4.6 Article

Fecal microbiota and their association with heat stress in Bos taurus

Journal

BMC MICROBIOLOGY
Volume 22, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12866-022-02576-0

Keywords

16S rRNA gene; Heat stress; Fecal microbiome; Sequencing; V3-V4 regions; Differential abundance

Categories

Funding

  1. Wroclaw University of Environmental and Life Sciences (Poland)
  2. Higher Education and Science
  3. China Agriculture Research System of MOF and MARA
  4. Program for Changjiang Scholar and Innovation Research Team in University [IRT_15R62]
  5. National Agricultural Genetic Improvement Program [2130135]
  6. Special Item of Regional Collaborative Innovation in Tibet Autonomous Region [QYXTZX-LS2021-01]

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This study analyzed the microbiome composition in Chinese Holstein cows and identified bacteria associated with heat stress. These bacteria can serve as biomarkers for further microbiological studies and provide insights into the effects of heat stress on cows.
Background Humans have been influencing climate changes by burning fossil fuels, farming livestock, and cutting down rainforests, which has led to global temperature rise. This problem of global warming affects animals by causing heat stress, which negatively affects their health, biological functions, and reproduction. On the molecular level, it has been proved that heat stress changes the expression level of genes and therefore causes changes in proteome and metabolome. The importance of a microbiome in many studies showed that it is considered as individuals' second genome. Physiological changes caused by heat stress may impact the microbiome composition. Results In this study, we identified fecal microbiota associated with heat stress that was quantified by three metrics - rectal temperature, drooling, and respiratory scores represented by their Estimated Breeding Values. We analyzed the microbiota from 136 fecal samples of Chinese Holstein cows through a 16S rRNA gene sequencing approach. Statistical modeling was performed using a negative binomial regression. The analysis revealed the total number of 24 genera and 12 phyla associated with heat stress metrics. Rhizobium and Pseudobutyrivibrio turned out to be the most significant genera, while Acidobacteria and Gemmatimonadetes were the most significant phyla. Phylogenetic analysis revealed that three heat stress indicators quantify different metabolic ways of animals' reaction to heat stress. Other studies already identified that those genera had significantly increased abundance in mice exposed to stressor-induced changes. Conclusions This study provides insights into the analysis of microbiome composition in cattle using heat stress measured as a continuous variable. The bacteria highly associated with heat stress were highlighted and can be used as biomarkers in further microbiological studies.

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