Mastitis is one of the costliest diseases in the dairy industry due to discarded milk and expense of treatments, and may lead to culling of cows (Gussmann et al., Reference Gussmann, Denwood, Kirkeby, Farre and Halasa2019). Streptococcus agalactiae is one of the major mastitis with a prevalence at herd level as high as 92% in China (Bi et al., Reference Bi, Wang, Qin, Vallverdú, García, Sun, Li and Cao2016).
Multilocus sequence typing (MLST) is a genotype method for characterizing and distinguishing specific clones among Strep. agalactiae. It is an unambiguous sequence-based and reliable typing tool, allowing comparison of the gene distribution of different isolates collected from all geographic areas and further investigation of the population structure (Yang et al., Reference Yang, Liu, Ding, Yi, Ma, Fan and Lu2013). The major sequence type (ST) of Strep. agalactiae varies in different regions: ST67 in British dairy herds and ST1 in Danish, Finnish, and Swedish dairy herds (Reyes et al., Reference Reyes, Chaffer, Rodriguez-Lecompte, Sánchez, Zadoks, Robinson, Cardona, Ramírez and Keefe2017). However, the authors believe that the studies are deficient for investigating the MLST of Strep. agalactiae in North China, which is the main milk production region in China.
Antimicrobials are still the major option for mastitis treatment (Keefe, Reference Keefe2012). However, the abusive use of antimicrobials increases the risks of antimicrobial resistance (AMR) in bacteria, which is of public health concern worldwide (Levy and Marshall, Reference Levy and Marshall2004). Investigation of the prevalence, predominant STs and the antimicrobial resistance profiles can contribute to treatment decisions and optimize Strep. agalactiae control programs to minimize use of antimicrobials (Kaczorek et al., Reference Kaczorek, Małaczewska, Wójcik, Rękawek and Siwicki2017). Thus, the objectives of this study were: (a) to study the prevalence of Strep. agalactiae and characterize the molecular type, (b) to investigate the antibiotic resistance and (c) determine the association between ST and antimicrobial resistance patterns of Strep. agalactiae.
Material and methods
Strep. agalactiae isolation
Strep. agalactiae were isolated from cows with clinical mastitis from large dairy farms (>500 cows) in China: Milk samples were collected into sterile tubes after teat disenfection and discarding the first three strippings. The volume of 10 μl of milk from each sample was plated onto a blood agar plate (Luqiao, Beijing, China), and plates were incubated at 37 °C for 24 to 48 h. Suspected Streptococcus spp. were identified as catalase-negative and Gram-positive cocci. Streptococci were differentiated as esculin-positive (Strep. uberis and other esculin-positive cocci) or esculin-negative cocci (Strep. dysgalactiae and Strep. agalactiae). Christie, Atkins and Munch-Petersen tests (CAMP) (Tianhe, Hangzhou, China) were used to distinguish Strep. dysgalactiae (CAMP-negative) from Strep. agalactiae (CAMP-positive). Finally, the putative isolates were identified using 16S rRNA amplification.
Multilocus sequence typing (MLST)
The seven housekeeping genes (adh, pheS, atr, glnA, sdhA, glcK and tkt) were amplified by PCR. For each isolate, the allele number and sequence types (STs) were defined by analysis of the alleles sequence referred to the Strep. agalactiae MLST reference database (http://pubmlst.org/sagalactiae/). The allele sequences or previously undescribed ST were assigned new numbers and the data were deposited in the MLST database. CC analysis and phylogenetic analysis of MLST data was performed using Phyloviz (version 2.0a, http://www.phyloviz.net/) using eBURST algorithm.
Antimicrobial resistance testing
Antimicrobial resistance testing was conducted using the broth microdilution method according to the Clinical and Laboratory Standards Institute (CLSI, 2020). Strep. pneumonia ATCC 49619 were used as quality control strains. The number of 12 antimicrobials used in practice for bovine mastitis treatment and human medicine (penicillin, cefalexin, ceftiofur, cefquinome, oxacillin, clindamycin, tetracycline, enrofloxacin, amoxicillin/clavulanate, daptomycin, erythromycin, and vancomycin) were selected for antimicrobial resistance testing.
