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Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning.

ABSTRACT: Streptococcus uberis is one of the leading pathogens causing mastitis worldwide. Identification of S. uberis strains that fail to respond to treatment with antibiotics is essential for better decision making and treatment selection. We demonstrate that the combination of supervised machine learning and matrix-assisted laser desorption ionization/time of flight (MALDI-TOF) mass spectrometry can discriminate strains of S. uberis causing clinical mastitis that are likely to be responsive or unresponsive to treatment. Diagnostics prediction systems trained on 90 individuals from 26 different farms achieved up to 86.2% and 71.5% in terms of accuracy and Cohen's kappa. The performance was further increased by adding metadata (parity, somatic cell count of previous lactation and count of positive mastitis cases) to encoded MALDI-TOF spectra, which increased accuracy and Cohen's kappa to 92.2% and 84.1% respectively. A computational framework integrating protein-protein networks and structural protein information to the machine learning results unveiled the molecular determinants underlying the responsive and unresponsive phenotypes.

SUBMITTER: Maciel-Guerra A

PROVIDER: S-EPMC8032699 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning.

Maciel-Guerra Alexandre A Esener Necati N Giebel Katharina K Lea Daniel D Green Martin J MJ Bradley Andrew J AJ Dottorini Tania T

Scientific reports 20210408 1

Streptococcus uberis is one of the leading pathogens causing mastitis worldwide. Identification of S. uberis strains that fail to respond to treatment with antibiotics is essential for better decision making and treatment selection. We demonstrate that the combination of supervised machine learning and matrix-assisted laser desorption ionization/time of flight (MALDI-TOF) mass spectrometry can discriminate strains of S. uberis causing clinical mastitis that are likely to be responsive or unrespo ...[more]

PMID: 33833319

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Project description:Streptococcus uberis is considered one of the most important pathogens associated with bovine mastitis. While traditionally acknowledged as an environmental pathogen, S. uberis has been shown to adopt a contagious epidemiological pattern in several dairy herds. Since different control strategies are employed depending on the mode of transmission, in-depth studies of S. uberis populations are essential to determine the best practices to control this pathogen. In this work, we optimized and validated a dot blot platform, combined with automatic image analysis, to rapidly assess the population structure of infective S. uberis, and evaluated its efficiency when compared to multilocus sequence analysis (MLSA) genotyping. Two dairy herds with prevalent S. uberis infections were followed in a 6 month period, in order to collect and characterize isolates from cows with persistent infections. These herds, located in Portugal (Barcelos and Maia regions), had similar management practices, with the herd from Barcelos being smaller and having a better milking parlor management, since infected cow segregation was immediate. A total of 54 S. uberis isolates were obtained from 24 different cows from the two herds. To overcome operator-dependent analysis of the dot blots and increase the technique's consistency and reliability, the hybridization signals were converted into probability values, with average probabilities higher than 0.5 being considered positive results. These data allowed to confirm the isolates' identity as S. uberis using taxa-specific markers and to determine the presence of virulence- and antibiotic resistance-related genes. In addition, MLSA allowed to disclose the most prevalent S. uberis clonal lineages in both herds. Seven different clusters were identified, with Barcelos showing a high clonal diversity and Maia a dominant lineage infecting most cows, suggesting distinct epidemiological patterns, with S. uberis displaying an environmental or contagious transmission pattern depending on the herd. Overall, this work showed the utility of dot blot and MLSA to characterize population structure and epidemiological patterns of mastitis-causing S. uberis. This approach allowed to disclose prevalent virulence patterns and clonal lineages of S. uberis in two distinct herds, and gain insights on the impact of herd management practices on pathogen population structure.

