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Related Concept Videos

Methods to Assess Microbial Communities01:19

Methods to Assess Microbial Communities

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Microbial communities, comprising bacteria, archaea, and eukaryotic microorganisms, inhabit diverse ecosystems and play crucial roles in environmental and biological processes. Their diversity is defined by three main parameters: species richness (the number of distinct species), species abundance (the relative quantity of each species), and species evenness (how uniformly individual species are distributed in various locations). These factors together shape the structure and ecological balance...
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Microorganisms colonize various regions of the human body, including the mouth, nasal passages, throat, stomach, intestines, urogenital tract, and skin. The total number of microbial cells is estimated to range from 10¹³ to 10¹⁴—comparable to, or exceeding, the number of human somatic cells. This host–microbiome relationship has led to the conceptualization of humans as supraorganisms, wherein microbial communities perform vital roles in development, immunity,...
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Modern Molecular Taxonomy

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Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
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Microbial genome evolution is a highly dynamic process shaped by continual gene gain and loss across species and strains. This genomic flexibility allows microorganisms to adapt rapidly to environmental pressures and interactions with other organisms. Central to understanding this diversity is the distinction between the core and pan genomes.The core genome comprises the genes shared by all sampled strains of a species, representing essential functions needed for fundamental cellular processes.
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The human microbiota begins developing at birth and undergoes continual change as we age. Infancy marks a critical period of microbial sensitivity, offering a “window of opportunity” during which beneficial microbes help mature the immune system. By age three, children typically develop a more stable and diverse microbial community. Newborns acquire microbes from their immediate environment; vaginal delivery favors maternal vaginal microbes, while cesarean births favor microbes from...
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Assessing microbial populations is crucial for understanding microbial roles in health, ecology, and industry. Various complementary techniques—both culture-based and molecular—enable detailed analysis of microbial abundance, diversity, and function.Viable Plate CountThe viable plate count is a traditional culture-based method used to estimate the number of living microbes in a sample. After serial dilution, the sample is spread onto nutrient agar plates. Each viable cell forms a...
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Shiny-phyloseq: Web application for interactive microbiome analysis with provenance tracking.

Paul J McMurdie1, Susan Holmes1

  • 1Department of Statistics, Stanford University, Stanford, CA 94305, USA.

Bioinformatics (Oxford, England)
|September 29, 2014
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Summary

Shiny-phyloseq is a web application that simplifies microbiome data analysis using R tools. It requires no programming, making complex analyses accessible for archiving, sharing, and reproducing results.

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Area of Science:

  • Microbiome research
  • Bioinformatics
  • Computational biology

Background:

  • Microbiome data analysis often requires programming skills in R.
  • Existing tools like phyloseq have a steep learning curve.
  • Accessibility to microbiome data analysis tools is limited for non-programmers.

Purpose of the Study:

  • To develop a user-friendly web application for microbiome data analysis.
  • To enhance the accessibility of phyloseq and related R tools.
  • To enable reproducible microbiome data exploration without coding.

Main Methods:

  • Developed Shiny-phyloseq, a Shiny-based web application.
  • Implemented in the R language for broad system compatibility (Windows, Mac OS, Linux).
  • Designed a dynamic interface for exploring parameters and methods, with session recording.

Main Results:

  • Shiny-phyloseq provides dynamic interaction with microbiome data via a web browser.
  • Users can explore data and analysis parameters without programming.
  • Complete user input and graphical results are recorded for archiving and sharing.

Conclusions:

  • Shiny-phyloseq significantly lowers the barrier to entry for microbiome data analysis.
  • The application promotes reproducible research by documenting analysis workflows.
  • It increases the accessibility and usability of advanced bioinformatics tools for a wider audience.