Shotgun metagenomics and volatilome profile of the microbiota of fermented sausages

Applied and Environmental Microbiology

Volumn 84, Issue 3, 2018, Pages

  Ferrocino, Ilario ^a   Bellio, Alberto ^b   Giordano, Manuela ^a   Macori, Guerrino ^b   Romano, Angelo ^b   Rantsiou, Kalliopi ^a   Decastelli, Lucia ^b   Cocolin, Luca ^a  

^a UNIVERSITY OF TURIN   (Italy)

^b Liguria e Valle d'Aosta   (Italy)

Author keywords

Fermented sausages; Metabolic pathways; Shotgun metagenomics; Volatile organic compounds

Indexed keywords

ACETIC ACID; FOOD PROCESSING; GENES; MEATS; METABOLISM; ORGANIC ACIDS; ORGANIC COMPOUNDS; PH; VOLATILE ORGANIC COMPOUNDS;

CONCENTRATION OF ACETIC ACID; FERMENTED SAUSAGES; INOCULATED FERMENTATION; METABOLIC PATHWAYS; METAGENOMICS; ORGANOLEPTIC CHARACTERISTICS; SPONTANEOUS FERMENTATION; VOLATILE METABOLITES;

FERMENTATION;

ABUNDANCE; BACTERIUM; DATABASE; FERMENTATION; GENE; GENETIC ANALYSIS; GENOMICS; MEAT; META-ANALYSIS; METABOLISM; MICROORGANISM; SPECIES DIVERSITY; VOLATILE ORGANIC COMPOUND;

ENTEROBACTERIACEAE; LACTOBACILLUS SAKEI; STAPHYLOCOCCUS XYLOSUS;

ACETIC ACID; ACETOIN; FRAGRANCE; VOLATILE ORGANIC COMPOUND;

ANALYSIS; ANIMAL; BACTERIAL COUNT; ENTEROBACTERIACEAE; FERMENTATION; FERMENTED PRODUCT; FOOD CONTROL; GENETICS; ISOLATION AND PURIFICATION; LACTOBACILLUS; MEAT; META ANALYSIS; METABOLISM; METAGENOMICS; MICROBIOLOGY; MICROFLORA; PHYSIOLOGY; PIG; PROCEDURES; STAPHYLOCOCCUS; VOLATILIZATION;

ACETIC ACID; ACETOIN; ANIMALS; COLONY COUNT, MICROBIAL; ENTEROBACTERIACEAE; FERMENTATION; FERMENTED FOODS; FOOD MICROBIOLOGY; LACTOBACILLUS; MEAT PRODUCTS; METABOLIC NETWORKS AND PATHWAYS; METAGENOMICS; MICROBIOTA; ODORANTS; STAPHYLOCOCCUS; SWINE; VOLATILE ORGANIC COMPOUNDS; VOLATILIZATION;

EID: 85040680949     PISSN: 00992240     EISSN: 10985336     Source Type: Journal    
DOI: 10.1128/AEM.02120-17     Document Type: Article

References (54)

