The microbial pan-genome

TL;DR: The main goal is to establish the total number of non-redundant genes that are present in a determined dataset and to perform all of the required calculations, a substantial amount of software has been developed, based on orthologous and paralogous gene identification.

TL;DR: Application of machine learning algorithms to predict whether specific strains were resistant to antibiotic drugs yielded the best prediction accuracy for the set of AMR genes within the accessory part of the pan‐genome, suggesting that these gene clusters were most crucial to AMR activities in E. coli.

TL;DR: Multiple lines of evidence suggested that Lb.

TL;DR: Krupovic et al. as mentioned in this paper reconstructed the last universal cellular ancestor (LUCA) virome by projecting back in time using the extant distribution of viruses across the two primary domains of life, bacteria and archaea.

TL;DR: Over 1.2 million previously unknown genes represented in these samples, including more than 782 new rhodopsin-like photoreceptors are identified, suggesting substantial oceanic microbial diversity.

TL;DR: The genomic sequence of six strains representing the five major disease-causing serotypes of Streptococcus agalactiae, the main cause of neonatal infection in humans, was generated and Mathematical extrapolation of the data suggests that the gene reservoir available for inclusion in the S. agalactic pan-genome is vast and that unique genes will continue to be identified even after sequencing hundreds of genomes.

TL;DR: Mobile elements within genomes have driven genome evolution in diverse ways and are becoming useful tools for learning more about genome evolution and gene function.

TL;DR: The current review presents the available genomics and biological data on prophages from bacterial pathogens in an evolutionary framework to demonstrate that the chromosomes from bacteria and their viruses (bacteriophages) are coevolving.