The Landscape of Adaptive Evolution of a Gut Commensal Bacteria in Aging Mice.

The Landscape of Adaptive Evolution of a Gut Commensal Bacteria in Aging Mice.

Barreto, Hugo C;Sousa, Ana;Gordo, Isabel;
Current biology : CB 2020 Vol. 30 pp. 1102-1109.e5
296
barreto2020thecurrent

Abstract

Aging is a complex process, with many associated time-dependent phenotypes. The gut microbiota have long been postulated as an important factor in shaping healthy aging [1, 2]. During aging, changes in the microbiota composition occur, with taxa that are rare in adults becoming dominant in the elderly [3, 4]. Increased inflammation associated with aging is also known to modulate and be modulated by the microbiota [5]. Ecological interactions are known to affect the evolution of bacteria both in vitro [6] and in vivo [7], but the extent to which these and the host age-dependent inflammatory environment can alter the pattern of evolutionary change of a gut commensal lineage is still unknown [8]. Here, we provide the first genomic analysis of such evolution in cohorts of old mice, under controlled host genetics and lifestyle conditions. We find that Escherichia coli evolution when colonizing the gut of old mice significantly differs from its evolution in young mice. Evolution toward metabolic adaptation is slower in old than young mice, and mutational targets concerning stress-related functions were found specifically in the inflamed gut of old mice. Taking the genetic basis of E. coli short-term evolution as a reflection of the environment it experiences, the sequencing data indicate that aging imposes a more stressful environment to this important colonizer of the mammalian gut.

Citation

ID: 107545
Ref Key: barreto2020thecurrent
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
107545
Unique Identifier:
S0960-9822(20)30037-3
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet