Set Of Marker Genes Research Articles

Phylogenetic Signal, Congruence, and Uncertainty across Bacteria and Archaea.

Reconstruction of the Tree of Life is a central goal in biology. Although numerous novel phyla of bacteria and archaea have recently been discovered, inconsistent phylogenetic relationships are routinely reported, and many inter-phylum and inter-domain evolutionary relationships remain unclear. Here, we benchmark different marker genes often used in constructing multidomain phylogenetic trees of bacteria and archaea and present a set of marker genes that perform best for multidomain trees constructed from concatenated alignments. We use recently-developed Tree Certainty metrics to assess the confidence of our results and to obviate the complications of traditional bootstrap-based metrics. Given the vastly disparate number of genomes available for different phyla of bacteria and archaea, we also assessed the impact of taxon sampling on multidomain tree construction. Our results demonstrate that biases between the representation of different taxonomic groups can dramatically impact the topology of resulting trees. Inspection of our highest-quality tree supports the division of most bacteria into Terrabacteria and Gracilicutes, with Thermatogota and Synergistota branching earlier from these superphyla. This tree also supports the inclusion of the Patescibacteria within the Terrabacteria as a sister group to the Chloroflexota instead of as a basal-branching lineage. For the Archaea, our tree supports three monophyletic lineages (DPANN, Euryarchaeota, and TACK/Asgard), although we note the basal placement of the DPANN may still represent an artifact caused by biased sequence composition. Our findings provide a robust and standardized framework for multidomain phylogenetic reconstruction that can be used to evaluate inter-phylum relationships and assess uncertainty in conflicting topologies of the Tree of Life.

Oral Microbiota Composition and Function Changes During Chronic Erythematous Candidiasis.

Oral microbiota is constantly changing with the host state, whereas the oral microbiome of chronic erythematous candidiasis remains poorly understood. The aim of this study was to compare oral microbial signatures and functional profiling between chronic erythematous candidiasis and healthy subjects. Using shotgun metagenomic sequencing, we analyzed the microbiome in 12 chronic erythematous candidiasis, 12 healthy subjects, and 2 chronic erythematous candidiasis cured by antifungal therapy. We found that the salivary microbiota of chronic erythematous candidiasis was significantly different from that of healthy subjects. Among them, Rothia mucilaginosa and Streptococcus mitis were the most abundant disease-enriched species (Mann-Whitney U-test, P < 0.05). In addition, co-occurrence network analysis showed that C. albicans formed densely connected modules with oral bacterial species and was mainly positive connected to Streptococcus species. Furthermore, we investigated the functional potentials of the microbiome and identified a set of microbial marker genes associated with chronic erythematous candidiasis. Some of these genes enriching in chronic erythematous candidiasis are involved in eukaryotic ribosome, putative glutamine transport system, and cytochrome bc1 complex respiratory unit. Altogether, this study revealed the changes of oral microbial composition, the co-occurrence between C. albicans and oral bacteria, as well as the changes of microbial marker genes during chronic erythematous candidiasis, which provides evidence of oral microbiome as a target for the treatment and prevention of chronic erythematous candidiasis.

A targeted transcriptomics approach for the determination of mixture effects of pesticides

While real-life exposure occurs to complex chemical mixtures, toxicological risk assessment mostly focuses on individual compounds. There is an increasing demand for in vitro tools and strategies for mixture toxicity analysis. Based on a previously established set of hepatotoxicity marker genes, we analyzed mixture effects of non-cytotoxic concentrations of different pesticides in exposure-relevant binary mixtures in human HepaRG hepatocarcinoma cells using targeted transcriptomics. An approach for mixture analysis at the level of a complex endpoint such as a transcript pattern is presented, including mixture design based on relative transcriptomic potencies and similarities. From a mechanistic point of view, goal of the study was to evaluate combinations of chemicals with varying degrees of similarity in order to determine whether differences in mechanisms of action lead to different mixtures effects. Using a model deviation ratio-based approach for assessing mixture effects, it was revealed that most data points are consistent with the assumption of dose addition. A tendency for synergistic effects was only observed at high concentrations of some combinations of the test compounds azoxystrobin, cyproconazole, difenoconazole, propiconazole and thiacloprid, which may not be representative of human real-life exposure. In summary, the findings of our study suggest that, for the pesticide mixtures investigated, risk assessment based on the general assumption of dose addition can be considered sufficiently protective for consumers. The way of data analysis presented in this paper can pave the way for a more comprehensive use of multi-gene expression data in experimental studies related to mixture toxicity.