1. Casaburi A, Piombino P, Nychas G-J, Villani F, Ercolini D. 2015. Bacterial populations and the volatilome associated to meat spoilage. Food Microbiol 45:83-102. https://doi.org/10.1016/j.fm.2014.02.002
2. Cenci-Goga BT, Ranucci D, Miraglia D, Cioffi A. 2008. Use of starter cultures of dairy origin in the production of Salame nostrano, an Italian dry-cured sausage. Meat Sci 78:381-390. https://doi.org/10.1016/j.meatsci.2007.07 .001
3. Mauriello G, Casaburi A, Blaiotta G, Villani F. 2004. Isolation and technological properties of coagulase negative staphylococci from fermented sausages of Southern Italy. Meat Sci 67:149-158. https://doi.org/10 .1016/j.meatsci.2003.10.003
4. Cocolin L, Dolci P, Rantsiou K, Urso R, Cantoni C, Comi G. 2009. Lactic acid bacteria ecology of three traditional fermented sausages produced in the North of Italy as determined by molecular methods. Meat Sci 82:125-132. https://doi.org/10.1016/j.meatsci.2009.01.004
5. Blaiotta G, Pennacchia C, Villani F, Ricciardi A, Tofalo R, Parente E. 2004. Diversity and dynamics of communities of coagulase-negative staphylococci in traditional fermented sausages. J Appl Microbiol 97:271-284. https://doi.org/10.1111/j.1365-2672.2004.02298.x
6. Francesca N, Sannino C, Moschetti G, Settanni L. 2012. Microbial characterisation of fermented meat products from the Sicilian swine breed "Suino Nero Dei Nebrodi." Ann Microbiol 63:53-62
7. Kesmen Z, Yetiman A, Gulluce A, Kacmaz N, Sagdic O, Cetin B, Adiguzel A, Sahin F, Yetim H. 2012. Combination of culture-dependent and culture-independent molecular methods for the determination of lactic microbiota in sucuk. Int J Food Microbiol 153:428-435. https://doi.org/ 10.1016/j.ijfoodmicro.2011.12.008
8. Stellato G, La Storia A, De Filippis F, Borriello G, Villani F, Ercolini D. 2016. Overlap of spoilage-associated microbiota between meat and the meat processing environment in small-scale and large-scale retail. Appl Environ Microbiol 82:4045-4054. https://doi.org/10.1128/AEM.00793-16
9. Polka J, Rebecchi A, Pisacane V, Morelli L, Puglisi E. 2015. Bacterial diversity in typical Italian salami at different ripening stages as revealed by high-throughput sequencing of 16S rRNA amplicons. Food Microbiol 46:342-356. https://doi.org/10.1016/j.fm.2014.08.023
10. Greppi A, Ferrocino I, La Storia A, Rantsiou K, Ercolini D, Cocolin L. 2015. Monitoring of the microbiota of fermented sausages by culture independent rRNA-based approaches. Int J Food Microbiol 212:67-75. https://doi.org/10.1016/j.ijfoodmicro.2015.01.016
11. De Filippis F, Genovese A, Ferranti P, Gilbert JA, Ercolini D. 2016. Metatranscriptomics reveals temperature-driven functional changes in microbiome impacting cheese maturation rate. Sci Rep 6:21871. https://doi .org/10.1038/srep21871
12. Sharpton TJ. 2014. An introduction to the analysis of shotgun metagenomic data. Front Plant Sci 5:209. https://doi.org/10.3389/fpls.2014 .00209
13. Yang X, Noyes NR, Doster E, Martin JN, Linke LM, Magnuson RJ, Yang H, Geornaras I, Woerner DR, Jones KL. 2016. Use of metagenomic shotgun sequencing technology to detect foodborne pathogens within the microbiome of the beef production chain. Appl Environ Microbiol 82: 2433-2443. https://doi.org/10.1128/AEM.00078-16
14. Leonard SR, Mammel MK, Lacher DW, Elkins CA. 2015. Application of metagenomic sequencing to food safety: detection of Shiga toxinproducing Escherichia coli on fresh bagged spinach. Appl Environ Microbiol 81:8183-8191. https://doi.org/10.1128/AEM.02601-15
15. Nalbantoglu U, Cakar A, Dogan H, Abaci N, Ustek D, Sayood K, Can H. 2014. Metagenomic analysis of the microbial community in kefir grains. Food Microbiol 41:42-51. https://doi.org/10.1016/j.fm.2014.01.014
16. Jung JY, Lee SH, Kim JM, Park MS, Bae J, Hahn Y, Madsen EL, Jeon CO. 2011. Metagenomic analysis of kimchi, a traditional Korean fermented food. Appl Environ Microbiol 77:2264-2274. https://doi.org/10.1128/ AEM.02157-10
17. Sulaiman J, Gan HM, Yin WF, Chan KG. 2014. Microbial succession and the functional potential during the fermentation of Chinese soy sauce brine. Front Microbiol 5:556. https://doi.org/10.3389/fmicb.2014.00556
