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Daakour S, Nelson DR, Fu W, Jaiswal A, Dohai B, Alzahmi AS, Koussa J, Huang X, Shen Y, Twizere JC, Salehi-Ashtiani K. Adaptive Evolution Signatures in Prochlorococcus: Open Reading Frame (ORF)eome Resources and Insights from Comparative Genomics. Microorganisms 2024; 12:1720. [PMID: 39203562 PMCID: PMC11357015 DOI: 10.3390/microorganisms12081720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 07/30/2024] [Accepted: 08/13/2024] [Indexed: 09/03/2024] Open
Abstract
Prochlorococcus, a cyanobacteria genus of the smallest and most abundant oceanic phototrophs, encompasses ecotype strains adapted to high-light (HL) and low-light (LL) niches. To elucidate the adaptive evolution of this genus, we analyzed 40 Prochlorococcus marinus ORFeomes, including two cornerstone strains, MED4 and NATL1A. Employing deep learning with robust statistical methods, we detected new protein family distributions in the strains and identified key genes differentiating the HL and LL strains. The HL strains harbor genes (ABC-2 transporters) related to stress resistance, such as DNA repair and RNA processing, while the LL strains exhibit unique chlorophyll adaptations (ion transport proteins, HEAT repeats). Additionally, we report the finding of variable, depth-dependent endogenous viral elements in the 40 strains. To generate biological resources to experimentally study the HL and LL adaptations, we constructed the ORFeomes of two representative strains, MED4 and NATL1A synthetically, covering 99% of the annotated protein-coding sequences of the two species, totaling 3976 cloned, sequence-verified open reading frames (ORFs). These comparative genomic analyses, paired with MED4 and NATL1A ORFeomes, will facilitate future genotype-to-phenotype mappings and the systems biology exploration of Prochlorococcus ecology.
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Affiliation(s)
- Sarah Daakour
- Center for Genomics and Systems Biology (CGSB), New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates; (S.D.); (D.R.N.); (W.F.); (A.J.); (B.D.); (A.S.A.); (J.K.); (J.-C.T.)
- Division of Science and Math, New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates
| | - David R. Nelson
- Center for Genomics and Systems Biology (CGSB), New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates; (S.D.); (D.R.N.); (W.F.); (A.J.); (B.D.); (A.S.A.); (J.K.); (J.-C.T.)
- Division of Science and Math, New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates
| | - Weiqi Fu
- Center for Genomics and Systems Biology (CGSB), New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates; (S.D.); (D.R.N.); (W.F.); (A.J.); (B.D.); (A.S.A.); (J.K.); (J.-C.T.)
- Division of Science and Math, New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates
- Department of Marine Science, Ocean College, Zhejiang University, Zhoushan 316021, China
| | - Ashish Jaiswal
- Center for Genomics and Systems Biology (CGSB), New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates; (S.D.); (D.R.N.); (W.F.); (A.J.); (B.D.); (A.S.A.); (J.K.); (J.-C.T.)
- Division of Science and Math, New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates
| | - Bushra Dohai
- Center for Genomics and Systems Biology (CGSB), New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates; (S.D.); (D.R.N.); (W.F.); (A.J.); (B.D.); (A.S.A.); (J.K.); (J.-C.T.)
- Division of Science and Math, New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates
- Helmholtz Center Munich, Institute of Network Biology (INET), German Research Center for Environmental Health, 85764 Munich, Germany
| | - Amnah Salem Alzahmi
- Center for Genomics and Systems Biology (CGSB), New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates; (S.D.); (D.R.N.); (W.F.); (A.J.); (B.D.); (A.S.A.); (J.K.); (J.-C.T.)
- Division of Science and Math, New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates
- Laboratory of Viral Interactomes Networks, Unit of Molecular & Computational Biology, Interdisciplinary Cluster for Applied Genoproteomics (GIGA Institute), University of Liège, 4000 Liège, Belgium
| | - Joseph Koussa
- Center for Genomics and Systems Biology (CGSB), New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates; (S.D.); (D.R.N.); (W.F.); (A.J.); (B.D.); (A.S.A.); (J.K.); (J.-C.T.)
