Evolution of generalists by phenotypic plasticity

Fraebel, David T.; Gowda, Karna; Mani, Madhav; Kuehn, Seppe

doi:10.1101/761288

Cited by 3 publications

(5 citation statements)

References 43 publications

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“…i ) provide the most predictive power while also avoiding overfitting. In situations where the levels of noise are not too high and a sparse solution (small number of non-zero b k ) do allow for good predictions, these regularization methods typically succeed (Fraebel et al, 2020). However, if the noise levels are high or the underlying process is not sparse, then even these methods will fail.…”

Section: Ll Open Accessmentioning

confidence: 99%

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An ensemble approach to the structure-function problem in microbial communities

et al. 2022

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The metabolic activity of microbial communities plays a primary role in the flow of essential nutrients throughout the biosphere. Molecular genetics has revealed the metabolic pathways that model organisms utilize to generate energy and biomass, but we understand little about how the metabolism of diverse, natural communities emerges from the collective action of its constituents. We propose that quantifying and mapping metabolic fluxes to sequencing measurements of genomic, taxonomic, or transcriptional variation across an ensemble of diverse communities, either in the laboratory or in the wild, can reveal low-dimensional descriptions of community structure that can explain or predict their emergent metabolic activity. We survey the types of communities for which this approach might be best suited, review the analytical techniques available for quantifying metabolite fluxes in communities, and discuss what types of data analysis approaches might be lucrative for learning the structure-function mapping in communities from these data.

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Section: Ll Open Accessmentioning

confidence: 99%

“…However, if the noise levels are high or the underlying process is not sparse, then even these methods will fail. Care must be taken in diagnosing when such a regression works and when it does not, see (Fraebel et al, 2020;Gowda et al, 2022).…”

Section: Ll Open Accessmentioning

confidence: 99%

An ensemble approach to the structure-function problem in microbial communities

et al. 2022

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“…Regularization provides a solution to the problem of selecting which regressors (entries of x i ) provide the most predictive power while also avoiding overfitting. In situations where the levels of noise are not too high and a sparse solution (small number of nonzero β k ) do allow for good predictions, these regularization methods typically succeed [218]. However, if the noise levels are high or the underlying process is not sparse, then even these methods will fail.…”

Section: Dimension Reduction: With or Without Supervisionmentioning

confidence: 99%

Section: Dimension Reduction: With or Without Supervisionmentioning

confidence: 99%

An ensemble approach to the structure-function problem in microbial communities

Gopalakrishnappa,

Gowda,

Prabhakara

et al. 2021

Preprint

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The metabolic activity of microbes has played an essential role in the evolution and persistence of life on Earth. Microbial metabolism plays a primary role in the flow of carbon, nitrogen and other essential resources through the biosphere on a global scale. Microbes perform these metabolic activities in the context of complex communities comprised of many species that interact in dynamic and spatially-structured environments. Molecular genetics has revealed many of the metabolic pathways microbes utilize to generate energy and biomass. However, most of this knowledge is derived from model organisms, so we have a limited view of role of the massive genomic diversity in the wild on metabolic phenotypes. Further, we are only beginning to get a glimpse of the principles governing how the metabolism of a community emerges from the collective action of its constituent members. As a result, one of the biggest challenges in the field is to understand how the metabolic activity of a community emerges from the genomic structure of the constituents. Here we propose an approach to this problem that rests on the quantitative analysis of metabolic activity in ensembles of microbial communities. We propose quantifying metabolic fluxes in diverse communities, either in the laboratory or the wild. We suggest that using sequencing data to quantify the genomic, taxonomic or transcriptional variation across an

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“…This theme has been investigated in developmental and evolutionary biology in detail [2,3], and is gaining importance in the context of disease progression as well [4][5][6][7]. Further, this theme is well-studied in cases of bacterial and yeast populations [8][9][10][11][12], and is increasingly being investigated for mammalian cells as well [13][14][15]. Mechanisms underlying phenotypic plasticity and consequent non-mutational or non-genetic heterogeneity, and their implications in determining the fitness of individual cells and entire cell populations remain to be comprehensively elucidated [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Coupled feedback loops involving PAGE4, EMT and Notch signaling can give rise to non-genetic heterogeneity in prostate cancer cells

Singh

Bocci

Kulkarni

et al. 2020

Preprint

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Non-genetic heterogeneity is emerging to be a crucial factor underlying therapy resistance in multiple cancers. However, the design principles of regulatory networks underlying non-genetic heterogeneity in cancer remain poorly understood. Here, we investigate the coupled dynamics of feedback loops involving a) oscillations in androgen receptor (AR) signaling mediated through an intrinsically disordered protein PAGE4, b) multistability in epithelial-mesenchymal transition (EMT), and c) Notch-Delta-Jagged signaling mediated cell-cell communication, each of which can generate non-genetic heterogeneity through multistability and/or oscillations. Our results show how different coupling strengths between AR and EMT signaling can lead to possible bistability in the levels of AR. These results reveal the emergent dynamics of coupled oscillatory and multi-stable systems and unravel mechanisms by which non-genetic heterogeneity in AR levels can be generated, which can act as a barrier to most existing therapies for prostate cancer patients.

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Evolution of generalists by phenotypic plasticity

Cited by 3 publications

References 43 publications

An ensemble approach to the structure-function problem in microbial communities

An ensemble approach to the structure-function problem in microbial communities

An ensemble approach to the structure-function problem in microbial communities

Coupled feedback loops involving PAGE4, EMT and Notch signaling can give rise to non-genetic heterogeneity in prostate cancer cells

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