RÉSUMÉ
Background Bacteria are the most diverse and widely sourced microorganisms in the indoor air of subway stations, where pathogenic bacteria can spread through the air, leading to increased health risks. Objective To understand the status and distribution characteristics of indoor air bacterial pollution in subway stations and compartments in a city of Central South China, and to provide a scientific basis for formulating intervention measures to address indoor air bacteria pollution in subways. Methods Three subway stations and the compartments of trains parking there in a city in Central South China were selected according to passenger flow for synchronous air sampling and monitoring. Temperature, humidity, wind speed, carbon dioxide (CO2), fine particulate matter (PM2.5), and inhalable particulate matter (PM10) were measured by direct reading method. In accordance with the requirements of Examination methods for public places-Part 3: Airborne microorganisms (GB/T 18204.3-2013), air samples were collected at a flow rate of 28.3 L·min−1, and total bacterial count was estimated. Bacterial microbial species were identified with a mass spectrometer and pathogenic bacteria were distinguished from non-pathogenic bacteria according to the Catalogue of pathogenic microorganisms transmitted to human beings issued by National Health Commission. Kruskal-Wallis H test was used to compare the subway hygiene indicators in different regions and time periods, and Bonferroni test was used for pairwise comparison. Spearman correlation test was used to evaluate the correlation between CO2 concentration and total bacterial count. Results The pass rates were 100.0% for airborne total bacteria count, PM2.5, and PM10 in the subway stations and train compartments, 94.4% for temperature and wind speed, 98.6% for CO2, but 0% for humidity. The overall median (P25, P75) total bacteria count was 177 (138,262) CFU·m−3. Specifically, the total bacteria count was higher in station halls than in platforms, and higher during morning peak hours than during evening peak hours (P<0.05). A total of 874 strains and 82 species were identified by automatic microbial mass spectrometry. The results of identification were all over 9 points, and the predominant bacteria in the air were Micrococcus luteus (52.2%) and Staphylococcus hominis (9.8%). Three pathogens, Acinetobacter baumannii (0.3%), Corynebacterium striatum (0.1%), and Staphylococcus epidermidis bacilli (2.2%) were detected in 23 samples (2.6%), and the associated locations were mainly distributed in train compartments during evening rush hours. Conclusion The total bacteria count in indoor air varies by monitoring sites of subway stations and time periods, and there is a risk of opportunistic bacterial infection. Attention should be paid to cleaning and disinfection during peak passenger flow hours in all areas.
RÉSUMÉ
Objective:A nested-PCR assay is developed to detect and identify the genomic DNA of Brucella vaccine A19 strain. Methods:The whole genomic sequences of Brucella vaccine A19 strain and other Brucella spp. strains were compared and analyzed. The primers were designed by nucleotide difference sites. The nested-PCR assay was established to detect and identify Brucella vaccine A19 strain. The genomic DNA of Brucella vaccine A19 strain was extracted and diluted. The diluted template DNA was tested for sensitivity of using nested-PCR assay. And the specificity of nested-PCR assay was tested for the genomic DNA of other Brucella spp. strains and non- Brucella spp. strains. Results:The minimum detection limit of the nested-PCR assay was 3.43 fg. The nested-PCR assay established for amplification of Brucella vaccine A19 strain showed 246 bp electrophoresis bands, while other Brucella spp. strains showed 314 bp electrophoresis bands, and non- Brucella spp. strains did not produce electrophoresis bands. Conclusions:The nested-PCR assay established has the characteristics of high sensitivity and specificity. It can be detected when there is one copy of Brucella vaccine A19 strain genomic DNA in the reaction system. This method is particularly suitable for the detection and identification of trace genomic DNA of Brucella vaccine A19 strain in sample.
RÉSUMÉ
Objective:To establish a quantitative real-time PCR detection system for Brucella S2 vaccine strain. Methods:Based on the differences in the entire genome sequence between Brucella S2 vaccine strain and other reference strains of Brucella, primers and probes were designed to establish a quantitative real-time PCR detection system for Brucella S2 vaccine strain. The DNA of 22 reference strains of Brucella and 8 non- Brucella control strains were obtained from the National Institute for Infectious Disease Control and Prevention of the Chinese Center for Disease Control and Prevention. At the same time, environmental samples were obtained from the brucellosis vaccine manufacturers, and bacterial DNA from environmental samples was extracted using a blood/tissue genomic DNA extraction kit. The obtained DNA was pre-amplified by conventional PCR, and then subjected to quantitative real-time PCR secondary amplification (nested fluorescence quantitative PCR) using the amplified PCR product as a template. The specific fluorescence curve and corresponding number of cycles (Ct value) were observed, and the sensitivity was tested. Results:The quantitative real-time PCR detection system established did not detect specific fluorescence curves (without Ct values) for 21 reference strains of Brucella and 8 non- Brucella control strains, except for S2 vaccine strains. The established detection system had a minimum detection limit of 4.34 fg (genomic DNA) for detecting the DNA of Brucella S2 vaccine strain; DNA of Brucella S2 vaccine strain was detected in 3 of the 14 environmental samples collected. Conclusion:The quantitative real-time PCR detection system established can detect Brucella S2 vaccine strain in samples, with good sensitivity and specificity.