Combined Transcriptome and Proteome Leukocyte's Profiling Reveals Up-Regulated Module of Genes/Proteins Related to Low Density Neutrophils and Impaired Transcription and Translation Processes in Clinical Sepsis

Characterizing a low-density neutrophil gene signature in acute and chronic infections and its impact on disease severity

Low-density neutrophils (LDNs) or polymorphonuclear myeloid-derived suppressor cells are involved in the pathogenesis of cancer, autoimmune, and infectious diseases. They are crucial in the host response to invading pathogens, especially during acute illness, and are associated with poor prognosis in many infectious diseases. However, their gene expression profile and contribution to disease outcomes are not well described. We conducted a meta-analysis of gene expression datasets from peripheral blood mononuclear cells (PBMCs), focusing on patients with viral and bacterial infections. We identified a consensus set of 2,798 differentially expressed genes. Among these, 49 genes were commonly found in both the neutrophil degranulation pathway and the granule lumen-specific community. To validate this signature, we evaluated its expression in RNA-seq datasets, finding consistent upregulation of 24 genes in severe infections, 17 of them overlapped with genes overexpressed in CD16int cells. We also investigated the abundance of LDN-related proteins in a PBMC proteomics dataset from a cohort of sepsis and septic shock patients. Out of the 17 genes analyzed, 13 corresponding proteins were identified, 10 of which demonstrated significantly higher abundance in sepsis and septic shock patients compared with healthy controls. In conclusion, our study identified a pattern of 17 upregulated LDN genes, common to PBMC transcriptome and RNA-seq, and upregulated in CD16int, associated with acute infections and severe clinical outcomes, marking the first time these genes have been collectively presented as a potential signature of LDNs in relation to disease severity. Further research with prospective cohorts is needed to validate this LDN signature and explore its clinical implications.

Bacteria and host: what does this mean for sepsis bottleneck?

BACKGROUND

Sepsis is a life-threatening inflammatory condition in which the invading pathogen avoids the host's defense mechanisms and continuously stimulates and damages host cells. Consequently, many immune responses initially triggered for protection become harmful because of the failure to restore homeostasis, resulting in ongoing hyperinflammation and immunosuppression.

METHODS

A literature review was conducted to address bacterial sepsis, describe advances in understanding complex immunological reactions, critically assess diagnostic approaches, and emphasize the importance of studying bacterial bottlenecks in the detection and treatment of sepsis.

RESULTS

Diagnosing sepsis via a single laboratory test is not feasible; therefore, multiple key biomarkers are typically monitored, with a focus on trends rather than absolute values. The immediate interpretation of sepsis-associated clinical signs and symptoms, along with the use of specific and sensitive laboratory tests, is crucial for the survival of patients in the early stages. However, long-term mortality associated with sepsis is now recognized, and alongside the progression of this condition, there is an in vivo selection of adapted pathogens.

CONCLUSION

Bacterial sepsis remains a significant cause of mortality across all ages and societies. While substantial progress has been made in understanding the immunological mechanisms underlying the inflammatory response, there is growing recognition that the ongoing host-pathogen interactions, including the emergence of adapted virulent strains, shape both the acute and long-term outcomes in sepsis. This underscores the urgent need for novel high-throughput diagnostic methods and a shift toward more pre-emptive, rather than reactive, treatment strategies in sepsis care.

Proteomic profiling of peripheral blood mononuclear cells reveals immune dysregulation and metabolic alterations in kidney transplant recipients with COVID-19

