Application of metagenomics in bacterial resistance in cattle production

PDF (English)
Δημοσιευμένα: May 15, 2026
DOI: https://doi.org/10.12681/jhvms.41197
X Zhang
Inner Mongolia Minzu University, College of Animal Science and Technology, Tongliao 028000, Inner Mongolia, China.
J Li
Tongliao Kulun Banner Animal Disease Prevention and Control Center, Tongliao 028000, Inner Mongolia, China
Y Chen
Inner Mongolia Tongliao Agricultural and Animal Husbandry Development Centre, Tongliao 028042, China
W Jia
Tongliao Academy of Agricultural and Animal Husbandry Sciences, Tongliao 028000, Inner Mongolia, China
Z Jia
Inner Mongolia Minzu University, College of Animal Science and Technology, Tongliao 028000, Inner Mongolia, China
J Cui
Inner Mongolia Minzu University, College of Animal Science and Technology, Tongliao 028000, Inner Mongolia, China
Y Zhang
Inner Mongolia Minzu University, College of Animal Science and Technology, Tongliao 028000, Inner Mongolia, China
H Xiong
Inner Mongolia Minzu University, College of Animal Science and Technology, Tongliao 028000, Inner Mongolia, China
X Wang
Inner Mongolia Minzu University, College of Animal Science and Technology, Tongliao 028000, Inner Mongolia, China
Περίληψη

Microorganisms are widely found in nature, mostly in soil and water. For ruminant animals, microorganisms make up a high percentage of their rumen. In recent years, the inappropriate use of antibiotics has led to a gradual increase in the resistance of bacteria commonly found in the bovine digestive tract which can be transmitted between humans, animals, and the environment. With the rapid development of molecular biology technology, Metagenomics technology can be more efficient, fast, and accurate in detecting resistance genes in samples and discovering novel resistance genes, making the study of bovine bacterial resistance more convenient and thorough. This paper mainly reviews bacterial resistance in cattle and the application of Metagenomics technology in this study. It intends to provide a theoretical reference for understanding the clinical application of metagenomics in bovine production to slow the emergence of bacterial resistance.

Λεπτομέρειες άρθρου
  • Ενότητα
  • Review Articles
Creative Commons License

Αυτή η εργασία είναι αδειοδοτημένη υπό το CC Αναφορά Δημιουργού – Μη Εμπορική Χρήση 4.0.

Οι συγγραφείς των άρθρων που δημοσιεύονται στο περιοδικό διατηρούν τα δικαιώματα πνευματικής ιδιοκτησίας επί των άρθρων τους, δίνοντας στο περιοδικό το δικαίωμα της πρώτης δημοσίευσης.

Άρθρα που δημοσιεύονται στο περιοδικό διατίθενται με άδεια Creative Commons 4.0 Non Commercial και σύμφωνα με την άδεια μπορούν να χρησιμοποιούνται ελεύθερα, με αναφορά στο/στη συγγραφέα και στην πρώτη δημοσίευση για μη κερδοσκοπικούς σκοπούς.

Οι συγγραφείς μπορούν να καταθέσουν το άρθρο σε ιδρυματικό ή άλλο αποθετήριο ή/και να το δημοσιεύσουν σε άλλη έκδοση, με υποχρεωτική την αναφορά πρώτης δημοσίευσης στο J Hellenic Vet Med Soc

Οι συγγραφείς ενθαρρύνονται να καταθέσουν σε αποθετήριο ή να δημοσιεύσουν την εργασία τους στο διαδίκτυο πριν ή κατά τη διαδικασία υποβολής και αξιολόγησής της.

