Mining RNA-seq data for infections and contaminations

Computational Integration of HSV-1 Multi-omics Data

Functional genomics techniques based on next-generation sequencing provide new avenues for studying host responses to viral infections at multiple levels, including transcriptional and translational processes and chromatin organization. This chapter provides an overview on the computational integration of multiple types of "omics" data on lytic herpes simplex virus 1 (HSV-1) infection. It summarizes methods developed and applied in two publications that combined 4sU-seq for studying de novo transcription, ribosome profiling for investigating active translation, RNA-seq of subcellular RNA fractions for determining subcellular location of transcripts, and ATAC-seq for profiling chromatin accessibility genome-wide. These studies revealed an unprecedented disruption of transcription termination in HSV-1 infection resulting in widespread read-through transcription beyond poly(A) sites for most but not all host genes. This impacts chromatin architecture by increasing chromatin accessibility selectively in downstream regions of affected genes. In this way, computational integration of multi-omics data identified novel and unsuspected mechanisms at play in lytic HSV-1 infection.

MetaMap: an atlas of metatranscriptomic reads in human disease-related RNA-seq data

Background

With the advent of the age of big data in bioinformatics, large volumes of data and high-performance computing power enable researchers to perform re-analyses of publicly available datasets at an unprecedented scale. Ever more studies imply the microbiome in both normal human physiology and a wide range of diseases. RNA sequencing technology (RNA-seq) is commonly used to infer global eukaryotic gene expression patterns under defined conditions, including human disease-related contexts; however, its generic nature also enables the detection of microbial and viral transcripts.

Findings

We developed a bioinformatic pipeline to screen existing human RNA-seq datasets for the presence of microbial and viral reads by re-inspecting the non-human-mapping read fraction. We validated this approach by recapitulating outcomes from six independent, controlled infection experiments of cell line models and compared them with an alternative metatranscriptomic mapping strategy. We then applied the pipeline to close to 150 terabytes of publicly available raw RNA-seq data from  more than 17,000 samples from more than 400 studies relevant to human disease using state-of-the-art high-performance computing systems. The resulting data from this large-scale re-analysis are made available in the presented MetaMap resource.

Conclusions

Our results demonstrate that common human RNA-seq data, including those archived in public repositories, might contain valuable information to correlate microbial and viral detection patterns with diverse diseases. The presented MetaMap database thus provides a rich resource for hypothesis generation toward the role of the microbiome in human disease. Additionally, codes to process new datasets and perform statistical analyses are made available.

Transcriptome sequencing reveals high isoform diversity in the ant Formica exsecta

Transcriptome resources for social insects have the potential to provide new insight into polyphenism, i.e., how divergent phenotypes arise from the same genome. Here we present a transcriptome based on paired-end RNA sequencing data for the ant Formica exsecta (Formicidae, Hymenoptera). The RNA sequencing libraries were constructed from samples of several life stages of both sexes and female castes of queens and workers, in order to maximize representation of expressed genes. We first compare the performance of common assembly and scaffolding software (Trinity, Velvet-Oases, and SOAPdenovo-trans), in producing de novo assemblies. Second, we annotate the resulting expressed contigs to the currently published genomes of ants, and other insects, including the honeybee, to filter genes that have annotation evidence of being true genes. Our pipeline resulted in a final assembly of altogether 39,262 mRNA transcripts, with an average coverage of >300X, belonging to 17,496 unique genes with annotation in the related ant species. From these genes, 536 genes were unique to one caste or sex only, highlighting the importance of comprehensive sampling. Our final assembly also showed expression of several splice variants in 6,975 genes, and we show that accounting for splice variants affects the outcome of downstream analyses such as gene ontologies. Our transcriptome provides an outstanding resource for future genetic studies on F. exsecta and other ant species, and the presented transcriptome assembly can be adapted to any non-model species that has genomic resources available from a related taxon.

Functional variants of human papillomavirus type 16 demonstrate host genome integration and transcriptional alterations corresponding to their unique cancer epidemiology

BACKGROUND

Human papillomaviruses (HPVs) are a worldwide burden as they are a widespread group of tumour viruses in humans. Having a tropism for mucosal tissues, high-risk HPVs are detected in nearly all cervical cancers. HPV16 is the most common high-risk type but not all women infected with high-risk HPV develop a malignant tumour. Likely relevant, HPV genomes are polymorphic and some HPV16 single nucleotide polymorphisms (SNPs) are under evolutionary constraint instigating variable oncogenicity and immunogenicity in the infected host.

