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Related Experiment Video

Updated: Jun 21, 2025

Author Spotlight: Methods for Electroporation and Transformation Confirmation in Limosilactobacillus reuteri DSM20016
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Convergent reductive evolution in bee-associated lactic acid bacteria.

Ana Pontes1,2, Marie-Claire Harrison3,4, Antonis Rokas3,4

  • 1Associate Laboratory i4HB-Institute for Health and Bioeconomy and UCIBIO-Applied Molecular Biosciences Unit, Department of Life Sciences, NOVA School of Science and Technology, Universidade NOVA de Lisboa, Caparica, Portugal.

Biorxiv : the Preprint Server for Biology
|July 15, 2024
PubMed
Summary
This summary is machine-generated.

Convergent evolution in bee-associated bacteria (LAB) shows independent gene loss driving unique traits like fructophily. Machine learning identified these adaptation patterns, highlighting shared genomic changes in distantly related species.

Keywords:
bee symbiontsconvergent evolutionfructophilic lactic acid bacteria (FLAB)gene lossmachine learningreductive evolution

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Empirical, Metagenomic, and Computational Techniques Illuminate the Mechanisms by which Fungicides Compromise Bee Health
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Area of Science:

  • Microbial Genomics and Evolution
  • Bacterial Adaptation and Speciation
  • Symbiotic Microbiology

Background:

  • Distantly related organisms can evolve similar traits (convergent evolution) when adapting to similar environments or lifestyles.
  • Many Lactic Acid Bacteria (LAB) species are found in the floral niche, particularly associated with bees.
  • Bee-associated LAB exhibit unique genomic (e.g., genome reduction) and phenotypic (e.g., fructophily) traits, suggesting convergent adaptation.

Purpose of the Study:

  • To test the hypothesis that specific genomic and phenotypic traits in bee-associated LAB evolved convergently.
  • To investigate the role of gene loss in the adaptation of LAB to the floral niche.
  • To identify genomic fingerprints of adaptation and instances of convergent evolution using machine learning.

Main Methods:

  • Phylogenomic analysis of 369 representative genomes of bee-associated and non-bee-associated LAB.
  • Comparative genomic analysis to identify genome reduction (size, gene repertoire, GC content).
  • Machine learning classification to distinguish bee-associated from non-bee-associated LAB based on gene content.

Main Results:

  • Seven independent ecological shifts to the floral niche were identified in LAB.
  • Bee-associated LAB showed significant genome reduction and loss of genes related to metabolism, osmotic stress, and DNA repair.
  • Machine learning accurately (94%) distinguished bee-associated from non-bee-associated species, with key genes like 'adhE' (aldehyde-alcohol dehydrogenase) frequently lost independently.

Conclusions:

  • Convergent evolution, driven by independent loss of the same genes, underlies the distinctive phenotypes of bee-associated LAB.
  • Gene loss, particularly of 'adhE', is linked to the evolution of fructophily, a key trait in floral LAB.
  • Machine learning is a powerful tool for detecting adaptation patterns and convergent evolution in microbial genomes.