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Summary Reliability and reproducibility of transcriptomics‐based studies are dependent on RNA integrity. In microbial ecology, microfluidics‐based techniques, such as the Ribosomal Integrity Number (RIN), targeting rRNA are currently the only approaches to evaluate RNA integrity. However, the relationship between rRNA and mRNA integrity is unknown. Here, we present an integrity index, the Ratio Amplicon, R amp, adapted from human clinical studies, to directly monitor mRNA integrity from complex environmental samples. We show, in a suite of experimental degradations of RNA extracted from sediment, that while the RIN generally reflected the degradation status of RNA the R amp mapped mRNA degradation better. Furthermore, we examined the effect of degradation on transcript community structure by amplicon sequencing of 16S rRNA, amoA and glnA transcripts. We successfully sequenced transcripts for all three targets even from highly‐degraded RNA samples. While RNA degradation changed the community structure of the mRNA profiles, no changes were observed for the 16S rRNA transcript profiles. Since both RT‐Q‐PCR and sequencing results were obtained, even from highly degraded samples, we strongly recommend evaluating RNA integrity prior to downstream processing to ensure meaningful results. For this, both the RIN and R amp are useful, with the R amp better evaluating mRNA integrity in this study.

Additional file 4. Supplementary Tables 1, 2, 3.

Additional file 2: Fig. S2. (.pdf) Hierarchical dendrogram showing the classification of individual food groups to larger level food groups, based on the National Diet and Nutrition Survey

Background & Aims: \ud It is not clear whether alterations in the intestinal microbiota of children with celiac disease cause the disease or are a result of disease and/or its treatment with gluten-free diet (GFD).\ud \ud Methods: \ud We obtained 167 fecal samples from 141 children (20 with new-onset celiac disease, 45 treated with a GFD, 57 healthy children, and 19 unaffected siblings of children with celiac disease) in Glasgow, Scotland. Samples were analyzed by 16S rRNA sequencing and diet-related metabolites were measured by gas chromatography. We obtained fecal samples from 13 of the children with new-onset CD after 6 and 12 months on GFD. Relationships between microbiota with diet composition, gastrointestinal function, and biomarkers of GFD compliance were explored.\ud \ud Results: \ud Microbiota α diversity did not differ among groups. Microbial dysbiosis was not observed in children with new-onset celiac disease. In contrast, 2.8% (Bray-Curtis dissimilarity index, P=.025) and 2.5% (UniFrac distances, P=.027) of the variation in microbiota composition could be accounted for by the GFD. Between 3% to 5% of all taxa differed among all group comparisons. Eleven distinctive operational taxonomic units composed a microbe signature specific to celiac disease with high diagnostic probability. Most of the operational taxonomic units that differed between patients on GFD with new-onset celiac disease vs healthy children were associated with nutrient and food group intake (from 75% to 94%), and with biomarkers of gluten ingestion. Fecal levels of butyrate and ammonia decreased during the GFD.\ud \ud Conclusions: \ud Although several alterations in the intestinal microbiota of children with established celiac disease appear to be effects of a GFD, there are specific bacteria that are distinct biomarkers of celiac disease. Studies are needed to determine whether these bacteria contribute to pathogenesis of celiac disease.

Background:\ud \ud Exclusive enteral nutrition (EEN) is an effective treatment for Crohn's disease.\ud \ud Aims:\ud \ud To investigate the hypothesis that ingredients of EEN formulas are unlikely to initiate a disease flare and that their dietary elimination is not essential for disease amelioration.\ud \ud Methods:\ud \ud We performed compositional analysis of EEN formulas with evidence of efficacy in management of active Crohn's disease. Macronutrient content was compared against the dietary reference values (DRV), the UK National Diet and Nutrition Survey (NDNS) and intake of Crohn's disease children. Food additives were cross‐referenced against the FAO/WHO database.\ud \ud Results:\ud \ud Sixty‐one formulas were identified with variable composition (carbohydrates [22.8%‐89.3%], protein [7.8%‐30.1%], fat [0%‐52.5%]). Maltodextrin, milk protein and vegetable/plant oils were the commonest macronutrient sources. Their n‐6:n‐3 fatty acid ratio varied from 0.25 to 46.5. 56 food additives were identified (median per formula: 11). All formulas were lactose‐free, gluten‐free, and 82% lacked fibre. The commonest food additives were emulsifiers, stabilisers, antioxidants, acidity regulators and thickeners. Food additives, implicated in Crohn's disease aetiology, were present in formulas (modified starches [100%], carrageenan [22%], carboxymethyl cellulose [13%] and polysorbate 80 [5%]). Remission rates did not differ between EEN formulas with and without those food additives. Analysis including only formulas from randomised controlled trials (RCTs) retained in the latest Cochrane meta‐analysis produced similar findings. EEN formulas contained less energy from saturated fat than NDNS intake.\ud \ud Conclusion:\ud \ud We have identified food ingredients which are present in EEN formulas that are effective in Crohn's disease and challenge perceptions that these ingredients might be harmful.

