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Related Concept Videos

Microbial Phylogeny01:28

Microbial Phylogeny

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Understanding the evolutionary relationships among microorganisms is fundamental to microbial ecology and taxonomy. Phylogenetic trees are essential tools for inferring these relationships, relying primarily on comparative analyses of molecular sequences such as DNA, RNA, or proteins. In microbial studies, these trees typically depict the evolutionary paths of diverse bacterial and archaeal species by mapping genetic differences accumulated over time.Phylogenetic trees are composed of tips,...
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Methods to Assess Microbial Populations01:30

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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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Methods to Assess Microbial Communities01:19

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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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Soil Microbial Ecology01:29

Soil Microbial Ecology

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Soil microbial ecology is defined by highly diverse, spatially structured communities that drive nutrient cycling, organic matter turnover, and overall ecosystem stability. Although a gram of soil can contain thousands of bacterial and archaeal taxa, the ecological processes they mediate are even more crucial for sustaining terrestrial life.Microhabitats and NichesSoil is a heterogeneous mixture of minerals, organic matter, water, and air. Microbes inhabit distinct microhabitats formed by...
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Development of Human Microbiota01:30

Development of Human Microbiota

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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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Microbiota of the Large Intestine01:27

Microbiota of the Large Intestine

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The large intestine hosts the most densely populated microbial ecosystem in the human body. This complex community primarily consists of anaerobic bacteria, with Bacillota (formerly Firmicutes) and Bacteroidota (formerly Bacteroidetes) as the predominant groups. The distribution of these microbes varies along different sections of the large intestine, influenced by local environmental factors such as oxygen availability and nutrient composition.The cecum, located at the beginning of the large...
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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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TARO: tree-aggregated factor regression for microbiome data integration.

Aditya K Mishra1,2, Iqbal Mahmud3, Philip L Lorenzi3

  • 1Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.

Bioinformatics (Oxford, England)
|May 24, 2024
PubMed
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We developed Tree-Aggregated factor RegressiOn (TARO) to integrate microbiome and metabolomic data, overcoming challenges in analyzing complex biological datasets. TARO accurately identifies key microbial and metabolite associations, aiding in understanding host-microbiome interactions.

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Area of Science:

  • Microbiome research
  • Metabolomics
  • Computational biology

Background:

  • The human microbiome's role in health and disease is significant but poorly understood.
  • Integrating microbiome data with other molecular profiles (e.g., metabolomics) is crucial for identifying therapeutic targets.
  • High dimensionality, compositionality, and rare features in microbiome data present analytical challenges.

Purpose of the Study:

  • To develop a novel method for integrating microbiome and metabolomic data.
  • To address the challenges posed by the complex nature of microbiome profiling data.
  • To identify microbial contributions to host metabolite abundances.

Main Methods:

  • Proposed Tree-Aggregated factor RegressiOn (TARO) for joint analysis of microbiome and metabolomic data.
  • Utilized the taxonomic tree structure to aggregate rare microbial features.
  • Validated TARO's performance through simulation studies for accurate coefficient matrix recovery and feature identification.

Main Results:

  • TARO successfully integrated microbiome and metabolomic data.
  • Simulations confirmed TARO's ability to recover low-rank coefficient matrices and identify relevant features.
  • Application to colorectal cancer screening data revealed insights into gut microbe-metabolite interactions.

Conclusions:

  • TARO provides an effective approach for integrating microbiome and metabolomic data.
  • The method facilitates a deeper understanding of host-microbiome interactions.
  • TARO aids in discovering microbial biomarkers and therapeutic targets.