OpenLB
Open Library of Bioscience
Advanced Search
Microbial ecology
Oct, 2021;82 (3): 613-622.

Analysis of Bacterial Communities by 16S rRNA Gene Sequencing in a Melon-Producing Agro-environment.

Eduardo Franco-Frías, Victor Mercado-Guajardo, Angel Merino-Mascorro, Janeth Pérez-Garza, Norma Heredia, Juan S León, Lee-Ann Jaykus, Jorge Dávila-Aviña, Santos García
Author Information
  1. Eduardo Franco-Frías: Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, Apdo. Postal 124-F, San Nicolás, N.L., 66451, México. ORCID
  2. Victor Mercado-Guajardo: Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, Apdo. Postal 124-F, San Nicolás, N.L., 66451, México.
  3. Angel Merino-Mascorro: Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, Apdo. Postal 124-F, San Nicolás, N.L., 66451, México. ORCID
  4. Janeth Pérez-Garza: Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, Apdo. Postal 124-F, San Nicolás, N.L., 66451, México. ORCID
  5. Norma Heredia: Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, Apdo. Postal 124-F, San Nicolás, N.L., 66451, México. ORCID
  6. Juan S León: Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA. ORCID
  7. Lee-Ann Jaykus: Department of Food Science, North Carolina State University, Raleigh, NC, USA.
  8. Jorge Dávila-Aviña: Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, Apdo. Postal 124-F, San Nicolás, N.L., 66451, México. ORCID
  9. Santos García: Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, Apdo. Postal 124-F, San Nicolás, N.L., 66451, México. santos@microbiosymas.com. ORCID
PMID: 33570667 DOI: 10.1007/s00248-021-01709-8

Abstract

Cantaloupe melons, which have been responsible of an increasing number of foodborne disease outbreaks, may become contaminated with microbial pathogens during production. However, little information is available on the microbial populations in the cantaloupe farm environment. The purpose of this work was to characterize the bacterial communities present on cantaloupe farms. Fruit, soil, and harvester hand rinsates were collected from two Mexican cantaloupe farms, each visited three times. Microbiome analysis was performed by sequencing 16sRNA and analyzed using qiime2 software. Correlations were determined between sample type and microbial populations. The α and β diversity analysis identified 2777 sequences across all samples. The soil samples had the highest number and diversity of unique species (from 130 to 1329 OTUs); cantaloupe (from 112 to 205 OTUs), and hands (from 67 to 151 OTUs) had similar diversity. Collectively, Proteobacteria was the most abundant phyla (from 42 to 95%), followed by Firmicutes (1-47%), Actinobacteria (< 1 to 23%), and Bacteroidetes (< 1 to 4.8%). The most abundant genera were Acinetobacter (20-58%), Pseudomonas (14.5%), Erwinia (13%), and Exiguobacterium (6.3%). Genera with potential to be pathogenic included Bacillus (4%), Salmonella (0.85%), Escherichia-Shigella (0.38%), Staphylococcus (0.32%), Listeria (0.29%), Clostridium (0.28%), and Cronobacter (0.27%), which were found at lower frequencies. This study provides information on the cantaloupe production microbiome, which can inform future research into critical food safety issues such as antimicrobial resistance, virulence, and genomic epidemiology.