RESULTS

To investigate the tumourigenicity of two common HPV16 variants, we used our recently developed, three-dimensional organotypic model reminiscent of the natural HPV infectious cycle and conducted various "omics" and bioinformatics approaches. Based on epidemiological studies we chose to examine the HPV16 Asian-American (AA) and HPV16 European Prototype (EP) variants. They differ by three non-synonymous SNPs in the transforming and virus-encoded E6 oncogene where AAE6 is classified as a high- and EPE6 as a low-risk variant. Remarkably, the high-risk AAE6 variant genome integrated into the host DNA, while the low-risk EPE6 variant genome remained episomal as evidenced by highly sensitive Capt-HPV sequencing. RNA-seq experiments showed that the truncated form of AAE6, integrated in chromosome 5q32, produced a local gene over-expression and a large variety of viral-human fusion transcripts, including long distance spliced transcripts. In addition, differential enrichment of host cell pathways was observed between both HPV16 E6 variant-containing epithelia. Finally, in the high-risk variant, we detected a molecular signature of host chromosomal instability, a common property of cancer cells.

CONCLUSIONS

We show how naturally occurring SNPs in the HPV16 E6 oncogene cause significant changes in the outcome of HPV infections and subsequent viral and host transcriptome alterations prone to drive carcinogenesis. Host genome instability is closely linked to viral integration into the host genome of HPV-infected cells, which is a key phenomenon for malignant cellular transformation and the reason for uncontrolled E6 oncogene expression. In particular, the finding of variant-specific integration potential represents a new paradigm in HPV variant biology.

Infer Metagenomic Abundance and Reveal Homologous Genomes Based on the Structure of Taxonomy Tree

Metagenomic research uses sequencing technologies to investigate the genetic biodiversity of microbiomes presented in various ecosystems or animal tissues. The composition of a microbial community is highly associated with the environment in which the organisms exist. As large amount of sequencing short reads of microorganism genomes obtained, accurately estimating the abundance of microorganisms within a metagenomic sample is becoming an increasing challenge in bioinformatics. In this paper, we describe a hierarchical taxonomy tree-based mixture model (HTTMM) for estimating the abundance of taxon within a microbial community by incorporating the structure of the taxonomy tree. In this model, genome-specific short reads and homologous short reads among genomes can be distinguished and represented by leaf and intermediate nodes in the taxonomy tree, respectively. We adopt an expectation-maximization algorithm to solve this model. Using simulated and real-world data, we demonstrate that the proposed method is superior to both flat mixture model and lowest common ancestry-based methods. Moreover, this model can reveal previously unaddressed homologous genomes.

Widespread disruption of host transcription termination in HSV-1 infection

Herpes simplex virus 1 (HSV-1) is an important human pathogen and a paradigm for virus-induced host shut-off. Here we show that global changes in transcription and RNA processing and their impact on translation can be analysed in a single experimental setting by applying 4sU-tagging of newly transcribed RNA and ribosome profiling to lytic HSV-1 infection. Unexpectedly, we find that HSV-1 triggers the disruption of transcription termination of cellular, but not viral, genes. This results in extensive transcription for tens of thousands of nucleotides beyond poly(A) sites and into downstream genes, leading to novel intergenic splicing between exons of neighbouring cellular genes. As a consequence, hundreds of cellular genes seem to be transcriptionally induced but are not translated. In contrast to previous reports, we show that HSV-1 does not inhibit co-transcriptional splicing. Our approach thus substantially advances our understanding of HSV-1 biology and establishes HSV-1 as a model system for studying transcription termination.

Herpes simplex virus 1 (HSV-1) efficiently shuts down host gene expression in infected cells. Here Rutkowski et al. analyse the genome-wide changes in transcription and translation in infected cells, and show that HSV-1 triggers an extensive disruption of transcription termination of cellular genes.

ContextMap 2: fast and accurate context-based RNA-seq mapping

Background

Mapping of short sequencing reads is a crucial step in the analysis of RNA sequencing (RNA-seq) data. ContextMap is an RNA-seq mapping algorithm that uses a context-based approach to identify the best alignment for each read and allows parallel mapping against several reference genomes.

Results

In this article, we present ContextMap 2, a new and improved version of ContextMap. Its key novel features are: (i) a plug-in structure that allows easily integrating novel short read alignment programs with improved accuracy and runtime; (ii) context-based identification of insertions and deletions (indels); (iii) mapping of reads spanning an arbitrary number of exons and indels. ContextMap 2 using Bowtie, Bowtie 2 or BWA was evaluated on both simulated and real-life data from the recently published RGASP study.

Conclusions

We show that ContextMap 2 generally combines similar or higher recall compared to other state-of-the-art approaches with significantly higher precision in read placement and junction and indel prediction. Furthermore, runtime was significantly lower than for the best competing approaches. ContextMap 2 is freely available at http://www.bio.ifi.lmu.de/ContextMap.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0557-5) contains supplementary material, which is available to authorized users.

