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Related Concept Videos

Introduction to the Human Microbiota01:22

Introduction to the Human Microbiota

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, and disease...
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Polyethylene terephthalate (PET) is a synthetic polymer widely utilized in the packaging industry, particularly for bottles and containers. Due to its chemical stability and durability, PET accumulates in the environment, contributing significantly to plastic pollution. It comprises repeating units of terephthalic acid and ethylene glycol, resulting in a semi-crystalline structure that is resistant to natural degradation processes.A notable breakthrough in plastic biodegradation came with the...
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Unraveling Microplastic Effects on Gut Microbiota across Various Animals Using Machine Learning.

Lingzi Yin1, Minghao Yang1, Anqi Teng1

  • 1Bioscience and Biomedical Engineering Thrust, Systems Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong 511453, China.

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Microplastic pollution harms animal gut microbiota, with mice being particularly vulnerable. Exposure duration is the primary driver of these toxic effects, impacting microbial diversity and balance.

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Area of Science:

  • Environmental Science
  • Microbiology
  • Toxicology

Background:

  • Microplastics are persistent pollutants with widespread ecological impacts.
  • Significant effects on animal gut microbiota are documented, but comparative analyses are lacking.
  • Understanding factors driving microplastic-induced microbiota changes is crucial.

Purpose of the Study:

  • To conduct a meta-analysis comparing microplastic effects on gut microbiota across diverse animal species.
  • To identify key factors influencing microplastic toxicity on gut microbial communities.
  • To discover potential biomarkers for microplastic exposure.

Main Methods:

  • Compiled and analyzed 1352 gut microbiota samples from six animal categories.
  • Employed machine learning for an in-depth meta-analysis.
  • Utilized statistical models to identify critical exposure factors and biomarkers.

Main Results:

  • Mice showed higher susceptibility to microplastics, with reduced diversity and altered microbial balance (e.g., increased Firmicutes/Bacteroidetes ratio).
  • Earthworms and insects demonstrated greater microplastic degradation potential than mice.
  • Machine learning identified exposure duration as the primary factor driving microplastic-induced gut microbiota alterations.
  • Lactobacillus, Helicobacter, and Pseudomonas were identified as potential biomarkers.

Conclusions:

  • Microplastic exposure poses significant health risks to animals, varying by species.
  • Exposure duration is a critical determinant of microplastic impact on gut microbiota.
  • Specific bacterial species can serve as indicators of microplastic toxicity in animal guts.