Keywords

16 s RNA Bacterial population Cantaloupe farms Sequencing

References

  1. CDC (2017) Foodborne Diseases Active Surveillance Network (FoodNet): FoodNet 2015 Surveillance Report (Final Data). U.S. Department of Health and Human Services, CDC, Atlanta
  2. Richards G, Beuchat L (2004) Attachment of Salmonella poona to cantaloupe rind and stem scar tissues as affected by temperature of fruit and inoculum. J Food Prot 67:1359–1364. https://doi.org/10.4315/0362-028x-67.7.1359 [DOI: 10.4315/0362-028x-67.7.1359]
  3. Garcia S, Heredia N (2017) Microbiological Safety of vegetables in the field, during harvest and packaging: a global issue. In: Buckle K, Yada R, Rosenthal A (eds) Barbosa-Cánovas G, Pastore G, Candogan K, Medina Meza IG, Caetano da Silva Lannes S. Global Food Security and Wellness. Springer, New York, pp 27–48
  4. Leon JS, Jaykus L, Moe C (2007) Food safety issues and the microbiology of fruits and vegetables. In: Heredia N, Wesley I, Garcia S (eds) Microbiologically safe foods. John Wiley and Sons, New York, pp 255–290
  5. Marti R, Scott A, Tien YC, Murray R, Sabourin L, Zhang Y, Topp E (2013) Impact of manure fertilization on the abundance of antibiotic-resistant bacteria and frequency of detection of antibiotic resistance genes in soil and on vegetables at harvest. Appl Environ Microbiol 79:5701–5709. https://doi.org/10.1128/AEM.01682-13 [DOI: 10.1128/AEM.01682-13]
  6. Hill GT, Mitkowski NA, Aldrich-Wolfe L, Emele LR, Jurkoine DD, Ficke A, Maldonado-Ramirez S, Lynch ST, Nelson EB (2000) Methods for assessing the composition and diversity of soil microbial communities. Appl Soil Ecol 15:25–36. https://doi.org/10.1016/S0929-1393(00)00069-X [DOI: 10.1016/S0929-1393(00)00069-X]
  7. Rosselló-Mora R, Amann R (2001) The species concept for prokaryotes. FEMS Microbiol Rev 25:39–67. https://doi.org/10.1111/j.1574-6976.2001.tb00571.x [DOI: 10.1111/j.1574-6976.2001.tb00571.x]
  8. Heritage J, Evans EGV, Killington RA (1999) The microbiology of soil and of nutrient cycling. In: Heritage J, EGV E, Killington RA (eds) Microbiology in action. Cambridge University Press, Cambridge, pp 1–10 [DOI: 10.1017/CBO9780511811234]
  9. Bulgarelli D, Schlaeppi K, Spaepen S, van Themaat EVL, Schulze-Lefert P (2013) Structure and functions of the bacterial microbiota of plants. Annu Rev Plant Biol 64:807–838. https://doi.org/10.1146/annurev-arplant-050312-120106 [DOI: 10.1146/annurev-arplant-050312-120106]
  10. Kostic AD, Howitt MR, Garrett WS (2013) Exploring host-microbiota interactions in animal models and humans. Genes Dev 27:701–718. https://doi.org/10.1101/gad.212522.112 [DOI: 10.1101/gad.212522.112]
  11. Caplice E, Fitzgerald GF (1999) Food fermentations: role of microorganisms in food production and preservation. Int J Food Microbiol 50:131–149. https://doi.org/10.1016/s0168-1605(99)00082-3 [DOI: 10.1016/s0168-1605(99)00082-3]
  12. Schloss PD, Handelsman J (2003) Biotechnological prospects from metagenomics. Curr Opin Biotechnol 14:303–310. https://doi.org/10.1016/s0958-1669(03)00067-3 [DOI: 10.1016/s0958-1669(03)00067-3]
  13. Kunin V, Copeland A, Lapidus A, Mavromatis K, Hugenholtz (2008) A bioinformatician's guide to metagenomics. MMBR 72:557–578. https://doi.org/10.1128/MMBR.00009-08 [DOI: 10.1128/MMBR.00009-08]
  14. Alkema W, Boekhorst J, Wels M, van Hijum SAFT (2016) Microbial bioinformatics for food safety and production. Brief Bioinform 17:283–292. https://doi.org/10.1093/bib/bbv034 [DOI: 10.1093/bib/bbv034]
  15. Mirete S, Morgante V, Pastor JEG (2016) Functional metagenomics of extreme environments. Curr Opin Biotechnol. 38:143–149. https://doi.org/10.1016/j.copbio.2016.01.017 [DOI: 10.1016/j.copbio.2016.01.017]
  16. Sekse C, Jensen H, Dobrindt U, Johannessen GS, Li W, Spilsberg N, Shi J (2017) High throughput sequencing for detection of foodborne pathogens. Front Microbiol 8:2029. https://doi.org/10.3389/fmicb.2017.02029 [DOI: 10.3389/fmicb.2017.02029]
