Literature DB >> 35599257

Metabolite-based cell sorting workflow for identifying microbes producing carbonyls in tobacco leaves.

Tianfei Zheng1,2,3, Qianying Zhang4, Zheng Peng1,2,3, Dongliang Li4, Xinying Wu1,2,3, Yi Liu4, Pinhe Li4, Juan Zhang5,6, Guocheng Du7,8.   

Abstract

Carbonyl compounds represented by aldehydes and ketones make an important contribution to the flavor of tobacco. Since most carbonyl compounds are produced by microbes during tobacco fermentation, identifying their producers is important to improve the quality of tobacco. Here, we created an efficient workflow that combines metabolite labeling with fluorescence-activated cell sorting (ML-FACS), 16S rRNA gene sequencing, and microbial culture to identify the microbes that produce aldehydes or ketones in fermented cigar tobacco leaves (FCTL). Microbes were labeled with a specific fluorescent dye (cyanine5 hydrazide) and separated by flow cytometry. Subsequently, the sorted microbes were identified and cultured under laboratory conditions. Four genera, Acinetobacter, Sphingomonas, Solibacillus, and Lysinibacillus, were identified as the main carbonyl compound-producing microbes in FCTL. In addition, these microorganisms could produce flavor-related aldehydes and ketones in a simple synthetic medium, such as benzaldehyde, phenylacetaldehyde, 4-hydroxy-3-ethoxy-benzaldehyde, and 3,5,5-trimethyl-2-cyclohexene-1-one. On the whole, this research has developed a new method to quickly isolate and identify microorganisms that produce aldehydes or ketones from complex microbial communities. ML-FACS would also be used to identify other compound-producing microorganisms in other systems. KEY POINTS: • An approach was developed to identify target microbes in complex communities. • Microbes that produce aldehyde/ketone flavor compounds in fermented cigar tobacco leaves were identified. • Functional microbes that produce aldehyde/ketone flavor compounds from the native environment were captured in pure cultures.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Carbonyl compound; Cigar tobacco leaves; Fluorescence activated cell sorting; Functional microbe; Metabolite labeling

Mesh:

Substances:

Year:  2022        PMID: 35599257     DOI: 10.1007/s00253-022-11982-3

Source DB:  PubMed          Journal:  Appl Microbiol Biotechnol        ISSN: 0175-7598            Impact factor:   4.813


  33 in total

1.  Microbial community structure and dynamics of dark fire-cured tobacco fermentation.

Authors:  Michele Di Giacomo; Marianna Paolino; Daniele Silvestro; Giovanni Vigliotta; Francesco Imperi; Paolo Visca; Pietro Alifano; Dino Parente
Journal:  Appl Environ Microbiol       Date:  2006-12-01       Impact factor: 4.792

2.  Impact of feeding and stirring regimes on the internal stratification of microbial communities in the fermenter of anaerobic digestion plants.

Authors:  Robert Heyer; Johanna Klang; Patrick Hellwig; Kay Schallert; Philipp Kress; Benedikt Huelsemann; Susanne Theuerl; Udo Reichl; Dirk Benndorf
Journal:  Bioresour Technol       Date:  2020-06-13       Impact factor: 9.642

Review 3.  The multi-omics promise in context: from sequence to microbial isolate.

Authors:  Johanna Gutleben; Maryam Chaib De Mares; Jan Dirk van Elsas; Hauke Smidt; Jörg Overmann; Detmer Sipkema
Journal:  Crit Rev Microbiol       Date:  2017-05-31       Impact factor: 7.624

Review 4.  Symposium review: Interaction of starter cultures and nonstarter lactic acid bacteria in the cheese environment.

Authors:  J Blaya; Z Barzideh; G LaPointe
Journal:  J Dairy Sci       Date:  2017-12-21       Impact factor: 4.034

5.  Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.