The COVID-19 pandemic has significantly impacted global health, especially in vulnerable populations like kidney transplant recipients (KTRs). Recently, mass spectrometry-based proteomics has emerged as a powerful tool to shed light on a broad spectrum of dysregulated biological processes in KTRs with COVID-19. In this study, we prospectively collected blood samples from 17 COVID-19-positive KTRs and 10 non-infected KTRs between May and September 2020. Using tandem mass tag-based quantitative proteomics, we analyzed peripheral blood mononuclear cells (PBMCs), plasma protein biomarkers, and lymphocyte counts, followed by bioinformatics analysis. Our results revealed significant proteomic alterations in COVID-19-infected KTRs, particularly in pathways related to glycolysis, glucose metabolism, and neutrophil degranulation. Additionally, we observed an altered immune response characterized by elevated cytokines and decreased lymphocyte counts. Notably, KTRs with AKI exhibited worse clinical outcomes, including higher rates of ICU admission and mechanical ventilation. Comparative analysis of PBMC proteomic profiles between AKI and non-AKI patients identified distinct immune-related pathways, with AKI patients showing marked changes in innate immune responses, particularly neutrophil degranulation. Furthermore, we observed a negative correlation between T cell counts and neutrophil degranulation, suggesting a role for immune dysregulation in COVID-19. Our findings provide critical insights into the immune and metabolic responses in COVID-19-infected KTRs, especially those with AKI, highlighting the need for focused research and therapeutic strategies targeting immune dysregulation in this high-risk population.

Neutrophil-based single-cell sequencing combined with transcriptome sequencing to explore a prognostic model of sepsis

Sepsis is a life-threatening condition influenced by various factors. Although gene expression profiling has offered new insights, accurately assessing patient risk and prognosis remains challenging. We utilized single-cell and gene expression data of sepsis patients from public databases. The Seurat package was applied for preprocessing and clustering single-cell data, focusing on neutrophils. Lasso regression identified key genes, and a prognostic model was built. Model performance was evaluated using Receiver Operating Characteristic (ROC) curves, and further analyses, including immune cell infiltration, Gene Set Enrichment Analysis (GSEA), and clinical correlation, were conducted. Several neutrophil subtypes were identified with distinct gene expression profiles. A prognostic model based on these profiles demonstrated strong predictive accuracy. Risk scores were significantly correlated with clinical features, immune responses, and key signalling pathways. This study provides a comprehensive analysis of sepsis at the molecular level. The prognostic model shows promise in predicting patient outcomes, offering potential new strategies for diagnosis and treatment.

High-throughput mass spectrometry maps the sepsis plasma proteome and differences in patient response

Sepsis, the dysregulated host response to infection causing life-threatening organ dysfunction, is a global health challenge requiring better understanding of pathophysiology and new therapeutic approaches. Here, we applied high-throughput tandem mass spectrometry to delineate the plasma proteome for sepsis and comparator groups (noninfected critical illness, postoperative inflammation, and healthy volunteers) involving 2612 samples (from 1611 patients) and 4553 liquid chromatography-mass spectrometry analyses acquired through a single batch of continuous measurements, with a throughput of 100 samples per day. We show how this scale of data can delineate proteins, pathways, and coexpression modules in sepsis and be integrated with paired leukocyte transcriptomic data (837 samples from n = 649 patients). We mapped the plasma proteomic landscape of the host response in sepsis, including changes over time, and identified features relating to etiology, clinical phenotypes (including organ failures), and severity. This work reveals subphenotypes informative for sepsis response state, disease processes, and outcome; identifies potential biomarkers; and advances opportunities for a precision medicine approach to sepsis.

Assessing the potential relevance of CEACAM6 as a blood transcriptional biomarker

Background

Changes in blood transcript abundance levels have been associated with pathogenesis in a wide range of diseases. While next generation sequencing technology can measure transcript abundance on a genome-wide scale, downstream clinical applications often require small sets of genes to be selected for inclusion in targeted panels. Here we set out to gather information from the literature and transcriptome datasets that would help researchers determine whether to include the gene CEACAM6 in such panels.

Methods

We employed a workflow to systematically retrieve, structure, and aggregate information derived from both the literature and public transcriptome datasets. It consisted of profiling the CEACAM6 literature to identify major diseases associated with this candidate gene and establish its relevance as a biomarker. Accessing blood transcriptome datasets identified additional instances where CEACAM6 transcript levels differ in cases vs controls. Finally, the information retrieved throughout this process was captured in a structured format and aggregated in interactive circle packing plots.

