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Background The correct identification of differentially abundant microbial taxa between experimental conditions is a methodological and computational challenge. Recent work has produced methods to deal with the high sparsity and compositionality characteristic of microbiome data, but independent benchmarks comparing these to alternatives developed for RNA-seq data analysis are lacking. Results We compare methods developed for single-cell and bulk RNA-seq, and specifically for microbiome data, in terms of suitability of distributional assumptions, ability to control false discoveries, concordance, power, and correct identification of differentially abundant genera. We benchmark these methods using 100 manually curated datasets from 16S and whole metagenome shotgun sequencing. Conclusions The multivariate and compositional methods developed specifically for microbiome analysis did not outperform univariate methods developed for differential expression analysis of RNA-seq data. We recommend a careful exploratory data analysis prior to application of any inferential model and we present a framework to help scientists make an informed choice of analysis methods in a dataset-specific manner.

Background Gene set analysis is moving towards considering pathway topology as a crucial feature. Pathway elements are complex entities such as protein complexes, gene family members and chemical compounds. The conversion of pathway topology to a gene/protein networks (where nodes are a simple element like a gene/protein) is a critical and challenging task that enables topology-based gene set analyses. Unfortunately, currently available R/Bioconductor packages provide pathway networks only from single databases. They do not propagate signals through chemical compounds and do not differentiate between complexes and gene families. Results Here we present graphite , a Bioconductor package addressing these issues. Pathway information from four different databases is interpreted following specific biologically-driven rules that allow the reconstruction of gene-gene networks taking into account protein complexes, gene families and sensibly removing chemical compounds from the final graphs. The resulting networks represent a uniform resource for pathway analyses. Indeed, graphite provides easy access to three recently proposed topological methods. The graphite package is available as part of the Bioconductor software suite. Conclusions graphite is an innovative package able to gather and make easily available the contents of the four major pathway databases. In the field of topological analysis graphite acts as a provider of biological information by reducing the pathway complexity considering the biological meaning of the pathway elements.

Hepatitis C virus infection (HCV) represents a unique model to characterize, from early to late stages of infection, the T cell differentiation process leading to exhaustion of human CD8+ T cells. Here we show that in early HCV infection, exhaustion-committed virus-specific CD8+ T cells display a marked upregulation of transcription associated with impaired glycolytic and mitochondrial functions, that are linked to enhanced ataxia-telangiectasia mutated (ATM) and p53 signaling. After evolution to chronic infection, exhaustion of HCV-specific T cell responses is instead characterized by a broad gene downregulation associated with a wide metabolic and anti-viral function impairment, which can be rescued by histone methyltransferase inhibitors. These results have implications not only for treatment of HCV-positive patients not responding to last-generation antivirals, but also for other chronic pathologies associated with T cell dysfunction, including cancer. Here, the authors report that exhausted HCV-specific CD8+ T cells are marked by upregulation of p53 signaling already detectable in an early phase of chronic HCV infection and by a later development of a repressive chromatin state, and show that chemical targeting of these pathways improves CD8+ T cell metabolism and antiviral function.

Survival rates of oral squamous cell carcinoma (OSCC) remained substantially unchanged over the last decades; thus, additional prognostic tools are strongly needed. Salivary miRNAs have emerged as excellent non-invasive cancer biomarker candidates, but their association with OSCC prognosis has not been investigated yet. In this study, we analyzed global salivary miRNA expression in OSCC patients and healthy controls, with the aim to define its diagnostic and prognostic potential. Saliva was collected from patients with newly diagnosed untreated primary OSCC and healthy controls. Global profiling of salivary miRNAs was carried out through a microarray approach, while signature validation was performed by quantitative real-time PCR (RT-qPCR). A stringent statistical approach for microarray and RT-qPCR data normalization was applied. The diagnostic performance of miRNAs and their correlation with OSCC prognosis were comprehensively analyzed. In total, 25 miRNAs emerged as differentially expressed between OSCC patients and healthy controls and, among them, seven were significantly associated with disease-free survival (DFS). miR-106b-5p, miR-423-5p and miR-193b-3p were expressed at high levels in saliva of OSCC patients and their combination displays the best diagnostic performance (ROC - AUC = 0.98). Moreover, high expression of miR-423-5p was an independent predictor of poor DFS, when included in multivariate survival analysis with the number of positive lymph nodes - the only significant clinical prognosticator. Finally, we observed a significant decrease in miR-423-5p expression in matched post-operative saliva samples, suggesting its potential cancer-specific origin. Salivary miRNAs identified in our cohort of patients show to be accurate in OSCC detection and to effectively stratify patients according to their likelihood of relapse. These results, if validated in an independent set of patients, could be particularly promising for screening/follow-up of high-risk populations and useful for preoperative prognostic assessment.

