The clock in growing hyphae and their synchronization in Neurospora crassa.

Utilizing a microfluidic chip with serpentine channels, we inoculated the chip with an agar plug with Neurospora crassa mycelium and successfully captured individual hyphae in channels. For the first time, we report the presence of an autonomous clock in hyphae. Fluorescence of a mCherry reporter gene driven by a clock-controlled gene-2 promoter (ccg-2p) was measured simultaneously along hyphae every half an hour for at least 6 days. We entrained single hyphae to light over a wide range of day lengths, including 6,12, 24, and 36 h days. Hyphae tracked in individual serpentine channels were highly synchronized (K = 0.60-0.78). Furthermore, hyphae also displayed temperature compensation properties, where the oscillation period was stable over a physiological range of temperatures from 24 °C to 30 °C (Q10 = 1.00-1.10). A Clock Tube Model developed could mimic hyphal growth observed in the serpentine chip and provides a mechanism for the stable banding patterns seen in race tubes at the macroscopic scale and synchronization through molecules riding the growth wave in the device.

The macroscopic limit to synchronization of cellular clocks in single cells of Neurospora crassa.

We determined the macroscopic limit for phase synchronization of cellular clocks in an artificial tissue created by a "big chamber" microfluidic device to be about 150,000 cells or less. The dimensions of the microfluidic chamber allowed us to calculate an upper limit on the radius of a hypothesized quorum sensing signal molecule of 13.05 nm using a diffusion approximation for signal travel within the device. The use of a second microwell microfluidic device allowed the refinement of the macroscopic limit to a cell density of 2166 cells per fixed area of the device for phase synchronization. The measurement of averages over single cell trajectories in the microwell device supported a deterministic quorum sensing model identified by ensemble methods for clock phase synchronization. A strong inference framework was used to test the communication mechanism in phase synchronization of quorum sensing versus cell-to-cell contact, suggesting support for quorum sensing. Further evidence came from showing phase synchronization was density-dependent.

Competition between DNA Methylation, Nucleotide Synthesis, and Antioxidation in Cancer versus Normal Tissues.

Global DNA hypomethylation occurs in many cancer types, but there is no explanation for its differential occurrence or possible impact on cancer cell physiology. Here we address these issues with a computational study of genome-scale DNA methylation in 16 cancer types. Specifically, we identified (i) a possible determinant for global DNA methylation in cancer cells and (ii) a relationship between levels of DNA methylation, nucleotide synthesis, and intracellular oxidative stress in cells. We developed a system of kinetic equations to capture the metabolic relations among DNA methylation, nucleotide synthesis, and antioxidative stress response, including their competitions for methyl and sulfur groups, based on known information about one-carbon metabolism and trans-sulfuration pathways. We observed a kinetic-based regulatory mechanism that controls reaction rates of the three competing processes when their shared resources are limited, particularly when the nucleotide synthesis rates or oxidative states are high. The combination of this regulatory mechanism and the need for rapid nucleotide synthesis, as well as high production of glutathione dictated by cancer-driving forces, led to the nearly universal observations of reduced global DNA methylation in cancer. Our model provides a natural explanation for differential global DNA methylation levels across cancer types and supports the observation that more malignant cancers tend to exhibit reduced DNA methylation levels. Insights obtained from this work provide useful information about the complexities of cancer due to interplays among competing, dynamic biological processes. Cancer Res; 77(15); 4185-95. ©2017 AACR.

Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development.

Collective cell movement is critical to the emergent properties of many multicellular systems, including microbial self-organization in biofilms, embryogenesis, wound healing, and cancer metastasis. However, even the best-studied systems lack a complete picture of how diverse physical and chemical cues act upon individual cells to ensure coordinated multicellular behavior. Known for its social developmental cycle, the bacterium Myxococcus xanthus uses coordinated movement to generate three-dimensional aggregates called fruiting bodies. Despite extensive progress in identifying genes controlling fruiting body development, cell behaviors and cell-cell communication mechanisms that mediate aggregation are largely unknown. We developed an approach to examine emergent behaviors that couples fluorescent cell tracking with data-driven models. A unique feature of this approach is the ability to identify cell behaviors affecting the observed aggregation dynamics without full knowledge of the underlying biological mechanisms. The fluorescent cell tracking revealed large deviations in the behavior of individual cells. Our modeling method indicated that decreased cell motility inside the aggregates, a biased walk toward aggregate centroids, and alignment among neighboring cells in a radial direction to the nearest aggregate are behaviors that enhance aggregation dynamics. Our modeling method also revealed that aggregation is generally robust to perturbations in these behaviors and identified possible compensatory mechanisms. The resulting approach of directly combining behavior quantification with data-driven simulations can be applied to more complex systems of collective cell movement without prior knowledge of the cellular machinery and behavioral cues.

