Host Gene Expression Research Articles

Limitation of amino acid availability by bacterial populations during enhanced colitis in IBD mouse model.

Inflammatory bowel disease is associated with an increase in Enterobacteriaceae and Enterococcus species; however, the specific mechanisms are unclear. Previous research has reported the associations between microbiota and inflammation, here we investigate potential pathways that specific bacteria populations use to drive gut inflammation. Richie et al. show that these bacterial populations utilize an alternate sulfur metabolism and are tolerant of host-derived immune-response products. These metabolic pathways drive host gut inflammation and fuel over colonization of these pathobionts in the dysbiotic colon. Cultured isolates from dysbiotic mice indicated faster growth supplemented with L-cysteine, showing these microbes can utilize essential host nutrients.

Expression and Regulatory Roles of Small Nucleolar RNA Host Gene 4 in Gastric Cancer.

The role of SNHG4 in the initiation and development of gastric cancer. Gastric cancer is one of the leading causes of cancer death worldwide. Studies have shown that lncRNAs have a regulatory function in human diseases, particularly cancers. Small nuclear RNA host gene 4 (SNHG4) has been known as an oncogenic long noncoding RNA (lncRNA) in various cancers, and its dysregulation can lead to tumorigenesis and cancer progression. The present study aims to determine the molecular mechanism of SNHG4 and the effects of its expression on the development of GC. Based on the bioinformatics investigations, we studied gene expression analysis, Kaplan-Meier survival, Gene ontology (GO), KEGG pathway enrichment, microRNA targets, transcription factor targets, and proteins interacting with SNHG4. During the experimental phase, SNHG4 expression was examined by quantitative real-time PCR (qRTPCR) in 40 paired gastric adenocarcinoma tissues and normal neighboring tissues. Also, we investigated the correlation between SNHG4 expression and patients' clinicopathological characteristics. Alteration of SNHG4 expression in gastric cancer and its correlation whit with clinical features of patients with stomach cancer; also, the accomplishment of bioinformatic analysis to find the potential pathways which could be impressed by changes in SNHG4 RNA expression. Increased SNHG4 expression was detected in GC tissues, which is significantly associated with the TNM stage, grade group, tumor size, and metastatic status. Evaluation survival analysis demonstrated that overexpression of SNHG4 in GC tissues is remarkably related to poor overall survival (OS). SNHG4 is closely related to miR-490 and E2F family transcription factors. GO analysis suggested the possible role of SNHG4 in cell-cell adhesion, and KEGG enrichment analysis revealed that SNHG4 could be associated with the gastric cancer signaling pathway. ELAVL1 and IGF2BP2 have the highest number of SNHG4 target sites, and these proteins are involved in the PI3K-Akt-mTOR and ERK-MAPK signaling pathways. Based on our results, we conclude that SNHG4 may have a function in GC development by regulating tumor-related signaling pathways.

SARS-CoV-2 infection engenders heterogeneous ribonucleoprotein interactions to impede translation elongation in the lungs.

Translational regulation in tissue environments during in vivo viral pathogenesis has rarely been studied due to the lack of translatomes from virus-infected tissues, although a series of translatome studies using in vitro cultured cells with viral infection have been reported. In this study, we exploited tissue-optimized ribosome profiling (Ribo-seq) and severe-COVID-19 model mice to establish the first temporal translation profiles of virus and host genes in the lungs during SARS-CoV-2 pathogenesis. Our datasets revealed not only previously unknown targets of translation regulation in infected tissues but also hitherto unreported molecular signatures that contribute to tissue pathology after SARS-CoV-2 infection. Specifically, we observed gradual increases in pseudoribosomal ribonucleoprotein (RNP) interactions that partially overlapped the trails of ribosomes, being likely involved in impeding translation elongation. Contemporaneously developed ribosome heterogeneity with predominantly dysregulated 5 S rRNP association supported the malfunction of elongating ribosomes. Analyses of canonical Ribo-seq reads (ribosome footprints) highlighted two obstructive characteristics to host gene expression: ribosome stalling on codons within transmembrane domain-coding regions and compromised translation of immunity- and metabolism-related genes with upregulated transcription. Our findings collectively demonstrate that the abrogation of translation integrity may be one of the most critical factors contributing to pathogenesis after SARS-CoV-2 infection of tissues.

