The highly conserved MraZ protein is a transcriptional regulator in Escherichia coli

MioC and GidA proteins promote cell division in E. coli

The well-conserved genes surrounding the E. coli replication origin, mioC and gidA, do not normally affect chromosome replication and have little known function. We report that mioC and gidA mutants exhibit a moderate cell division inhibition phenotype. Cell elongation is exacerbated by a fis deletion, likely owing to delayed replication and subsequent cell cycle stress. Measurements of replication initiation frequency and origin segregation indicate that mioC and gidA do not inhibit cell division through any effect on oriC function. Division inhibition is also independent of the two known replication/cell division checkpoints, SOS and nucleoid occlusion. Complementation analysis indicates that mioC and gidA affect cell division in trans, indicating their effect is at the protein level. Transcriptome analysis by RNA sequencing showed that expression of a cell division septum component, YmgF, is significantly altered in mioC and gidA mutants. Our data reveal new roles for the gene products of gidA and mioC in the division apparatus, and we propose that their expression, cyclically regulated by chromatin remodeling at oriC, is part of a cell cycle regulatory program coordinating replication initiation and cell division.

Protein complexes in bacteria

Large-scale analyses of protein complexes have recently become available for Escherichia coli and Mycoplasma pneumoniae, yielding 443 and 116 heteromultimeric soluble protein complexes, respectively. We have coupled the results of these mass spectrometry-characterized protein complexes with the 285 “gold standard” protein complexes identified by EcoCyc. A comparison with databases of gene orthology, conservation, and essentiality identified proteins conserved or lost in complexes of other species. For instance, of 285 “gold standard” protein complexes in E. coli, less than 10% are fully conserved among a set of 7 distantly-related bacterial “model” species. Complex conservation follows one of three models: well-conserved complexes, complexes with a conserved core, and complexes with partial conservation but no conserved core. Expanding the comparison to 894 distinct bacterial genomes illustrates fractional conservation and the limits of co-conservation among components of protein complexes: just 14 out of 285 model protein complexes are perfectly conserved across 95% of the genomes used, yet we predict more than 180 may be partially conserved across at least half of the genomes. No clear relationship between gene essentiality and protein complex conservation is observed, as even poorly conserved complexes contain a significant number of essential proteins. Finally, we identify 183 complexes containing well-conserved components and uncharacterized proteins which will be interesting targets for future experimental studies.

Though more than 20,000 binary protein-protein interactions have been published for a few well-studied bacterial species, the results rarely capture the full extent to which proteins take part in complexes. Here, we use experimentally-observed protein complexes from E. coli or Mycoplasma pneumoniae, as well as gene orthology, to predict protein complexes across many species of bacteria. Surprisingly, the majority of protein complexes is not conserved, demonstrating an unexpected evolutionary flexibility. We also observe broader trends within protein complex conservation, especially in genome-reduced species with minimal sets of protein complexes.

Detecting rare structural variation in evolving microbial populations from new sequence junctions using breseq

New mutations leading to structural variation (SV) in genomes—in the form of mobile element insertions, large deletions, gene duplications, and other chromosomal rearrangements—can play a key role in microbial evolution. Yet, SV is considerably more difficult to predict from short-read genome resequencing data than single-nucleotide substitutions and indels (SN), so it is not yet routinely identified in studies that profile population-level genetic diversity over time in evolution experiments. We implemented an algorithm for detecting polymorphic SV as part of the breseq computational pipeline. This procedure examines split-read alignments, in which the two ends of a single sequencing read match disjoint locations in the reference genome, in order to detect structural variants and estimate their frequencies within a sample. We tested our algorithm using simulated Escherichia coli data and then applied it to 500- and 1000-generation population samples from the Lenski E. coli long-term evolution experiment (LTEE). Knowledge of genes that are targets of selection in the LTEE and mutations present in previously analyzed clonal isolates allowed us to evaluate the accuracy of our procedure. Overall, SV accounted for ~25% of the genetic diversity found in these samples. By profiling rare SV, we were able to identify many cases where alternative mutations in key genes transiently competed within a single population. We also found, unexpectedly, that mutations in two genes that rose to prominence at these early time points always went extinct in the long term. Because it is not limited by the base-calling error rate of the sequencing technology, our approach for identifying rare SV in whole-population samples may have a lower detection limit than similar predictions of SNs in these data sets. We anticipate that this functionality of breseq will be useful for providing a more complete picture of genome dynamics during evolution experiments with haploid microorganisms.