A two-parameter model describes the microbial growth trend of planktonic cultures. Based on the assumption that cell duplication underlies the growth, the model defines an average generation time that depends on time and complies with the phenomenological evidence that the growth rate is naught at the start and at the end of the process. This is tantamount as to replace the real growth process with a virtual one, where all the generation lines stemming from the inoculum are synchronous and imply a duplication tree with no truncated branches. A simple function that complies with these constraints is τ=(a/t+bt), where a and b are parameters defined through a best fit treatment of the experimental plate count data. Surprisingly simple relationships come out for specific items of the growth trend, like maximum specific growth rate, eventual cell number, Nmax, duration of lag phase, etc., as well as some intriguing correlations between them. Published plate count data allowed testing the reliability of the model. The agreement is satisfactory being in line with the accuracy of the data (R2 ≥ 0.98).

Microbial Growth in Planktonic Conditions / A. Schiraldi. - In: CELL & DEVELOPMENTAL BIOLOGY. - ISSN 2168-9296. - 6:3(2017 Jun), pp. 1000185.1-1000185.6. [10.4172/2168-9296.1000185]

Microbial Growth in Planktonic Conditions

A. Schiraldi
2017

Abstract

A two-parameter model describes the microbial growth trend of planktonic cultures. Based on the assumption that cell duplication underlies the growth, the model defines an average generation time that depends on time and complies with the phenomenological evidence that the growth rate is naught at the start and at the end of the process. This is tantamount as to replace the real growth process with a virtual one, where all the generation lines stemming from the inoculum are synchronous and imply a duplication tree with no truncated branches. A simple function that complies with these constraints is τ=(a/t+bt), where a and b are parameters defined through a best fit treatment of the experimental plate count data. Surprisingly simple relationships come out for specific items of the growth trend, like maximum specific growth rate, eventual cell number, Nmax, duration of lag phase, etc., as well as some intriguing correlations between them. Published plate count data allowed testing the reliability of the model. The agreement is satisfactory being in line with the accuracy of the data (R2 ≥ 0.98).
Duplication model; Plate count fit; Correlated growth parameters
Settore CHIM/02 - Chimica Fisica
giu-2017
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/516263
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