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Multi-omics data and model integration reveal the main mechanisms associated with respiro-fermentative metabolism and ethanol stress responses in Kluyveromyces marxianus
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Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077
featureCounts: an efficient general purpose program for assigning sequence reads to genomic features
Liao, Y., Smyth, G. K., & Shi, W. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt656 · Cited by 27,219
Bioconductor: open software development for computational biology and bioinformatics
Gentleman, R. C., Carey, V. J., Bates, D. M., Bolstad, B., Dettling, M., Dudoit, S., Ellis, B., Gautier, L., Ge, Y., Gentry, J., et al. (2004) · Genome Biology · doi:10.1186/gb-2004-5-10-r80 · Cited by 12,172
InterProScan 5: genome-scale protein function classification
Jones, P., Binns, D., Chang, H.-Y., Fraser, M., Li, W., McAnulla, C., McWilliam, H., Maslen, J., Mitchell, A., Nuka, G., et al. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu031 · Cited by 9,301
UniProt: a worldwide hub of protein knowledge
The UniProt Consortium (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1049 · Cited by 7,698
What is flux balance analysis?
Orth, J. D., Thiele, I., & Palsson, B. Ø. (2010) · Nature Biotechnology · doi:10.1038/nbt.1614 · Cited by 3,903
The Gene Ontology resource: enriching a GOld mine
The Gene Ontology Consortium, Carbon, S., Douglass, E., Good, B. M., Unni, D. R., Harris, N. L., Mungall, C. J., Basu, S., Chisholm, R. L., Dodson, R. J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1113 · Cited by 3,555
Kim, S., Chen, J., Cheng, T., Gindulyte, A., He, J., He, S., Li, Q., Shoemaker, B. A., Thiessen, P. A., Yu, B., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkac956 · Cited by 3,443
Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0
Heirendt, L., Arreckx, S., Pfau, T., Mendoza, S. N., Richelle, A., Heinken, A., Haraldsdóttir, H. S., Wachowiak, J., Keating, S. M., Vlasov, V., et al. (2019) · Nature Protocols · doi:10.1038/s41596-018-0098-2 · Cited by 1,242
BRENDA, the ELIXIR core data resource in 2021: new developments and updates
Chang, A., Jeske, L., Ulbrich, S., Hofmann, J., Koblitz, J., Schomburg, I., Neumann-Schaal, M., Jahn, D., & Schomburg, D. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1025 · Cited by 789
Overflow metabolism in Escherichia coli results from efficient proteome allocation
Basan, M., Hui, S., Okano, H., Zhang, Z., Shen, Y., Williamson, J. R., & Hwa, T. (2015) · Nature · doi:10.1038/nature15765 · Cited by 785
The SWI/SNF complex in cancer — biology, biomarkers and therapy
Mittal, P., & Roberts, C. W. M. (2020) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-020-0357-3 · Cited by 735
Technological trends, global market, and challenges of bio-ethanol production
Mussatto, S. I., Dragone, G., Guimarães, P. M. R., Silva, J. P. A., Carneiro, L. M., Roberto, I. C., Vicente, A., Domingues, L., & Teixeira, J. A. (2010) · Biotechnology Advances · doi:10.1016/j.biotechadv.2010.07.001 · Cited by 727
Review of Second-Generation Bioethanol Production from Residual Biomass
Lodz University of Technology, F. O. B. A. F. S., Robak, K., Balcerek, M., & Lodz University of Technology, F. O. B. A. F. S. (2018) · Food Technology and Biotechnology · doi:10.17113/ftb.56.02.18.5428 · Cited by 649
Deep learning-based kcat prediction enables improved enzyme-constrained model reconstruction
Li, F., Yuan, L., Lu, H., Li, G., Chen, Y., Engqvist, M. K. M., Kerkhoven, E. J., & Nielsen, J. (2022) · Nature Catalysis · doi:10.1038/s41929-022-00798-z · Cited by 466
Sánchez, B. J., Zhang, C., Nilsson, A., Lahtvee, P., Kerkhoven, E. J., & Nielsen, J. (2017) · Molecular Systems Biology · doi:10.15252/msb.20167411 · Cited by 466
Chandrasekaran, S., & Price, N. D. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1005139107 · Cited by 398
