Structure of association networks in food bacterial communities

Food Microbiology - Tập 73 - Trang 49-60 - 2018
Eugenio Parente1, Teresa Zotta2, Karoline Faust3, Francesca De Filippis4,5, Danilo Ercolini4,5
1Dipartimento di Scienze, Università degli Studi della Basilicata, 85100, Potenza, Italy
2Istituto di Scienze dell’Alimentazione, CNR, 83100 Avellino, Italy
3Department of Microbiology and Immunology, REGA Institute, KU Leuven, 3000, Belgium
4Department of Agricultural Sciences, Division of Microbiology, University of Naples “Federico II”, 80055 Portici, Italy
5Task Force on Microbiome Studies, University of Naples “Federico II”, Naples, Italy

Tài liệu tham khảo

Alessandria, 2016, Microbiota of an Italian Grana like cheese during manufacture and ripening unraveled by 16S rRNA-based approaches, Appl. Environ. Microbiol., 82, 3988, 10.1128/AEM.00999-16 Berry, 2014, Deciphering microbial interactions and detecting keystone species with co-occurrence networks, Front. Microbiol., 5, 219, 10.3389/fmicb.2014.00219 Biswas, 2016, Learning microbial interaction networks from metagenomic count data, J. Comput. Biol., 23, 526, 10.1089/cmb.2016.0061 Calasso, 2016, Relationships among house, rind and core microbiotas during manufacture of traditional Italian cheeses at the same dairy plant, Food Microbiol., 54, 115, 10.1016/j.fm.2015.10.008 Caplice, 1999, Food fermentations: role of microorganisms in food production and preservation, Int. J. Food Microbiol., 50, 131, 10.1016/S0168-1605(99)00082-3 Cardinale, 2015, Bacterial networks and co-occurrence relationships in the lettuce root microbiota, Environ. Microbiol., 17, 239, 10.1111/1462-2920.12686 Cauchie, 2017, The use of 16S rRNA gene metagenetic monitoring of refrigerated food products for understanding the kinetics of microbial subpopulations at different storage temperatures: the example of white pudding, Int. J. Food Microbiol., 247, 70, 10.1016/j.ijfoodmicro.2016.10.012 Chaillou, 2015, Origin and ecological selection of core and food-specific bacterial communities associated with meat and seafood spoilage, ISME J., 9, 1105, 10.1038/ismej.2014.202 Chaffron, 2010, A global network of coexisting microbes from environmental and whole-genome sequence data, Genome Res., 20, 947, 10.1101/gr.104521.109 Cocolin, 2015, Zooming into food-associated microbial consortia: a “cultural”evolution, Curr. Opin. Food. Sci., 2, 43, 10.1016/j.cofs.2015.01.003 Csardi, 2006, The igraph software package for complex network research, InterJournal Complex Syst., 1695 De Filippis, 2016, Metatranscriptomics reveals temperature-driven functional changes in microbiome impacting cheese maturation rate, Sci. Rep., 6, 21871, 10.1038/srep21871 De Filippis, 2014, A selected core microbiome drives the early stages of three popular Italian cheese manufactures, PLoS One, 9, 10.1371/journal.pone.0089680 De Filippis, 2013, Exploring the sources of bacterial spoilers in beefsteaks by culture-independent high-throughput sequencing, PLoS One, 8, 10.1371/journal.pone.0070222 Deng, 2012, Molecular ecological network analyses, BMC Bioinf., 13, 30, 10.1186/1471-2105-13-113 Dolci, 2014, rRNA-based monitoring of the microbiota involved in Fontina PDO cheese production in relation to different stages of cow lactation, Int. J. Food Microbiol., 185, 127, 10.1016/j.ijfoodmicro.2014.05.021 Dong, 2007, Understanding network concepts in modules, BMC Syst. Biol., 4, 1 Dormann, 2008, Introducing the bipartite package: analysing ecological networks, R. News, 8/2, 8 Dunne, 2002, Food-web structure and network theory: the role of connectance and size, Proc. Natl. Acad. Sci. U. S. A., 99, 12917, 10.1073/pnas.192407699 Duran-Pinedo, 2011, Correlation network analysis applied to complex biofilm communities, PLoS One, 6, 10.1371/journal.pone.0028438 Elizaquível, 2014, Recent developments in the use of viability dyes and quantitative PCR in the food microbiology field, J. Appl. Microbiol., 116, 1, 10.1111/jam.12365 Ercolini, 2013, High-throughput sequencing and metagenomics: moving forward in the culture-independent analysis of food microbial ecology, Appl. Environ. Microbiol., 79, 3148, 10.1128/AEM.00256-13 Erkus, 2016, Use of propidium monoazide for selective profiling of viable microbial cells during Gouda cheese ripening, Int. J. Food Microbiol., 228, 1, 10.1016/j.ijfoodmicro.2016.03.027 Faust, 2016, CoNet app: inference of biological association networks using Cytoscape, F1000Res., 5, 1519, 10.12688/f1000research.9050.1 Faust, 2015, Cross-biome comparison of microbial association networks, Front. Microbiol., 6, 1200, 10.3389/fmicb.2015.01200 Faust, 2012, Microbial interactions: from networks to models, Nat. Rev. Microbiol., 10, 538, 10.1038/nrmicro2832 Faust, 2012, Microbial co-occurrence relationships in the human microbiome, PLoS Comput. Biol., 8, 10.1371/journal.pcbi.1002606 Ferrocino, 2015, Impact of nisin-activated packaging on microbiota of beef burgers during storage, Appl. Environ. Microbiol., 