Related Experiment Video
Updated: May 8, 2025
04:52
Following the Dynamics of Structural Variants in Experimentally Evolved Populations
Published on: February 3, 2023
898
Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes arising during coevolutionary
Adriana Lucia-Sanz1, Shengyun Peng2, Chung Yin Joey Leung3
1School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Virus Evolution
|December 25, 2024
Summary
Predicting phage-bacteria interactions is challenging. Machine learning accurately forecasts infection outcomes by analyzing phage and bacterial genetics, identifying key mutations driving these interactions.
Area of Science:
- Microbiology
- Genetics
- Bioinformatics
Background:
- Bacteriophage (phage) and bacteria interactions are complex due to uncharacterized genetic factors.
- Predicting specific phage-host interactions remains a significant challenge in microbial ecology.
Purpose of the Study:
- To develop a machine learning framework for predicting phage-bacteria interactions.
- To identify genetic drivers influencing phage infection outcomes.
Main Methods:
- Trained a machine learning model on genome sequences and phenotypic interactions of coevolved Escherichia coli and phage lambda strains.
- Employed multiple inference strategies without prior knowledge of driver mutations.
- Predicted infection phenotypes and quantitative infection levels for 2,295 potential interactions.
Main Results:
- The most effective model accurately predicted 86% of phage-bacteria interactions.
- Reduced the error in estimating infection strength by 40%.
- Identified key phage lambda and E. coli mutations influencing interaction outcomes, including novel resistance-associated mutations.
Conclusions:
- Machine learning can accurately predict phage-bacteria infection outcomes and identify genetic determinants.
- This approach advances understanding of coevolutionary dynamics and can inform strategies for complex microbial communities.
Related Concept Videos
00:43Lysogenic Cycle of Bacteriophages
61.3K
In contrast to the lytic cycle, phages infecting bacteria via the lysogenic cycle do not immediately kill their host cell. Instead, they combine their genome with the host genome, allowing the bacteria to replicate the phage DNA along with the bacterial genome. The incorporated copy of the phage genome is called the prophage. Some prophages can re-activate and enter the lytic cycle. This often occurs in response to a perturbation, such as DNA damage, but can also transpire in the absence of...
61.3K
01:30Lytic Cycle of Bacteriophages
69.8K
Bacteriophages, also known as phages, are specialized viruses that infect bacteria. A key characteristic of phages is their distinctive “head-tail” morphology. A phage begins the infection process (i.e., lytic cycle) by attaching to the outside of a bacterial cell. Attachment is accomplished via proteins in the phage tail that bind to specific receptor proteins on the outer surface of the bacterium. The tail injects the phage’s DNA genome into the bacterial cytoplasm. In the...
69.8K
00:36Viral Mutations
32.0K
A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...
32.0K
00:57Antibiotic Selection
51.8K
Overview
51.8K
01:39Epistasis
43.1K
In addition to multiple alleles at the same locus influencing traits, numerous genes or alleles at different locations may interact and influence phenotypes in a phenomenon called epistasis. For example, rabbit fur can be black or brown depending on whether the animal is homozygous dominant or heterozygous at a TYRP1 locus. However, if the rabbit is also homozygous recessive at a locus on the tyrosinase gene (TYR), it will have an unshaded coat that appears white, regardless of its TYRP1...
43.1K
01:09Mutation, Gene Flow, and Genetic Drift
57.4K
In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
57.4K