Statistical analysis
In order to make the data representative, n ≥ 10 farms (A, K, and G) and STs (ST103, ST1413, and ST1414) were selected to research the correlation between AMR and farms and STs. A longitudinal comparison between the MIC and ST changes of isolates collected in 2017 (n = 29) and 2019 (n = 53) from farm A in Shandong province was conducted. Kruskal–Wallis and Mann–Whitney U test were performed using SPSS 26.0 (IBM Corp, Armonk, NY).
Results and discussion
Distribution of Strep. agalactiae
A total of 140 Strep. agalactiae isolates were identified from 12 out of 201 farms in 6 provinces from 2017 to 2019. Overall herd prevalence was 18.6% (95% CI 16%_21.6%), the most high prevalence region of Strep. agalactiae was Shandong province (n = 83, prevalence = 19.5%), followed by Tianjin (n = 4, prevalence = 4.3%) and Hebei province (n = 26, prevalence = 3%). (online Supplementary Tables 1 and 2; Supplementary Fig. 1). Only a few samples and isolates were collected in several provinces (Henan, Tianjin, and Heilongjiang), so more samples should be collected from these regions in further research to make the samples more representative. As a contagious mastitis pathogen, Strep. agalactiae can transfect among cows and persist for a long period. Strict biosecurity and sterile standards should be taken to eliminate Strep. agalactiae from herds (Jørgensen et al., Reference Jørgensen, Nordstoga, Sviland, Zadoks, Sølverød, Kvitle and Mørk2016). The high prevalence of Strep. agalactiae was observed in a few herds in the main milk production regions in north China (Herd A in Shandong and herd K in Hebei, online Supplementary Table 2), which indicates the infection of Strep. agalactiae was not under proper control in these herds.
MLST analysis
The MLST analysis showed that two main clonal complexes (CC), CC 103 and CC 67, were present in these herds (online Supplementary Fig. 2). The isolates of CC 103 were predominant, accounting for 97.9% (95% CI 93.89%_99.27%; Supplementary Table 3). This finding is consistent with studies in Denmark (Zadoks et al., Reference Zadoks, Middleton, McDougall, Katholm and Schukken2011) and eastern China (Yang et al., Reference Yang, Liu, Ding, Yi, Ma, Fan and Lu2013). CC 67, including ST 301 and 1422, only accounted for 1.4% of isolates in our study, but was extensively distributed in Europe in mastitis cases (Reyes et al., Reference Reyes, Chaffer, Rodriguez-Lecompte, Sánchez, Zadoks, Robinson, Cardona, Ramírez and Keefe2017), indicating the predominant subgroup in China was CC103. A total of 13 new STs were found in this study, which clarified the prevalence and the predominant STs of Strep. agalactiae in Chinese dairy herds, and is important for tailor-made Strep. agalactiae mastitis control programs (Yang et al., Reference Yang, Liu, Ding, Yi, Ma, Fan and Lu2013).
Figure 1 shows the distribution of STs amongst the 12 farms. Several STs were widely distributed on different farms, and heterogeneous STs were also found within herds in the current study, which agrees with a study on dairy farms in east China (Yang et al., Reference Yang, Liu, Ding, Yi, Ma, Fan and Lu2013). CC67 is considered to be contagious (Jørgensen et al., Reference Jørgensen, Nordstoga, Sviland, Zadoks, Sølverød, Kvitle and Mørk2016), while CC103 is an environmental pathogen (Cobo-Ángel et al., Reference Cobo-Ángel, Jaramillo-Jaramillo, Lasso-Rojas, Aguilar-Marin, Sanchez, Rodriguez-Lecompte, Ceballos-Márquez and Zadoks2018), which indicated parallel transmission routes (cow to cow and environmental reservoir to cow transmission) within herds.
Fig. 1. Sequence types of the 140 Strep. agalactiae isolated from 12 farms in 6 provinces.