Plant PhysioSpace: a robust tool to compare stress response across plant species.

Generalization of transcriptomics results can be achieved by comparison across experiments. This generalization is based on integration of interrelated transcriptomics studies into a compendium. Such a focus on the bigger picture enables both characterizations of the fate of an organism and distinction between generic and specific responses. Numerous methods for analyzing transcriptomics datasets exist. Yet, most of these methods focus on gene-wise dimension reduction to obtain marker genes and gene sets for, for example, pathway analysis. Relying only on isolated biological modules might result in missing important confounders and relevant contexts. We developed a method called Plant PhysioSpace, which enables researchers to compute experimental conditions across species and platforms without a priori reducing the reference information to specific gene sets. Plant PhysioSpace extracts physiologically relevant signatures from a reference dataset (i.e. a collection of public datasets) by integrating and transforming heterogeneous reference gene expression data into a set of physiology-specific patterns. New experimental data can be mapped to these patterns, resulting in similarity scores between the acquired data and the extracted compendium. Because of its robustness against platform bias and noise, Plant PhysioSpace can function as an inter-species or cross-platform similarity measure. We have demonstrated its success in translating stress responses between different species and platforms, including single-cell technologies. We have also implemented two R packages, one software and one data package, and a Shiny web application to facilitate access to our method and precomputed models.

Agrobacterium tumefaciens-Mediated Nuclear Transformation of a Biotechnologically Important Microalga-Euglena gracilis.

Euglena gracilis (E. gracilis) is an attractive organism due to its evolutionary history and substantial potential to produce biochemicals of commercial importance. This study describes the establishment of an optimized protocol for the genetic transformation of E. gracilis mediated by Agrobacterium (A. tumefaciens). E. gracilis was found to be highly sensitive to hygromycin and zeocin, thus offering a set of resistance marker genes for the selection of transformants. A. tumefaciens-mediated transformation (ATMT) yielded hygromycin-resistant cells. However, hygromycin-resistant cells hosting the gus gene (encoding β-glucuronidase (GUS)) were found to be GUS-negative, indicating that the gus gene had explicitly been silenced. To circumvent transgene silencing, GUS was expressed from the nuclear genome as transcriptional fusions with the hygromycin resistance gene (hptII) (encoding hygromycin phosphotransferase II) with the foot and mouth disease virus (FMDV)-derived 2A self-cleaving sequence placed between the coding sequences. ATMT of Euglena with the hptII-2A–gus gene yielded hygromycin-resistant, GUS-positive cells. The transformation was verified by PCR amplification of the T-DNA region genes, determination of GUS activity, and indirect immunofluorescence assays. Cocultivation factors optimization revealed that a higher number of transformants was obtained when A. tumefaciens LBA4404 (A600 = 1.0) and E. gracilis (A750 = 2.0) cultures were cocultured for 48 h at 19 °C in an organic medium (pH 6.5) containing 50 µM acetosyringone. Transformation efficiency of 8.26 ± 4.9% was achieved under the optimized cocultivation parameters. The molecular toolkits and method presented here can be used to bioengineer E. gracilis for producing high-value products and fundamental studies.

Distinctive Molecular typing of 16S rRNA of Bacillus species isolated from farm settlement.

Distinctive Molecular typing of 16S rRNA of Bacillus species isolated from farm settlement.