18. Nieminen TT, Koskinen K, Laine P, Hultman J, Säde E, Paulin L, Paloranta A, Johansson P, Björkroth J, Auvinen P. 2012. Comparison of microbial communities in marinated and unmarinated broiler meat by metagenomics. Int J Food Microbiol 157:142-149. https://doi.org/10.1016/j .ijfoodmicro.2012.04.016
19. Dugat-Bony E, Straub C, Teissandier A, Onésime D, Loux V, Monnet C, Irlinger F, Landaud S, Leclercq-Perlat M-N, Bento P, Fraud S, Gibrat JF, Aubert J, Fer F, Guédon E, Pons N, Kennedy S, Beckerich JM, Swennen D, Bonnarme P. 2015. Overview of a surface-ripened cheese community functioning by meta-omics analyses. PLoS One 10:e0124360. https://doi .org/10.1371/journal.pone.0124360
20. Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, Huttenhower C. 2012. Metagenomic microbial community profiling using unique clade-specific marker genes. Nat Methods 9:811-814. https://doi.org/10 .1038/nmeth.2066
21. Castellano P, Aristoy MC, Sentandreu MA, Vignolo G, Toldrá F. 2012. Lactobacillus sakei CRL1862 improves safety and protein hydrolysis in meat systems. J Appl Microbiol 113:1407-1416. https://doi.org/10.1111/ jam.12005
22. Jung JY, Lee SH, Jin HM, Hahn Y, Madsen EL, Jeon CO. 2013. Metatranscriptomic analysis of lactic acid bacterial gene expression during kimchi fermentation. Int J Food Microbiol 163:171-179. https://doi.org/10.1016/ j.ijfoodmicro.2013.02.022
23. Lessard MH, Viel C, Boyle B, St-Gelais D, Labrie S. 2014. Metatranscriptome analysis of fungal strains Penicillium camemberti and Geotrichum candidum reveal cheese matrix breakdown and potential development of sensory properties of ripened Camembert-type cheese. BMC Genomics 15:235. https://doi.org/10.1186/1471-2164-15-235
24. Chaillou S, Champomier-Vergès MC, Cornet M, Crutz-Le Coq AM, Dudez AM, Martin V, Beaufils S, Darbon-Rongère E, Bossy R, Loux V, Zagorec M. 2005. The complete genome sequence of the meat-borne lactic acid bacterium Lactobacillus sakei 23K. Nat Biotechnol 23:1527-1533. https:// doi.org/10.1038/nbt1160
25. Ardö Y. 2006. Flavour formation by amino acid catabolism. Biotechnol Adv 24:238-242. https://doi.org/10.1016/j.biotechadv.2005.11.005
26. Leroy S, Vermassen A, Ras G, Talon R. 2017. Insight into the genome of Staphylococcus xylosus, a ubiquitous species well adapted to meat products. Microorganisms 5:52. https://doi.org/10.3390/microorganisms5030052
27. Dainty RH, Edwards RA, Hibbard CM. 1989. Spoilage of vacuum-packed beef by a Clostridium sp. J Sci Food Agric 49:473-486. https://doi.org/ 10.1002/jsfa.2740490410
28. Xu H, Gao L, Jiang Y, Tian Y, Peng J, Xa Q, Chen Y. 2015. Transcriptome response of Lactobacillus sakei to meat protein environment. J Basic Microbiol 55:490-499. https://doi.org/10.1002/jobm.201400540
29. Freiding S, Gutsche KA, Ehrmann MA, Vogel RF. 2011. Genetic screening of Lactobacillus sakei and Lactobacillus curvatus strains for their peptidolytic system and amino acid metabolism, and comparison of their volatilomes in a model system. Syst Appl Microbiol 34:311-320. https:// doi.org/10.1016/j.syapm.2010.12.006
30. Talon R, Chastagnac C, Vergnais L, Montel MC, Berdagué JL. 1998. Production of esters by staphylococci. Int J Food Microbiol 45:143-150. https://doi.org/10.1016/S0168-1605(98)00159-7
31. Lee SB, Rhee YK, Gu EJ, Kim DW, Jang GJ, Song SH, Lee JI, Kim BM, Lee HJ, Hong HD, Cho CW, Kim HJ. 2017. Mass-based metabolomic analysis of Lactobacillus sakei and its growth media at different growth phases. J Microbiol Biotechnol 27:925-932. https://doi.org/10.4014/jmb.1609 .09014
32. Stentz R, Cornet M, Chaillou S, Zagorec M. 2001. Adaptation of Lactobacillus sakei to meat: a new regulatory mechanism of ribose utilization? Lait 81:131-138. https://doi.org/10.1051/lait:2001117
33. Champomier-Vergès MC, Maguin E, Mistou MY, Anglade P, Chich JF. 2002. Lactic acid bacteria and proteomics: current knowledge and perspectives. J Chromatogr B Analt Technol Biomed Life Sci 771: 329-342
