Single-cell RNA sequencing reveals the sustained immune cell dysfunction in the pathogenesis of sepsis secondary to bacterial pneumonia

Detection of >400 Cluster of Differentiation Biomarkers and Pathway Proteins in Single Immune Cells by Cyclic Multiplex In Situ Tagging for Single-Cell Proteomic Studies

The identification and characterization of immune cell subpopulations are critical to reveal cell development throughout life and immune responses to environmental factors. Next-generation sequencing technologies have dramatically advanced single-cell genomics and transcriptomics for immune cell classification. However, gene expression is often not correlated with protein expression, and immunotyping is mostly accepted in protein format. Current single-cell proteomic technologies are either limited in multiplex capacity or not sensitive enough to detect the critical functional proteins. Herein, we present a single-cell cyclic multiplex in situ tagging (CycMIST) technology to simultaneously measure >400 proteins, a scale of >10 times than similar technologies. Such an ultrahigh multiplexity is achieved by reiterative staining of the single cells coupled with a MIST array for detection. This technology has been thoroughly validated through comparison with flow cytometry and fluorescence immunostaining techniques. Both peripheral blood mononuclear cells (PBMCs) and T cells are analyzed by the CycMIST technology, and almost the entire spectrum of cluster of differentiation (CD) surface markers has been measured. The landscape of fluctuation of CD protein expression in single cells has been uncovered by our technology. Further study found T cell activation signatures and protein-protein networks. This study represents the highest multiplexity of single immune cell marker measurement targeting functional proteins. With additional information from intracellular proteins of the same single cells, our technology can potentially facilitate mechanistic studies of immune responses under various disease conditions.

Single-Cell Transcriptomic Analysis Reveals Dynamic Cellular Processes in Corneal Epithelium During Wound Healing in Cynomolgus Monkeys

Purpose

Corneal wounding healing is critical for maintaining clear vision, however, a complete understanding of its dynamic regulatory mechanisms remains elusive. Here, we used single-cell RNA sequencing (scRNA-seq) to analyze the cellular activities and transcriptional changes of corneal limbal epithelial cells at different stages after wound healing in cynomolgus monkeys, which exhibit a closer transcriptomic similarity to humans.

Methods

Corneal limbal tissues were collected during uninjured, 1-day and 3-day healing stages, dissociated into single cells, and subjected to scRNA-seq using the 10× Genomics platform. Cell types were clustered by graph-based visualization methods and unbiased computational analysis. Additionally, cell migration assays and immunofluorescent staining were performed on cultured human corneal epithelial cells.

Results

We characterized nine cell clusters by scRNA-seq analysis of the cynomolgus monkey corneal epithelium. By comparing heterogeneous transcriptional changes in major cell types during corneal healing, we highlighted the importance of limbal epithelial cells (LEPCs) and basal epithelial cells (BEPCs) in extracellular matrix (ECM) formation and wound healing, as well as suprabasal epithelial cells (SEPCs) in epithelial differentiation during the healing processes. We further identified five different sub-clusters in LEPC, including the transit amplifying cell (TAC) sub-cluster that promotes early healing through the activation of thrombospondin-1 (THBS1) expression.

Conclusions

Our study represents the first comprehensive exploration of the detailed transcriptome profile of individual corneal cells during the wound healing process in nonhuman primates. We demonstrate the intricate mechanisms involved in corneal healing and provide a promising avenue for potential therapies in corneal wound healing.

Exploring the role of pyroptosis and immune infiltration in sepsis based on bioinformatic analysis

PURPOSE

Sepsis is a disease that is typically treated in intensive care units with high mortality and morbidity. Pyroptosis is a newly identified type of programmed cell death and is characterized by inflammatory cytokine secretion. However, the role of pyroptosis in sepsis remains unclear.

METHODS

GSE28750 and GSE134347 datasets were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed pyroptosis genes (DEPGs) were identified between sepsis and healthy controls. Machine learning was used to further narrow the gene range. Receiver operating curves (ROC) were generated to estimate the diagnostic efficacy. Immune infiltration levels were estimated via single-sample gene set enrichment analysis (ssGSEA). A network database was used to predict the upstream transcription factors and miRNAs of DEPGs. Finally, the expression of the genes was validated by qRT-PCR between sepsis patients and healthy controls.

RESULTS

We found that the pyroptosis pathway was enriched and activated in sepsis. 8 DEPGs were identified. A heatmap showed that the genes, NLRC4, NAIP, IL-18, AIM2 and ELANE, were abundant in the sepsis samples, and the genes, NLRP1, CHMP7 and TP53, were abundant in the healthy control samples. The ssGSEA results showed that the abundances of activated dendritic cells, MDSC, macrophage, plasmacytoid dendritic cells, regulatory T-cells, and Th17-cells were significantly higher, while the activated B-cell, activated CD8 T-cell, CD56 dim tural killer cell, immature B-cell, monocyte, and T follicular helper cell abundances were lower in sepsis samples compared to healthy controls. The qRT-PCR results showed that the expression levels of NAIP, IL-18, TP53, CHMP7, NLRC4, ELANE and NLRP1 were consistant with the bioinformatic analyses, while the expression level of AIM2 has no significant difference.

CONCLUSION

Our study identified seven potential pyroptosis-related genes, NAIP, IL-18, TP53, CHMP7, NLRC4, ELANE and NLRP1. This study revealed that pyroptosis may promote sepsis development by activating the immune response.

Single-cell transcriptomics of blood identified IFIT1+ neutrophil subcluster expansion in NTM-PD patients

OBJECTIVE

Non-tuberculous mycobacterial pulmonary disease (NTM-PD) is caused by an imbalance between pathogens and impaired host immune responses. Mycobacterium avium complex (MAC) and Mycobacterium abscessus (MAB) are the two major pathogens that cause NTM-PD. In this study, we sought to dissect the transcriptomes of peripheral blood immune cells at the single-cell resolution in NTM-PD patients and explore potential clinical markers for NTM-PD diagnosis and treatment.

METHODS

Peripheral blood samples were collected from six NTM-PD patients, including three MAB-PD patients, three MAC-PD patients, and two healthy controls. We employed single-cell RNA sequencing (scRNA-seq) to define the transcriptomic landscape at a single-cell resolution. A comprehensive scRNA-seq analysis was performed, and flow cytometry was conducted to validate the results of scRNA-seq.

RESULTS

A total of 27,898 cells were analyzed. Nine T-cells, six mononuclear phagocytes (MPs), and four neutrophil subclusters were defined. During NTM infection, naïve T-cells were reduced, and effector T-cells increased. High cytotoxic activities were shown in T-cells of NTM-PD patients. The proportion of inflammatory and activated MPs subclusters was enriched in NTM-PD patients. Among neutrophil subclusters, an IFIT1+ neutrophil subcluster was expanded in NTM-PD compared to healthy controls. This suggests that IFIT1+ neutrophil subcluster might play an important role in host defense against NTM. Functional enrichment analysis of this subcluster suggested that it is related to interferon response. Cell-cell interaction analysis revealed enhanced CXCL8-CXCR1/2 interactions between the IFIT1+ neutrophil subcluster and NK cells, NKT cells, classical mononuclear phagocytes subcluster 1 (classical Mo1), classical mononuclear phagocytes subcluster 2 (classical Mo2) in NTM-PD patients compared to healthy controls.