Integrated Single-Cell Atlas of Endothelial Cells of the Human Lung.

Cellular diversity of the lung endothelium has not been systematically characterized in humans. We provide a reference atlas of human lung endothelial cells (ECs) to facilitate a better understanding of the phenotypic diversity and composition of cells comprising the lung endothelium. We reprocessed human control single-cell RNA sequencing (scRNAseq) data from 6 datasets. EC populations were characterized through iterative clustering with subsequent differential expression analysis. Marker genes were validated by fluorescent microscopy and in situ hybridization. scRNAseq of primary lung ECs cultured in vitro was performed. The signaling network between different lung cell types was studied. For cross-species analysis or disease relevance, we applied the same methods to scRNAseq data obtained from mouse lungs or from human lungs with pulmonary hypertension. Six lung scRNAseq datasets were reanalyzed and annotated to identify >15 000 vascular EC cells from 73 individuals. Differential expression analysis of EC revealed signatures corresponding to endothelial lineage, including panendothelial, panvascular, and subpopulation-specific marker gene sets. Beyond the broad cellular categories of lymphatic, capillary, arterial, and venous ECs, we found previously indistinguishable subpopulations; among venous EC, we identified 2 previously indistinguishable populations: pulmonary-venous ECs (COL15A1neg) localized to the lung parenchyma and systemic-venous ECs (COL15A1pos) localized to the airways and the visceral pleura; among capillary ECs, we confirmed their subclassification into recently discovered aerocytes characterized by EDNRB, SOSTDC1, and TBX2 and general capillary EC. We confirmed that all 6 endothelial cell types, including the systemic-venous ECs and aerocytes, are present in mice and identified endothelial marker genes conserved in humans and mice. Ligand-receptor connectome analysis revealed important homeostatic crosstalk of EC with other lung resident cell types. scRNAseq of commercially available primary lung ECs demonstrated a loss of their native lung phenotype in culture. scRNAseq revealed that endothelial diversity is maintained in pulmonary hypertension. Our article is accompanied by an online data mining tool (www.LungEndothelialCellAtlas.com). Our integrated analysis provides a comprehensive and well-crafted reference atlas of ECs in the normal lung and confirms and describes in detail previously unrecognized endothelial populations across a large number of humans and mice.

Prognostic and Immunological Role of mRNA ac4C Regulator NAT10 in Pan-Cancer: New Territoryfor Cancer Research?

BackgroundNAT10 (also known as human N-acetyltransferase-like protein) is a critical gene that regulates N4-acetylcytidine formation in RNA, similar to the multiple regulators of N6-methyladenosine. However, the underlying functions and mechanisms of NAT10 in tumor progression and immunology are unclear.MethodsIn this study, we systematically analyzed the pan-cancer expression and correlations of NAT10, using databases including Oncomine, PrognoScan, GEPIA2, and Kaplan-Meier Plotter. The potential correlations of NAT10 with immune infiltration stages and gene marker sets were analyzed using the Tumor Immune Estimation Resource and GEPIA2.ResultsCompared with normal tissues, NAT10 showed higher expression in most cancers based on combined data from TCGA and GTEx. In different datasets, high NAT10 expression was significantly correlated with poor prognosis in adrenocortical carcinoma, head and neck squamous cell carcinoma, liver hepatocellular carcinoma, kidney renal papillary cell carcinoma, and pheochromocytoma and paraganglioma. Moreover, there were significant positive correlations between NAT10 expression and immune infiltrates, including B cells, CD8+ T cells, CD4+ T cells, neutrophils, macrophages, dendritic cells, endothelial cells, and fibroblasts in LIHC. NAT10 expression showed strong correlations with diverse immune marker gene sets in LIHC.ConclusionNAT10 expression affects the prognosis of pan-cancer patients and is significantly correlated with tumor immune infiltration. Furthermore, it represents a potential target for cancer therapy.

