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Yang TH, Hsu CW, Wang YX, Yu CH, Rathod J, Tseng YY, Wu WS. YMLA: A comparative platform to carry out functional enrichment analysis for multiple gene lists in yeast. Comput Biol Med 2022; 151:106314. [PMID: 36455295 DOI: 10.1016/j.compbiomed.2022.106314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 10/23/2022] [Accepted: 11/13/2022] [Indexed: 11/16/2022]
Abstract
Comparative analysis among multiple gene lists on their functional features is now a routine task due to the advancement of high-throughput experiments. Several enrichment analysis tools were developed in the past. However, these tools mainly focus on one gene list and contain only gene ontology or interaction features. What makes it worse, comparative investigation and customized feature set reanalysis are still unavailable. Therefore, we constructed the YMLA (Yeast Multiple List Analyzer) platform in this research. YMLA includes 39 yeast features and facilitates comparative analysis among multiple gene lists via tabular views, heatmaps, and network plots. Moreover, the customized feature set reanalysis function was implemented in YMLA to help form mechanism hypotheses based on a selected enriched feature subset. We demonstrated the biological applicability of YMLA via example lists consisting of genes with top/bottom translation efficiency values. The analysis results provided by YMLA reveal novel facts consistent with previous experiments. YMLA is available at https://cosbi7.ee.ncku.edu.tw/YMLA/.
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Affiliation(s)
- Tzu-Hsien Yang
- Department of Biomedical Engineering, National Cheng Kung University, University Road, 701 Tainan, Taiwan.
| | - Chia-Wei Hsu
- Department of Electrical Engineering, National Cheng Kung University, University Road, 701 Tainan, Taiwan.
| | - Yan-Xiang Wang
- Department of Electrical Engineering, National Cheng Kung University, University Road, 701 Tainan, Taiwan.
| | - Chien-Hung Yu
- Department of Biochemistry and Molecular Biology, National Cheng Kung University, University Road, 701 Tainan, Taiwan.
| | - Jagat Rathod
- Department of Environmental Biotechnology, Gujarat Biotechnology University, Gujarat International Finance Tec (GIFT)-City, Gandhinagar 382355, Gujarat, India.
| | - Yan-Yuan Tseng
- Center for Molecular Medicine and Genetics, Wayne State University, School of Medicine, Detroit, MI 48201, USA.
| | - Wei-Sheng Wu
- Department of Electrical Engineering, National Cheng Kung University, University Road, 701 Tainan, Taiwan.
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Persson K, Stenberg S, Tamás MJ, Warringer J. Adaptation of the yeast gene knockout collection is near-perfectly predicted by fitness and diminishing return epistasis. G3 (BETHESDA, MD.) 2022; 12:6694849. [PMID: 36083011 PMCID: PMC9635671 DOI: 10.1093/g3journal/jkac240] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 08/29/2022] [Indexed: 05/31/2023]
Abstract
Adaptive evolution of clonally dividing cells and microbes is the ultimate cause of cancer and infectious diseases. The possibility of constraining the adaptation of cell populations, by inhibiting proteins enhancing the evolvability, has therefore attracted interest. However, our current understanding of how genes influence adaptation kinetics is limited, partly because accurately measuring adaptation for many cell populations is challenging. We used a high-throughput adaptive laboratory evolution platform to track the adaptation of >18,000 cell populations corresponding to single-gene deletion strains in the haploid yeast deletion collection. We report that the preadaptation fitness of gene knockouts near-perfectly (R2= 0.91) predicts their adaptation to arsenic, leaving at the most a marginal role for dedicated evolvability gene functions. We tracked the adaptation of another >23,000 gene knockout populations to a diverse range of selection pressures and generalized the almost perfect (R2=0.72-0.98) capacity of preadaptation fitness to predict adaptation. We also reconstructed mutations in FPS1, ASK10, and ARR3, which together account for almost all arsenic adaptation in wild-type cells, in gene deletions covering a broad fitness range and show that the predictability of arsenic adaptation can be understood as a by global epistasis, where excluding arsenic is more beneficial to arsenic unfit cells. The paucity of genes with a meaningful evolvability effect on adaptation diminishes the prospects of developing adjuvant drugs aiming to slow antimicrobial and chemotherapy resistance.
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Affiliation(s)
- Karl Persson
- Corresponding author: Department of Biology and Biological Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden.
| | - Simon Stenberg
- Department of Chemistry and Molecular Biology, University of Gothenburg, 40530 Gothenburg, Sweden
| | - Markus J Tamás
- Department of Chemistry and Molecular Biology, University of Gothenburg, 40530 Gothenburg, Sweden
| | - Jonas Warringer
- Corresponding author: Department of Chemistry and Molecular Biology, University of Gothenburg, PO Box 462, 40530 Gothenburg, Sweden.
