Evolution and Plasticity of the Transcriptome Under Temperature Fluctuations in the Fungal Plant Pathogen Zymoseptoria tritici

Jallet, Arthur J.; Rouzic, Arnaud Le; Génissel, Anne

doi:10.3389/fmicb.2020.573829

“…These findings extend observations from previous studies illustrating parallel transcriptome adaptation after imposition of a uniform selection pressure. Under laboratory conditions, convergence towards a shared genic transcriptome has been observed several times in bacteria [ 49 – 52 ] and even in fungi [ 53 ]. One study of P .…”

Section: Discussionmentioning

confidence: 99%

Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth

Youngblom,

Smith,

Murray

et al. 2024

PLoS Pathog

3

0

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Mycobacterium tuberculosis (M. tb), the causative agent of tuberculosis (TB), is a leading global cause of death from infectious disease. Biofilms are increasingly recognized as a relevant growth form during M. tb infection and may impede treatment by enabling bacterial drug and immune tolerance. M. tb has a complicated regulatory network that has been well-characterized for many relevant disease states, including dormancy and hypoxia. However, despite its importance, our knowledge of the genes and pathways involved in biofilm formation is limited. Here we characterize the biofilm transcriptomes of fully virulent clinical isolates and find that the regulatory systems underlying biofilm growth vary widely between strains and are also distinct from regulatory programs associated with other environmental cues. We used experimental evolution to investigate changes to the transcriptome during adaptation to biofilm growth and found that the application of a uniform selection pressure resulted in loss of strain-to-strain variation in gene expression, resulting in a more uniform biofilm transcriptome. The adaptive trajectories of transcriptomes were shaped by the genetic background of the M. tb population leading to convergence on a sub-lineage specific transcriptome. We identified widespread upregulation of non-coding RNA (ncRNA) as a common feature of the biofilm transcriptome and hypothesize that ncRNA function in genome-wide modulation of gene expression, thereby facilitating rapid regulatory responses to new environments. These results reveal a new facet of the M. tb regulatory system and provide valuable insight into how M. tb adapts to new environments.

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“…These findings extend observations from previous studies illustrating parallel transcriptome adaptation after imposition of a uniform selection pressure. Under laboratory conditions, convergence towards a shared genic transcriptome has been observed several times in bacteria (47)(48)(49)(50) and even in fungus (51). One study of P. aeruginosa transcriptomes from an explanted lung showed that genetically distinct strains exhibited minimal variability in their transcriptomes (52),…”

Section: How Do Transcriptomes Evolve?mentioning

confidence: 99%

Adaptation of theMycobacterium tuberculosistranscriptome to biofilm growth

Youngblom

¹

,

Smith

²

,

Pepperell

³

2023

Preprint

0

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Mycobacterium tuberculosis (M. tb), the causative agent of tuberculosis (TB), is a leading global cause of death from infectious disease. Biofilms are increasingly recognized as a relevant growth form during M. tb infection and may impede treatment by enabling bacterial drug and immune tolerance. M. tb has a complicated regulatory network that has been well-characterized for many relevant disease states, including dormancy and hypoxia. However, despite its importance, our knowledge of the genes and pathways involved in biofilm formation is limited. Here we characterize the biofilm transcriptomes of fully virulent clinical isolates and find that the regulatory systems underlying biofilm growth vary widely between strains and are also distinct from regulatory programs associated with other environmental cues. We used experimental evolution to investigate changes to the transcriptome during adaptation to biofilm growth and found that the application of a uniform selection pressure resulted in loss of strain-to-strain variation in gene expression, resulting in a more uniform biofilm transcriptome. The adaptive trajectories of transcriptomes were shaped by the genetic background of the M. tb population leading to convergence on a sub-lineage specific transcriptome. We identified widespread upregulation of non-coding RNA (ncRNA) as a common feature of the biofilm transcriptome and hypothesize that ncRNA function in genome-wide modulation of gene expression, thereby facilitating rapid regulatory responses to new environments. These results reveal a new facet of the M. tb regulatory system and provide valuable insight into how M. tb adapts to new environments.

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“…Because the expression of genes affect phenotypic traits, and thus condition the individual fitness, gene expression levels are believed to be driven by natural selection, at least for a subset of genes. For instance, specific sets of genes have been shown to evolve in a direction consistent with prior knowledge in the wild (Philippe et al, 2007;Verta and Jones, 2019;Huang et al, 2021), or during experimental evolution (Philippe et al, 2007;Ghalambor et al, 2015;Jallet et al, 2020). In contrast, the structure of the network itself is less directly subject to natural selection.…”

Section: Introductionmentioning

confidence: 99%

Correlated stabilizing selection shapes the topology of gene regulatory networks

Petit

¹

,

Guez

²

,

Rouzic

³

2023

Self Cite

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The evolution of gene expression is constrained by the topology of gene regulatory networks, as co-expressed genes are likely to have their expressions affected together by mutations. Conversely, co-expression can also be an advantage when genes are under joint selection. Here, we assessed theoretically whether correlated selection (selection for a combination of traits) was able to affect the pattern of correlated gene expressions and the underlying gene regulatory networks. We ran individual-based simulations, applying a stabilizing correlated fitness function to three genetic architectures: a quantitative genetics (multilinear) model featuring epistasis and pleiotropy, a quantitative genetics model where each genes has an independent mutational structure, and a gene regulatory network model, mimicking the mechanisms of gene expression regulation. Simulations showed that correlated mutational effects evolved in the three genetic architectures as a response to correlated selection, but the response in gene networks was specific. The intensity of gene co-expression was mostly explained by the regulatory distance between genes (largest correlations being associated to genes directly interacting with each other), and the sign of co-expression was associated with the nature of the regulation (transcription activation or inhibition). These results concur to the idea that gene network topologies could partly reflect past selection patterns on gene expression.

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Evolution and Plasticity of the Transcriptome Under Temperature Fluctuations in the Fungal Plant Pathogen Zymoseptoria tritici

Cited by 7 publications

References 92 publications

Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth

Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth

Adaptation of theMycobacterium tuberculosistranscriptome to biofilm growth

Correlated stabilizing selection shapes the topology of gene regulatory networks

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