Ovarian cancer is a leading cause of cancer deaths among women. Effective targets to treat advanced epithelial ovarian cancer (EOC) and biomarkers to predict treatment response are still lacking because of the complexity of pathways involved in ovarian cancer progression. Here we show that miR-181a promotes TGF-β-mediated epithelial-to-mesenchymal transition via repression of its functional target, Smad7. miR-181a and phosphorylated Smad2 are enriched in recurrent compared with matched-primary ovarian tumours and their expression is associated with shorter time to recurrence and poor outcome in patients with EOC. Furthermore, ectopic expression of miR-181a results in increased cellular survival, migration, invasion, drug resistance and in vivo tumour burden and dissemination. In contrast, miR-181a inhibition via decoy vector suppression and Smad7 re-expression results in significant reversion of these phenotypes. Combined, our findings highlight an unappreciated role for miR-181a, Smad7, and the TGF-β signalling pathway in high-grade serous ovarian cancer. Ovarian cancer is often diagnosed at a late stage when metastasis has already occurred. In this study, Parikh et al. show that mir-181a is involved in mediating the epithelial-to-mesenchymal transition in ovarian cancer, leading to activation of the TGF-β signalling pathway and metastasis.

The krill species Euphausia superba plays a critical role in the food chain of the Antarctic ecosystem. Significant changes in climate conditions observed in the Antarctic Peninsula region in the last decades have already altered the distribution of krill and its reproductive dynamics. A deeper understanding of the adaptation capabilities of this species is urgently needed. The availability of a large body of RNA-seq assays allowed us to extend the current knowledge of the krill transcriptome. Our study covered the entire developmental process providing information of central relevance for ecological studies. Here we identified a series of genes involved in different steps of the krill moulting cycle, in the reproductive process and in sexual maturation in accordance with what was already described in previous works. Furthermore, the new transcriptome highlighted the presence of differentially expressed genes previously unknown, playing important roles in cuticle development as well as in energy storage during the krill life cycle. The discovery of new opsin sequences, specifically rhabdomeric opsins, one onychopsin, and one non-visual arthropsin, expands our knowledge of the krill opsin repertoire. We have collected all these results into the KrillDB 2 database, a resource combining the latest annotation of the krill transcriptome with a series of analyses targeting genes relevant to krill physiology. KrillDB 2 provides in a single resource a comprehensive catalog of krill genes; an atlas of their expression profiles over all RNA-seq datasets publicly available; a study of differential expression across multiple conditions. Finally, it provides initial indications about the expression of microRNA precursors, whose contribution to krill physiology has never been reported before.

We investigated the potential plant growth-promoting traits of 377 culturable endophytic bacteria, isolated from Vitis vinifera cv. Glera, as good biofertilizer candidates in vineyard management. Endophyte ability in promoting plant growth was assessed in vitro by testing ammonia production, phosphate solubilization, indole-3-acetic acid (IAA) and IAA-like molecule biosynthesis, siderophore and lytic enzyme secretion. Many of the isolates were able to mobilize phosphate (33%), release ammonium (39%), secrete siderophores (38%) and a limited part of them synthetized IAA and IAA-like molecules (5%). Effects of each of the 377 grapevine beneficial bacteria on Arabidopsis thaliana root development were also analyzed to discern plant growth-promoting abilities (PGP) of the different strains, that often exhibit more than one PGP trait. A supervised model-based clustering analysis highlighted six different classes of PGP effects on root architecture. A. thaliana DR5::GUS plantlets, inoculated with IAA-producing endophytes, resulted in altered root growth and enhanced auxin response. Overall, the results indicate that the Glera PGP endospheric culturable microbiome could contribute, by structural root changes, to obtain water and nutrients increasing plant adaptation and survival. From the complete cultivable collection, twelve promising endophytes mainly belonging to the Bacillus but also to Micrococcus and Pantoea genera, were selected for further investigations in the grapevine host plants towards future application in sustainable management of vineyards.

