A dynamic model linking cell growth to intracellular metabolism and extracellular by-product accumulation

Mathematical modeling of animal cell growth and metabolism is essential for the understanding and improvement of the production of biopharmaceuticals. Models can explain the dynamic behavior of cell growth and product formation, support the identification of the most relevant parameters for process design, and significantly reduce the number of experiments to be performed for process optimization. Few dynamic models have been established that describe both extracellular and intracellular dynamics of growth and metabolism of animal cells. In this study, a model was developed, which comprises a set of 33 ordinary differential equations to describe batch cultivations of suspension AGE1.HN.AAT cells considered for the production of α1-antitrypsin. This model combines a segregated cell growth model with a structured model of intracellular metabolism. Overall, it considers the viable cell concentration, mean cell diameter, viable cell volume, concentration of extracellular substrates, and intracellular concentrations of key metabolites from the central carbon metabolism. Furthermore, the release of metabolic by-products such as lactate and ammonium was estimated directly from the intracellular reactions. Based on the same set of parameters, this model simulates well the dynamics of four independent batch cultivations. Analysis of the simulated intracellular rates revealed at least two distinct cellular physiological states. The first physiological state was characterized by a high glycolytic rate and high lactate production. Whereas the second state was characterized by efficient adenosine triphosphate production, a low glycolytic rate, and reactions of the TCA cycle running in the reverse direction from α-ketoglutarate to citrate. Finally, we show possible applications of the model for cell line engineering and media optimization with two case studies.     

Noninvasive tool for optical online monitoring of individual biomass concentrations in a defined coculture

Cocultures bear great potential in the conversion of complex substrates and process intensification, as well as, in the formation of unique components only available due to inter-species interactions. Dynamic data of coculture composition is necessary for understanding and optimizing coculture systems. However, most standard online determined parameters measure the sum of all species in the reactor system. The kinetic behavior of the individual species remains unknown. Up to now, different offline methods are available to determine the culture composition, as well as the online measurement of fluorescence of genetically modified organisms. To avoid any genetic modification, a noninvasive online monitoring tool based on the scattered light spectrum was developed for microtiter plate cultivations. To demonstrate the potential, a coculture consisting of the bacterium Lactococcus lactis and the yeast Kluyveromyces marxianus was cultivated. Via partial least squares regression of scattered light spectra, the online determination of the individual biomass concentrations without further sampling and analyses is possible. The results were successfully validated by a Coulter counter-analysis, taking advantage of the different cell sizes of both organisms. The findings prove the applicability of the new method to follow in detail the dynamics of a coculture.     

When size does matter: organelle size influences the properties of transport mediated by molecular motors

Background

Organelle transport is driven by the action of molecular motors. In this work, we studied the dynamics of organelles of different sizes with the aim of understanding the complex relation between organelle motion and microenvironment.

Methods

We used single particle tracking to obtain trajectories of melanosomes (pigmented organelles in Xenopus laevis melanophores). In response to certain hormones, melanosomes disperse in the cytoplasm or aggregate in the perinuclear region by the combined action of microtubule and actin motors.

Results and conclusions

Melanosome trajectories followed an anomalous diffusion model in which the anomalous diffusion exponent (α) provided information regarding the trajectories' topography and thus of the processes causing it. During aggregation, the directionality of big organelles was higher than that of small organelles and did not depend on the presence of either actin or intermediate filaments (IF). Depolymerization of IF significantly reduced α values of small organelles during aggregation but slightly affect their directionality during dispersion.

General significance

Our results could be interpreted considering that the number of copies of active motors increases with organelle size. Transport of big organelles was not influenced by actin or IF during aggregation showing that these organelles are moved processively by the collective action of dynein motors. Also, we found that intermediate filaments enhance the directionality of small organelles suggesting that this network keeps organelles close to the tracks allowing their efficient reattachment. The higher directionality of small organelles during dispersion could be explained considering the better performance of kinesin-2 vs. dynein at the single molecule level.     

Cellulose-bound Peptide Arrays: Preparation and Applications

Spatial organization of metabolic enzymes may represent a general cellular mechanism to regulate metabolic flux. One recent example of this type of cellular phenomenon is the purinosome, a newly discovered multi-enzyme metabolic assembly that includes all of the enzymes within the de novo purine biosynthetic pathway. Our understanding of the components and regulation of purinosomes has significantly grown in recent years. This paper reviews the purine de novo biosynthesis pathway and its regulation, and presents the evidence supporting the purinosome assembly and disassembly processes under the control of G-protein-coupled receptor (GPCR) signaling. This paper also discusses the implications of purinosome and GPCR regulation in drug discovery.     