CONCLUSIONS

Our data revealed disease-specific immune cell subclusters and provided potential new targets of NTM-PD. Specific expansion of IFIT1+ neutrophil subclusters and the CXCL8-CXCR1/2 axis may be involved in the pathogenesis of NTM-PD. These insights may have implications for the diagnosis and treatment of NTM-PD.

Plac8-ERK pathway modulation of monocyte function in sepsis

Sepsis, a life-threatening condition caused by infection, is characterized by the dysregulation of immune responses and activation of monocytes. Plac8, a protein, has been implicated in various inflammatory conditions. This study aimed to investigate the effect of Plac8 upregulation on monocyte proliferation and activation in sepsis patients. Peripheral blood samples were collected from healthy individuals and sepsis patients. Monocytes were stimulated with lipopolysaccharide (LPS) to create an in vitro sepsis model, while a murine sepsis model was established using cecal ligation and puncture (CLP). The levels of monocyte markers, proliferation index (PI), and pro-inflammatory cytokines were assessed using flow cytometry and qPCR, respectively. Plac8 and phosphorylated ERK protein levels were determined by western blot, and TNF-α, IL-6, and IL-10 levels were quantified using ELISA. The CCK-8 assay was used to evaluate PBMC proliferation and activation. The results showed that Plac8 was highly expressed in sepsis models, promoting the survival, proliferation, and activation of monocytes. Plac8 upregulation activated the ERK pathway, leading to increased phosphorylation of ERK protein and elevated levels of CD14, CD16, TNF-α, IL-6, Plac8, and IL-10. In sepsis mice, Plac8 overexpression similarly activated the ERK pathway and promoted the survival, proliferation, and activation of monocytes. In conclusion, the upregulation of Plac8 enhances the activation of the ERK pathway and promotes monocyte proliferation and activation in sepsis patients.

A multimodal integration pipeline for accurate diagnosis, pathogen identification, and prognosis prediction of pulmonary infections

Pulmonary infections pose formidable challenges in clinical settings with high mortality rates across all age groups worldwide. Accurate diagnosis and early intervention are crucial to improve patient outcomes. Artificial intelligence (AI) has the capability to mine imaging features specific to different pathogens and fuse multimodal features to reach a synergistic diagnosis, enabling more precise investigation and individualized clinical management. In this study, we successfully developed a multimodal integration (MMI) pipeline to differentiate among bacterial, fungal, and viral pneumonia and pulmonary tuberculosis based on a real-world dataset of 24,107 patients. The area under the curve (AUC) of the MMI system comprising clinical text and computed tomography (CT) image scans yielded 0.910 (95% confidence interval [CI]: 0.904-0.916) and 0.887 (95% CI: 0.867-0.909) in the internal and external testing datasets respectively, which were comparable to those of experienced physicians. Furthermore, the MMI system was utilized to rapidly differentiate between viral subtypes with a mean AUC of 0.822 (95% CI: 0.805-0.837) and bacterial subtypes with a mean AUC of 0.803 (95% CI: 0.775-0.830). Here, the MMI system harbors the potential to guide tailored medication recommendations, thus mitigating the risk of antibiotic misuse. Additionally, the integration of multimodal factors in the AI-driven system also provided an evident advantage in predicting risks of developing critical illness, contributing to more informed clinical decision-making. To revolutionize medical care, embracing multimodal AI tools in pulmonary infections will pave the way to further facilitate early intervention and precise management in the foreseeable future.

Single-cell landscape of immunological responses in elderly patients with sepsis

Sepsis is a dysregulated host response to severe infections, and immune dysfunction plays a crucial role in its pathogenesis. Elderly patients, a special population influenced by immunosenescence, are more susceptible to sepsis and have a worse prognosis. However, the immunopathogenic mechanisms underlying sepsis in elderly patients remain unclear. Here, we performed single-cell RNA sequencing of peripheral blood samples from young and old subjects and patients with sepsis. By exploring the transcriptional profiles of immune cells, we analyzed immune cell compositions, phenotype shifts, expression heterogeneities, and intercellular communication. In elderly patients with sepsis, innate immune cells (e.g., monocytes and DCs) exhibit decreased antigen presentation, presenting an overactive inflammatory and senescent phenotype. However, the immunophenotype of T cells shifted to characterize effector, memory, and exhaustion. Moreover, we identified strong interferon-γ responses of T cells in both aging and sepsis groups and a deranged inflammaging status in elderly sepsis patients. Tregs in elderly patients with sepsis showed increased abundance and enhanced immunosuppressive effects. In addition, metabolism-associated pathways were upregulated in T cells in elderly patients with sepsis, and the lysine metabolism pathway was enriched in Tregs. Cell-cell interaction analysis showed that the expression profile of ligand-receptor pairs was probably associated with aggravated immune dysfunction in elderly patients with sepsis. A novel HLA-KIR interaction was observed between Tregs and CD8 + T cells. These findings illustrate the immunological hallmarks of sepsis in elderly patients, and highlight that immunosuppressive and metabolic regulatory pathways may undergo important alterations in elderly patients with sepsis.

Identification and experimental validation of cuproptosis regulatory program in a sepsis immune microenvironment through a combination of single-cell and bulk RNA sequencing

Background

In spite of its high mortality rate and poor prognosis, the pathogenesis of sepsis is still incompletely understood. This study established a cuproptosis-based risk model to diagnose and predict the risk of sepsis. In addition, the cuproptosis-related genes were identified for targeted therapy.

Methods

Single-cell sequencing analyses were used to characterize the cuproptosis activity score (CuAS) and intercellular communications in sepsis. Differential cuproptosis-related genes (CRGs) were identified in conjunction with single-cell and bulk RNA sequencing. LASSO and Cox regression analyses were employed to develop a risk model. Three external cohorts were conducted to assess the model's accuracy. Differences in immune infiltration, immune cell subtypes, pathway enrichment, and the expression of immunomodulators were further evaluated in distinct groups. Finally, various in-vitro experiments, such as flow cytometry, Western blot, and ELISA, were used to explore the role of LST1 in sepsis.

Results

ScRNA-seq analysis demonstrated that CuAS was highly enriched in monocytes and was closely related to the poor prognosis of sepsis patients. Patients with higher CuAS exhibited prominent strength and numbers of cell-cell interactions. A total of five CRGs were identified based on the LASSO and Cox regression analyses, and a CRG-based risk model was established. The lower riskScore cohort exhibited enhanced immune cell infiltration, elevated immune scores, and increased expression of immune modulators, indicating the activation of an antibacterial response. Ultimately, in-vitro experiments demonstrated that LST1, a key gene in the risk model, was enhanced in the macrophage in response to LPS, which was closely related to the decrease of macrophage survival rate, the enhancement of apoptosis and oxidative stress injury, and the imbalance of the M1/M2 phenotype.

Conclusions

This study constructed a cuproptosis-related risk model to accurately predict the prognosis of sepsis. We further characterized the cuproptosis-related gene LST1 to provide a theoretical framework for sepsis therapy.

Dynamic immune status analysis of peripheral blood mononuclear cells in patients with Klebsiella pneumoniae bloodstream infection sepsis using single-cell RNA sequencing

Background

Klebsiella pneumoniae is a common Gram-negative bacterium. Blood infection caused by K. pneumoniae is one of the most common causes of human sepsis, which seriously threatens the life of patients. The immune status of peripheral blood mononuclear cells (PBMCs) based on single-cell RNA sequencing (scRNA-seq) in acute stage and recovery stage of sepsis caused by K. pneumoniae bloodstream infection has not been studied.

