| Literature DB >> 34427985 |
Patrícia Apura1, Luis G Gonçalves1, Sandra C Viegas1, Cecília M Arraiano1.
Abstract
The development of synthetic biology has brought an unprecedented increase in the number molecular tools applicable into a microbial chassis. The exploration of such tools into different bacteria revealed not only the challenges of context dependency of biological functions but also the complexity and diversity of regulatory layers in bacterial cells. Most of the standardized genetic tools and principles/functions have been mostly based on model microorganisms, namely Escherichia coli. In contrast, the non-model pseudomonads lack a deeper understanding of their regulatory layers and have limited molecular tools. They are resistant pathogens and promising alternative bacterial chassis, making them attractive targets for further studies. Ribonucleases (RNases) are key players in the post-transcriptional control of gene expression by degrading or processing the RNA molecules in the cell. These enzymes act according to the cellular requirements and can also be seen as the recyclers of ribonucleotides, allowing a continuous input of these cellular resources. This makes these post-transcriptional regulators perfect candidates to regulate microbial physiology. This review summarizes the current knowledge and unique properties of ribonucleases in the world of pseudomonads, taking into account genomic context analysis, biological function and strategies to use ribonucleases to improve biotechnological processes.Entities:
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Year: 2021 PMID: 34427985 PMCID: PMC8601179 DOI: 10.1111/1751-7915.13890
Source DB: PubMed Journal: Microb Biotechnol ISSN: 1751-7915 Impact factor: 5.813
Essentiality of ribonuclease genes in E. coli and Pseudomonas.
| Ribonuclease | Gene | Essentiality | Mutants available in | |
|---|---|---|---|---|
|
|
| |||
| RNase E |
| Yes | Yes |
|
|
| ||||
| YbeY |
| No | Yes |
|
| RNase III |
| No | Conditional |
|
| RNase G |
| No | No |
|
| MazF |
| No | No |
|
| PNPase |
| No | Yes |
|
| RNase PH |
| No | No | – |
| RNase R |
| No | No |
|
| Oligoribonuclease |
| Yes | No |
|
Details on the essentiality of ribonuclease genes in E. coli and P. aeruginosa, as predicted from studies that created Tn‐mutant libraries (third column). On the right column are indicated the ribonuclease mutants available in different pseudomonads, based on experimental data details discriminated on the bottom row.
As predicted from Tn‐mutant libraries in P. aeruginosa (Lee et al., 2015; Poulsen et al., 2019).
based on experimental evidence.
Fig. 1Comparison of the genomic context of the ribonuclease genes in different Pseudomonas strains (P. aeruginosa PAO1, P. putida KT2440, P. fluorescens SBW25, P. syringae pv. tomato DC300) and Escherichia coli K12. Ribonucleases are divided according to specificity of activity in endoribonucleases and exoribonucleases (panels A and B, respectively). Ribonuclease genes are colour‐highlighted, and each arrow corresponds to a gene that is identified by its name and/or the corresponding locus tag. The genomic context of each Pseudomonas’ RNase was retrieved from the Pseudomonas Genome database [http://www.pseudomonas.com; (Winsor et al., 2016)] and/or Microbial Genome Annotation & Analysis Platform (MicroScope) (Vallenet et al., 2020). E. coli genomic context was retrieved from xBASE (Chaudhuri et al., 2008).
Fig. 2Distribution of P. putida strains with different RNase mutations based on their phenotypes. The area under the growth curve of the different phenotypes tested in BIOLOG analysis performed by Apura et al. (2021) for the P. putida KT2440 (WT) and 5 RNase single mutant strains: RNase G‐, RNase EN‐term, RNase III‐, RNase R‐ and PNPase‐ were used as variables for a principal component analysis (PCA). The analysis was performed in R with the package FactoMineR, the variables were scaled using UV and centred. (A) PCA score graph, with three principal components. First component (PC1) is responsible for 64.7% of variation; PC2 responsible for 18.6% of variance and PC3 responsible for 8.2% of variance. Different strains are colour‐highlighted: WT (red), RNase G‐ (grey), RNase EN‐term (yellow), RNase III‐ (pink), RNase R‐ (green) and PNPase‐ (blue). (B) Top 20 positive and negative phenotypes responsible for the PC1. (C) Top 20 positive and negative phenotypes responsible for the PC2. (D) Top 20 positive and negative phenotypes responsible for the PC3. Phenotypes increased in the PC are in red, while phenotypes decreased in the PC are in green (in panels B, C and D).