13. HPV forms chimeric virus-human transcripts that affect host gene expression in cervical tumors

13. HPV forms chimeric virus-human transcripts that affect host gene expression in cervical tumors

KSHV RTA utilizes the host E3 ubiquitin ligase complex RNF20/40 to drive lytic reactivation.

Kaposi's sarcoma-associated herpesvirus (KSHV) is a cancer-causing human herpesvirus that establishes a persistent infection in humans. The lytic viral cycle plays a crucial part in lifelong infection as it is involved in the viral dissemination. The master regulator of the KSHV lytic replication cycle is the viral replication and transcription activator (RTA) protein, which is necessary and sufficient to push the virus from latency into the lytic phase. Thus, the identification of host factors utilized by RTA for controlling the lytic cycle can help to find novel targets that could be used for the development of antiviral therapies against KSHV. Using a proteomics approach, we have identified a novel interaction between RTA and the cellular E3 ubiquitin ligase complex RNF20/40, which we have shown to be necessary for promoting RTA-induced KSHV lytic cycle.

Heme Metabolism Mediates the Effects of Smoking on Gut Microbiome.

The number of smokers worldwide increased greatly during the past decades and reached 1.14 billion in 2019, becoming a leading risk factor for human health. Tobacco smoking has wide effects on human genetics, epigenetics, transcriptome, and gut microbiome. Although many studies have revealed effects of smoking on host transcriptome, research on the relationship between smoking, host gene expression, and the gut microbiome is limited. We first explored transcriptome and metagenome profile differences between smokers and nonsmokers. To evaluate the relationship between host gene expression and gut microbiome, we then applied bidirectional mediation analysis to infer causal relationships between smoking, gene expression, and gut microbes. Metagenome and transcriptome analyses revealed 71 differential species and 324 differential expressed genes between smokers and nonsmokers. With smoking as an exposure variable, we identified 272 significant causal relationships between gene expression and gut microbes, among which there were 247 genes that mediate the effect of smoking on gut microbes. Pathway-based enrichment analysis showed that these genes were significantly enriched in heme metabolic pathway, which mainly mediated the changes of Bacteroides finegoldii and Lachnospiraceae bacterium 9_1_43BFAA. Additionally, by performing metabolome data analysis in the Integrated Human Microbiome Project (iHMP) database, we verified the correlation between the intermediate products of the heme metabolism pathway (porphobilinogen, bilirubin, and biliverdin) and gut microbiome. By investigating the bidirectional interaction between smoking-related host gene expression and gut microbes, this study provided evidence for the mediation of smoking on gut microbes through co-involvement or interaction of heme metabolism. By comparing the metagenome and transcriptome sequencing profiles between 34 smokers and 33 age- and gender-matched nonsmokers, we are the first to reveal causal relationships among tobacco smoking, host gene expression, and gut microbes. These findings offer insight into how smoking affects gut microbes through host gene expression and metabolism, which highlights the importance of heme metabolism in modulating the effects of smoking on gut microbiome.