34. Rimaux T, Vrancken G, Vuylsteke B, De Vuyst L, Leroy F. 2011. The pentose moiety of adenosine and inosine is an important energy source for the fermented-meat starter culture Lactobacillus sakei CTC 494 Appl Environ Microbiol 77:6539-6550. https://doi.org/10.1128/AEM .00498-11
35. Sunesen LO, Dorigoni V, Zanardi E, Stahnke L. 2001. Volatile compounds released during ripening in Italian dried sausage. Meat Sci 58:93-97. https://doi.org/10.1016/S0309-1740(00)00139-X
36. Olesen PT, Stahnke LH. 2004. The influence of environmental parameters on the catabolism of branched-chain amino acids by Staphylococcus xylosus and Staphylococcus carnosus. Food Microbiol 21:43-50. https:// doi.org/10.1016/S0740-0020(03)00048-0
37. Kenneally PM, Fransen NG, Grau H, O'Neill EE, Arendt EK. 1999. Effects of environmental conditions on microbial proteolysis in a pork myofibril model system. J Appl Microbiol 87:794-803. https://doi.org/10.1046/j .1365-2672.1999.00829.x
38. Peterson RJ, Chang SS. 1982. Identification of volatile flavor compounds of fresh, frozen beef stew and a comparison of these with those of canned beef stew. J Food Sci 47:1444-1448. https://doi.org/10.1111/j .1365-2621.1982.tb04957.x
39. Toldra F. 1998. Proteolysis and lipolysis in flavour development of dry-cured meat products. Meat Sci 49:S101-S110. https://doi.org/10 .1016/S0309-1740(98)90041-9
40. Bautista-Gallego J, Alessandria V, Fontana M, Bisotti S, Taricco S, Dolci P, Cocolin L, Rantsiou K. 2014. Diversity and functional characterization of Lactobacillus spp. isolated throughout the ripening of a hard cheese. Int J Food Microbiol 181:60-66. https://doi.org/10.1016/j.ijfoodmicro.2014 .04.020
41. Iacumin L, Comi G, Cantoni C, Cocolin L. 2006. Molecular and technological characterization of Staphylococcus xylosus isolated from naturally fermented Italian sausages by RAPD, Rep-PCR and Sau-PCR analysis. Meat Sci 74:281-288. https://doi.org/10.1016/j.meatsci.2006.03.020
42. Vauterin L, Vauterin P. 1992. Computer-aided objective comparison of electrophoresis patterns for grouping and identification of microorganisms. Eur Microbiol 1:37-41
43. Weisburg WG, Barns SM, Pelletier DA, Lane DJ. 1991. 16S ribosomal DNA amplification for phylogenetic study. J Bacteriol 173:697-703. https:// doi.org/10.1128/jb.173.2.697-703.1991
44. Ercolini D, Russo F, Ferrocino I, Villani F. 2009. Molecular identification of mesophilic and psychrotrophic bacteria from raw cow's milk. Food Microbiol 26:228-231. https://doi.org/10.1016/j.fm.2008.09.005
45. Cox MP, Peterson DA, Biggs PJ. 2010. SolexaQA: at-a-glance quality assessment of Illumina second-generation sequencing data. BMC Bioinformatics 11:485. https://doi.org/10.1186/1471-2105-11-485
46. Schmieder R, Edwards R. 2011. Quality control and preprocessing of metagenomic datasets. Bioinformatics 27:863-864. https://doi.org/10 .1093/bioinformatics/btr026
47. Langmead B, Salzberg SL. 2012. Fast gapped-read alignment with Bowtie 2. Nat Methods 9:357-359. https://doi.org/10.1038/nmeth.1923
48. Zerbino DR, Birney E. 2008. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 18:821-829. https://doi .org/10.1101/gr.074492.107
49. Zhu W, Lomsadze A, Borodovsky M. 2010. Ab initio gene identification in metagenomic sequences. Nucleic Acids Res 38:e132. https://doi.org/10 .1093/nar/gkq275
50. Edgar RC. 2010. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460-2461. https://doi.org/10.1093/bioinformatics/ btq461
51. Davis C. 2015. mBLAST: keeping up with the sequencing explosion for (meta) genome analysis. J Data Mining Genomics Proteomics 4:135. https://doi.org/10.4172/2153-0602.1000135
52. Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M. 2014. Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res 42:D199-D205. https://doi.org/10.1093/nar/ gkt1076
53. Mitra S, Stärk M, Huson DH. 2011. Analysis of 16S rRNA environmental sequences using MEGAN. BMC Genomics 12 Suppl 3:S17. https://doi.org/ 10.1186/1471-2164-12-S3-S17
54. Love M, Huber W, Anders S. 2014. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:550. https://doi.org/10.1186/s13059-014-0550-8