Similar solutions to a common challenge: regulation of genes encoding Ralstonia solanacearum xanthine dehydrogenase

Quantitative proteomics analysis reveals an important role of the transcriptional regulator UidR in the bacterial biofilm formation of Aeromonas hydrophila

Introduction

Bacterial biofilm is a well-known characteristic that plays important roles in diverse physiological functions, whereas the current intrinsic regulatory mechanism of its formation is still largely unknown.

Methods

In the present study, a label-free based quantitative proteomics technology was conducted to compare the differentially expressed proteins (DEPs) between ΔuidR and the wild-type strain in the biofilm state.

Results

The results showed that the deletion of gene uidR encoding a TetR transcriptional regulator significantly increased the biofilm formation in Aeromonas hydrophila. And there was a total of 220 DEPs, including 120 up-regulated proteins and 100 down-regulated proteins between ΔuidR and the wild-type strain based on the quantitative proteomics. Bioinformatics analysis suggested that uidR may affect bacterial biofilm formation by regulating some related proteins in glyoxylic acid and dicarboxylic acid pathway. The expressions of selected proteins involved in this pathway were further confirmed by q-PCR assay, and the results was in accordance with the quantitative proteomics data. Moreover, the deletion of four genes (AHA_3063, AHA_3062, AHA_4140 and aceB) related to the glyoxylic acid and dicarboxylic acid pathway lead to a significant decrease in the biofilm formation.

Discussion

Thus, the results indicated that uidR involved in the regulatory of bacterial biofilm formation, and it may provide a potential target for the drug development and a new clue for the prevention of pathogenic A. hydrophila in the future.

A catalogue of signal molecules that interact with sensor kinases, chemoreceptors and transcriptional regulators

Bacteria have evolved many different signal transduction systems that sense signals and generate a variety of responses. Generally, most abundant are transcriptional regulators, sensor histidine kinases and chemoreceptors. Typically, these systems recognize their signal molecules with dedicated ligand-binding domains (LBDs), which, in turn, generate a molecular stimulus that modulates the activity of the output module. There are an enormous number of different LBDs that recognize a similarly diverse set of signals. To give a global perspective of the signals that interact with transcriptional regulators, sensor kinases and chemoreceptors, we manually retrieved information on the protein-ligand interaction from about 1,200 publications and 3D structures. The resulting 811 proteins were classified according to the Pfam family into 127 groups. These data permit a delineation of the signal profiles of individual LBD families as well as distinguishing between families that recognize signals in a promiscuous manner and those that possess a well-defined ligand range. A major bottleneck in the field is the fact that the signal input of many signaling systems is unknown. The signal repertoire reported here will help the scientific community design experimental strategies to identify the signaling molecules for uncharacterised sensor proteins.