Methods

A total of 13 subjects were included in this study, 3 healthy controls, 7 patients with K. pneumoniae bloodstream infection in the acute stage (4 patients died), and 3 patients in the recovery stage. Peripheral blood of all patients was collected and PBMCs were isolated for scRNA-seq analysis. We studied the changes of PBMCs components, signaling pathways, differential genes, and cytokines in acute and recovery stages.

Results

During K. pneumoniae acute infection we observed a decrease in the proportion of T cells, most probably due to apoptosis and the function of T cell subtypes was disorder. The proportion of monocytes increased in acute stage. Although genes related to their phagocytosis function were upregulated, their antigen presentation capacity-associated genes were downregulated. The expression of IL-1β, IL-18, IFNGR1 and IFNGR2 genes was also increased in monocytes. The proportion of DCs was depleted during the acute stage and did not recover during sepsis recovery. DCs antigen presentation was weakened during the acute stage but recovered fast during the recovery stage. pDCs response to MCP-1 chemokine was weakened, they recovered it quickly during the recovery stage. B cells showed apoptosis both in the acute stage and recovery stage. Their response to complement was weakened, but their antigen presentation function was enhanced. The proportion of NK cells stable during all disease's stages, and the expression of IFN-γ gene was upregulated.

Conclusion

The proportion of PBMCs and their immune functions undergo variations throughout the course of the disease, spanning from the acute stage to recovery. These findings provide new insights into the mechanism of PBMCs immune function during K. pneumoniae bloodstream infection sepsis and recovery and sets the basis for further understanding and treatment.

OTUD5 promotes the inflammatory immune response by enhancing MyD88 oligomerization and Myddosome formation

Myddosome is an oligomeric complex required for the transmission of inflammatory signals from TLR/IL1Rs and consists of MyD88 and IRAK family kinases. However, the molecular basis for the self-assemble of Myddosome proteins and regulation of intracellular signaling remains poorly understood. Here, we identify OTUD5 acts as an essential regulator for MyD88 oligomerization and Myddosome formation. OTUD5 directly interacts with MyD88 and cleaves its K11-linked polyubiquitin chains at Lys95, Lys231 and Lys250. This polyubiquitin cleavage enhances MyD88 oligomerization after LPS stimulation, which subsequently promotes the recruitment of downstream IRAK4 and IRAK2 to form Myddosome and the activation of NF-κB and MAPK signaling and production of inflammatory cytokines. Consistently, Otud5-deficient mice are less susceptible to LPS- and CLP-induced sepsis. Taken together, our findings reveal a positive regulatory role of OTUD5 in MyD88 oligomerization and Myddosome formation, which provides new sights into the treatment of inflammatory diseases.

Effect of ethanol exposure on innate immune response in sepsis

Alcohol use disorder, reported by 1 in 8 critically ill patients, is a risk factor for death in sepsis patients. Sepsis, the leading cause of death, kills over 270,000 patients in the United States alone and remains without targeted therapy. Immune response in sepsis transitions from an early hyperinflammation to persistent inflammation and immunosuppression and multiple organ dysfunction during late sepsis. Innate immunity is the first line of defense against pathogen invasion. Ethanol exposure is known to impair innate and adaptive immune response and bacterial clearance in sepsis patients. Specifically, ethanol exposure is known to modulate every aspect of innate immune response with and without sepsis. Multiple molecular mechanisms are implicated in causing dysregulated immune response in ethanol exposure with sepsis, but targeted treatments have remained elusive. In this article, we outline the effects of ethanol exposure on various innate immune cell types in general and during sepsis.

Integrated multi-omics and artificial intelligence to explore new neutrophils clusters and potential biomarkers in sepsis with experimental validation

Background

Sepsis, causing serious organ and tissue damage and even death, has not been fully elucidated. Therefore, understanding the key mechanisms underlying sepsis-associated immune responses would lead to more potential therapeutic strategies.

Methods

Single-cell RNA data of 4 sepsis patients and 2 healthy controls in the GSE167363 data set were studied. The pseudotemporal trajectory analyzed neutrophil clusters under sepsis. Using the hdWGCNA method, key gene modules of neutrophils were explored. Multiple machine learning methods were used to screen and validate hub genes for neutrophils. SCENIC was then used to explore transcription factors regulating hub genes. Finally, quantitative reverse transcription-polymerase chain reaction was to validate mRNA expression of hub genes in peripheral blood neutrophils of two mice sepsis models.

Results

We discovered two novel neutrophil subtypes with a significant increase under sepsis. These two neutrophil subtypes were enriched in the late state during neutrophils differentiation. The hdWGCNA analysis of neutrophils unveiled that 3 distinct modules (Turquoise, brown, and blue modules) were closely correlated with two neutrophil subtypes. 8 machine learning methods revealed 8 hub genes with high accuracy and robustness (ALPL, ACTB, CD177, GAPDH, SLC25A37, S100A8, S100A9, and STXBP2). The SCENIC analysis revealed that APLP, CD177, GAPDH, S100A9, and STXBP2 were significant associated with various transcriptional factors. Finally, ALPL, CD177, S100A8, S100A9, and STXBP2 significantly up regulated in peripheral blood neutrophils of CLP and LPS-induced sepsis mice models.

Conclusions

Our research discovered new clusters of neutrophils in sepsis. These five hub genes provide novel biomarkers targeting neutrophils for the treatment of sepsis.

Integrated analysis of transcriptional changes in major depressive disorder: Insights from blood and anterior cingulate cortex

Background

Major depressive disorder (MDD) was involved in widely transcriptional changes in central and peripheral tissues. While, previous studies focused on single tissues, making it difficult to represent systemic molecular changes throughout the body. Thus, there is an urgent need to explore the central and peripheral biomarkers with intrinsic correlation.

Methods

We systematically retrieved gene expression profiles of blood and anterior cingulate cortex (ACC). 3 blood datatsets (84 MDD and 88 controls) and 6 ACC datasets (100 MDD and 100 controls) were obtained. Differential expression analysis, RobustRankAggreg (RRA) analysis, functional enrichment analysis, immune associated analysis and protein-protein interaction networks (PPI) were integrated. Furthermore, the key genes were validated in an independent ACC dataset (12 MDD and 15 controls) and a cohort with 120 MDD and 117 controls.

Results

Differential expression analysis identified 2211 and 2021 differential expressed genes (DEGs) in blood and ACC, respectively. RRA identified 45 and 25 robust DEGs in blood and ACC based on DEGs, and all of them were closely associated with immune cells. Functional enrichment results showed both the robust DEGs in blood and ACC were enriched in humoral immune response. Furthermore, PPI identified 8 hub DEGs (CD79A, CD79B, CD19, MS4A1, PLP1, CLDN11, MOG, MAG) in blood and ACC. Independent ACC dataset showed the area under the curve (AUC) based on these hub DEGs was 0.77. Meanwhile, these hub DEGs were validated in the serum of MDD patients, and also showed a promising diagnostic power.

Conclusions

The biomarker panel based on hub DEGs yield a promising diagnostic efficacy, and all of these hub DEGs were strongly correlated with immunity. Humoral immune response may be the key link between the brain and blood in MDD, and our results may provide further understanding for MDD.

