When old metagenomic data meet newly sequenced genomes, a case study

Are the predicted known bacterial strains in a sample really present? A case study

With mutations constantly accumulating in bacterial genomes, it is unclear whether the previously identified bacterial strains are really present in an extant sample. To address this question, we did a case study on the known strains of the bacterial species S. aureus and S. epidermis in 68 atopic dermatitis shotgun metagenomic samples. We evaluated the likelihood of the presence of all sixteen known strains predicted in the original study and by two popular tools in this study. We found that even with the same tool, only two known strains were predicted by the original study and this study. Moreover, none of the sixteen known strains was likely present in these 68 samples. Our study thus indicates the limitation of the known-strain-based studies, especially those on rapidly evolving bacterial species. It implies the unlikely presence of the previously identified known strains in a current environmental sample. It also called for de novo bacterial strain identification directly from shotgun metagenomic reads.

Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes

Metagenomics is increasingly used to describe microbial communities in biological specimens. Ideally, the steps involved in the processing of the biological specimens should not change the microbiome composition in a way that it could lead to false interpretations of inferred microbial community composition. Common steps in sample preparation include sample collection, storage, DNA isolation, library preparation, and DNA sequencing. Here, we assess the effect of three library preparation kits and two DNA sequencing platforms. Of the library preparation kits, one involved a PCR step (Nextera), and two were PCR free (NEXTflex and KAPA). We sequenced the libraries on Illumina HiSeq and NextSeq platforms. As example microbiomes, two pig fecal samples and two sewage samples of which aliquots were stored at different storage conditions (immediate processing and storage at -80°C) were assessed. All DNA isolations were performed in duplicate, totaling 80 samples, excluding controls. We found that both library preparation and sequencing platform had systematic effects on the inferred microbial community composition. The different sequencing platforms introduced more variation than library preparation and freezing the samples. The results highlight that all sample processing steps need to be considered when comparing studies. Standardization of sample processing is key to generating comparable data within a study, and comparisons of differently generated data, such as in a meta-analysis, should be performed cautiously. IMPORTANCE Previous research has reported effects of sample storage conditions and DNA isolation procedures on metagenomics-based microbiome composition; however, the effect of library preparation and DNA sequencing in metagenomics has not been thoroughly assessed. Here, we provide evidence that library preparation and sequencing platform introduce systematic biases in the metagenomic-based characterization of microbial communities. These findings suggest that library preparation and sequencing are important parameters to keep consistent when aiming to detect small changes in microbiome community structure. Overall, we recommend that all samples in a microbiome study are processed in the same way to limit unwanted variations that could lead to false conclusions. Furthermore, if we are to obtain a more holistic insight from microbiome data generated around the world, we will need to provide more detailed sample metadata, including information about the different sample processing procedures, together with the DNA sequencing data at the public repositories.

ganon: precise metagenomics classification against large and up-to-date sets of reference sequences

MOTIVATION

The exponential growth of assembled genome sequences greatly benefits metagenomics studies. However, currently available methods struggle to manage the increasing amount of sequences and their frequent updates. Indexing the current RefSeq can take days and hundreds of GB of memory on large servers. Few methods address these issues thus far, and even though many can theoretically handle large amounts of references, time/memory requirements are prohibitive in practice. As a result, many studies that require sequence classification use often outdated and almost never truly up-to-date indices.

RESULTS

Motivated by those limitations, we created ganon, a k-mer-based read classification tool that uses Interleaved Bloom Filters in conjunction with a taxonomic clustering and a k-mer counting/filtering scheme. Ganon provides an efficient method for indexing references, keeping them updated. It requires <55 min to index the complete RefSeq of bacteria, archaea, fungi and viruses. The tool can further keep these indices up-to-date in a fraction of the time necessary to create them. Ganon makes it possible to query against very large reference sets and therefore it classifies significantly more reads and identifies more species than similar methods. When classifying a high-complexity CAMI challenge dataset against complete genomes from RefSeq, ganon shows strongly increased precision with equal or better sensitivity compared with state-of-the-art tools. With the same dataset against the complete RefSeq, ganon improved the F1-score by 65% at the genus level. It supports taxonomy- and assembly-level classification, multiple indices and hierarchical classification.

AVAILABILITY AND IMPLEMENTATION

The software is open-source and available at: https://gitlab.com/rki_bioinformatics/ganon.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Divergent Effect of Cigarette Smoke on Innate Immunity in Inflammatory Bowel Disease: A Nicotine-Infection Interaction

Cigarette smoke (CS) has adverse effects in patients with Crohn’s disease (CD), an inflammatory bowel disease (IBD) that has been associated with microbial infection, immuno-dysregulation, and mucosal dysfunction. However, CS seems to provide relief and protection to patients with another IBD known as ulcerative colitis (UC). These two subsets are featured as M1- and M2-mediated responses, respectively. Nicotine is the most active, addictive, and studied ingredient in CS. The mechanism of how nicotine and/or other CS ingredients induce pro-inflammatory or anti-inflammatory phenotypes in IBD patients remains under investigation. Our most recent in vitro nicotine study provided significant insights toward understanding the contradictory effects of nicotine on IBD patients, and it elucidated the mechanistic role of α7nAChR in modulation of macrophages in tobacco smokers. Shifting the beneficial effect of nicotine to a harmful outcome in CD patients was linked to a nicotine-microbe interaction that supports a microbial etiology in CD pathogenesis. Among the most debated pathogens in CD etiology is Mycobacterium avium subspecies paratuberculosis (MAP). Other studies associated nicotine with upregulation of miR-124 expression in macrophages, which led to anti-inflammatory response. This review discusses published work on the role of nicotine in modulation of the innate immune response and subsequent signaling in macrophages in IBD subsets.