Heat Shock Response in CHO Mammalian Cells Is Controlled by a Nonlinear Stochastic Process

In many biological systems, the interactions that describe the coupling between different units in a genetic network are nonlinear and stochastic. We study the interplay between stochasticity and nonlinearity using the responses of Chinese hamster ovary (CHO) mammalian cells to different temperature shocks. The experimental data show that the mean value response of a cell population can be described by a mathematical expression (empirical law) which is valid for a large range of heat shock conditions. A nonlinear stochastic theoretical model was developed that explains the empirical law for the mean response. Moreover, the theoretical model predicts a specific biological probability distribution of responses for a cell population. The prediction was experimentally confirmed by measurements at the single-cell level. The computational approach can be used to study other nonlinear stochastic biological phenomena

Impact of Interdisciplinary Undergraduate Research in Mathematics and Biology on the Development of a New Course Integrating Five STEM Disciplines

Funded by innovative programs at the National Science Foundation and the Howard Hughes Medical Institute, University of Richmond faculty in biology, chemistry, mathematics, physics, and computer science teamed up to offer first- and second-year students the opportunity to contribute to vibrant, interdisciplinary research projects. The result was not only good science but also good science that motivated and informed course development. Here, we describe four recent undergraduate research projects involving students and faculty in biology, physics, mathematics, and computer science and how each contributed in significant ways to the conception and implementation of our new Integrated Quantitative Science course, a course for first-year students that integrates the material in the first course of the major in each of biology, chemistry, mathematics, computer science, and physics

In silico dynamic optimisation studies for batch/fed-batch mammalian cell suspension cultures producing biopharmaceuticals

Mammalian cell cultures are valuable for synthesis of therapeutic proteins and antibodies. They are commonly cultivated in bioindustry in form of large-scale suspension fed-batch cultures. The structure and regulatory responses of mammalian cells are complex, making it challenging to model them for practical process optimisation. The adjustable degrees of freedom in the cell cultures can be continuous variables as well as binary-type variables. The binary-type variables may be irreversible in cases such as cell-cycle arrest. The main aim of this study was to develop a general model for mammalian cell cultures using extracellular variables and capturing major changes in cellular responses between batch and fed-batch cultures. The model development started with a simple model for a hybridoma cell culture using first-principle equations. The growth kinetics was only linked to glucose and glutamine and the cell population was divided into three cell-cycle phases to study the phenomenon of cell-cycle arrest. But there were certain deficiencies in predicting growth rates in the death phase in fed-batch cultures although it was successful to simultaneously optimise a combination of continuous and binary-irreversible degrees of freedom. Thus, the growth kinetics was further related to amino acids concentration and cellular responses to high versus low concentration of glutamine and glucose based on a Chinese hamster ovary cell-line where amino acids data were available. The model contained 192 parameters with 26 measured cell culture variables. Most of the sensitive parameters were able to be identified using the Sobol' method of Global Sensitivity Analysis. The model could capture the main trends of key variables and be used to search for the optimal working range of the controllable variables. But uncertainties in the sensitive model parameters caused non-negligible variations in the model-based optimisation results. It is recommended to couple such off-line optimisation with on-line measurements of a few major variables to tackle the real-time uncertain nature of the complex cell culture system.Open acces

Nuclear speckle dynamics and function of speckle association in gene expression

Nuclear speckles have been studied intensively for a long time. Accumulating evidence has suggested that nuclear speckles have a dynamic structure, and are associated with a significant fraction of active chromosome regions and genes. However, their mobility and the regulation mechanism of their number and size are still poorly understood. Importantly, the functional significance of the speckle-gene association also remains unclear. To understand speckle dynamics and effects of speckle-gene association on gene expression better, I study the mobility of nuclear speckle bodies and its effect on morphological change of speckle size in chapter 2, and transcription enhancement by speckle-gene association in chapter 3. In chapter 2, I show significantly increased mobility of nuclear speckles after transcriptional inhibition, including long-range directed motion of one speckle towards another speckle, terminated by speckle fusion, over distances up to 4 µm and with velocities between 0.2-1.5 µm/min. Frequently, 3 or even 4 speckles follow very similar paths, with new speckles appearing along the path followed by a preceding speckle. Speckle movements and fusion events contribute to the formation of fewer but larger speckles after transcriptional inhibition. These speckle movements are not actin-dependent, but occur within chromatin-depleted channels enriched with small granules containing the speckle-marker protein SON. Our observations suggest a mechanism for long-range, directed nuclear speckle movements, contributing to the overall regulation of nuclear speckle number and size as well as the nuclear organization. In chapter 3, I show nuclear speckle association results in several-fold transcriptional amplification of Hsp70 genes. Hsp70 BAC transgenes and endogenous genes turn on 2-4 mins after heat shock irrespective of their distance to nuclear speckles. However, I observe 12-56-fold and 3-7-fold higher transcription levels for speckle-associated Hsp70 transgenes and endogenous genes, respectively, after 1-2 hrs heat shock. Several-fold higher transcription levels for several genes flanking the Hsp70 locus also correlate with speckle-association at 37 ℃. Live-cell imaging reveals this modulation of Hsp70 transcription temporally correlates with speckle association/disassociation. Our results demonstrate stochastic gene expression dependent on positioning relative to a liquid-droplet nuclear compartment enriched in RNA processing and transcription-related factors through a “transcriptional amplification” mechanism, which is distinct from transcriptional bursting