Λήψεις
Τα δεδομένα λήψης δεν είναι ακόμη διαθέσιμα.
Αναφορές
Zhu C, Diao Z, Yang Y, Liao J, Wang C, et al. Recent advances
and challenges in metal-based antimicrobial materials: a review
of strategies to combat antibiotic resistance. J Nanobiotechnology.
;9;23(1):193. doi: 10.1186/s12951-025-03249-6.
Okeke IN, de Kraker MEA, Van Boeckel TP, Kumar CK, Schmitt
H, et al. The scope of the antimicrobial resistance challenge.
Lancet. 2024;1;403(10442):2426-2438. doi: 10.1016/S0140-
(24)00876-6.
Goldberg J, Clezy K, Jasovský D, Uyen-Cateriano A. Leaving no
one behind: the need for a truly global response to antimicrobial
resistance. Lancet Microbe. 2022;3(1):e2-e3. doi: 10.1016/S2666-
(21)00303-7.
Ahmadian E, Samiei M, Hasanzadeh A, Kavetskyy T, Jafari S, et
al. Monitoring of drug resistance towards reducing the toxicity
of pharmaceutical compounds: Past, present and future. J Pharm
Biomed Anal. 2020;186:113265. doi: 10.1016/j.jpba.2020.113265.
Rousham EK, Unicomb L, Islam MA. Human, animal and environmental
contributors to antibiotic resistance in low-resource
settings: integrating behavioural, epidemiological and One Health
approaches. Proc Biol Sci. 2018;285(1876):20180332. doi: 10.1098/
rspb.2018.0332.
Ferri M, Ranucci E, Romagnoli P, Giaccone V. Antimicrobial
resistance: A global emerging threat to public health systems.
Crit Rev Food Sci Nutr. 2017;57(13):2857-2876. doi:
1080/10408398.2015.1077192.
Hu HY, Liu HM, Meng L, Dong L, Lan T, Zhen N, et al. Metagenomics
is applied to detect antibiotic resistance genes in microorganisms.
Microbiology. 2019; 46(11): 3110-3123.
References
Rao RT, Madhavan V, Kumar P, Muniraj G, Sivakumar N, et al.
Epidemiology and zoonotic potential of Livestock-associated Staphylococcus
aureus isolated at Tamil Nadu, India. BMC Microbiol.
;23(1):326. doi: 10.1186/s12866-023-03024-3.
Song LL, Zhang LY, Jia WJ, Bai ZH, Liu Y, Chen YJ, et al. Isolation
and identification of a strain of Bacillus cereus of bovine origin and
detection of virulence genes. Acta Agriculturae Boreali-occidentalis
Sinica. 2019; 28(11): 1735-1741.
Jia WJ, Zhang JQ, Zhang LY, He YJ, Chi SS, Wang XL. Isolation
and identification and biological characterization of Staphylococcus
aureus of bovine origin. Chinese Journal of Biologicals. 2022;
(05): 562-566+574. doi:10.3969/j.issn.1004-5503.
Zheng Y, Qiu X, Wang T, Zhang J. The Diagnostic Value of
Metagenomic Next-Generation Sequencing in Lower Respiratory
Tract Infection. Front Cell Infect Microbiol. 2021;9;11:694756.
doi: 10.3389/fcimb.2021.694756.
Billington C, Kingsbury JM, Rivas L. Metagenomics Approaches
for Improving Food Safety: A Review. J Food Prot. 2022;85(3):448-
doi: 10.4315/JFP-21-301.
Sunagawa S, Mende DR, Zeller G, Izquierdo-Carrasco F, Berger
SA, Kultima JR, et al. Metagenomic species profiling using universal
phylogenetic marker genes. Nat Methods. 2013;10(12):1196-9.
doi: 10.1038/nmeth.2693.
Taş N, de Jong AE, Li Y, Trubl G, Xue Y, Dove NC. Metagenomic
tools in microbial ecology research. Curr Opin Biotechnol.
;67:184-191. doi:10.1016/j.copbio.2021.01.019.
