Abstract
The safety of meat from a microbiological standpoint is of paramount concern to public health, given the potential for bacterial contaminants to grow and persist during processing and storage. To address this issue, a culture-independent approach targeting the V3-V4 region of the 16S rRNA gene was utilized to investigate the inherent bacterial communities present in 10 chicken meat samples obtained from retail markets. Amplicons were sequenced using the Illumina MiSeq platform, and unique amplicon sequence variants (ASVs) were identified using the DADA2 pipeline. Results indicated the presence of 5 phyla, 7 classes, 16 orders, 33 families, 59 genera, and 273 unique ASVs. The dominant families were Flavobacteriaceae, Moraxellaceae, Enterobacteriaceae, Wohlfahrtiimonadaceae, Morganellaceae, and Pseudomonadaceae, comprising 27.03, 22.04, 15.67, 9.40, 7.92, and 5.02% of the identified families, respectively. Functional analysis using PICRUSt showed a diverse range of functional pathways. These findings have significant implications for policymaking regarding food safety and public health. Regular monitoring of bacterial communities in meat products is crucial to ensure their safety for consumption. This study demonstrates the utility of culture-independent approaches in characterizing microbial communities, which can provide valuable information for ensuring food safety and safeguarding public health.
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References
Clayton E, WORLD ZW-CF 2020 U (2020) Trends and opportunities in the global plant-based meat industry. Cereal Foods World. https://doi.org/10.1094/cfw-65-4-0041
Henchion M, Moloney AP, Hyland J et al (2021) Review: trends for meat, milk and egg consumption for the next decades and the role played by livestock systems in the global production of proteins. Animal 15:100287
Giromini C, Givens DI (2022) Benefits and risks associated with meat consumption during key life processes and in relation to the risk of chronic diseases. Foods 11:2063
Zhao S, Wang L, Hu W, Zheng Y (2022) Meet the meatless: demand for new generation plant-based meat alternatives. Appl Econ Perspect Policy. https://doi.org/10.1002/aepp.13232
Cho WH, Choi JS (2021) Sensory quality evaluation of superheated steam-treated chicken leg and breast meats with a combination of marination and hot smoking. Foods. https://doi.org/10.3390/foods10081924
Huang Y, Cao D, Chen Z et al (2021) Red and processed meat consumption and cancer outcomes: umbrella review. Food Chem 356:129697
Grashorn MA (2010) Research into poultry meat quality. Br Poult Sci 51:60–67. https://doi.org/10.1080/00071668.2010.506761
Pires SM, Devleesschauwer B (2021) Estimates of global disease burden associated with foodborne pathogens. In: Foodborne infections and intoxications. Academic Press, Cambridge, MA, USA. pp 3–17. https://doi.org/10.1016/B978-0-12-819519-2.00020-7
Bhaskar S V. (2017) Foodborne diseases-disease burden. In: Food Safety in the 21st Century: Public health perspective. Academic Press, Cambridge, MA, USA. pp 1–10. https://doi.org/10.1016/B978-0-12-801773-9.00001-7
Rouger A, Tresse O, Zagorec M (2017) Bacterial contaminants of poultry meat: sources, species, and dynamics. Microorganisms 5:50
Chai SJ, Cole D, Nisler A, Mahon BE (2017) Poultry: the most common food in outbreaks with known pathogens, United States, 1998–2012. Epidemiol Infect 145:316–325. https://doi.org/10.1017/S0950268816002375
Praveen PK, Debnath C, Shekhar S et al (2016) Incidence of Aeromonas spp. infection in fish and chicken meat and its related public health hazards: a review. Vet World 9:6–11
Allard MW, Bell R, Ferreira CM et al (2018) Genomics of foodborne pathogens for microbial food safety. Curr Opin Biotechnol 49:224–229
