Architecture of genome-wide transcriptional regulatory network reveals dynamic functions and evolutionary trajectories in Pseudomonas syringae

  1. Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, China
  2. The University of Hong Kong, Pokfulam, Hong Kong, China
  3. Shenzhen Research Institute, City University of Hong Kong, Shenzhen, Guangdong, China
  4. Tung Biomedical Sciences Center, City University of Hong Kong, Hong Kong, China
  5. Chengdu Research Institute, City University of Hong Kong, Chengdu, China

Editors

  • Reviewing Editor
    Kenichi Tsuda
    Huazhong Agricultural University, Wuhan, China
  • Senior Editor
    Detlef Weigel
    Max Planck Institute for Biology Tübingen, Tübingen, Germany

Reviewer #1 (Public Review):

In this work, the authors provide a comprehensive description of transcriptional regulation in Pseudomonas syringae by investigating the binding characteristics of various transcription factors. They uncover the hierarchical network structure of the transcriptome by identifying top-, middle-, and bottom-level transcription factors that govern the flow of information in the network. Additionally, they assess the functional variability and conservation of transcription factors across different strains of P. syringae by studying DNA-binding characteristics. These findings notably expand our current knowledge of the P. syringae transcriptome.

The findings associated with crosstalk between transcription factors and pathways, and the diversity of transcription factor functions across strains provide valuable insights into the transcriptional regulatory network of P. syringae. However, these results are at times underwhelming as their significance is unclear. This study would benefit from a discussion of the implications of transcription factor crosstalk on the functioning of the organism as a whole. Additionally, the implications of variability in transcription factor functions on the phenotype of the strains studied would further this analysis.

Overall, this manuscript serves as a key resource for researchers studying the transcriptional regulatory network of P. syringae.

Reviewer #2 (Public Review):

Summary:

The phytopathogenic bacterium Pseudomonas syringae is comprised of many pathovars with different host plant species and has been used as a model organism to study bacterial pathogenesis in plants. Transcriptional regulation is key to plant infection and adaptation to host environments by this bacterium. However, researchers have focused on a limited number of transcription factors (TFs) that regulate virulence-related pathways. Thus, a comprehensive, systems-level understanding of regulatory interactions between transcription factors in P. syringae has not been achieved.

This study by Sun et al performed ChIP-seq analysis of 170 out of 301 TFs in P. syringae pv. syringae 1448A and used this unique dataset to infer transcriptional regulatory networks in this bacterium. The network analyses revealed hierarchical interactions between TFs, various network motifs, and co-regulation of target genes by TF pairs, which collectively mediate information flow. As discussed, the structure and properties of the P. syringae transcriptional regulatory networks are somewhat different from those identified in humans, yeast, and E. coli, highlighting the significance of this study. Further, the authors made use of the P. syringae transcriptional regulatory networks to find TFs of unknown functions to be involved in virulence-related pathways. For some of these TFs, their target specificity and biological functions, such as motility and biofilm formation, were experimentally validated. Of particular interest is the finding that despite conservation of TFs between P. syringae pv. syringae 1448A, P. syringae pv. tomato DC3000, P. syringae pv. syringae B728a, and P. syringae pv. actinidiae C48, some of the conserved TFs show different repertoires of target genes in these four P. syringae strains.

Strengths:

This study presents a systems-level analysis of transcriptional regulatory networks in relation to P. syringae virulence and metabolism, and highlights differences in transcriptional regulatory landscapes of conserved TFs between different P. syringae strains, and develops a user-friendly database for mining the ChIP-seq data generated in this study. These findings and resources will be valuable to researchers in the fields of systems biology, bacteriology, and plant-microbe interactions.

Weaknesses:

No major weaknesses were found, but some of the results may need to be interpreted with caution. ChIP-seq was performed with bacterial strains overexpressing TFs. This may cause artificial binding of TFs to promoters which may not occur when TFs are expressed at physiological levels. Another caution is applied to the interpretation of the biological functions of TFs. The biological roles of the tested TFs are based on in vitro experiments. Thus, functional relevance of the tested TFs during plant infection and/or survival under natural environmental conditions remains to be demonstrated.

Reviewer #3 (Public Review):

Summary:

This study aims to understand gene regulation of the plant bacterial pathogen Pseudomonas syringae. Although the function of some TFs has been characterized in this strain, a global picture of the gene regulatory network remains elusive. The authors conducted a large-scale ChIP-seq analysis, covering 170 out of 301 TFs of this strain, and revealed gene regulatory hierarchy with functional validation of some previously uncharacterized TFs.

Strengths:

- This study provides one of the largest ChIP-seq datasets for a single bacterial strain, covering more than half of its TFs. This impressive resource enabled comprehensive systems-level analysis of the TF hierarchy.

- This study identified novel gene regulation and function with validations through biochemical and genetic experiments.

- The authors attempted on broad analyses including comparisons between different bacterial strains, providing further insights into the diversity and conservation of gene regulatory mechanisms.

Weaknesses:

(1) Some conclusions are not backed by quantitative or statistical analyses, and they are sometimes overinterpreted.

(2) Some figures and analyses are not well explained, and I was not able to understand them.

(3) The Method section lacks depth, especially in data analyses. It is strongly recommended that the authors share their analysis codes so that others can reproduce the analyses.

  1. Howard Hughes Medical Institute
  2. Wellcome Trust
  3. Max-Planck-Gesellschaft
  4. Knut and Alice Wallenberg Foundation