Early-life fecal microbiome and metabolome dynamics in response to an intervention with infant formula containing specific prebiotics and postbiotics.

This study examined fecal metabolome dynamics to gain greater functional insights into the interactions between nutrition and the activity of the developing gut microbiota in healthy term-born infants. The fecal samples used here originate from a randomized, controlled, double-blind clinical study that assessed the efficacy of infant formula with prebiotics and postbiotics (experimental arm) compared with a standard infant formula (control arm). A group of exclusively breast-fed term infants was used as a reference arm. First, conventional targeted physiological and microbial measurements were performed, which showed differences in fecal Bifidobacterium levels and corresponding activity (e.g., lactate levels). Next, the overall fecal microbiota composition was determined by 16S rRNA gene amplicon sequencing. The microbiota composition profiles showed several bacterial groups in the experimental arm to be significantly different from the control arm and mostly closer to the levels observed in the reference arm. Finally, we applied an untargeted UPLC-MS/MS approach to examine changes in the fecal metabolome. Fecal metabolome profiles showed the most distinct separation, up to 404 significantly different metabolites, between the study arms. Our data reveal that infant formula with specific prebiotics and postbiotics may trigger responses in the intestinal microbiota composition that brings the ensuing fecal metabolite profile of formula-fed infants closer toward those observed in breast-fed infants. Furthermore, our results demonstrate a clear need for establishing an infant gut metabolome reference database to translate these metabolite profile dynamics into functional and physiologically relevant responses.NEW & NOTEWORTHY Untargeted metabolomics techniques can provide a "snapshot" of an ecosystem in response to environmental stimuli, such as nutritional interventions. Our analyses of fecal samples from infants demonstrate the potential of phenotyping by metabolomics while deciphering the complex interactions of early-life nutrition and gut microbiome development.

CoPub update: CoPub 5.0 a text mining system to answer biological questions.

In this article, we present CoPub 5.0, a publicly available text mining system, which uses Medline abstracts to calculate robust statistics for keyword co-occurrences. CoPub was initially developed for the analysis of microarray data, but we broadened the scope by implementing new technology and new thesauri. In CoPub 5.0, we integrated existing CoPub technology with new features, and provided a new advanced interface, which can be used to answer a variety of biological questions. CoPub 5.0 allows searching for keywords of interest and its relations to curated thesauri and provides highlighting and sorting mechanisms, using its statistics, to retrieve the most important abstracts in which the terms co-occur. It also provides a way to search for indirect relations between genes, drugs, pathways and diseases, following an ABC principle, in which A and C have no direct connection but are connected via shared B intermediates. With CoPub 5.0, it is possible to create, annotate and analyze networks using the layout and highlight options of Cytoscape web, allowing for literature based systems biology. Finally, operations of the CoPub 5.0 Web service enable to implement the CoPub technology in bioinformatics workflows. CoPub 5.0 can be accessed through the CoPub portal http://www.copub.org.

CoPub: a literature-based keyword enrichment tool for microarray data analysis.

Medline is a rich information source, from which links between genes and keywords describing biological processes, pathways, drugs, pathologies and diseases can be extracted. We developed a publicly available tool called CoPub that uses the information in the Medline database for the biological interpretation of microarray data. CoPub allows batch input of multiple human, mouse or rat genes and produces lists of keywords from several biomedical thesauri that are significantly correlated with the set of input genes. These lists link to Medline abstracts in which the co-occurring input genes and correlated keywords are highlighted. Furthermore, CoPub can graphically visualize differentially expressed genes and over-represented keywords in a network, providing detailed insight in the relationships between genes and keywords, and revealing the most influential genes as highly connected hubs. CoPub is freely accessible at http://services.nbic.nl/cgi-bin/copub/CoPub.pl.

Literature-based compound profiling: application to toxicogenomics.

