, thrombotic complications in patients with COVID-19 are common and contribute to organ failure and mortality. Patients with severe COVID-19 present with hemostatic abnormalities that mimic disseminated intravascular coagulopathy associated with sepsis, with the major difference being increased risk of thrombosis rather than bleeding. However, whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection alters platelet function to contribute to the pathophysiology of COVID-19 remains unknown. In this study, we report altered platelet gene expression and functional responses in patients infected with SARS-CoV-2. RNA sequencing demonstrated distinct changes in the gene-expression profile of circulating platelets of COVID-19 patients. Pathway analysis revealed differential gene-expression changes in pathways associated with protein ubiquitination, antigen presentation, and mitochondrial dysfunction. The receptor for SARS-CoV-2 binding, angiotensin-converting enzyme 2 (ACE2), was not detected by messenger RNA (mRNA) or protein in platelets. Surprisingly, mRNA from the SARS-CoV-2 N1 gene was detected in platelets from 2 of 25 COVID-19 patients, suggesting that platelets may take-up SARS-COV-2 mRNA independent of ACE2. Resting platelets from COVID-19 patients had increased P-selectin expression basally and upon activation. Circulating platelet-neutrophil, -monocyte, and -T-cell aggregates were all significantly elevated in COVID-19 patients compared with healthy donors. Furthermore, platelets from COVID-19 patients aggregated faster and showed increased spreading on both fibrinogen and collagen. The increase in platelet activation and aggregation could partially be attributed to increased MAPK pathway activation and thromboxane generation. These findings demonstrate that SARS-CoV-2 infection is associated with platelet hyperreactivity, which may contribute to COVID-19 pathophysiology.
[Characteristic bioanalysis of skeletal muscle cells gene markers in septic patients].
Tian Kuo,Wang Jianjian,Liu Peifang,Zhang Huixue,Lu Xiaoyu,Xu Chen
Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE:To analyze the characteristics of skeletal muscle cells gene markers in septic patients by using bioinformatics. METHODS:The differential gene expression of marker microarrays (GSE13205) in skeletal muscle tissue of patients with sepsis was obtained from gene expression omnibus (GEO) database of National Center for Biotechnology Information (NCBI). Gene differential expression analysis was carried out using online GEO2R provided by NCBI. Data processing, analysis and mapping were carried out using online bioinformatics array research tool (BART) and Cytoscpe software, the software of the national resource for network biology. Functional annotation and pathway analysis of differential expression genes were performed using Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology (GO) provided by the database for annotation, visualization and integrated discovery (DAVID), and protein interaction analysis was further performed in search tool for the retrieve of interacting genes/proteins (STRING-DB). RESULTS:The TOP250 genes were extracted from the GSE13205 dataset. A total of 242 differentially expressed genes were included in the analysis. Among them, 78 up-regulated genes and 164 down-regulated genes were identified. After extensive data analysis, these differentially expressed genes were enriched into different biological processes or subsets of molecular functions, mainly enriched in the positive and negative regulation of growth, mineral absorption and other pathways. The 14 most closely related genes among differentially expressed genes were identified from the protein interaction network. CONCLUSIONS:The differential expression genes in patients with sepsis were mainly concentrated on cell growth and apoptosis and mediating tumor-related immune function regulation.
Identification and evaluation of hub mRNAs and long non-coding RNAs in neutrophils during sepsis.
Huang Jiamin,Sun Ran,Sun Bingwei
Inflammation research : official journal of the European Histamine Research Society ... [et al.]
OBJECTIVE:To reveal the systematic response of neutrophils to sepsis and to study the hub lncRNAs in sepsis. MATERIALS AND METHODS:Neutrophils taken from the femur and tibia of male C57 BL/6 mice were used in this study. And neutrophils were treated for 0 h, 0.5 h, 1 h, and 4 h with or without 1 µg/mL lipopolysaccharide (LPS) for further chip detection. In addition, cecal ligation and perforation were used to simulate sepsis. Here, we used different bioinformatics analyses, including differential expression analysis, weighted gene co-expression network analysis (WGCNA), and gene regulatory network analysis, to analyze the systemic response of neutrophils to sepsis. RESULTS:We identified nine modules and found hub lncRNAs in each module. The blue and pink modules were closely related to the inflammatory state of sepsis. Some hub lncRNAs (NONMMUT005259, KnowTID_00004196, and NR_003507) may have functions related to the inflammatory state in sepsis. CONCLUSIONS:Based on a new biological approach, our research results revealed the systemic-level response of neutrophils to sepsis and identified several hub lncRNAs with potential regulatory effects on this condition.
Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis.
Yang Fang,Wang Yumei
Experimental and therapeutic medicine
Sepsis is a type of systemic inflammatory response syndrome with high morbidity and mortality. Skeletal muscle dysfunction is one of the major complications of sepsis that may also influence the outcome of sepsis. The aim of the present study was to explore and identify potential mechanisms and therapeutic targets of sepsis. Systemic bioinformatics analysis of skeletal muscle gene expression profiles from the Gene Expression Omnibus was performed. Differentially expressed genes (DEGs) in samples from patients with sepsis and control samples were screened out using the limma package. Differential co-expression and coregulation (DCE and DCR, respectively) analysis was performed based on the Differential Co-expression Analysis package to identify differences in gene co-expression and coregulation patterns between the control and sepsis groups. Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways of DEGs were identified using the Database for Annotation, Visualization and Integrated Discovery, and inflammatory, cancer and skeletal muscle development-associated biological processes and pathways were identified. DCE and DCR analysis revealed several potential therapeutic targets for sepsis, including genes and transcription factors. The results of the present study may provide a basis for the development of novel therapeutic targets and treatment methods for sepsis.