Student or educator? Sign up with your school email and get 6 months of Pro free.
PreprintCited by 6Plant Pathogenic Bacteria StudiesBacterial Genetics and BiotechnologyPlant-Microbe Interactions and Immunity

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

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

Open access

Preprint — published as 10.7554/elife.96172.3 · Paper page

Abstract

The model Gram-negative plant pathogen Pseudomonas syringae utilises hundreds of transcription factors (TFs) to regulate its functional processes, including virulence and metabolic pathways that control its ability to infect host plants. Although the molecular mechanisms of regulators have been studied for decades, a comprehensive understanding of genome-wide TFs in Psph 1448A remains limited. Here, we investigated the binding characteristics of 170 of 301 annotated TFs through ChIP-seq. Fifty-four TFs, 62 TFs and 147 TFs were identified in top-level, middle-level and bottom-level, reflecting multiple higher-order network structures and direction of information-flow. More than forty thousand TF-pairs were classified into 13 three-node submodules which revealed the regulatory diversity of TFs in Psph 1448A regulatory network. We found that bottom-level TFs performed high co-associated scores to their target genes. Functional categories of TFs at three levels encompassed various regulatory pathways. Three and 25 master TFs were identified to involve in virulence and metabolic regulation, respectively. Evolutionary analysis and topological modularity network revealed functional variability and various conservation of TFs in P. syringae ( Psph 1448A, Pst DC3000, Pss B728a and Psa C48). Overall, our findings demonstrated the global transcriptional regulatory network of genome-wide TFs in Psph 1448A. This knowledge can advance the development of effective treatment and prevention strategies for related infectious diseases.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1101/2024.01.18.576191