Dual RNA-seq to catalogue host and parasite gene expression changes associated with virulence of T. annulata-transformed bovine leukocytes: towards identification of attenuation biomarkers

The apicomplexan parasite Theileria annulata is transmitted by Hyalomma ticks and causes an acute lymphoproliferative disease that is invariably lethal in exotic cattle breeds. The unique ability of the schizont stage of T. annulata to transform infected leukocytes to a cancer-like phenotype and the simplicity of culturing and passaging T. annulata-transformed cells in vitro have been explored for live vaccine development by attenuating the transformed cells using lengthy serial propagation in vitro. The empirical in vivo evaluation of attenuation required for each batch of long-term cultured cells is a major constraint since it is resource intensive and raises ethical issues regarding animal welfare. As yet, the molecular mechanisms underlying attenuation are not well understood. Characteristic changes in gene expression brought about by attenuation are likely to aid in the identification of novel biomarkers for attenuation. We set out to undertake a comparative transcriptome analysis of attenuated (passage 296) and virulent (passage 26) bovine leukocytes infected with a Tunisian strain of T. annulata termed Beja. RNA-seq was used to analyse gene expression profiles and the relative expression levels of selected genes were verified by real-time quantitative PCR (RT-qPCR) analysis. Among the 3538 T. annulata genes analysed, 214 were significantly differentially expressed, of which 149 genes were up-regulated and 65 down-regulated. Functional annotation of differentially expressed T. annulata genes revealed four broad categories of metabolic pathways: carbon metabolism, oxidative phosphorylation, protein processing in the endoplasmic reticulum and biosynthesis of secondary metabolites. It is interesting to note that of the top 40 genes that showed altered expression, 13 were predicted to contain a signal peptide and/or at least one transmembrane domain, suggesting possible involvement in host-parasite interaction. Of the 16,514 bovine transcripts, 284 and 277 showed up-regulated and down-regulated expression, respectively. These were assigned to functional categories relevant to cell surface, tissue morphogenesis and regulation of cell adhesion, regulation of leucocyte, lymphocyte and cell activation. The genetic alterations acquired during attenuation that we have catalogued herein, as well as the accompanying in silico functional characterization, do not only improve understanding of the attenuation process, but can also be exploited by studies aimed at identifying attenuation biomarkers across different cell lines focusing on some host and parasite genes that have been highlighted in this study, such as bovine genes (CD69, ZNF618, LPAR3, and APOL3) and parasite genes such as TA03875.

Chikungunya virus perturbs the Wnt/β-catenin signaling pathway for efficient viral infection.

Being obligate parasites, viruses use various host cell machineries in effectively replicating their genome, along with virus-encoded enzymes. In order to carry out infection and pathogenesis, viruses are known to manipulate fundamental cellular processes in cells and interfere with host gene expression. Several viruses interact with the cellular proteins involved in the Wnt/β-catenin pathway; however, reports regarding the involvement of protein components of the Wnt/β-catenin pathway in Chikungunya virus (CHIKV) infection are scarce. Additionally, there are currently no remedies or vaccines available for CHIKV. This is the first study to report that modulation of the Wnt/β-catenin pathway is crucial for effective CHIKV infection. These investigations deepen the understanding of the underlying mechanisms of CHIKV infection and offer new avenue for developing effective countermeasures to efficiently manage CHIKV infection.

Dual spatially resolved transcriptomics for human host–pathogen colocalization studies in FFPE tissue sections

Technologies to study localized host–pathogen interactions are urgently needed. Here, we present a spatial transcriptomics approach to simultaneously capture host and pathogen transcriptome-wide spatial gene expression information from human formalin-fixed paraffin-embedded (FFPE) tissue sections at a near single-cell resolution. We demonstrate this methodology in lung samples from COVID-19 patients and validate our spatial detection of SARS-CoV-2 against RNAScope and in situ sequencing. Host–pathogen colocalization analysis identified putative modulators of SARS-CoV-2 infection in human lung cells. Our approach provides new insights into host response to pathogen infection through the simultaneous, unbiased detection of two transcriptomes in FFPE samples.

CCR4-NOT differentially controls host versus virus poly(a)-tail length and regulates HCMV infection.

