Comparative Analysis of Core and Accessory Genes in Coexpression Network

Cofitness network connectivity determines a fuzzy essential zone in open bacterial pangenome

Most in silico evolutionary studies commonly assumed that core genes are essential for cellular function, while accessory genes are dispensable, particularly in nutrient-rich environments. However, this assumption is seldom tested genetically within the pangenome context. In this study, we conducted a robust pangenomic Tn-seq analysis of fitness genes in a nutrient-rich medium for Sinorhizobium strains with a canonical open pangenome. To evaluate the robustness of fitness category assignment, Tn-seq data for three independent mutant libraries per strain were analyzed by three methods, which indicates that the Hidden Markov Model (HMM)-based method is most robust to variations between mutant libraries and not sensitive to data size, outperforming the Bayesian and Monte Carlo simulation-based methods. Consequently, the HMM method was used to classify the fitness category. Fitness genes, categorized as essential (ES), advantage (GA), and disadvantage (GD) genes for growth, are enriched in core genes, while nonessential genes (NE) are over-represented in accessory genes. Accessory ES/GA genes showed a lower fitness effect than core ES/GA genes. Connectivity degrees in the cofitness network decrease in the order of ES, GD, and GA/NE. In addition to accessory genes, 1599 out of 3284 core genes display differential essentiality across test strains. Within the pangenome core, both shared quasi-essential (ES and GA) and strain-dependent fitness genes are enriched in similar functional categories. Our analysis demonstrates a considerable fuzzy essential zone determined by cofitness connectivity degrees in Sinorhizobium pangenome and highlights the power of the cofitness network in understanding the genetic basis of ever-increasing prokaryotic pangenome data.

The Ros/MucR Zinc-Finger Protein Family in Bacteria: Structure and Functions

Ros/MucR is a widespread family of bacterial zinc-finger-containing proteins that integrate multiple functions, such as symbiosis, virulence, transcription regulation, motility, production of surface components, and various other physiological processes in cells. This regulatory protein family is conserved in bacteria and is characterized by its zinc-finger motif, which has been proposed as the ancestral domain from which the eukaryotic C₂H₂ zinc-finger structure has evolved. The first prokaryotic zinc-finger domain found in the transcription regulator Ros was identified in Agrobacterium tumefaciens. In the past decades, a large body of evidence revealed Ros/MucR as pleiotropic transcriptional regulators that mainly act as repressors through oligomerization and binding to AT-rich target promoters. The N-terminal domain and the zinc-finger-bearing C-terminal region of these regulatory proteins are engaged in oligomerization and DNA binding, respectively. These properties of the Ros/MucR proteins are similar to those of xenogeneic silencers, such as H-NS, MvaT, and Lsr2, which are mainly found in other lineages. In fact, a novel functional model recently proposed for this protein family suggests that they act as H-NS-'like' gene silencers. The prokaryotic zinc-finger domain exhibits interesting structural and functional features that are different from that of its eukaryotic counterpart (a βββα topology), as it folds in a significantly larger zinc-binding globular domain (a βββαα topology). Phylogenetic analysis of Ros/MucR homologs suggests an ancestral origin of this type of protein in α-Proteobacteria. Furthermore, multiple duplications and lateral gene transfer events contributing to the diversity and phyletic distribution of these regulatory proteins were found in bacterial genomes.

In vivo, in vitro and in silico: an open space for the development of microbe-based applications of synthetic biology

Living systems are studied using three complementary approaches: living cells, cell-free systems and computer-mediated modelling. Progresses in understanding, allowing researchers to create novel chassis and industrial processes rest on a cycle that combines in vivo, in vitro and in silico studies. This design-build-test-learn iteration loop cycle between experiments and analyses combines together physiology, genetics, biochemistry and bioinformatics in a way that keeps going forward. Because computer-aided approaches are not directly constrained by the material nature of the entities of interest, we illustrate here how this virtuous cycle allows researchers to explore chemistry which is foreign to that present in extant life, from whole chassis to novel metabolic cycles. Particular emphasis is placed on the importance of evolution.