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Metagenomics reveals flavour metabolic network of cereal vinegar microbiota

Wu, Lin-Huan, Lu, Zhen-Ming, Zhang, Xiao-Juan, Wang, Zong-Min, Yu, Yong-Jian, Shi, Jin-Song, Xu, Zheng-Hong·2017·Food Microbiology

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Research works printed but not linked: 26

  1. Altschul, 1997, Gapped BLAST and PSI-BLAST: a new generation of protein database search programs, Nucleic Acids Res., 25, 3389, 10.1093/nar/25.17.3389 · DOI · Paper page
  2. Bokulich, 2014, Microbial biogeography of wine grapes is conditioned by cultivar, vintage, and climate, Proc. Nat. Acad. Sci. U. S. A., 111, E139, 10.1073/pnas.1317377110 · DOI · Paper page
  3. Cheon, 2014, A biosynthetic pathway for hexanoic acid production in Kluyveromyces marxianus, J. Biotechnol., 182–183, 30, 10.1016/j.jbiotec.2014.04.010 · DOI
  4. Chou, 2015, Amino acid, mineral, and polyphenolic profiles of black vinegar, and its lipid lowering and antioxidant effects in vivo, Food Chem., 168, 63, 10.1016/j.foodchem.2014.07.035 · DOI
  5. Hanson, 2014, Metabolic pathways for the whole community, BMC Genomics, 15, 619, 10.1186/1471-2164-15-619 · DOI
  6. Heems, 1998, Fully automated precolumn derivatization, on-line dialysis and high-performance liquid chromatographic analysis of amino acids in food, beverages and feedstuff, J. Chromatogr. A, 798, 9, 10.1016/S0021-9673(97)01007-8 · DOI
  7. Hua, 2015, Ecological roles of dominant and rare prokaryotes in acid mine drainage revealed by metagenomics and metatranscriptomics, ISME J., 9, 1280, 10.1038/ismej.2014.212 · DOI · Paper page
  8. Huang, 2015, Single cell biotechnology to shed a light on biological ‘dark matter’ in nature, Microb. Biotechnol., 8, 15, 10.1111/1751-7915.12249 · doi:10.1111/1751-7915.12249
  9. Hugenholtz, 2013, Traditional biotechnology for new foods and beverages, Curr. Opin. Biotechnol., 24, 155, 10.1016/j.copbio.2013.01.001 · DOI
  10. Illeghems, 2015, Applying meta-pathway analyses through metagenomics to identify the functional properties of the major bacterial communities of a single spontaneous cocoa bean fermentation process sample, Food Microbiol., 50, 54, 10.1016/j.fm.2015.03.005 · DOI
  11. Ishii, 2013, A novel metatranscriptomic approach to identify gene expression dynamics during extracellular electron transfer, Nat. Commun., 4, 1061, 10.1038/ncomms2615 · DOI
  12. Kanehisa, 2014, Data, information, knowledge and principle: back to metabolism in KEGG, Nucleic Acids Res., 42, D199, 10.1093/nar/gkt1076 · DOI · Paper page
  13. Koopman, 2010, Identification and characterization of the furfural and 5-(hydroxymethyl)furfural degradation pathways of Cupriavidus basilensis HMF14, Proc. Nat. Acad. Sci. U. S. A., 107, 4919, 10.1073/pnas.0913039107 · DOI · Paper page
  14. Liu, 2013, Composition-based classification of short metagenomic sequences elucidates the landscapes of taxonomic and functional enrichment of microorganisms, Nucleic Acids Res., 41, e3, 10.1093/nar/gks828 · DOI
  15. Namiki, 2012, MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads, Nucleic Acids Res., 40, e155, 10.1093/nar/gks678 · DOI · Paper page
  16. Nie, 2015, Dynamics and diversity of microbial community succession in traditional fermentation of Shanxi aged vinegar, Food Microbiol., 47, 62, 10.1016/j.fm.2014.11.006 · DOI
  17. Rho, 2010, FragGeneScan: predicting genes in short and error-prone reads, Nucleic Acids Res., 38, e191, 10.1093/nar/gkq747 · DOI · Paper page
  18. Vanwonterghem, 2014, Linking microbial community structure, interactions and function in anaerobic digesters using new molecular techniques, Curr. Opin. Biotechnol., 27, 55, 10.1016/j.copbio.2013.11.004 · DOI · Paper page
  19. Wang, 2015, Batch-to-batch uniformity of bacterial community succession and flavour formation in the fermentation of Zhenjiang aromatic vinegar, Food Microbiol., 50, 64, 10.1016/j.fm.2015.03.012 · DOI
  20. Wu, 2010, Diversity of Acetobacter pasteurianus strains isolated from solid-state fermentation of cereal vinegars, Curr. Microbiol., 60, 280, 10.1007/s00284-009-9538-0 · DOI
  21. Wu, 2012, Biodiversity of yeasts, lactic acid bacteria and acetic acid bacteria in the fermentation of “Shanxi aged vinegar“, a traditional Chinese vinegar, Food Microbiol., 30, 289, 10.1016/j.fm.2011.08.010 · DOI
  22. Xiao, 2014, Strategies for enhancing fermentative production of acetoin: a review, Biotechnol. Adv., 32, 492, 10.1016/j.biotechadv.2014.01.002 · DOI · Paper page
  23. Xu, 2011, Monitoring the microbial community during solid-state acetic acid fermentation of Zhenjiang aromatic vinegar, Food Microbiol., 28, 1175, 10.1016/j.fm.2011.03.011 · DOI
  24. Xu, 2011, Ligustrazine formation in Zhenjiang aromatic vinegar: changes during fermentation and storing process, J. Sci. Food Agric., 91, 1612, 10.1002/jsfa.4356 · DOI
  25. Yu, 2012, HS-SPME/GC-MS and chemometrics for volatile composition of Chinese traditional aromatic vinegar in the Zhenjiang region, J. Inst. Brew., 118, 133, 10.1002/jib.20 · DOI
  26. Zhou, 1996, DNA recovery from soils of diverse composition, Appl. Environ. Microbiol., 62, 316, 10.1128/aem.62.2.316-322.1996 · DOI · Paper page

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Metadata

Authors
Wu, L.-H., Lu, Z.-M., Zhang, X.-J., Wang, Z.-M., Yu, Y.-J., Shi, J.-S., & Xu, Z.-H.
Venue
Food Microbiology
Publisher
Elsevier BV
Published
2017-04
Volume
62
Pages
23-31
ISSN
0740-0020 (ISSN-L)
OpenAlex
W2520557948
Cited by
168
References
1
FWCI
8.23
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Funders
  • National Natural Science Foundation of China (2012AA021301, 2013AA102106, 2014AA021501, 31271922, 31530055)
  • Ministry of Education of the People's Republic of China (JUSRP51516)

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CoChat. (2026). Citation check: Metagenomics reveals flavour metabolic network of cereal vinegar microbiota. https://app.cochat.ai/papers/10.1016/j.fm.2016.09.010
The paper
Wu, L.-H., Lu, Z.-M., Zhang, X.-J., Wang, Z.-M., Yu, Y.-J., Shi, J.-S., & Xu, Z.-H. (2017). Metagenomics reveals flavour metabolic network of cereal vinegar microbiota. Food Microbiology. https://doi.org/10.1016/j.fm.2016.09.010

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