  17. Ottesen A, González A, Bell R, Pettengill JB (2013) Co-enriching microflora associated with culture based methods to detect Salmonella from tomato phyllosphere. PLoS One 8:e73079. https://doi.org/10.1371/journal.pone.0073079 [DOI: 10.1371/journal.pone.0073079]
  18. Jarvis KG, White JR, Grim CJ, Ewing L, Otesen AR, Beabrun JJG, Pettengill JB, Brown E, Hanes DE (2015) Cilantro microbiome before and after nonselective pre-enrichment for Salmonella using 16S rRNA and metagenomic sequencing. BMC Microbiology 15:160. https://doi.org/10.1186/s12866-015-0497-2 [DOI: 10.1186/s12866-015-0497-2]
  19. Williams TR, Moyne AL, Harris LJ, Marco ML (2013) Season, irrigation, leaf age, and Escherichia coli inoculation influence the bacterial diversity in the lettuce phyllosphere. PLoS One 8:e68642. https://doi.org/10.1371/journal.pone.0068642 [DOI: 10.1371/journal.pone.0068642]
  20. Leonard SR, Mammel MK, Lacher DW, Elkins CA (2015) Application of metagenomic sequencing to food safety: detection of shiga toxin-producing Escherichia coli on fresh bagged spinach. Appl Environ Microbiol 81:8183–8191. https://doi.org/10.1128/AEM.02601-15 [DOI: 10.1128/AEM.02601-15]
  21. Bartz FE, Lickness JS, Heredia N, Fabiszewski de Aceituno A, Newman KL, Hodge DW, Jaykus LA, García S, Leon JS (2017) Contamination of fresh produce by microbial indicators on farms and in packing facilities: elucidation of environmental routes. Appl Environ Microbiol 83:e02984–e02916. https://doi.org/10.1128/AEM.02984-16 [DOI: 10.1128/AEM.02984-16]
  22. Heredia N, Caballero C, Cárdenas C, Molina K, García R, Solis L, Burrowes V, Bartz FE, Fabiszewski A, Jaykus LA, García S, Leon J (2016) Microbial indicator profiling of fresh produce and environmental samples from farms and packing facilities in northern Mexico. J Food Prot 79:1197–1209. https://doi.org/10.4315/0362-028X.JFP-15-499 [DOI: 10.4315/0362-028X.JFP-15-499]
  23. Thien SJ (1979) A flow diagram for teaching texture by feel analysis. J Agric Educ 8:54–55. https://doi.org/10.2134/jae.1979.0054 [DOI: 10.2134/jae.1979.0054]
  24. Secretaría de Medio Ambiente y Recursos Naturales (2004) Norma Mexicana a NMX-AA-25-1984: environmental protection-soil contamination – solid residues-pH determination-potentiometric method. SEMARNAT. http://www.ordenjuridico.gob.mx/Federal/PE/APF/APC/SEMARNAT/Normas/Oficiales/SEMARNAT%201984%20I.pdf
  25. Junttila S, Lim KJ, Rudd S (2009) Optimization and comparison of different methods for RNA isolation for cDNa library construction from the reindeer lichen Cladonia rangiferina. BMC Res Notes 2:204. https://doi.org/10.1186/1756-0500-2-204 [DOI: 10.1186/1756-0500-2-204]
  26. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, Smith G, Knight R (2012) Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J 6:1621–1624. https://doi.org/10.1038/ismej.2012.8 [DOI: 10.1038/ismej.2012.8]
  27. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41:D590–D596. https://doi.org/10.1093/nar/gks1219 [DOI: 10.1093/nar/gks1219]
  28. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215:403–410. https://doi.org/10.1016/S0022-2836(05)80360-2 [DOI: 10.1016/S0022-2836(05)80360-2]
  29. Cao Y, Fanning S, Proos S, Jorgan K, Srikumar S (2017) A review on the application of next generation sequencing technologies as applied to food-related microbiome studies. Front Microbiol 8:1829. https://doi.org/10.3389/fmicb.2017.01829 [DOI: 10.3389/fmicb.2017.01829]
  30. Delmont TO, Robe P, Cecillon S, Clarck IM, Constancias F, Simonet P, Hirsch PR, Vogel TM (2011) Accessing the soil metagenome for studies of microbial diversity. Appl Environ Microbiol 77:1315–1324. https://doi.org/10.1128/AEM.01526-10 [DOI: 10.1128/AEM.01526-10]
  31. Barboza ADM, Pylro VS, Jacques RJS, Gubiani PI, de Quadros FLF, da Trindade JK, Triplett EW, Roesch L (2018) Seasonal dynamics alter taxonomical and functional microbial profiles in Pampa biome soils under natural grasslands. PeerJ 6:e4991. https://doi.org/10.7717/peerj.4991 [DOI: 10.7717/peerj.4991]
