A Fecal MicroRNA Signature by Small RNA Sequencing Accurately Distinguishes Colorectal Cancers: Results From a Multicenter Study.

BACKGROUND & AIMS: Fecal tests currently used for colorectal cancer (CRC) screening show limited accuracy in detecting early tumors or precancerous lesions. In this respect, we comprehensively evaluated stool microRNA (miRNA) profiles as biomarkers for noninvasive CRC diagnosis. METHODS: A total of 1273 small RNA sequencing experiments were performed in multiple biospecimens. In a cross-sectional study, miRNA profiles were investigated in fecal samples from an Italian and a Czech cohort (155 CRCs, 87 adenomas, 96 other intestinal diseases, 141 colonoscopy-negative controls). A predictive miRNA signature for cancer detection was defined by a machine learning strategy and tested in additional fecal samples from 141 CRC patients and 80 healthy volunteers. miRNA profiles were compared with those of 132 tumors/adenomas paired with adjacent mucosa, 210 plasma extracellular vesicle samples, and 185 fecal immunochemical test leftover samples. RESULTS: Twenty-five miRNAs showed altered levels in the stool of CRC patients in both cohorts (adjusted P < .05). A 5-miRNA signature, including miR-149-3p, miR-607-5p, miR-1246, miR-4488, and miR-6777-5p, distinguished patients from control individuals (area under the curve [AUC], 0.86; 95% confidence interval [CI], 0.79-0.94) and was validated in an independent cohort (AUC, 0.96; 95% CI, 0.92-1.00). The signature classified control individuals from patients with low-/high-stage tumors and advanced adenomas (AUC, 0.82; 95% CI, 0.71-0.97). Tissue miRNA profiles mirrored those of stool samples, and fecal profiles of different gastrointestinal diseases highlighted miRNAs specifically dysregulated in CRC. miRNA profiles in fecal immunochemical test leftover samples showed good correlation with those of stool collected in preservative buffer, and their alterations could be detected in adenoma or CRC patients. CONCLUSIONS: Our comprehensive fecal miRNome analysis identified a signature accurately discriminating cancer aimed at improving noninvasive diagnosis and screening strategies.

Enrichment of human nasopharyngeal bacteriome with bacteria from dust after short-term exposure to indoor environment: a pilot study.

BACKGROUND: Indoor dust particles are an everyday source of human exposure to microorganisms and their inhalation may directly affect the microbiota of the respiratory tract. We aimed to characterize the changes in human nasopharyngeal bacteriome after short-term exposure to indoor (workplace) environments. METHODS: In this pilot study, nasopharyngeal swabs were taken from 22 participants in the morning and after 8 h of their presence at the workplace. At the same time points, indoor dust samples were collected from the participants' households (16 from flats and 6 from houses) and workplaces (8 from a maternity hospital - NEO, 6 from a pediatric hospital - ENT, and 8 from a research center - RCX). 16S rRNA sequencing analysis was performed on these human and environmental matrices. RESULTS: Staphylococcus and Corynebacterium were the most abundant genera in both indoor dust and nasopharyngeal samples. The analysis indicated lower bacterial diversity in indoor dust samples from flats compared to houses, NEO, ENT, and RCX (p < 0.05). Participants working in the NEO had the highest nasopharyngeal bacterial diversity of all groups (p < 0.05). After 8 h of exposure to the workplace environment, enrichment of the nasopharynx with several new bacterial genera present in the indoor dust was observed in 76% of study participants; however, no significant changes were observed at the level of the nasopharyngeal bacterial diversity (p > 0.05, Shannon index). These "enriching" bacterial genera overlapped between the hospital workplaces - NEO and ENT but differed from those in the research center - RCX. CONCLUSIONS: The results suggest that although the composition of nasopharyngeal bacteriome is relatively stable during the day. Short-term exposure to the indoor environment can result in the enrichment of the nasopharynx with bacterial DNA from indoor dust; the bacterial composition, however, varies by the indoor workplace environment.

Evaluation of Microbiome-Host Relationships in the Zebrafish Gastrointestinal System Reveals Adaptive Immunity Is a Target of Bis(2-ethylhexyl) Phthalate (DEHP) Exposure.

