Spatial-temporal genome analysis and its application for the prediction of functional systems in bacteria and archaea

ABSTRACT Evolution of prokaryotic genomes is highly dynamic, including extensive gene gain via horizontal gene transfer and gene loss, as well as different types of genome rearrangements. Most quantitative analyses of prokaryotic genome evolution are based on single-gene events, although the distribution of genes is known to be non-random at the scales of operons and various genomic islands. Here, we present a spatial-temporal phylogenomic approach for detecting arrays of genes that are likely to have been acquired as a single block. It is shown that the acquisition of multi-gene blocks makes a major contribution to prokaryotic genome evolution and that these blocks consist primarily of co-directed, functionally coherent genes. A detailed analysis of the spatial-temporal data for the genomes of multiple groups of bacteria and archaea shows that the larger blocks of co-acquired genes represent primarily mobile genetic elements (MGEs), in many cases not identified previously. For example, this includes a new group of pleolipoviruses in Haloarchaea and a group of MGEs specific for Bacteroidota with hypervariable gene content and carrying a unique RNA polymerase enzyme. We also show that some ancestral phage-related large islands correspond to previously unnoticed R-type pyocins in Proteus and Morganella genomes. Many of the smaller gene blocks prone to high genome flux are expected to comprise antivirus defense systems and toxins-antitoxins. In a pilot analysis, eight novel toxin-antitoxin and seven novel defense systems were predicted in archaea of the phylum Thermococcaceae . IMPORTANCE With many thousands of diverse bacterial and archaeal genomes made available by the fast advancing genomic and metagenomic sequencing, methods for in-depth analysis of genome organization and evolution are essential for extracting the maximum amount of information from this wealth of genomic data. We present a spatial-temporal approach for genome analysis that detects blocks of genes that were simultaneously acquired during genome evolution and shows that genes in such blocks are mostly transcribed in the same direction and have related functions, allowing for the prediction of previously unknown functional systems. The predictive power of the approach is demonstrated by detecting multiple novel mobile genetic elements and antivirus defense systems. Unlike most other functional prediction methods, the spatial-temporal approach does not require prior knowledge of the functions of any genes and has the potential to predict hundreds of novel functional systems amenable to further in-depth study, especially for poorly characterized groups of bacteria and archaea.