Unlike most RNA and DNA viruses that broadly stimulate mRNA decay and interfere with host gene expression, human cytomegalovirus (HCMV) extensively remodels the host translatome without producing an mRNA decay enzyme. By performing a targeted loss-of-function screen in primary human fibroblasts, we here identify the host CCR4-NOT deadenylase complex members CNOT1 and CNOT3 as unexpected pro-viral host factors that selectively regulate HCMV reproduction. We find that the scaffold subunit CNOT1 is specifically required for late viral gene expression and genome-wide host responses in CCR4-NOT-disrupted cells. By profiling poly(A)-tail lengths of individual HCMV and host mRNAs using nanopore direct RNA sequencing, we reveal poly(A)-tails of viral messages to be markedly longer than those of cellular mRNAs and significantly less sensitive to CCR4-NOT disruption. Our data establish that mRNA deadenylation by host CCR4-NOT is critical for productive HCMV replication and define a new mechanism whereby herpesvirus infection subverts cellular mRNA metabolism to remodel the gene expression landscape of the infected cell. Moreover, we expose an unanticipated host factor with potential to become a therapeutic anti-HCMV target.

Novel stripe rust effector boosts the transcription of a host susceptibility factor through affecting histone modification to promote infection in wheat.

Regulation of host gene expression to promote disease is a common strategy for plant pathogens. However, it remains unclear whether or not fungal pathogens manipulate host gene expression directly through secreted effectors with transcriptional activity. Here, we identified a fungal effector PstGTA1 from Puccinia striiformis f. sp. tritici (Pst), which has partial homology to the subunit of global transcriptional activator SNF2 from oyster. The transcriptional activating activity of PstGTA1 was validated in yeast, and the potential role of PstGTA1 in pathogenicity was assessed using gene silenced and overexpression transgenic wheat plants. Candidate targets regulated by PstGTA1 were screened by transcriptomic analysis, and the specific promoter region binding to PstGTA1 was further determined. PstGTA1 can be delivered to the wheat cell nucleus and contributes to the full virulence of Pst by targeting the promoter of TaSIG, a gene negatively regulating wheat immunity, and possibly activates its transcription by affecting the histone H3K4 acetylation level. Our study provides the first direct evidence for a fungal effector with transactivation activity modulating the transcription of a host specific susceptibility gene through promoter binding and histone acetylation.

The specific viral composition in triple-negative breast cancer tissue shapes the specific tumor microenvironment characterized on pathological images

Numerous studies have shown that different subtypes of breast cancer (BC) have significant differences in terms of the tumor microbiome, host gene expression, and histopathological image, whereas the biological links between these cancer-associated indicators are still unknown. Here, we performed a comprehensive analysis with 610 patients of the four subtypes of BC with matched tissue microbiota, host transcriptome, and histopathological image samples. Correlation analysis showed that the composition of intratumoral viruses shaped the tumor microenvironment (TME) of patients with BC, and the TME was further reflected in the histopathological images. Of the four subtypes, patients with triple-negative breast cancer (TNBC) had unique intratumoral viral community composition, non-cancer cell infiltration in the TME, and histopathological image characteristics. Furthermore, we detected multiple virus-cell-image association axes in TNBC, in which tumor-associated macrophages (TAMs) have clinical prognostic implication. This study provides a comprehensive map of the associations between the intratumoral virome, TME, and histopathological image of TNBC, as well as insights into disease prognosis that can be crucial for precise therapeutic intervention strategies.

Physiological and cognitive changes after treatments of cyclophosphamide, methotrexate, and fluorouracil: implications of the gut microbiome and depressive-like behavior.