  32. Castro HF, Classen AT, Austin EE, Norby RJ, Schadt CW (2010) Soil microbial community responses to multiple experimental climate change drivers. Appl Environ Microbiol 76:999–1007. https://doi.org/10.1128/AEM.02874-09 [DOI: 10.1128/AEM.02874-09]
  33. Chau JF, Bagtzoglou AC, Wilig MR (2011) The effect of soil texture on richness and diversity of bacterial communities. Environ Forensics 12:333–341. https://doi.org/10.1080/15275922.2011.622348 [DOI: 10.1080/15275922.2011.622348]
  34. Fierer N, Jackson RB (2006) The diversity and biogeography of soil bacterial communities. Proc Natl Acad Sci U S A 103:626–631. https://doi.org/10.1073/pnas.0507535103 [DOI: 10.1073/pnas.0507535103]
  35. Lauber CL, Hamady M, Knight R, Fierer N (2009) Pyrosequencing-based assessment of soil pH as a predictor of soil bacterial communities’ structure at the continental scale. Appl Environ Microbiol 75:5111–5120. https://doi.org/10.1128/AEM.00335-09 [DOI: 10.1128/AEM.00335-09]
  36. Lauber CL, Ramirez KS, Aanderud Z, Lennon J, Fierer N (2013) Temporal variability in soil microbial communities across land-use types. ISME J 7:1641–1650. https://doi.org/10.1038/ismej.2013.50 [DOI: 10.1038/ismej.2013.50]
  37. Leff JW, Fierer N (2013) Bacterial communities associated with the surfaces of fresh fruits and vegetables. PLoS One 8:e59310. https://doi.org/10.1371/journal.pone.0059310 [DOI: 10.1371/journal.pone.0059310]
  38. Glassner H, Zchori-Fein E, Compant S, Sessitsch A, Katzir N, Portnoy V, Yaron S (2015) Characterization of endophytic bacteria from cucurbit fruits with potential benefits to agriculture in melons (Cucumis melo L.). FEMS Microbiol Ecol 91:fiv074. https://doi.org/10.1093/femsec/fiv074 [DOI: 10.1093/femsec/fiv074]
  39. Crowther TW, Maynard DS, Leff JW, Oldfield EE, McCulley R, Fierer N, Bradford MA (2014) Predicting the responsiveness of soil biodiversity to deforestation: a cross-biome study. Glob Chang Biol 20:2983–2994. https://doi.org/10.1111/gcb.12565 [DOI: 10.1111/gcb.12565]
  40. Adam E, Bernhart M, Müller H, Winkler J, Beg G (2018) The Cucurbita pepo seed microbiome: genotype-specific composition and implications for breeding. Plant Soil 422:35–49. https://doi.org/10.1007/s11104-016-3113-9 [DOI: 10.1007/s11104-016-3113-9]
  41. Zhou X, Wu F (2018) Vanillic acid changed cucumber (Cucumis sativus L.) seedling rhizosphere total bacterial, Pseudomonas and Bacillus spp. communities. Sci Rep 8:4929. https://doi.org/10.1038/s41598-018-23406-2 [DOI: 10.1038/s41598-018-23406-2]
  42. Bowen A, Fry A, Richards G, Beauchat L (2006) Infections associated with cantaloupe consumption: a public health concern. Epidemiol Infect 134:675–685. https://doi.org/10.1017/S0950268805005480 [DOI: 10.1017/S0950268805005480]
  43. Berg G, Erlacher A, Smalla K, Krause R (2014) Vegetable microbiomes: is there a connection among opportunistic infections, human health and our ‘gut feeling’. Microb Biotechnol 7:487–495. https://doi.org/10.1111/1751-7915.12159 [DOI: 10.1111/1751-7915.12159]
  44. Vivant AL, Garmyn D, Pivetau P (2013) Listeria monocytogenes, a down-to-earth pathogen. Front Cell Infect Microbiol 3:97. https://doi.org/10.3389/fcimb.2013.00087 [DOI: 10.3389/fcimb.2013.00087]
  45. Pérez-Garza J, García S, Heredia N (2017) Removal of Escherichia coli and Enterococcus faecalis after hand washing with antimicrobial and nonantimicrobial soap and persistence of these bacteria in rinsates. J Food Prot 80:1670–1675. https://doi.org/10.4315/0362-028X.JFP-17-088 [DOI: 10.4315/0362-028X.JFP-17-088]
  46. der Wolf J, de Boer SH (2014) Phytopathogenic bacteria. In: Lugtenberg B (ed) Principles of plant-microbe interaction: microbes for sustainable agriculture. Springer, Leiden, pp 65–77
  47. Turnet TR, James EK, Poole PS (2013) The plant microbiome. Genome Biol 14:209. https://doi.org/10.1186/gb-2013-14-6-209 [DOI: 10.1186/gb-2013-14-6-209]
  48. Kumagai LB, Woods PW, Walcott R, Moua X (2014) First report of bacterial fruit blotch on melon caused by Acidovorax citrulli in California. Plant Dis 98:1423–1423. https://doi.org/10.1094/PDIS-03-14-0286-PDN [DOI: 10.1094/PDIS-03-14-0286-PDN]