To improve physical characteristics of plastics such as flexibility and durability, producers enrich materials with phthalates such as di-2-(ethylhexyl) phthalate (DEHP). DEHP is a high production volume chemical associated with metabolic and immune disruption in animals and humans. To reveal mechanisms implicated in phthalate-related disruption in the gastrointestinal system, male and female zebrafish were fed DEHP (3 ppm) daily for two months. At the transcriptome level, DEHP significantly upregulated gene networks in the intestine associated with helper T cells' (Th1, Th2, and Th17) specific pathways. The activation of gene networks associated with adaptive immunity was linked to the suppression of networks for tight junction, gap junctional intercellular communication, and transmembrane transporters, all of which are precursors for impaired gut integrity and performance. On a class level, DEHP exposure increased Bacteroidia and Gammaproteobacteria and decreased Verrucomicrobiae in both the male and female gastrointestinal system. Further, in males there was a relative increase in Fusobacteriia and Betaproteobacteria and a relative decrease in Saccharibacteria. Predictive algorithms revealed that the functional shift in the microbiome community, and the metabolites they produce, act to modulate intestinal adaptive immunity. This finding suggests that the gut microbiota may contribute to the adverse effects of DEHP on the host by altering metabolites sensed by both intestinal and immune Th cells. Our results suggest that the microbiome-gut-immune axis can be modified by DEHP and emphasize the value of multiomics approaches to study microbiome-host interactions following chemical perturbations.

Circulating T cell subsets are associated with clinical outcome of anti-VEGF-based 1st-line treatment of metastatic colorectal cancer patients: a prospective study with focus on primary tumor sidedness.

BACKGROUND: In a prospective study with long-term follow-up, we analyzed circulating T cell subsets in patients with metastatic colorectal cancer (mCRC) in the context of primary tumor sidedness, KRAS status, and clinical outcome. Our primary goal was to investigate whether baseline levels of circulating T cell subsets serve as a potential biomarker of clinical outcome of mCRC patients treated with an anti-VEGF-based regimen. METHODS: The study group consisted of 36 patients with colorectal adenocarcinoma who started first-line chemotherapy with bevacizumab for metastatic disease. We quantified T cell subsets including Tregs and CD8+ T cells in the peripheral blood prior to therapy initiation. Clinical outcome was evaluated as progression-free survival (PFS), overall survival (OS), and objective response rate (ORR). RESULTS: 1) mCRC patients with KRAS wt tumors had higher proportions of circulating CD8+ cytotoxic T cells among all T cells but also higher measures of T regulatory (Treg) cells such as absolute count and a higher proportion of Tregs in the CD4+ subset. 2) A low proportion of circulating Tregs among CD4+ cells, and a high CD8:Treg ratio at initiation of VEGF-targeting therapy, were associated with favorable clinical outcome. 3) In a subset of patients with primarily right-sided mCRC, superior PFS and OS were observed when the CD8:Treg ratio was high. CONCLUSIONS: The baseline level of circulating immune cells predicts clinical outcome of 1st-line treatment with the anti-VEGF angio/immunomodulatory agent bevacizumab. Circulating immune biomarkers, namely the CD8:Treg ratio, identified patients in the right-sided mCRC subgroup with favorable outcome following treatment with 1st-line anti-VEGF treatment.

Image-based surrogate biomarkers for molecular subtypes of colorectal cancer.

MOTIVATION: Whole genome expression profiling of large cohorts of different types of cancer led to the identification of distinct molecular subcategories (subtypes) that may partially explain the observed inter-tumoral heterogeneity. This is also the case of colorectal cancer (CRC) where several such categorizations have been proposed. Despite recent developments, the problem of subtype definition and recognition remains open, one of the causes being the intrinsic heterogeneity of each tumor, which is difficult to estimate from gene expression profiles. However, one of the observations of these studies indicates that there may be links between the dominant tumor morphology characteristics and the molecular subtypes. Benefiting from a large collection of CRC samples, comprising both gene expression and histopathology images, we investigated the possibility of building image-based classifiers able to predict the molecular subtypes. We employed deep convolutional neural networks for extracting local descriptors which were then used for constructing a dictionary-based representation of each tumor sample. A set of support vector machine classifiers were trained to solve different binary decision problems, their combined outputs being used to predict one of the five molecular subtypes. RESULTS: A hierarchical decomposition of the multi-class problem was obtained with an overall accuracy of 0.84 (95%CI=0.79-0.88). The predictions from the image-based classifier showed significant prognostic value similar to their molecular counterparts. CONTACT: popovici@iba.muni.cz. AVAILABILITY AND IMPLEMENTATION: Source code used for the image analysis is freely available from https://github.com/higex/qpath . SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Dynamics of allergy development during the first 5 years of life.

