Gonzales-Gustavson Eloy, Cárdenas-Youngs Yexenia, Calvo Miquel, da Silva Marcelle Figueira Marques, Hundesa Ayalkibet, Amorós Inmaculada, Moreno Yolanda, Moreno-Mesonero Laura, Rosell Rosa, Ganges Llilianne, Araujo Rosa, Girones Rosina
Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Av. Diagonal 643, 08028 Barcelona, Catalonia, Spain.
Instituto de Ingeniería del Agua y Medio Ambiente, Ciudad Politécnica de la Innovación, Ed. 8G, Acceso D, planta 2, Universidad Politécnica de Valencia, Camino de Vera s/n, 46022 Valencia, Spain.
J Microbiol Methods. 2017 Mar;134:46-53. doi: 10.1016/j.mimet.2017.01.006. Epub 2017 Jan 16.
In this study, the use of skimmed milk flocculation (SMF) to simultaneously concentrate viruses, bacteria and protozoa was evaluated. We selected strains of faecal indicator bacteria and pathogens, such as Escherichia coli and Helicobacter pylori. The viruses selected were adenovirus (HAdV 35), rotavirus (RoV SA-11), the bacteriophage MS2 and bovine viral diarrhoea virus (BVDV). The protozoa tested were Acanthamoeba, Giardia and Cryptosporidium. The mean recoveries with q(RT)PCR were 66% (HAdV 35), 24% (MS2), 28% (RoV SA-11), 15% (BVDV), 60% (E. coli), 30% (H. pylori) and 21% (Acanthamoeba castellanii). When testing the infectivity, the mean recoveries were 59% (HAdV 35), 12% (MS2), 26% (RoV SA-11) and 0.7% (BVDV). The protozoa Giardia lamblia and Cryptosporidium parvum were studied by immunofluorescence with recoveries of 18% and 13%, respectively. Although q(RT)PCR consistently showed higher quantification values (as expected), q(RT)PCR and the infectivity assays showed similar recoveries for HAdV 35 and RoV SA-11. Additionally, we investigated modelling the variability and uncertainty of the recovery with this method to extrapolate the quantification obtained by q(RT)PCR and estimate the real concentration. The 95% prediction intervals of the real concentration of the microorganisms inoculated were calculated using a general non-parametric bootstrap procedure adapted in our context to estimate the technical error of the measurements. SMF shows recoveries with a low variability that permits the use of a mathematical approximation to predict the concentration of the pathogen and indicator with acceptable low intervals. The values of uncertainty may be used for a quantitative microbial risk analysis or diagnostic purposes.
在本研究中,评估了使用脱脂牛奶絮凝法(SMF)同时浓缩病毒、细菌和原生动物的效果。我们选择了粪便指示菌和病原体的菌株,如大肠杆菌和幽门螺杆菌。所选病毒为腺病毒(HAdV 35)、轮状病毒(RoV SA - 11)、噬菌体MS2和牛病毒性腹泻病毒(BVDV)。所测试的原生动物为棘阿米巴、贾第虫和隐孢子虫。采用q(RT)PCR检测时,平均回收率分别为66%(HAdV 35)、24%(MS2)、28%(RoV SA - 11)、15%(BVDV)、60%(大肠杆菌)、30%(幽门螺杆菌)和21%(卡氏棘阿米巴)。在检测感染性时,平均回收率分别为59%(HAdV 35)、12%(MS2)、26%(RoV SA - 11)和0.7%(BVDV)。通过免疫荧光法研究了贾第虫和微小隐孢子虫,回收率分别为18%和13%。尽管q(RT)PCR始终显示出更高的定量值(如预期),但q(RT)PCR和感染性检测对HAdV 35和RoV SA - 11显示出相似的回收率。此外,我们研究了用该方法对回收率的变异性和不确定性进行建模,以推断q(RT)PCR获得的定量结果并估计实际浓度。使用在我们的研究背景下适用的通用非参数自助程序计算接种微生物实际浓度的95%预测区间,以估计测量的技术误差。SMF显示出回收率的低变异性,这使得可以使用数学近似法来预测病原体和指示菌的浓度,且预测区间可接受的低。不确定性值可用于定量微生物风险分析或诊断目的。