Efficient computation of stochastic cell-size transient dynamics

Background How small, fast-growing bacteria ensure tight cell-size distributions remains elusive. High-throughput measurement techniques have propelled efforts to build modeling tools that help to shed light on the relationships between cell size, growth and cycle progression. Most proposed models describe cell division as a discrete map between size at birth and size at division with stochastic fluctuations assumed. However, such models underestimate the role of cell size transient dynamics by excluding them. Results We propose an efficient approach for estimation of cell size transient dynamics. Our technique approximates the transient size distribution and statistical moment dynamics of exponential growing cells following an adder strategy with arbitrary precision. Conclusions We approximate, up to arbitrary precision, the distribution of division times and size across time for the adder strategy in rod-shaped bacteria cells. Our approach is able to compute statistical moments like mean size and its variance from such distributions efficiently, showing close match with numerical simulations. Additionally, we observed that these distributions have periodic properties. Our approach further might shed light on the mechanisms behind gene product homeostasis.

Modeling the Separation of Microorganisms in Bioprocesses by Flotation

Bioprocesses for the production of renewable energies and materials lack efficient separation processes for the utilized microorganisms such as algae and yeasts. Dissolved air flotation (DAF) and microflotation are promising approaches to overcome this problem. The efficiency of these processes depends on the ability of microorganisms to aggregate with microbubbles in the flotation tank. In this study, different new or adapted aggregation models for microbubbles and microorganisms are compared and investigated for their range of suitability to predict the separation efficiency of microorganisms from fermentation broths. The complexity of the heteroaggregation models range from an algebraic model to a 2D population balance model (PBM) including the formation of clusters containing several bubbles and microorganisms. The effect of bubble and cell size distributions on the flotation efficiency is considered by applying PBMs, as well. To determine the sensitivity of the results on the model assumptions, the modeling approaches are compared, and suggestions for their range of applicability are given. Evaluating the computational fluid dynamics (CFD) of a dissolved air flotation (DAF) system shows the heterogeneity of the fluid dynamics in the flotation tank. Since analysis of the streamlines of the tank show negligible back mixing, the proposed aggregation models are coupled to the CFD data by applying a Lagrangian approach.

Modeling the Separation of Microorganisms in Bioprocesses by Flotation

Bioprocesses for the production of renewable energies and materials lack efficient separation processes for the utilized microorganisms such as algae and yeasts. Dissolved air flotation (DAF) and microflotation are promising approaches to overcome this problem. The efficiency of these processes depends on the ability of microorganisms to aggregate with microbubbles in the flotation tank. In this study, different new or adapted aggregation models for microbubbles and microorganisms are compared and investigated for their range of suitability to predict the separation efficiency of microorganisms from fermentation broths. The complexity of the heteroaggregation models range from an algebraic model to a 2D population balance model (PBM) including the formation of clusters containing several bubbles and microorganisms. The effect of bubble and cell size distributions on the flotation efficiency is considered by applying PBMs, as well. To determine the impact of the model assumptions, the modeling approaches are compared and classified for their range of applicability. Evaluating computational fluid dynamics (CFD) of a DAF system shows the heterogeneity of the fluid dynamics in the flotation tank. Since analysis of the streamlines of the tank show negligible backmixing, the proposed aggregation models are coupled to the CFD data by applying a Lagrangian approach.

Synthesis and characterization of porous polyimide films containing benzimidazole moieties

In this study, a series of porous polyimide films containing benzimidazole units were prepared through a phase separation process. The dibutyl phthalate was selected as porogen. The copolyimides were prepared by the reaction of 3,3′,4,4′-benzophenonetetracarboxylic dianhydride with two diamines of 2-(4-aminophenyl)-5-aminobenzimidazole (BIA) and 4,4′-diaminodiphenyl ether with various molar ratios. The resultant porous polyimide films exhibit optimum cell-size distributions. The effects of BIA on morphology, mechanical, and thermal properties of the porous films were explored. It was found that as the BIA content reached up to 30 mol%, the porous copolyimide film demonstrates remarkable thermal stability and admirable mechanical properties with the glass transition temperature of 294°C, 5% weight loss temperature in argon flow up to 545°C, and a tensile strength of 48 MPa. The incorporation of BIA into the polyimide chains brought the highly rigid structures and strong intermolecular interactions, resulting in the enhancement in the thermal stability and the mechanical properties.

Threshold effect of growth rate on population variability of Escherichia coli cell lengths

A long-standing question in biology is the effect of growth on cell size. Here, we estimate the effect of Escherichia coli growth rate ( r ) on population cell size distributions by estimating the coefficient of variation of cell lengths (CV L ) from image analysis of fixed cells in DIC microscopy. We find that the CV L is constant at growth rates less than one division per hour, whereas above this threshold, CV L increases with an increase in the growth rate. We hypothesize that stochastic inhibition of cell division owing to replication stalling by a RecA-dependent mechanism, combined with the growth rate threshold of multi-fork replication (according to Cooper and Helmstetter), could form the basis of such a threshold effect. We proceed to test our hypothesis by increasing the frequency of stochastic stalling of replication forks with hydroxyurea (HU) treatment and find that cell length variability increases only when the growth rate exceeds this threshold. The population effect is also reproduced in single-cell studies using agar-pad cultures and ‘mother machine’-based experiments to achieve synchrony. To test the role of RecA, critical for the repair of stalled replication forks, we examine the CV L of E. coli ΔrecA cells. We find cell length variability in the mutant to be greater than wild-type, a phenotype that is rescued by plasmid-based RecA expression. Additionally, we find that RecA-GFP protein recruitment to nucleoids is more frequent at growth rates exceeding the growth rate threshold and is further enhanced on HU treatment. Thus, we find growth rates greater than a threshold result in increased E. coli cell lengths in the population, and this effect is, at least in part, mediated by RecA recruitment to the nucleoid and stochastic inhibition of division.