Allergic diseases have increased in developed countries during the past decades. A cohort of Slovak children was followed from birth to track allergic symptoms dynamics in early childhood. Information on allergic symptoms (atopic dermatitis = AD, rhino conjunctivitis = RC, wheezing = Wh, urticaria = Ur) and food allergies among children was based on clinical evaluation of children by allergists at three developmental stages (infant, toddler, preschool). Out of 320 cases of allergies, 64 infants, 145 toddlers, and 195 preschool children suffered from AD, RC, Wh, Ur, or their combinations (i.e., significant increase with age, p < 0.001). AD first appeared in infants, Wh and/or RC rose mainly in toddlers, and Ur among preschool children. AD in infants or toddlers disappeared in the subsequent developmental stage in approximately one third of all cases. Single AD persistence without remission or extension was not common and accounted only for 6.9% of AD infants' allergic manifestations. In addition to single-symptom allergic diseases, this study also identified several combinations of atopic symptoms.Conclusions: The proportion of multi-symptom allergies increased while single-symptom forms decreased. The observed temporal trends of allergic symptoms correspond to the atopic march. What is Known: • The observed temporal trends of allergic symptoms correspond to the atopic march. What is New: • Allergic diseases in children were first manifested as single forms, with atopic dermatitis (AD) commonly functioning as the "entry point" to allergies. • The overall proportion of single-symptom allergic disorders decreased over time while the proportion of multi-symptom allergies increased.

Dirigent proteins in plants: modulating cell wall metabolism during abiotic and biotic stress exposure.

Dirigent (DIR) proteins were found to mediate regio- and stereoselectivity of bimolecular phenoxy radical coupling during lignan biosynthesis. Here we summarize the current knowledge of the importance of DIR proteins in lignan and lignin biosynthesis and highlight their possible importance in plant development. We focus on the still rather enigmatic Arabidopsis DIR gene family, discussing the few members with known functional importance. We comment on recent discoveries describing the detailed structure of two DIR proteins with implications in the mechanism of DIR-mediated catalysis. Further, we summarize the ample evidence for stress-induced dirigent gene expression, suggesting the role of DIRs in adaptive responses. In the second part of our work, we present a preliminary bioinformatics-based characterization of the AtDIR family. The phylogenetic analysis of AtDIRs complemented by comparison with DIR proteins of mostly known function from other species allowed us to suggest possible roles for several members of this family and identify interesting AtDIR targets for further study. Finally, based on the available metadata and our in silico analysis of AtDIR promoters, we hypothesize about the existence of specific transcriptional controls for individual AtDIR genes and implicate them in various stress responses, hormonal regulations, and developmental processes.

Combined Proteomics and Transcriptomics Identifies Carboxypeptidase B1 and Nuclear Factor κB (NF-κB) Associated Proteins as Putative Biomarkers of Metastasis in Low Grade Breast Cancer.

