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Wei H, He P, Yu D, Liu S, Li C, Qiu D. Characterization of the Positive Transcription Regulator PfaR for Improving Eicosapentaenoic Acid Production in Shewanella putrefaciens W3-18-1. Appl Environ Microbiol 2023; 89:e0002123. [PMID: 36916911 PMCID: PMC10132093 DOI: 10.1128/aem.00021-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 02/17/2023] [Indexed: 03/15/2023] Open
Abstract
The biosynthetic pathway of eicosapentaenoic acid (EPA) has previously been reported in marine bacteria, while the regulatory mechanism remains poorly understood. In this study, a putative transcriptional regulator PfaR encoded adjacent to the PFA biosynthesis gene cluster (pfaEABCD) was computationally and experimentally characterized. Comparative analyses on the wild type (WT) strain, in-frame deletion, and overexpression mutants revealed that PfaR positively regulated EPA synthesis at low temperature. RNA-Seq and real-time quantitative PCR analyses demonstrated that PfaR stimulated the transcription of pfaABCD. The transcription start site of pfaR was mapped by using primer extension and highly conserved promoter motifs bound by the housekeeping Sigma 70 factor that were identified in the upstream of pfaR. Moreover, overexpression of PfaR in WT strain W3-18-1 at low temperature could improve EPA productivity from 0.07% to 0.13% (percentage of EPA to dry weight, mg/mg) of dry weight. Taken together, these findings could provide important implications into the transcriptional control and metabolic engineering in terms of EPA productivity for industrial strains. IMPORTANCE We have experimentally confirmed that PfaR is a positive transcription regulator that promotes EPA synthesis at low temperature in Shewanella putrefaciens W3-18-1. Overexpression of PfaR in WT strain W3-18-1 could lead to a 1.8-fold increase in EPA productivity at low temperature. It is further shown that PfaR may be regulated by housekeeping Sigma 70 factor at low temperature.
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Affiliation(s)
- Hehong Wei
- College of Energy and Environmental Engineering, Hebei University of Engineering, Handan, China
| | - Penghui He
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, China
| | - Dianzhen Yu
- SIBS-UGENT-SJTU Joint Laboratory of Mycotoxin Research, CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, China
| | - Shuangyuan Liu
- Eco-Environmental Monitoring and Research Center, Pearl River Valley and South China Sea Ecology and Environment Administration, Ministry of Ecology and Environment, Guangzhou, China
| | - Chengtao Li
- College of Environmental Science and Engineering, Shaanxi University of Science & Technology, Xi'an, China
| | - Dongru Qiu
- Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
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Zhang M, Jia C, Li F, Li C, Zhu Y, Akutsu T, Webb GI, Zou Q, Coin LJM, Song J. Critical assessment of computational tools for prokaryotic and eukaryotic promoter prediction. Brief Bioinform 2022; 23:6502561. [PMID: 35021193 PMCID: PMC8921625 DOI: 10.1093/bib/bbab551] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 11/12/2021] [Accepted: 11/30/2021] [Indexed: 01/13/2023] Open
Abstract
Promoters are crucial regulatory DNA regions for gene transcriptional activation. Rapid advances in next-generation sequencing technologies have accelerated the accumulation of genome sequences, providing increased training data to inform computational approaches for both prokaryotic and eukaryotic promoter prediction. However, it remains a significant challenge to accurately identify species-specific promoter sequences using computational approaches. To advance computational support for promoter prediction, in this study, we curated 58 comprehensive, up-to-date, benchmark datasets for 7 different species (i.e. Escherichia coli, Bacillus subtilis, Homo sapiens, Mus musculus, Arabidopsis thaliana, Zea mays and Drosophila melanogaster) to assist the research community to assess the relative functionality of alternative approaches and support future research on both prokaryotic and eukaryotic promoters. We revisited 106 predictors published since 2000 for promoter identification (40 for prokaryotic promoter, 61 for eukaryotic promoter, and 5 for both). We systematically evaluated their training datasets, computational methodologies, calculated features, performance and software usability. On the basis of these benchmark datasets, we benchmarked 19 predictors with functioning webservers/local tools and assessed their prediction performance. We found that deep learning and traditional machine learning-based approaches generally outperformed scoring function-based approaches. Taken together, the curated benchmark dataset repository and the benchmarking analysis in this study serve to inform the design and implementation of computational approaches for promoter prediction and facilitate more rigorous comparison of new techniques in the future.