The stomach is inhabited by diverse microbial communities, co-existing in a dynamic balance. Long-term use of drugs such as proton pump inhibitors (PPIs), or bacterial infection such as Helicobacter pylori, cause significant microbial alterations. Yet, studies revealing how the commensal bacteria re-organize, due to these perturbations of the gastric environment, are in early phase and rely principally on linear techniques for multivariate analysis. Here we disclose the importance of complementing linear dimensionality reduction techniques with nonlinear ones to unveil hidden patterns that remain unseen by linear embedding. Then, we prove the advantages to complete multivariate pattern analysis with differential network analysis, to reveal mechanisms of bacterial network re-organizations which emerge from perturbations induced by a medical treatment (PPIs) or an infectious state (H. pylori). Finally, we show how to build bacteria-metabolite multilayer networks that can deepen our understanding of the metabolite pathways significantly associated to the perturbed microbial communities., Drug use or bacterial infection can cause significant alterations of gastric microbiome. Here, the authors show how advanced pattern recognition by nonlinear machine intelligence can help disclose a bacteria-metabolite network which enlightens mechanisms behind such perturbations.

No abstract available.

SummaryRT-Q-PCR, and RT-PCR amplicon sequencing, provide a convenient, target-specific, high-sensitivity approach for gene expression studies and are widely used in environmental microbiology. Yet, the effectiveness and reproducibility of the reverse transcription step has not been evaluated. Therefore, we tested a combination of four commercial reverse transcriptases with two priming techniques to faithfully transcribe 16S rRNA and amoA transcripts from marine sediments. Both enzyme and priming strategy greatly affected quantification of the exact same target with differences of up to 600-fold. Furthermore, the choice of RT system significantly changed the communities recovered. For 16S rRNA, both enzyme and priming had a significant effect with enzyme having a stronger impact than priming. Inversely, for amoA only the change in priming strategy resulted in significant differences between the same sample. Specifically, more OTUs and better coverage of amoA transcripts diversity were obtained with GS priming indicating this approach was better at recovering the diversity of amoA transcripts. Moreover, sequencing of RNA mock communities revealed that, even though transcript α diversities (i.e. OTU counts within a sample) can be biased by the RT, the comparison of β diversities (i.e. differences in OTU counts between samples) is reliable as those biases are reproducible between environments.Originality-Significance StatementIs the complementary DNA (cDNA) produced after Reverse Transcription (RT) a faithful representation of the starting RNA? This is a fundamental and important question for transcriptomic-based studies in environmental microbiology that aim to quantify and/or examine the diversity of transcripts via RT approaches. Yet little is known about the reliability and reproducibility of this step. Here, we evaluated the effect of the two main components of the RT reaction – the retro transcriptase enzyme and priming strategy (gene specific vs random priming), on the quantification and diversity of cDNA. We found that both have a significant impact. We further provide evidence to enable informed choices as to the enzyme and priming combinations to improve the performance of RT-PCR approaches. Taken together, this work will improve the reliability and reproducibility of transcript-based studies in environmental microbiology.

Reliability and reproducibility of transcriptomics‐based studies are dependent on RNA integrity. In microbial ecology, microfluidics‐based techniques, such as the Ribosomal Integrity Number (RIN), targeting rRNA are currently the only approaches to evaluate RNA integrity. However, the relationship between rRNA and mRNA integrity is unknown. Here we present an integrity index, the Ratio Amplicon, Ramp, adapted from human clinical studies, to directly monitor mRNA integrity from complex environmental samples. We show, in a suite of experimental degradations of RNA extracted from sediment, that while the RIN generally reflected the degradation status of RNA the Ramp mapped mRNA degradation better. Furthermore, we examined the effect of degradation on transcript community structure by amplicon sequencing of 16S rRNA, amoA and glnA transcripts. We successfully sequenced transcripts for all three targets even from highly‐degraded RNA samples. While RNA degradation changed the community structure of the mRNA profiles, no changes were observed for the 16S rRNA transcript profiles. Since both RT‐Q‐PCR and sequencing results were obtained, even from highly degraded samples, we strongly recommend evaluating RNA integrity prior to downstream processing to ensure meaningful results. For this both the RIN and Ramp are useful, with the Ramp better evaluating mRNA integrity in this study.

