Identification of Two Flip-Over Genes in Grass Family as Potential Signature of C4 Photosynthesis Evolution.

In flowering plants, C4 photosynthesis is superior to C3 type in carbon fixation efficiency and adaptation to extreme environmental conditions, but the mechanisms behind the assembly of C4 machinery remain elusive. This study attempts to dissect the evolutionary divergence from C3 to C4 photosynthesis in five photosynthetic model plants from the grass family, using a combined comparative transcriptomics and deep learning technology. By examining and comparing gene expression levels in bundle sheath and mesophyll cells of five model plants, we identified 16 differentially expressed signature genes showing cell-specific expression patterns in C3 and C4 plants. Among them, two showed distinctively opposite cell-specific expression patterns in C3 vs. C4 plants (named as FOGs). The in silico physicochemical analysis of the two FOGs illustrated that C3 homologous proteins of LHCA6 had low and stable pI values of ~6, while the pI values of LHCA6 homologs increased drastically in C4 plants Setaria viridis (7), Zea mays (8), and Sorghum bicolor (over 9), suggesting this protein may have different functions in C3 and C4 plants. Interestingly, based on pairwise protein sequence/structure similarities between each homologous FOG protein, one FOG PGRL1A showed local inconsistency between sequence similarity and structure similarity. To find more examples of the evolutionary characteristics of FOG proteins, we investigated the protein sequence/structure similarities of other FOGs (transcription factors) and found that FOG proteins have diversified incompatibility between sequence and structure similarities during grass family evolution. This raised an interesting question as to whether the sequence similarity is related to structure similarity during C4 photosynthesis evolution.

A novel transcriptional signature identifies T-cell infiltration in high-risk paediatric cancer.

BACKGROUND: Molecular profiling of the tumour immune microenvironment (TIME) has enabled the rational choice of immunotherapies in some adult cancers. In contrast, the TIME of paediatric cancers is relatively unexplored. We speculated that a more refined appreciation of the TIME in childhood cancers, rather than a reliance on commonly used biomarkers such as tumour mutation burden (TMB), neoantigen load and PD-L1 expression, is an essential prerequisite for improved immunotherapies in childhood solid cancers. METHODS: We combined immunohistochemistry (IHC) with RNA sequencing and whole-genome sequencing across a diverse spectrum of high-risk paediatric cancers to develop an alternative, expression-based signature associated with CD8+ T-cell infiltration of the TIME. Furthermore, we explored transcriptional features of immune archetypes and T-cell receptor sequencing diversity, assessed the relationship between CD8+ and CD4+ abundance by IHC and deconvolution predictions and assessed the common adult biomarkers such as neoantigen load and TMB. RESULTS: A novel 15-gene immune signature, Immune Paediatric Signature Score (IPASS), was identified. Using this signature, we estimate up to 31% of high-risk cancers harbour infiltrating T-cells. In addition, we showed that PD-L1 protein expression is poorly correlated with PD-L1 RNA expression and TMB and neoantigen load are not predictive of T-cell infiltration in paediatrics. Furthermore, deconvolution algorithms are only weakly correlated with IHC measurements of T-cells. CONCLUSIONS: Our data provides new insights into the variable immune-suppressive mechanisms dampening responses in paediatric solid cancers. Effective immune-based interventions in high-risk paediatric cancer will require individualised analysis of the TIME.

Landscape of Exhausted T Cells in Tuberculosis Revealed by Single-Cell Sequencing.

Tuberculosis, a contagious bacterial infection caused by Mycobacterium tuberculosis, is a substantial global health problem, impacting millions of lives annually. Exhausted T-cell signatures are critical for predicting clinical responses to tuberculosis infection. To obtain a panoramic transcriptional profile of T cells, we performed single-cell RNA-sequencing analysis of CD4+ T and CD8+ T cells isolated from peripheral blood mononuclear cells of healthy individuals and patients with tuberculosis. We identified seven subsets in CD8+ T cells and eight subsets in CD4+ T cells and elucidated the transcriptomic landscape changes and characteristics of each subset. We further investigated the cell-to-cell relationship of each subgroup of the two cell types. Different signature genes and pathways of exhausted CD4+ and CD8+ T cells were examined. We identified 12 genes with potential associations of T-cell exhaustion after tuberculosis infection. We also identified five genes as potential exhaustion marker genes. The CD8-EX3 subcluster in CD8+ T-exhausted cells was identified as an exhaustion-specific subcluster. The identified gene module further clarified the key factors influencing CD8+ T cell exhaustion. These data provide new insights into T-cell signatures in tuberculosis-exhausted populations. IMPORTANCE Identifying the changes in immune cells in response to infection can provide a better understanding of the effects of Mycobacterium tuberculosis on the host immune system. We performed single-cell RNA-sequencing analysis of CD4+ T and CD8+ T cells isolated from peripheral blood mononuclear cells of healthy individuals and patients with tuberculosis to reveal the cellular characteristics. Different signature genes and pathways of exhausted CD4+ and CD8+ T cells were examined. These will facilitate a more comprehensive understanding of the onset and underlying mechanism of T-cell exhaustion during active Mtb infection.

