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Optimisation of 16S rRNA gut microbiota profiling of extremely low birth weight infants.

ABSTRACT: Infants born prematurely, particularly extremely low birth weight infants (ELBW) have altered gut microbial communities. Factors such as maternal health, gut immaturity, delivery mode, and antibiotic treatments are associated with microbiota disturbances, and are linked to an increased risk of certain diseases such as necrotising enterocolitis. Therefore, there is a requirement to optimally characterise microbial profiles in this at-risk cohort, via standardisation of methods, particularly for studying the influence of microbiota therapies (e.g. probiotic supplementation) on community profiles and health outcomes. Profiling of faecal samples using the 16S rRNA gene is a cost-efficient method for large-scale clinical studies to gain insights into the gut microbiota and additionally allows characterisation of cohorts were sample quantities are compromised (e.g. ELBW infants). However, DNA extraction method, and the 16S rRNA region targeted can significantly change bacterial community profiles obtained, and so confound comparisons between studies. Thus, we sought to optimise a 16S rRNA profiling protocol to allow standardisation for studying ELBW infant faecal samples, with or without probiotic supplementation.Using ELBW faecal samples, we compared three different DNA extraction methods, and subsequently PCR amplified and sequenced three hypervariable regions of the 16S rRNA gene (V1 + V2 + V3), (V4 + V5) and (V6 + V7 + V8), and compared two bioinformatics approaches to analyse results (OTU and paired end). Paired shotgun metagenomics was used as a 'gold-standard'.Results indicated a longer bead-beating step was required for optimal bacterial DNA extraction and that sequencing regions (V1 + V2 + V3) and (V6 + V7 + V8) provided the most representative taxonomic profiles, which was confirmed via shotgun analysis. Samples sequenced using the (V4 + V5) region were found to be underrepresented in specific taxa including Bifidobacterium, and had altered diversity profiles. Both bioinformatics 16S rRNA pipelines used in this study (OTU and paired end) presented similar taxonomic profiles at genus level.We determined that DNA extraction from ELBW faecal samples, particularly those infants receiving probiotic supplementation, should include a prolonged beat-beating step. Furthermore, use of the 16S rRNA (V1 + V2 + V3) and (V6 + V7 + V8) regions provides reliable representation of ELBW microbiota profiles, while inclusion of the (V4 + V5) region may not be appropriate for studies where Bifidobacterium constitutes a resident microbiota member.

SUBMITTER: Alcon-Giner C

PROVIDER: S-EPMC5668952 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Optimisation of 16S rRNA gut microbiota profiling of extremely low birth weight infants.

Alcon-Giner Cristina C Caim Shabhonam S Mitra Suparna S Ketskemety Jennifer J Wegmann Udo U Wain John J Belteki Gusztav G Clarke Paul P Hall Lindsay J LJ

BMC genomics 20171102 1

<h4>Background</h4>Infants born prematurely, particularly extremely low birth weight infants (ELBW) have altered gut microbial communities. Factors such as maternal health, gut immaturity, delivery mode, and antibiotic treatments are associated with microbiota disturbances, and are linked to an increased risk of certain diseases such as necrotising enterocolitis. Therefore, there is a requirement to optimally characterise microbial profiles in this at-risk cohort, via standardisation of methods, ...[more]

PMID: 29096601

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Project description:ObjectiveThe goal of this study was to comprehensively investigate the characteristics of gut microbiota dysbiosis and metabolites levels in very low or extremely low birth weight (VLBW/ELBW) infants with white matter injury (WMI).MethodsIn this prospective cohort study, preterm infants with gestational age < 32 weeks and weight < 1.5 kg were investigated. Additionally, fecal samples were collected on days zero, 14d and 28d after admission to the intensive care unit. All subjects underwent brain scan via MRI and DTI at a corrected gestational age of 37 ~ 40 weeks. Based on the results of MRI examination, the VLBW/ELBW infants were divided into two groups: WMI and non-WMI. Finally, based on a multi-omics approach, we performed 16S rRNA gene sequencing, LC-MS/MS, and diffusion tension imaging to identify quantifiable and informative biomarkers for WMI.ResultWe enrolled 23 patients with and 48 patients without WMI. The results of 16S RNA sequencing revealed an increase in the number of Staphylococcus and Acinetobacter species in the fecal samples of infants with WMI, as well as increasing levels of S. caprae and A._johnsonii. LEfSe analysis (LDA ≥ 4) showed that the WMI group carried an abundance of Staphylococcus species including S. caprae, members of the phyla Bacteroidota and Actinobacteriota, and Acinetobacter species. A total of 139 metabolic markers were significantly and differentially expressed between WMI and nWMI. KEGG pathway enrichment analysis revealed that the WMI group showed significant downregulation of 17 metabolic pathways including biosynthesis of arginine and primary bile acids. The WMI group showed delayed brain myelination, especially in the paraventricular white matter and splenium of corpus callosum. Staphylococcus species may affect WMI by downregulating metabolites such as cholic acid, allocholic acid, and 1,3-butadiene. Gut microbiota such as Acinetobacter and Bacteroidetes may alter white matter structurally by upregulating metabolites such as cinobufagin.ConclusionBased on 16S RNA sequencing results, severe gut microbiota dysbiosis was observed in the WMI group. The results might reveal damage to potential signaling pathways of microbiota-gut-brain axis in gut microbiota. The mechanism was mediated via downregulation of the bile acid biosynthetic pathway.

Project description:Proper preservation of stool samples to minimize microbial community shifts and inactivate infectious agents is important for self-collected specimens requiring shipment to laboratories when cold chain transport is not feasible. In this study, we evaluated the performance of six preservation solutions (Norgen, OMNI, RNAlater, CURNA, HEMA, and Shield) for these aspects. Following storage of human stool samples with these preservatives at room temperature for 7 days, three hypervariable regions of the bacterial 16S rRNA gene (V1-V2, V3-V4, and V4) were amplicon sequenced. We found that samples collected in two preservatives, Norgen and OMNI, showed the least shift in community composition relative to -80°C standards compared with other storage conditions, and both efficiently inhibited the growth of aerobic and anaerobic bacteria. RNAlater did not prevent bacterial activity and exhibited relatively larger community shift. Although the effect of preservation solution was small compared to intersubject variation, notable changes in microbiota composition were observed, which could create biases in downstream data analysis. When community profiles inferred from different 16S rRNA gene hypervariable regions were compared, we found differential sensitivity of primer sets in identifying overall microbial community and certain bacterial taxa. For example, reads generated by the V4 primer pair showed a higher alpha diversity of the gut microbial community. The degenerate 27f-YM primer failed to detect the majority of Bifidobacteriales. Our data indicate that choice of preservation solution and 16S rRNA gene primer pair are critical determinants affecting gut microbiota profiling. IMPORTANCE Large-scale human microbiota studies require specimens collected from multiple sites and/or time points to maximize detection of the small effects in microbe-host interactions. However, batch biases caused by experimental protocols, such as sample collection, massively parallel sequencing, and bioinformatics analyses, remain critical and should be minimized. This work evaluated the effects of preservation solutions and bacterial 16S rRNA gene primer pairs in revealing human gut microbiota composition. Since notable changes in detecting bacterial composition and abundance were observed among choice of preservatives and primer pairs, a consistent methodology is essential in minimizing their effects to facilitate comparisons between data sets.

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Optimisation of 16S rRNA gut microbiota profiling of extremely low birth weight infants.

Publications

Optimisation of 16S rRNA gut microbiota profiling of extremely low birth weight infants.

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