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Record W2541297604 · doi:10.1098/rspb.2016.1458

Molecular and cellular bases of adaptation to a changing environment in microorganisms

2016· review· en· W2541297604 on OpenAlexafffund
Clara Bleuven, Christian R. Landry

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsUniversité LavalPROTEO
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsPleiotropyAdaptation (eye)BiologyMechanism (biology)GeneMolecular evolutionCellular adaptationNatural selectionEvolutionary biologyAdaptive responseComputational biologyAdaptive evolutionGeneticsPhenotypeGenomeSelection (genetic algorithm)Computer scienceNeuroscience

Abstract

fetched live from OpenAlex

Environmental heterogeneity constitutes an evolutionary challenge for organisms. While evolutionary dynamics under variable conditions has been explored for decades, we still know relatively little about the cellular and molecular mechanisms involved. It is of paramount importance to examine these molecular bases because they may play an important role in shaping the course of evolution. In this review, we examine the diversity of adaptive mechanisms in the face of environmental changes. We exploit the recent literature on microbial systems because those have benefited the most from the recent emergence of genetic engineering and experimental evolution followed by genome sequencing. We identify four emerging trends: (i) an adaptive molecular change in a pathway often results in fitness trade-off in alternative environments but the effects are dependent on a mutation's genetic background; (ii) adaptive changes often modify transcriptional and signalling pathways; (iii) several adaptive changes may occur within the same molecular pathway but be associated with pleiotropy of different signs across environments; (iv) because of their large associated costs, macromolecular changes such as gene amplification and aneuploidy may be a rapid mechanism of adaptation in the short-term only. The course of adaptation in a variable environment, therefore, depends on the complexity of the environment but also on the molecular relationships among the genes involved and between the genes and the phenotypes under selection.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.733
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.252
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations112
Published2016
Admission routes2
Has abstractyes

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