Methods for construction and analysis of computational models in systems biology: applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis

SOLID-SHELL FINITE ELEMENT MODELS FOR EXPLICIT SIMULATIONS OF CRACK PROPAGATION IN THIN STRUCTURES

Crack propagation in thin shell structures due to cutting is conveniently simulated using explicit finite element approaches, in view of the high nonlinearity of the problem. Solidshell elements are usually preferred for the discretization in the presence of complex material behavior and degradation phenomena such as delamination, since they allow for a correct representation of the thickness geometry. However, in solid-shell elements the small thickness leads to a very high maximum eigenfrequency, which imply very small stable time-steps. A new selective mass scaling technique is proposed to increase the time-step size without affecting accuracy. New ”directional” cohesive interface elements are used in conjunction with selective mass scaling to account for the interaction with a sharp blade in cutting processes of thin ductile shells

Bioprocess Monitoring and Control

Process monitoring and control are fundamental to all processes; this holds especially for bioprocesses, due to their complex nature. Usually, bioprocesses deal with living cells, which have their own regulatory systems. It helps to adjust the cell to its environmental condition. This must not be the optimal condition that the cell needs to produce whatever is desired. Therefore, a close monitoring of the cell and its environment is essential to provide optimal conditions for production. Without measurement, no information of the current process state is obtained. In this book, methods and techniques are provided for the monitoring and control of bioprocesses. From new developments for sensors, the application of spectroscopy and modelling approaches, the estimation and observer implementation for ethanol production and the development and scale-up of various bioprocesses and their closed loop control information are presented. The processes discussed here are very diverse. The major applications are cultivation processes, where microorganisms were grown, but also an incubation process of bird’s eggs, as well as an indoor climate control for humans, will be discussed. Altogether, in 12 chapters, nine original research papers and three reviews are presented

Doctor of Philosophy

dissertationThe nervous system is comprised of an estimated 100 billion individual neurons, which are connected to one another to form a network that senses environmental stimuli and coordinates the organism's behavior. Because of the complexity of the nervous system, deciphering the developmental processes and adult wiring diagram has proved challenging. A number of axon guidance molecules have been identified; however, the means by which they guide billions of axons to their target cells in vivo remains poorly understood. Several axon guidance molecules have been found to be bifunctional, meaning they can elicit different growth cone responses depending on the presence or absence of other molecules, such as growth cone receptors, intracellular signal transduction molecules, or extracellular modulators. Axon sorting within axon tracts is perhaps a means by which axons are presorted to make a precise connection on their target cells. The zebrafish, Danio rerio, is an ideal model organism to study vertebrate axon guidance and axon sorting due to its external fertilization, optical transparency, amenability to forward genetics, and ease of making transgenic lines. In order to study axon guidance within the zebrafish retinotectal system, I developed a new method of misexpressing genes. Local misexpression can be induced by using a modified soldering iron in transgenic zebrafish in which a gene of interest is driven by a heat shock promoter. This method allowed me to examine the mechanisms by which Slit1a and Slit2 guide axons from the retina to the optic tectum. I determined the expression pattern of Slits in the zebrafish and used antisense morpholino technology to knock down Slit1a. The iv resultant axon guidance errors indicated that Slit1a acts to guide retinal axons through the optic tract. I then misexpressed Slit1a and Slit2 near the optic tract to observe their effect on axons. I found that both proteins appeared to attract retinal axons. Additionally, I saw that Slit2 seems to attract retinal axons earlier in the retinotectal pathway, at the optic chiasm. I also report on a new method, to whose development I contributed, for automated tracking of axons through electron microscopy datasets. Taken together, my results add new methods to the endeavor of mapping neural connectivity and development, and suggest a new role for Slits in axon guidance