Results

Although it is not routinely used clinically, the relevance of CEACAM6 as a biomarker has already been well established in the cancer field, where it has invariably been found to be associated with poor prognosis. Focusing on the blood transcriptome literature, we found studies reporting elevated levels of CEACAM6 abundance across a wide range of pathologies, especially diseases where inflammation plays a dominant role, such as asthma, psoriasis, or Parkinson's disease. The screening of public blood transcriptome datasets completed this picture, showing higher abundance levels in patients with infectious diseases caused by viral and bacterial pathogens.

Conclusions

Targeted assays measuring CEACAM6 transcript abundance in blood may be of potential utility for the management of patients with diseases presenting with systemic inflammation and for the management of patients with cancer, where the assay could potentially be run both on blood and tumor tissues.

Human peripheral blood mononuclear cells as a valuable source of disease-related biomarkers: Evidence from comparative proteomics studies

PURPOSE

The discovery of specific and sensitive disease-associated biomarkers for early diagnostic purposes of many diseases is still highly challenging due to various complex molecular mechanisms triggered, high variability of disease-related interactions, and an overlap of manifestations among diseases. Human peripheral blood mononuclear cells (PBMCs) contain protein signatures corresponding to essential immunological interplay. Certain diseases stimulate PBMCs and contribute towards modulation of their proteome which can be effectively identified and evaluated via the comparative proteomics approach.

EXPERIMENTAL DESIGN

In this review, we made a detailed survey of the PBMCS-derived protein biomarker candidates for a variety of diseases, published in the last 15 years. Articles were preselected to include only comparative proteomics studies.

RESULTS

PBMC-derived biomarkers were investigated for cancer, glomerular, neurodegenerative/neurodevelopmental, psychiatric, chronic inflammatory, autoimmune, endocrinal, infectious, and other diseases. A detailed review of these studies encompassed the proteomics platforms, proposed candidate biomarkers, their immune cell type specificity, and potential clinical application.

CONCLUSIONS

Overall, PBMCs have shown a solid potential in giving early diagnostic and prognostic biomarkers for many diseases. The future of PBMC biomarker research should reveal its full potential through well-designed comparative studies and extensive testing of the most promising protein biomarkers identified so far.

Activation of estrogen receptor induces differential proteomic responses mainly involving migration, invasion, and tumor development pathways in human testicular embryonal carcinoma NT2/D1 cells

The aims of the present study were to investigate the global changes on proteome of human testicular embryonal carcinoma NT2/D1 cells treated with 17β-estradiol (E2), and the effects of this hormone on migration, invasion, and colony formation of these cells. A quantitative proteomic analysis identified the presence of 1230 proteins in both E2-treated and control cells. The analysis revealed 75 differentially abundant proteins (DAPs), out of which 43 proteins displayed a higher abundance and, 30 proteins showed a lower abundance in E2-treated NT2/D1 cancer cells. Functional analysis using IPA highlighted some activation processes such as migration, invasion, metastasis, and tumor growth. Interestingly, the treatment with E2 and ERβ-selective agonist DPN increased the migration of NT2/D1 cells. On the other hand, ERα-selective agonist PPT did not modify cell migration, indicating that ERβ is the upstream receptor involved in this process. The activation of ERβ increased the invasion and anchorage‑independent growth of NT2/D1 cells more intensely than ERα. ERα and ERβ may play overlapping roles on invasion and colony formation of these cells. Further studies are required to clarify the mechanism underlying these effects. The molecular mechanisms revealed by proteomic and functional studies might also guide the development of potential targets for a better understanding of the biology of these cells and novel treatments for non-seminoma in the future.