Metagenomic profiling of known and unknown microbes with microbeGPS

Microbial community profiling identifies and quantifies organisms in metagenomic sequencing data using either reference based or unsupervised approaches. However, current reference based profiling methods only report the presence and abundance of single reference genomes that are available in databases. Since only a small fraction of environmental genomes is represented in genomic databases, these approaches entail the risk of false identifications and often suggest a higher precision than justified by the data. Therefore, we developed MicrobeGPS, a novel metagenomic profiling approach that overcomes these limitations. MicrobeGPS is the first method that identifies microbiota in the sample and estimates their genomic distances to known reference genomes. With this strategy, MicrobeGPS identifies organisms down to the strain level and highlights possibly inaccurate identifications when the correct reference genome is missing. We demonstrate on three metagenomic datasets with different origin that our approach successfully avoids misleading interpretation of results and additionally provides more accurate results than current profiling methods. Our results indicate that MicrobeGPS can enable reference based taxonomic profiling of complex and less characterized microbial communities. MicrobeGPS is open source and available from https://sourceforge.net/projects/microbegps/ as source code and binary distribution for Windows and Linux operating systems.

Association between changes in reproductive activity and D-glucose metabolism in the tephritid fruit fly, Bactrocera dorsalis (Hendel)

Reproduction is an important life process in insects; however, few studies have attempted to demonstrate the association between reproductive activity and energy metabolism. To address this problem, we focused on the reproductive changes in Bactrocera dorsalis males. We analyzed B. dorsalis male gene expression profiles during mating (DM), 3 h after mating (A3HM) and 12 h after mating (A12HM). Gene annotation and pathway analyses of differentially expressed genes show that galactose metabolism and the starch and sucrose metabolism pathway activities were significantly higher in A12HM group. Moreover, the maltase D gene was the most strongly up-regulated gene. The D-glucose levels were significantly higher in A12HM group. Maltase D expression level was significantly higher in males reared with sucrose. Body weights of the males reared with D-glucose and sucrose were significantly higher than those of the males reared with yeast extract. We observed more mated males from the groups fed sucrose and D-glucose than from those fed yeast extract. The D-glucose levels in individual males were highest at 18:00 h, when flies exhibit the most active mating behavior. This study shows that the maltase D gene and D-glucose are the critical gene and substrate, respectively, in male B. dorsalis mating process.

Reagent and laboratory contamination can critically impact sequence-based microbiome analyses

Background

The study of microbial communities has been revolutionised in recent years by the widespread adoption of culture independent analytical techniques such as 16S rRNA gene sequencing and metagenomics. One potential confounder of these sequence-based approaches is the presence of contamination in DNA extraction kits and other laboratory reagents.

Results

In this study we demonstrate that contaminating DNA is ubiquitous in commonly used DNA extraction kits and other laboratory reagents, varies greatly in composition between different kits and kit batches, and that this contamination critically impacts results obtained from samples containing a low microbial biomass. Contamination impacts both PCR-based 16S rRNA gene surveys and shotgun metagenomics. We provide an extensive list of potential contaminating genera, and guidelines on how to mitigate the effects of contamination.

Conclusions

These results suggest that caution should be advised when applying sequence-based techniques to the study of microbiota present in low biomass environments. Concurrent sequencing of negative control samples is strongly advised.

Electronic supplementary material

The online version of this article (doi:10.1186/s12915-014-0087-z) contains supplementary material, which is available to authorized users.

Thermophilic microbial cellulose decomposition and methanogenesis pathways recharacterized by metatranscriptomic and metagenomic analysis

The metatranscriptomic recharacterization in the present study captured microbial enzymes at the unprecedented scale of 40,000 active genes belonged to 2,269 KEGG functions were identified. The novel information obtained herein revealed interesting patterns and provides an initial transcriptional insight into the thermophilic cellulose methanization process. Synergistic beta-sugar consumption by Thermotogales is crucial for cellulose hydrolysis in the thermophilic cellulose-degrading consortium because the primary cellulose degraders Clostridiales showed metabolic incompetence in subsequent beta-sugar pathways. Additionally, comparable transcription of putative Sus-like polysaccharide utilization loci (PULs) was observed in an unclassified order of Bacteroidetes suggesting the importance of PULs mechanism for polysaccharides breakdown in thermophilic systems. Despite the abundance of acetate as a fermentation product, the acetate-utilizing Methanosarcinales were less prevalent by 60% than the hydrogenotrophic Methanobacteriales. Whereas the aceticlastic methanogenesis pathway was markedly more active in terms of transcriptional activities in key genes, indicating that the less dominant Methanosarcinales are more active than their hydrogenotrophic counterparts in methane metabolism. These findings suggest that the minority of aceticlastic methanogens are not necessarily associated with repressed metabolism, in a pattern that was commonly observed in the cellulose-based methanization consortium, and thus challenge the causal likelihood proposed by previous studies.