Nardosinone and aurantio-obtusin, two medicine food homology natural compounds, are anti-influenza agents as indicated by transcriptome signature reversion.

BACKGROUND: Medicine food homology (MFH) refers to food that can be used as medicine, and compounds isolated from MFH materials are valuable in novel drug discovery due to their good safety. Transcriptome signature reversion (TSR) is an attractive method for discovering drugs through transcriptional reverse matching; namely, the changes in transcriptional signatures induced by compounds are matched to a certain disease. This strategy can be used to discover anti-influenza agents among MFH natural compounds. PURPOSE: MFH natural compounds with anti-influenza activities were identified through analyses of the reversal in the expression of multiple informative genes followed by in vitro evaluation of the cytopathic effect (CPE) caused by influenza infection and relative quantification of the nucleoprotein (NP) gene in viral RNA (vRNA). The combined effect of active compounds was determined through network-based separation score prediction followed by quantification of the viral hemagglutinin (HA) level. METHODS: The transcriptome profiles of 4 lung or airway cell lines infected with 7 influenza virus strains were analyzed by robust rank aggregation (RRA) to identify informative genes in the signature of influenza virus infection. The identified informative genes were then matched to a transcriptomic profile library of MFH natural compounds. The anti-influenza activities of MFH natural compounds with negative enrichment scores (ESs) were evaluated in vitro using a CPE assay and relative quantification of the NP gene in the vRNA in the supernatant and cytoplasm to identify anti-influenza agents. The effects of combinations of active compounds were analyzed using network-based calculations followed by confirmation through bioassays for quantifying the viral HA levels. RESULTS: Among the 159 MFH natural compounds, 54 compounds had negative ESs, as determined through TSR, and the anti-influenza activities of nardosinone and aurantio-obtusin were confirmed by bioassays. The half-maximal effective concentrations (EC50) of nardosinone and aurantio-obtusin were 4.3-84.4 µM and 31.9-113.6 µM, respectively. The separation score between the informative genes with expression that was negatively regulated by nardosinone and aurantio-obtusin in the human protein-protein interaction (PPI) network was calculated to be 0.10, which indicated that the two compounds potentially exert a synergistic effect, and this effect was confirmed by the finding that the combination indexes (CIs) were calculated to equal 0.86 at inhibition level of 50% and 0.44 at inhibition level of 90%. CONCLUSION: The TSR analysis and in vitro evaluation identified nardosinone and aurantio-obtusin as anti-influenza agents. Their antiviral activities were exerted by reversing the expression of multiple informative genes of the host cells. The separation analysis between the informative genes that were reversely regulated by nardosinone and aurantio-obtusin indicated that their combination may exert a synergistic effect, which was confirmed in vitro.

Exhaustion of CD39-Expressing CD8+ T Cells in Crohn's Disease Is Linked to Clinical Outcome.

BACKGROUND & AIMS: Exhaustion of CD8 T cells has been suggested to inform different clinical outcomes in Crohn's disease, but detailed analyses are lacking. This study aimed to identify the role of exhaustion on a single-cell level and identify relevant CD8 T cell populations in Crohn's disease. METHODS: Blood and intestinal tissue from 58 patients with Crohn's disease (active disease or remission) were assessed for CD8 T cell expression of exhaustion markers and their cytokine profile by highly multiplexed flow and mass cytometry. Key disease-associated subsets were sorted and analyzed by RNA sequencing. CD39 inhibition assays were performed in vitro. RESULTS: Activated CD39+ and CD39+PD-1+ CD8 T cell subsets expressing multiple exhaustion markers were enriched at low frequency in active Crohn's disease. Their cytokine production capacity was inversely linked to the Harvey-Bradshaw Index. Subset-level protein and transcriptome profiling revealed co-existence of effector and exhaustion programs in CD39+ and CD39+ PD-1+CD8 T cells, with CD39+ cells likely originating from the intestine. CD39 enzymatic activity controlled T cell cytokine production. Importantly, transcriptional exhaustion signatures were enriched in remission in CD39-expressing subsets with up-regulation of TOX. Subset-level transcriptomics revealed a CD39-related gene module that is associated with the clinical course. CONCLUSIONS: These data showed a role for the exhaustion of peripheral CD39-expressing CD8 T cell subsets in Crohn's disease. Their low frequency illustrated the utility of single-cell cytometry methods for identification of relevant immune populations. Importantly, the link of their exhaustion status to the clinical activity and their specific gene signatures have implications for exhaustion-based personalized medicine approaches.

