Environmental Science and Pollution Research

, Volume 26, Issue 9, pp 8665–8674 | Cite as

Detecting antibiotic resistance genes and human potential pathogenic Bacteria in fishmeal by culture-independent method

  • Ying Han
  • Jing WangEmail author
  • Zelong Zhao
  • Jingwen Chen
  • Hong Lu
  • Guangfei Liu
Research Article


Fishmeal is a fundamental ingredient of feedstuffs and is used globally in aquaculture. However, there are few data on the antibiotic resistance genes (ARGs) and human pathogenic bacteria in fishmeal and little understanding of the potential risks of fishmeal application in mariculture systems. Here, we investigated the high-throughput profiles of ARGs and human potential pathogenic bacteria (HPPB) in representative fishmeals (n = 5) and the potential impact of fishmeal on mariculture sediments. ARGs were quantified with microbial DNA quantitative PCR arrays and HPPB were analyzed with Illumina sequencing of 16S rRNA genes. The impact of the fishmeal on the aquaculture sediments was assessed in a microcosm study. Twenty-four unique ARGs (3–14 per sample) and 25 HPPB species were detected in the fishmeal samples. The most prevalent ARGs were fluoroquinolone resistance genes. The overall abundance of HPPB was 5.0–25.5%, and the HPPB species were dominated by Vibrio parahaemolyticus, Clostridium novyi, and Escherichia coli. In the mariculture microcosm sediment, fishmeal significantly increased the normalized abundance of the class I integrase gene (25.4-fold), which plays an important role in the dissemination of ARGs. Dosing with fishmeal also contributed to increases in a resident sulfanilamide resistance gene (sulI gene) and the emergence of a macrolide resistance gene (ermB gene) in the sediment. These findings demonstrated that fishmeal itself is an underestimated reservoir and source of ARGs and HPPBs, and that the application of fishmeal facilitates the dissemination of ARGs in aquaculture sediments. Our results extend our knowledge of the ARGs and HPPB within fishmeal and may provide a feasible and effective approach to the detection of ARGs and HPPB in fishmeal during food safety inspection.

Graphical abstract


Fishmeal Antibiotic resistance genes (ARGs) Human potential pathogenic bacteria (HPPB) Mariculture microcosm 



The authors would like to thank Professor Lin Cai at the Hong Kong University of Science and Technology, China, for providing the human pathogenic bacteria 16S rRNA gene database.


This work has been supported by the National Basic Research Program of China (2013CB430403).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

11356_2019_4303_MOESM1_ESM.docx (131 kb)
ESM 1 (DOCX 130 kb)


