Evidence map›Paper›PMID 31680682›Full record

ArticleJournal of visualized experiments : JoVE2019

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing.

Shailesh K Shahi, Kasra Zarei, Natalya V Guseva, Ashutosh K Mangalam

Abstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

58 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Roux-en-Y gastric bypass alters microbial circadian rhythms with links to metabolic improvement.American journal of physiology. Gastrointestinal and liver physiology · 2026
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  6. Maternal Low-Fat and High-Fat Diet Decreases Survival and Alters Cytokine Signaling in Neonatal Mice With Staphylococcus epidermidis Sepsis.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shailesh K ShahiDepartment of Pathology, University of Iowa.
Kasra ZareiMedical Scientist Training Program, University of Iowa.
Natalya V GusevaDepartment of Pathology, University of Iowa.
Ashutosh K MangalamDepartment of Pathology, University of Iowa; Medical Scientist Training Program, University of Iowa; Graduate Program in Immunology, University of Iowa; Graduate Program in Molecular Medicine, University of Iowa; ashutosh-mangalam@uiowa.edu.

Funding

Pulmonary Toxicology Facility CoreP30ES005605 · NIEHS · UNIVERSITY OF IOWA · PI Brandi Janssen · 1990 to 2026
$40.5M
Linking diet, gut microbiota and autoimmune disease: Bacteria induced phytoestrogen metabolites impact immune function in Experimental Autoimmune EncephalitisR01AI137075 · NIAID · UNIVERSITY OF IOWA · PI MANGALAM, ASHUTOSH KUMAR · 2018 to 2022
$2.0M
NIAID NIH HHS R01 AI137075NIEHS NIH HHS P30 ES005605
6 · The paper itself

Abstract

The human gut is colonized by trillions of bacteria that support physiologic functions such as food metabolism, energy harvesting, and regulation of the immune system. Perturbation of the healthy gut microbiome has been suggested to play a role in the development of inflammatory diseases, including multiple sclerosis (MS). Environmental and genetic factors can influence the composition of the microbiome; therefore, identification of microbial communities linked with a disease phenotype has become the first step towards defining the microbiome's role in health and disease. Use of 16S rRNA metagenomic sequencing for profiling bacterial community has helped in advancing microbiome research. Despite its wide use, there is no uniform protocol for 16S rRNA-based taxonomic profiling analysis. Another limitation is the low resolution of taxonomic assignment due to technical difficulties such as smaller sequencing reads, as well as use of only forward (R1) reads in the final analysis due to low quality of reverse (R2) reads. There is need for a simplified method with high resolution to characterize bacterial diversity in a given biospecimen. Advancements in sequencing technology with the ability to sequence longer reads at high resolution have helped to overcome some of these challenges. Present sequencing technology combined with a publicly available metagenomic analysis pipeline such as R-based Divisive Amplicon Denoising Algorithm-2 (DADA2) has helped advance microbial profiling at high resolution, as DADA2 can assign sequence at the genus and species levels. Described here is a guide for performing bacterial profiling using two-step amplification of the V3-V4 region of the 16S rRNA gene, followed by analysis using freely available analysis tools (i.e., DADA2, Phyloseq, and METAGENassist). It is believed that this simple and complete workflow will serve as an excellent tool for researchers interested in performing microbiome profiling studies.

Indexed as

AnimalsFecesGastrointestinal MicrobiomeHigh-Throughput Nucleotide SequencingHumansMiceMice, Inbred C57BLMice, TransgenicMicrobiotaPolymerase Chain ReactionRNA, Ribosomal, 16SSequence Analysis, RNARNA, Ribosomal, 16S

Identifiers

PMID31680682
PMCPMC6945761

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.