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Protein Families02:47

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Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key...
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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Phage evolutionary relationships emerge from protein language model-based proteome representation.

Swapnesh Panigrahi1, Mireille Ansaldi1, Nicolas Ginet1

  • 1Phage cycle and bacterial metabolism team - Laboratoire de Chimie Bactérienne - UMR7283 CNRS/Aix-Marseille Université, Marseille 13009, France.

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This study introduces hierarchical viruses, a framework using protein Language Model embeddings for bacteriophage genomics. It reveals a multi-scale phage hierarchy that aligns with current taxonomy, enabling large-scale discovery of phage relationships.

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Area of Science:

  • Virology
  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Viral taxonomy faces challenges due to recombination and lack of universal markers.
  • Current viral classification increasingly relies on proteome-based clustering.
  • Expanding viral datasets necessitate scalable methods for analyzing phage relationships.

Purpose of the Study:

  • To develop a framework for comparative genomics of bacteriophages.
  • To leverage protein Language Model (pLM) embeddings for phage proteome representation.
  • To enable large-scale organization, analysis, and discovery of phage evolutionary relationships.

Main Methods:

  • Introduction of the 'hierarchical viruses' framework for bacteriophage comparative genomics.
  • Generation of proteome-wide vector representations using pLM embeddings.
  • Clustering of vector representations for 24,362 phages from the INPHARED dataset.

Main Results:

  • Discovery of a multi-scale hierarchical organization of phages.
  • Demonstration that the hierarchy aligns with ICTV genus and subfamily taxonomic rankings (AMI score > 0.9).
  • Validation of pLM-based proteome representations for capturing evolutionary relationships without multiple sequence alignments.

Conclusions:

  • pLM-based proteome representations effectively capture phage evolutionary relationships.
  • The 'hierarchical viruses' framework facilitates scalable analysis and discovery of phage relationships.
  • This approach lays the foundation for vectorial phage datasets encoding evolutionary information.