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Affiliation(s)
| | - Cangzhi Jia
- Corresponding authors: Jiangning Song, Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia. E-mail: ; Lachlan J.M. Coin, Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, 792 Elizabeth Street, Melbourne, Victoria 3000, Australia. E-mail: ; Quan Zou, Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China. E-mail: ; Cangzhi Jia, School of Science, Dalian Maritime University, Dalian 116026, China. E-mail:
| | | | | | | | | | - Geoffrey I Webb
- Department of Data Science and Artificial Intelligence, Monash University, Melbourne, VIC 3800, Australia,Monash Data Futures Institute, Monash University, Melbourne, VIC 3800, Australia
| | - Quan Zou
- Corresponding authors: Jiangning Song, Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia. E-mail: ; Lachlan J.M. Coin, Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, 792 Elizabeth Street, Melbourne, Victoria 3000, Australia. E-mail: ; Quan Zou, Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China. E-mail: ; Cangzhi Jia, School of Science, Dalian Maritime University, Dalian 116026, China. E-mail:
| | - Lachlan J M Coin
- Corresponding authors: Jiangning Song, Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia. E-mail: ; Lachlan J.M. Coin, Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, 792 Elizabeth Street, Melbourne, Victoria 3000, Australia. E-mail: ; Quan Zou, Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China. E-mail: ; Cangzhi Jia, School of Science, Dalian Maritime University, Dalian 116026, China. E-mail:
| | - Jiangning Song
- Corresponding authors: Jiangning Song, Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia. E-mail: ; Lachlan J.M. Coin, Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, 792 Elizabeth Street, Melbourne, Victoria 3000, Australia. E-mail: ; Quan Zou, Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China. E-mail: ; Cangzhi Jia, School of Science, Dalian Maritime University, Dalian 116026, China. E-mail:
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Dijkstra AR, Starrenburg MJC, Todt T, van Hijum SAFT, Hugenholtz J, Bron PA. Transcriptome Analysis of a Spray Drying-Resistant Subpopulation Reveals a Zinc-Dependent Mechanism for Robustness in L. lactis SK11. Front Microbiol 2018; 9:2418. [PMID: 30374338 PMCID: PMC6196286 DOI: 10.3389/fmicb.2018.02418] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2018] [Accepted: 09/20/2018] [Indexed: 11/20/2022] Open
Abstract
The viability of starter cultures is essential for an adequate contribution to the fermentation process and end-product. Therefore, robustness during processing and storage is an important characteristic of starter culture strains. For instance, during spray drying cells are exposed to heat and oxidative stress, generally resulting in loss of viability. In this study, we exposed the industrially relevant but stress-sensitive Lactococcus lactis strain SK11 to two cycles of heat stress, with intermediate recovery and cultivation at moderate temperatures. After these two cycles of heat exposure, the abundance of robust derivatives was increased as compared with the original culture, which enabled isolation of heat-resistant subpopulations displaying up to 1,000-fold enhanced heat stress survival. Moreover, this heat-resistant subpopulation demonstrated an increased survival during spray drying. Derivatives from two independent lineages displayed different transcriptome changes as compared with the wild type strain, indicating that the increased robustness within these lineages was established by different adaptive strategies. Nevertheless, an overlap in differential gene expression in all five derivatives tested in both lineages included three genes in an operon involved in zinc transport. The link between zinc homeostasis and heat stress survival in L. lactis was experimentally established by culturing of the wild type strain SK11 in medium with various levels of zinc ions, which resulted in alterations in heat stress survival phenotypes. This study demonstrates that robust derivatives of a relatively sensitive L. lactis strain can be isolated by repeated exposure to heat stress. Moreover, this work demonstrates that transcriptome analysis of these robust derivatives can provide clues for improvement of the robustness of the original strain. This could boost the industrial application of strains with specific desirable traits but inadequate robustness characteristics.