  1. (2002) Aerobic and anaerobic transformation in aquatic sediment systems. In Guidelines for testing of chemicals no. 308; Organisation for Economic Cooperation and Development: ParisGoogle Scholar
  2. Baker-Austin C, Wright MS, Stepanauskas R, McArthur JV (2006) Co-selection of antibiotic and metal resistance. Trends Microbiol 14:176–182CrossRefGoogle Scholar
  3. Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for illumina sequence data. Bioinformatics 30:2114–2120CrossRefGoogle Scholar
  4. Bouwman L, Beusen A, Glibert PM, Overbeek C, Pawlowski M, Herrera J, Mulsow S, Yu RC, Zhou MJ (2013) Mariculture: significant and expanding cause of coastal nutrient enrichment. Environ Res Lett 8:4CrossRefGoogle Scholar
  5. Cai L, Zhang T (2013) Detecting human bacterial pathogens in wastewater treatment plants by a high-throughput shotgun sequencing technique. Environ Sci Technol 47:5433–5441CrossRefGoogle Scholar
  6. Cao L, Naylor R, Henriksson P, Leadbitter D, Metian M, Troell M, Zhang WB (2015) China's aquaculture and the world’s wild fisheries. Science 347:133–135CrossRefGoogle Scholar
  7. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Peña AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R (2010) Qiime allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336CrossRefGoogle Scholar
  8. Chen LH, Yang J, Yu J, Ya ZJ, Sun LL, Shen Y et al (2005) Vfdb: a reference database for bacterial virulence factors. Nucleic Acids Res 33:D325–D328CrossRefGoogle Scholar
  9. De Santis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K et al (2006) Greengenes, a chimera-checked 16s rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72:5069–5072CrossRefGoogle Scholar
  10. Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26(19):2460–2461CrossRefGoogle Scholar
  11. FAO. (Food and Agriculture Organization of the United Unions) (2014) Global aquaculture production 1950-2014. Available: http://www.Fao.Org/fishery/statistics/global-aquaculture-production/query/en[accessed 4 Mar 2016]
  12. Fischbach MA, Walsh CT (2009) Antibiotics for emerging pathogens. Science 325:1089–1093CrossRefGoogle Scholar
  13. Gao P, Mao D, Luo Y, Wang L, Xu B, Xu L (2012) Occurrence of sulfonamide and tetracycline-resistant bacteria and resistance genes in aquaculture environment. Water Res 46:2355–2364CrossRefGoogle Scholar
  14. Han Y, Wang J, Zhao Z, Chen J, Lu H, Liu G (2017) Fishmeal application induces antibiotic resistance gene propagation in mariculture sediment. Environ Sci Technol 51(18):10850–10860CrossRefGoogle Scholar
  15. Hofacre CL, White DG, Maurer JJ, Morales C, Lobsinger C, Hudson C (2001) Characterization of antibiotic-resistant bacteria in rendered animal products. Avian Dis 45:953–961CrossRefGoogle Scholar
  16. Hsieh YC, Poole TL, Runyon M, Hume M, Herrman TJ (2016) Prevalence of nontyphoidal salmonella and salmonella strains with conjugative antimicrobial-resistant serovars contaminating animal feed in Texas. J Food Prot 79:194–204CrossRefGoogle Scholar
  17. Huang Y, Zhang L, Tiu L, Wang HH (2015) Characterization of antibiotic resistance in commensal bacteria from an aquaculture ecosystem. Front Microbiol 6:7Google Scholar
  18. International fish meal and fish oil organization (IFFO) (2015) IFFO response to the recent paper on China’s aquaculture and the world’s wild fisheries. Available: Accessed Dec 2017
  19. Kang Y, Gu X, Hao Y, Hu J (2016) Autoclave treatment of pig manure does not reduce the risk of transmission and transfer of tetracycline resistance genes in soil: successive determinations with soil column experiments. Environ Sci Pollut Res 23:4551–4560CrossRefGoogle Scholar
  20. Klappenbach JA, Saxman PR, Cole JR, Schmidt TM (2001) rrndb: the ribosomal RNA operon copy number database. Nucleic Acids Res 29:181–184CrossRefGoogle Scholar
  21. Knapp CW, Dolfing J, Ehlert PAI, Graham DW (2010) Evidence of increasing antibiotic resistance gene abundances in archived soils since 1940. Environ Sci Technol 44:580–587CrossRefGoogle Scholar
  22. Kumaraswamy R, Amha YM, Anwar MZ, Henschel A, Rodriguez J, Ahmad F (2014) Molecular analysis for screening human bacterial pathogens in municipal wastewater treatment and reuse. Environ Sci Technol 48:11610–11619CrossRefGoogle Scholar
  23. Laxminarayan R, Duse A, Wattal C, Zaidi AKM, Wertheim HFL, Sumpradit N, Vlieghe E, Hara GL, Gould IM, Goossens H, Greko C, So AD, Bigdeli M, Tomson G, Woodhouse W, Ombaka E, Peralta AQ, Qamar FN, Mir F, Kariuki S, Bhutta ZA, Coates A, Bergstrom R, Wright GD, Brown ED, Cars O (2013) Antibiotic resistance-the need for global solutions. Lancet Infect Dis 13:1057–1098CrossRefGoogle Scholar
  24. Levy SB, Marshall B (2004) Antibacterial resistance worldwide: causes, challenges and responses. Nat Med 10:S122–S129CrossRefGoogle Scholar
  25. Looft T, Johnson TA, Allen HK, Bayles DO, Alt DP, Stedtfeld RD, Sul WJ, Stedtfeld TM, Chai B, Cole JR, Hashsham SA, Tiedje JM, Stanton TB (2012) In-feed antibiotic effects on the swine intestinal microbiome. Proc Natl Acad Sci U S A 109:1691–1696CrossRefGoogle Scholar
  26. Luo Y, Mao DQ, Rysz M, Zhou DX, Zhang HJ, Xu L et al (2010) Trends in antibiotic resistance genes occurrence in the Haihe river, China. Environ Sci Technol 44:7220–7225CrossRefGoogle Scholar
  27. Magoc T, Salzberg SL (2011) Flash: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27:2957–2963CrossRefGoogle Scholar
  28. Malorny B, Huehn S, Dieckmann R, Kramer N, Helmuth R (2009) Polymerase chain reaction for the rapid detection and serovar identification of salmonella in food and feeding stuff. Food Anal Methods 2:81–95CrossRefGoogle Scholar