Role of tyrosine hot‐spot residues at the interface of colicin E9 and immunity protein 9: A comparative free energy simulation study

The endonuclease activity of the bacterial colicin 9 enzyme is controlled by the specific and high‐affinity binding of immunity protein 9 (Im9). Molecular dynamics simulation studies in explicit solvent were used to investigate the free energy change associated with the mutation of two hot‐spot interface residues [tyrosine (Tyr): Tyr54 and Tyr55] of Im9 to Ala. In addition, the effect of several other mutations (Leu33Ala, Leu52Ala, Val34Ala, Val37Ala, Ser48Ala, and Ile53Ala) with smaller influence on binding affinity was also studied. Good qualitative agreement of calculated free energy changes and experimental data on binding affinity of the mutations was observed. The simulation studies can help to elucidate the molecular details on how the mutations influence protein–protein binding affinity. The role of solvent and conformational flexibility of the partner proteins was studied by comparing the results in the presence or absence of solvent and with or without positional restraints. Restriction of the conformational mobility of protein partners resulted in significant changes of the calculated free energies but of similar magnitude for isolated Im9 and for the complex and therefore in only modest changes of binding free energy differences. Although the overall binding free energy change was similar for the two Tyr–Ala mutations, the physical origin appeared to be different with solvation changes contributing significantly to the Tyr55Ala mutation and to a loss of direct protein–protein interactions dominating the free energy change due to the Tyr54Ala mutation. Proteins 2013. © 2012 Wiley Periodicals, Inc.     

Combinatorial materials research applied to the development of new surface coatings IV. A high-throughput bacterial biofilm retention and retraction assay for screening fouling-release performance of coatings

Abstract

A high-throughput bacterial biofilm retention screening method has been augmented to facilitate the rapid analysis and down-selection of fouling-release coatings for identification of promising candidates. Coatings were cast in modified 24-well tissue culture plates and inoculated with the marine bacterium Cytophaga lytica for attachment and biofilm growth. Biofilms retained after rinsing with deionised water were dried at ambient laboratory conditions. During the drying process, retained biofilms retracted through a surface de-wetting phenomenon on the hydrophobic silicone surfaces. The retracted biofilms were stained with crystal violet, imaged, and analysed for percentage coverage. Two sets of experimental fouling-release coatings were analysed with the high-throughput biofilm retention and retraction assay (HTBRRA). The first set consisted of a series of model polysiloxane coatings that were systematically varied with respect to ratios of low and high MW silanol-terminated PDMS, level of cross-linker, and amount of silicone oil. The second set consisted of cross-linked PDMS-polyurethane coatings varied with respect to the MW of the PDMS and end group functionality. For the model polysiloxane coatings, HTBRRA results were compared to data obtained from field immersion testing at the Indian River Lagoon at the Florida Institute of Technology. The percentage coverage calculations of retracted biofilms correlated well to barnacle adhesion strength in the field (R² = 0.82) and accurately identified the best and poorest performing coating compositions. For the cross-linked PDMS-polyurethane coatings, the HTBRRA results were compared to combinatorial pseudobarnacle pull-off adhesion data and good agreement in performance was observed. Details of the developed assay and its implications in the rapid discovery of new fouling-release coatings are discussed.     

Characterization of the Structure and Melting Behavior of the Loop I fragment of ColE1 RNA I

Abstract

We have synthesized two RNA fragments: a 42-mer corresponding to the full loop I sequence of the loop I region of ColE1 antisense RNA (RNA I), plus three additional Gs at the 5′-end, and a 31-mer which has 11 5′-end nucleotides (G(-2)-U9) deleted. The secondary structure of the 42-mer, deduced from one- and two-dimensional NMR spectra, consists of a stem of 11 base-pairs which contains a U-U base-pair and a bulged C base, a 7 nucleotide loop, and a single-stranded 5′ end of 12 nucleotides. The UV-melting study of the 42-mer further revealed a multi-step melting behavior with transition temperatures 32°C and 71°C clearly discernible. In conjunction with NMR melting study the major transition at 71°C is assigned to the overall melting of the stem region and the 32°C transition is assigned to the opening of the loop region. The deduced secondary structure agrees with that proposed for the intact RNA I and provides structural bases for understanding the specificity of RNase E.