Quantitative Biology

The emerging era of personalized medicine relies on medical decisions, practices, and products being tailored to the individual patient. Point-of-care systems, at the heart of this model, play two important roles. First, they are required for identifying subjects for optimal therapies based on their genetic make-up and epigenetic profile. Second, they will be used for assessing the progression of such therapies. Central to this vision is designing systems that, with minimal user-intervention, can transduce complex signals from biosystems in complement with clinical information to inform medical decision within point-of-care settings. To reach our ultimate goal of developing point-of-care systems and realizing personalized medicine, we are taking a multistep systems-level approach towards understanding cellular processes and biomolecular profiles, to quantify disease states and external interventions.

The more we learn about the cytoplasm of cells, the more we realise that the cytoplasm is not uniform but instead is highly inhomogeneous. In any inhomogeneous solution, there are concentration gradients, and particles move either up or down these gradients due to a mechanism called diffusiophoresis. I estimate that inside metabolically active cells, the dynamics of particles can be strongly accelerated by diffusiophoresis, provided that they are at least tens of nanometres across. The dynamics of smaller objects, such as single proteins are largely unaffected.

Recent experimental results have shown that active enzymes can diffuse faster when they are in the presence of their substrates. Fluorescence correlation spectroscopy (FCS), which relies on analyzing the fluctuations in fluorescence intensity signal to measure the diffusion coefficient of particles, has typically been employed in most of the prior studies. However, flaws in the FCS method, due to its high sensitivity to the environment, have recently been evaluated, calling the prior diffusion results into question. It behooves us to adopt complimentary and direct methods to measure the mobility of enzymes in solution. Herein, we use a novel technique of direct single-molecule imaging to observe the diffusion of single enzymes. This technique is less sensitive to intensity fluctuations and gives the diffusion coefficient directly based on the trajectory of the enzymes. Our measurements recapitulate that enzyme diffusion is enhanced in the presence of its substrate and find that the relative increase in diffusion of a single enzyme is even higher than those previously reported using FCS. We also use this complementary method to test if the total enzyme concentration affects the relative increase in diffusion and if enzyme oligomerization state changes during catalytic turnover. We find that the diffusion increase is independent of the total background concentration of enzyme and the catalysis of substrate does not change the oligomerization state of enzymes.

A discrete-state model of the F1-ATPase molecular motor is developed which describes not only the dependences of the rotation and ATP consumption rates on the chemical concentrations of ATP, ADP, and inorganic phosphate, but also on mechanical control parameters such as the friction coefficient and the external torque. The dependence on these mechanical parameters is given to the discrete-state model by fitting its transition rates to the continuous-angle model of P. Gaspard and E. Gerritsma [J. Theor. Biol. 247 (2007) 672-686]. This discrete-state model describes the behavior of the F1 motor in the regime of tight coupling between mechanical motion and chemical reaction. In this way, kinetic and thermodynamic properties of the F1 motor are obtained such as the Michaelis-Menten dependence of the rotation and ATP consumption rates on ATP concentration and its extension in the presence of ADP and Pi, their dependences on friction and external torque, as well as the chemical and mechanical thermodynamic efficiencies.

Following recent discoveries of colocalization of downstream-regulating genes in living cells, the impact of the spatial distance between such genes on the kinetics of gene product formation is increasingly recognized. We here show from analytical and numerical analysis that the distance between a transcription factor (TF) gene and its target gene drastically affects the speed and reliability of transcriptional regulation in bacterial cells. For an explicit model system we develop a general theory for the interactions between a TF and a transcription unit. The observed variations in regulation efficiency are linked to the magnitude of the variation of the TF concentration peaks as a function of the binding site distance from the signal source. Our results support the role of rapid binding site search for gene colocalization and emphasize the role of local concentration differences.