Current prognostic factors are insufficient for precise risk-discrimination in breast cancer patients with low grade breast tumors, which, in disagreement with theoretical prognosis, occasionally form early lymph node metastasis. To identify markers for this group of patients, we employed iTRAQ-2DLC-MS/MS proteomics to 24 lymph node positive and 24 lymph node negative grade 1 luminal A primary breast tumors. Another group of 48 high-grade tumors (luminal B, triple negative, Her-2 subtypes) was also analyzed to investigate marker specificity for grade 1 luminal A tumors. From the total of 4405 proteins identified (FDR < 5%), the top 65 differentially expressed together with 30 previously identified and control markers were analyzed also at transcript level. Increased levels of carboxypeptidase B1 (CPB1), PDZ and LIM domain protein 2 (PDLIM2), and ring finger protein 25 (RNF25) were associated specifically with lymph node positive grade 1 tumors, whereas stathmin 1 (STMN1) and thymosin beta 10 (TMSB10) associated with aggressive tumor phenotype also in high grade tumors at both protein and transcript level. For CPB1, these differences were also observed by immunohistochemical analysis on tissue microarrays. Up-regulation of putative biomarkers in lymph node positive (versus negative) luminal A tumors was validated by gene expression analysis of an independent published data set (n = 343) for CPB1 (p = 0.00155), PDLIM2 (p = 0.02027) and RELA (p = 0.00015). Moreover, statistically significant connections with patient survival were identified in another public data set (n = 1678). Our findings indicate unique pro-metastatic mechanisms in grade 1 tumors that can include up-regulation of CPB1, activation of NF-κB pathway and changes in cell survival and cytoskeleton. These putative biomarkers have potential to identify the specific minor subpopulation of breast cancer patients with low grade tumors who are at higher than expected risk of recurrence and who would benefit from more intensive follow-up and may require more personalized therapy.

Joint analysis of histopathology image features and gene expression in breast cancer.

BACKGROUND: Genomics and proteomics are nowadays the dominant techniques for novel biomarker discovery. However, histopathology images contain a wealth of information related to the tumor histology, morphology and tumor-host interactions that is not accessible through these techniques. Thus, integrating the histopathology images in the biomarker discovery workflow could potentially lead to the identification of new image-based biomarkers and the refinement or even replacement of the existing genomic and proteomic signatures. However, extracting meaningful and robust image features to be mined jointly with genomic (and clinical, etc.) data represents a real challenge due to the complexity of the images. RESULTS: We developed a framework for integrating the histopathology images in the biomarker discovery workflow based on the bag-of-features approach - a method that has the advantage of being assumption-free and data-driven. The images were reduced to a set of salient patterns and additional measurements of their spatial distribution, with the resulting features being directly used in a standard biomarker discovery application. We demonstrated this framework in a search for prognostic biomarkers in breast cancer which resulted in the identification of several prognostic image features and a promising multimodal (imaging and genomic) prognostic signature. The source code for the image analysis procedures is freely available. CONCLUSIONS: The framework proposed allows for a joint analysis of images and gene expression data. Its application to a set of breast cancer cases resulted in image-based and combined (image and genomic) prognostic scores for relapse-free survival.

TopKLists: a comprehensive R package for statistical inference, stochastic aggregation, and visualization of multiple omics ranked lists.

High-throughput sequencing techniques are increasingly affordable and produce massive amounts of data. Together with other high-throughput technologies, such as microarrays, there are an enormous amount of resources in databases. The collection of these valuable data has been routine for more than a decade. Despite different technologies, many experiments share the same goal. For instance, the aims of RNA-seq studies often coincide with those of differential gene expression experiments based on microarrays. As such, it would be logical to utilize all available data. However, there is a lack of biostatistical tools for the integration of results obtained from different technologies. Although diverse technological platforms produce different raw data, one commonality for experiments with the same goal is that all the outcomes can be transformed into a platform-independent data format - rankings - for the same set of items. Here we present the R package TopKLists, which allows for statistical inference on the lengths of informative (top-k) partial lists, for stochastic aggregation of full or partial lists, and for graphical exploration of the input and consolidated output. A graphical user interface has also been implemented for providing access to the underlying algorithms. To illustrate the applicability and usefulness of the package, we integrated microRNA data of non-small cell lung cancer across different measurement techniques and draw conclusions. The package can be obtained from CRAN under a LGPL-3 license.

ToPASeq: an R package for topology-based pathway analysis of microarray and RNA-Seq data.

