Estimating Bacterial Growth Parameters by Means of Detection Times

摘要: Automated measures are commonly used to estimate bacterial growth parameters. Unfortunately, little information is obtained on the lag phase because change in physical properties of a culture (turbidity, conductance, etc.) detectable only at high cell concentrations. This problem serious, for example, food microbiology, where predicting end great importance (5). Microbiologists traditionally divide curves into lag, exponential, and stationary phases. The maximum specific rate, denoted by μ, can be estimated slope tangent drawn inflexion sigmoid curve which fitted data representing natural logarithm concentration against time. (If log10 instead logarithm, that ln 10 ≈ 2.3 times smaller than real rate). The period λ, usually interpreted as time elapsed from inoculation intercept with level inoculum (6). Figure ​Figure11 demonstrates these definitions, concentrating exponential most popular functions suitable fit viable-count listed, example reference 5. Generating data, however, laborious task, consequently there interest finding alternative approaches FIG. 1 The marks phase. detection time, Tdet, depends linearly if ... The parameter α = exp (−μλ) was introduced 2 quantify physiological state initial population. As shown previously (3), curve, also termed population not simple arithmetical average individual cells, τi (i 1…x0, x0 denotes number). inoculum, equal mean states αi (−μτi) quantities. We refer this physiological-state theorem. theorem valid irrespective actual distribution times. proof relies upon rather geometrical definition based logarithmic representation growth. Consider biological interpretation inoculum. level, starts after period, λ. Find another, hypothetical will identical previous “real” its but has no (Fig. ​(Fig.1).1). Denote point x0(hyp). During increases, scale, μλ; hence, x0(hyp)/x0 factor. In other words, expresses potential fraction counts which, without could “catch up” does have lag. extreme values 0 1, corresponding situations “infinitely long lag” “no lag,” respectively. dimensionless quantifying “suitability” environment. It is, fact, an value, just like derived 3 λ −ln α/μ, expressing idea inversely proportional rate well environment. In paper, we highlight useful feature parameter. develop new method, analysis variance (ANOVA) procedure, homogeneous advantage method it uses times, first available when recording growth, allows estimation within-population