Wang, H., Marcišauskas, S., Sánchez, B. J., Domenzain, I., Hermansson, D., Agren, R., Nielsen, J., & Kerkhoven, E. J. (2018) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1006541 · Cited by 381
Kluyveromyces marxianus: A yeast emerging from its sister's shadow
Lane, M. M., & Morrissey, J. P. (2010) · Fungal Biology Reviews · doi:10.1016/j.fbr.2010.01.001 · Cited by 371
Beg, Q. K., Vazquez, A., Ernst, J., de Menezes, M. A., Bar-Joseph, Z., Barabási, A.-L., & Oltvai, Z. N. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0609845104 · Cited by 368
Biofuels 2020: Biorefineries based on lignocellulosic materials
Valdivia, M., González, J. L. G., Briones, J. L., & Ramos, J. L. (2016) · Microbial Biotechnology · doi:10.1111/1751-7915.12387 · Cited by 291
Gallagher, P. W. (2004) · Integrated Crop Management Conference · doi:10.31274/icm-180809-771 · Cited by 249
Consolidated bio-saccharification: Leading lignocellulose bioconversion into the real world
Liu, Y., Li, B., Feng, Y., & Cui, Q. (2020) · Biotechnology Advances · doi:10.1016/j.biotechadv.2020.107535 · Cited by 183
Adadi, R., Volkmer, B., Milo, R., Heinemann, M., & Shlomi, T. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002575 · Cited by 179
A comprehensive overview and critical evaluation of gene regulatory network inference technologies
Zhao, M., He, W., Tang, J., Zou, Q., & Guo, F. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab009 · Cited by 139
Protein degradation and the stress response
Flick, K. M., & Kaiser, P. (2012) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2012.01.019 · Cited by 135
da Silveira, W. B., Passos, F. V., Mantovani, H. C., & Passos, F. M. L. (2005) · Enzyme and Microbial Technology · doi:10.1016/j.enzmictec.2005.01.018 · Cited by 133
Self-citationChen, Y., Gustafsson, J., Rangel, A. E. T., Anton, M., Domenzain, I., Kittikunapong, C., Li, F., Yuan, L., Nielsen, J., & Kerkhoven, E. J. (2024) · Nature Protocols · doi:10.1038/s41596-023-00931-7 · Cited by 132
Fonseca, G. G., Gombert, A. K., Heinzle, E., & Wittmann, C. (2007) · FEMS Yeast Research · doi:10.1111/j.1567-1364.2006.00192.x · Cited by 129
Experimental Evolution of Yeast for High-Temperature Tolerance
Huang, C.-J., Lu, M. J., Chang, Y.-W., & Li, W. (2018) · Molecular Biology and Evolution · doi:10.1093/molbev/msy077 · Cited by 127
Thorsen, M. K., Lagniel, G., Kristiansson, E., Junot, C., Nerman, O., Labarre, J., & Tamás, M. J. (2007) · Physiological Genomics · doi:10.1152/physiolgenomics.00236.2006 · Cited by 122
Mo, W., Wang, M., Zhan, R., Yu, Y., He, Y., & Lü, H. (2019) · Biotechnology for Biofuels · doi:10.1186/s13068-019-1393-z · Cited by 117
Teixeira, M. C., Viana, R., Palma, M., Oliveira, J. S., Galocha, M., Mota, M. N., Couceiro, D., Pereira, M. G., Antunes, M., Costa, I. V., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac1041 · Cited by 108
Almeida‐Silva, F., & Venâncio, T. M. (2021) · Functional & Integrative Genomics · doi:10.1007/s10142-021-00821-9 · Cited by 105
Jenior, M. L., Moutinho, T. J., Dougherty, B. V., & Papin, J. A. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007099 · Cited by 90
Fonseca, G. G., de Carvalho, N. M. B., & Gombert, A. K. (2013) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-013-4748-6 · Cited by 88
de Alteriis, E., Cartenì, F., Parascandola, P., Serpa, J., & Mazzoleni, S. (2018) · Cell Cycle · doi:10.1080/15384101.2018.1442622 · Cited by 84
Action areas and the need for research in biofuels
Unglert, M., Bockey, D., Bofinger, C., Buchholz, B., Fisch, G., Luther, R., Müller, M., Schaper, K., Schmitt, J. A., Schröder, O., et al. (2020) · Fuel · doi:10.1016/j.fuel.2020.117227 · Cited by 84
Dissection of Combinatorial Control by the Met4 Transcriptional Complex
Lee, T. A., Jorgensen, P., Bognar, A. L., Peyraud-Thomas, C., Thomas, D., & Tyers, M. (2009) · Molecular Biology of the Cell · doi:10.1091/mbc.e09-05-0420 · Cited by 83
Physiological characterization of thermotolerant yeast for cellulosic ethanol production