  29. Meeker DL (2009) North American rendering - processing high quality protein and fats for feed. Rev Bras Zootecn 38:432–U443CrossRefGoogle Scholar
  30. Muziasari WI, Managaki S, Parnanen K, Karkman A, Lyra C, Tamminen M et al (2014) Sulphonamide and trimethoprim resistance genes persist in sediments at Baltic Sea aquaculture farms but are not detected in the surrounding environment. PLoS One 9:e92702CrossRefGoogle Scholar
  31. Naylor RL, Goldburg RJ, Primavera JH, Kautsky N, Beveridge MCM, Clay J, Folke C, Lubchenco J, Mooney H, Troell M (2000) Effect of aquaculture on world fish supplies. Nature 405:1017–1024CrossRefGoogle Scholar
  32. Nygaard H, Hostmark O (2008) Microbial inactivation during superheated steam drying of fish meal. Dry Technol 26:222–230CrossRefGoogle Scholar
  33. Pruden A, Pei R, Storteboom H, Carlson KH (2006) Antibiotic resistance genes as emerging contaminants: studies in northern Colorado. Environ Sci Technol 40:7445–7450CrossRefGoogle Scholar
  34. Pruden A, Arabi M, Storteboom HN (2012) Correlation between upstream human activities and riverine antibiotic resistance genes. Environ Sci Technol 46:11541–11549CrossRefGoogle Scholar
  35. Sapkota AR, Lefferts LY, McKenzie S, Walker P (2007) What do we feed to food-production animals? A review of animal feed ingredients and their potential impacts on human health. Environ Health Perspect 115:663–670CrossRefGoogle Scholar
  36. Segata N et al (2012) Metagenomic microbial community profiling using unique clade-specific marker genes. Nat Methods 9(8):811–814CrossRefGoogle Scholar
  37. Shah SQA, Colquhoun DJ, Nikuli HL, Sorum H (2012) Prevalence of antibiotic resistance genes in the bacterial flora of integrated fish farming environments of Pakistan and Tanzania. Environ Sci Technol 46:8672–8679CrossRefGoogle Scholar
  38. Suzuki MT, Taylor LT, DeLong EF (2000) Quantitative analysis of small-subunit rRNA genes in mixed microbial populations via 5′-nuclease assays. Appl Environ Microbiol 66:4605–4614CrossRefGoogle Scholar
  39. Tamminen M, Karkman A, Lohmus A, Muziasari WI, Takasu H, Wada S et al (2011) Tetracycline resistance genes persist at aquaculture farms in the absence of selection pressure. Environ. Sci. Technol. 45:386–391CrossRefGoogle Scholar
  40. Tamura K, Stecher G, Peterson D, Filipski A, Kumar S (2013) Mega6: molecular evolutionary genetics analysis version 6.0. Mol Biol Evol 30:2725–2729CrossRefGoogle Scholar
  41. Tomova A, Ivanova L, Buschmann AH, Rioseco ML, Kalsi RK, Godfrey HP, Cabello FC (2015) Antimicrobial resistance genes in marine bacteria and human uropathogenic Escherichia coli from a region of intensive aquaculture. Environ Microbiol Rep 7:803–809CrossRefGoogle Scholar
  42. Udikovic-Kolic N, Wichmann F, Broderick NA, Handelsman J (2014) Bloom of resident antibiotic-resistant bacteria in soil following manure fertilization. Proc Natl Acad Sci U S A 111:15202–15207CrossRefGoogle Scholar
  43. Uyaguari MI, Scott GI, Norman RS (2013) Abundance of class 1-3 integrons in South Carolina estuarine ecosystems under high and low levels of anthropogenic influence. Mar Pollut Bull 76:77–84CrossRefGoogle Scholar
  44. Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73:5261–5267CrossRefGoogle Scholar
  45. Welch TJ, Fricke WF, McDermott PF, White DG, Rosso ML, Rasko DA, Mammel MK, Eppinger M, Rosovitz MJ, Wagner D, Rahalison L, LeClerc JE, Hinshaw JM, Lindler LE, Cebula TA, Carniel E, Ravel J (2007) Multiple antimicrobial resistance in plague: an emerging public health risk. PLoS One 2:e309CrossRefGoogle Scholar
  46. Wu B, Song JM, Li XG (2014) Evaluation of potential relationships between benthic community structure and toxic metals in Laizhou bay. Mar Pollut Bull 87:247–256CrossRefGoogle Scholar
  47. Yang J, Wang C, Shu C, Liu L, Geng J, Hu S, Feng J (2013) Marine sediment bacteria harbor antibiotic resistance genes highly similar to those found in human pathogens. Microb Ecol 65(4):975–981CrossRefGoogle Scholar
  48. Yang J, Wang C, Wu J, Liu L, Zhang G, Feng J (2014) Characterization of a multiresistant mosaic plasmid from a fish farm Sediment Exiguobacterium sp isolate reveals aggregation of functional clinic-associated antibiotic resistance genes. Appl Environ Microbiol 80:1482–1488CrossRefGoogle Scholar
  49. Ye L, Zhang L, Li X, Shi L, Huang Y, Wang HH (2013) Antibiotic-resistant bacteria associated with retail aquaculture products from Guangzhou, China. J Food Prot 76:295–301CrossRefGoogle Scholar
  50. Zhang T, Fang HHP (2006) Applications of real-time polymerase chain reaction for quantification of microorganisms in environmental samples. Appl Microbiol Biotechnol 70:281–289CrossRefGoogle Scholar
  51. Zhang XX, Zhang T, Zhang M, Fang HHP, Cheng SP (2009) Characterization and quantification of class 1 integrons and associated gene cassettes in sewage treatment plants. Appl Microbiol Biotechnol 82:1169–1177CrossRefGoogle Scholar
  52. Zhao Z, Wang J, Han Y, Chen J, Liu G, Lu H, Yan B, Chen S (2017) Nutrients, heavy metals and microbial communities co-driven distribution of antibiotic resistance genes in adjacent environment of mariculture. Environ Pollut 220:909–918CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Key Laboratory of Industrial Ecology and Environmental Engineering, Ministry of Education, School of Environmental Science and TechnologyDalian University of TechnologyDalianPeople’s Republic of China

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