Goodwin S, McPherson JD, McCombie WR (2016) Coming of age: ten years of next-generation sequencing technologies. Nat Rev Genet 17:333–351
Quainoo S, Coolen JPM, van Hijum SAFT et al (2017) Whole-genome sequencing of bacterial pathogens: the future of nosocomial outbreak analysis. Clin Microbiol Rev 30:1015–1063
Jagadeesan B, Gerner-Smidt P, Allard MW et al (2019) The use of next generation sequencing for improving food safety: translation into practice. Food Microbiol 79:96–115. https://doi.org/10.1016/J.FM.2018.11.005
Stanley D, Hughes RJ, Moore RJ (2014) Microbiota of the chicken gastrointestinal tract: influence on health, productivity and disease. Appl Microbiol Biotechnol 98:4301–4310
Borda-Molina D, Seifert J, Camarinha-Silva A (2018) Current perspectives of the chicken gastrointestinal tract and its microbiome. Comput Struct Biotechnol J 16:131–139
Klindworth A, Pruesse E, Schweer T et al (2013) Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. https://doi.org/10.1093/nar/gks808
Ewels P, Magnusson M, Lundin S, Käller M (2016) MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32:3047–3048. https://doi.org/10.1093/bioinformatics/btw354
Chen S, Zhou Y, Chen Y, Gu J (2018) Fastp: An ultra-fast all-in-one FASTQ preprocessor. In: Bioinformatics. Oxford Academic, Oxford, United Kingdom. pp i884–i890. https://doi.org/10.1093/bioinformatics/bty560
Callahan BJ, McMurdie PJ, Rosen MJ et al (2016) DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods 13:581–583. https://doi.org/10.1038/nmeth.3869
McMurdie PJ, Holmes S (2013) Phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One. https://doi.org/10.1371/journal.pone.0061217
Endicott-Yazdani TR, Dhiman N, Benavides R, Spak CW (2015) Myroides Odoratimimus bacteremia in a diabetic patient. Baylor Univ Med Cent Proc 28:342–343. https://doi.org/10.1080/08998280.2015.11929268
Abd El-Aziz DM (2015) Detection of Pseudomonas spp. in chicken and fish sold in markets of Assiut City. Egypt J Food Qual Hazards Control 2:86–89
İnat G, Sırıken B, Başkan C et al (2021) Quorum sensing systems and related virulence factors in Pseudomonas aeruginosa isolated from chicken meat and ground beef. Sci Rep 11:1–9. https://doi.org/10.1038/s41598-021-94906-x
Aras Z, Hadimli HH, Hadimli HH (2014) Detection and molecular typing of Clostridium perfringens isolates from beef, chicken and turkey meats. Elsevier. https://doi.org/10.1016/j.anaerobe.2014.11.004
Cooper KK, Bueschel DM, Songer JG (2013) Presence of Clostridium perfringens in retail chicken livers. Anaerobe 21:67–68. https://doi.org/10.1016/j.anaerobe.2013.03.013
Younis G, Awad A, El-Gamal A, Hosni R (2016) Virulence properties and antimicrobial susceptibility profiles of Klebsiella species recovered from clinically diseased broiler chicken. Adv Anim Vet Sci 4:536–542. https://doi.org/10.14737/JOURNAL.AAVS/2016/4.10.536.542
Meng J, Huang X, Song L et al (2019) Effect of storage temperature on bacterial diversity in chicken skin. J Appl Microbiol 126:854–863. https://doi.org/10.1111/jam.14183
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The authors are thankful to the Principal, College of Veterinary Science and Animal Husbandry, Kamdhenu University, Anand for providing all the necessary facilities and consumables, Department of Animal Biotechnology, Anand, for providing the platform to carry out the work.
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Anjaria, P., Koringa, P., Bhavsar, P. et al. Metagenomic Analysis Reveals the Complex Microbial Landscape of Market Chicken Meat. Indian J Microbiol (2024). https://doi.org/10.1007/s12088-024-01249-y
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DOI: https://doi.org/10.1007/s12088-024-01249-y