International Journal of Medical Microbiology · 2022 · 19 citations · 31 references
Life SciencesMicrobiologyMedical MicrobiologyMicrobial EcologyMicrobiome ResearchGut MicrobiomeGut MicrobiotaMicrobial Community ProfilingMicrobial DiversityMicrobiome DiversityMicrobiome SamplingAlpha DiversityBeta DiversityBeta Diversity PatternsGut Microbiota CompositionMicrobial Diversity AssessmentMicrobiome Diversity AnalysisRectal Swab CollectionStool Sampling
BACKGROUND: Advances in genome sequencing have enabled detailed microbiome analysis; however, the ideal specimen type for sequencing is yet to be determined. Rectal swabs may offer a rapid and convenient modality for colonic microbiome analysis. The aim of this study is to evaluate the use of rectal swabs compared to faecal specimens. METHODS AND RESULTS: Twenty health professionals participated in this study and provided a faecal specimen, a self-collected rectal swab and a rectal swab taken by a clinician. DNA was extracted and 16S rRNA gene sequencing was carried out for microbiome analysis. Alpha diversity was higher in swabs compared to faecal specimens; however, the difference was only significant when comparing clinician-obtained swabs to faeces. Analysis of beta diversity consistently showed that few taxa were affected by sample type. We found sample type accounted for only 6.8% of community variation (R2 = 0.067, p < 0.001, permanova). Notably, there were only six genera identified in clinician-obtained swabs that were not also found in the self-taken swabs. CONCLUSIONS: Both self-collected and clinician obtained rectal swabs are a reliable method of analysing the colonic microbiome. Obtaining specimens for microbiome analysis is often time-critical due to therapy, such as antibiotics, influencing the microbiome. Rectal swabs are shown to be a valid and convenient modality for microbiome analysis.
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Fast gapped-read alignment with Bowtie 2
Ben Langmead, Steven L. Salzberg · Nature Methods · 2012 · 61.1K citations
DADA2: High-resolution sample inference from Illumina amplicon data
Benjamin J. Callahan, Paul J. McMurdie, Michael Rosen et al. · Nature Methods · 2016 · 36.3K citations