Chemotherapy-induced cognitive impairment colloquially referred to as chemobrain is a poorly understood phenomenon affecting a highly variable proportion of patients with breast cancer. Here we investigate the association between anxiety and despair-like behaviors in mice treated with cyclophosphamide, methotrexate, and fluorouracil (CMF) along with host histological, proteomic, gene expression, and gut microbial responses. Forced swim and sociability tests were used to evaluate depression and despair-like behaviors. The tandem mass tag (TMT) proteomics approach was used to assess changes in the neural protein network of the amygdala and hippocampus. The composition of gut microbiota was assessed through 16S rRNA gene sequencing. Finally, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to evaluate changes in intestinal gap junction markers. We observed that CMF induced social and despair-like behavior in mice 96 hours following treatment. Proteomic analysis identified changes in various proteins related to progressive neurological disease, working memory deficit, primary anxiety disorder, and gene expression revealing increases in NMDA and AMPA receptors in both the hippocampus and the amygdala because of CMF treatment. These changes finally, we observed immediate changes in the microbial population after chemotherapy treatment, with a notable abundance of Muribaculaceae and Romboutsia which may contribute to changes seen in the gut.

SARS-CoV-2 protein NSP2 enhances microRNA-mediated translational repression.

Viruses use microRNAs (miRNAs) to impair the host antiviral response and facilitate viral infection by expressing their own miRNAs or co-opting cellular miRNAs. miRNAs inhibit translation initiation of their target mRNAs by recruiting the GIGYF2/4EHP translation repressor complex to the mRNA 5´-cap structure. We recently reported that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encoded non-structural protein 2 (NSP2) interacts with GIGYF2. This interaction is critical for blocking translation of the Ifn1-b mRNA that encodes the cytokine Interferon-ß, and thereby impairs the host antiviral response. However, it is not known whether NSP2 also affects miRNA-mediated silencing. Here, we demonstrate the pervasive augmentation of the miRNA-mediated translational repression of cellular mRNAs by NSP2. We show that NSP2 interacts with Argonaute 2, the core component of the miRNA-Induced Silencing Complex (miRISC) via GIGYF2 and enhances the translational repression mediated by natural miRNA binding sites in the 3´ UTR of cellular mRNAs. Our data reveal an additional layer of the complex mechanism by which SARS-CoV-2 and likely other coronaviruses manipulate the host gene expression program through co-opting the host miRNA-mediated silencing machinery.

A comparative transcriptome analysis of how shrimp endure and adapt to long-term symbiosis with Enterocytozoon hepatopenaei infection

Enterocytozoon hepatopenaei (EHP) is a prevalent microsporidian pathogen responsible for hepatopancreatic microsporidiosis (HPM) in Litopenaeus vannamei. This infection not only leads to slowed growth in shrimp abut aslo inflicts substantial economic losses in the global aquaculture industry. However, the molecular mechanisms by which EHP influences the host during various infection stages remain unclear. This study employed comparative transcriptomics to examine the effects of EHP infection on Litopenaeus vannamei between early and late stage of infection groups. Utilizing transcriptomic approaches, we identified differentially expressed genes (DEGs) with notable biological significance through the COG, GO, KEGG, GSEA, and Mufzz time-series methodologies. The results reveal that EHP infection considerably influences host gene expression, with marked differences between early and late infection across distinct timeframes. Key processes such as detoxification, cell apoptosis, and lipid metabolism are pivotal during host-parasite interactions. Hexokinase and phosphatidic acid phosphatase emerge as key factors enabling invasion and sustained effects. Cytochrome P450 and glucose-6-phosphate dehydrogenase could facilitate infection progression. EHP significantly impacts growth, especially through ecdysteroids and 17β-estradiol dehydrogenase. By delineating stage-specific effects, we gain insights into interaction between EHP and Litopenaeus vannamei, showing how intracellular pathogens reprogram host defenses into mechanisms enabling long-term persistence. This study provides a deeper understanding of host-pathogen dynamics, emphasizing the interplay between detoxification, metabolism, immunity, apoptosis and growth regulation over the course of long-term symbiosis.

The impact of Parkinson's disease-associated gut microbiota on the transcriptome in Drosophila.

