دورية أكاديمية

Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network.

التفاصيل البيبلوغرافية
العنوان: Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network.
المؤلفون: Lim HG; Department of Bioengineering, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA; Joint BioEnergy Institute, 5885 Hollis Street, 4th Floor, Emeryville, CA, 94608, USA., Rychel K; Department of Bioengineering, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA., Sastry AV; Department of Bioengineering, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA., Bentley GJ; Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO, 80401, USA; Agile BioFoundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Emeryville, CA, 94720, USA., Mueller J; Department of Chemical & Biomolecular Engineering, University of Nebraska-Lincoln, 1400 R St, Lincoln, NE, 68588, USA., Schindel HS; Biosciences Division, Oak Ridge National Laboratory, 5200 Bethel Valley Rd, Oak Ridge, TN, 37830, USA., Larsen PE; Biosciences Division, Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL, 60539, USA., Laible PD; Biosciences Division, Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL, 60539, USA., Guss AM; Agile BioFoundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Emeryville, CA, 94720, USA; Biosciences Division, Oak Ridge National Laboratory, 5200 Bethel Valley Rd, Oak Ridge, TN, 37830, USA., Niu W; Department of Chemical & Biomolecular Engineering, University of Nebraska-Lincoln, 1400 R St, Lincoln, NE, 68588, USA., Johnson CW; Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO, 80401, USA; Agile BioFoundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Emeryville, CA, 94720, USA., Beckham GT; Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO, 80401, USA; Agile BioFoundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Emeryville, CA, 94720, USA., Feist AM; Department of Bioengineering, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA; Joint BioEnergy Institute, 5885 Hollis Street, 4th Floor, Emeryville, CA, 94608, USA; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800, Kgs, Lyngby, Denmark., Palsson BO; Department of Bioengineering, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA; Joint BioEnergy Institute, 5885 Hollis Street, 4th Floor, Emeryville, CA, 94608, USA; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800, Kgs, Lyngby, Denmark; Department of Pediatrics, University of California, San Diego, CA, 92093, USA. Electronic address: palsson@ucsd.edu.
المصدر: Metabolic engineering [Metab Eng] 2022 Jul; Vol. 72, pp. 297-310. Date of Electronic Publication: 2022 Apr 27.
نوع المنشور: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: Academic Press Country of Publication: Belgium NLM ID: 9815657 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1096-7184 (Electronic) Linking ISSN: 10967176 NLM ISO Abbreviation: Metab Eng Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Brugge, Belgium ; Orlando, FL : Academic Press, c1999-
مواضيع طبية MeSH: Pseudomonas putida*/genetics , Pseudomonas putida*/metabolism, Gene Expression Regulation, Bacterial ; Gene Regulatory Networks ; Machine Learning ; Transcription Factors/genetics ; Transcription Factors/metabolism ; Transcriptome
مستخلص: Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida KT2440, an important organism for bioproduction. We performed independent component analysis of a compendium of 321 high-quality gene expression profiles, which were previously published or newly generated in this study. We identified 84 groups of independently modulated genes (iModulons) that explain 75.7% of the total variance in the compendium. With these iModulons, we (i) expand our understanding of the regulatory functions of 39 iModulon associated TFs (e.g., HexR, Zur) by systematic comparison with 1993 previously reported TF-gene interactions; (ii) outline transcriptional changes after the transition from the exponential growth to stationary phases; (iii) capture group of genes required for utilizing diverse carbon sources and increased stationary response with slower growth rates; (iv) unveil multiple evolutionary strategies of transcriptome reallocation to achieve fast growth rates; and (v) define an osmotic stimulon, which includes the Type VI secretion system, as coordination of multiple iModulon activity changes. Taken together, this study provides the first quantitative genome-scale TRN for P. putida KT2440 and a basis for a comprehensive understanding of its complex transcriptome changes in a variety of physiological states.
(Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)
فهرسة مساهمة: Keywords: Independent component analysis; Machine learning; Pseudomonas putida; Systems biology; Transcriptome
المشرفين على المادة: 0 (Transcription Factors)
تواريخ الأحداث: Date Created: 20220430 Date Completed: 20220614 Latest Revision: 20220627
رمز التحديث: 20240628
DOI: 10.1016/j.ymben.2022.04.004
PMID: 35489688
قاعدة البيانات: MEDLINE
الوصف
تدمد:1096-7184
DOI:10.1016/j.ymben.2022.04.004