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Record W2151100623 · doi:10.1128/mbio.00076-15

Xenorhabdus bovienii Strain Diversity Impacts Coevolution and Symbiotic Maintenance with <i>Steinernema</i> spp. Nematode Hosts

2015· article· en· W2151100623 on OpenAlexfundno aff
Kristen E. Murfin, Ming-Min Lee, Jonathan L. Klassen, Bradon R. McDonald, Bret Larget, Steven Forst, S. Patricia Stock, Cameron R. Currie, Heidi Goodrich‐Blair

Bibliographic record

VenuemBio · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEntomopathogenic Microorganisms in Pest Control
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNatural Sciences and Engineering Research Council of CanadaGreat Lakes Bioenergy Research CenterOffice of ScienceBrigham Young UniversityNational Institute of General Medical SciencesUniversidad de Costa RicaU.S. Department of EnergyNational Institutes of HealthNational Science Foundation
KeywordsBiologyCoevolutionSymbiosisMutualism (biology)Symbiotic bacteriaHost (biology)NematodeStrain (injury)Phylogenetic treeEcologyEvolutionary biologyBacteriaGeneticsGene

Abstract

fetched live from OpenAlex

UNLABELLED: Microbial symbionts provide benefits that contribute to the ecology and fitness of host plants and animals. Therefore, the evolutionary success of plants and animals fundamentally depends on long-term maintenance of beneficial associations. Most work investigating coevolution and symbiotic maintenance has focused on species-level associations, and studies are lacking that assess the impact of bacterial strain diversity on symbiotic associations within a coevolutionary framework. Here, we demonstrate that fitness in mutualism varies depending on bacterial strain identity, and this is consistent with variation shaping phylogenetic patterns and maintenance through fitness benefits. Through genome sequencing of nine bacterial symbiont strains and cophylogenetic analysis, we demonstrate diversity among Xenorhabdus bovienii bacteria. Further, we identified cocladogenesis between Steinernema feltiae nematode hosts and their corresponding X. bovienii symbiont strains, indicating potential specificity within the association. To test the specificity, we performed laboratory crosses of nematode hosts with native and nonnative symbiont strains, which revealed that combinations with the native bacterial symbiont and closely related strains performed significantly better than those with more divergent symbionts. Through genomic analyses we also defined potential factors contributing to specificity between nematode hosts and bacterial symbionts. These results suggest that strain-level diversity (e.g., subspecies-level differences) in microbial symbionts can drive variation in the success of host-microbe associations, and this suggests that these differences in symbiotic success could contribute to maintenance of the symbiosis over an evolutionary time scale. IMPORTANCE: Beneficial symbioses between microbes and plant or animal hosts are ubiquitous, and in these associations, microbial symbionts provide key benefits to their hosts. As such, host success is fundamentally dependent on long-term maintenance of beneficial associations. Prolonged association between partners in evolutionary time is expected to result in interactions in which only specific partners can fully support symbiosis. The contribution of bacterial strain diversity on specificity and coevolution in a beneficial symbiosis remains unclear. In this study, we demonstrate that strain-level differences in fitness benefits occur in beneficial host-microbe interactions, and this variation likely shapes phylogenetic patterns and symbiotic maintenance. This highlights that symbiont contributions to host biology can vary significantly based on very-fine-scale differences among members of a microbial species. Further, this work emphasizes the need for greater phylogenetic resolution when considering the causes and consequences of host-microbe interactions.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 science0.0000.001
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 head0.013
GPT teacher head0.183
Teacher spread0.170 · 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 designObservational
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

Citations75
Published2015
Admission routes1
Has abstractyes

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