A gene network database for the identification of key genes for diagnosis, prognosis, and treatment in sepsis

Sepsis and sepsis-related diseases cause a high rate of mortality worldwide. The molecular and cellular mechanisms of sepsis are still unclear. We aim to identify key genes in sepsis and reveal potential disease mechanisms. Six sepsis-related blood transcriptome datasets were collected and analyzed by weighted gene co-expression network analysis (WGCNA). Functional annotation was performed in the gProfiler tool. DSigDB was used for drug signature enrichment analysis. The proportion of immune cells was estimated by the CIBERSORT tool. The relationships between modules, immune cells, and survival were identified by correlation analysis and survival analysis. A total of 37 stable co-expressed gene modules were identified. These modules were associated with the critical biology process in sepsis. Four modules can independently separate patients with long and short survival. Three modules can recurrently separate sepsis and normal patients with high accuracy. Some modules can separate bacterial pneumonia, influenza pneumonia, mixed bacterial and influenza A pneumonia, and non-infective systemic inflammatory response syndrome (SIRS). Drug signature analysis identified drugs associated with sepsis, such as testosterone, phytoestrogens, ibuprofen, urea, dichlorvos, potassium persulfate, and vitamin B12. Finally, a gene co-expression network database was constructed ( https://liqs.shinyapps.io/sepsis/ ). The recurrent modules in sepsis may facilitate disease diagnosis, prognosis, and treatment.

Understanding COVID-19 progression with longitudinal peripheral blood mononuclear cell proteomics: Changes in the cellular proteome over time

The clinical presentation of COVID-19 is highly variable, and understanding the underlying biological processes is crucial. This study utilized a proteomic analysis to investigate dysregulated processes in the peripheral blood mononuclear cells of patients with COVID-19 compared to healthy volunteers. Samples were collected at different stages of the disease, including hospital admission, after 7 days of hospitalization, and 30 days after discharge. Metabolic pathway alterations and increased abundance of neutrophil-related proteins were observed in patients. Patients progressing to critical illness had significantly low-abundance proteins in the pentose phosphate and glycolysis pathways compared with those presenting clinical recovery. Important biological processes, such as fatty acid concentration and glucose metabolism disorder, remained altered even after 30 days of hospital discharge. Temporal proteomic changes revealed distinct pathways in critically ill and non-critically ill patients. Our study emphasizes the significance of longitudinal cellular proteomic studies in identifying disease progression-related pathways and persistent protein changes post-hospitalization.

Integrated transcriptomic and proteomic analyses of plerocercoid and adult Spirometra mansoni reveal potential important pathways in the development of the medical tapeworm

BACKGROUND

Spirometra mansoni can parasitize animals and humans through food and water, causing parasitic zoonosis. Knowledge of the developmental process of S. mansoni is crucial for effective treatment; thus, it is important to characterize differential and specific proteins and pathways associated with parasite development.

METHODS

In this study, we performed a comparative proteomic analysis of the plerocercoid and adult stages using a tandem mass tag-based quantitative proteomic approach. Additionally, integrated transcriptomic and proteomic analyses were conducted to obtain the full protein expression profiles of different life cycle stages of the tapeworm.

RESULTS

Approximately 1166 differentially expressed proteins (DEPs) were identified in adults versus plerocercoids, of which 641 DEPs were upregulated and 525 were downregulated. Gene Ontology (GO), Clusters of Orthologous groups (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that most DEPs related to genetic information processing and metabolism of energy in adults seem to be more activated. In the plerocercoid stage, compared to metabolism, genetic information processing appears more dynamic. Protein-protein interaction (PPI) revealed six key proteins (phosphomannomutase, glutathione transferase, malate dehydrogenase, cytoplasmic, 40S ribosomal protein S15, ribosomal protein L15 and 60S acidic ribosomal protein P2) that may play active roles in the growth and development of S. mansoni. Finally, the combination of transcriptomic and proteomic data suggested that three pathways (ubiquitin-mediated proteolysis, phagosome and spliceosome) and five proteins closely related to these pathways might have a significant influence in S. mansoni.

CONCLUSIONS

These findings contribute to increasing the knowledge on the protein expression profiles of S. mansoni and provide new insights into functional studies on the molecular mechanisms of the neglected medical tapeworm.

