Reversions Mask the Extent of Adaptive Evolution in Microbiomes

Core Concepts

Adaptive reversions, rather than weak purifying selection, can explain the timescale dependence of dN/dS in bacterial genomes, suggesting that adaptive evolution is more prevalent than previously thought.

Abstract

The content examines the time-dependent changes in the ratio of nonsynonymous to synonymous mutations (dN/dS) in bacterial populations, particularly in the human gut microbiome. It challenges the conventional view that high dN/dS values over short timescales are an artifact of weak purifying selection.
The key insights are:

The traditional purifying selection model struggles to replicate theoretical results in realistic population sizes, as it requires an unrealistic prevalence of weakly deleterious mutations that are difficult to eliminate effectively.

The authors propose an alternative model in which adaptive reversions, driven by constantly changing environmental pressures, can explain the observed timescale dependence of dN/dS. Reversions that sweep within-host populations are likely in microbiomes due to large population sizes, short generation times, and variable environments.

The adaptive reversion model fits the empirical data well, with reasonable parameter estimates in the context of bacterial genomics. It suggests that adaptive dynamics can be significantly underestimated from the genomic record, as apparent and actual dN/dS values can diverge quickly.

The success of the reversion model highlights the importance of simulating large population sizes, the potential for local adaptation in bacterial populations, and the need for continued population genetics work on microbial systems.

Stats

"Even within a bacterial species, genomes separated by larger mutational distances exhibit stronger evidence of purifying selection as assessed by dN/dS."
"Fitting the data from Garud & Good et al [14], we infer median values of α ≈ .10 (0.09-0.14) and s ≈ 3.5 × 10-5 (2.6× 10-5-6.5 × 10-5) across all species."
"The value of µN/s for the above fits is ∼29, indicating that most cells in the population contain dozens of deleterious mutations."

Quotes

"Notably, the value of µN/s for the above fits is ∼29, indicating that most cells in the population contain dozens of deleterious mutations."
"Reversions are likely to occur in large populations when mutations are adaptive locally but deleterious in other environments. In the gut microbiome, these alternative environments could represent different hosts."
"Given a mutation rate of 10-9 per site per generation, we anticipate 10 mutants at any given site each generation. Consequently, if selection strongly benefits a reverting mutation (i.e. >1% selective benefit), a genotype with a beneficial mutation is essentially guaranteed to emerge within days to weeks and replace its ancestors within the host within months to years."

Key Insights Distilled From

Reversions mask the contribution of adaptive evolution in microbiomes

by Torrillo,P. ... at www.biorxiv.org 09-17-2023

https://www.biorxiv.org/content/10.1101/2023.09.14.557751v1

Deeper Inquiries

How might the dynamics of adaptive reversions differ in smaller microbial populations, such as those found in environmental or industrial settings, compared to the large gut microbiome populations considered here?

In smaller microbial populations, such as those found in environmental or industrial settings, the dynamics of adaptive reversions may differ in several key ways. Firstly, the smaller population size would likely result in a higher impact of genetic drift on the fate of mutations. With fewer individuals, the random fluctuation in allele frequencies due to genetic drift could play a more significant role in determining which mutations become fixed in the population. This could affect the likelihood of adaptive reversions reaching fixation.
Additionally, in smaller populations, the rate of adaptation and fixation of mutations may be slower compared to the large gut microbiome populations. With fewer individuals and potentially lower mutation rates, the process of adaptive evolution, including the occurrence of reversions, may take longer to manifest in smaller populations. This slower rate of evolution could impact the overall genetic diversity and adaptive potential of the population.
Furthermore, the environmental and selective pressures in smaller microbial populations may be more homogeneous compared to the diverse and fluctuating conditions found in the gut microbiome. This could influence the types of mutations that are beneficial or deleterious in these populations, potentially affecting the occurrence and frequency of adaptive reversions.

How might the dynamics of adaptive reversions differ in smaller microbial populations, such as those found in environmental or industrial settings, compared to the large gut microbiome populations considered here?

In smaller microbial populations, such as those found in environmental or industrial settings, the dynamics of adaptive reversions may differ in several key ways. Firstly, the smaller population size would likely result in a higher impact of genetic drift on the fate of mutations. With fewer individuals, the random fluctuation in allele frequencies due to genetic drift could play a more significant role in determining which mutations become fixed in the population. This could affect the likelihood of adaptive reversions reaching fixation.
Additionally, in smaller populations, the rate of adaptation and fixation of mutations may be slower compared to the large gut microbiome populations. With fewer individuals and potentially lower mutation rates, the process of adaptive evolution, including the occurrence of reversions, may take longer to manifest in smaller populations. This slower rate of evolution could impact the overall genetic diversity and adaptive potential of the population.
Furthermore, the environmental and selective pressures in smaller microbial populations may be more homogeneous compared to the diverse and fluctuating conditions found in the gut microbiome. This could influence the types of mutations that are beneficial or deleterious in these populations, potentially affecting the occurrence and frequency of adaptive reversions.

What experimental or observational evidence would be needed to directly confirm the occurrence of adaptive reversions in bacterial genomes, beyond the indirect inferences made in this study?

Directly confirming the occurrence of adaptive reversions in bacterial genomes would require specific experimental or observational evidence. One approach could involve longitudinal studies tracking bacterial populations over time to observe the emergence and fixation of specific mutations, including potential reversions. This would involve whole-genome sequencing of bacterial isolates at multiple time points to identify genetic changes, including reversions, that occur in response to environmental pressures.
Another experimental approach could involve targeted genetic manipulation experiments in the laboratory to introduce specific mutations and observe the subsequent occurrence of reversions under different selective conditions. By creating controlled evolutionary scenarios, researchers could directly observe the dynamics of adaptive reversions and their impact on bacterial fitness.
Additionally, comparative genomic analyses of closely related bacterial strains or species could provide insights into the prevalence and patterns of adaptive reversions. By examining the genetic differences between strains that have adapted to different environments, researchers could identify signatures of reversions and assess their role in adaptive evolution.

Could the principles of adaptive reversions uncovered here be extended to understand evolutionary dynamics in other rapidly evolving biological systems, such as viral populations or cancer cell lineages?

The principles of adaptive reversions uncovered in bacterial genomes could indeed be extended to understand evolutionary dynamics in other rapidly evolving biological systems, such as viral populations or cancer cell lineages. In viral populations, where high mutation rates and rapid evolution are common, adaptive reversions could play a significant role in the emergence of drug resistance or immune evasion. By studying the occurrence of reversions in viral genomes under different selective pressures, researchers could gain insights into the mechanisms of viral adaptation.
Similarly, in cancer cell lineages, where genetic mutations drive tumor evolution and progression, adaptive reversions could contribute to the development of treatment resistance and tumor heterogeneity. Understanding the dynamics of reversions in cancer genomes could provide valuable information for developing targeted therapies and predicting treatment outcomes.
Overall, the concept of adaptive reversions as a mechanism for rapid adaptation and evolutionary change is a fundamental principle that can be applied across diverse biological systems to enhance our understanding of evolutionary dynamics and the emergence of genetic diversity.