INTRODUCTION: To reduce continuously increasing costs in drug development, adverse effects of drugs need to be detected as early as possible in the process. In recent years, compound-induced gene expression profiling methodologies have been developed to assess compound toxicity, including Gene Ontology term and pathway over-representation analyses. The objective of this study was to introduce an additional approach, in which literature information is used for compound profiling to evaluate compound toxicity and mode of toxicity. METHODS: Gene annotations were built by text mining in Medline abstracts for retrieval of co-publications between genes, pathology terms, biological processes and pathways. This literature information was used to generate compound-specific keyword fingerprints, representing over-represented keywords calculated in a set of regulated genes after compound administration. To see whether keyword fingerprints can be used for assessment of compound toxicity, we analyzed microarray data sets of rat liver treated with 11 hepatotoxicants. RESULTS: Analysis of keyword fingerprints of two genotoxic carcinogens, two nongenotoxic carcinogens, two peroxisome proliferators and two randomly generated gene sets, showed that each compound produced a specific keyword fingerprint that correlated with the experimentally observed histopathological events induced by the individual compounds. By contrast, the random sets produced a flat aspecific keyword profile, indicating that the fingerprints induced by the compounds reflect biological events rather than random noise. A more detailed analysis of the keyword profiles of diethylhexylphthalate, dimethylnitrosamine and methapyrilene (MPy) showed that the differences in the keyword fingerprints of these three compounds are based upon known distinct modes of action. Visualization of MPy-linked keywords and MPy-induced genes in a literature network enabled us to construct a mode of toxicity proposal for MPy, which is in agreement with known effects of MPy in literature. CONCLUSION: Compound keyword fingerprinting based on information retrieved from literature is a powerful approach for compound profiling, allowing evaluation of compound toxicity and analysis of the mode of action.

A portrait of cisplatin-induced transcriptional changes in mouse embryonic stem cells reveals a dominant p53-like response.

Accumulation of damage in undifferentiated cells may threaten homeostasis and regenerative capacity. Remarkably, p53 has been suggested to be transcriptionally inactive in these cells. To gain insight in the kinetics and interplay of the predominant transcriptional responses of DNA damage signalling pathways in undifferentiated cells, mouse embryonic stem cells were exposed to cisplatin at four different time points (2, 4, 8 and 24h) and concentrations (1, 2, 5 and 10 microM). RNA was isolated and subjected to genome-wide expression profiling. Up to one fourth of the tested genes could be identified as being differentially expressed (false discovery rate=10%) after the cisplatin treatment. Clustering of the expression changes showed a strong time dependency. To investigate the relationship between affected genes, a gene set analysis method was used. Functionally related gene sets were defined using gene ontologies or transcription factor binding sites and were tested for overrepresentation within the differentially expressed genes. A variety of gene sets were clearly enriched among which 'apoptosis' and 'cell cycle' were the most pronounced. Furthermore, there was a strong enrichment of genes with a p53-binding motif. The involvement of the 'cell cycle' and 'apoptosis' gene sets in the cisplatin response was detected at concentrations and time points where the respective biological assays were still negative. The results reveal novel insights into the mechanisms which maintain the genomic integrity in undifferentiated cells. Additionally the results illustrate that gene set analysis of genome-wide expression changes provides a sensitive instrument to detect cellular stress responses to DNA damage.

CoPub Mapper: mining MEDLINE based on search term co-publication.

BACKGROUND: High throughput microarray analyses result in many differentially expressed genes that are potentially responsible for the biological process of interest. In order to identify biological similarities between genes, publications from MEDLINE were identified in which pairs of gene names and combinations of gene name with specific keywords were co-mentioned. RESULTS: MEDLINE search strings for 15,621 known genes and 3,731 keywords were generated and validated. PubMed IDs were retrieved from MEDLINE and relative probability of co-occurrences of all gene-gene and gene-keyword pairs determined. To assess gene clustering according to literature co-publication, 150 genes consisting of 8 sets with known connections (same pathway, same protein complex, or same cellular localization, etc.) were run through the program. Receiver operator characteristics (ROC) analyses showed that most gene sets were clustered much better than expected by random chance. To test grouping of genes from real microarray data, 221 differentially expressed genes from a microarray experiment were analyzed with CoPub Mapper, which resulted in several relevant clusters of genes with biological process and disease keywords. In addition, all genes versus keywords were hierarchical clustered to reveal a complete grouping of published genes based on co-occurrence. CONCLUSION: The CoPub Mapper program allows for quick and versatile querying of co-published genes and keywords and can be successfully used to cluster predefined groups of genes and microarray data.