Thomas T, Gilbert J, Meyer F. Metagenomics - a guide from
sampling to data analysis. Microb Inform Exp. 2012;2(1):3. doi:
1186/2042-5783-2-3.
Wang Q, Li F, Liang B, Liang Y, Chen S, Mo X, Ju Y, Zhao H, Jia
H, Spector TD, Xie H, Guo R. A metagenome-wide association
study of gut microbiota in asthma in UK adults. BMC Microbiol.
;18(1):114. doi:10.1186/s12866-018-1257-x.
Jünemann S, Kleinbölting N, Jaenicke S, Henke C, Hassa J, Nelkner
J, et al. Bioinformatics for NGS-based metagenomics and the
application to biogas research. J Biotechnol. 2017;261:10-23. doi:
1016/j.jbiotec.2017.08.012.
Xu P, Zhang XF, Zhao ZJ, Ma Y. Advances in wild animal fecal
microbial metagenomics. Chinese Journal of Vector Biology and
Control. 2022; 33(03): 446-452. doi:10.11853/j.issn.1003.8280.
Chang HH, Yang XY, Yu X, Li XQ, Wang GJ, Sun HW. Metabolic
Function analysis of nitrite-oxidizing bacteria based on metagenomics.
Chinese Journal of Environmental Engineering. 2022;16(04):
-1399. doi:10.12030/j.cjee.202104117.
Chen C, Zhou Y, Fu H, Xiong X, Fang S, Jiang H, Wu J, Yang H,
Gao J, Huang L. Expanded catalog of microbial genes and metagenome-
assembled genomes from the pig gut microbiome. Nat Commun.
;17;12(1):1106. doi: 10.1038/s41467-021-21295-0.
Schmieder R, Edwards R. Insights into antibiotic resistance through
metagenomic approaches. Future Microbiol. 2012;7(1):73-89. doi:
2217/fmb.11.135.
Guo KX, Wang XR, Zhao Y, Peng Z, Cui LQ, Fen JW, et al.
Research progress in monitoring and early warning of antibiotic
resistance of animal-derived bacteria in China [J]. Chinese Journal
of Veterinary Medicine. 2021; 55(04): 79-85.
Mattar C, Edwards S, Baraldi E, Hood J. An overview of the
global antimicrobial resistance research and development hub and
the current landscape. Curr Opin Microbiol. 2020;57:56-61. doi:
1016/j.mib.2020.06.009.
Trotter AJ, Aydin A, Strinden MJ, O’Grady J. Recent and emerging
technologies for the rapid diagnosis of infection and antimicrobial
resistance. Curr Opin Microbiol. 2019;51:39-45. doi: 10.1016/j.
mib.2019.03.001.
Wang H, Ju F. Applications and perspectives of macrogenomics in
environmental microbiome research[J]. Microbiology. 2024;51(06):
-1833.
Xiong W, Wang Y, Sun Y, Ma L, Zeng Q, Jiang X, et al. Antibiotic-
mediated changes in the fecal microbiome of broiler chickens
define the incidence of antibiotic resistance genes. Microbiome.
;6(1):34. doi: 10.1186/s40168-018-0419-2.
Zhang X, Ma CJ, Zhang W, Wu XL, Deng GC. Study on microbial
diversity and drug resistance gene abundance in accumulated feces
of dairy cows. Genomics and Applied Biology. 2022; 41(01): 82-92.
Haley BJ, Kim SW, Salaheen S, Hovingh E, Van Kessel JAS. Differences
in the Microbial Community and Resistome Structures of
Feces from Preweaned Calves and Lactating Dairy Cows in Commercial
Dairy Herds. Foodborne Pathog Dis. 2020;17(8):494-503.
doi: 10.1089/fpd.2019.2768.
Li B, Li X, Wang B, Yan T. A Metagenomic Approach for Characterizing
Antibiotic Resistance Genes in Specific Bacterial Populations:
Demonstration with Escherichia coli in Cattle Manure. Appl Environ