BACKGROUND: Pathway analysis methods, in which differentially expressed genes are mapped to databases of reference pathways and relative enrichment is assessed, help investigators to propose biologically relevant hypotheses. The last generation of pathway analysis methods takes into account the topological structure of a pathway, which helps to increase both specificity and sensitivity of the findings. Simultaneously, the RNA-Seq technology is gaining popularity and becomes widely used for gene expression profiling. Unfortunately, majority of topological pathway analysis methods remains without implementation and if an implementation exists, it is limited in various factors. RESULTS: We developed a new R/Bioconductor package ToPASeq offering uniform interface to seven distinct topology-based pathway analysis methods, of which three we implemented de-novo and four were adjusted from existing implementations. Apart this, ToPASeq offers a set of tailored visualization functions and functions for importing and manipulating pathways and their topologies, facilitating the application of the methods on different species. The package can be used to compare the differential expression of pathways between two conditions on both gene expression microarray and RNA-Seq data. The package is written in R and is available from Bioconductor 3.2 using AGPL-3 license. CONCLUSION: ToPASeq is a novel package that offers seven distinct methods for topology-based pathway analysis, which are easily applicable on microarray as well as RNA-Seq data, both in human and other species. At the same time, it provides specific tools for visualization of the results.

Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer.

The recognition that colorectal cancer (CRC) is a heterogeneous disease in terms of clinical behaviour and response to therapy translates into an urgent need for robust molecular disease subclassifiers that can explain this heterogeneity beyond current parameters (MSI, KRAS, BRAF). Attempts to fill this gap are emerging. The Cancer Genome Atlas (TGCA) reported two main CRC groups, based on the incidence and spectrum of mutated genes, and another paper reported an EMT expression signature defined subgroup. We performed a prior free analysis of CRC heterogeneity on 1113 CRC gene expression profiles and confronted our findings to established molecular determinants and clinical, histopathological and survival data. Unsupervised clustering based on gene modules allowed us to distinguish at least five different gene expression CRC subtypes, which we call surface crypt-like, lower crypt-like, CIMP-H-like, mesenchymal and mixed. A gene set enrichment analysis combined with literature search of gene module members identified distinct biological motifs in different subtypes. The subtypes, which were not derived based on outcome, nonetheless showed differences in prognosis. Known gene copy number variations and mutations in key cancer-associated genes differed between subtypes, but the subtypes provided molecular information beyond that contained in these variables. Morphological features significantly differed between subtypes. The objective existence of the subtypes and their clinical and molecular characteristics were validated in an independent set of 720 CRC expression profiles. Our subtypes provide a novel perspective on the heterogeneity of CRC. The proposed subtypes should be further explored retrospectively on existing clinical trial datasets and, when sufficiently robust, be prospectively assessed for clinical relevance in terms of prognosis and treatment response predictive capacity. Original microarray data were uploaded to the ArrayExpress database (http://www.ebi.ac.uk/arrayexpress/) under Accession Nos E-MTAB-990 and E-MTAB-1026.

An invasion front gene expression signature for higher-risk patient selection in stage IIA MSS colon cancer.

Stage II colon cancer (CC) encompasses a heterogeneous group of patients with diverse survival experiences: 87% to 58% 5-year relative survival rates for stages IIA and IIC, respectively. While stage IIA patients are usually spared the adjuvant chemotherapy, some of them relapse and may benefit from it; thus, their timely identification is crucial. Current gene expression signatures did not specifically target this group nor did they find their place in clinical practice. Since processes at invasion front have also been linked to tumor progression, we hypothesize that aside from bulk tumor features, focusing on the invasion front may provide additional clues for this stratification. A retrospective matched case-control collection of 39 stage IIA microsatellite-stable (MSS) untreated CCs was analyzed to identify prognostic gene expression-based signatures. The endpoint was defined as relapse within 5 years vs. no relapse for at least 6 years. From the same tumors, three different classifiers (bulk tumor, invasion front, and constrained baseline on bulk tumor) were developed and their performance estimated. The baseline classifier, while the weakest, was validated in two independent data sets. The best performing signature was based on invasion front profiles [area under the receiver operating curve (AUC) = 0.931 (0.815-1.0)] and contained genes associated with KRAS pathway activation, apical junction complex, and heme metabolism. Its combination with bulk tumor classifier further improved the accuracy of the predictions.

Context-dependent interpretation of the prognostic value of BRAF and KRAS mutations in colorectal cancer.