Identification of Nifurtimox and Chrysin as Anti-Influenza Virus Agents by Clinical Transcriptome Signature Reversion.

The rapid development in the field of transcriptomics provides remarkable biomedical insights for drug discovery. In this study, a transcriptome signature reversal approach was conducted to identify the agents against influenza A virus (IAV) infection through dissecting gene expression changes in response to disease or compounds' perturbations. Two compounds, nifurtimox and chrysin, were identified by a modified Kolmogorov-Smirnov test statistic based on the transcriptional signatures from 81 IAV-infected patients and the gene expression profiles of 1309 compounds. Their activities were verified in vitro with half maximal effective concentrations (EC50s) from 9.1 to 19.1 µM against H1N1 or H3N2. It also suggested that the two compounds interfered with multiple sessions in IAV infection by reversing the expression of 28 IAV informative genes. Through network-based analysis of the 28 reversed IAV informative genes, a strong synergistic effect of the two compounds was revealed, which was confirmed in vitro. By using the transcriptome signature reversion (TSR) on clinical datasets, this study provides an efficient scheme for the discovery of drugs targeting multiple host factors regarding clinical signs and symptoms, which may also confer an opportunity for decelerating drug-resistant variant emergence.

Mechanisms and Regulation of Cellular Senescence.

Cellular senescence entails a state of an essentially irreversible proliferative arrest in which cells remain metabolically active and secrete a range of pro-inflammatory and proteolytic factors as part of the senescence-associated secretory phenotype. There are different types of senescent cells, and senescence can be induced in response to many DNA damage signals. Senescent cells accumulate in different tissues and organs where they have distinct physiological and pathological functions. Despite this diversity, all senescent cells must be able to survive in a nondividing state while protecting themselves from positive feedback loops linked to the constant activation of the DNA damage response. This capacity requires changes in core cellular programs. Understanding how different cell types can undergo extensive changes in their transcriptional programs, metabolism, heterochromatin patterns, and cellular structures to induce a common cellular state is crucial to preventing cancer development/progression and to improving health during aging. In this review, we discuss how senescent cells continuously evolve after their initial proliferative arrest and highlight the unifying features that define the senescent state.

Transcriptomic Correlates of Immunologic Activation in Head and Neck and Cervical Cancer.

Targeting the immune system has emerged as an effective therapeutic strategy for the treatment of various tumor types, including Head and Neck Squamous Cell Carcinoma (HNSCC) and Non-small-Cell Lung Cancer (NSCLC), and checkpoint inhibitors have shown to improve patient survival in these tumor types. Unfortunately, not all cancers respond to these agents, making it necessary to identify responsive tumors. Several biomarkers of response have been described and clinically tested. As of yet what seems to be clear is that a pre-activation state of the immune system is necessary for these agents to be efficient. In this study, using established transcriptomic signatures, we identified a group of gene combination associated with favorable outcome in HNSCC linked to a higher presence of immune effector cells. CD2, CD3D, CD3E, and CXCR6 combined gene expression is associated with improved outcome of HNSCC patients and an increase of infiltrating immune effector cells. This new signature also identifies a subset of cervical squamous cell carcinoma (CSCC) patients with favorable prognosis, who show an increased presence of immune effector cells in the tumor, which outcome shows similarities with the HP-positive HNSCC cohort of patients. In addition, CD2, CD3D, CD3E, and CXCR6 signature is able to predict the best favorable prognosis in terms of overall survival of CSSC patients. Of note, these findings were not reproduced in other squamous cell carcinomas like esophageal SCC or lung SCC. Prospective confirmatory studies should be employed to validate these findings.

[Identification of differentially expressed genes between lung adenocarcinoma and squamous cell carcinoma using transcriber signature analysis].