Microbiol. 2022;88(7):e0255421. doi: 10.1128/aem.02554-21.
Weinroth MD, Martin JN, Doster E, Geornaras I, Parker JK, Carlson
CR, et al. Investigation of tylosin in feed of feedlot cattle and
effects on liver abscess prevalence, and fecal and soil microbiomes
and resistomes1. J Anim Sci. 2019;97(11):4567-4578. doi: 10.1093/
jas/skz306.
Kim I, Kang K, Song Y, Kim TJ. Application of Artificial Intelligence
in Pathology: Trends and Challenges. Diagnostics (Basel).
;12(11):2794. doi:10.3390/diagnostics12112794.
Li Y, Cui X, Yang X, Liu G, Zhang J. Artificial intelligence in
predicting pathogenic microorganisms’ antimicrobial resistance:
challenges, progress, and prospects. Front Cell Infect Microbiol.
;14:1482186. doi: 10.3389/fcimb.2024.1482186.
Freeman CN, Herman EK, Abi Younes J, Ramsay DE, Erikson
N, Stothard P, et al. Evaluating the potential of third generation
metagenomic sequencing for the detection of BRD pathogens and
genetic determinants of antimicrobial resistance in chronically ill
feedlot cattle. BMC Vet Res. 2022;18(1):211. doi: 10.1186/s12917-
-03269-6.
Li B, Li X, Yan T. A Quantitative Metagenomic Sequencing Approach
for High-Throughput Gene Quantification and Demonstration
with Antibiotic Resistance Genes. Appl Environ Microbiol.
;87(16):e0087121. doi: 10.1128/AEM.00871-21.
Miller E, Vikram A, Agga GE, Arthur TM, Schmidt JW. Effects of
In-Feed Chlortetracycline Prophylaxis in Beef Cattle on Antimicrobial
Resistance Genes. Foodborne Pathog Dis. 2018 ;15(11):689-
doi: 10.1089/fpd.2018.2475.
Lim SK, Kim D, Moon DC, Cho Y, Rho M. Antibiotic resistomes
discovered in the gut microbiomes of Korean swine and cattle.
Gigascience. 2020;9(5):giaa043. doi: 10.1093/gigascience/giaa043.
Bryan A, Shapir N, Sadowsky MJ. Frequency and distribution of
tetracycline resistance genes in genetically diverse, nonselected,
and nonclinical Escherichia coli strains isolated from diverse human
and animal sources. Appl Environ Microbiol. 2004;70(4):2503-7.
doi: 10.1128/AEM.70.4.2503-2507.2004.
Zaheer R, Lakin SM, Polo RO, Cook SR, Larney FJ, Morley PS,
et al. Comparative diversity of microbiomes and Resistomes in
beef feedlots, downstream environments and urban sewage influent.
BMC Microbiol. 2019;19(1):197. doi: 10.1186/s12866-019-1548-x.
He J, Hai L, Siren DL, Ming L, Yi L, Jiri MG. Macrogenomics
in mammalian gut microorganisms. China Animal Husbandry &
Veterinary Medicine. 2018; 45(12): 3438-3446.
Zhu Z. Analysis of drug resistance genes in bovine intestinal flora
and isolation, typing and drug resistance of Shigella. (2018). Chinese
Academy of Agricultural Sciences.
Joshi S, Shrestha L, Bisht N, Wu N, Ismail M, Dorji T, Dangol G,
Long R. Ethnic and Cultural Diversity amongst Yak Herding Communities
in the Asian Highlands. Sustainability. 2020; 12(3):957.
Zhuang Y, Guo W, Cui K, Tu Y, Diao Q, Zhang N, Bi Y, Ma T.
Altered microbiota, antimicrobial resistance genes, and functional
enzyme profiles in the rumen of yak calves fed with milk replacer.
Microbiol Spectr. 2024; 12(1):e0131423.
Liang C, Wang L, Wu X, Wang K, Ding X, Wang M, et al. Genome-