Molecular mechanism analyses of post-traumatic epilepsy and hereditary epilepsy based on 10× single-cell transcriptome sequencing technology

BACKGROUND

Single-cell RNA sequencing analysis has been usually conducted on post-traumatic epilepsy (PET) and hereditary epilepsy (HE) patients; however, the transcriptome of patients with traumatic temporal lobe epilepsy has rarely been studied.

MATERIALS AND METHODS

Hippocampus tissues isolated from one patient with PTE and one patient with HE were used in the present study. Single cell isolates were prepared and captured using a 10× Genomics Chromium Single-Cell 3' kit (V3) according to the manufacturer's instructions. The libraries were sequenced on an Illumina NovaSeq 6000 sequencing system. Raw data were processed, and the cells were filtered and classified using the Seurat R package. Uniform Manifold Approximation and Projection was used for visualization. Differentially expressed genes (DEGs) were identified based on a p-value ≤0.01 and log fold change (FC) ≥0.25. Gene Ontology (GO, http://geneontology.org/) and KEGG (Kyoto Encyclopedia of Genes and Genomes, www.genome.jp/kegg) analyses were performed on the DEGs for enrichment analysis.

RESULTS

The reads obtained from the 10× genomic platform for PTE and HE were 39.56 M and 30.08 M, respectively. The Q30 score of the RNA reads was >91.6%. After filtering, 7479 PTE cells and 9357 HE cells remained for further study. More than 96.4% of the reads were mapped to GRCh38/GRCm38. The cells were differentially distributed in two groups, with higher numbers of oligodendrocytes (6522 vs. 2532) and astrocytes (133 vs. 52), and lower numbers of microglial cells (2242 vs. 3811), and neurons (3 vs. 203) present in the HE group than in the PTE group. The DEGs in four cell clusters were identified, with 25 being in oligodendrocytes (13 upregulated and 12 downregulated), 87 in microglia cells (42 upregulated and 45 downregulated), 222 in astrocytes (115 upregulated and 107 downregulated), and 393 in neurons (305 upregulated and 88 downregulated). The genes MTND1P23 (downregulated), XIST (downregulated), and RPS4Y1 (upregulated) were commonly expressed in all four cell clusters. The DEGs in microglial cells and astrocytes were enriched in the IL-17 signaling pathway.

CONCLUSION

Our study explored differences in cells found in a patient with PE compared to a patient with HE, and the transcriptome in the different cells was analyzed for the first time. Studying inflammatory and immune functions might be the best approach for investigating traumatic temporal lobe epilepsy in neurons.

Integrating single-cell RNA sequencing data to genome-wide association analysis data identifies significant cell types in influenza A virus infection and COVID-19

With the global pandemic of COVID-19, the research on influenza virus has entered a new stage, but it is difficult to elucidate the pathogenesis of influenza disease. Genome-wide association studies (GWASs) have greatly shed light on the role of host genetic background in influenza pathogenesis and prognosis, whereas single-cell RNA sequencing (scRNA-seq) has enabled unprecedented resolution of cellular diversity and in vivo following influenza disease. Here, we performed a comprehensive analysis of influenza GWAS and scRNA-seq data to reveal cell types associated with influenza disease and provide clues to understanding pathogenesis. We downloaded two GWAS summary data, two scRNA-seq data on influenza disease. After defining cell types for each scRNA-seq data, we used RolyPoly and LDSC-cts to integrate GWAS and scRNA-seq. Furthermore, we analyzed scRNA-seq data from the peripheral blood mononuclear cells (PBMCs) of a healthy population to validate and compare our results. After processing the scRNA-seq data, we obtained approximately 70 000 cells and identified up to 13 cell types. For the European population analysis, we determined an association between neutrophils and influenza disease. For the East Asian population analysis, we identified an association between monocytes and influenza disease. In addition, we also identified monocytes as a significantly related cell type in a dataset of healthy human PBMCs. In this comprehensive analysis, we identified neutrophils and monocytes as influenza disease-associated cell types. More attention and validation should be given in future studies.

An Evaluation of Type 1 Interferon Related Genes in Male and Female-Matched, SARS-CoV-2 Infected Individuals Early in the COVID-19 Pandemic

SARS-CoV-2 infection has claimed just over 1.1 million lives in the US since 2020. Globally, the SARS-CoV-2 respiratory infection spread to 771 million people and caused mortality in 6.9 million individuals to date. Much of the early literature showed that SARS-CoV-2 immunity was defective in the early stages of the pandemic, leading to heightened and, sometimes, chronic inflammatory responses in the lungs. This lung-associated 'cytokine storm' or 'cytokine release syndrome' led to the need for oxygen supplementation, respiratory distress syndrome, and mechanical ventilation in a relatively high number of people. In this study, we evaluated circulating PBMC from non-hospitalized, male and female, COVID-19+ individuals over the course of infection, from the day of diagnosis (day 0) to one-week post diagnosis (day 7), and finally 4 weeks after diagnosis (day 28). In our early studies, we included hospitalized and critically care patient PBMC; however, most of these individuals were lymphopenic, which limited our assessments of their immune integrity. We chose a panel of 30 interferon-stimulated genes (ISG) to evaluate by PCR and completed flow analysis for immune populations present in those PBMC. Lastly, we assessed immune activation by stimulating PBMC with common TLR ligands. We identified changes in innate cells, primarily the innate lymphoid cells (ILC, NK cells) and adaptive immune cells (CD4+ and CD8+ T cells) over this time course of infection. We found that the TLR-7 agonist, Resiquimod, and the TLR-4 ligand, LPS, induced significantly better IFNα and IFNγ responses in the later phase (day 28) of SARS-CoV-2 infection in those non-hospitalized COVID-19+ individuals as compared to early infection (day 0 and day 7). We concluded that TLR-7 and TLR-4 agonists may be effective adjuvants in COVID-19 vaccines for mounting immunity that is long-lasting against SARS-CoV-2 infection.

Single-Cell Sequencing Reveals Functional Alterations in Tuberculosis

Despite its importance, the functional heterogeneity surrounding the dynamics of interactions between mycobacterium tuberculosis and human immune cells in determining host immune strength and tuberculosis (TB) outcomes, remains far from understood. This work now describes the development of a new technological platform to elucidate the immune function differences in individuals with TB, integrating single-cell RNA sequencing and cell surface antibody sequencing to provide both genomic and phenotypic information from the same samples. Single-cell analysis of 23 990 peripheral blood mononuclear cells from a new cohort of primary TB patients and healthy controls enables to not only show four distinct immune phenotypes (TB, myeloid, and natural killer (NK) cells), but also determine the dynamic changes in cell population abundance, gene expression, developmental trajectory, transcriptomic regulation, and cell-cell signaling. In doing so, TB-related changes in immune cell functions demonstrate that the immune response is mediated through host T cells, myeloid cells, and NK cells, with TB patients showing decreased naive, cytotoxicity, and memory functions of T cells, rather than their immunoregulatory function. The platform also has the potential to identify new targets for immunotherapeutic treatment strategies to restore T cells from dysfunctional or exhausted states.

Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

BACKGROUND

Gut microbiota alterations have been implicated in sepsis and related infectious diseases, but the causal relationship and underlying mechanisms remain unclear.

METHODS

We evaluated the association between gut microbiota composition and sepsis using two-sample Mendelian randomization (MR) analysis based on published genome-wide association study (GWAS) summary statistics. Sensitivity analyses were conducted to validate the robustness of the results. Reverse MR analysis and integration of GWAS and expression quantitative trait loci (eQTL) data were performed to identify potential genes and therapeutic targets.