82, 549, 10.1128/AEM.03093-15 Friedman, 2012, Inferring correlation networks from genomic survey data, PLoS Comput. Biol., 8, 10.1371/journal.pcbi.1002687 Fronczak, 2004, Average path length in random networks, Phys. Rev. E - Stat. Nonlinear Soft Matter Phys., 70 Gillespie, 2015, Fitting heavy tailed distributions: the poweRlaw package, J. Stat. Software, 64, 1 Gram, 2002, Food spoilage-interactions between food spoilage bacteria, Int. J. Food Microbiol., 78, 79, 10.1016/S0168-1605(02)00233-7 Greppi, 2015, Monitoring of the microbiota of fermented sausages by culture independent rRNA-based approaches, Int. J. Food Microbiol., 212, 67, 10.1016/j.ijfoodmicro.2015.01.016 Guidone, 2016, The microbiota of high-moisture mozzarella cheese produced with different acidification methods, Int. J. Food Microbiol., 216, 9, 10.1016/j.ijfoodmicro.2015.09.002 Hultman, 2015, Meat processing plant microbiome and contamination patterns of cold-tolerant bacteria causing food safety and spoilage risks in the manufacture of vacuum-packaged cooked sausages, Appl. Environ. Microbiol., 81, 7088, 10.1128/AEM.02228-15 International Commission on Microbiologial Specifications for Foods, 1980, Microorganisms in Foods 3: Microbial Ecology of Foods, vol. 1 Ivey, 2013, Microbial interactions in food fermentations, Annu. Rev. Food Sci. Technol., 4, 141, 10.1146/annurev-food-022811-101219 Kastman, 2016, Biotic interactions shape the ecological distributions of Staphylococcus species, mBio, 7, 10.1128/mBio.01157-16 Koeppel, 2012, Lineage-dependent ecological coherence in bacteria, FEMS Microbiol. Ecol., 81, 574, 10.1111/j.1574-6941.2012.01387.x Kurtz, 2015, Sparse and compositionally robust inference of microbial ecological networks, PLoS Comput. Biol., 11, 10.1371/journal.pcbi.1004226 Layeghifard, 2017, Disentangling interactions in the microbiome: a network perspective, Trends Microbiol., 25, 217, 10.1016/j.tim.2016.11.008 Leff, 2013, Bacterial communities associated with the surfaces of fresh fruits and vegetables, PLoS One, 8, 10.1371/journal.pone.0059310 Lima-Mendez, 2015, Ocean plankton. Determinants of community structure in the global plankton interactome, Science, 348, 10.1126/science.1262073 Malakar, 2003, Relevance of microbial interactions to predictive microbiology, Int. J. Food Microbiol., 84, 263, 10.1016/S0168-1605(02)00424-5 McMurdie, 2013, phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data, PLoS One, 8, 10.1371/journal.pone.0061217 Newman, 2010 Oksanen, 2017 Parente, 2016, FoodMicrobionet: a database for the visualisation and exploration of food bacterial communities based on network analysis, Int. J. Food Microbiol., 219, 28, 10.1016/j.ijfoodmicro.2015.12.001 Parente, 2016, FoodMicrobionet 1.1.6: a network analysis tool for the exploration of food bacterial communities Parente, 2016, Microbial community dynamics in thermophilic undefined milk starter cultures, Int. J. Food Microbiol., 217, 59, 10.1016/j.ijfoodmicro.2015.10.014 Peura, 2015, Resistant microbial cooccurrence patterns inferred by network topology, Appl. Environ. Microbiol., 81, 2090, 10.1128/AEM.03660-14 Pothakos, 2015, Processing Environment and ingredients are both sources of Leuconostoc gelidum, which emerges as a major spoiler in ready-to-eat meals, Appl. Environ. Microbiol., 81, 3529, 10.1128/AEM.03941-14 R Core Team, 2016 Remenant, 2015, Bacterial spoilers of food: behavior, fitness and functional properties, Food Microbiol., 45, 45, 10.1016/j.fm.2014.03.009 Revelle, 2016 Smid, 2013, Microbe-microbe interactions in mixed culture food fermentations, Curr. Opin. Biotechnol., 24, 148, 10.1016/j.copbio.2012.11.007 Sohier, 2014, Evolution of microbiological analytical methods for dairy industry needs, Front. Microbiol., 5, 16, 10.3389/fmicb.2014.00016 Steele, 2011, Marine bacterial, archaeal and protistan association networks reveal ecological linkages, ISME J., 5, 1414, 10.1038/ismej.2011.24 Stellato, 2016, Overlap of spoilage microbiota between meat and meat processing environment in small-scale vs large-scale retail distribution, Appl. Environ. Microbiol., 82, 4045, 10.1128/AEM.00793-16 Stellato, 2015, Coexistence of lactic acid bacteria and potential spoilage microbiota in a dairy processing environment, Appl. Environ. Microbiol., 81, 7893, 10.1128/AEM.02294-15 Stellato, 2015, Bacterial biogeographical patterns in a cooking center for hospital foodservice, Int. J. Food Microbiol., 193, 99, 10.1016/j.ijfoodmicro.2014.10.018 Wang, 2017, Combined use of network inference tools identifies ecologically meaningful bacterial associations in a paddy soil, Soil Biol. Biochem., 105, 227, 10.1016/j.soilbio.2016.11.029 Warnes, 2016 Weiss, 2016, Correlation detection strategies in microbial data sets vary widely in sensitivity and precision, ISME J., 10, 1669, 10.1038/ismej.2015.235 Zhou, 2011, Phylogenetic molecular ecological network of soil microbial communities in response to elevated CO2, mBio, 2, 10.1128/mBio.00122-11