Authors:  Evan Bolyen; Jai Ram Rideout; Matthew R Dillon; Nicholas A Bokulich; Christian C Abnet; Gabriel A Al-Ghalith; Harriet Alexander; Eric J Alm; Manimozhiyan Arumugam; Francesco Asnicar; Yang Bai; Jordan E Bisanz; Kyle Bittinger; Asker Brejnrod; Colin J Brislawn; C Titus Brown; Benjamin J Callahan; Andrés Mauricio Caraballo-Rodríguez; John Chase; Emily K Cope; Ricardo Da Silva; Christian Diener; Pieter C Dorrestein; Gavin M Douglas; Daniel M Durall; Claire Duvallet; Christian F Edwardson; Madeleine Ernst; Mehrbod Estaki; Jennifer Fouquier; Julia M Gauglitz; Sean M Gibbons; Deanna L Gibson; Antonio Gonzalez; Kestrel Gorlick; Jiarong Guo; Benjamin Hillmann; Susan Holmes; Hannes Holste; Curtis Huttenhower; Gavin A Huttley; Stefan Janssen; Alan K Jarmusch; Lingjing Jiang; Benjamin D Kaehler; Kyo Bin Kang; Christopher R Keefe; Paul Keim; Scott T Kelley; Dan Knights; Irina Koester; Tomasz Kosciolek; Jorden Kreps; Morgan G I Langille; Joslynn Lee; Ruth Ley; Yong-Xin Liu; Erikka Loftfield; Catherine Lozupone; Massoud Maher; Clarisse Marotz; Bryan D Martin; Daniel McDonald; Lauren J McIver; Alexey V Melnik; Jessica L Metcalf; Sydney C Morgan; Jamie T Morton; Ahmad Turan Naimey; Jose A Navas-Molina; Louis Felix Nothias; Stephanie B Orchanian; Talima Pearson; Samuel L Peoples; Daniel Petras; Mary Lai Preuss; Elmar Pruesse; Lasse Buur Rasmussen; Adam Rivers; Michael S Robeson; Patrick Rosenthal; Nicola Segata; Michael Shaffer; Arron Shiffer; Rashmi Sinha; Se Jin Song; John R Spear; Austin D Swafford; Luke R Thompson; Pedro J Torres; Pauline Trinh; Anupriya Tripathi; Peter J Turnbaugh; Sabah Ul-Hasan; Justin J J van der Hooft; Fernando Vargas; Yoshiki Vázquez-Baeza; Emily Vogtmann; Max von Hippel; William Walters; Yunhu Wan; Mingxun Wang; Jonathan Warren; Kyle C Weber; Charles H D Williamson; Amy D Willis; Zhenjiang Zech Xu; Jesse R Zaneveld; Yilong Zhang; Qiyun Zhu; Rob Knight; J Gregory Caporaso
Journal:  Nat Biotechnol       Date:  2019-08       Impact factor: 54.908

6.  Revealing oxidative damage to enzymes of carbohydrate metabolism in yeast: An integration of 2D DIGE, quantitative proteomics, and bioinformatics.

Authors:  Cory H T Boone; Ryan A Grove; Dana Adamcova; Camila P Braga; Jiri Adamec
Journal:  Proteomics       Date:  2016-06-08       Impact factor: 3.984

7.  Acinetobacter species isolates from a range of environments: species survey and observations of antimicrobial resistance.

Authors:  Ji-Young Choi; Yejin Kim; Eun Ah Ko; Young Kyoung Park; Weon-Hwa Jheong; GwangPyo Ko; Kwan Soo Ko
Journal:  Diagn Microbiol Infect Dis       Date:  2012-08-16       Impact factor: 2.803

8.  Rheological behaviors of a novel exopolysaccharide produced by Sphingomonas WG and the potential application in enhanced oil recovery.

Authors:  Sixue Ji; Hui Li; GuanHua Wang; Teng Lu; Wenzhe Ma; Jiqian Wang; Hu Zhu; Hai Xu
Journal:  Int J Biol Macromol       Date:  2020-08-15       Impact factor: 6.953

9.  Metabolomics reveals impact of seven functional foods on metabolic pathways in a gut microbiota model.

Authors:  Mohamed A Farag; Amr Abdelwareth; Ibrahim E Sallam; Mohamed El Shorbagi; Nico Jehmlich; Katarina Fritz-Wallace; Stephanie Serena Schäpe; Ulrike Rolle-Kampczyk; Anja Ehrlich; Ludger A Wessjohann; Martin von Bergen
Journal:  J Adv Res       Date:  2020-01-03       Impact factor: 10.479

10.  Cultivation-independent and cultivation-dependent metagenomes reveal genetic and enzymatic potential of microbial community involved in the degradation of a complex microbial polymer.

Authors:  Ohana Y A Costa; Mattias de Hollander; Agata Pijl; Binbin Liu; Eiko E Kuramae
Journal:  Microbiome       Date:  2020-06-01       Impact factor: 14.650

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