Assessing microbiota composition in the context of aging

Methods Cell Biol. 2024:181:73-85. doi: 10.1016/bs.mcb.2022.12.007. Epub 2023 Feb 8.

Abstract

The gut microbiota is a complex community of different microbial species that influence many aspects of health. Consequently, shifts in the composition of gut microbiome have been proposed to exert negative effects on the host physiology, leading to the pathogenesis of various age-related disorders, including cardiovascular and neurological diseases, type 2 diabetes, obesity, non-alcoholic liver disease, and other pathological conditions. Thus, understanding how the gut microbiota influences the aging-related decline is particularly topical. Advances in next-generation sequencing techniques, together with mechanistic experiments in animal models, have provided substantial improvements in microbiome analysis. However, standardization and best practices are needed to limit experimental variation between different studies. Here, we detail a simple method for microbiota composition analysis in mouse fecal samples using 16S rRNA next-generation sequencing.

Keywords: 16S rRNA sequencing; Aging; Amplicon sequencing; Fecal DNA extraction; Gut microbiota; Microbiome; Mouse models.

MeSH terms

  • Animals
  • Diabetes Mellitus, Type 2*
  • Feces
  • Gastrointestinal Microbiome* / genetics
  • Mice
  • Microbiota* / genetics
  • RNA, Ribosomal, 16S / genetics

Substances

  • RNA, Ribosomal, 16S