- Division of Science and Math, New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates
- Department of Biology, New York University, New York, NY 10012, USA
- Department of Chemical and Biological Sciences, Montgomery College, Germantown, MD 20850, USA
| | - Xiaoluo Huang
- Genome Synthesis and Editing Platform, China National GeneBank (CNGB), BGI-Research, Shenzhen 518120, China; (X.H.); (Y.S.)
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Beijing 100045, China
| | - Yue Shen
- Genome Synthesis and Editing Platform, China National GeneBank (CNGB), BGI-Research, Shenzhen 518120, China; (X.H.); (Y.S.)
| | - Jean-Claude Twizere
- Center for Genomics and Systems Biology (CGSB), New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates; (S.D.); (D.R.N.); (W.F.); (A.J.); (B.D.); (A.S.A.); (J.K.); (J.-C.T.)
- Division of Science and Math, New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates
- Laboratory of Viral Interactomes Networks, Unit of Molecular & Computational Biology, Interdisciplinary Cluster for Applied Genoproteomics (GIGA Institute), University of Liège, 4000 Liège, Belgium
| | - Kourosh Salehi-Ashtiani
- Center for Genomics and Systems Biology (CGSB), New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates; (S.D.); (D.R.N.); (W.F.); (A.J.); (B.D.); (A.S.A.); (J.K.); (J.-C.T.)
- Division of Science and Math, New York University-Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates
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Gavgani HN, Grotewold E, Gray J. Methodology for Constructing a Knowledgebase for Plant Gene Regulation Information. Methods Mol Biol 2023; 2698:277-300. [PMID: 37682481 DOI: 10.1007/978-1-0716-3354-0_17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/09/2023]
Abstract
The amount of biological data is growing at a rapid pace as many high-throughput omics technologies and data pipelines are developed. This is resulting in the growth of databases for DNA and protein sequences, gene expression, protein accumulation, structural, and localization information. The diversity and multi-omics nature of such bioinformatic data requires well-designed databases for flexible organization and presentation. Besides general-purpose online bioinformatic databases, users need narrowly focused online databases to quickly access a meaningful collection of related data for their research. Here, we describe the methodology used to implement a plant gene regulatory knowledgebase, with data, query, and tool features, as well as the ability to expand to accommodate future datasets. We exemplify this methodology for the GRASSIUS knowledgebase, but it is applicable to developing and updating similar plant gene regulatory knowledgebases. GRASSIUS organizes and presents gene regulatory data from grass species with a central focus on maize (Zea mays). The main class of data presented include not only the families of transcription factors (TFs) and co-regulators (CRs) but also protein-DNA interaction data, where available.
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Affiliation(s)
- Hadi Nayebi Gavgani
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA
- Dandelions Therapeutics Inc., San Francisco, CA, USA
| | - Erich Grotewold
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA
| | - John Gray
- Department of Biological Sciences, University of Toledo, Toledo, OH, USA.
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Tang M, Li B, Zhou X, Bolt T, Li JJ, Cruz N, Gaudinier A, Ngo R, Clark‐Wiest C, Kliebenstein DJ, Brady SM. A genome-scale TF-DNA interaction network of transcriptional regulation of Arabidopsis primary and specialized metabolism. Mol Syst Biol 2021; 17:e10625. [PMID: 34816587 PMCID: PMC8611409 DOI: 10.15252/msb.202110625] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 10/26/2021] [Accepted: 10/28/2021] [Indexed: 12/13/2022] Open
Abstract
Plant metabolism is more complex relative to individual microbes. In single-celled microbes, transcriptional regulation by single transcription factors (TFs) is sufficient to shift primary metabolism. Corresponding genome-level transcriptional regulatory maps of metabolism reveal the underlying design principles responsible for these shifts as a model in which master regulators largely coordinate specific metabolic pathways. Plant primary and specialized metabolism occur within innumerable cell types, and their reactions shift depending on internal and external cues. Given the importance of plants and their metabolites in providing humanity with food, fiber, and medicine, we set out to develop a genome-scale transcriptional regulatory map of Arabidopsis metabolic genes. A comprehensive set of protein-DNA interactions between Arabidopsis thaliana TFs and gene promoters in primary and specialized metabolic pathways were mapped. To demonstrate the utility of this resource, we identified and functionally validated regulators of the tricarboxylic acid (TCA) cycle. The resulting network suggests that plant metabolic design principles are distinct from those of microbes. Instead, metabolism appears to be transcriptionally coordinated via developmental- and stress-conditional processes that can coordinate across primary and specialized metabolism. These data represent the most comprehensive resource of interactions between TFs and metabolic genes in plants.
