A model of cell growth dynamics

1967 ◽  
Vol 15 (2) ◽  
pp. 190-207 ◽  
Author(s):  
F.M. Williams
Keyword(s):  
Author(s):  
Oben M. Tataw ◽  
Min Liu ◽  
Amit Roy-Chowdhurry ◽  
Ram K. Yadav ◽  
G. Venugopala Reddy

2015 ◽  
Vol 197 (7) ◽  
pp. 955-963
Author(s):  
Sharmistha Samanta Koruri ◽  
Ranjana Chowdhury ◽  
Pinaki Bhattacharya

2020 ◽  
Author(s):  
Joris Messelink ◽  
Fabian Meyer ◽  
Marc Bramkamp ◽  
Chase P. Broedersz

AbstractIn many bacteria, protein mass production is thought to be rate limiting for growth, implying exponential growth at the single cell level. To maintain cell-size homeostasis in proliferating populations of exponentially growing bacteria, tight growth and division mechanisms are required. However, it remains unclear whether these considerations set universal physical limits to bacterial growth. Here, we characterize the growth dynamics of the actinobacterium Corynebacterium glutamicum - a promising candidate for uncovering novel growth modes. This bacterium exhibits apical cell wall synthesis and division site selection systems appear to be absent, as reflected by a broad distribution of division asymmetries. We develop a novel growth inference method that averages out measurement noise and single-cell variability to obtain elongation rate curves as a function of birth length. Using this approach, we find that C. glutamicum exhibits asymptotically linear single-cell growth. To explain this growth mode, we model elongation as being rate-limited by the apical growth mechanism mediated by cell wall transglycosylases. This model accurately reproduces the observed elongation rate curves, and we further validate the model with growth measurements on a transglycosylase deficient ΔrodA mutant. Finally, with simulations we show that asymptotically linear growth yields a narrower distribution of cell lengths, suggesting that this growth mode can act as a substitute for tight division length and division symmetry regulation.SignificanceRegulation of growth and cell size is crucial for the optimization of bacterial cellular function. So far, single bacterial cells have been found to grow exponentially, which implies the need for tight regulation mechanisms to maintain cell size throughout growth and division cycles. Here, we characterize the growth behavior of the apically growing bacterium Corynebacterium glutamicum, by developing a novel and broadly applicable inference method for single-cell growth dynamics. We find that this bacterium grows asymptotically linearly, enabling it to maintain a narrow distribution of cell sizes, despite having a large variability of single-cell growth features. Our results imply a novel interplay between mode of growth and division regulation mechanisms, which may extend to other bacteria with non-exponential growth modes.


This is a review article to show that delay differential models have a richer mathematical framework (compared with models without memory or after-effects) and a better consistency with biological phenomena such dynamical diseases and cell growth dynamics. The article provides a general computational technique to treat numerically the emerging delay differential models. It introduces the numerical algorithms for parameter estimations, using least squares approach. The article introduces a variational method to evaluate sensitivity of the state variables to small perturbations in the initial conditions and parameters appear in the model. An application to show the consistency of DDE models with cell growth dynamics is also considered.


eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Joris Jan Boudewijn Messelink ◽  
Fabian Meyer ◽  
Marc Bramkamp ◽  
Chase P Broedersz

Regulation of growth and cell size is crucial for the optimization of bacterial cellular function. So far, single bacterial cells have been found to grow predominantly exponentially, which implies the need for tight regulation to maintain cell size homeostasis. Here, we characterize the growth behavior of the apically growing bacterium Corynebacterium glutamicum using a novel broadly applicable inference method for single-cell growth dynamics. Using this approach, we find that C. glutamicum exhibits asymptotically linear single-cell growth. To explain this growth mode, we model elongation as being rate-limited by the apical growth mechanism. Our model accurately reproduces the inferred cell growth dynamics and is validated with elongation measurements on a transglycosylase deficient ΔrodA mutant. Finally, with simulations we show that the distribution of cell lengths is narrower for linear than exponential growth, suggesting that this asymptotically linear growth mode can act as a substitute for tight division length and division symmetry regulation.


2019 ◽  
Author(s):  
Teemu P Miettinen ◽  
Joon Ho Kang ◽  
Lucy F Yang ◽  
Scott R Manalis

2017 ◽  
Vol 53 (17) ◽  
pp. 2571-2574 ◽  
Author(s):  
Pankaj Gaur ◽  
Ajay Kumar ◽  
Reena Dalal ◽  
Shalmoli Bhattacharyya ◽  
Subrata Ghosh

A bright and biostable molecular fluorogenic material for real-time monitoring of in vitro cellular growth dynamics.


2007 ◽  
Vol 129 (3) ◽  
pp. 446-452 ◽  
Author(s):  
Ivana Pajić-Lijaković ◽  
Milenko Plavšić ◽  
Branko Bugarski ◽  
Viktor Nedović

1988 ◽  
Vol 43 (1-3) ◽  
pp. 151-173 ◽  
Author(s):  
Samuel M. Cohen ◽  
Leon B. Ellwein

Development ◽  
2021 ◽  
Author(s):  
Rocky Diegmiller ◽  
Caroline A. Doherty ◽  
Tomer Stern ◽  
Jasmin Imran Alsous ◽  
Stanislav Y. Shvartsman

Size is a fundamental feature of living entities and is intimately tied to their function. Scaling laws, which can be traced to D'Arcy Thompson and Julian Huxley, have emerged as a powerful tool for studying regulation of the growth dynamics of organisms and their constituent parts. Yet throughout the 20th century, as scaling laws were established for single cells, quantitative studies of the coordinated growth of multicellular structures have lagged, largely due to technical challenges associated with imaging and image processing. Here, we present a supervised learning approach for quantifying the growth dynamics of germline cysts during oogenesis. Our analysis uncovers growth patterns induced by the groupwise developmental dynamics among connected cells, and differential growth rates of their organelles. We also identify inter-organelle volumetric scaling laws, finding that nurse cell growth is linear over several orders of magnitude. Our approach leverages the ever increasing quantity and quality of imaging data, and is readily amenable for studies of collective cell growth in other developmental contexts, including early mammalian embryogenesis and germline development.


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