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相关概念视频

Microbial Phylogeny01:28

Microbial Phylogeny

89
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

Methods to Assess Microbial Populations

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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...
102
Methods to Assess Microbial Communities01:19

Methods to Assess Microbial Communities

66
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...
66
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

68
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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相关实验视频

Updated: May 5, 2026

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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塔罗:微生物组数据集成的树聚合因子回归.

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
概括

我们开发了Tree-Aggregated factor RegressiOn (TARO) 来整合微生物组和代谢组数据,克服了分析复杂生物数据集的挑战. 塔罗准确地识别了关键的微生物和代谢物关联,有助于理解宿主-微生物群相互作用.

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科学领域:

  • 微生物组研究的研究.
  • 代谢学 代谢学 代谢学
  • 计算生物学是一种计算生物学.

背景情况:

  • 人类微生物组在健康和疾病中的作用是显著的,但不太了解.
  • 将微生物组数据与其他分子配置文件 (例如,代谢学) 整合起来,对于确定治疗点至关重要.
  • 微生物组数据中的高维度,复合性和罕见特征带来了分析挑战.

研究的目的:

  • 开发一种用于整合微生物组和代谢学数据的新方法.
  • 为了应对微生物组分析数据的复杂性所带来的挑战.
  • 为了确定微生物对宿主代谢物丰度的贡献.

主要方法:

  • 拟议的Tree-Aggregated Factor RegressiOn (TARO) 用于微生物组和代谢组数据的联合分析.
  • 利用分类树结构来聚合罕见的微生物特征.
  • 通过模拟研究验证了TARO的性能,用于准确的系数矩阵恢复和特征识别.

主要成果:

  • 塔罗成功地整合了微生物组和代谢组数据.
  • 模拟证实TARO能够恢复低级系数矩阵并识别相关特征.
  • 对结直肠癌查数据的应用揭示了对肠道微生物-代谢物相互作用的见解.

结论:

  • 塔罗提供了一种有效的方法来整合微生物组和代谢学数据.
  • 该方法有助于更深入地了解宿主微生物群相互作用.
  • 塔罗有助于发现微生物生物标志物和治疗点.