应用一种新的多位点可变数串联重复分析(MLVA)方案对2022年春季威尔士和英格兰西北部细小隐孢子虫病例进行季节性调查

Harriet Risby , Guy Robinson , Nastassya Chandra , Grace King , Roberto Vivancos , Robert Smith , Daniel Thomas , Andrew Fox , Noel McCarthy , Rachel M. Chalmers
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引用次数: 1

摘要

小隐孢子虫是人类和牲畜肠胃炎的一个重要原因,隐孢子虫病的暴发是常见的。然而,多位点基因分型方案并未被广泛采用。我们描述了7位点多位点可变串联重复序列分析(MLVA)方案的进一步发展和应用。从2022年3月28日至7月31日,采用MLVA对威尔士(n = 95)和英格兰西北部(n = 118)隐孢子虫病患者(病例)确诊的小梭菌粪便(n = 213)进行检测。可分型性(定义为在样本中所有7个位点均鉴定出等位基因)为81.2%,根据亨特加斯顿歧视指数估计的歧视力为0.99。从等位基因中构建MLVA谱,按染色体顺序表达。基因型被定义为简单型(单个等位基因在每个位点)或混合型(多个等位基因在任何位点)。共鉴定出161个MLVA谱;13个是混合的,另外38个简单概要包含空记录,110个是完整的简单概要。最小生成树是由简单的MLVA谱和在所有7个位点上相同的基因定义的病例遗传簇(在这里,零记录被认为是等位基因)构建的;77例形成25组,从2例到9例(模式= 2例)不等。在流行病学调查之后,最大的聚集性病例表明出现了新发现的疫情。在疫情调查中还包括另外两例具有混合概况且包含疫情等位基因的病例。在另一次流行病学确定的6例初始病例暴发中,MLVA发现了另外2例病例。在第三次,三个病例的小规模爆发中,相同的MLVA谱加强了微生物证据。对单个基因座和七个基因座方案的性能特征的审查表明,两个基因座可能是审查的候选基因座,但在更广泛的地理区域和更长的时间框架内建立更大的数据集将有助于用户实验室和利益攸关方(如公共卫生机构)就该方案做出决策。与基于序列的方法相比,该MLVA方案使用简单,快速且便宜,可识别混合感染,为微小梭状虫监测提供了重要工具,并可加强疫情调查和公共卫生行动。
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Application of a new multi-locus variable number tandem repeat analysis (MLVA) scheme for the seasonal investigation of Cryptosporidium parvum cases in Wales and the northwest of England, spring 2022

The protozoan Cryptosporidium parvum is an important cause of gastroenteritis in humans and livestock, and cryptosporidiosis outbreaks are common. However, a multi-locus genotyping scheme is not widely adopted. We describe the further development and application of a seven-locus multi-locus variable number of tandem repeats analysis (MLVA) scheme. From 28th March to 31st July 2022, confirmed C. parvum stools (n = 213) from cryptosporidiosis patients (cases) in Wales (n = 95) and the north west of England (n = 118) were tested by MLVA. Typability (defined as alleles identified at all seven loci in a sample) was 81.2% and discriminatory power estimated by Hunter Gaston Discriminatory Index was 0.99. A MLVA profile was constructed from the alleles, expressed in chromosomal order. Profiles were defined as simple (single allele at each locus) or mixed (more than one allele at any locus). A total of 161 MLVA profiles were identified; 13 were mixed, an additional 38 simple profiles contained null records, and 110 were complete simple profiles. A minimum spanning tree was constructed of simple MLVA profiles and those identical at all seven loci defined genetic clusters of cases (here, null records were considered as an allele); 77 cases formed 25 clusters, ranging from two to nine (mode = two) cases. The largest cluster, following epidemiological investigation, signalled a newly-identified outbreak. Two other cases with mixed profiles that contained the outbreak alleles were included in the outbreak investigation. In another epidemiologically-identified outbreak of six initial cases, MLVA detected two additional cases. In a third, small outbreak of three cases, identical MLVA profiles strengthened the microbiological evidence. Review of the performance characteristics of the individual loci and of the seven-locus scheme suggested that two loci might be candidates for review, but a larger dataset over a wider geographical area and longer timeframe will help inform decision-making about the scheme by user laboratories and stakeholders (such as public health agencies). This MLVA scheme is straightforward in use, fast and cheap compared to sequence-based methods, identifies mixed infections, provides an important tool for C. parvum surveillance, and can enhance outbreak investigations and public health action.

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