Synchronizing stochastic circadian oscillators in single cells of Neurospora crassa.

The synchronization of stochastic coupled oscillators is a central problem in physics and an emerging problem in biology, particularly in the context of circadian rhythms. Most measurements on the biological clock are made at the macroscopic level of millions of cells. Here measurements are made on the oscillators in single cells of the model fungal system, Neurospora crassa, with droplet microfluidics and the use of a fluorescent recorder hooked up to a promoter on a clock controlled gene-2 (ccg-2). The oscillators of individual cells are stochastic with a period near 21 hours (h), and using a stochastic clock network ensemble fitted by Markov Chain Monte Carlo implemented on general-purpose graphical processing units (or GPGPUs) we estimated that >94% of the variation in ccg-2 expression was stochastic (as opposed to experimental error). To overcome this stochasticity at the macroscopic level, cells must synchronize their oscillators. Using a classic measure of similarity in cell trajectories within droplets, the intraclass correlation (ICC), the synchronization surface ICC is measured on >25,000 cells as a function of the number of neighboring cells within a droplet and of time. The synchronization surface provides evidence that cells communicate, and synchronization varies with genotype.

Time-resolved NMR: extracting the topology of complex enzyme networks.

The use of nondestructive NMR spectroscopy for enzymatic studies offers unique opportunities to identify nearly all enzymatic byproducts and detect unstable short-lived products or intermediates at the molecular level; however, numerous challenges must be overcome before it can become a widely used tool. The biosynthesis of acetyl-coenzyme A (acetyl-CoA) by acetyl-CoA synthetase is used here as a case study for the development of an analytical NMR-based time-course assay platform. We describe an algorithm to deconvolve superimposed spectra into spectra for individual molecules, and further develop a model to simulate the acetyl-CoA synthetase enzyme reaction network using the data derived from time-course NMR. Simulation shows indirectly that synthesis of acetyl-CoA is mediated via an enzyme-bound intermediate (possibly acetyl-AMP) and is accompanied by a nonproductive loss from an intermediate. The ability to predict enzyme function based on partial knowledge of the enzymatic pathway topology is also discussed.

Cellulose hydrolysis in evolving substrate morphologies III: time-scale analysis.

We present a time-scale analysis for the enzymatic hydrolysis of solid cellulosic substrates, based on our recently developed kinetic model (Zhou et al., 2009a, Biotechnol Bioeng 104:261-274; Zhou et al., 2009b, Biotechnol Bioeng 104:275-289) which incorporates both enzymatic chain fragmentation and hydrolytic time evolution of the solid substrate morphology. Analytical order-of-magnitude estimates of the relevant single-layer chain depolymerization times are first discussed. These time-scale estimates for pure and mixed enzyme systems can be employed to calculate the degree of synergy between endo- and exo-acting enzymes in a mixed enzyme system. By the way of a quasi-steady-state approximation which allows for a greatly simplified analytical solution of the model, we also explain the origin and give order-of-magnitude estimates of the two characteristic hydrolysis time scales which arise in this model when the solid substrate morphology is taken into account. These analytically derived time-scale relations explain how the embedding of cellulose chains in a solid substrate acts as a crucial rate-limiting factor and results in a substantial slowing down of the hydrolytic conversion process, compared to a hypothetical substrate of immediately enzyme-accessible, isolated chains. The analytical time-scale results are verified by numerical simulations and compared to experimental observations.

Cellulose hydrolysis in evolving substrate morphologies I: A general modeling formalism.

