Microbial Cell Factories (Mar 2022)

Assess the diversity of gut microbiota among healthy adults for forensic application

  • Shuangshuang Wang,
  • Feng Song,
  • Haoyu Gu,
  • Zhilong Shu,
  • Xiaowen Wei,
  • Ke Zhang,
  • Yuxiang Zhou,
  • Lanrui Jiang,
  • Zefei Wang,
  • Jienan Li,
  • Haibo Luo,
  • Weibo Liang

DOI
https://doi.org/10.1186/s12934-022-01769-6
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 12

Abstract

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Abstract Background Human gut microbiota is individually unique that hints the microbiota in fecal traces left in the crime scene could act as a potential biomarker for forensic personal identification. Next-generation DNA sequencing and bioinformatic analysis of fecal samples are revolutionizing our insights into gut microbial communities. While the formation of the gut microbiota is known to be multifactorial, it is unclear whether these characteristics can be applied to forensic applications. Therefore, the gut microbiota of healthy adults with different traits was investigated in this study. Results Based on the STAMP analysis of each study group, the difference in gut microbiota composition of male and female subjects was observed. The male group was characterized by taxa in the phylum Proteobacteria, while the female group was described by Synergistetes phylum. The gut bacterial community assembly mechanism was mainly affected by the deterministic process. In addition, gut microbiota composition showed meaningful discrimination in each of the BMI groups. At the phylum level, in male subjects, increased representative phyla were Patescibacteria (p < 0.05) in the underweight group and Bacteroidetes (p < 0.05) in the normal-weight group, while in the female group, the significantly different phyla were Bacteroidetes, Firmicutes, and Actinobacteria. At the genus level, 44 unique genera were found to be significantly distinct across BMI study groups. By Fisher’s Linear Discriminant Analysis, ninety-four point four percent (94.4%) of original BMI grouped subjects were correctly classified. The linear regression analysis model showed an accuracy of seventy-four percent (74%) in predicting body type. Conclusion In conclusion, subjects with different individual characters have specific gut microbiota, and can be discriminated by bioinformatics methods, suggesting it is promising to apply gut microbiota to forensic personal identification.

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