PlantscRNAdb: A database for plant single-cell RNA analysis

PlantscRNAdb: A database for plant single-cell RNA analysis

Identification, Validation, and Utilization of Immune Cells in Pancreatic Ductal Adenocarcinoma Based on Marker Genes.

The immune response affects tumor biological behavior and progression. The specific immune characteristics of pancreatic ductal adenocarcinoma (PDAC) can determine the metastatic abilities of cancerous cells and the survival of patients. Therefore, it is important to characterize the specific immune landscape in PDAC tissue samples, and the effect of various types of therapy on that immune composition. Previously, a set of marker genes was identified to assess the immune cell composition in different types of cancer tissue samples. However, gene expression and subtypes of immune cells may vary across different types of cancers. The aim of this study was to provide a method to identify immune cells specifically in PDAC tissue samples. The method is based on defining a specific set of marker genes expressed by various immune cells in PDAC samples. A total of 90 marker genes were selected and tested for immune cell type-specific definition in PDAC; including 43 previously used, and 47 newly selected marker genes. The immune cell-type specificity was checked mathematically by calculating the “pairwise similarity” for all candidate genes using the PDAC RNA-sequenced dataset available at The Cancer Genome Atlas. A set of 55 marker genes that identify 22 different immune cell types for PDAC was created. To validate the method and the set of marker genes, an independent mRNA expression dataset of 24 samples of PDAC patients who received various types of (neo)adjuvant treatments was used. The results showed that by applying our method we were able to identify PDAC specific marker genes to characterize immune cell infiltration in tissue samples. The method we described enabled identifying different subtypes of immune cells that were affected by various types of therapy in PDAC patients. In addition, our method can be easily adapted and applied to identify the specific immune landscape in various types of tissue samples.

The Analysis of Live-Attenuated Piscirickettsia salmonis Vaccine Reveals the Short-Term Upregulation of Innate and Adaptive Immune Genes in Atlantic Salmon (Salmo salar): An In Situ Open-Sea Cages Study.

Piscirickettsia salmonis, the etiological agent of the Salmon Rickettsial Septicemia (SRS), is one the most serious health problems for the Chilean salmon industry. Typical antimicrobial strategies used against P. salmonis include antibiotics and vaccines, but these applications have largely failed. A few years ago, the first attenuated-live vaccine against SRS (ALPHA JECT LiVac® SRS vaccine) was released to the market. However, there is no data about the agents involved in the activation of the immune response induced under field conditions. Therefore, in this study we evaluated the expression profile of a set of gene markers related to innate and adaptive immunity in the context of a cellular response in Atlantic salmon (Salmo salar) reared under productive farm conditions and immunized with a live-attenuated vaccine against P. salmonis. We analyzed the expression at zero, 5-, 15- and 45-days post-vaccination (dpv). Our results reveal that the administration of the attenuated live SRS LiVac vaccine induces a short-term upregulation of the cellular-mediated immune response at 5 dpv modulated by the upregulation of ifnα, ifnγ, and the cd4 and cd8α T cell surface markers. In addition, we also registered the upregulation of il-10 and tgfβ. Altogether, the results suggest that a balanced activation of the immune response took place only at early times post-vaccination (5 dpv). The scope of this short-term upregulation of the cellular-mediated immune response against a natural outbreak in fish subjected to productive farm conditions deserves further research.

BMPR2 expression level is correlated with low immune infiltration and predicts metastasis and poor survival in osteosarcoma.

