Modeling synchronous growth of bacterial populations in phased cultivation

Determination of Mutation Rates with Two Symmetric and Asymmetric Mutation Types

We revisit our earlier paper, with two of the coauthors, in which we proposed an unbiased and consistent estimator μ^n for an unknown mutation rate μ of microorganisms. Previously, we proved that the associated sequence of estimators μ^n converges to μ almost surely pointwise on a nonextinct set Ω0. Here, we show that this sequence converges also in the mean square with respect to conditional probability measure P0·=P·∩Ω0/PΩ0 and that, with respect to P0, the estimator is asymptotically unbiased. We further assume that a microorganism can mutate or turn to a different variant of one of the two types. In particular, it can mean that bacteria under attack by a virus or chemical agent are either perishing or surviving, turning them to stronger variant. We propose estimators for their respective types and show that they are a.s. pointwise and L2-consistent and asymptotically unbiased with respect to measure P0.

Chemoadaptive Polymeric Assemblies by Integrated Chemical Feedback in Self-Assembled Synthetic Protocells

The design and chemical synthesis of artificial material objects which can mimic the functions of living cells is an important ongoing scientific endeavor. A key challenge necessary for fulfilling the criteria for a system to be living currently regards evolution, which is derived from adaptivity. Integrated chemical loops capable of feedback control are required to achieve chemical systems which exhibit adaptivity. To explore this, we present an integrated, two-component orthogonal chemical process involving reversible addition-fragmentation chain transfer (RAFT) based polymerization-induced self-assembly (PISA) and a copper-catalyzed azide-alkyne click (CuAAC) coupling reaction. The chemical processes are linked through electron transfer from the activated chain-transfer agent (CTA) to the dormant Cu(II) precatalyst. We show that combining these complementary chemistries in a single reaction pot resulted in two primary outcomes: (i) simplification of the PISA process to synthesize the macro-CTA in situ from available nonamphiphilic components and (ii) routes to complexity and adaptation involving population dynamics, morphologies, and dissipative phenomena observed during in situ microscopy analysis.

Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling

Cellular heterogeneity influences bioprocess performance in ways that until date are not completely elucidated. In order to account for this phenomenon in the design and operation of bioprocesses, reliable analytical and mathematical descriptions are required. We present an overview of the single cell analysis, and the mathematical modeling frameworks that have potential to be used in bioprocess control and optimization, in particular for microbial processes. In order to be suitable for bioprocess monitoring, experimental methods need to be high throughput and to require relatively short processing time. One such method used successfully under dynamic conditions is flow cytometry. Population balance and individual based models are suitable modeling options, the latter one having in particular a good potential to integrate the various data collected through experimentation. This will be highly beneficial for appropriate process design and scale up as a more rigorous approach may prevent a priori unwanted performance losses. It will also help progressing synthetic biology applications to industrial scale.

Micro-Electromechanical Affinity Sensor for the Monitoring of Glucose in Bioprocess Media

An affinity-viscometry-based micro-sensor probe for continuous glucose monitoring was investigated with respect to its suitability for bioprocesses. The sensor operates with glucose and dextran competing as binding partner for concanavalin A, while the viscosity of the assay scales with glucose concentration. Changes in viscosity are determined with a micro-electromechanical system (MEMS) in the measurement cavity of the sensor probe. The study aimed to elucidate the interactions between the assay and a typical phosphate buffered bacterial cultivation medium. It turned out that contact with the medium resulted in a significant long-lasting drift of the assay's viscosity at zero glucose concentration. Adding glucose to the medium lowers the drift by a factor of eight. The cglc values measured off-line with the glucose sensor for monitoring of a bacterial cultivation were similar to the measurements with an enzymatic assay with a difference of less than ±0.15 g·L-1. We propose that lectin agglomeration, the electro-viscous effect, and constitutional changes of concanavalin A due to exchanges of the incorporated metal ions may account for the observed viscosity increase. The study has demonstrated the potential of the MEMS sensor to determine sensitive viscosity changes within very small sample volumes, which could be of interest for various biotechnological applications.

From single cells to microbial population dynamics: modelling in biotechnology based on measurements of individual cells

The development of dynamic modelling of microbial populations in bioprocesses is reviewed. In the 1960s Arnold Fredrickson established the theoretical basis of such models, and other researchers have subsequently advanced them. This review explores the relationships that describe cell proliferation and evaluates the importance of the application of flow cytometry to the fundamental parameterisation of the models for their use in bioprocess engineering. The section "Individual-Based Modelling" discusses recent theoretical developments. Delay-differential equations are demonstrated to describe accurately temporal variation of the cell proliferation cycle and specialised approaches and related iconography are applied to stochastic and deterministic modelling of stages of cellular development. Synchronised cultures of the bacterium Cupriavidus necator were prepared and monitored using a flow cytometer. The data obtained demonstrate that cell proliferation could be simulated quantitatively using the developed model.

Weak transcription of the cry1Ac gene in nonsporulating Bacillus thuringiensis cells

The cry1Ac gene of Bacillus thuringiensis subsp. kurstaki HD-73 (B. thuringiensis HD-73) is a typical example of a sporulation-dependent crystal gene and is controlled by sigma E and sigma K during sporulation. To monitor the production and accumulation of Cry1Ac at the cellular level, we developed a green fluorescent protein-based reporter system. The production of Cry1Ac was monitored in spo0A, sigE, and sigK mutants, and these mutants were able to express the Cry1Ac-green fluorescent protein fusion protein. In nonsporulating B. thuringiensis HD-73 cells, low-level expression of cry1Ac was also observed. Reverse transcription-PCR and Western blotting results confirmed that the cry1Ac promoter has low activity in nonsporulating B. thuringiensis cells. A beta-galactosidase assay demonstrated that the transcription of the cry1Ac gene during exponential and transition phases is positively regulated by Spo0A. Additional bioassay results indicated that spo0A and sigE mutants containing the cry1Ac-gfp fusion exhibited insecticidal activity against Plutella xylostella larvae.

Origin and analysis of microbial population heterogeneity in bioprocesses

Heterogeneity of industrial production cultures is accepted to a certain degree; however, the underlying mechanisms are seldom perceived or included in the development of new bioprocess control strategies. Population heterogeneity and its basics, perceptible in the diverse proficiency of cells, begins with asymmetric birth and is found to recess during the life cycle. Since inefficient subpopulations have significant impact on the productivity of industrial cultures, cellular heterogeneity needs to be detected and quantified by using high speed detection tools like flow cytometry. Possible origins of population heterogeneity, sophisticated fluorescent techniques for detection of individual cell states, and cutting-edge Omics-technologies for extended information beyond the resolution of fluorescent labelling are highlighted.