Prediction and identification of novel sRNAs involved in Agrobacterium strains by integrated genome-wide and transcriptome-based methods

Virulence and Ecology of Agrobacteria in the Context of Evolutionary Genomics

Among plant-associated bacteria, agrobacteria occupy a special place. These bacteria are feared in the field as agricultural pathogens. They cause abnormal growth deformations and significant economic damage to a broad range of plant species. However, these bacteria are revered in the laboratory as models and tools. They are studied to discover and understand basic biological phenomena and used in fundamental plant research and biotechnology. Agrobacterial pathogenicity and capability for transformation are one and the same and rely on functions encoded largely on their oncogenic plasmids. Here, we synthesize a substantial body of elegant work that elucidated agrobacterial virulence mechanisms and described their ecology. We review findings in the context of the natural diversity that has been recently unveiled for agrobacteria and emphasize their genomics and plasmids. We also identify areas of research that can capitalize on recent findings to further transform our understanding of agrobacterial virulence and ecology.

Identification of sigma factor 54-regulated small non-coding RNAs by employing genome-wide and transcriptome-based methods in rhizobium strains

Rhizobium-legume symbiosis is considered as the major contributor of biological nitrogen fixation. Bacterial small non-coding RNAs are crucial regulators in several cellular adaptation processes that occur due to the changes in metabolism, physiology, or the external environment. Identifying and analysing the conditional specific/sigma factor-54 regulated sRNAs provides a better understanding of sRNA regulation/mechanism in symbiotic association. In the present study, we have identified sigma factor 54-regulated sRNAs from the genome of six rhizobium strains and from the RNA-seq data of free-living and symbiotic conditions of Bradyrhizobium diazoefficiens USDA 110 to identify the novel putative sRNAs that are over expressed during the regulation of nitrogen fixation. A total of 1351 sRNAs were predicted from the genome of six rhizobium strains and 1375 sRNAs were predicted from the transcriptome data of B. diazoefficiens USDA 110. Analysis of target mRNA for these novel sRNAs was inferred to target several nodulation and nitrogen fixation genes including nodC, nodJ, nodY, nodJ, nodM, nodW, nodZ, nifD, nifN, nifQ, fixK, fixL, fdx, nolB, and several cytochrome proteins. In addition, sRNAs of B. diazoefficiens USDA 110 which targeted the regulatory genes of nitrogen fixation were confirmed by wet-lab experiments with semi-quantitative reverse transcription polymerase chain reaction. Predicted target mRNAs were functionally classified based on the COG analysis and GO annotations. The genome-wide and transcriptome-based integrated methods have led to the identification of several sRNAs involved in the nodulation and symbiosis. Further validation of the functional role of these sRNAs can help in exploring the role of sRNAs in nitrogen metabolism during free-living and symbiotic association with legumes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03394-x.

Genome-wide identification of Azospirillum brasilense Sp245 small RNAs responsive to nitrogen starvation and likely involvement in plant-microbe interactions

BACKGROUND

Small RNAs (sRNAs) are non-coding RNAs known to regulate various biological functions such as stress adaptation, metabolism, virulence as well as pathogenicity across a wide range of bacteria, mainly by controlling mRNA stabilization or regulating translation. Identification and functional characterization of sRNAs has been carried out in various plant growth-promoting bacteria and they have been shown to help the cells cope up with environmental stress. No study has been carried out to uncover these regulatory molecules in the diazotrophic alpha-proteobacterium Azospirillum brasilense Sp245 to date.

RESULTS

Expression-based sRNA identification (RNA-seq) revealed the first list of ~ 468 sRNA candidate genes in A. brasilense Sp245 that were differentially expressed in nitrogen starvation versus non-starved conditions. In parallel, in silico tools also identified 2 of the above as candidate sRNAs. Altogether, putative candidates were stringently curated from RNA-seq data based on known sRNA parameters (size, location, secondary structure, and abundance). In total, ~ 59 significantly expressed sRNAs were identified in this study of which 53 are potentially novel sRNAs as they have no Rfam and BSRD homologs. Sixteen sRNAs were randomly selected and validated for differential expression, which largely was found to be in congruence with the RNA-seq data.

CONCLUSIONS

Differential expression of 468 A. brasilense sRNAs was indicated by RNA-seq data, a subset of which was confirmed by expression analysis. Four of the significantly expressed sRNAs were not observed in nitrogen starvation while 16 sRNAs were found to be exclusively expressed in nitrogen depletion. Putative candidate sRNAs identified have potential mRNA targets primarily involved in stress (abiotic and biotic) adaptability; regulation of bacterial cellular, biological and molecular pathways such as nitrogen fixation, polyhydroxybutyrate synthesis, chemotaxis, biofilm formation and transcriptional regulation. In addition to directly influencing bacteria, some of these sRNAs also have targets influencing plant-microbe interactions through adhesion of bacteria to plant roots directly, suppressing host response, inducing plant defence and signalling.

Transcriptome based Identification of silver stress responsive sRNAs from Bacillus cereus ATCC14579

Microbes modulate their metabolic and physiological mechanisms in response to changing environmental conditions. It is our interest to identify small regulatory RNAs using microarray expression data (GSE26043) obtained from B. cereus ATCC 14579 in AgNO3 stress. By definition, expression of transcripts from the Intergenic Regions (IGR) with >=2 fold under silver stress is predicted as novel small RNAs. Computational analysis of the IGR expression levels extracted from the available microarray data help in the identification of stress responsive sRNAs with rare promoters (Sigma 24, 28, 32, 54 and 70) followed by terminator signals predicted using the sRNAscanner tool. We predicted 1512 sRNA specific regions on both positive and negative strands collectively. Thus, a non-redundant high scoring unique 860 sRNAs with distinct promoter (S24: 83, S28: 86, S32: 31, S54: 57, S70: 223, sRNA_specific_S70: 380) and terminator signals are reported. These unique computationally predicted sRNA regions were verified with the highly expressing IGRs from the microarray data. It should be noted that 14 sRNAs reported in earlier studies were also found in this dataset. This study has reported 71 additional sRNAs from the transcriptome under metal stress response. Hence, we use global transcriptomics data for the identification of novel sRNAs in B. cereus. We described a general model using a procedure for the identification of small regulatory RNAs using microarray expression data with appropriate cross validation modules. It is found that some sRNAs reported in this study were found to have multiple rare promoters. This opens the possibility of sRNA activation under multiple stress condition. These sRNA data reported in this study should be characterized for their mRNA targets and molecular functional networks in future investigations.