Grants

  1. A1-S-250/Consejo Nacional de Ciencia y Tecnología
  2. 2018-07410, 2019-67017-29642/National Institute of Food and Agriculture
  3. HHSF223201710406P/U.S. Food and Drug Administration

MeSH Term

Bacteria
Cucurbitaceae
Genes, rRNA
RNA, Ribosomal, 16S
Salmonella

Chemicals

RNA, Ribosomal, 16S
Journal Article
Article has an altmetric score of 2

Word Cloud

Created with Highcharts 10.0.00cantaloupemicrobialfarmsdiversityOTUsCantaloupenumberproductioninformationpopulationssoilanalysissamplesabundant<1BacterialSequencingmelonsresponsibleincreasingfoodbornediseaseoutbreaksmaybecomecontaminatedpathogensHoweverlittleavailablefarmenvironmentpurposeworkcharacterizebacterialcommunitiespresentFruitharvesterhandrinsatescollectedtwoMexicanvisitedthreetimesMicrobiomeperformedsequencing16sRNAanalyzedusingqiime2softwareCorrelationsdeterminedsampletypeαβidentified2777sequencesacrosshighestuniquespecies1301329112205hands67151similarCollectivelyProteobacteriaphyla4295%followedFirmicutes1-47%Actinobacteria23%Bacteroidetes48%generaAcinetobacter20-58%Pseudomonas145%Erwinia13%Exiguobacterium63%GenerapotentialpathogenicincludedBacillus4%Salmonella85%Escherichia-Shigella38%Staphylococcus32%Listeria29%Clostridium28%Cronobacter27%foundlowerfrequenciesstudyprovidesmicrobiomecaninformfutureresearchcriticalfoodsafetyissuesantimicrobialresistancevirulencegenomicepidemiologyAnalysisCommunities16SrRNAGeneMelon-ProducingAgro-environment16sRNApopulation

Similar Articles

Cited By (3)