Assessment of transfer methods for comparative genomics of regulatory networks in bacteria

Corynebacterium glutamicum Regulation beyond Transcription: Organizing Principles and Reconstruction of an Extended Regulatory Network Incorporating Regulations Mediated by Small RNA and Protein-Protein Interactions

Corynebacterium glutamicum is a Gram-positive bacterium found in soil where the condition changes demand plasticity of the regulatory machinery. The study of such machinery at the global scale has been challenged by the lack of data integration. Here, we report three regulatory network models for C. glutamicum: strong (3040 interactions) constructed solely with regulations previously supported by directed experiments; all evidence (4665 interactions) containing the strong network, regulations previously supported by nondirected experiments, and protein-protein interactions with a direct effect on gene transcription; sRNA (5222 interactions) containing the all evidence network and sRNA-mediated regulations. Compared to the previous version (2018), the strong and all evidence networks increased by 75 and 1225 interactions, respectively. We analyzed the system-level components of the three networks to identify how they differ and compared their structures against those for the networks of more than 40 species. The inclusion of the sRNA-mediated regulations changed the proportions of the system-level components and increased the number of modules but decreased their size. The C. glutamicum regulatory structure contrasted with other bacterial regulatory networks. Finally, we used the strong networks of three model organisms to provide insights and future directions of the C.glutamicum regulatory network characterization.

Flexible comparative genomics of prokaryotic transcriptional regulatory networks

Background

Comparative genomics methods enable the reconstruction of bacterial regulatory networks using available experimental data. In spite of their potential for accelerating research into the composition and evolution of bacterial regulons, few comparative genomics suites have been developed for the automated analysis of these regulatory systems. Available solutions typically rely on precomputed databases for operon and ortholog predictions, limiting the scope of analyses to processed complete genomes, and several key issues such as the transfer of experimental information or the integration of regulatory information in a probabilistic setting remain largely unaddressed.

Results

Here we introduce CGB, a flexible platform for comparative genomics of prokaryotic regulons. CGB has few external dependencies and enables fully customized analyses of newly available genome data. The platform automates the merging of experimental information and uses a gene-centered, Bayesian framework to generate and integrate easily interpretable results. We demonstrate its flexibility and power by analyzing the evolution of type III secretion system regulation in pathogenic Proteobacteria and by characterizing the SOS regulon of a new bacterial phylum, the Balneolaeota.

Conclusions

Our results demonstrate the applicability of the CGB pipeline in multiple settings. CGB’s ability to automatically integrate experimental information from multiple sources and use complete and draft genomic data, coupled with its non-reliance on precomputed databases and its easily interpretable display of gene-centered posterior probabilities of regulation provide users with an unprecedented level of flexibility in launching comparative genomics analyses of prokaryotic transcriptional regulatory networks. The analyses of type III secretion and SOS response regulatory networks illustrate instances of convergent and divergent evolution of these regulatory systems, showcasing the power of formal ancestral state reconstruction at inferring the evolutionary history of regulatory networks.

CoryneRegNet 7, the reference database and analysis platform for corynebacterial gene regulatory networks

We present the newest version of CoryneRegNet, the reference database for corynebacterial regulatory interactions, available at www.exbio.wzw.tum.de/coryneregnet/. The exponential growth of next-generation sequencing data in recent years has allowed a better understanding of bacterial molecular mechanisms. Transcriptional regulation is one of the most important mechanisms for bacterial adaptation and survival. These mechanisms may be understood via an organism's network of regulatory interactions. Although the Corynebacterium genus is important in medical, veterinary and biotechnological research, little is known concerning the transcriptional regulation of these bacteria. Here, we unravel transcriptional regulatory networks (TRNs) for 224 corynebacterial strains by utilizing genome-scale transfer of TRNs from four model organisms and assigning statistical significance values to all predicted regulations. As a result, the number of corynebacterial strains with TRNs increased twenty times and the back-end and front-end were reimplemented to support new features as well as future database growth. CoryneRegNet 7 is the largest TRN database for the Corynebacterium genus and aids in elucidating transcriptional mechanisms enabling adaptation, survival and infection.

An in silico analysis of acquired antimicrobial resistance genes in Aeromonas plasmids

Sequences of 105 Aeromonas species plasmids were probed for acquired anti-microbial resistance (AMR) genes using a bioinformatics approach. The plasmids showed no positive linear correlation between size and GC content and up to 55 acquired AMR genes were found in 39 (37%) plasmids after in silico screening for resistance against 15 antibiotic drug classes. Overall, potential multiple antibiotic resistance (p-MAR) index ranged from 0.07 to 0.53. Up to 18 plasmids were predicted to mediate multiple drug resistance (MDR). Plasmids pS121-1a (A. salmonicida), pWCX23_1 (A. hydrophila) and pASP-a58 (A. veronii) harboured 18, 15 and 14 AMR genes respectively. The five most occurring drug classes for which AMR genes were detected were aminoglycosides (27%), followed by beta-lactams (17%), sulphonamides (13%), fluoroquinolones (13%), and phenicols (10%). The most prevalent genes were a sulphonamide resistant gene Sul1, the gene aac (6')-Ib-cr (aminoglycoside 6'-N-acetyl transferase type Ib-cr) resistant to aminoglycosides and the blaKPC-2 gene, which encodes carbapenemase-production. Plasmid acquisition of AMR genes was mainly inter-genus rather than intra-genus. Eighteen plasmids showed template or host genes acquired from Pseudomonas monteilii, Salmonella enterica or Escherichia coli. The most occurring antimicrobial resistance determinants (ARDs) were beta-lactamase, followed by aminoglycosides acetyl-transferases, and then efflux pumps. Screening of new isolates in vitro and in vivo is required to ascertain the level of phenotypic expression of colistin and other acquired AMR genes detected.