Mastitis in goats is mainly caused by coagulase-negative Staphylococcus (CNS). The identification methods for this group are based on evaluating the expression of phenotypic characteristics such as the ability to metabolize various substrates; however, this is disadvantageous as these methods are dependent on gene expression. In recent years, genotyping methods such as the Multiple Locus Variable-Number Tandem Repeat Analysis (MLVA) and gene identification have been useful for epidemiological study of several bacterial species. To develop a genotyping method, the genome sequence of Staphylococcus chromogenes MU970 was analysed. The analysis showed nine virulence genes described in Staphylococcus aureus. The MLVA was developed using four loci identified in the genome of S. chromogenes MU970. This genotyping method was examined in 23 strains of CNS isolated from goat mastitis. The rate of discrimination for MLVA was 0.8893, and the highest rates of discrimination per the index of Simpson and Hunter-Gaston were 0.926 and 0.968 for the locus 346_06, respectively. The virulence genes were present in all strains of S. chromogenes but not in other CNS. The genotyping method presented in this paper is a viable and easy method for typifying CNS isolates from mastitis cases in different regions and is an ideal mean of tracking this disease.
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http://dx.doi.org/10.21307/pjm-2018-019 | DOI Listing |
Eur J Appl Physiol
January 2025
Department of Exercise Physiology and Sports Therapy, Institute of Sports Science, Justus Liebig University Giessen, Kugelberg 62, 35394, Giessen, Germany.
Purpose: This study investigated elite German athletes to (1) assess their serum 25(OH)D levels and the prevalence of insufficiency, (2) identify key factors influencing serum 25(OH)D levels, and (3) analyze the association between serum 25(OH)D levels and handgrip strength.
Methods: In this cross-sectional study, a total of 474 athletes (231 female), aged 13-39 years (mean 19.3 years), from ten Olympic disciplines were included.
Virol J
January 2025
Department of Microbiology, College of Medicine, Taif University, Taif, 21944, Saudi Arabia.
Background: Despite numerous genetic studies on Infectious Bronchitis Virus (IBV), many strains from the Middle East remain misclassified or unclassified. Genotype 1 (GI-1) is found globally, while genotype 23 (GI-23) has emerged as the predominant genotype in the Middle East region, evolving continuously through inter- and intra-genotypic recombination. The GI-23 genotype is now enzootic in Europe and Asia.
View Article and Find Full Text PDFInt Immunopharmacol
January 2025
Department of Transfusion Medicine, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou 225300, Jiangsu, China. Electronic address:
Objective: The objective of this study was to rigorously investigate and elucidate the genetic mechanisms underlying the formation of the RH blood group in a specific case and to systematically analyse the RH blood group genes among the family members of the proband.
Methods: Serological methods were used to determine the RH blood group phenotype of the proband. To elucidate the underlying genetic mechanism responsible for the RH phenotype, a comprehensive approach was undertaken, including RHCE genotyping, sequencing of RHD and RHCE genes, and exon sequencing of RHAG.
J Infect Public Health
December 2024
Department of Medical Microbiology, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey; Department of Medical Biotechnology, Institute of Health Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey. Electronic address:
Background: Drug-resistant Group A beta-hemolytic streptococci remain significant infectious agents globally. This study investigated the major S. pyogenes strains responsible for infections in Türkiye and their susceptibility to beta-lactam and macrolide antibiotics.
View Article and Find Full Text PDFAging (Albany NY)
January 2025
Department of Public Health Sciences, University of Chicago, Chicago, IL 60615, USA.
Background: DNA methylation (DNAm) data from human samples has been leveraged to develop "epigenetic clock" algorithms that predict age and other aging-related phenotypes. Some DNAm clocks were trained using DNAm obtained from blood cells, while other clocks were trained using data from diverse tissue/cell types. To assess how DNAm clocks perform across non-blood tissue types, we applied DNAm algorithms to DNAm data generated from 9 different human tissue types.
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