OBJECTIVE: To analyze the differentially expressed genes (DEGs) between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) with bioinformatics analysis and search for potential biomarkers for clinical diagnosis of nonsmall cell lung cancer (NSCLC). METHODS: The gene expression profiling datasets of LUAD and LUSC were acquired. The transcriptome differences between LUAD and LUSC were identified using R language processing and t-test analysis. The differential expressions of the genes were shown by Venn diagram. The DEGs identified by GEO2R were analyzed with DAVID and Ingenuity Pathway Analysis (IPA) to identify the signaling pathways and biomarkers that could be used for differential diagnosis of LUAD and LUSC. The TCGA data and the biomarker expression data from clinical lung cancer samples were used to verify the differential expressions of the Osteoarthritis pathway and LXR/RXR between LUAD and LUSC. We further examined the differential expressions of miR-181 and its two target genes, WNT5A and MBD2, in 23 clinical specimens of lung squamous cell carcinoma and the paired adjacent tissues. RESULTS: GEO data analysis identified 851 DEGs (including 276 up-regulated and 575 down-regulated genes) in LUAD and 885 DEGs (including 406 up-regulated and 479 down-regulated genes) in LUSC. DAVID and IPA analysis revealed that leukocyte migration and inflammatory responses were more abundant in LUAD than in LUSC. Osteoarthritis pathway was inhibited in LUAD and activated in LUSC. IPA analysis showed that transcription factors (GATA4, RELA, YBX1, TP63 and MBD2), cytokines (WNT5A and IL1A) and microRNAs (miR-34a, miR-181b and miR-15a) differed significantly between LUAD and LUSC. miR-34a with IL-1A, miR-15a with YBX1, and miR-181b with WNT5A and MBD2 could serve as the paired microRNA and mRNA targets for differential diagnosis of NSCLC subtypes. Analysis of the clinical samples showed an increased expression of miR-181b-5p and the down-regulation of WNT5A, which could be used as molecular markers for the diagnosis of LUSC. CONCLUSIONS: Through transcriptome analysis, we identified candidate genes, paired microRNAs and pathways for differentiating LUAD and LUSC, and they can provide novel differential diagnosis and therapeutic strategies for LUAD and LUSC.

Identification of differentially expressed genes between lung adenocarcinoma and squamous cell carcinoma using transcriber signature analysis / 南方医科大学学报

OBJECTIVE@#To analyze the differentially expressed genes (DEGs) between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) with bioinformatics analysis and search for potential biomarkers for clinical diagnosis of nonsmall cell lung cancer (NSCLC).@*METHODS@#The gene expression profiling datasets of LUAD and LUSC were acquired. The transcriptome differences between LUAD and LUSC were identified using R language processing and t-test analysis. The differential expressions of the genes were shown by Venn diagram. The DEGs identified by GEO2R were analyzed with DAVID and Ingenuity Pathway Analysis (IPA) to identify the signaling pathways and biomarkers that could be used for differential diagnosis of LUAD and LUSC. The TCGA data and the biomarker expression data from clinical lung cancer samples were used to verify the differential expressions of the Osteoarthritis pathway and LXR/RXR between LUAD and LUSC. We further examined the differential expressions of miR-181 and its two target genes, and , in 23 clinical specimens of lung squamous cell carcinoma and the paired adjacent tissues.@*RESULTS@#GEO data analysis identified 851 DEGs (including 276 up-regulated and 575 down-regulated genes) in LUAD and 885 DEGs (including 406 up-regulated and 479 down-regulated genes) in LUSC. DAVID and IPA analysis revealed that leukocyte migration and inflammatory responses were more abundant in LUAD than in LUSC. Osteoarthritis pathway was inhibited in LUAD and activated in LUSC. IPA analysis showed that transcription factors (GATA4, RELA, YBX1, TP63 and MBD2), cytokines (WNT5A and IL1A) and microRNAs (miR-34a, miR-181b and miR-15a) differed significantly between LUAD and LUSC. miR-34a with IL-1A, miR-15a with YBX1, and miR-181b with WNT5A and MBD2 could serve as the paired microRNA and mRNA targets for differential diagnosis of NSCLC subtypes. Analysis of the clinical samples showed an increased expression of miR-181b-5p and the down-regulation of WNT5A, which could be used as molecular markers for the diagnosis of LUSC.@*CONCLUSIONS@#Through transcriptome analysis, we identified candidate genes, paired microRNAs and pathways for differentiating LUAD and LUSC, and they can provide novel differential diagnosis and therapeutic strategies for LUAD and LUSC.