LEUKOCYTE PHENOTYPING IN SEPSIS USING OMICS, FUNCTIONAL ANALYSIS, AND IN SILICO MODELING

ABSTRACT

Sepsis is a major health issue and a leading cause of death in hospitals globally. The treatment of sepsis is largely supportive, and there are no therapeutics available that target the underlying pathophysiology of the disease. The development of therapeutics for the treatment of sepsis is hindered by the heterogeneous nature of the disease. The presence of multiple, distinct immune phenotypes ranging from hyperimmune to immunosuppressed can significantly impact the host response to infection. Recently, omics, biomarkers, cell surface protein expression, and immune cell profiles have been used to classify immune status of sepsis patients. However, there has been limited studies of immune cell function during sepsis and even fewer correlating omics and biomarker alterations to functional consequences. In this review, we will discuss how the heterogeneity of sepsis and associated immune cell phenotypes result from changes in the omic makeup of cells and its correlation with leukocyte dysfunction. We will also discuss how emerging techniques such as in silico modeling and machine learning can help in phenotyping sepsis patients leading to precision medicine.

Bone Marrow Mesenchymal Stem Cells (BMSC) from Exosome with High miR-184 Level Ameliorates Sepsis

This study assesses whether BMSC from exosome with high miR-184 level ameliorates sepsis. BMSC with high miR-184 expression established. RAW264.7 cells were cultivated in vitro and divided into control set, model set, BMSC set and BMSC with high miR-184 level set. The model was established through infection of RAW264.7 cells with LPS followed by analysis of cell proliferation and apoptosis, activity of ROS and SOD, secretion of IL-1β, IL-6 and TNF-α as well as the expression of NF-κB and TRAIL. BMSC set showed significantly upregulated miR-184 expression, increased cell proliferation and SOD activity, reduced ROS activity, decreased secretion of IL-1β, IL-6 and TNF-α as well as the expression of NF-κB and TRAIL. The above changes were more significant in the set of BMSC with overexpression of miR-184. In conclusion, cell proliferation, apoptosis and inflammation in RAW264.7 cells induced with LPS is regulated by BMSC from exosome with high expression of miR-184, which is possibly through restraining the NF-κB and TRAIL and oxidative stress.

Glucose metabolism is upregulated in the mononuclear cell proteome during sepsis and supports endotoxin-tolerant cell function

Metabolic adaptations shape immune cell function. In the acute response, a metabolic switch towards glycolysis is necessary for mounting a proinflammatory response. During the clinical course of sepsis, both suppression and activation of immune responses take place simultaneously. Leukocytes from septic patients present inhibition of cytokine production while other functions such as phagocytosis and production of reactive oxygen species (ROS) are preserved, similarly to the in vitro endotoxin tolerance model, where a first stimulation with lipopolysaccharide (LPS) affects the response to a second stimulus. Here, we sought to investigate how cellular metabolism is related to the modulation of immune responses in sepsis and endotoxin tolerance. Proteomic analysis in peripheral blood mononuclear cells (PBMCs) from septic patients obtained at intensive care unit admission showed an upregulation of proteins related to glycolysis, the pentose phosphate pathway (PPP), production of ROS and nitric oxide, and downregulation of proteins in the tricarboxylic acid cycle and oxidative phosphorylation compared to healthy volunteers. Using the endotoxin-tolerance model in PBMCs from healthy subjects, we observed increased lactate production in control cells upon LPS stimulation, while endotoxin-tolerant cells presented inhibited tumor necrosis factor-α and lactate production along with preserved phagocytic capacity. Inhibition of glycolysis and PPP led to impairment of phagocytosis and cytokine production both in control and in endotoxin-tolerant cells. These data indicate that glucose metabolism supports leukocyte functions even in a condition of endotoxin tolerance.

Single-cell transcriptome profiling reveals heterogeneous neutrophils with prognostic values in sepsis

Neutrophils constitute the largest proportion of nucleated peripheral blood cells, and neutrophils have substantial heterogeneity. We profiled nearly 300,000 human peripheral blood cells in this study using single-cell RNA sequencing. A large proportion (>50%) of these cells were annotated as neutrophils. Neutrophils were further clustered into four subtypes, including Neu1, Neu2, Neu3, and Neu4. Neu1 is characterized by high expression of MMP9, HP, and RGL4. Neu1 was associated with septic shock and significantly correlated with the sequential organ failure assessment (SOFA) score. A gene expression module in Neu1 named Neu1_C (characterized by expression of NFKBIA, CXCL8, G0S2, and FTH1) was highly predictive of septic shock with an area under the curve of 0.81. The results were extensively validated in external bulk datasets by using single-cell deconvolution methods. In summary, our study establishes a general framework for studying neutrophil-related mechanisms, prognostic biomarkers, and potential therapeutic targets for septic shock.