Polyglutamine expansion in the androgen receptor (AR) causes spinobulbar muscular atrophy (SBMA). Skeletal muscle is a primary site of toxicity; however, the current understanding of the early pathological processes that occur and how they unfold during disease progression remains limited. Using transgenic and knock-in mice and patient-derived muscle biopsies, we show that SBMA mice in the presymptomatic stage develop a respiratory defect matching defective expression of genes involved in excitation-contraction coupling (ECC), altered contraction dynamics, and increased fatigue. These processes are followed by stimulus-dependent accumulation of calcium into mitochondria and structural disorganization of the muscle triads. Deregulation of expression of ECC genes is concomitant with sexual maturity and androgen raise in the serum. Consistent with the androgen-dependent nature of these alterations, surgical castration and AR silencing alleviate the early and late pathological processes. These observations show that ECC deregulation and defective mitochondrial respiration are early but reversible events followed by altered muscle force, calcium dyshomeostasis, and dismantling of triad structure. Marchioretti and colleagues show that in the skeletal muscle of SBMA mice and patients there is an early, but reversible alteration of expression of genes involved in muscle contraction and of mitochondrial respiration, followed by accumulation of calcium inside the mitochondria, which is concomitant with the onset of motor dysfunction, and late alteration of muscle structure.

Topological gene-set analysis has emerged as a powerful means for omic data interpretation. Although numerous methods for identifying dysregulated genes have been proposed, few of them aim to distinguish genes that are the real source of perturbation from those that merely respond to the signal dysregulation. Here, we propose a new method, called SourceSet, able to distinguish between the primary and the secondary dysregulation within a Gaussian graphical model context. The proposed method compares gene expression profiles in the control and in the perturbed condition and detects the differences in both the mean and the covariance parameters with a series of likelihood ratio tests. The resulting evidence is used to infer the primary and the secondary set, i.e. the genes responsible for the primary dysregulation, and the genes affected by the perturbation through network propagation. The proposed method demonstrates high specificity and sensitivity in different simulated scenarios and on several real biological case studies. In order to fit into the more traditional pathway analysis framework, SourceSet R package also extends the analysis from a single to multiple pathways and provides several graphical outputs, including Cytoscape visualization to browse the results.

Background Mitochondrial DNA (mtDNA) pathogenic variants have been reported in several solid tumors including ovarian cancer (OC), the most lethal gynecologic malignancy, and raised interest as they potentially induce mitochondrial dysfunction and rewiring of cellular metabolism. Despite advances in recent years, functional characterization of mtDNA variants in cancer and their possible modulation of drug response remain largely uncharted. Methods Here, we characterized mtDNA variants in OC patient derived xenografts (PDX) and investigated their impact on cancer cells at multiple levels. Results Genetic analysis revealed that mtDNA variants predicted as pathogenic, mainly involving complex I and IV genes, were present in all but one PDX ( n  = 20) at different levels of heteroplasmy, including 7 PDXs with homoplasmic variants. Functional analyses demonstrated that pathogenic mtDNA variants impacted on respiratory complexes activity and subunits abundance as well as on mitochondrial morphology. Moreover, PDX cells bearing homoplasmic mtDNA variants behaved as glucose-addicted and could barely survive glucose starvation in vitro. RNA-seq analysis indicated that mtDNA mutated (heteroplasmy > 50%) PDXs were endowed with upregulated glycolysis and other pathways connected with cancer metabolism. These findings led us to investigate whether pathogenic mtDNA variants correlated with response to anti-VEGF therapy, since the latter was shown to reduce glucose availability in tumors. Strikingly, PDXs bearing homoplasmic pathogenic mtDNA variants associated with improved survival upon anti-VEGF treatment in mice, compared with mtDNA wild type or low heteroplasmy PDXs. Conclusions These results hint at mtDNA variants as potential biomarkers of response to antiangiogenic drugs.