Osteosarcoma is the most common malignant bone tumor in adolescents and young adults, and identifying biomarkers for prognosis and therapy is necessary. Bone morphogenetic protein receptor 2 (BMPR2) is involved in various cellular functions, including cell adhesion, proliferation and invasion, inflammation, apoptosis and metastatic spread. However, the correlation between BMPR2 expression levels and prognosis and tumor-infiltrating immune cells in osteosarcoma is not well understood. In the present study, the expression level of BMPR2 was investigated using the Oncomine and R2 databases. The association between the expression level of BMPR2 and the clinical prognosis of patients with cancer was analyzed using the R2 database. The relationship between the expression level of BMPR2 and immune cell infiltration in the stroma of osteosarcoma was assessed using the Tumor Immune Estimation Resource (TIMER) and CIBERSORT. The correlations between BMPR2 expression level and infiltrated immune cell gene marker sets in osteosarcoma were validated in the TIMER and R2 databases. Analysis of a cohort of patients with osteosarcoma revealed that BMPR2 expression was significantly higher in osteosarcoma compared with in normal tissue and was correlated with poor prognosis. M0 macrophages, M2 macrophages, resting mast, γ δ T and CD8+ T cells were the top five immune cells with the highest degrees of infiltration in osteosarcoma. In addition, BMPR2 expression level showed a significant negative correlation with the gene markers of CD8+ T cells, monocytes and M2 macrophages. Low levels of infiltrating CD8+ T cells, monocytes or M2 macrophages in osteosarcoma was significantly associated with poor survival. These data suggested that CD8+ T cells, monocytes and M2 macrophages play significant roles in the establishment of the immune microenvironment of osteosarcoma. High BMPR2 expression was associated with poor prognosis and low infiltration of CD8+ T cells, monocytes and M2 macrophages in osteosarcoma. Hence, BMPR2 can be considered a biomarker of the immune infiltration, metastasis and prognosis of osteosarcoma.

SLC7A7 is a prognostic biomarker correlated with immune infiltrates in non-small cell lung cancer

BackgroundSLC7A7 (solute carrier family 7, amino acid transporter light chain, y + L system, member 7) is a critical gene in the regulation of cationic amino acid transport. However, the relationships between SLC7A7 and prognosis and tumor-infiltrating lymphocytes in different cancers remain unclear.MethodsSLC7A7 expression was analyzed using the Oncomine database and Tumor Immune Estimation Resource (TIMER) site. The enrichment of the GO (Gene Oncology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways was conducted by DAVID. We evaluated the influence of SLC7A7 on clinical prognosis using the PrognoScan database. The functional state of SLC7A7 in various types of cancers was analyzed by CancerSEA. The relationships between SLC7A7 and cancer immune infiltrates was investigated by TIMER. Furthermore, correlations between SLC7A7 expression and gene marker sets of immune infiltrates were analyzed by TIMER and Gene Expression Profiling Interactive Analysis (GEPIA). The expression of SLC7A7 was verified by GEO database and immunohistochemistry.ResultsA lung cancer cohort study (GSE31210) showed that high SLC7A7 expression was associated with poor overall survival (OS) and relapse-free survival (RFS). In addition, SLC7A7 had a significant impact on the prognosis of diverse cancers. SLC7A7 expression was positively correlated with infiltrating levels of CD4 + and CD8 + T cells, macrophages, neutrophils and dendritic cells (DCs) in non-small cell lung cancer (NSCLC). SLC7A7 expression was also strongly correlated with various immune marker sets in NSCLC.ConclusionsThese results indicated a role for SLC7A7 in infiltration of CD8 + T cells, CD4 + T cells, tumor-associated macrophages (TAMs), neutrophils and DCs in multiple cancers, and regulation of T cell exhaustion and Tregs in NSCLC. These findings suggest that SLC7A7 could be served as a biomarker for prognosis and immune infiltration in NSCLC.

Comprehensive analysis of macrophage-related multigene signature in the tumor microenvironment of head and neck squamous cancer.

