{"doi":"10.3389/fenrg.2022.884582","title":"OMICs-Based Strategies to Explore Stress Tolerance Mechanisms of Saccharomyces cerevisiae for Efficient Fuel Ethanol Production","abstract":"<jats:p>Efficient biotransformation of lignocellulosic biomass to second-generation (2G) bioethanol requires promising strains harboring built-in resistance against limitations imposed by pretreated lignocellulose-derived compounds. Ethanol fermentation and stress tolerance of yeast cells are almost simultaneously exposed to sequence variations and multiple inhibitory factors during the phases of proliferation, metabolism, and productivity. Several studies have extensively concentrated on identification or characterization of genes which confer resistance to various stresses and yeast tolerance enhancement through genetic breeding. However, the investigation of individual genes is inadequate to explain the global molecular mechanism. Herewith, “OMICs-approaches,” including genomics, transcriptomics, proteomics, and metabolomics, which are comprehensively aimed at comparative, functional profiling of the whole metabolic network, have elucidated complex cellular reactions under stressful conditions. This review briefly discusses the research progress in the field of multi-OMICs with a special focus on stress-responsive factors in frequently used <jats:italic>S. cerevisiae.</jats:italic> It also highlights how to promote metabolic-engineered strains for increased tolerance and higher production yield, which should be deeply exploited to achieve robustness during the lignocellulose-to-ethanol conversion process.</jats:p>","journal":"Frontiers in Energy Research","year":2022,"id":639624,"datarank":0.594889074918259,"base_score":2.995732273553991,"endowment":2.995732273553991,"self_citation_contribution":0.4493598410330987,"citation_network_contribution":0.14552923388516034,"self_endowment_contribution":0.4493598410330987,"citer_contribution":0.14552923388516034,"corpus_percentile":null,"corpus_rank":null,"citation_count":19,"citer_count":19,"citers_with_citation_signal":10,"citers_with_endowment":10,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1661912,"name":"Muhammad Aamer Mehmood","orcid":null,"position":1,"is_corresponding":false},{"id":499066,"name":"Lan Wang","orcid":"0000-0003-0588-4899","position":2,"is_corresponding":false},{"id":1394865,"name":"Niaz Ahmad","orcid":"0000-0002-9391-2089","position":3,"is_corresponding":false},{"id":1661914,"name":"Hai-Jun Ma","orcid":null,"position":4,"is_corresponding":false},{"id":1661911,"name":"Jian-Ren Xu","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"OMICs-Based Strategies to Explore Stress Tolerance Mechanisms of Saccharomyces cerevisiae for Efficient Fuel Ethanol Production","abstract":"<jats:p>Efficient biotransformation of lignocellulosic biomass to second-generation (2G) bioethanol requires promising strains harboring built-in resistance against limitations imposed by pretreated lignocellulose-derived compounds. Ethanol fermentation and stress tolerance of yeast cells are almost simultaneously exposed to sequence variations and multiple inhibitory factors during the phases of proliferation, metabolism, and productivity. Several studies have extensively concentrated on identification or characterization of genes which confer resistance to various stresses and yeast tolerance enhancement through genetic breeding. However, the investigation of individual genes is inadequate to explain the global molecular mechanism. Herewith, “OMICs-approaches,” including genomics, transcriptomics, proteomics, and metabolomics, which are comprehensively aimed at comparative, functional profiling of the whole metabolic network, have elucidated complex cellular reactions under stressful conditions. This review briefly discusses the research progress in the field of multi-OMICs with a special focus on stress-responsive factors in frequently used <jats:italic>S. cerevisiae.</jats:italic> It also highlights how to promote metabolic-engineered strains for increased tolerance and higher production yield, which should be deeply exploited to achieve robustness during the lignocellulose-to-ethanol conversion process.</jats:p>","is_dataset_classified":null,"base_score":2.995732273553991,"endowment":2.995732273553991,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19767382","pmcid":null,"openalex_id":"https://openalex.org/W4281745653","authors":[],"funders":[],"total_grants":0,"fwci":0.7873,"citation_percentile":0.64847749,"influential_citations":0,"citation_trend":[{"year":2023,"count":1},{"year":2024,"count":2},{"year":2025,"count":8},{"year":2026,"count":8}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://www.frontiersin.org/articles/10.3389/fenrg.2022.884582/pdf","host_type":"journal"},{"url":"https://www.frontiersin.org/articles/10.3389/fenrg.2022.884582/pdf","host_type":"publisher"},{"url":"https://www.frontiersin.org/articles/10.3389/fenrg.2022.884582/full","host_type":"publisher"},{"url":"https://doi.org/10.3389/fenrg.2022.884582","host_type":"journal"},{"url":"https://doaj.org/article/e7431b02ab9f41ba84b353094cdb7022","host_type":"repository"}],"fields_of_study":["Biofuel production and bioconversion","Microbial Metabolic Engineering and Bioproduction","Fungal and yeast genetics research"],"mesh_terms":[],"keywords":["Metabolomics","Saccharomyces cerevisiae","Yeast","Transcriptome","Computational biology","Functional genomics","Biology","Proteomics","Biotechnology","Biofuel","Metabolic engineering","Systems biology","Lignocellulosic biomass","Robustness (evolution)","Biotransformation","Ethanol fuel","Genomics","Biochemical engineering","Gene","Biochemistry","Bioinformatics","Gene expression","Engineering","Enzyme","Genome"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-07T01:04:23.649595Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}