Key Signature Genes of Early Terminal Granulocytic Differentiation Distinguish Sepsis From Systemic Inflammatory Response Syndrome on Intensive Care Unit Admission

Infection can induce granulopoiesis. This process potentially contributes to blood gene classifiers of sepsis in systemic inflammatory response syndrome (SIRS) patients. This study aimed to identify signature genes of blood granulocytes from patients with sepsis and SIRS on intensive care unit (ICU) admission. CD15+ cells encompassing all stages of terminal granulocytic differentiation were analyzed. CD15 transcriptomes from patients with sepsis and SIRS on ICU admission and presurgical controls (discovery cohort) were subjected to differential gene expression and pathway enrichment analyses. Differential gene expression was validated by bead array in independent sepsis and SIRS patients (validation cohort). Blood counts of granulocyte precursors were determined by flow cytometry in an extension of the validation cohort. Despite similar transcriptional CD15 responses in sepsis and SIRS, enrichment of canonical pathways known to decline at the metamyelocyte stage (mitochondrial, lysosome, cell cycle, and proteasome) was associated with sepsis but not SIRS. Twelve of 30 validated genes, from 100 selected for changes in response to sepsis rather than SIRS, were endo-lysosomal. Revisiting the discovery transcriptomes revealed an elevated expression of promyelocyte-restricted azurophilic granule genes in sepsis and myelocyte-restricted specific granule genes in sepsis followed by SIRS. Blood counts of promyelocytes and myelocytes were higher in sepsis than in SIRS. Sepsis-induced granulopoiesis and signature genes of early terminal granulocytic differentiation thus provide a rationale for classifiers of sepsis in patients with SIRS on ICU admission. Yet, the distinction of this process from noninfectious tissue injury-induced granulopoiesis remains to be investigated.

Immune Cell Plasticity in Inflammation: Insights into Description and Regulation of Immune Cell Phenotypes

Inflammation is a life-saving immune reaction occurring in response to invading pathogens. Nonetheless, inflammation can also occur in an uncontrolled, unrestricted manner, leading to chronic disease and organ damage. Mechanisms triggering an inflammatory response, hindering such a response, or leading to its resolution are well-studied but so far insufficiently elucidated with regard to precise therapeutic interventions. Notably, as an immune reaction evolves, requirements and environments for immune cells change, and thus cellular phenotypes adapt and shift, leading to the appearance of distinct cellular subpopulations with new functional features. In this article, we aim to highlight properties of, and overarching regulatory factors involved in, the occurrence of immune cell phenotypes with a special focus on neutrophils, macrophages and platelets. Additionally, we point out implications for both diagnostics and therapeutics in inflammation research.

Human peripheral blood mononuclear cells: A review of recent proteomic applications

Human peripheral blood mononuclear cells (PBMCs) represent a sentinel blood sample which reacts to different pathophysiological stimuli in the form of immunological responses/immunophenotypic changes. The study of molecular content of PBMCs can provide better understanding of immune processes giving the possibility of monitoring the health conditions of the host organism. Proteomic analysis of PBMCs can achieve mentioned goal as important immune-related biomarkers are easily accessible for analysis. PBMCs have been gaining attention in different research areas including preclinical or clinical investigations. In this review, recent applications of proteomic analysis of PBMCs are described and discussed. Approaches are divided based on different proteomic workflows such as in-gel, in-solution and on-filter modes. The effect of various diseases such as autoimmune, cancer, neurodegenerative, viral, metabolic, and various immune stimulations such as radiation, vaccine, corticosteroids over PBMCs proteome, are described with emphasis on promising protein biomarker candidates. This article is protected by copyright. All rights reserved.