Use of non-linear mixed-effects modelling and regression analysis to predict the number of somatic coliphages by plaque enumeration after 3 hours of incubation

Abstract

The present study aimed to establish the kinetics of the appearance of coliphage plaques using the double agar layer titration technique to evaluate the feasibility of using traditional coliphage plaque forming unit (PFU) enumeration as a rapid quantification method. Repeated measurements of the appearance of plaques of coliphages titrated according to ISO 10705-2 at different times were analysed using non-linear mixed-effects regression to determine the most suitable model of their appearance kinetics. Although this model is adequate, to simplify its applicability two linear models were developed to predict the numbers of coliphages reliably, using the PFU counts as determined by the ISO after only 3 hours of incubation. One linear model, when the number of plaques detected was between 4 and 26 PFU after 3 hours, had a linear fit of: (1.48 × Counts + 1.97); and the other, values >26 PFU, had a fit of (1.18 × Counts + 2.95). If the number of plaques detected was <4 PFU after 3 hours, we recommend incubation for (18 ± 3) hours. The study indicates that the traditional coliphage plating technique has a reasonable potential to provide results in a single working day without the need to invest in additional laboratory equipment.

Statistical calibration of microbial suspensions in carrier controls during a textile disinfection ring trial

“…A regression was used to test a significant slope between N 0 a nd LR, and in the results obtained using the lm() function of R [5] The regression used indicates a significant influence of the initial microbial load on the reduction of microorganisms in the carrier after laundering, which could lead to a misinterpretation of the LR value if not corrected.…”

“…For each microorganism, it is indicated if the model is significant and if so, it would suggest that a calibration is necessary. The scatterplot between the studied variables and the relationship line is also represented according to the literature [5] [6].…”

A priori estimation of sequencing effort in complex microbial metatranscriptomes

“…In this type of study, it is common to perform an initial analysis for model selection. Thus, rarefaction curves were first fitted based on previous experience and a selection of possible nonlinear models (Mendez et al, 2017) The Weibull growth model used in our studies is derived from the one-parameter Weibull function (10), given by:…”

“…Weibull model or other similar and well-known models such as the logistics curve model (Mendez et al, 2017). Other predictors used were the minimum-maximum number of genes observed and, finally, the minimum-maximum number of reads observed (see Table 3, central column; model 1 and model 2 and supplementary material).…”

“…or the use of Bayesian methods(Monleon- Getino et al, 2017) were tested.Several functions, including Weibull, logistic, asymptotic regression through the origin (or a two-parameter Weibull growth model), Gompertz, and Michaelis-Menten models, were tested using nonlinear regression for use as extrapolations of the rarefaction curves(Mendez et al, 2017). The regression analysis was performed using the R-package function nls( ), and the model accuracy was tested with the function accuracy( ) of the R-package rcompanion (R Companion, 2018), which produces a table of statistics that can fit multiple models.…”