Macrophages are among the most abundant cells of the tumor microenvironment in head and neck squamous cancer (HNSC). Although the marker gene sets of macrophages have been found, the mechanism by which they affect macrophages and whether they further predict the clinical outcome is unclear. In this study, a univariate COX analysis and a random forest algorithm were used to construct a prognostic model. Differential expression of the key gene, methylation status, function, and signaling pathways were further analyzed. We cross-analyzed multiple databases to detect the relationship between the most critical gene and the infiltration of multiple immune cells, as well as its impact on the prognosis of pan-cancer. FANCE is recognized as hub gene by different algorithms. It was overexpressed in HNSC, and high expression was predictive of better prognosis. It might promote apoptosis through the Wnt/β-catenin pathway. The expression of FANCE is inversely proportional to the infiltration of CD4 + T cells and their subsets, tumor-associated macrophages (TAMs), M2 macrophages, but positively co-expressed with M1 macrophages. In summary, FANCE was identified as the hub gene from the macrophage marker gene set, and it may improve the prognosis of HNSC patients by inhibiting lymphocytes and tumor-associated macrophages infiltration.

Chitosan induces delayed grapevine defense mechanisms and protects grapevine against Botrytis cinerea

In the present study, a commercial chitosan soluble in acid solution and obtained from shrimp shell waste, with a molecular weight of 173 kDa and a degree of acetylation of 17%, named as chitosan (173/17), was investigated. Chitosan is a well-known biopolymer whose antimicrobial properties are highly influenced by the molecular weight, degree of acetylation as well as the preparation and derivatization methods used. Chitosan (173/17) was applied on grapevine leaves before Botrytis cinerea inoculation to verify its effectiveness as a preventive treatment against the fungal infection. The expression of a set of defense marker genes, as well as accumulation of stilbene phytoalexins, was investigated. Thanks to its fungistatic and filmogenic properties, chitosan (173/17) protected grapevine leaves against B. cinerea. Moreover, it induced grapevine defense response: three days after the treatment an induction of the jasmonic acid and ethylene-mediated response, a repression of the salicylic acid-mediated signaling, and a transient accumulation of trans-resveratrol were registered. Our data indicate that chitosan (173/17), when used in preventive application, is able to protect grapevine against B. cinerea infection. The effectiveness of chitosan (173/17) as a natural ecofriendly product for the control of B. cinerea on grapevine was demonstrated.

Examination of the usability of leaf chlorophyll content and gene expression analyses as nitrogen status biomarkers in Sorghum bicolor

Sorghum [Sorghum bicolor (L.) Moench] has been receiving attention as a feedstock for biomass energy. Since nitrogen (N) significantly affects the plant biomass production, diagnosing the N status of sorghum during its growth would be significant. Therefore, in this study, we analyzed the changes in several physiological parameters of sorghum in response to N limitation, with the aim of identifying candidates of N status biomarkers in this species. Parameters responding early and sensitively to N deficiency were searched in hydroponically cultured seedlings, and their applicability to field conditions was examined. We found that the leaf chlorophyll content measured as a soil-plant analysis development (SPAD) value was promising as a candidate N status biomarker, as it showed responses consistent with N regimes in field conditions in multiple genotypes. A gene expression analysis was capable of detecting N deficiency sensitively at an early stage, although its application to practical situations requires further investigation to identify a suitable sets of marker genes.

Clinicopathological Significances of Cancer Stem Cell-Associated HHEX Expression in Breast Cancer.