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Affiliation(s)
- Annereinou R Dijkstra
- Kluyver Centre for Genomics of Industrial Fermentation, Delft, Netherlands.,Nederlands Instituut Voor Zuivel Oonderzoek (NIZO), Ede, Netherlands.,Swammerdam Institute for Life Sciences, Universiteit van Amsterdam, Amsterdam, Netherlands
| | | | - Tilman Todt
- Centre for Molecular and Biomolecular Informatics, Radboud umc, Nijmegen, Netherlands
| | - Sacha A F T van Hijum
- Kluyver Centre for Genomics of Industrial Fermentation, Delft, Netherlands.,Nederlands Instituut Voor Zuivel Oonderzoek (NIZO), Ede, Netherlands.,Centre for Molecular and Biomolecular Informatics, Radboud umc, Nijmegen, Netherlands
| | - Jeroen Hugenholtz
- Swammerdam Institute for Life Sciences, Universiteit van Amsterdam, Amsterdam, Netherlands
| | - Peter A Bron
- Kluyver Centre for Genomics of Industrial Fermentation, Delft, Netherlands.,Nederlands Instituut Voor Zuivel Oonderzoek (NIZO), Ede, Netherlands
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Conserved S-Layer-Associated Proteins Revealed by Exoproteomic Survey of S-Layer-Forming Lactobacilli. Appl Environ Microbiol 2015; 82:134-45. [PMID: 26475115 PMCID: PMC4702614 DOI: 10.1128/aem.01968-15] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2015] [Accepted: 10/13/2015] [Indexed: 11/20/2022] Open
Abstract
The Lactobacillus acidophilus homology group comprises Gram-positive species that include L. acidophilus, L. helveticus, L. crispatus, L. amylovorus, L. gallinarum, L. delbrueckii subsp. bulgaricus, L. gasseri, and L. johnsonii. While these bacteria are closely related, they have varied ecological lifestyles as dairy and food fermenters, allochthonous probiotics, or autochthonous commensals of the host gastrointestinal tract. Bacterial cell surface components play a critical role in the molecular dialogue between bacteria and interaction signaling with the intestinal mucosa. Notably, the L. acidophilus complex is distinguished in two clades by the presence or absence of S-layers, which are semiporous crystalline arrays of self-assembling proteinaceous subunits found as the outermost layer of the bacterial cell wall. In this study, S-layer-associated proteins (SLAPs) in the exoproteomes of various S-layer-forming Lactobacillus species were proteomically identified, genomically compared, and transcriptionally analyzed. Four gene regions encoding six putative SLAPs were conserved in the S-layer-forming Lactobacillus species but not identified in the extracts of the closely related progenitor, L. delbrueckii subsp. bulgaricus, which does not produce an S-layer. Therefore, the presence or absence of an S-layer has a clear impact on the exoproteomic composition of Lactobacillus species. This proteomic complexity and differences in the cell surface properties between S-layer- and non-S-layer-forming lactobacilli reveal the potential for SLAPs to mediate intimate probiotic interactions and signaling with the host intestinal mucosa.
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Expression of heterologous sigma factors enables functional screening of metagenomic and heterologous genomic libraries. Nat Commun 2015; 6:7045. [PMID: 25944046 PMCID: PMC4432631 DOI: 10.1038/ncomms8045] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2015] [Accepted: 03/26/2015] [Indexed: 11/20/2022] Open
Abstract
A key limitation in using heterologous genomic or metagenomic libraries in functional genomics and genome engineering is the low expression of heterologous genes in screening hosts, such as Escherichia coli. To overcome this limitation, here we generate E. coli strains capable of recognizing heterologous promoters by expressing heterologous sigma factors. Among seven sigma factors tested, RpoD from Lactobacillus plantarum (Lpl) appears to be able of initiating transcription from all sources of DNA. Using the promoter GFP-trap concept, we successfully screen several heterologous and metagenomic DNA libraries, thus enlarging the genomic space that can be functionally sampled in E. coli. For an application, we show that screening fosmid-based Lpl genomic libraries in an E. coli strain with a chromosomally integrated Lpl rpoD enables the identification of Lpl genetic determinants imparting strong ethanol tolerance in E. coli. Transcriptome analysis confirms increased expression of heterologous genes in the engineered strain. Screening genomic or metagenomic libraries for interesting products or activities is often hampered by poor gene expression in a heterologous host. Here the authors show that the expression of a Lactobacillus sigma factor greatly enhances transcription of heterologous and environmental DNA in E. coli.
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Lloréns-Rico V, Lluch-Senar M, Serrano L. Distinguishing between productive and abortive promoters using a random forest classifier in Mycoplasma pneumoniae. Nucleic Acids Res 2015; 43:3442-53. [PMID: 25779052 PMCID: PMC4402517 DOI: 10.1093/nar/gkv170] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2014] [Accepted: 02/22/2015] [Indexed: 12/01/2022] Open
Abstract
Distinguishing between promoter-like sequences in bacteria that belong to true or abortive promoters, or to those that do not initiate transcription at all, is one of the important challenges in transcriptomics. To address this problem, we have studied the genome-reduced bacterium Mycoplasma pneumoniae, for which the RNAs associated with transcriptional start sites have been recently experimentally identified. We determined the contribution to transcription events of different genomic features: the –10, extended –10 and –35 boxes, the UP element, the bases surrounding the –10 box and the nearest-neighbor free energy of the promoter region. Using a random forest classifier and the aforementioned features transformed into scores, we could distinguish between true, abortive promoters and non-promoters with good –10 box sequences. The methods used in this characterization of promoters can be extended to other bacteria and have important applications for promoter design in bacterial genome engineering.
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Affiliation(s)
- Verónica Lloréns-Rico
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Dr Aiguader 88, 08003 Barcelona, Spain Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Spain
| | - Maria Lluch-Senar
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Dr Aiguader 88, 08003 Barcelona, Spain Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Spain
| | - Luis Serrano
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Dr Aiguader 88, 08003 Barcelona, Spain Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Spain Institució Catalana de Recerca i Estudis Avançats (ICREA), Pg. Lluis Companys 23, 08010 Barcelona, Spain
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