Parkinson's disease (PD) is a common neurodegenerative disease in middle-aged and elderly people, and many studies have confirmed that the disorder of gut microbiota is involved in the pathophysiological process of PD. However, the molecular mechanism of gut microbiota in regulating the pathogenesis of PD is still lacking. In this study, to investigate the impact of PD-associated gut microbiota on host transcriptome, we established various PD models with fecal microbiota transplantation (FMT) in the model organism Drosophila followed by integrative data analysis of microbiome and transcriptome. We first constructed rotenone-induced PD models in Drosophila followed by FMT in different groups. Microbial analysis by 16S rDNA sequencing showed that gut microbiota from PD Drosophila could affect bacterial structure of normal Drosophila, and gut microbiota from normal Drosophila could affect bacterial structure of PD Drosophila. Transcriptome analysis revealed that PD-associated gut microbiota influenced expression patterns of genes enriched in neuroactive ligand-receptor interaction, lysosome, and diverse metabolic pathways. Importantly, to verify our findings, we transplanted Drosophila with fecal samples from clinical PD patients. Compared to the control, Drosophila transplanted with fecal samples from PD patients had reduced microbiota Acetobacter and Lactobacillus, and differentially expressed genes enriched in diverse metabolic pathways. In summary, our results reveal the influence of PD-associated gut microbiota on host gene expression, and this study can help better understand the link between gut microbiota and PD pathogenesis through gut-brain axis. IMPORTANCE Gut microbiota plays important roles in regulating host gene expression and physiology through complex mechanisms. Recently, it has been suggested that disorder of gut microbiota is involved in the pathophysiological process of Parkinson's disease (PD). However, the molecular mechanism of gut microbiota in regulating the pathogenesis of PD is still lacking. In this study, to investigate the impact of PD-associated gut microbiota on host transcriptome, we established various PD models with fecal microbiota transplantation in the model organism Drosophila followed by integrative data analysis of microbiome and transcriptome. We also verified our findings by transplanting Drosophila with fecal samples from clinical PD patients. Our results demonstrated that PD-associated gut microbiota can induce differentially expressed genes enriched in diverse metabolic pathways. This study can help better understand the link between gut microbiota and PD pathogenesis through gut-brain axis.

A-242 Integrating Respiratory Metagenomics and Metatranscriptomics for Diagnosis of Lung Cancer and Infection in Patients with Pulmonary Diseases

Abstract Background Advances in unbiased metagenomic next generation sequencing (mNGS) technologies have enabled the study of microbial and host genetic material (DNA and RNA) in one test. In this study, we aimed to develop machine learning-based differential diagnostic models (MLBDDMs) using the metagenomic and human transcriptomic data generated by an affordable bronchoalveolar lavage fluid (BLAF) mNGS assay and investigated their clinical utility for early differential diagnosis of lung cancer and pulmonary infection in patients with pulmonary diseases. Methods We recruited 775 patients with respiratory disease, including 160 pathologically diagnosed lung cancer and clinically diagnosed 615 infectious causes (131 tuberculosis, 172 fungal pneumonia and 312 bacterial pneumonia). An affordable mNGS assay on BALF samples collected from these patients on admission were performed. Using the generated mNGS data, we compared the differences in microbial diversity and host gene expression between lung cancer patients and pulmonary infection patients. The BLAF mNGS datasets of lung cancer group and each infection group were then randomly divided into a training dataset and a validation dataset at a ratio of approximately 3:1 for developing optimal MLBDDMs that can be used to distinguish lung cancer from various pulmonary infections. Results By comparing the BALF mNGS data of lung cancer (n = 160) and pulmonary infection (n = 615), we found that the infection group had higher microbial diversity than lung cancer group (P-value < 0.05). Respiratory colonizing microorganisms (e.g., Corynebacterium propinquum and Bacteroides uniformis) and pathogen (Mycobacterium tuberculosis and Cryptococcus neoformans) were found as differential microbes (adjusted p-value < 0.05, LDA score > 2). From BALF gene expression data, we detected 175 genes enriched in NOD-like receptor signaling pathway and chemokine signaling pathway differentially expressed between lung cancer and pulmonary infection groups (False Discovery Rate, FDR < 0.05). Cell composition analysis revealed that macrophage M1 was higher in lung infection group (P-value < 0.001), whereas mast cell activated and DCs activated were higher in lung cancer group (P-value < 0.001, P-value = 0.016). We integrated the metagenomic (microbial composition and human copy number variation) and transcriptomic data (host differentially expressed genes and cell composition) generated by the BALF mNGS assay with eleven machine learning classifiers to establish diagnosis models for distinguishing lung cancer from pulmonary infection (we named LC/PI model). The results showed that a Random Forest diagnostic model (the RF-LC/PI model) had optimal performance, with a sensitivity and specificity of 86.7% and 87.8%, respectively, in distinguishing lung cancer from pulmonary infection (area under the receiver operating characteristic curve [AUC] = 0.838 in the training dataset; AUC = 0.79 in a held-out validation dataset). Similar to the establishment of the LC/PI model, we further developed three diagnostic models for distinguishing lung cancer and tuberculosis (LC/TB model), lung cancer and fungal pneumonia (LC/FP model), and lung cancer and bacterial pneumonia (LC/BP model), respectively. The AUC of these three models were 0.91, 0.88, 0.91, respectively, showing a high differential diagnosis accuracy. Conclusions We have established MLBDDMs using BALF metagenomic and metatranscriptomic data and achieved superior accuracy for differentiating lung cancer and pulmonary infections, which could promote early diagnosis of pulmonary diseases and benefit more patients with one test.