wide Association Study Identifies Loci for the Polled Phenotype
in Yak. PLoS One. 2016;11(7):e0158642. doi: 10.1371/journal.
pone.0158642.
Ma J, Zhu Y, Wang Z, Yu X, Hu R, Wang X, Cao G, Zou H,
Shah AM, Peng Q, Xue B, Wang L, Zhao S, Kong X. Comparing
the Bacterial Community in the Gastrointestinal Tracts Between
Growth-Retarded and Normal Yaks on the Qinghai-Tibetan Plateau.
Front Microbiol. 2020; 11:600516.
Wang W, Wei X, Wu L, Shang X, Cheng F, Li B, et al. Correction:
The occurrence of antibiotic resistance genes in the microbiota
of yak, beef and dairy cattle characterized by a metagenomic approach.
J Antibiot (Tokyo). 2023;76(3):190. doi: 10.1038/s41429-
-00590-y.
Keijser BJF, Agamennone V, van den Broek TJ, Caspers M, van de
Braak A, Bomers R, et al. Dose-dependent impact of oxytetracycline
on the veal calf microbiome and resistome. BMC Genomics.
;20(1):65. doi: 10.1186/s12864-018-5419-x.
Freeman CN, Herman EK, Abi Younes J, Ramsay DE, Erikson N,
Stothard P, Links MG, Otto SJG, Waldner C. Evaluating the potential
of third generation metagenomic sequencing for the detection of
BRD pathogens and genetic determinants of antimicrobial resistance
in chronically ill feedlot cattle. BMC Vet Res. 2022;18(1):211. doi:
1186/s12917-022-03269-6.
Huws SA, Creevey CJ, Oyama LB, Mizrahi I, Denman SE, Popova
M, et al. Addressing Global Ruminant Agricultural Challenges
Through Understanding the Rumen Microbiome: Past,
Present, and Future. Front Microbiol. 2018;9:2161. doi: 10.3389/
fmicb.2018.02161.
Miao Y, Zhu QH, Chen L, Lan SJ, Yu CL, Zhang L, et al. Progress of
research on the application of macrogenomics in cattle production.
Chinese Journal of Animal Science. 2023;59(05): 11-16.
Jing R, Yan Y. Metagenomic analysis reveals antibiotic resistance
genes in the bovine rumen. Microb Pathog. 2020;149:104350. doi:
1016/j.micpath.2020.104350.
Xue MY, Xie YY, Zhong YF, Liu JX, Guan LL, Sun HZ. Ruminal
resistome of dairy cattle is individualized and the resistotypes are
associated with milking traits. Anim Microbiome. 2021;3(1):18.
doi: 10.1186/s42523-021-00081-9.
Sun HZ, Peng KL, Xue MY, Liu JX. Metagenomics analysis revealed
the distinctive ruminal microbiome and resistive profiles
in dairy buffaloes. Anim Microbiome. 2021;3(1):44. doi: 10.1186/
s42523-021-00103-6.
Wylie KM, Wylie TN, Buller R, Herter B, Cannella MT, Storch
GA. Detection of Viruses in Clinical Samples by Use of Metagenomic
Sequencing and Targeted Sequence Capture. J Clin Microbiol.
;56(12):e01123-18. doi: 10.1128/JCM.01123-18.
Fadiji AE, Babalola OO. Metagenomics methods for the study
of plant-associated microbial communities: A review. J Microbiol
Methods. 2020;170:105860. doi: 10.1016/j.mimet.2020.105860.
Wang W, Wei Z, Li Z, Ren J, Song Y, Xu J, Liu A, Li X, Li M, Fan
H, Jin L, Niyazbekova Z, Wang W, Gao Y, Jiang Y, Yao J, Li F, Wu
S, Wang Y. Integrating genome- and transcriptome-wide association
studies to uncover the host-microbiome interactions in bovine rumen
methanogenesis. Imeta. 2024;3(5):e234. doi: 10.1002/imt2.234.
Τα περισσότερο διαβασμένα άρθρα του ίδιου συγγραφέα(s)