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Record W4396924195 · doi:10.1128/msystems.01135-23

<i>SoxY</i> gene family expansion underpins adaptation to diverse hosts and environments in symbiotic sulfide oxidizers

2024· article· en· W4396924195 on OpenAlexaff
Marta Sudo, Jay Osvatic, John D. Taylor, Suzanne C. Dufour, Anchana Prathep, Laetitia Wilkins, Thomas Rattei, Benedict Yuen, Jillian M. Petersen

Bibliographic record

VenuemSystems · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsMemorial University of Newfoundland
FundersUniversität WienÖsterreichischen Akademie der WissenschaftenVienna Science and Technology FundAustrian Science FundMedizinische Universität WienEuropean Commission
KeywordsBiologySymbiosisEcologyGenomeAdaptation (eye)Host adaptationGeneralist and specialist speciesRange (aeronautics)Evolutionary biologyHabitatGeneGeneticsBacteria

Abstract

fetched live from OpenAlex

ABSTRACT Sulfur-oxidizing bacteria (SOB) have developed distinct ecological strategies to obtain reduced sulfur compounds for growth. These range from specialists that can only use a limited range of reduced sulfur compounds to generalists that can use many different forms as electron donors. Forming intimate symbioses with animal hosts is another highly successful ecological strategy for SOB, as animals, through their behavior and physiology, can enable access to sulfur compounds. Symbioses have evolved multiple times in a range of animal hosts and from several lineages of SOB. They have successfully colonized a wide range of habitats, from seagrass beds to hydrothermal vents, with varying availability of symbiont energy sources. Our extensive analyses of sulfur transformation pathways in 234 genomes of symbiotic and free-living SOB revealed widespread conservation in metabolic pathways for sulfur oxidation in symbionts from different host species and environments, raising the question of how they have adapted to such a wide range of distinct habitats. We discovered a gene family expansion of soxY in these genomes, with up to five distinct copies per genome. Symbionts harboring only the “canonical” soxY were typically ecological “specialists” that are associated with specific host subfamilies or environments (e.g., hydrothermal vents, mangroves). Conversely, symbionts with multiple divergent soxY genes formed versatile associations across diverse hosts in various marine environments. We hypothesize that expansion and diversification of the soxY gene family could be one genomic mechanism supporting the metabolic flexibility of symbiotic SOB enabling them and their hosts to thrive in a range of different and dynamic environments. IMPORTANCE Sulfur metabolism is thought to be one of the most ancient mechanisms for energy generation in microorganisms. A diverse range of microorganisms today rely on sulfur oxidation for their metabolism. They can be free-living, or they can live in symbiosis with animal hosts, where they power entire ecosystems in the absence of light, such as in the deep sea. In the millions of years since they evolved, sulfur-oxidizing bacteria have adopted several highly successful strategies; some are ecological “specialists,” and some are “generalists,” but which genetic features underpin these ecological strategies are not well understood. We discovered a gene family that has become expanded in those species that also seem to be “generalists,” revealing that duplication, repurposing, and reshuffling existing genes can be a powerful mechanism driving ecological lifestyle shifts.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.018
GPT teacher head0.224
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations17
Published2024
Admission routes1
Has abstractyes

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