RESULTS

Our analysis identified 11 causal bacterial taxa associated with sepsis, with increased abundance of six taxa showing positive causal relationships. Ten taxa had causal effects on the 28-day survival outcome of septic patients, with increased abundance of six taxa showing positive associations. Sensitivity analyses confirmed the robustness of these associations. Reverse MR analysis did not provide evidence of reverse causality. Integration of GWAS and eQTL data revealed 76 genes passing the summary data-based Mendelian randomization (SMR) test. Differential expression of these genes was observed between sepsis patients and healthy individuals. These genes represent potential therapeutic targets for sepsis. Molecular docking analysis predicted potential drug-target interactions, further supporting their therapeutic potential.

CONCLUSION

Our study provides insights for the development of personalized treatment strategies for sepsis and offers preliminary candidate targets and drugs for future drug development.

Comparative analysis of peripheral blood immunoinflammatory landscapes in patients with acute cholangitis and its secondary septic shock using single-cell RNA sequencing

BACKGROUND

Acute cholangitis (AC) is a key pathogeny of septic shock, which has a high mortality rate. AC has significant clinical heterogeneity, but no study has analyzed the discrepancies in immunoresponsiveness between AC and its secondary septic shock. The immune inflammatory responses play a critical role in the development of septic shock.

METHODS

We performed single-cell RNA sequencing (scRNA-seq) to analyze the differences of immunocytes in immunoresponse and inflammation between the early stages of AC (A1, A2, and A3) and its secondary septic shock (B1, B2, and B3).

RESULTS

This study has identified seven cell types, including T cells, B cells, plasma cells, neutrophils, monocytes, platelets and erythrocytes. We mainly focused on neutrophils, monocytes, and T cells. Neutrophil subpopulation analysis indicated that neutrophil progenitors (proNeus) were identified in neutrophil subsets. Compared with patients suffering from AC, the gene phenotypes of proNeus (ELANE, AZU1, MPO, and PRTN3) were significantly upregulated in septic shock. The differentiation direction of neutrophil subsets in peripheral blood mononuclear cells (PBMCs) was determined; Moreover, the proNeus in septic shock presented a state of "expansion", with upregulation of neutrophil degranulation and downregulation of monocyte and T cell proliferation. Neutrophils-7 (CCL5, RPL23A, RPL13, RPS19 and RPS18) were mainly involved in the regulation of cellular functions. The neutrophils-7 subpopulation in septic shock were in a state of "exhaustion", and its biological functions showed the characteristics of weakening neutrophil migration and phagocytosis, etc., which maked infection difficult to control and aggravated the development of septic shock. Analysis of monocyte and T cell subpopulations showed that the expression genes and biological functions of subpopulations were closely related to immunoinflammatory regulation. In addition, CCL3 - CCR1, CXCL1 - CXCR2 and other ligand-receptors were highly expressed in neutrophils and monocytes, enhancing interactions between immune cells.

CONCLUSION

ScRNA-seq revealed significant differences in immune cells between AC and its secondary septic shock, which were primarily manifested in the cellular numbers, differentially expressed genes, functions of cellular subsets, differentiation trajectories, cell-cell interactions and so on. We identified many subsets of neutrophil, T cell and monocyte were associated with inflammation and immunosuppression induced by septic shock. These provided a reference for accurately evaluating the pathological severity of patients with AC and discovering the targets for therapy.

Persistent sepsis-induced transcriptomic signatures in signaling pathways of peripheral blood leukocytes: A pilot study

Sepsis is a dysregulated immune response to infections that frequently precipitates multiple organ dysfunction and death despite intensive supportive therapy. The aim of the present study was to identify sepsis-induced alterations in the signaling transcriptome of peripheral blood leukocytes that might shed light on the elusive transition from proinflammatory to anti-inflammatory responses and underlie long-term post-sepsis immunosuppression. Peripheral blood leukocytes were collected from subjects (i) with systemic inflammation, (ii) with sepsis in the acute phase and (iii) 6 months after recovery from sepsis, corresponding to progressive stages of the disease. Transcriptomic analysis was performed with the QuantStudio 12K Flex OpenArray Human Signal Transduction Panel analyzing transcripts of 573 genes playing a significant role in signaling. Of them, 145 genes exhibited differential expression in sepsis as compared to systemic inflammation. Pathway analysis revealed enhanced expression levels of genes involved in primary immune responses (proinflammatory cytokines, neutrophil and macrophage activation markers) and signatures characteristic of immunosuppression (increased expression of anti-inflammatory cytokines and proapoptotic genes; diminished expression of T and B cell receptor dependent activating and survival pathways). Importantly, sepsis-induced expression patterns of 39 genes were not normalized by the end of the 6-month follow-up period, indicating expression aberrations persisting long after clinical recovery. Functional analysis of these transcripts revealed downregulation of the antiapoptotic Wnt and mTOR signaling pathways that might explain the post-sepsis immunosuppression commonly seen in sepsis survivors.

Shikonin prevents mice from heat stroke-induced death via suppressing a trigger IL-17A on the inflammatory and oxidative pathways

Heat stroke (HS) is the deadliest disease. Due to the complex pathogenesis of HS, lack of effective therapeutic drugs for clinical treatment. Shikonin (SK) is the main active compound of Radix Arnebiae, which was evaluated on the HS model (temperature: (41 ± 0.5) ℃, relative humidity: (60 ± 5) %) via pathological and biochemical approaches in vivo and in vitro. Upon the dose of 10 mg.kg-1, SK delays the rising rate of core temperature, prolongs the survival time of mice, and improves organ injury and coagulation function markedly. Serum HS biomarkers interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) were decreased significantly by SK, which contribute to liver and lung protection in the models. Three pathways' responses to heat-stress were found to have a close connection with the IL-17 pathway via RNA sequencing and network analysis. WB and IHC results showed that the nuclear factor-κB (NF-κB) p65 in the SK group was down-regulated (P < 0.05). The expressions of nuclear factor erythroid 2 like 2 (NFE2L2/Nrf2) and heat shock protein 70 (HSP70) were up-regulated (P < 0.05). Additional administration of recombinant IL-17A protein on the HS model up-regulated the expression level of NF- κB p65 in the liver and lung tissue, additional intraperitoneal injection of IL-17A antibody in mice has a synergistic effect with SK in inhibiting tissue inflammatory response and protecting HS. In summary, SK was proved an effective compound for fulfilling the anti-inflammatory and antioxidative capacity of the HS model by reducing the production and inhibiting the expression of IL-17A.

Comprehensive single-cell analysis reveals novel anergic antigen-presenting cell subtypes in human sepsis

Background

Sepsis is a life-threatening condition with high mortality. A few studies have emerged utilizing single-cell RNA sequencing (scRNA-seq) to analyze gene expression at the single-cell resolution in sepsis, but a comprehensive high-resolution analysis of blood antigen-presenting cells has not been conducted.

Methods

All published human scRNA-seq data were downloaded from the single cell portal database. After manually curating the dataset, we extracted all antigen-presenting cells, including dendritic cells (DCs) and monocytes, for identification of cell subpopulations and their gene profiling and intercellular interactions between septic patients and healthy controls. Finally, we further validated the findings by performing deconvolution analysis on bulk RNA sequencing (RNA-seq) data and flow cytometry.