BACKGROUND: The mutation status of the BRAF and KRAS genes has been proposed as prognostic biomarker in colorectal cancer. Of them, only the BRAF V600E mutation has been validated independently as prognostic for overall survival and survival after relapse, while the prognostic value of KRAS mutation is still unclear. We investigated the prognostic value of BRAF and KRAS mutations in various contexts defined by stratifications of the patient population. METHODS: We retrospectively analyzed a cohort of patients with stage II and III colorectal cancer from the PETACC-3 clinical trial (N = 1,423), by assessing the prognostic value of the BRAF and KRAS mutations in subpopulations defined by all possible combinations of the following clinico-pathological variables: T stage, N stage, tumor site, tumor grade and microsatellite instability status. In each such subpopulation, the prognostic value was assessed by log rank test for three endpoints: overall survival, relapse-free survival, and survival after relapse. The significance level was set to 0.01 for Bonferroni-adjusted p-values, and a second threshold for a trend towards statistical significance was set at 0.05 for unadjusted p-values. The significance of the interactions was tested by Wald test, with significance level of 0.05. RESULTS: In stage II-III colorectal cancer, BRAF mutation was confirmed a marker of poor survival only in subpopulations involving microsatellite stable and left-sided tumors, with higher effects than in the whole population. There was no evidence for prognostic value in microsatellite instable or right-sided tumor groups. We found that BRAF was also prognostic for relapse-free survival in some subpopulations. We found no evidence that KRAS mutations had prognostic value, although a trend was observed in some stratifications. We also show evidence of heterogeneity in survival of patients with BRAF V600E mutation. CONCLUSIONS: The BRAF mutation represents an additional risk factor only in some subpopulations of colorectal cancers, in others having limited prognostic value. However, in the subpopulations where it is prognostic, it represents a marker of much higher risk than previously considered. KRAS mutation status does not seem to represent a strong prognostic variable.

DUSP 4 expression identifies a subset of colorectal cancer tumors that differ in MAPK activation, regardless of the genotype.

As dual-specificity phosphatase (DUSP) expression has been correlated to sensitivity to MEK inhibitors, DUSP expression levels may indicate activation of the mitogen-activated protein kinase (MAPK) pathway in many tumor types. In this study, we investigate if DUSP levels can indicate different levels of MAPK activation within colorectal cancer (CRC) patients. In three different CRC patient microarray datasets, we analyzed the expression of DUSP1. DUSP4 and DUSP6 according to mutational status, their correlation with survival and their association with different clinical characteristics. DUSP4 was significantly differentially expressed between all mutational subgroups with the highest expression in BRAF mutated tumors. Moreover, high DUSP4 expression was associated with a worse overall survival and with clinical characteristics typical for BRAF mutant patients. The use of DUSP expression as a predictive biomarker towards MAPK targeted therapy in CRC patients needs further investigation.

Molecular portraits of colorectal cancer morphological regions.

Heterogeneity of colorectal carcinoma (CRC) represents a major hurdle towards personalized medicine. Efforts based on whole tumor profiling demonstrated that the CRC molecular subtypes were associated with specific tumor morphological patterns representing tumor subregions. We hypothesize that whole-tumor molecular descriptors depend on the morphological heterogeneity with significant impact on current molecular predictors. We investigated intra-tumor heterogeneity by morphology-guided transcriptomics to better understand the links between gene expression and tumor morphology represented by six morphological patterns (morphotypes): complex tubular, desmoplastic, mucinous, papillary, serrated, and solid/trabecular. Whole-transcriptome profiling by microarrays of 202 tumor regions (morphotypes, tumor-adjacent normal tissue, supportive stroma, and matched whole tumors) from 111 stage II-IV CRCs identified morphotype-specific gene expression profiles and molecular programs and differences in their cellular buildup. The proportion of cell types (fibroblasts, epithelial and immune cells) and differentiation of epithelial cells were the main drivers of the observed disparities with activation of EMT and TNF-α signaling in contrast to MYC and E2F targets signaling, defining major gradients of changes at molecular level. Several gene expression-based (including single-cell) classifiers, prognostic and predictive signatures were examined to study their behavior across morphotypes. Most exhibited important morphotype-dependent variability within same tumor sections, with regional predictions often contradicting the whole-tumor classification. The results show that morphotype-based tumor sampling allows the detection of molecular features that would otherwise be distilled in whole tumor profile, while maintaining histopathology context for their interpretation. This represents a practical approach at improving the reproducibility of expression profiling and, by consequence, of gene-based classifiers.