A Transcriptomic Severity Classifier IMX-SEV-3b to Predict Mortality in Intensive Care Unit Patients with COVID-19: A Prospective Observational Pilot Study.

The prediction of disease outcomes in COVID-19 patients in the ICU is of critical importance, and the examination of host gene expressions is a promising tool. The 29-host mRNA Inflam-matix-Severity-3b (IMX-SEV-3b) classifier has been reported to predict mortality in emergency department COVID-19 patients and surgical ICU patients. The accuracy of the IMX-SEV-3b in predicting mortality in COVID-19 patients admitted to the ICU is yet unknown. Our aim was to investigate the accuracy of the IMX-SEV-3b in predicting the ICU mortality of COVID-19 patients. In addition, we assessed the predictive performance of routinely measured biomarkers and the Sequential Organ Failure Assessment (SOFA) score as well. This was a prospective observational study enrolling COVID-19 patients who received mechanical ventilation on the ICU of the Erasmus MC, the Netherlands. The IMX-SEV-3b scores were generated by amplifying 29 host response genes from blood collected in PAXgene® Blood RNA tubes. A severity score was provided, ranging from 0 to 1 for increasing disease severity. The primary outcome was the accuracy of the IMX-SEV-3b in predicting ICU mortality, and we calculated the AUROC of the IMX-SEV-3b score, the biomarkers C-reactive protein (CRP), D-dimer, ferritin, leukocyte count, interleukin-6 (IL-6), lactate dehydrogenase (LDH), neutrophil-to-lymphocyte ratio (NLR), procalcitonin (PCT) and the SOFA score. A total of 53 patients were included between 1 March and 30 April 2020, with 47 of them being included within 72 h of their admission to the ICU. Of these, 18 (34%) patients died during their ICU stay, and the IMX-SEV-3b scores were significantly higher in non-survivors compared to survivors (0.65 versus 0.57, p = 0.05). The Area Under the Receiver Operating Characteristic Curve (AUROC) for prediction of ICU mortality by the IMX-SEV-3b was 0.65 (0.48-0.82). The AUROCs of the biomarkers ranged from 0.52 to 0.66, and the SOFA score had an AUROC of 0.81 (0.69-0.93). The AUROC of the pooled biomarkers CRP, D-dimer, ferritin, leukocyte count, IL-6, LDH, NLR and PCT for prediction of ICU mortality was 0.81 (IQR 0.69-0.93). Further validation in a larger interventional trial of a point-of-care version of the IMX-SEV-3b classifier is warranted to determine its value for patient management.