Effect of controlled ovarian hyperstimulation in IVF on endometrial gene expression profiles.

Controlled ovarian hyperstimulation (COH) used in IVF produces lower implantation rates per embryo transferred compared to natural cycles utilized in ovum donation, suggesting a suboptimal endometrial development. Endometrial receptivity has recently been investigated in natural menstrual cycles with the aid of microarray technology. The aim of this study is to investigate the impact of COH using urinary gonadotrophins with a long protocol with GnRH agonists without progesterone supplementation (similar to the natural cycle) on endometrial gene expression profiles during the window of implantation by comparing the profiles at day hCG + 7 of COH versus LH + 7 of a previous natural cycle in the same women. For this purpose we have used microarray technology by Affymetrix (GeneChip HG_U133A), which allows more than 22,000 genes to be tested simultaneously. Results were validated by semi-quantitative PCR and quantitative PCR experiments. We found that more than 200 genes showed a differential expression of more than 3-fold when COH and normal cycles were compared at hCG + 7 versus LH + 7. We simultaneously re-analysed the LH + 2 versus LH + 7 endometrial gene expression profiles in previous natural cycles in the same subject using this specific GeneChip, the results obtained were consistent with our own published results. This is the first time that gene expression profiles of the endometrium during COH are reported. The large degree of gene expression disturbance is surprising and highlights the need for further efforts to optimize COH protocols.

Abnormal gene expression profiles in human ovaries from polycystic ovary syndrome patients.

Polycystic ovary syndrome (PCOS) represents the most common cause of anovulatory infertility and affects 5-10% of women of reproductive age. The etiology of PCOS is still unknown. The current study is the first to describe consistent differences in gene expression profiles in human ovaries comparing PCOS patients vs. healthy normoovulatory individuals. The microarray analysis of PCOS vs. normal ovaries identifies dysregulated expression of genes encoding components of several biological pathways or systems such as Wnt signaling, extracellular matrix components, and immunological factors. Resulting data may provide novel clues for ovarian dysfunction in PCOS. Intriguingly, the gene expression profiles of ovaries from (long-term) androgen-treated female-to-male transsexuals (TSX) show considerable overlap with PCOS. This observation provides supportive evidence that androgens play a key role in the pathogenesis of PCOS. Presented data may contribute to a better understanding of dysregulated pathways in PCOS, which might ultimately reveal novel leads for therapeutic intervention.

Gene expression profiling of human endometrial receptivity on days LH+2 versus LH+7 by microarray technology.

In humans, embryonic implantation and reproduction depends on the interaction of the embryo with the receptive endometrium. To gain a global molecular understanding of human endometrial receptivity, we compared gene expression profiles of pre-receptive (day LH+2) versus receptive (LH+7) endometria obtained from the same fertile woman (n = 5) in the same menstrual cycle in five independent experiments. Biopsies were analysed using the Affymetrix HG-U95A array, a DNA chip containing approximately 12,000 genes. Using the pre-defined criteria of a fold change >/=3 in at least four out of five women, we identified 211 regulated genes. Of these, 153 were up-regulated at LH+7 versus LH+2, whereas 58 were down-regulated. Amongst these 211 regulated genes, we identified genes that were known to play a role in the development of a receptive endometrium, and genes for which a role in endometrial receptivity, or even endometrial expression, has not been previously described. Validation of array data was accomplished by mRNA quantification by real time quantitative fluorescent PCR (Q-PCR) of three up-regulated [glutathione peroxidase 3 (GPx-3), claudin 4 (claudin-4) and solute carrier family 1 member 1 (SLC1A1)] genes in independent LH+2 versus LH+7 endometrial samples from fertile women (n = 3) and the three up-regulated genes throughout the menstrual cycle (n = 15). Human claudin-4 peaks specifically during the implantation window, whereas GPx-3 and SLC1A1 showed highest expression in the late secretory phase. In-situ hybridization (ISH) experiments showed that GPx-3 and SLC1A1 expression was restricted to glandular and luminal epithelial cells during the mid- and late luteal phase. The present work adds new and important data in this field, and highlights the complexity of studying endometrial receptivity even using global gene-expression analysis.