Rgtsp: a generalized top scoring pairs package for class prediction.

SUMMARY: A top scoring pair (TSP) classifier consists of a pair of variables whose relative ordering can be used for accurately predicting the class label of a sample. This classification rule has the advantage of being easily interpretable and more robust against technical variations in data, as those due to different microarray platforms. Here we describe a parallel implementation of this classifier which significantly reduces the training time, and a number of extensions, including a multi-class approach, which has the potential of improving the classification performance. AVAILABILITY AND IMPLEMENTATION: Full C++ source code and R package Rgtsp are freely available from http://lausanne.isb-sib.ch/~vpopovic/research/. The implementation relies on existing OpenMP libraries.

Derivation and Molecular Characterization of a Morphological Subpopulation of Human iPSC Astrocytes Reveal a Potential Role in Schizophrenia and Clozapine Response.

Astrocytes are the most abundant cell type in the human brain and are important regulators of several critical cellular functions, including synaptic transmission. Although astrocytes are known to play a central role in the etiology and pathophysiology of schizophrenia, little is known about their potential involvement in clinical response to the antipsychotic clozapine. Moreover, astrocytes display a remarkable degree of morphological diversity, but the potential contribution of astrocytic subtypes to disease biology and drug response has received little attention. Here, we used state-of-the-art human induced pluripotent stem cell (hiPSC) technology to derive a morphological subtype of astrocytes from healthy individuals and individuals with schizophrenia, including responders and nonresponders to clozapine. Using functional assays and transcriptional profiling, we identified a distinct gene expression signature highly specific to schizophrenia as shown by disease association analysis of more than 10 000 diseases. We further found reduced levels of both glutamate and the NMDA receptor coagonist d-serine in subtype astrocytes derived from schizophrenia patients, and that exposure to clozapine only rescued this deficiency in cells from clozapine responders, providing further evidence that d-serine in particular, and NMDA receptor-mediated glutamatergic neurotransmission in general, could play an important role in disease pathophysiology and clozapine action. Our study represents a first attempt to explore the potential contribution of astrocyte diversity to schizophrenia pathophysiology using a human cellular model. Our findings suggest that specialized subtypes of astrocytes could be important modulators of disease pathophysiology and clinical drug response, and warrant further investigations.

Sex-dependent host-microbiome dynamics in zebrafish: Implications for toxicology and gastrointestinal physiology.

The physiology of males and females can be vastly different, complicating interpretation of toxicological and physiological data. The objectives of this study were to elucidate the sex differences in the microbiome-gastrointestinal (GI) transcriptome of adult zebrafish. We compared microbial composition and diversity in both males and females fed the same diet and housed in the same environment. There were no sex-specific differences in weight gain nor gastrointestinal morphology based on histopathology. There was no difference in gut microbial diversity, richness (Shannon and Chao1 index) nor predicted functional composition of the microbiome between males and females. Prior to post-hoc correction, male zebrafish showed higher abundance for the bacterial families Erythrobacteraceae and Lamiaceae, both belonging to the phyla Actinobacteria and Proteobacteria. At the genus level, Lamia and Altererythrobacter were more dominant in males and an unidentified genus in Bacteroidetes was more abundant in females. There were 16 unique differentially expressed transcripts in the gastrointestinal tissue between male and female zebrafish (FDR corrected, p < 0.05). Relative to males, the mRNA expression for trim35-9, slc25a48, chchd3b, csad, and hsd17b3 were lower in female GI while cyp2k6, adra2c, and bckdk were higher in the female GI. Immune and lipid-related gene network expression differed between the sexes (i.e., cholesterol export and metabolism) as well as networks related to gastric motility, gastrointestinal system absorption and digestion. Such data provide clues as to putative differences in gastrointestinal physiology between male and female zebrafish. This study identifies host-transcriptome differences that can be considered when interpreting the microgenderome of zebrafish in studies investigating GI physiology and toxicology of fishes.