We develop a general framework for a realistic rate equation modeling of cellulose hydrolysis using non-complexed cellulase. Our proposed formalism, for the first time, takes into account explicitly the time evolution of the random substrate morphology resulting from the hydrolytic cellulose chain fragmentation and solubilization. This is achieved by integrating novel geometrical concepts to quantitatively capture the time-dependent random morphology, together with the enzymatic chain fragmentation, into a coupled morphology-plus-kinetics rate equation approach. In addition, an innovative site number representation, based on tracking available numbers of beta(1,4) glucosidic bonds, of different "site" types, exposed to attacks by different enzyme types, is presented. This site number representation results in an ordinary differential equation (ODE) system, with a substantially reduced ODE system size, compared to earlier chain fragmentation kinetics approaches. This formalism enables us to quantitatively simulate both the hydrolytically evolving random substrate morphology and the profound, and heretofore neglected, morphology effects on the hydrolysis kinetics. By incorporating the evolving morphology on an equal footing with the hydrolytic chain fragmentation, our formalism provides a framework for the realistic modeling of the entire solubilization process, beyond the short-time limit and through near-complete hydrolytic conversion. As part I of two companion papers, the present paper focuses on the development of the general modelling formalism. Results and testable experimental predictions from detailed numerical simulations are presented in part II.

Cellulose hydrolysis in evolving substrate morphologies II: Numerical results and analysis.

Numerical simulation results are presented for a cellulose hydrolysis model which incorporates both the enzymatic glucan chain fragmentation kinetics and the hydrolytic substrate morphology evolution within the general framework of our companion article I. To test the local Poisson (LP) approximation employed in the site number formalism of I, we numerically compare it to the corresponding exact chain number formalism of I. The LP results agree to very high accuracy with the exact chain number kinetics, assuming realistic parameters. From simulations of different types of random and non-random model morphologies, we then show that the details of the random substrate morphology distribution, and its hydrolytic time evolution, profoundly affect the hydrolysis kinetics. Essential, likely very general, experimentally testable features of such morphology-based hydrolysis models are (i) the existence of two distinct time scales, associated with the hydrolysis of the outermost surface-exposed cellulose chains and, respectively, of the entire substrate; (ii) a strongly morphology-dependent hydrolysis slow-down effect, which has also been observed in previous experimental work. Our results also suggest that previously proposed non-morphologic chain fragmentation models can only be applied to describe the hydrolytic short-time behavior in the low enzyme limit. Further experiments to test our modeling framework and its potential applications to the optimization of the hydrolytic conversion process are discussed.

Genome-wide expression analysis of genetic networks in Neurospora crassa.

The products of five structural genes and two regulatory genes of the qa gene cluster of Neurospora crassa control the metabolism of quinic acid (QA) as a carbon source. A detailed genetic network model of this metabolic process has been reported. This investigation is designed to expand the current model of the QA reaction network. The ensemble method of network identification was used to model RNA profiling data on the qa gene cluster. Through microarray and cluster analysis, genome-wide identification of RNA transcripts associated with quinic acid metabolism in N. crassa is described and suggests a connection to other metabolic circuits. More than 100 genes whose products include carbon metabolism, protein degradation and modification, amino acid metabolism and ribosome synthesis appear to be connected to quinic acid metabolism. The core of the qa gene cluster network is validated with respect to RNA profiling data obtained from microarrays.

A genetic network for the clock of Neurospora crassa.

A diverse array of organisms from bacteria to humans may have evolved the ability to tell time in the presence or absence of external environmental cues. In the lowly bread mould, Neurospora crassa, biomolecular reactions involving the white-collar-1 (wc-1), white-collar-2 (wc-2), and frequency (frq) genes and their products constitute building blocks of a biological clock. Here we use genetic network models to explain quantitatively, from a systems perspective, how these building blocks interact, and how a complex trait like clock oscillation emerges from these interactions. We use a recently developed method of genetic network identification to find an ensemble of oscillating network models quantitatively consistent with available RNA and protein profiling data on the N. crassa clock. Predicted key features of the N. crassa clock system are a dynamically frustrated closed feedback loop, cooperativity in frq gene activation, and/or WC-1/WC-2 protein complex deactivation and substantial posttranscriptional enhancement of wc-1 RNA lifetime. Measuring the wc-1 mRNA lifetime provides a critical test of the genetic networks.