Jeroen Raes

Bio: Jeroen Raes is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: Microbiome & Gut flora. The author has an hindex of 84, co-authored 240 publications receiving 66805 citations. Previous affiliations of Jeroen Raes include Flanders Institute for Biotechnology & Université catholique de Louvain.

Genetics of human gut microbiome composition

Abstract: To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed whole-genome genotypes and 16S fecal microbiome data from 18,473 individuals (25 cohorts) Microbial composition showed high variability across cohorts: we detected only 9 out of 410 genera in more than 95% of the samples A genome-wide association study (GWAS) of host genetic variation in relation to microbial taxa identified 30 loci affecting microbome taxa at a genome-wide significant (P

Microbiome-based companion diagnostics: no longer science fiction?

Abstract: In the last decade, our knowledge on the role of the gut microbiome in health and disease has greatly increased, accompanied by an unseen hype around both its diagnostic and therapeutic potential. Yet, one application area of the microbiome has thus far remained understudied: its role as guidance for therapeutic decisions, treatment monitoring and prediction of response. In this issue of Gut , Mondot et al 1 investigate to what extent the microbiome can both inform us on as well as contribute to treatment outcome in resection surgery for Crohn's disease (CD). Although often the only resort next to dilatation,2 this intervention is not curative, with first-year endoscopic recurrence rates at 28–93% and frequent necessity of reoperation.3 As such, there is an important need for effective postoperative maintenance strategies and predictions for postoperative outcome. In a longitudinal study of both the faecal and mucosa-adherent microbiota in 20 patients undergoing resection surgery, Mondot et al describe the microbial groups recolonising the intestinal lining around the anastomosis and show different trajectories in recurring patients versus those in remission; the latter were found to exhibit …

NoDe: a fast error-correction algorithm for pyrosequencing amplicon reads

Abstract: The popularity of new sequencing technologies has led to an explosion of possible applications, including new approaches in biodiversity studies However each of these sequencing technologies suffers from sequencing errors originating from different factors For 16S rRNA metagenomics studies, the 454 pyrosequencing technology is one of the most frequently used platforms, but sequencing errors still lead to important data analysis issues (eg in clustering in taxonomic units and biodiversity estimation) Moreover, retaining a higher portion of the sequencing data by preserving as much of the read length as possible while maintaining the error rate within an acceptable range, will have important consequences at the level of taxonomic precision The new error correction algorithm proposed in this work - NoDe (Noise Detector) - is trained to identify those positions in 454 sequencing reads that are likely to have an error, and subsequently clusters those error-prone reads with correct reads resulting in error-free representative read A benchmarking study with other denoising algorithms shows that NoDe can detect up to 75% more errors in a large scale mock community dataset, and this with a low computational cost compared to the second best algorithm considered in this study The positive effect of NoDe in 16S rRNA studies was confirmed by the beneficial effect on the precision of the clustering of pyrosequencing reads in operational taxonomic units NoDe was shown to be a computational efficient denoising algorithm for pyrosequencing reads, producing the lowest error rates in an extensive benchmarking study with other denoising algorithms

Dietary emulsifiers alter composition and activity of the human gut microbiota in vitro, irrespective of chemical or natural emulsifier origin

Abstract: The use of additives in food products has become an important public health concern In recent reports, dietary emulsifiers have been shown to affect the gut microbiota, contributing to a pro-inflammatory phenotype and metabolic syndrome So far, it is not yet known whether similar microbiome shifts are observable for a more diverse set of emulsifier types and to what extent these effects vary with the unique features of an individual’s microbiome To bridge this gap, we investigated the effect of five dietary emulsifiers on the fecal microbiota from 10 human individuals upon a 48 hour exposure Community structure was assessed with quantative microbial profiling, functionality was evaluated by measuring fermentation metabolites and pro-inflammatory properties were assessed with the phylogenetic prediction algorythm PICRUSt, together with a TLR5 reporter cell assay for flagellin A comparison was made between two mainstream chemical emulsifiers (carboxymethylcellulose and P80), a natural extract (soy lecithin) and biotechnological emulsifiers (sophorolipids and rhamnolipids) While fecal microbiota responded in a donor-dependent manner to the different emulsifiers, profound differences between emulsifier were observed Rhamnolipids, sophorolipids and soy lecithin eliminated 91% ± 0%, 89% ± 1% and 87% ± 1% of the viable bacterial population after 48 hours, yet they all selectively increased the proportional abundance of putative pathogens Moreover, profound shifts in butyrate (−96% ± 6 %, −73% ± 24% and −34 ± 25% respectively) and propionate (+13% ± 24 %, +88% ± 50% and +29% ± 16% respectively) production were observed for these emulsifiers Phylogenetic prediction indicated higher motility, which was, however, not confirmed by increased flagellin levels using the TLR5 reporter cell assay We conclude that dietary emulsifiers can severely impact the gut microbiota and this seems to be proportional to their emulsifying strength, rather than emulsifier type or origin As biotechnological emulsifiers were especially more impactful than chemical emulsifiers, caution is warranted when considering them as more natural alternatives for clean label strategies

Tracking humans and microbes.

Abstract: The Human Microbiome Project put the health-associated microbes found in humans on centre stage. The project’s second phase shows how microbial disturbance in disease is linked to host processes. The second phase of studies of the Human Microbiome Project.

DADA2: High-resolution sample inference from Illumina amplicon data

Abstract: We present the open-source software package DADA2 for modeling and correcting Illumina-sequenced amplicon errors (https://github.com/benjjneb/dada2). DADA2 infers sample sequences exactly and resolves differences of as little as 1 nucleotide. In several mock communities, DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.

The Theory of Island Biogeography

Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

UPARSE: highly accurate OTU sequences from microbial amplicon reads

Abstract: Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.

phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.

Abstract: Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.