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Stefanini I, Di Paola M, Liti G, Marranci A, Sebastiani F, Casalone E, Cavalieri D. Resistance to Arsenite and Arsenate in Saccharomyces cerevisiae Arises through the Subtelomeric Expansion of a Cluster of Yeast Genes. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19138119. [PMID: 35805774 PMCID: PMC9266342 DOI: 10.3390/ijerph19138119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 06/25/2022] [Accepted: 06/28/2022] [Indexed: 01/25/2023]
Abstract
Arsenic is one of the most prevalent toxic elements in the environment, and its toxicity affects every organism. Arsenic resistance has mainly been observed in microorganisms, and, in bacteria, it has been associated with the presence of the Ars operon. In Saccharomyces cerevisiae, three genes confer arsenic resistance: ARR1, ARR2, and ARR3. Unlike bacteria, in which the presence of the Ars genes confers per se resistance to arsenic, most of the S. cerevisiae isolates present the three ARR genes, regardless of whether the strain is resistant or sensitive to arsenic. To assess the genetic features that make natural S. cerevisiae strains resistant to arsenic, we used a combination of comparative genomic hybridization, whole-genome sequencing, and transcriptomics profiling with microarray analyses. We observed that both the presence and the genomic location of multiple copies of the whole cluster of ARR genes were central to the escape from subtelomeric silencing and the acquisition of resistance to arsenic. As a result of the repositioning, the ARR genes were expressed even in the absence of arsenic. In addition to their relevance in improving our understanding of the mechanism of arsenic resistance in yeast, these results provide evidence for a new cluster of functionally related genes that are independently duplicated and translocated.
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Affiliation(s)
- Irene Stefanini
- Department of Life Sciences and Systems Biology, University of Turin, 10123 Turin, Italy;
| | - Monica Di Paola
- Department of Biology, University of Florence, Sesto Fiorentino, 50019 Florence, Italy; (M.D.P.); (E.C.)
| | - Gianni Liti
- National Centre for Scientific Research (CNRS), National Institute of Health and Medical Research (INSERM), Institute for Research on Cancer and Aging (IRCAN), Université Côte d’Azur, 06103 Nice, France;
| | - Andrea Marranci
- Core Research Laboratory, Oncogenomics Unit, Istituto di Fisiologia Clinica, Institute for Cancer Research and Pre-vention (ISPRO), 56124 Pisa, Italy;
| | - Federico Sebastiani
- Institute for Sustainable Plant Protection, National Research Council (IPSP-CNR), Sesto Fiorentino, 50019 Florence, Italy;
| | - Enrico Casalone
- Department of Biology, University of Florence, Sesto Fiorentino, 50019 Florence, Italy; (M.D.P.); (E.C.)
| | - Duccio Cavalieri
- Department of Biology, University of Florence, Sesto Fiorentino, 50019 Florence, Italy; (M.D.P.); (E.C.)
- Correspondence:
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Rathod J, Yen HC, Liang B, Tseng YY, Chen CS, Wu WS. YPIBP: A repository for phosphoinositide-binding proteins in yeast. Comput Struct Biotechnol J 2021; 19:3692-3707. [PMID: 34285772 PMCID: PMC8261538 DOI: 10.1016/j.csbj.2021.06.035] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 06/08/2021] [Accepted: 06/22/2021] [Indexed: 11/25/2022] Open
Abstract
Phosphoinositides (PIs) are a family of eight lipids consisting of phosphatidylinositol (PtdIns) and its seven phosphorylated forms. PIs have important regulatory functions in the cell including lipid signaling, protein transport, and membrane trafficking. Yeast has been recognized as a eukaryotic model system to study lipid-protein interactions. Hundreds of yeast PI-binding proteins have been identified, but this research knowledge remains scattered. Besides, the complete PI-binding spectrum and potential PI-binding domains have not been interlinked. No comprehensive databases are available to support the lipid-protein interaction research on phosphoinositides. Here we constructed the first knowledgebase of Yeast Phosphoinositide-Binding Proteins (YPIBP), a repository consisting of 679 PI-binding proteins collected from high-throughput proteome-array and lipid-array studies, QuickGO, and a rigorous literature mining. The YPIBP also contains protein domain information in categories of lipid-binding domains, lipid-related domains and other domains. The YPIBP provides search and browse modes along with two enrichment analyses (PI-binding enrichment analysis and domain enrichment analysis). An interactive visualization is given to summarize the PI-domain-protein interactome. Finally, three case studies were given to demonstrate the utility of YPIBP. The YPIBP knowledgebase consolidates the present knowledge and provides new insights of the PI-binding proteins by bringing comprehensive and in-depth interaction network of the PI-binding proteins. YPIBP is available at http://cosbi7.ee.ncku.edu.tw/YPIBP/.