Results

Within the traditional DC populations, we discovered novel anergic DC subtypes characterized by low major histocompatibility complex class II expression. Notably, these anergic DC subtypes showed a significant increase in septic patients. Additionally, we found that a previously reported immunosuppressive monocyte subtype, Mono1, exhibited a similar gene expression profile to these anergic DCs. The consistency of our findings was confirmed through validation using bulk RNA-seq and flow cytometry, ensuring accurate identification of cell subtypes and gene expression patterns.

Conclusions

This study represents the first comprehensive single-cell analysis of antigen-presenting cells in human sepsis, revealing novel disease-associated anergic DC subtypes. These findings provide new insights into the cellular mechanisms of immune dysregulation in bacterial sepsis.

Single-cell transcriptome analysis reveals the regulatory effects of artesunate on splenic immune cells in polymicrobial sepsis

Sepsis is characterized by a severe and life-threatening host immune response to polymicrobial infection accompanied by organ dysfunction. Studies on the therapeutic effect and mechanism of immunomodulatory drugs on the sepsis-induced hyperinflammatory or immunosuppression states of various immune cells remain limited. This study aimed to investigate the protective effects and underlying mechanism of artesunate (ART) on the splenic microenvironment of cecal ligation and puncture-induced sepsis model mice using single-cell RNA sequencing (scRNA-seq) and experimental validations. The scRNA-seq analysis revealed that ART inhibited the activation of pro-inflammatory macrophages recruited during sepsis. ART could restore neutrophils' chemotaxis and immune function in the septic spleen. It inhibited the activation of T regulatory cells but promoted the cytotoxic function of natural killer cells during sepsis. ART also promoted the differentiation and activity of splenic B cells in mice with sepsis. These results indicated that ART could alleviate the inflammatory and/or immunosuppressive states of various immune cells involved in sepsis to balance the immune homeostasis within the host. Overall, this study provided a comprehensive investigation of the regulatory effect of ART on the splenic microenvironment in sepsis, thus contributing to the application of ART as adjunctive therapy for the clinical treatment of sepsis.

Peripheral immune cell death in sepsis based on bulk RNA and single-cell RNA sequencing

Background

Immune cell activation in early sepsis is beneficial to clear pathogens, but immune cell exhaustion during the inflammatory response induces immunosuppression in sepsis. Here, we studied the relationship between immune cell survival status and the prognosis of sepsis patients.

Methods

Sepsis patients admitted to our hospital with a diagnosis time of less than 24 h were recruited. RNA sequencing technologies were used to study functional alterations in various immune cells in peripheral blood mononuclear cells (PBMCs) from sepsis patients. Flow cytometry and electron microscopy were performed to study cell apoptosis and morphological alterations.

Results

A total of 68 sepsis patients with complete data were enrolled and divided into survival (45 patients) and death (23 patients) groups according to their prognosis. Patients in the death group had significantly increased lactic acid levels compared with those in the survival group, but there was no significant difference in other physiological and coagulation functional indicators between the two groups. Bulk RNA sequencing showed that cell death-related pathways and biomarkers were highly enriched and activated in the PBMCs of the death group than that in the survival group. Signs of mitochondrial damage, autophagosomes, cell surface damage and cell surface pore forming were also more pronounced in PBMCs from the death group under electron microscopy. Further single-cell RNA sequencing revealed that cell death occurred mainly in myeloid cells rather than lymphocytes at the early stage of sepsis; cell death patterns of destructive necrosis and pyroptosis were predominant in neutrophils, and apoptosis, autophagy and ferroptosis with less damage to the surroundings were predominant in monocytes.

Conclusion

Cell death mainly occurs in monocytes and neutrophils in the PBMCs of sepsis at the early stage. The study provides a perspective for the immunotherapy of early sepsis targeting immune cell death.

Urinary microRNAs in sepsis function as a novel prognostic marker

Renal dysfunction is a common complication of sepsis. Early diagnosis and prompt treatment of sepsis with renal insufficiency are crucial for improving patient outcomes. Diagnostic markers can help identify patients at risk for sepsis and AKI, allowing for early intervention and potentially preventing the development of severe complications. The aim of the present study was to investigate the expression difference of urinary microRNAs (miRNAs/miRs) in elderly patients with sepsis and secondary renal insufficiency, and to evaluate their diagnostic value in these patients. In the present study, RNA was extracted from urine samples of elderly sepsis-related acute renal damage patients and the expression profiles of several miRNAs were analyzed. In order to evaluate the expression profile of several miRNAs, urine samples from elderly patients with acute renal damage brought on by sepsis were obtained. RNA extraction and sequencing were then performed on the samples. Furthermore, multiple bioinformatics methods were used to analyze miRNA profiles, including differential expression analysis, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis of different miRNA target genes, to further explore miRNAs that are suitable for utilization as biomarkers. A total of four miRNAs, including hsa-miR-31-5p, hsa-miR-151a-3p, hsa-miR-142-5p and hsa-miR-16-5p, were identified as potential biological markers and were further confirmed in sepsis using reverse transcription-quantitative PCR. The results of the present study demonstrated that the four urinary miRNAs were differentially expressed and may serve as specific markers for prediction of secondary acute kidney injury in elderly patients with sepsis.

HOPX is a tumor-suppressive biomarker that corresponds to T cell infiltration in skin cutaneous melanoma

BACKGROUND

Skin cutaneous melanoma (SKCM) is the most threatening type of skin cancer. Approximately 55,000 people lose their lives every year due to SKCM, illustrating that it seriously threatens human life and health. Homeodomain-only protein homeobox (HOPX) is the smallest member of the homeodomain family and is widely expressed in a variety of tissues. HOPX is involved in regulating the homeostasis of hematopoietic stem cells and is closely related to the development of tumors such as breast cancer, nasopharyngeal carcinoma, and head and neck squamous cell carcinoma. However, its function in SKCM is unclear, and further studies are needed.

METHODS

We used the R language to construct ROC (Receiver-Operating Characteristic) curves, KM (Kaplan‒Meier) curves and nomograms based on databases such as the TCGA and GEO to analyze the diagnostic and prognostic value of HOPX in SKCM patients. Enrichment analysis, immune scoring, GSVA (Gene Set Variation Analysis), and single-cell sequencing were used to verify the association between HOPX expression and immune infiltration. In vitro experiments were performed using A375 cells for phenotypic validation. Transcriptome sequencing was performed to further analyze HOPX gene-related genes and their signaling pathways.

RESULTS

Compared to normal cells, SKCM cells had low HOPX expression (p < 0.001). Patients with high HOPX expression had a better prognosis (p < 0.01), and the marker had good diagnostic efficacy (AUC = 0.744). GO/KEGG (Gene Ontology/ Kyoto Encyclopedia of Genes and Genomes) analysis, GSVA and single-cell sequencing analysis showed that HOPX expression is associated with immune processes and high enrichment of T cells and could serve as an immune checkpoint in SKCM. Furthermore, cellular assays verified that HOPX inhibits the proliferation, migration and invasion of A375 cells and promotes apoptosis and S-phase arrest. Interestingly, tumor drug sensitivity analysis revealed that HOPX also plays an important role in reducing clinical drug resistance.

CONCLUSION

These findings suggest that HOPX is a blocker of SKCM progression that inhibits the proliferation of SKCM cells and promotes apoptosis. Furthermore, it may be a new diagnostic and prognostic indicator and a novel target for immunotherapy in SKCM patients.

