Intestinal Microbiome Analysis
Intestinal Microbiome Analysis - Related Videos
10:51
Co-culture of Living Microbiome with Microengineered Human Intestinal Villi in a Gut-on-a-Chip Microfluidic Device
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Cited by 68 •
2016
We describe an in vitro protocol to co-culture gut microbiome and intestinal villi for an extended period using a human gut-on-a-chip microphysiological system.
10:58
A Protocol for Lentiviral Transduction and Downstream Analysis of Intestinal Organoids
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Cited by 81 •
2015
In this video protocol we give a step by step explanation of lentiviral transduction in organoids of primary intestinal epithelium and of processing and downstream analysis of these cultures by quantitative RT-PCR, RNA-microarray and immunohistochemistry.
09:47
Selective Cleaning of Wild Caenorhabditis Nematodes to Enrich for Intestinal Microbiome Bacteria
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Cited by 9 •
2021
Wild Caenorhabditis nematodes are associated with many microbes, often in the gut lumen or infecting the intestine. This protocol details a method to enrich unculturable microbes colonizing the intestine, taking advantage of the resistance of the dauer cuticle.
08:38
Application of Flow Vermimetry for Quantification and Analysis of the Caenorhabditis elegans Gut Microbiome
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2023
Caenorhabditis elegans is a powerful model to examine the molecular determinants driving host-microbiome interactions. We present a high throughput pipeline profiling the single animal levels of gut microbiome colonization together with key aspects of the C. elegans physiology.
10:42
Oral Biofilm Sampling for Microbiome Analysis in Healthy Children
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Cited by 16 •
2017
Changes in the oral microbiome throughout childhood are of growing interest. Comparison of different microbiome studies reveals a lack of standardized sampling protocols. Limited space makes sampling the sound subgingival sulcus of children challenging. Paper point sampling is presented here in detail as the method of choice for this area.
FAQs
These approaches provide different levels of information. 16S rRNA gene sequencing supports identification of organisms and estimation of community composition, whereas shotgun metagenomics can also characterize functional genes across microbial genetic material. Choosing between them therefore affects whether the analysis emphasizes which microorganisms are present, what functions may be represented, or both.
Examining diversity alongside composition and functional genes helps distinguish a change in the range of microorganisms from a change in the kinds of organisms or capabilities represented. This broader view is useful because intestinal microbiome analysis can connect community structure with microbial metabolic activity, immune regulation, and host responses rather than relying on one measure alone.
Comparative designs can reveal patterns associated with disease or treatment, including differences linked to inflammation, pathogen colonization, or antibiotic exposure. These comparisons help researchers determine whether particular microbiome profiles track with health status or therapeutic conditions. The result is an evidence base for studying associations, rather than treating a profile as an isolated finding.
The analysis connects microbial community patterns with processes central to immunology and infection, including inflammation, pathogen colonization, immune regulation, and host responses. Researchers can use these relationships to examine how intestinal microorganisms may be associated with infection-related states or immune activity. This context also supports investigations of therapeutic outcomes and the biological factors accompanying disease.
A typical workflow starts with an intestinal sample, followed by extraction of microbial DNA. Researchers then apply 16S rRNA gene sequencing or shotgun metagenomics to the extracted material. The resulting data can be used to identify organisms, estimate community composition, and characterize functional genes. Keeping these stages distinct clarifies how laboratory preparation connects to biological interpretation.
Microbiome profiles can serve as candidates for biomarkers when their patterns distinguish healthy, diseased, or treated individuals. Researchers can then examine whether those patterns are associated with inflammation, pathogen colonization, immune regulation, or therapeutic outcomes. The value lies in linking measurable community features to a biological or health-related context while retaining the association-based nature of the analysis.
Antibiotic exposure provides a treatment-related condition for comparison with microbiome profiles. In immunology and infection studies, those patterns may be considered alongside pathogen colonization, inflammation, immune regulation, and host responses. This approach helps frame how microbial community features relate to treatment conditions and can inform investigations of therapeutic outcomes.