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Key Words
- ANTH, AP180 N-terminal Homology
- BAR, Bin-Amphiphysin-Rvs
- CAFA, Critical Assessment of Functional Annotation
- CRAL-TRIO, cellular retinaldehyde-binding protein (CRALBP) and TRIO guanine exchange factor
- Cvt, Cytoplasm-to-vacuole targeting
- ENTH, Epsin N-terminal Homology
- FDR, False Discovery Rate
- FYVE, Fab 1 (yeast orthologue of PIKfyve), YOTB, Vac 1 (vesicle transport protein), and EEA1
- GO, Gene Ontology
- ITC, Isothermal Titration Calorimetry
- LBD, Lipid-Binding Domain
- LMPD, LIPID MAPS Proteome Database
- LMSD, LIPID MAPS Structure Database
- LRD, Lipid-Related Domain
- Lipid-binding domain
- OMIM, Online Mendelian Inheritance in Man
- OSBP, Oxysterol-Binding Protein
- PH, Pleckstrin Homology
- PI(3,4)P2, phosphatidylinositol-3,4-bisphosphate
- PI(3,4,5)P3, phosphatidylinositol-3,4,5-trisphosphate
- PI(3,5)P2, phosphatidylinositol-3,5-bisphosphate
- PI(4,5)P2, phosphatidylinositol-4,5-bisphosphate
- PI-binding protein
- PI3P, phosphatidylinositol-3-phosphate
- PI4P, phosphatidylinositol-4-phosphate
- PI5P, phosphatidylinositol-5-phosphate
- PIs, Phosphoinositides
- PMID, PubMed ID
- PX, Phox Homology
- Phosphatidylinositol (PtdIns)
- Phosphoinositides (PIs)
- PtdIns, Phosphatidylinositol
- QCM, Quartz Crystal Microbalance
- S. cerevisiae
- SNX, Sorting Nexin
- SPR, Surface Plasmon Resonance
- YPIBP, Yeast Phosphoinositide-Binding Proteins
- Yeast
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Affiliation(s)
- Jagat Rathod
- Department of Earth Sciences, College of Sciences, National Cheng Kung University, Tainan 701, Taiwan
| | - Han-Chen Yen
- Department of Electrical Engineering, College of Electrical Engineering and Computer Science, National Cheng Kung University, Tainan 701, Taiwan
| | - Biqing Liang
- Department of Earth Sciences, College of Sciences, National Cheng Kung University, Tainan 701, Taiwan
| | - Yan-Yuan Tseng
- Center for Molecular Medicine and Genetics, Wayne State University, School of Medicine, Detroit, MI 48201, USA
| | - Chien-Sheng Chen
- Department of Food Safety/Hygiene and Risk Management, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan
- Institute of Basic Medical Sciences, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan
| | - Wei-Sheng Wu
- Department of Electrical Engineering, College of Electrical Engineering and Computer Science, National Cheng Kung University, Tainan 701, Taiwan
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Wu WS, Wang LJ, Yen HC, Tseng YY. YQFC: a web tool to compare quantitative biological features between two yeast gene lists. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2020; 2020:5981333. [PMID: 33186464 PMCID: PMC7805433 DOI: 10.1093/database/baaa076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 07/27/2020] [Accepted: 08/11/2020] [Indexed: 11/14/2022]
Abstract
Nowadays high-throughput omics technologies are routinely used in biological research. From the omics data, researchers can easily get two gene lists (e.g. stress-induced genes vs. stress-repressed genes) related to their biological question. The next step would be to apply enrichment analysis tools to identify distinct functional/regulatory features between these two gene lists for further investigation. Although various enrichment analysis tools are already available, two challenges remain to be addressed. First, most existing tools are designed to analyze only one gene list, so they cannot directly compare two gene lists. Second, almost all existing tools focus on identifying the enriched qualitative features (e.g. gene ontology [GO] terms, pathways, domains, etc.). Many quantitative features (e.g. number of mRNA isoforms of a gene, mRNA half-life, protein half-life, transcriptional plasticity, translational efficiency, etc.) are available in the yeast, but no existing tools provide analyses on these quantitative features. To address these two challenges, here we present Yeast Quantitative Features Comparator (YQFC) that can directly compare various quantitative features between two yeast gene lists. In YQFC, we comprehensively collected and processed 85 quantitative features from the yeast literature and yeast databases. For each quantitative feature, YQFC provides three statistical tests (t-test, U test and KS test) to test whether this quantitative feature is statistically different between the two input yeast gene lists. The distinct quantitative features identified by YQFC may help researchers to study the underlying molecular mechanisms that differentiate the two input yeast gene lists. We believe that YQFC is a useful tool to expedite the biological research that uses high-throughput omics technologies. DATABASE URL http://cosbi2.ee.ncku.edu.tw/YQFC/.
