Achieving Desired Microbial Collective Compositions through Artificial Selection: Challenges and Optimal Experimental Setup

Khái niệm cốt lõi

The success of artificial selection on microbial collectives depends on the target composition and the initial conditions, due to the interplay between intra-collective selection favoring fast-growing types and inter-collective selection aiming to maintain the target composition.

Tóm tắt

The article explores the challenges in achieving desired genotype or species compositions in microbial collectives through artificial selection. It focuses on collectives comprising fast-growing (F) and slow-growing (S) types, and aims to reach specific S frequencies.
Through simulations and analytical calculations, the authors show that intermediate target S frequencies can be elusive to achieve, akin to maintaining a raft's position within a waterfall, rather than above or below it. This is because intra-collective selection, favoring F during growth, is strongest at intermediate S frequencies, which can overpower counteracting inter-collective selection effects.
Achieving low target S frequencies is consistently possible, but high target S frequencies require an initially high S frequency - similar to a raft that can descend but not ascend a waterfall. The range of attainable target frequencies is significantly influenced by the initial population size of the collectives, while the number of collectives under selection plays a less critical role.
The authors also show that the waterfall phenomenon extends to systems with more than two types, where the evolutionary trajectory must navigate entirely away from the metaphorical 'waterfall drop' to achieve the target composition.
The findings illustrate that the strength of intra-collective evolution is frequency-dependent, with implications for experimental planning in artificial selection of microbial collectives.

Thống kê

"Intermediate target S frequencies might be elusive, akin to maintaining a raft's position within a waterfall, rather than above or below it."
"Achieving low target S frequencies is consistently possible, but high target S frequencies require an initially high S frequency - similar to a raft that can descend but not ascend a waterfall."
"The range of attainable target frequencies is significantly influenced by the initial population size of the collectives, while the number of collectives under selection plays a less critical role."

Trích dẫn

"The success of collective selection is constrained by the target composition, and sometimes also by the initial composition."
"Intra-collective selection is akin to a waterfall, driving the S frequency s from high to low."
"Inter-collective selection is akin to a raftman, rowing the raft to a target."

Thông tin chi tiết chính được chắt lọc từ

Artificial selection for microbial collective composition can succeed or fail depending on the initial and target values

by Lee,J., Shou... lúc www.biorxiv.org 03-08-2023

https://www.biorxiv.org/content/10.1101/2023.03.07.531234v3

Yêu cầu sâu hơn

How could the authors' findings be applied to engineer microbial communities for specific functions beyond the two-type system studied

The findings from this study on artificial selection of microbial collectives can be extended to engineer more complex microbial communities for specific functions. By considering systems with more than two types, similar principles can be applied to design and manipulate microbial communities with multiple species. For instance, in a three-type system where each type has different growth rates and interactions, the concept of the "waterfall" phenomenon can guide the selection of target compositions that are stable and achievable. By understanding how intra-collective and inter-collective selection dynamics interact in multi-species systems, researchers can strategically design selection protocols to steer the evolution of microbial communities towards desired functions.
Furthermore, the insights gained from this study can be utilized to optimize the design of synthetic microbial consortia for various applications. By carefully selecting initial compositions and target frequencies based on the principles of the waterfall phenomenon, researchers can enhance the stability and performance of engineered microbial communities. This approach can be particularly valuable in fields such as bioremediation, bioproduction, and ecosystem restoration, where the functionality of microbial communities plays a crucial role in achieving desired outcomes.

What are potential limitations or confounding factors that could affect the generalizability of the waterfall phenomenon observed in this study

While the waterfall phenomenon observed in this study provides valuable insights into the dynamics of artificial selection in microbial collectives, there are potential limitations and confounding factors that could impact its generalizability. One limitation is the simplifying assumptions made in the mathematical models, such as the absence of spatial considerations, environmental fluctuations, and complex interactions among multiple species. In natural microbial ecosystems, factors like spatial heterogeneity, resource availability, and microbial diversity can significantly influence the outcomes of selection processes.
Additionally, the applicability of the waterfall phenomenon may vary depending on the specific characteristics of the microbial community under study. Factors such as mutation rates, growth advantages, and ecological interactions can affect the strength of intra-collective and inter-collective selection, potentially leading to deviations from the predicted outcomes. Furthermore, the scalability of the findings to larger and more diverse microbial communities remains a challenge, as the complexity of interactions increases with the number of species involved.
Overall, while the waterfall phenomenon provides a valuable framework for understanding artificial selection in microbial collectives, its generalizability may be limited by the complexity and variability of natural microbial ecosystems.

How might the insights from this work on artificial selection of microbial collectives inform our understanding of natural selection and evolution in complex microbial ecosystems

The insights gained from this work on artificial selection of microbial collectives can offer valuable perspectives on natural selection and evolution in complex microbial ecosystems. By studying how different types within a collective compete and evolve over time, researchers can gain a deeper understanding of the mechanisms driving evolutionary dynamics in microbial communities.
The concept of the waterfall phenomenon, where the strength of intra-collective evolution is frequency-dependent, can shed light on the interplay between individual-level selection and community-level selection in natural ecosystems. By considering how selection pressures act at different levels of organization, researchers can better comprehend the emergence of cooperative behaviors, niche specialization, and biodiversity in microbial communities.
Furthermore, the study of artificial selection in microbial collectives can provide insights into the adaptive potential of microbial populations facing changing environmental conditions. By observing how microbial communities respond to selective pressures and evolve towards specific compositions, researchers can extrapolate these findings to understand how natural selection shapes the diversity and functionality of microbial ecosystems in various habitats.
In essence, the findings from this work can serve as a bridge between controlled laboratory experiments on artificial selection and the complex dynamics of natural selection in microbial ecosystems, offering a valuable perspective on the evolutionary processes that govern microbial communities.