Periodic fermentor yield and enhanced product enrichment from autonomous oscillations

Dual-Color Monitoring Overcomes the Limitations of Single Bioluminescent Reporters in Fast-Growing Microbes and Reveals Phase-Dependent Protein Productivity during the Metabolic Rhythms of Saccharomyces cerevisiae

Luciferase is a useful, noninvasive reporter of gene regulation that can be continuously monitored over long periods of time; however, its use is problematic in fast-growing microbes like bacteria and yeast because rapidly changing cell numbers and metabolic states also influence bioluminescence, thereby confounding the reporter's signal. Here we show that these problems can be overcome in the budding yeast Saccharomyces cerevisiae by simultaneously monitoring bioluminescence from two different colors of beetle luciferase, where one color (green) reports activity of a gene of interest, while a second color (red) is stably expressed and used to continuously normalize green bioluminescence for fluctuations in signal intensity that are unrelated to gene regulation. We use this dual-luciferase strategy in conjunction with a light-inducible promoter system to test whether different phases of yeast respiratory oscillations are more suitable for heterologous protein production than others. By using pulses of light to activate production of a green luciferase while normalizing signal variation to a red luciferase, we show that the early reductive phase of the yeast metabolic cycle produces more luciferase than other phases.

Cell cycle dynamics in a response/signalling feedback system with a gap

We consider a dynamical model of cell cycles of n cells in a culture in which cells in one specific phase (S for signalling) of the cell cycle produce chemical agents that influence the growth/cell cycle progression of cells in another phase (R for responsive). In the case that the feedback is negative, it is known that subpopulations of cells tend to become clustered in the cell cycle; while for a positive feedback, all the cells tend to become synchronized. In this paper, we suppose that there is a gap between the two phases. The gap can be thought of as modelling the physical reality of a time delay in the production and action of the signalling agents. We completely analyse the dynamics of this system when the cells are arranged into two cell cycle clusters. We also consider the stability of certain important periodic solutions in which clusters of cells have a cyclic arrangement and there are just enough clusters to allow interactions between them. We find that the inclusion of a small gap does not greatly alter the global dynamics of the system; there are still large open sets of parameters for which clustered solutions are stable. Thus, we add to the evidence that clustering can be a robust phenomenon in biological systems. However, the gap does effect the system by enhancing the stability of the stable clustered solutions. We explain this phenomenon in terms of contraction rates (Floquet exponents) in various invariant subspaces of the system. We conclude that in systems for which these models are reasonable, a delay in signalling is advantageous to the emergence of clustering.

Dynamics of oscillatory phenotypes in Saccharomyces cerevisiae reveal a network of genome-wide transcriptional oscillators

Genetic and environmental factors are well-studied influences on phenotype; however, time is a variable that is rarely considered when studying changes in cellular phenotype. Time-resolved microarray data revealed genome-wide transcriptional oscillation in a yeast continuous culture system with ∼ 2 and ∼ 4 h periods. We mapped the global patterns of transcriptional oscillations into a 3D map to represent different cellular phenotypes of redox cycles. This map shows the dynamic nature of gene expression in that transcripts are ordered and coupled to each other through time and concentration space. Although cells differed in oscillation periods, transcripts involved in certain processes were conserved in a deterministic way. When oscillation period lengthened, the peak to trough ratio of transcripts increased and the fraction of cells in the unbudded (G0/G1) phase of the cell division cycle increased. Decreasing the glucose level in the culture medium was one way to increase the redox cycle, possibly from changes in metabolic flux. The period may be responding to lower glucose levels by increasing the fraction of cells in G1 and reducing S-phase gating so that cells can spend more time in catabolic processes. Our results support that gene transcripts are coordinated with metabolic functions and the cell division cycle.

Simultaneous on-chip DC dielectrophoretic cell separation and quantitative separation performance characterization

Through integration of a MOSFET-based microfluidic Coulter counter with a dc-dielectrophoretic cell sorter, we demonstrate simultaneous on-chip cell separation and sizing with three different samples including 1) binary mixtures of polystyrene beads, 2) yeast cells of continuous size distribution, and 3) mixtures of 4T1 tumor cells and murine bone marrow cells. For cells with continuous size distribution, it is found that the receiver operator characteristic analysis is an ideal method to characterize the separation performance. The characterization results indicate that dc-DEP separation performance degrades as the sorting throughput (cell sorting rate) increases, which provides insights into the design and operation of size-based microfluidic cell separation.

Clustering in cell cycle dynamics with general response/signaling feedback

Motivated by experimental and theoretical work on autonomous oscillations in yeast, we analyze ordinary differential equations models of large populations of cells with cell-cycle dependent feedback. We assume a particular type of feedback that we call responsive/signaling (RS), but do not specify a functional form of the feedback. We study the dynamics and emergent behavior of solutions, particularly temporal clustering and stability of clustered solutions. We establish the existence of certain periodic clustered solutions as well as "uniform" solutions and add to the evidence that cell-cycle dependent feedback robustly leads to cell-cycle clustering. We highlight the fundamental differences in dynamics between systems with negative and positive feedback. For positive feedback systems the most important mechanism seems to be the stability of individual isolated clusters. On the other hand we find that in negative feedback systems, clusters must interact with each other to reinforce coherence. We conclude from various details of the mathematical analysis that negative feedback is most consistent with observations in yeast experiments.

Measurement of the volume growth rate of single budding yeast with the MOSFET-based microfluidic Coulter counter

We report on measurements of the volume growth rate of ten individual budding yeast cells using a recently developed MOSFET-based microfluidic Coulter counter. The MOSFET-based microfluidic Coulter counter is very sensitive, provides signals that are immune from the baseline drift, and can work with cell culture media of complex composition. These desirable features allow us to directly measure the volume growth rate of single cells of Saccharomyces cerevisiae LYH3865 strain budding yeast in YNB culture media over a whole cell cycle. Results indicate that all budding yeast follow a sigmoid volume growth profile with reduced growth rates at the initial stage before the bud emerges and the final stage after the daughter gets mature. Analysis of the data indicates that even though all piecewise linear, Gomperitz, and Hill's function models can fit the global growth profile equally well, the data strongly support local exponential growth phenomenon. Accurate volume growth measurements are important for applications in systems biology where quantitative parameters are required for modeling and simulation.

ODE, RDE and SDE models of cell cycle dynamics and clustering in yeast

Biologists have long observed periodic-like oxygen consumption oscillations in yeast populations under certain conditions, and several unsatisfactory explanations for this phenomenon have been proposed. These ‘autonomous oscillations’ have often appeared with periods that are nearly integer divisors of the calculated doubling time of the culture. We hypothesize that these oscillations could be caused by a form of cell cycle synchronization that we call clustering. We develop some novel ordinary differential equation models of the cell cycle. For these models, and for random and stochastic perturbations, we give both rigorous proofs and simulations showing that both positive and negative growth rate feedback within the cell cycle are possible agents that can cause clustering of populations within the cell cycle. It occurs for a variety of models and for a broad selection of parameter values. These results suggest that the clustering phenomenon is robust and is likely to be observed in nature. Since there are necessarily an integer number of clusters, clustering would lead to periodic-like behaviour with periods that are nearly integer divisors of the period of the cell cycle. Related experiments have shown conclusively that cell cycle clustering occurs in some oscillating yeast cultures.