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Affiliation(s)
- Michelle Tang
- Department of Plant Biology and Genome CenterUniversity of California, DavisDavisCAUSA
- Department of Plant SciencesUniversity of California, DavisDavisCAUSA
- Plant Biology Graduate GroupUniversity of California, DavisDavisCAUSA
| | - Baohua Li
- Department of Plant SciencesUniversity of California, DavisDavisCAUSA
| | - Xue Zhou
- Department of Plant SciencesUniversity of California, DavisDavisCAUSA
| | - Tayah Bolt
- Department of Plant SciencesUniversity of California, DavisDavisCAUSA
| | - Jia Jie Li
- Department of Plant SciencesUniversity of California, DavisDavisCAUSA
| | - Neiman Cruz
- Department of Plant Biology and Genome CenterUniversity of California, DavisDavisCAUSA
| | - Allison Gaudinier
- Department of Plant Biology and Genome CenterUniversity of California, DavisDavisCAUSA
- Plant Biology Graduate GroupUniversity of California, DavisDavisCAUSA
| | - Richard Ngo
- Department of Plant Biology and Genome CenterUniversity of California, DavisDavisCAUSA
- Department of Plant SciencesUniversity of California, DavisDavisCAUSA
| | - Caitlin Clark‐Wiest
- Department of Plant Biology and Genome CenterUniversity of California, DavisDavisCAUSA
- Department of Plant SciencesUniversity of California, DavisDavisCAUSA
| | - Daniel J Kliebenstein
- Department of Plant SciencesUniversity of California, DavisDavisCAUSA
- DynaMo Center of ExcellenceUniversity of CopenhagenFrederiksberg CDenmark
| | - Siobhan M Brady
- Department of Plant Biology and Genome CenterUniversity of California, DavisDavisCAUSA
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Li Z, Bonaldi K, Kang SE, Pruneda-Paz JL. High-Throughput Yeast One-Hybrid Screens Using a Cell Surface gLUC Reporter. ACTA ACUST UNITED AC 2019; 4:e20086. [PMID: 30742367 DOI: 10.1002/cppb.20086] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Gene-centered yeast one-hybrid (Y1H) screens using arrayed genome-wide transcription factor (TF) clone collections provide a simple and effective strategy to identify TF-promoter interactions using a DNA fragment as bait. In an effort to improve the assay we recently developed a Y1H system that uses a cell surface Gaussia luciferase reporter (gLUC59). Compared to other available methods, this luciferase-based strategy requires a shorter processing time, enhances the throughput and improves result analysis of gene-centered Y1H screens. Here, we described the procedure to perform high-throughput screens using this novel strategy, which involves a protocol for mating two haploid yeast strains carrying an arrayed TF clone collection and a promoter::gLUC59 reporter, respectively, and a protocol for analyzing gLUC59 activity in the resulting diploid cells. © 2019 by John Wiley & Sons, Inc.
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Affiliation(s)
- Zheng Li
- Division of Biological Sciences, University of California San Diego, La Jolla, California
| | - Katia Bonaldi
- Division of Biological Sciences, University of California San Diego, La Jolla, California
| | - S Earl Kang
- Division of Biological Sciences, University of California San Diego, La Jolla, California
- Present address: Department of Plant Biology, University of Georgia, Athens, Georgia
| | - Jose L Pruneda-Paz
- Division of Biological Sciences, University of California San Diego, La Jolla, California
- Center for Circadian Biology, University of California San Diego, La Jolla, California
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