Exploration of m6A methylation regulators as epigenetic targets for immunotherapy in advanced sepsis

BACKGROUND

This study aims to deeply explore the relationship between m⁶A methylation modification and peripheral immune cells in patients with advanced sepsis and mine potential epigenetic therapeutic targets by analyzing the differential expression patterns of m⁶A-related genes in healthy subjects and advanced sepsis patients.

METHODS

A single cell expression dataset of peripheral immune cells containing blood samples from 4 patients with advanced sepsis and 5 healthy subjects was obtained from the gene expression comprehensive database (GSE175453). Differential expression analysis and cluster analysis were performed on 21 m⁶A-related genes. The characteristic gene was identified based on random forest  algorithm, and the correlation between the characteristic gene METTL16 and 23 immune cells in patients with advanced sepsis was evaluated using single-sample gene set enrichment analysis.

RESULTS

IGFBP1, IGFBP2, IGF2BP1, and WTAP were highly expressed in patients with advanced sepsis and m⁶A cluster B. IGFBP1, IGFBP2, and IGF2BP1 were positively correlated with Th17 helper T cells. The characteristic gene METTL16 exhibited a significant positive correlation with the proportion of various immune cells.

CONCLUSION

IGFBP1, IGFBP2, IGF2BP1, WTAP, and METTL16 may accelerate the development of advanced sepsis by regulating m⁶A methylation modification and promoting immune cell infiltration. The discovery of these characteristic genes related to advanced sepsis provides potential therapeutic targets for the diagnosis and treatment of sepsis.

Gut microbial metabolite hyodeoxycholic acid targets the TLR4/MD2 complex to attenuate inflammation and protect against sepsis

Sepsis, a critical condition resulting from the systemic inflammatory response to a severe microbial infection, represents a global public health challenge. However, effective treatment or intervention to prevent and combat sepsis is still lacking. Here, we report that hyodeoxycholic acid (HDCA) has excellent anti-inflammatory properties in sepsis. We discovered that the plasma concentration of HDCA was remarkably lower in patients with sepsis and negatively correlated with the severity of the disease. Similar changes in HDCA levels in plasma and cecal content samples were observed in a mouse model of sepsis, and these changes were associated with a reduced abundance of HDCA-producing strains. Interestingly, HDCA administration significantly decreased systemic inflammatory responses, prevented organ injury, and prolonged the survival of septic mice. We demonstrated that HDCA suppressed excessive activation of inflammatory macrophages by competitively blocking lipopolysaccharide binding to the Toll-like receptor 4 (TLR4) and myeloid differentiation factor 2 receptor complex, a unique mechanism that characterizes HDCA as an endogenous inhibitor of inflammatory signaling. Additionally, we verified these findings in TLR4 knockout mice. Our study highlights the potential value of HDCA as a therapeutic molecule for sepsis.

Parallel Dysregulated Immune Response in Severe Forms of COVID-19 and Bacterial Sepsis via Single-Cell Transcriptome Sequencing

Critically ill COVID-19 patients start developing single respiratory organ failure that often evolves into multiorgan failure. Understanding the immune mechanisms in severe forms of an infectious disease (either critical COVID-19 or bacterial septic shock) would help to achieve a better understanding of the patient’s clinical trajectories and the success of potential therapies. We hypothesized that a dysregulated immune response manifested by the abnormal activation of innate and adaptive immunity might be present depending on the severity of the clinical presentation in both COVID-19 and bacterial sepsis. We found that critically ill COVID-19 patients demonstrated a different clinical endotype that resulted in an inflammatory dysregulation in mild forms of the disease. Mild cases (COVID-19 and bacterial non severe sepsis) showed significant differences in the expression levels of CD8 naïve T cells, CD4 naïve T cells, and CD4 memory T cells. On the other hand, in the severe forms of infection (critical COVID-19 and bacterial septic shock), patients shared immune patterns with upregulated single-cell transcriptome sequencing at the following levels: B cells, monocyte classical, CD4 and CD8 naïve T cells, and natural killers. In conclusion, we identified significant gene expression differences according to the etiology of the infection (COVID-19 or bacterial sepsis) in the mild forms; however, in the severe forms (critical COVID-19 and bacterial septic shock), patients tended to share some of the same immune profiles related to adaptive and innate immune response. Severe forms of the infections were similar independent of the etiology. Our findings might promote the implementation of co-adjuvant therapies and interventions to avoid the development of severe forms of disease that are associated with high mortality rates worldwide.

Single-cell transcriptomics reveals immune infiltrate in sepsis

Immune cells and immune microenvironment play important in the evolution of sepsis. This study aimed to explore hub genes related to the abundance of immune cell infiltration in sepsis. The GEOquery package is used to download and organize data from the GEO database. A total of 61 differentially expressed genes (DEGs) between sepsis samples and normal samples were obtained through the 'limma' package. T cells, natural killer (NK) cells, monocytes, megakaryocytes, dendritic cells (DCs), and B cells formed six distinct clusters on the t-distributed stochastic neighbor embedding (t-SNE) plot generated using the Seurat R package. Gene set enrichment analysis (GSEA) enrichment analysis showed that sepsis samples and normal samples were related to Neutrophil Degranulation, Modulators of Tcr Signaling and T Cell Activation, IL 17 Pathway, T Cell Receptor Signaling Pathway, Ctl Pathway, Immunoregulatory Interactions Between a Lymphoid and A Non-Lymphoid Cell. GO analysis and KEGG analysis of immune-related genes showed that the intersection genes were mainly associated with Immune-related signaling pathways. Seven hub genes (CD28, CD3D, CD2, CD4, IL7R, LCK, and CD3E) were screened using Maximal Clique Centrality, Maximum neighborhood component, and Density of Maximum Neighborhood Component algorithms. The lower expression of the six hub genes (CD28, CD3D, CD4, IL7R, LCK, and CD3E) was observed in sepsis samples. We observed the significant difference of several immune cell between sepsis samples and control samples. Finally, we carried out in vivo animal experiments, including Western blotting, flow cytometry, Elisa, and qPCR assays to detect the concentration and the expression of several immune factors.

Identification of a novel sepsis prognosis model and analysis of possible drug application prospects: Based on scRNA-seq and RNA-seq data

Sepsis is a disease with a high morbidity and mortality rate. At present, there is a lack of ideal biomarker prognostic models for sepsis and promising studies using prognostic models to predict and guide the clinical use of medications. In this study, 71 differentially expressed genes (DEGs) were obtained by analyzing single-cell RNA sequencing (scRNA-seq) and transcriptome RNA-seq data, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analyses were performed on these genes. Then, a prognosis model with CCL5, HBD, IFR2BP2, LTB, and WFDC1 as prognostic signatures was successfully constructed after univariate LASSO regression analysis and multivariate Cox regression analysis. Kaplan-Meier (K-M) survival analysis, receiver operating characteristic (ROC) time curve analysis, internal validation, and principal component analysis (PCA) further validated the model for its high stability and predictive power. Furthermore, based on a risk prediction model, gene set enrichment analysis (GSEA) showed that multiple cellular functions and immune function signaling pathways were significantly different between the high- and low-risk groups. In-depth analysis of the distribution of immune cells in healthy individuals and sepsis patients using scRNA-seq data revealed immunosuppression in sepsis patients and differences in the abundance of immune cells between the high- and low-risk groups. Finally, the genetic targets of immunosuppression-related drugs were used to accurately predict the potential use of clinical agents in high-risk patients with sepsis.