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 81

  1. 10.1128/jb.179.18.5655-5662.1997 · DOI · Paper page
  2. 10.1038/nrg2102 · DOI · Paper page
  3. 10.1073/pnas.200327197 · DOI · Paper page
  4. 10.1126/science.1162327 · DOI · Paper page
  5. 10.1093/nar/gkp335 · DOI · Paper page
  6. 10.1038/35014651 · DOI · Paper page
  7. 10.1128/MMBR.63.2.266-292.1999 · DOI
  8. 10.1073/pnas.0910867107 · DOI
  9. 10.1371/journal.ppat.1002621 · DOI
  10. 10.1073/pnas.1731982100 · DOI · Paper page
  11. 10.1073/pnas.1109435108 · DOI
  12. 10.1038/s41598-019-50562-w · DOI
  13. Chan, S. S.-K. , & Kyba, M . (2013). What is a master regulator? Journal of stem cell research & therapy, 3.
  14. 10.1094/MPMI.2003.16.12.1106 · DOI
  15. 10.1016/j.mib.2008.12.003 · DOI · Paper page
  16. 10.1094/MPMI-23-7-0927 · DOI
  17. 10.1093/nar/gku865 · DOI
  18. 10.1094/MPMI-22-8-0964 · DOI
  19. 10.1093/bioinformatics/btn161 · DOI
  20. 2020, A compendium of DNA-binding specificities of transcription factors in Pseudomonas syringae, Nature Communications, 11, 4947, 10.1038/s41467-020-18744-7 · DOI
  21. 10.1128/jb.00538-00517 · DOI
  22. 2022, The Pseudomonas aeruginosa DksA1 protein is involved in H2O2 tolerance and within-macrophages survival and can be replaced by DksA2, Scientific Reports, 12, 10404, 10.1038/s41598-022-14635-7 · DOI
  23. 2015, Evolution of intra-specific regulatory networks in a multipartite bacterial genome, PLoS Computational Biology, 11, e1004478, 10.1371/journal.pcbi.1004478 · DOI
  24. 10.1038/nature11245 · DOI · Paper page
  25. 1984, Ultrasensitivity in biochemical systems controlled by covalent modification. Interplay between zero-order and multistep effects, Journal of Biological Chemistry, 259, 14441, 10.1016/S0021-9258(17)42619-6 · DOI · Paper page
  26. 10.1146/annurev.phyto.36.1.363 · DOI
  27. 10.1128/JB.182.12.3508-3516.2000 · DOI
  28. 10.1128/MMBR.64.3.624-653.2000 · DOI · Paper page
  29. 2022, Bacterial transcription factors bind to coding regions and regulate internal cryptic promoters, MBio, 13, e01643
  30. 2020, Pseudomonas syringae dual-function protein Lon switches between virulence and metabolism by acting as both DNA-binding transcriptional regulator and protease in different environments, Environmental Microbiology, 22, 2968, 10.1111/1462-2920.15067 · DOI
  31. Huang, J. , Yao, C. , Sun, Y. , Ji, Q. , & Deng, X . (2022). Virulence-related regulatory network of Pseudomonas syringae . Computational and Structural Biotechnology Journal. · DOI
  32. 2013, Pathogenicity and virulence factors of Pseudomonas syringae, Journal of general plant pathology, 79, 285, 10.1007/s10327-013-0452-8 · DOI
  33. 10.1093/nar/gkw051 · DOI
  34. 10.1038/35036627 · DOI · Paper page
  35. 10.1016/j.cell.2012.12.009 · DOI
  36. 10.1007/s00438-012-0693-9 · DOI
  37. 10.5555/uri:pii:002221435490222X · doi:10.5555/uri:pii:002221435490222x
  38. Kvitko, B. H. , & Collmer, A . (2011). Construction of Pseudomonas syringae pv. tomato DC3000 mutant and polymutant strains. Plant immunity: methods and protocols, 109–128. · DOI
  39. 10.1016/j.cell.2018.01.029 · DOI · Paper page
  40. 10.1094/MPMI-19-0976 · DOI
  41. 10.1126/science.1075090 · DOI · Paper page
  42. 10.1016/j.cell.2013.02.014 · DOI · Paper page
  43. 10.1093/nar/gkh1009 · DOI
  44. 10.1016/j.tig.2014.12.003 · DOI
  45. 10.1111/j.1365-2958.2005.04677.x · DOI
  46. 10.1126/science.298.5594.824 · DOI · Paper page
  47. 10.1073/pnas.98.2.404 · DOI · Paper page
  48. 10.1073/pnas.0706375104 · DOI · Paper page
  49. 2020, Abscisic acid (ABA)-importing transporter 1 (AIT1) contributes to the inhibition of Cd accumulation via exogenous ABA application in Arabidopsis, Journal of hazardous materials, 391, 122189, 10.1016/j.jhazmat.2020.122189 · DOI
  50. 10.1002/jcb.25605 · DOI
  51. 10.1016/j.cell.2009.07.002 · DOI
  52. 10.1016/j.mib.2010.12.008 · DOI
  53. 10.1016/S0022-2836(02)00994-4 · DOI
  54. 2018, MexEF-OprN multidrug efflux pump transporter negatively controls N-acyl-homoserine lactone accumulation in Pseudomonas syringae pv. tabaci 6605, Molecular genetics and genomics, 293, 907, 10.1007/s00438-018-1430-9 · DOI
  55. 2021, Integrated regulatory network in Pseudomonas syringae reveals dynamics of virulence, Cell Reports, 34, 13
  56. 2019, Biofilm formation assay in Pseudomonas syringae, Bio-protocol, 9, e3237
  57. 10.1038/ng881 · DOI
  58. 10.1016/S0092-8674(01)00494-9 · DOI
  59. 10.1038/35065725 · DOI
  60. 2022, Maintenance of tRNA and elongation factors supports T3SS proteins translational elongations in pathogenic bacteria during nutrient starvation, Cell & Bioscience, 12, 1
  61. 10.1094/MPMI-02-11-0026 · DOI
  62. 10.1093/nar/gkx842 · DOI
  63. 10.1002/(SICI)1521-1878(199805)20:5<433::AID-BIES10>3.0.CO;2-2 · DOI
  64. 10.1093/nar/gkp828 · DOI
  65. 10.1093/nar/gkab928 · DOI
  66. van Duin, L. , Krautz, R. , Rennie, S. , & Andersson, R. (2023). Transcription factor expression is the main determinant of variability in gene co - activity. Molecular Systems Biology, e11392. · DOI
  67. Wade, J. T . (2015). Mapping transcription regulatory networks with ChIP-seq and RNA-seq. Prokaryotic systems biology, 119–134. · DOI
  68. 10.1094/MPMI-02-18-0035-R · DOI
  69. 10.1101/gr.139105.112 · DOI · Paper page
  70. 10.1126/science.295.5559.1487 · DOI · Paper page
  71. 10.1093/nar/gkm964 · DOI · Paper page
  72. 10.1093/nar/gkv1227 · DOI · Paper page
  73. 10.1128/jb.176.10.3089-3091.1994 · DOI
  74. 10.1094/MPMI-20-3-0223 · DOI
  75. 2021, Pseudomonas syringae senses polyphenols via phosphorelay crosstalk to inhibit virulence, EMBO reports, 22, e52805, 10.15252/embr.202152805 · DOI
  76. 2022, An atlas of bacterial two-component systems reveals function and plasticity in signal transduction, Cell Reports, 41, 3
  77. 2019, Regulation of type III secretion system in Pseudomonas syringae, Environmental Microbiology, 21, 4465, 10.1111/1462-2920.14779 · DOI
  78. 2020, Ancient co-option of an amino acid ABC transporter locus in Pseudomonas syringae for host signal-dependent virulence gene regulation, PLoS Pathogens, 16, e1008680, 10.1371/journal.ppat.1008680 · DOI
  79. 10.1186/gb-2008-9-1-r7 · DOI
  80. 10.1101/gr.090233.108 · DOI · Paper page
  81. 10.1186/1471-2105-11-1 · DOI

Metadata

Authors
Sun, Y., Li, J., Huang, J., Li, S., Li, Y., Lu, B., & Deng, X.
Affiliations
  • City University of Hong Kong (HK)
  • University of Hong Kong (HK)
Corresponding author
Deng, Xin
Venue
eLife
Publisher
openRxiv
Published
2024-01-18
Volume
13
ISSN
2050-084X (ISSN-L)
OpenAlex
W4409071371
Cited by
6
References
1
Citations by year
2026: 1 · 2025: 4 · 2024: 1
FWCI
2.72
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • eLife (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
Funders
National Natural Science Foundation of China (32172358, 21103018, 31870116, 31670127)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant Pathogenic Bacteria Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant-Microbe Interactions and Immunity
Keywords
Pseudomonas syringae, transcriptional regulatory networks, transcription factors, ChIP-seq, virulence regulation, metabolic regulation, master transcription factors, network modularity, plant pathogens

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.