Analysis of a gene panel for targeted sequencing of colorectal cancer samples.

Colorectal cancer (CRC) is a leading cause of death worldwide. Surgical intervention is a successful treatment for stage I patients, whereas other more advanced cases may require adjuvant chemotherapy. The selection of effective adjuvant treatments remains, however, challenging. Accurate patient stratification is necessary for the identification of the subset of patients likely responding to treatment, while sparing others from pernicious treatment. Targeted sequencing approaches may help in this regard, enabling rapid genetic investigation, and at the same time easily applicable in routine diagnosis. We propose a set of guidelines for the identification, including variant calling and filtering, of somatic mutations driving tumorigenesis in the absence of matched healthy tissue. We also discuss the inclusion criteria for the generation of our gene panel. Furthermore, we evaluate the prognostic impact of individual genes, using Cox regression models in the context of overall survival and disease-free survival. These analyses confirmed the role of commonly used biomarkers, and shed light on controversial genes such as CYP2C8. Applying those guidelines, we created a novel gene panel to investigate the onset and progression of CRC in 273 patients. Our comprehensive biomarker set includes 266 genes that may play a role in the progression through the different stages of the disease. Tracing the developmental state of the tumour, and its resistances, is instrumental in patient stratification and reliable decision making in precision clinical practice.

Transcriptional interactions suggest niche segregation among microorganisms in the human gut.

The human gastrointestinal (GI) tract is the habitat for hundreds of microbial species, of which many cannot be cultivated readily, presumably because of the dependencies between species1. Studies of microbial co-occurrence in the gut have indicated community substructures that may reflect functional and metabolic interactions between cohabiting species2,3. To move beyond species co-occurrence networks, we systematically identified transcriptional interactions between pairs of coexisting gut microbes using metagenomics and microarray-based metatranscriptomics data from 233 stool samples from Europeans. In 102 significantly interacting species pairs, the transcriptional changes led to a reduced expression of orthologous functions between the coexisting species. Specific species-species transcriptional interactions were enriched for functions important for H2 and CO2 homeostasis, butyrate biosynthesis, ATP-binding cassette (ABC) transporters, flagella assembly and bacterial chemotaxis, as well as for the metabolism of carbohydrates, amino acids and cofactors. The analysis gives the first insight into the microbial community-wide transcriptional interactions, and suggests that the regulation of gene expression plays an important role in species adaptation to coexistence and that niche segregation takes place at the transcriptional level.

An integrated catalog of reference genes in the human gut microbiome.

Many analyses of the human gut microbiome depend on a catalog of reference genes. Existing catalogs for the human gut microbiome are based on samples from single cohorts or on reference genomes or protein sequences, which limits coverage of global microbiome diversity. Here we combined 249 newly sequenced samples of the Metagenomics of the Human Intestinal Tract (MetaHit) project with 1,018 previously sequenced samples to create a cohort from three continents that is at least threefold larger than cohorts used for previous gene catalogs. From this we established the integrated gene catalog (IGC) comprising 9,879,896 genes. The catalog includes close-to-complete sets of genes for most gut microbes, which are also of considerably higher quality than in previous catalogs. Analyses of a group of samples from Chinese and Danish individuals using the catalog revealed country-specific gut microbial signatures. This expanded catalog should facilitate quantitative characterization of metagenomic, metatranscriptomic and metaproteomic data from the gut microbiome to understand its variation across populations in human health and disease.

Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes.

Most current approaches for analyzing metagenomic data rely on comparisons to reference genomes, but the microbial diversity of many environments extends far beyond what is covered by reference databases. De novo segregation of complex metagenomic data into specific biological entities, such as particular bacterial strains or viruses, remains a largely unsolved problem. Here we present a method, based on binning co-abundant genes across a series of metagenomic samples, that enables comprehensive discovery of new microbial organisms, viruses and co-inherited genetic entities and aids assembly of microbial genomes without the need for reference sequences. We demonstrate the method on data from 396 human gut microbiome samples and identify 7,381 co-abundance gene groups (CAGs), including 741 metagenomic species (MGS). We use these to assemble 238 high-quality microbial genomes and identify affiliations between MGS and hundreds of viruses or genetic entities. Our method provides the means for comprehensive profiling of the diversity within complex metagenomic samples.

