Rapid dissemination of host metabolism-manipulating genes via integrative and conjugative elements.

Integrative and conjugative elements (ICEs) are self-transmissible mobile elements that transfer functional genetic units across broad phylogenetic distances. Accessory genes shuttled by ICEs can make significant contributions to bacterial fitness. Most ICEs characterized to date encode readily observable phenotypes contributing to symbiosis, pathogenicity, and antimicrobial resistance, yet the majority of ICEs carry genes of unknown function. Recent observations of rapid acquisition of ICEs in a pandemic lineage of Pseudomonas syringae pv. actinidae led to investigation of the structural and functional diversity of these elements. Fifty-three unique ICE types were identified across the P. syringae species complex. Together they form a distinct family of ICEs (PsICEs) that share a distant relationship to ICEs found in Pseudomonas aeruginosa. PsICEs are defined by conserved backbone genes punctuated by an array of accessory cargo genes, are highly recombinogenic, and display distinct evolutionary histories compared to their bacterial hosts. The most common cargo is a recently disseminated 16-kb mobile genetic element designated Tn6212. Deletion of Tn6212 did not alter pathogen growth in planta, but mutants displayed fitness defects when grown on tricarboxylic acid (TCA) cycle intermediates. RNA-seq analysis of a set of nested deletion mutants showed that a Tn6212-encoded LysR regulator has global effects on chromosomal gene expression. We show that Tn6212 responds to preferred carbon sources and manipulates bacterial metabolism to maximize growth.

Chromosome conformation maps in fission yeast reveal cell cycle dependent sub nuclear structure.

Successful progression through the cell cycle requires spatial and temporal regulation of gene transcript levels and the number, positions and condensation levels of chromosomes. Here we present a high resolution survey of genome interactions in Schizosaccharomyces pombe using synchronized cells to investigate cell cycle dependent changes in genome organization and transcription. Cell cycle dependent interactions were captured between and within S. pombe chromosomes. Known features of genome organization (e.g. the clustering of telomeres and retrotransposon long terminal repeats (LTRs)) were observed throughout the cell cycle. There were clear correlations between transcript levels and chromosomal interactions between genes, consistent with a role for interactions in transcriptional regulation at specific stages of the cell cycle. In silico reconstructions of the chromosome organization within the S. pombe nuclei were made by polymer modeling. These models suggest that groups of genes with high and low, or differentially regulated transcript levels have preferred positions within the S. pombe nucleus. We conclude that the S. pombe nucleus is spatially divided into functional sub-nuclear domains that correlate with gene activity. The observation that chromosomal interactions are maintained even when chromosomes are fully condensed in M phase implicates genome organization in epigenetic inheritance and bookmarking.

The statistical-mechanics of chromosome conformation capture.

Since Jacob and Monod's characterization of the role of DNA elements in gene control, it has been recognized that the linear organization of genome structure is important for the regulation of gene transcription and hence the manifestation of phenotypes. Similarly, it has long been hypothesized that the spatial organization (in three dimensions evolving through time), as part of the epigenome, makes a significant contribution to the genotype-phenotype transition. Proximity ligation assays commonly known as chromosome conformation capture (3C) and 3C based methodologies (e.g., GCC, HiC and ChIA-Pet) are increasingly being incorporated into empirical studies to investigate the role that three-dimensional genome structure plays in the regulation of phenotype. The apparent simplicity of these methodologies-crosslink chromatin, digest, dilute, ligate, detect interactions-belies the complexity of the data and the considerations that should be taken into account to ensure the generation and accurate interpretation of reliable data. Here we discuss the probabilistic nature of these methodologies and how this contributes to their endogenous limitations.