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Affiliation(s)
- Wei-Sheng Wu
- Department of Electrical Engineering, National Cheng Kung University, No.1, University Road, Tainan city, 70101 Taiwan
| | - Lai-Ji Wang
- Department of Electrical Engineering, National Cheng Kung University, No.1, University Road, Tainan city, 70101 Taiwan
| | - Han-Chen Yen
- Department of Electrical Engineering, National Cheng Kung University, No.1, University Road, Tainan city, 70101 Taiwan
| | - Yan-Yuan Tseng
- Center for Molecular Medicine and Genetics, Wayne State University, School of Medicine, 3127 Scott Hall, 540 East Canfield, Detroit, MI 48201, USA
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Rathod J, Jean JS, Jiang WT, Huang IH, Liu BH, Lee YC. Micro-colonization of arsenic-resistant Staphylococcus sp. As-3 on arsenopyrite (FeAsS) drives arsenic mobilization under anoxic sub-surface mimicking conditions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 669:527-539. [PMID: 30884274 DOI: 10.1016/j.scitotenv.2019.03.084] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2018] [Revised: 03/06/2019] [Accepted: 03/06/2019] [Indexed: 06/09/2023]
Abstract
We investigated the subsurface biomatrix of the most abundant As-mineral, arsenopyrite (FeAsS), and meticulously studied a potential biogenic arsenic mobilization phenomenon. An arsenic-resistant [up to 7.5 mM As(III) and 200 mM As(V)] and arsenate-reducing bacterial strain (Staphylococcus sp. As-3) was isolated from a sediment core sample taken from the Budai borehole, on the southwestern coast of Taiwan. Isolate As-3 could reduce 5 mM As(V) to 3.04 mM in 96 h, generating 1.6 mM As(III) under anoxic conditions. Isolate As-3, which adsorbed As(V) up to 19.02 mg g-1 (cdw) and As(III) up to 0.46 mg g-1 (cdw), demonstrated effective As-bioaccumulating ability, as corroborated by a TEM-EDS analysis. Under anaerobic batch conditions, isolate As-3 micro-colonies could grow on as well as interact with arsenopyrite (FeAsS), mobilizing arsenic into soluble phase as As(III) and As(V). Using synchrotron radiation-based FTIR micro-spectroscopy, various functional group signatures and critical chemical bonds enabling a direct interaction with arsenopyrite were underpinned, such as a potential P-OFe bond involved in facilitating bacteria-mineral interaction. Using atomic force microscopy, we analyzed the scattered bacterial cell arrangement and structure and measured various biomechanical properties of micro-colonized Staphylococcus sp. As-3 cells on arsenopyrite. We suggest that the release of organic acids from As-3 drives soluble arsenic release in the aqueous phase under anoxic conditions through oxidative dissolution. Furthermore, arsC-encoding putative cytoplasmic arsenic reductase sequencing and transcript characterization indicated that arsC plays a possible role in the reduction of moderately soluble As(V) to highly soluble toxic As(III) under anoxic conditions. Thus, we suggest that firmicutes such as Staphylococcus sp. As-3 may play an important role in microbially-mediated arsenic mobilization, leading to arsenic release in the sub-surface niche.
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Affiliation(s)
- Jagat Rathod
- Department of Earth Sciences, National Cheng Kung University, 1, University Road, Tainan 70101, Taiwan
| | - Jiin-Shuh Jean
- Department of Earth Sciences, National Cheng Kung University, 1, University Road, Tainan 70101, Taiwan; Graduate Institute of Applied Geology, National Central University, Chung-Li District, Taoyuan City 32001, Taiwan.
| | - Wei-Teh Jiang
- Department of Earth Sciences, National Cheng Kung University, 1, University Road, Tainan 70101, Taiwan
| | - I-Hsiu Huang
- Department of Microbiology and Immunology, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Center of Infectious Disease and Signalling Research, National Cheng Kung University, Tainan, Taiwan
| | - Bernard Haochih Liu
- Department of Materials Science and Engineering, National Cheng Kung University, Taiwan
| | - Yao-Chang Lee
- National Synchrotron Radiation Research Center, Life Science Group, Hsinchu 30076, Taiwan; Department of Optics and Photonics, National Central University, Chung-Li District, Taoyuan City 32001, Taiwan
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