Project description:The objectives of this study are to determine the occurrence of antimicrobial resistance (AMR) genes using whole-genome sequence (WGS) of Streptococcus uberis (S. uberis) and Streptococcus dysgalactiae (S. dysgalactiae) isolates, recovered from dairy cows in the Canadian Maritime Provinces. A secondary objective included the exploration of the association between phenotypic AMR and the genomic characteristics (genome size, guanine-cytosine content, and occurrence of unique gene sequences). Initially, 91 isolates were sequenced, and of these isolates, 89 were assembled. Furthermore, 16 isolates were excluded due to larger than expected genomic sizes (>2.3 bp × 1,000 bp). In the final analysis, 73 were used with complete WGS and minimum inhibitory concentration records, which were part of the previous phenotypic AMR study, representing 18 dairy herds from the Maritime region of Canada (1). A total of 23 unique AMR gene sequences were found in the bacterial genomes, with a mean number of 8.1 (minimum: 5; maximum: 13) per genome. Overall, there were 10 AMR genes [ANT(6), TEM-127, TEM-163, TEM-89, TEM-95, Linb, Lnub, Ermb, Ermc, and TetS] present only in S. uberis genomes and 2 genes unique (EF-TU and TEM-71) to the S. dysgalactiae genomes; 11 AMR genes [APH(3'), TEM-1, TEM-136, TEM-157, TEM-47, TetM, bl2b, gyrA, parE, phoP, and rpoB] were found in both bacterial species. Two-way tabulations showed association between the phenotypic susceptibility to lincosamides and the presence of linB (P = 0.002) and lnuB (P < 0.001) genes and the between the presence of tetM (P = 0.015) and tetS (P = 0.064) genes and phenotypic resistance to tetracyclines only for the S. uberis isolates. The logistic model showed that the odds of resistance (to any of the phenotypically tested antimicrobials) was 4.35 times higher when there were >11 AMR genes present in the genome, compared with <7 AMR genes (P < 0.001). The odds of resistance was lower for S. dysgalactiae than S. uberis (P = 0.031). When the within-herd somatic cell count was >250,000 cells/mL, a trend toward higher odds of resistance compared with the baseline category of <150,000 cells/mL was observed. When the isolate corresponded to a post-mastitis sample, there were lower odds of resistance when compared with non-clinical isolates (P = 0.01). The results of this study showed the strength of associations between phenotypic AMR resistance of both mastitis pathogens and their genotypic resistome and other epidemiological characteristics.

Project description:β-hydroxybutyrate (BHB) has been associated with disease incidence in early lactation dairy cattle, but such associations do not demonstrate causation. Therefore, the objective of this study was to examine the effects of BHB during an intramammary Streptococcus uberis challenge. A secondary objective was to elucidate the mechanisms behind BHB effects on cytokine transcript abundance using the RAW 264.7 cell line. Late lactation multiparous dairy cows (n = 12) were continuously infused intravenously with either BHB to induce hyperketonemia (target concentration: 1.8 mM) or with saline (CON) for 72 h during a S. uberis intramammary challenge. Body temperature, dry matter intake (DMI), milk production, and milk S. uberis cfu were measured daily until one week post-challenge. Blood samples were collected during infusion to assess changes in metabolism (glucose, insulin, glucagon, NEFA, and cortisol) and systemic inflammation (IL-1β and SAA). Mammary biopsies were conducted at 72 h post-challenge to assess transcript abundance of inflammation-associated genes. BHB-infused cows exhibited a delayed febrile response, noted by a lesser vaginal temperature during the final day of infusion, followed by a greater vaginal temperature 6 d post-challenge. Consequently, BHB-infused cows had greater S. uberis cfu on d 4, 6, and 7 as compared to CON. Accordingly, BHB-infused cows consumed less DM, produced less milk, had reduced blood glucose, and had increased cortisol concentrations, however, no effects were seen on other systemic parameters or transcript abundance of inflammation-related genes in mammary tissue. To elucidate mechanisms behind the impaired immune defenses, RAW 264.7 cells were transfected with a GPR109A siRNA for 24 h and then treated with or without 1.8 mM BHB and challenged or left unchallenged with S. uberis for an additional 3 h. Transfection with siRNA reduced Gpr109a by 75%. Although BHB treatment did not significantly increase Il10, GPR109A knockdown as compared to the scrambled control reduced Il10 by 90% in S. uberis challenged macrophages treated with BHB, suggesting that macrophage immune responses to S. uberis can be altered via a GPR109A-dependent mechanism. Taken together, these data suggest that BHB altered the immune response promoting tolerance toward S. uberis rather than resistance.

Dataset Information

Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning.

Publications

Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning.

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