Aberrant expression of the transcription factor hematopoietic ally expressed homeobox/proline-rich homeodomain (HHEX/PRH) is implicated in numerous cancers. However, the association of HHEX with breast cancer (BC) remains unclear. In this study, HHEX mRNA and protein expression were analyzed using the Oncomine, UALCAN, GEPIA, TCGAportal, and HPA databases. We evaluated the effect of HHEX on clinicopathological parameters using Kaplan–Meier plotter, OncoLnc, TCGAportal, PROGgeneV2, and BC-GenExMiner. Western blotting was performed to compare the level of HHEX in breast samples of Tientsin Albino 2 mice, human breast precancerous lesions, benign breast tumors, and BC. The correlation between HHEX and cancer stem cells was investigated using the GEO (GSE52327 and GSE94865) and GEPIA datasets. Networks between HHEX and survival-related gene marker sets and microRNAs were analyzed using GEPIA, StarBase, and Cytoscape. Results of this study showed that HHEX expression in BC was significantly lower than those in breast precancerous lesions and benign breast tumors at both mRNA and protein levels. BC patients with lower HHEX expression had significantly worse overall survival and disease-free survival. Moreover, HHEX significantly affected the clinicopathology of BC. Specifically, low HHEX expression was correlated with the following groups of patients: age ≤51 years, ER-negative or PR-negative patients, HER-2 positive, triple-negative breast cancer, and basal-like BC. Immunohistochemical analysis of the breast samples showed significant differences of HHEX staining index (P < 0.001) among the three groups. To further investigate the mechanism, we determined the intersection of differentially expressed genes related to BC stem cells and those genes after HHEX expression was altered. This led to the identification of four potentially regulated genes-CXL12, BLNK, PAG1, and LPXN. Using StarBase and km-plotter, the negative regulation of HHEX expression and survival trends, including miR-130b, miR-30e, and miR-301b were joined into miRNA-HHEX-mRNA potential regulatory network. The abilities of proliferation, migration and invasion increased in MDA-MB-231 and BT-549 breast cancer cell lines after HHEX down expression and decreased after HHEX overexpression compared them in the control cells. In conclusion, these data suggest that HHEX expression is downregulated in BC and HHEX may regulate the development of BC through the stem cell-related genes.

PStrain: an iterative microbial strains profiling algorithm for shotgun metagenomic sequencing data.

The microbial community plays an essential role in human diseases and physiological activities. The functions of microbes can differ due to strain-level differences in the genome sequences. Shotgun metagenomic sequencing allows us to profile the strains in microbial communities practically. However, current methods are underdeveloped due to the highly similar sequences among strains. We observe that strains genotypes at the same single nucleotide variant (SNV) locus can be speculated by the genotype frequencies. Also, the variants in different loci covered by the same reads can provide evidence that they reside on the same strain. These insights inspire us to design PStrain, an optimization method that utilizes genotype frequencies and the reads which cover multiple SNV loci to profile strains iteratively based on SNVs in a set of MetaPhlAn2 marker genes. Compared to the state-of-art methods, PStrain, on average, improved the performance of inferring strains abundances and genotypes by 87.75% and 59.45%, respectively. We have applied the PStrain package to the dataset with two cohorts of colorectal cancer (CRC) and found that the sequences of Bacteroides coprocola strains are significantly different between CRC and control samples, which is the first time to report the potential role of B.coprocola in the gut microbiota of CRC. https://github.com/wshuai294/PStrain. Supplementary data are available at Bioinformatics online.

FCGR1A Serves as a Novel Biomarker and Correlates With Immune Infiltration in Four Cancer Types.

BackgroundFCGR1A encodes a protein that plays an important role in the immune response. The prognostic impact and immune infiltration of FCGR1A in heterogeneous cancers remain unclear.MethodsDifferential expression of FCGR1A between tumor and normal tissues and the discrepancies in overall survival (OS) among diverse cancer types were performed by Gene Expression Profiling Interactive Analysis. The correlation between FCGR1A and immune cells or gene marker sets of immune infiltrates was analyzed via Tumor Immune Estimation Resource (TIMER). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and protein-to-protein interaction (PPI) network were used to explore the function and related genes of FCGR1A. The relationships among these genes were further analyzed by TIMER.ResultsFCGR1A is highly expressed in various cancer types. FCGR1A was significantly correlated with the OS of cervical and endocervical cancer (CESC), cholangiocarcinoma (CHOL), kidney renal clear cell carcinoma (KIRC), and skin cutaneous melanoma (SKCM) (P < 0.05). High expression of FCGR1A meant a better prognosis besides KIRC. FCGR1A showed significant differences at different stages of KIRC and SKCM (P < 0.05). Furthermore, FCGR1A was notably associated with infiltrating levels of CD4+ T cells, CD8+ T cells, B cells, macrophages, neutrophils, and dendritic cells in the four cancers (P < 0.05). FCGR1A also showed close relevance with different immune gene markers. The copy number variation of FCGR1A significantly influenced the abundance of immune infiltration in KIRC and SKCM. GO, KEGG analysis, and PPI network analysis revealed that FCGR1A is involved in many pathophysiological processes and was most related to FCGR3A. And this gene indicated highly significant positive correlations with FCGR1A in four cancers.ConclusionFCGR1A may be a potential prognostic biomarker and related to immune infiltration levels in diverse cancers, especially in CESC, CHOL, KIRC, and SKCM. Besides, FCGR1A may be involved in the activation, regulation, or induction of immune cells and diverse physiological and pathological processes.

