Vantarakis A, Venieri D, Komninou G, Papapetropoulou M
Laboratory of Hygiene & Environmental Protection, Medical School, Democritus University of Thrace, Alexandroupolis, Greece.
Lett Appl Microbiol. 2006 Jan;42(1):71-7. doi: 10.1111/j.1472-765X.2005.01803.x.
Multiple antibiotic resistance (MAR) was performed on 128 Escherichia coli isolates, recovered from faecal samples of humans and animals (cattle, goat, sheep) to determine and compare their antibiotic resistance patterns and to evaluate them statistically in order to specify the source of the faecal material.
Disk diffusion method was applied with a selection of antibiotics. Statistical approach was performed with hierarchical cluster analysis (CA), discriminant analysis (DA) and principal component analysis. Comparing human and animal isolates there was significant difference in levels of resistance to all antibiotics tested (P<0.05) with 46 and 24 distinct resistance patterns for human and animal isolates respectively. CA and DA separated human and animal isolates with a high average rate of correct classification (99.2%), when all animal isolates were pooled together.
MAR analysis compared with appropriate statistical evaluation may provide a useful tool for differentiating the human or animal origin of E. coli isolates derived from environmental samples. Subsequently, determination of the source of faecal pollution becomes possible.
Determining the source of faecal pollution enables the prediction of possible risk for public health and the application of appropriate management plans for prevention of further contamination.
对从人类和动物(牛、山羊、绵羊)粪便样本中分离出的128株大肠杆菌进行多重耐药性(MAR)检测,以确定并比较它们的抗生素耐药模式,并进行统计学评估,从而明确粪便物质的来源。
采用纸片扩散法并选用了多种抗生素。运用层次聚类分析(CA)、判别分析(DA)和主成分分析进行统计学分析。比较人类和动物分离株发现,对所有测试抗生素的耐药水平存在显著差异(P<0.05),人类和动物分离株分别有46种和24种不同的耐药模式。当所有动物分离株合并在一起时,CA和DA以较高的平均正确分类率(99.2%)区分了人类和动物分离株。
MAR分析结合适当的统计学评估,可能为区分环境样本中大肠杆菌分离株的人类或动物来源提供一种有用的工具。随后,确定粪便污染的来源成为可能。
确定粪便污染的来源有助于预测对公众健康的潜在风险,并应用适当的管理计划来防止进一步污染。