Endophytes Modulate Plant Genes: Present Status and Future Perspectives.

Interactions among endophytes and plants are widespread and can vary from neutral or positive or negative. Plants are continually in a functionally dynamic state due to interactions with diverse endophytic microorganisms, which produce various metabolic substances. Through quorum sensing, these substances not only help endophytes to outcompete other host-associated pathogens or microbes but also allow them to overcome the plant immune system. Manifold interactions between endophytic microbiota cause a reflective impact on the host plant functioning and the development of 'endobiomes,' by synthesizing chemicals that fill the gap between host and endophytes. Despite the advances in the field, specific mechanisms for the endophytes' precise methods to modulate plant genome and their effects on host plantsremain poorly understood. Deeper genomic exploration can provide a locked away understanding of the competencies of endophytes and their conceivable function in host growth and health. Endophytes also can modify host metabolites, which could manipulate plants' growth, adaptation, and proliferation, and can be a more exciting and puzzling topic that must be properly investigated. The consequence of the interaction of endophytes on the host genome was analyzed as it can help unravel the gray areas of endophytes about which very little or no knowledge exists. This review discusses the recent advances in understanding the future challenges in the emerging research investigating how endosymbionts affect the host's metabolism and gene expression as an effective strategy for imparting resistance to biotic and abiotic challenges.

Cell-intrinsic and -extrinsic effects of SARS-CoV-2 RNA on pathogenesis: single-cell meta-analysis.

Single-cell RNA-seq has been used to characterize human COVID-19. To determine if preclinical models successfully mimic the cell-intrinsic and -extrinsic effects of severe disease, we conducted a meta-analysis of single-cell data across five model species. To assess whether dissemination of viral RNA in lung cells tracks pathology and results in cell-intrinsic and -extrinsic transcriptomic changes in COVID-19. We conducted a meta-analysis by analyzing six publicly available, scRNA-seq data sets. We used dual mapping (host and virus) and differential gene expression analyses to compare viral+ and viral- cell populations. We conducted a principal component analysis to identify successful models of human COVID-19. We found expression of viral RNA in many non-epithelial cell types. Fibroblasts, macrophages, and endothelial cells exhibit clear evidence of viral-intrinsic and -extrinsic effects on host gene expression. Using viral RNA expression, we found that K18-hACE2 mice most closely modeled severe human COVID-19, followed by hamsters. Ferrets and macaques are poor models of human disease due to the low presence of viral RNA. Moreover, we found that increased transcripts of certain key inflammatory genes such as IL1B, IL18, and CXCL10 are not restricted to virally infected cells, suggesting these genes are regulated in a paracrine or autocrine fashion. These data affirm widespread dissemination of viral RNA in the lung, which may be key in the pathogenesis of severe COVID-19 and demonstrate ferrets and Rhesus macaques are poor models of human COVID-19. IMPORTANCE We conducted a high-resolution meta-analysis of scRNA-seq data from humans and five animal models of COVID-19. This study reports viral RNA dissemination in several cell types in human data as well as in some of the pre-clinical models. Using this metric, the K18-hACE2 mouse model, followed by the hamster model, most closely resembled human COVID-19. We observed clear evidence of viral-intrinsic effects within cells (e.g., IRF5 expression) as well as viral-extrinsic cytokine modulation (e.g., IL1B, IL18, CXCL10). We observed proinflammatory chemokine expression in cells devoid of viral RNA expression, suggesting autocrine/paracrine interferon regulation. This report serves as a resource-synthesizing data from COVID-19 humans and animal models and suggesting improvements for relevant pre-clinical models that may aid future diagnostic and therapeutic development projects.