Performance comparison of fecal preservative and stock solutions for gut microbiome storage at room temperature

Park, Chanhyeok; Yun, Kyeongeui; Chu, Jeong Min; Lee, Ji Yeon; Hong, Chang Pyo; Nam, Young-Do; Jeong, Jin-Uk; Han, Kyudong; Ahn, Yong Ju

doi:10.1007/s12275-020-0092-6

Cited by 14 publications

(17 citation statements)

References 35 publications

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“…For the LoopSeq, QIIME 2 was used to process the FASTQ les. In brief, the Divisive Amplicon Denoising Algorithm 2 (DADA2) in QIIME 2 plugin was used to obtain OTUs, which detected and corrected amplicon errors and ltered out the potential base error and chimeric sequences [42,43]. All the raw sequences were ltered, trimmed, and dereplicated.…”

Section: Discussionmentioning

confidence: 99%

Effects of Waterlogging on Soybean Rhizosphere Microbial Community Profiled Using Illumina MiSeq, LoopSeq, and PacBio 16S rRNA Genes Sequences

Ling

Liu

et al. 2021

Preprint

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Background: Waterlogging on the global environment has led to a significant decline in crop yields. However, the response of plant-associated microbes to waterlogging stress on different soils is not known. Moreover, there are few reports on whether this response is influenced by different sequencing methods. In this study, the effects of waterlogging on soybean rhizosphere microbial structure on two types of soil were examined, using a short reading 16S rRNA sequencing variable region V4 and two full-length 16S rRNA sequencing variable regions V1-V9.Results: The results revealed some similarities and differences in three sequencing methods for soybean rhizosphere microbial response to waterlogging stress. Based on CPCoA analysis, all the sequencing methods showed that waterlogging on both types of soil significantly affected the bacterial community structure of the soybean rhizosphere, and increased the relative abundance of Geobacter. However, the full-length sequencing methods had higher classification resolution than short-read sequencing (except phylum level of all sequencing methods and class level of LoopSeq sequencing). Further, analysis on OTU level and network showed that waterlogging increased the abundance of some microorganisms related to nitrogen cycle using V4 sequencing, and microorganisms related to phosphorus cycling when using two full-length sequencing methods. This is in line with the core microbial analysis. Environmental factors affecting the structure of microbial communities differed among sequencing methods.Conclusions: In summary, this piece of work detected the effects of waterlogging on soybean rhizosphere microbes using three sequencing methods. Some functional microbes were enriched in the rhizosphere, which may benefit soybean in resisting waterlogging stress. On the other hand, there were several differences in results among the three sequencing methods which might affect the response of rhizosphere microbial structure to stress. Our analysis of sequencing methods on various levels provides some useful information on environmental samples sequencing.

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Section: Discussionmentioning

confidence: 99%

Effects of Waterlogging on Soybean Rhizosphere Microbial Community Profiled Using Illumina MiSeq, LoopSeq, and PacBio 16S rRNA Genes Sequences

Ling

Liu

et al. 2021

Preprint

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show abstract

“…For V4 16S and LoopSeq sequencing, the raw FASTQ sequence file was processed by QIIME 2. In brief, the divisive amplicon denoising algorithm 2 (DADA2) in the QIIME 2 plugin was used to obtain OTUs, which detected and corrected amplicon errors and filtered out the potential base error and chimeric sequences ( 30 , 97 ). All the raw sequences were filtered, trimmed, and dereplicated.…”

Section: Methodsmentioning

confidence: 99%

“…All the raw sequences were filtered, trimmed, and dereplicated. The representative sequence generated after denoising was based on sklearn’s naive Bayes classifier for bacterial classification on the SILVA 16S full-length database ( 97 , 98 ). For PacBio 16S sequencing, the raw sequence files were processed using single-molecule, real-time (SMRT) Link software version 5.1.0.26412 (Pacific Biosciences).…”

Section: Methodsmentioning

confidence: 99%

Effects of Waterlogging on Soybean Rhizosphere Bacterial Community Using V4, LoopSeq, and PacBio 16S rRNA Sequence

Ling

Liu

et al. 2022

Microbiol Spectr

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“… 15 items Higher scores indicate more severe symptoms. Microbiome analysis 16s rRNA stool analysis using the Omnigene Gut OM-200 kit [ 100 , 101 ] by Atlas Biomed [ 102 ]. Raw data analysed using the Deblur algorithm [ 103 ].…”

Section: Methodsmentioning

confidence: 99%

Trialling a microbiome-targeted dietary intervention in children with ADHD—the rationale and a non-randomised feasibility study

Lawrence

Myrissa²,

Toribio-Mateas

et al. 2022

Pilot Feasibility Stud

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Background Dietary interventions have been previously explored in children with ADHD. Elimination diets and supplementation can produce beneficial behaviour changes, but little is known about the mechanisms mediating change. We propose that these interventions may work, in part, by causing changes in the gut microbiota. A microbiome-targeted dietary intervention was developed, and its feasibility assessed. Methods A non-randomised feasibility study was conducted on nine non-medicated children with ADHD, aged 8–13 years (mean 10.39 years), using a prospective one-group pre-test/post-test design. Participants were recruited from ADHD support groups in London and took part in the 6-week microbiome-targeted dietary intervention, which was specifically designed to impact the composition of gut bacteria. Children were assessed pre- and post-intervention on measures of ADHD symptomatology, cognition, sleep, gut function and stool-sample microbiome analysis. The primary aim was to assess the study completion rate, with secondary aims assessing adherence, adverse events (aiming for no severe and minimal), acceptability and suitability of outcome measures. Results Recruitment proved to be challenging and despite targeting 230 participants directly through support groups, and many more through social media, nine families (of the planned 10) signed up for the trial. The completion rate for the study was excellent at 100%. Exploration of secondary aims revealed that (1) adherence to each aspect of the dietary protocol was very good; (2) two mild adverse events were reported; (3) parents rated the treatment as having good acceptability; (4) data collection and outcome measures were broadly feasible for use in an RCT with a few suggestions recommended; (5) descriptive data for outcome measures is presented and suggests that further exploration of gut microbiota, ADHD symptoms and sleep would be helpful in future research. Conclusions This study provides preliminary evidence for the feasibility of a microbiome-targeted dietary intervention in children with ADHD. Recruitment was challenging, but the diet itself was well-tolerated and adherence was very good. Families wishing to trial this diet may find it an acceptable intervention. However, recruitment, even for this small pilot study, was challenging. Because of the difficulty experienced recruiting participants, future randomised controlled trials may wish to adopt a simpler dietary approach which requires less parental time and engagement, in order to recruit the number of participants required to make meaningful statistical interpretations of efficacy. Trial registration ClinicalTrials.gov Identifier: NCT03737877. Registered 13 November 2018—retrospectively registered, within 2 days of the first participant being recruited.

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Performance comparison of fecal preservative and stock solutions for gut microbiome storage at room temperature

Cited by 14 publications

References 35 publications

Effects of Waterlogging on Soybean Rhizosphere Microbial Community Profiled Using Illumina MiSeq, LoopSeq, and PacBio 16S rRNA Genes Sequences

Effects of Waterlogging on Soybean Rhizosphere Microbial Community Profiled Using Illumina MiSeq, LoopSeq, and PacBio 16S rRNA Genes Sequences

Effects of Waterlogging on Soybean Rhizosphere Bacterial Community Using V4, LoopSeq, and PacBio 16S rRNA Sequence

Trialling a microbiome-targeted dietary intervention in children with ADHD—the rationale and a non-randomised feasibility study

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