Culture free microbiology:A new approach to rapid eubacterial molecular diagnostics and clinical microbiota characterization

Savelkoul, P.H.M. [Promotor]Vandenbroucke-Grauls, C.M.J.E. [Promotor]Bodegraven, A.A. van [Copromotor

TreeSeq, a Fast and Intuitive Tool for Analysis of Whole Genome and Metagenomic Sequence Data

Next-generation sequencing is not yet commonly used in clinical laboratories because of a lack of simple and intuitive tools. We developed a software tool (TreeSeq) with a quaternary tree search structure for the analysis of sequence data. This permits rapid searches for sequences of interest in large datasets. We used TreeSeq to screen a gut microbiota metagenomic dataset and a whole genome sequencing (WGS) dataset of a strain of Klebsiella pneumoniae for antibiotic resistance genes and compared the results with BLAST and phenotypic resistance determination. TreeSeq was more than thirty times faster than BLAST and accurately detected resistance gene sequences in complex metagenomic data and resistance genes corresponding with the phenotypic resistance pattern of the Klebsiella strain. Resistance genes found by TreeSeq were visualized as a gene coverage heat map, aiding in the interpretation of results. TreeSeq brings analysis of metagenomic and WGS data within reach of clinical diagnostics

Evaluation of an optimal preparation of human standardized fecal inocula for in vitro fermentation studies

This study investigated the optimal preservation approach to prepare human feces as inoculum for in vitro fermentations as an alternative to the use of fresh feces. The four treatments studied were: Treatment 1) fresh feces resuspended in dialysate solution + glycerol; Treatment 2) fresh feces resuspended in dialysate solution + glycerol and then stored at -80 degrees C; Treatment 3) fecal sample frozen with 15 g glycerol; and Treatment 4) fecal sample frozen. All the treatments contained 8.75 g of feces, 3.5 ml dialysate and 4.9 ml glycerol when inoculated in TIM-2 in vitro system. Treatment 1 (fresh fecal preparation) was used as a reference. The effects were evaluated in terms of i) metabolic activity and ii) composition of the microbiota using fermentation experiments in the TIM-2 in vitro system. In all treatments, high levels of acetate were produced followed by n-butyrate and propionate. However, the metabolic activity of the bacteria, in terms of short-chain fatty acid production, was affected by the different treatments. Microbiota composition was analyzed using the IS-pro profiling technique. Diversity in Actinobacteria, Firmicutes, Fusobacteria and Verrucomicrobia and Proteobacteria groups seemed to be preserved in all treatments whereas. it was observed to decline in the Bacteroidetes group. Preparing a human fecal inoculum resuspended in dialysate solution with glycerol and then stored at 80 degrees C showed high similarities to the results obtained with fresh feces, and is proposed as the optimal way to freeze fecal material as an alternative to fresh feces for in vitro fermentation studies

Robust Microbiota-Based Diagnostics for Inflammatory Bowel Disease

Strong evidence suggests that the gut microbiota is altered in inflammatory bowel disease (IBD), indicating its potential role in noninvasive diagnostics. However, no clinical applications are currently used for routine patient care. The main obstacle to implementing a gut microbiota test for IBD is the lack of standardization, which leads to high interlaboratory variation. We studied the between-hospital and between-platform batch effects and their effects on predictive accuracy for IBD. Fecal samples from 91 pediatric IBD patients and 58 healthy children were collected. IS-pro, a standardized technique designed for routine microbiota profiling in clinical settings, was used for microbiota composition characterization. Additionally, a large synthetic data set was used to simulate various perturbations and study their effects on the accuracy of different classifiers. Perturbations were validated in two replicate data sets, one processed in another laboratory and the other with a different analysis platform. The type of perturbation determined its effect on predictive accuracy. Real-life perturbations induced by between-platform variation were significantly greater than those caused by between-laboratory variation. Random forest was found to be robust to both simulated and observed perturbations, even when these perturbations had a dramatic effect on other classifiers. It achieved high accuracy both when cross-validated within the same data set and when using data sets analyzed in different laboratories. Robust clinical predictions based on the gut microbiota can be performed even when samples are processed in different hospitals. This study contributes to the effort to develop a universal IBD test that would enable simple diagnostics and disease activity monitoring

Composition and diversity of the duodenal mucosa-associated microbiome in children with untreated coeliac disease

BACKGROUND: Intestinal microbiome may play a role in the pathogenesis of coeliac disease (CD). Studies comparing intestinal microbiome in children with and without CD are contradictory. AIM: To compare the composition and diversity of the duodenal mucosa-associated microbiome in children with untreated CD and control children without CD and to identify specific gut bacteria associated with CD at diagnosis. METHODS: Total microbiome profile in small bowel biopsies of 42 children (21 with untreated CD and 21 age-matched controls) were analyzed by means of IS-pro, a 16S-23S interspacer (IS) region-based profiling method. RESULTS: Both groups showed a similar mucosa-associated microbiome pattern and diversity, with high concentrations of the genera Streptococcus, Lactobacillus, and Clostridium. CONCLUSION: Mucosa-associated duodenal microbiome composition and diversity did not differ between children with untreated CD and control children. Duodenal mucosa-associated bacteria do not seem to play an important role in the pathogenesis of CD

Robust Microbiota-Based Diagnostics for Inflammatory Bowel Disease

Strong evidence suggests that the gut microbiota is altered in inflammatory bowel disease (IBD), indicating its potential role in noninvasive diagnostics. However, no clinical applications are currently used for routine patient care. The main obstacle to implementing a gut microbiota test for IBD is the lack of standardization, which leads to high interlaboratory variation. We studied the between-hospital and between-platform batch effects and their effects on predictive accuracy for IBD. Fecal samples from 91 pediatric IBD patients and 58 healthy children were collected. IS-pro, a standardized technique designed for routine microbiota profiling in clinical settings, was used for microbiota composition characterization. Additionally, a large synthetic data set was used to simulate various perturbations and study their effects on the accuracy of different classifiers. Perturbations were validated in two replicate data sets, one processed in another laboratory and the other with a different analysis platform. The type of perturbation determined its effect on predictive accuracy. Real-life perturbations induced by between-platform variation were significantly greater than those caused by between-laboratory variation. Random forest was found to be robust to both simulated and observed perturbations, even when these perturbations had a dramatic effect on other classifiers. It achieved high accuracy both when cross-validated within the same data set and when using data sets analyzed in different laboratories. Robust clinical predictions based on the gut microbiota can be performed even when samples are processed in different hospitals. This study contributes to the effort to develop a universal IBD test that would enable simple diagnostics and disease activity monitoring