Costa, D. A., de Souza, C. J. A., Costa, P. S., et al. (2014) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-014-5580-3 · Cited by 80
Topaloğlu, A., Esen, Ö., Turanlı-Yıldız, B., Arslan, M., & Çakar, Z. P. (2023) · Journal of Fungi · doi:10.3390/jof9100984 · Cited by 79
Beyond Genomics: Studying Evolution with Gene Coexpression Networks
Ruprecht, C., Vaid, N., Proost, S., Persson, S., & Mutwil, M. (2017) · Trends in Plant Science · doi:10.1016/j.tplants.2016.12.011 · Cited by 68
Diniz, R. H. S., Villada, J. C., Alvim, M. C. T., Vidigal, P. M. P., Vieira, N. M., Maceiras, M. L., Cerdán, M. E., González-Siso, M.-I., Lahtvee, P., & da Silveira, W. B. (2017) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-017-8432-0 · Cited by 65
Self-citationFu, X., Li, P., Zhang, L., & Li, S. (2019) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-019-09637-x · Cited by 65
Reconstruction and analysis of a Kluyveromyces marxianus genome-scale metabolic model
Marcišauskas, S., Ji, B., & Nielsen, J. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-3134-5 · Cited by 62
Diniz, R. H. S., Rodrigues, M. Q. R. B., Fietto, L. G., Passos, F. M. L., & da Silveira, W. B. (2013) · Biocatalysis and Agricultural Biotechnology · doi:10.1016/j.bcab.2013.09.002 · Cited by 61
Self-citationBourgarel, D., Nguyen, C. C., & Bolotin‐Fukuhara, M. (1999) · Molecular Microbiology · doi:10.1046/j.1365-2958.1999.01263.x · Cited by 57
Parra, K. J., Chan, C.-Y., & Chen, J. (2014) · Eukaryotic Cell · doi:10.1128/ec.00050-14 · Cited by 57
Liu, Z. L., & Ma, M. (2020) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-020-10434-0 · Cited by 57
Signori, L., Passolunghi, S., Ruohonen, L., Porro, D., & Branduardi, P. (2014) · Microbial Cell Factories · doi:10.1186/1475-2859-13-51 · Cited by 56
The Hap Complex in Yeasts: Structure, Assembly Mode, and Gene Regulation
Mao, Y., & Chen, C. (2019) · Frontiers in Microbiology · doi:10.3389/fmicb.2019.01645 · Cited by 53
Membrane fluidification by ethanol stress activates unfolded protein response in yeasts
Navarro‐Tapia, E., Querol, A., & Pérez‐Torrado, R. (2018) · Microbial Biotechnology · doi:10.1111/1751-7915.13032 · Cited by 51
Model-based biotechnological potential analysis of Kluyveromyces marxianus central metabolism
Pentjuss, A., Stalidzāns, E., Liepiņš, J., Kokina, A., Martynova, J., Zikmanis, P., Mozga, I., Scherbaka, R., Hartman, H. B., Poolman, M. G., et al. (2017) · Journal of Industrial Microbiology & Biotechnology · doi:10.1007/s10295-017-1946-8 · Cited by 44
Ferreira, P. G., da Silveira, F. A., dos Santos, R. C. V., Geniêr, H. L. A., Diniz, R. H. S., Ribeiro, J. I., Fietto, L. G., Passos, F. M. L., & da Silveira, W. B. (2015) · Food Science and Biotechnology · doi:10.1007/s10068-015-0182-0 · Cited by 42
Self-citationSWI/SNF Chromatin Remodelers: Structural, Functional and Mechanistic Implications
Singh, A., Modak, S. B., Chaturvedi, M. M., & Purohit, J. S. (2023) · Cell Biochemistry and Biophysics · doi:10.1007/s12013-023-01140-5 · Cited by 42
Thirty years of the HAP2/3/4/5 complex
Bolotin‐Fukuhara, M. (2016) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2016.10.011 · Cited by 41
Li, P., Fu, X., Chen, M., Zhang, L., & Li, S. (2019) · Biotechnology for Biofuels · doi:10.1186/s13068-019-1390-2 · Cited by 41
Acquired Resistance to Severe Ethanol Stress in Saccharomyces cerevisiae Protein Quality Control
Yoshida, M., Kato, S., Fukuda, S., & Izawa, S. (2020) · Applied and Environmental Microbiology · doi:10.1128/aem.02353-20 · Cited by 40
da Silveira, F. A., Soares, D. L. D. O., Bang, K. W., Balbino, T. R., Ferreira, M. A. D. M., Diniz, R. H. S., de Lima, L. A., Brandão, M. M., Villas-Bôas, S. G., & da Silveira, W. B. (2020) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-020-10768-9 · Cited by 39
Self-citationWang, Y., Zhang, Z., Lu, X., Zong, H., & Zhuge, B. (2020) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-020-10509-y · Cited by 32