Combining single-cell RNA sequencing of peripheral blood mononuclear cells and exosomal transcriptome to reveal the cellular and genetic profiles in COPD

Background

It has been a long-held consensus that immune reactions primarily mediate the pathology of chronic obstructive pulmonary disease (COPD), and that exosomes may participate in immune regulation in COPD. However, the relationship between exosomes and peripheral immune status in patients with COPD remains unclear.

Methods

In this study, we sequenced plasma exosomes and performed single-cell RNA sequencing on peripheral blood mononuclear cells (PBMCs) from patients with COPD and healthy controls. Finally, we constructed competing endogenous RNA (ceRNA) and protein–protein interaction (PPI) networks to delineate the interactions between PBMCs and exosomes within COPD.

Results

We identified 135 mRNAs, 132 lncRNAs, and 359 circRNAs from exosomes that were differentially expressed in six patients with COPD compared with four healthy controls. Functional enrichment analyses revealed that many of these differentially expressed RNAs were involved in immune responses including defending viral infection and cytokine–cytokine receptor interaction. We also identified 18 distinct cell clusters of PBMCs in one patient and one control by using an unsupervised cluster analysis called uniform manifold approximation and projection (UMAP). According to resultant cell identification, it was likely that the proportions of monocytes, dendritic cells, and natural killer cells increased in the COPD patient we tested, meanwhile the proportions of B cells, CD4 + T cells, and naïve CD8 + T cells declined. Notably, CD8 + T effector memory CD45RA + (Temra) cell and CD8 + effector memory T (Tem) cell levels were elevated in patient with COPD, which were marked by their lower capacity to differentiate due to their terminal differentiation state and lower reactive capacity to viral pathogens.

Conclusions

We generated exosomal RNA profiling and single-cell transcriptomic profiling of PBMCs in COPD, described possible connection between impaired immune function and COPD development, and finally determined the possible role of exosomes in mediating local and systemic immune reactions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02182-8.

Host and microbiome features of secondary infections in lethal covid-19

Secondary infections contribute significantly to covid-19 mortality but driving factors remain poorly understood. Autopsies of 20 covid-19 cases and 14 controls from the first pandemic wave complemented with microbial cultivation and RNA-seq from lung tissues enabled description of major organ pathologies and specification of secondary infections. Lethal covid-19 segregated into two main death causes with either dominant diffuse alveolar damage (DAD) or secondary pneumonias. The lung microbiome in covid-19 showed a reduced biodiversity and increased prototypical bacterial and fungal pathogens in cases of secondary pneumonias. RNA-seq distinctly mirrored death causes and stratified DAD cases into subgroups with differing cellular compositions identifying myeloid cells, macrophages and complement C1q as strong separating factors suggesting a pathophysiological link. Together with a prominent induction of inhibitory immune-checkpoints our study highlights profound alterations of the lung immunity in covid-19 wherein a reduced antimicrobial defense likely drives development of secondary infections on top of SARS-CoV-2 infection.

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Covid-19 autopsy cohort complemented with microbial cultivation and deep sequencing

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Major death causes stratify into DAD and secondary pneumonias

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Prototypical bacterial and fungal agents are found in secondary pneumonias

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Macrophages and C1q stratify DAD subgroups and indicate immune impairment in lungs

Bulk RNA Sequencing With Integrated Single-Cell RNA Sequencing Identifies BCL2A1 as a Potential Diagnostic and Prognostic Biomarker for Sepsis

Background

Sepsis is one of the leading causes of morbidity and mortality worldwide in the intensive care unit (ICU). The prognosis of the disease strongly depends on rapid diagnosis and appropriate treatment. Thus, some new and accurate sepsis-related biomarkers are pressing needed and their efficiency should be carefully demonstrated.

Methods

Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were applied to detect sepsis and monocyte/macrophage-related genes. Least absolute shrinkage and selection operator (LASSO) and random forest regression analyses were used in combination to screen out prognostic genes. Single-cell RNA sequence profiling was utilized to further verify the expression of these genes on a single cell level. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were also applied to verify the diagnostic value of the target biomarkers.

Results

The intersections of the genes detected by differential expression and WGCNA analyses identified 141 overlapping candidate genes that were closely related to sepsis and macrophages. The LASSO and random forest regression analyses further screened out 17 prognostic genes. Single-cell RNA sequencing analysis detected that FCGR1A and BCL2A1 might be potential biomarkers for sepsis diagnosis and the diagnostic efficacy of BCL2A1 was further validated by ROC curve and DCA.

Conclusions

It was revealed that BCL2A1 had good diagnostic and prognostic value for sepsis, and that it can be applied as a potential and novel biomarker for the management of the disease.

The balance between protective and pathogenic immune responses to pneumonia in the neonatal lung is enforced by gut microbiota

Although modern clinical practices such as cesarean sections and perinatal antibiotics have improved infant survival, treatment with broad-spectrum antibiotics alters intestinal microbiota and causes dysbiosis. Infants exposed to perinatal antibiotics have an increased likelihood of life-threatening infections, including pneumonia. Here, we investigated how the gut microbiota sculpt pulmonary immune responses, promoting recovery and resolution of infection in newborn rhesus macaques. Early-life antibiotic exposure interrupted the maturation of intestinal commensal bacteria and disrupted the developmental trajectory of the pulmonary immune system, as assessed by single-cell proteomic and transcriptomic analyses. Early-life antibiotic exposure rendered newborn macaques more susceptible to bacterial pneumonia, concurrent with increases in neutrophil senescence and hyperinflammation, broad inflammatory cytokine signaling, and macrophage dysfunction. This pathogenic reprogramming of pulmonary immunity was further reflected by a hyperinflammatory signature in all pulmonary immune cell subsets coupled with a global loss of tissue-protective, homeostatic pathways in the lungs of dysbiotic newborns. Fecal microbiota transfer was associated with partial correction of the broad immune maladaptations and protection against severe pneumonia. These data demonstrate the importance of intestinal microbiota in programming pulmonary immunity and support the idea that gut microbiota promote the balance between pathways driving tissue repair and inflammatory responses associated with clinical recovery from infection in infants. Our results highlight a potential role for microbial transfer for immune support in these at-risk infants.

An Organ System-Based Synopsis of Pseudomonas aeruginosa Virulence

Driven in part by its metabolic versatility, high intrinsic antibiotic resistance, and a large repertoire of virulence factors, Pseudomonas aeruginosa is expertly adapted to thrive in a wide variety of environments, and in the process, making it a notorious opportunistic pathogen. Apart from the extensively studied chronic infection in the lungs of people with cystic fibrosis (CF), P. aeruginosa also causes multiple serious infections encompassing essentially all organs of the human body, among others, lung infection in patients with chronic obstructive pulmonary disease, primary ciliary dyskinesia and ventilator-associated pneumonia; bacteremia and sepsis; soft tissue infection in burns, open wounds and postsurgery patients; urinary tract infection; diabetic foot ulcers; chronic suppurative otitis media and otitis externa; and keratitis associated with extended contact lens use. Although well characterized in the context of CF, pathogenic processes mediated by various P. aeruginosa virulence factors in other organ systems remain poorly understood. In this review, we use an organ system-based approach to provide a synopsis of disease mechanisms exerted by P. aeruginosa virulence determinants that contribute to its success as a versatile pathogen.