Antimicrobial resistance testing
Isolates were mostly sensitive to the tested antimicrobials: penicillin, ceftiofur, amoxi/clav, cefquinome, and vancomycin (100%), followed by cefalexin (97.9%), oxacillin (96.4%), enrofloxacin (95.7%), erythromycin (89.3%), and clindamycin (88.6%). However, only 19.3 and 0.7% of isolates were sensitive to tetracycline and daptomycin, respectively (Table 1). The MIC of the isolates against eight antimicrobials in 2019 was significantly lower than that in 2017 (online Supplementary Table 4). A total of 10 antimicrobials were effective to most of the isolates, and the multi-resistant rate is rare (13.6%), which was lower than the earlier report of Tian et al. (Reference Tian, Zheng, Han, Ho, Wang, Wang, Wang, Li, Liu and Yu2019). The antimicrobial resistance situation was also remarkably improved compared with Gao et al. (Reference Gao, Yu, Luo, He, Hou, Zhang, Li, Su and Han2012). Such an improvement is due to well-organized large dairy farms and the employment of on-farm veterinarians and pharmacists working together to optimize udder health.
Table 1. Antimicrobial resistance profile of the 140 Streptococcus agalactiae isolated from clinical mastitis cases on dairy farms in north China. Minimum concentration of an antimicrobial that inhibited the visible growth of 50% (MIC50) and 90% of microorganisms (MIC90)
MIC, minimum inhibitory concentration.
a Amoxicillin/clavulanate potassium.
The percentage of tetracycline resistance was 80% in our research, which was consistent with Gao et al. (Reference Gao, Yu, Luo, He, Hou, Zhang, Li, Su and Han2012) and Tomazi et al. (Reference Tomazi, de Souza Filho, Heinemann and Dos Santos2018), who reported resistance percentages of 72.5 and 68.6% in China and Brazil, respectively. The low efficacy of tetracycline in mastitis treatment was reported worldwide due to its abuse in treatment and growth promotion (Kaczorek et al., Reference Kaczorek, Małaczewska, Wójcik, Rękawek and Siwicki2017).
A total of 16 isolates exhibited resistance to clindamycin, accounting for 11.4%. The resistant gene of clindamycin was located on a plasmid (Bozdogan et al., Reference Bozdogan, Berrezouga, Kuo, Yurek, Farley, Stockman and Leclercq1999). Hence, the interspecies transmission of resistant genes of clindamycin within bacterial populations mediated by plasmid is a risk to public health.
The MIC of seven drugs (penicillin, cefalexin, ceftiofor, tetracycline, enrofloxacin, daptomycin, and erythromycin) against isolates from three farms (A, K, and G) is also heterogeneous. Overall, the MIC of drugs against isolates from A was the highest, followed by G and K. This finding may indicate that farm A has antimicrobial abuse problems because ST103 was a predominant subtype in farm A and MIC of ST103 was relatively higher than other STs (online Supplementary Table 5).
Association between antimicrobials resistance and MLST
Tomazi et al. (Reference Tomazi, de Souza Filho, Heinemann and Dos Santos2018) found through random amplified polymorphic DNA analysis that isolates of cluster Ib were the most resistant to tetracycline, erythromycin, and pirmycin due to the presence of resistant genes in exact sub-types of isolates. Yang et al. (Reference Yang, Liu, Ding, Yi, Ma, Fan and Lu2013) also found isolates assigned to capsular genotype II associated with alpha-like proteins 1 and 4. In our research, the association between STs and antimicrobial resistance profile patterns was determined. The ST103 had higher MIC in the 12 tested antimicrobials compared with the two remaining major STs (online Supplementary Table 6), and exhibited increasing MIC under antimicrobial pressure as time went by.
In conclusion, overall herd prevalence of Strep. agalactiae was 18.6% and 15 STs were found. The majority of the isolates were ST103, and 13 STs were newly reported in these Chinese dairy herds. The Strep. agalactiae isolates were susceptible to the commonly used antimicrobials in practice, except for resistance to clindamycin, erythromycin, tetracycline, and daptomycin. ST103 was significantly associated with antimicrobial resistance in this study. The current study suggests that Strep. agalactiae mastitis control programmes should mainly focus on ST103 type in Chinese dairy herds and awareness of the prudent use of antimicrobials should be improved on farms.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0022029922000152.
Acknowledgments
This study was financially supported by the National Natural Science Foundation of China (No. 31660730), Yunnan Expert Workstation (No. 202005AF150041) and Science Research Foundation of Yunnan Education Bureau (grant number: No. 2020y134).