Vriesekoop, F., Haass, C., & Pamment, N. B. (2009) · FEMS Yeast Research · doi:10.1111/j.1567-1364.2009.00492.x · Cited by 31
Exploration of sulfur metabolism in the yeast Kluyveromyces lactis
Hébert, A., Forquin, M.-P., Roux, A., Aubert, J., Junot, C., Loux, V., Heilier, J.-F., Bonnarme, P., Beckerich, J.-M., & Landaud, S. (2011) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-011-3481-2 · Cited by 31
Paz, S. M., Schmitz, J. P. J., dos Santos, V. A. P. M., & Diez, M. S. (2022) · Microbial Biotechnology · doi:10.1111/1751-7915.13995 · Cited by 30
Bao, W.-G., Guiard, B., Fang, Z., et al. (2008) · Eukaryotic Cell · doi:10.1128/ec.00018-08 · Cited by 29
Kerkhoven, E. J. (2022) · Current Opinion in Microbiology · doi:10.1016/j.mib.2022.102168 · Cited by 29
The SWI/SNF chromatin remodeling complex: a critical regulator of metabolism
Church, M. C., & Workman, J. L. (2024) · Biochemical Society Transactions · doi:10.1042/bst20231141 · Cited by 28
OM-FBA: Integrate Transcriptomics Data with Flux Balance Analysis to Decipher the Cell Metabolism
Guo, W., & Feng, X. (2016) · PLoS ONE · doi:10.1371/journal.pone.0154188 · Cited by 27
Ethanol stress responses in Kluyveromyces marxianus: current knowledge and perspectives
Ferreira, M. A. D. M., da Silveira, F. A., & da Silveira, W. B. (2022) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-022-11799-0 · Cited by 26
Self-citationFerreira, M. A. D. M., da Silveira, W. B., & Nikoloski, Z. (2024) · Biotechnology and Bioengineering · doi:10.1002/bit.28650 · Cited by 26
Self-citationShi, T., Zhou, J., Xue, A., Lü, H., He, Y., & Yu, Y. (2021) · Biotechnology for Biofuels · doi:10.1186/s13068-021-02086-7 · Cited by 24
Zhang, M., Zhang, H., He, Y.-X., Wu, Z., & Xu, K. (2023) · RSC Advances · doi:10.1039/d3ra05216h · Cited by 19
Fermentative capacity ofKluyveromyces marxianusandSaccharomyces cerevisiaeafter oxidative stress
Arellano‐Plaza, M., Noriega‐Cisneros, R., Clemente‐Guerrero, M., González‐Hernández, J. C., Robles-Herrera, P. D., Manzo‐Ávalos, S., Saavedra‐Molina, A., & Gschaedler, A. (2017) · Journal of the Institute of Brewing · doi:10.1002/jib.451 · Cited by 17
Experimental evolution reveals a general role for the methyltransferase Hmt1 in noise buffering
You, S., Jhou, Y., Kao, C.-F., & Leu, J. (2019) · PLoS Biology · doi:10.1371/journal.pbio.3000433 · Cited by 15
Dzanaeva, L., Kruk, B., Ruchała, J., Sibirny, A. А., & Dmytruk, K. V. (2021) · Antonie van Leeuwenhoek · doi:10.1007/s10482-021-01607-6 · Cited by 13
Wei, Z., Zhang, Z., Zhao, W., Yin, T., Liu, X., & Zhang, H. (2022) · Cells · doi:10.3390/cells11040636 · Cited by 6
Research works printed but not linked: 2
- RFA, 2020, 2020 RFA’S. Ethanol Ind. Outlook
- Diniz, 2012, The high fermentative metabolism of Kluyveromyces marxianus UFV-3 relies on the increased expression of key lactose metabolic enzymes, Antonie van Leeuwenhoek, Int. J. Gen. Mol. Microbiol., 101, 541
Metadata
- Authors
- Ferreira, M. A. D. M., & Silveira, W. B. D.
- Affiliations
- Universidade Federal de Viçosa (BR)
- Venue
- Biochemical Engineering Journal
- Publisher
- Elsevier BV
- Published
- 2024-11
- Volume
- 211
- Pages
- 109471
- ISSN
- 1369-703X (ISSN-L)
- OpenAlex
- W4401836203
- Cited by
- 3
- References
- 77
- Citations by year
- 2026: 3
- FWCI
- 0.41
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Biochemical Engineering Journal (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- Funders
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Physical Sciences › Engineering › Biomedical Engineering › Biofuel production and bioconversion
- Keywords
- Kluyveromyces marxianus, ethanol stress response, ethanol tolerance, genome-scale metabolic modeling, gene co-expression network, protein quality control, HAP3, Met4, SnF2, amino acid metabolism, membrane lipid metabolism, ergosterol, dilution rate, yeast metabolic engineering
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