Lasers are instrumental in advanced bioimaging and Raman spectroscopy. However, they are also well known for their destructive effects on living organisms, leading to concerns about the adverse effects of laser technologies. To implement Raman spectroscopy for cell analysis and manipulation, such as Raman-activated cell sorting, it is crucial to identify nondestructive conditions for living cells. Here, we evaluated quantitatively the effect of 532-nm laser irradiation on bacterial cell fate and growth at the single-cell level. Using a purpose-built microfluidic platform, we were able to quantify the growth characteristics, i.e., specific growth rates and lag times of individual cells, as well as the survival rate of a population in conjunction with Raman spectroscopy. Representative Gram-negative and Gram-positive species show similar trends in response to a laser irradiation dose. Laser irradiation could compromise the physiological function of cells, and the degree of destruction is both dose and strain dependent, ranging from reduced cell growth to a complete loss of cell metabolic activity and finally to physical disintegration. Gram-positive bacterial cells are more susceptible than Gram-negative bacterial strains to irradiation-induced damage. By directly correlating Raman acquisition with single-cell growth characteristics, we provide evidence of nondestructive characteristics of Raman spectroscopy on individual bacterial cells. However, while strong Raman signals can be obtained without causing cell death, the variety of responses from different strains and from individual cells justifies careful evaluation of Raman acquisition conditions if cell viability is critical. IMPORTANCE In Raman spectroscopy, the use of powerful monochromatic light in laser-based systems facilitates the detection of inherently weak signals. This allows environmentally and clinically relevant microorganisms to be measured at the single-cell level. The significance of being able to perform Raman measurement is that, unlike label-based fluorescence techniques, it provides a “fingerprint” that is specific to the identity and state of any (unlabeled) sample. Thus, it has emerged as a powerful method for studying living cells under physiological and environmental conditions. However, the laser's high power also has the potential to kill bacteria, which leads to concerns. The research presented here is a quantitative evaluation that provides a generic platform and methodology to evaluate the effects of laser irradiation on individual bacterial cells. Furthermore, it illustrates this by determining the conditions required to nondestructively measure the spectra of representative bacteria from several different groups.

Summary The bacterioplankton diversity in large rivers has thus far been under‐sampled despite the importance of streams and rivers as components of continental landscapes. Here, we present a comprehensive dataset detailing the bacterioplankton diversity along the midstream of the Danube River and its tributaries. Using 16S rRNA‐gene amplicon sequencing, our analysis revealed that bacterial richness and evenness gradually declined downriver in both the free‐living and particle‐associated bacterial communities. These shifts were also supported by beta diversity analysis, where the effects of tributaries were negligible in regards to the overall variation. In addition, the river was largely dominated by bacteria that are commonly observed in freshwaters. Dominated by the acI lineage, the freshwater SAR11 (LD12) and the P olynucleobacter group, typical freshwater taxa increased in proportion downriver and were accompanied by a decrease in soil and groundwater‐affiliated bacteria. Based on views of the meta‐community and River Continuum Concept, we interpret the observed taxonomic patterns and accompanying changes in alpha and beta diversity with the intention of laying the foundation for a unified concept for river bacterioplankton diversity.

Aberrant microbiota composition and function have been linked to several pathologies, including type 2 diabetes. In animal models, prebiotics induce favourable changes in the intestinal microbiota, intestinal permeability (IP) and endotoxaemia, which are linked to concurrent improvement in glucose tolerance. This is the first study to investigate the link between IP, glucose tolerance and intestinal bacteria in human type 2 diabetes. In all, twenty-nine men with well-controlled type 2 diabetes were randomised to a prebiotic (galacto-oligosaccharide mixture) or placebo (maltodextrin) supplement (5·5 g/d for 12 weeks). Intestinal microbial community structure, IP, endotoxaemia, inflammatory markers and glucose tolerance were assessed at baseline and post intervention. IP was estimated by the urinary recovery of oral 51Cr-EDTA and glucose tolerance by insulin-modified intravenous glucose tolerance test. Intestinal microbial community analysis was performed by high-throughput next-generation sequencing of 16S rRNA amplicons and quantitative PCR. Prebiotic fibre supplementation had no significant effects on clinical outcomes or bacterial abundances compared with placebo; however, changes in the bacterial family Veillonellaceae correlated inversely with changes in glucose response and IL-6 levels (r −0·90, P=0·042 for both) following prebiotic intake. The absence of significant changes to the microbial community structure at a prebiotic dosage/length of supplementation shown to be effective in healthy individuals is an important finding. We propose that concurrent metformin treatment and the high heterogeneity of human type 2 diabetes may have played a significant role. The current study does not provide evidence for the role of prebiotics in the treatment of type 2 diabetes.