Gene expression signatures identify paediatric patients with multiple organ dysfunction who require advanced life support in the intensive care unit.

BackgroundMultiple organ dysfunction syndrome (MODS) occurs in the setting of a variety of pathologies including infection and trauma. Some patients decompensate and require Veno-Arterial extra corporeal membrane oxygenation (ECMO) as a palliating manoeuvre for recovery of cardiopulmonary function. The molecular mechanisms driving progression from MODS to cardiopulmonary collapse remain incompletely understood, and no biomarkers have been defined to identify those MODS patients at highest risk for progression to requiring ECMO support.MethodsWhole blood RNA-seq profiling was performed for 23 MODS patients at three time points during their ICU stay (at diagnosis of MODS, 72 hours after, and 8 days later), as well as four healthy controls undergoing routine sedation. Of the 23 MODS patients, six required ECMO support (ECMO patients). The predictive power of conventional demographic and clinical features was quantified for differentiating the MODS and ECMO patients. We then compared the performance of markers derived from transcriptomic profiling including [1] transcriptomically imputed leukocyte subtype distribution, [2] relevant published gene signatures and [3] a novel differential gene expression signature computed from our data set. The predictive power of our novel gene expression signature was then validated using independently published datasets.FindingNone of the five demographic characteristics and 14 clinical features, including The Paediatric Logistic Organ Dysfunction (PELOD) score, could predict deterioration of MODS to ECMO at baseline. From previously published sepsis signatures, only the signatures positively associated with patient's mortality could differentiate ECMO patients from MODS patients, when applied to our transcriptomic dataset (P-value ranges from 0.01 to 0.04, Student's test). Deconvolution of bulk RNA-Seq samples suggested that lower neutrophil counts were associated with increased risk of progression from MODS to ECMO (P-value = 0.03, logistic regression, OR=2.82 [95% CI 0.63 - 12.45]). A total of 30 genes were differentially expressed between ECMO and MODS patients at baseline (log2 fold change ≥ 1 or ≤ -1 with false discovery rate ≤ 0.01). These genes are involved in protein maintenance and epigenetic-related processes. Further univariate analysis of these 30 genes suggested a signature of seven DE genes associated with ECMO (OR > 3.0, P-value ≤ 0.05, logistic regression). Notably, this contains a set of histone marker genes, including H1F0, HIST2H3C, HIST1H2AI, HIST1H4, HIST1H2BL and HIST1H1B, that were highly expressed in ECMO. A risk score derived from expression of these genes differentiated ECMO and MODS patients in our dataset (AUC = 0.91, 95% CI 0.79-1.00, P-value = 7e-04, logistic regression) as well as validation dataset (AUC= 0.73, 95% CI 0.53-0.93, P-value = 2e-02, logistic regression).InterpretationThis study demonstrates that transcriptomic features can serve as indicators of severity that could be superior to traditional methods of ascertaining acuity in MODS patients. Analysis of expression of signatures identified in this study could help clinicians in the diagnosis and prognostication of MODS patients after arrival to the Hospital.