Hyperactivity of the Ero1α oxidase elicits endoplasmic reticulum stress but no broad antioxidant response.

Oxidizing equivalents for the process of oxidative protein folding in the endoplasmic reticulum (ER) of mammalian cells are mainly provided by the Ero1α oxidase. The molecular mechanisms that regulate Ero1α activity in order to harness its oxidative power are quite well understood. However, the overall cellular response to oxidative stress generated by Ero1α in the lumen of the mammalian ER is poorly characterized. Here we investigate the effects of overexpressing a hyperactive mutant (C104A/C131A) of Ero1α. We show that Ero1α hyperactivity leads to hyperoxidation of the ER oxidoreductase ERp57 and induces expression of two established unfolded protein response (UPR) targets, BiP (immunoglobulin-binding protein) and HERP (homocysteine-induced ER protein). These effects could be reverted or aggravated by N-acetylcysteine and buthionine sulfoximine, respectively. Because both agents manipulate the cellular glutathione redox buffer, we conclude that the observed effects of Ero1α-C104A/C131A overexpression are likely caused by an oxidative perturbation of the ER glutathione redox buffer. In accordance, we show that Ero1α hyperactivity affects cell viability when cellular glutathione levels are compromised. Using microarray analysis, we demonstrate that the cell reacts to the oxidative challenge caused by Ero1α hyperactivity by turning on the UPR. Moreover, this analysis allowed the identification of two new targets of the mammalian UPR, CRELD1 and c18orf45. Interestingly, a broad antioxidant response was not induced. Our findings suggest that the hyperoxidation generated by Ero1α-C104A/C131A is addressed in the ER lumen and is unlikely to exert oxidative injury throughout the cell.

Deciphering diseases and biological targets for environmental chemicals using toxicogenomics networks.

Exposure to environmental chemicals and drugs may have a negative effect on human health. A better understanding of the molecular mechanism of such compounds is needed to determine the risk. We present a high confidence human protein-protein association network built upon the integration of chemical toxicology and systems biology. This computational systems chemical biology model reveals uncharacterized connections between compounds and diseases, thus predicting which compounds may be risk factors for human health. Additionally, the network can be used to identify unexpected potential associations between chemicals and proteins. Examples are shown for chemicals associated with breast cancer, lung cancer and necrosis, and potential protein targets for di-ethylhexyl-phthalate, 2,3,7,8-tetrachlorodibenzo-p-dioxin, pirinixic acid and permethrine. The chemical-protein associations are supported through recent published studies, which illustrate the power of our approach that integrates toxicogenomics data with other data types.

Analysis of gene expression profiles of microdissected cell populations indicates that testicular carcinoma in situ is an arrested gonocyte.

Testicular germ cell cancers in young adult men derive from a precursor lesion called carcinoma in situ (CIS) of the testis. CIS cells were suggested to arise from primordial germ cells or gonocytes. However, direct studies on purified samples of CIS cells are lacking. To overcome this problem, we performed laser microdissection of CIS cells. Highly enriched cell populations were obtained and subjected to gene expression analysis. The expression profile of CIS cells was compared with microdissected gonocytes, oogonia, and cultured embryonic stem cells with and without genomic aberrations. Three samples of each tissue type were used for the analyses. Unique expression patterns for these developmentally very related cell types revealed that CIS cells were very similar to gonocytes because only five genes distinguished these two cell types. We did not find indications that CIS was derived from a meiotic cell, and the similarity to embryonic stem cells was modest compared with gonocytes. Thus, we provide new evidence that the molecular phenotype of CIS cells is similar to that of gonocytes. Our data are in line with the idea that CIS cells may be gonocytes that survived in the postnatal testis. We speculate that disturbed development of somatic cells in the fetal testis may play a role in allowing undifferentiated cells to survive in the postnatal testes. The further development of CIS into invasive germ cell tumors may depend on signals from their postpubertal niche of somatic cells, including hormones and growth factors from Leydig and Sertoli cells.