In early development, regulation of transcription results in precisely positioned and highly reproducible expression patterns that specify cellular identities. How transcription, a fundamentally noisy molecular process, is regulated to achieve reliable embryonic patterning remains unclear. In particular, it is unknown how gene-specific regulation mechanisms affect kinetic rates of transcription, and whether there are common, global features that govern these rates across a genetic network. Here, we measure nascent transcriptional activity in the gap gene network of early Drosophila embryos and characterize the variability in absolute activity levels across expression boundaries. We demonstrate that boundary formation follows a common transcriptional principle: a single control parameter determines the distribution of transcriptional activity, regardless of gene identity, boundary position, or enhancer-promoter architecture. By employing a minimalist model of transcription, we infer kinetic rates of transcriptional bursting for these patterning genes; we find that the key regulatory parameter is the fraction of time a gene is in an actively transcribing state, while the rate of Pol II loading appears globally conserved. These results point to a universal simplicity underlying the apparently complex transcriptional processes responsible for early embryonic patterning and indicate a path to general rules in transcriptional regulation.

Do biological cells sense time by the number of their divisions, a process that ends at senescence? We consider the question "can the cell's perception of time be expressed through the length of the shortest telomere?" The answer is that the absolute time before senescence cannot be expressed by the telomere's length and that a cell can survive many more divisions than intuitively expected. This apparent paradox is due to shortening and elongation of the telomere, which suggests a random walk model of the telomere's length. The model indicates two phases, first, a determinist drift of the length toward a quasi-equilibrium state, and second, persistence of the length near an attracting state for the majority of divisions prior to senescence. The measure of stability of the latter phase is the expected number of divisions at the attractor ("lifetime") prior to crossing a threshold to senescence. The telomerase regulates stability by creating an effective potential barrier that separates statistically the shortest lifetime from the next shortest. The random walk has to overcome the barrier in order to extend the range of the first regime. The model explains how random telomere dynamics underlies the extension of cell survival time.

Plasmodium falciparum is the parasite that causes the most severe form of malaria. Currently, science has been established about its cellular structures, its metabolic processes, and even the molecular structures of its intrinsic membrane proteins responsible for transporting water, nutrient, and waste molecules across the parasite plasma membrane (PPM). I hypothesize that Plasmodium falciparum has an Achilles' heel that can be attacked with erythritol, the well-known sweetener that is classified as generally safe. Most organisms have in their cell membrane two types of water-channel proteins: aquaporins to maintain hydro-homeostasis across the membrane and aquaglyceroporins to uptake glycerols etc. In contrast, P. falciparum has only one type of such proteins---the multi-functional aquaglyceroporin (PfAQP) expressed in the PPM---to do both jobs. Moreover, the parasite also uses PfAQP to excrete its metabolic wastes (ammonia included) produced at a very high rate in the blood stage. This extremely high efficiency of the bug using one protein for multiple essential tasks makes the parasite fatally vulnerable. Erythritol in the blood stream can kill the parasite by clogging up its PfAQP channel that needs to be open for maintaining hydro-homeostasis and for excreting toxic wastes across the bug's PPM. In vitro tests are to measure the growth/death rate of P. falciparum in blood with various erythritol concentrations. In vivo experiments are to administer groups of infected mice with various doses of erythritol and monitor the parasite growth levels from blood samples drawn from each group. Clinic trials can be performed to observe the added effects of administering to patients erythritol along with the known drugs because erythritol was classified as a safe food ingredient.

During beer production, yeast generate ethanol that is exported to the extracellular environment where it accumulates. Depending on the initial carbohydrate concentration in the wort a high concentration of ethanol can be achieved in beer, often higher than 20% (v/v). It is noteworthy that the effects of elevated ethanol concentrations generated during beer fermentation resemble those of heat shock stress, with similar responses observed in both situations, such as the activation of proteostasis and protein quality control mechanisms in different cell compartments, including endoplasmic reticulum (ER), mitochondria, and cytosol. Despite the extensive published molecular and biochemical data regarding the roles of proteostasis in different organelles of yeast cells, little is known about how this mechanism impacts beer fermentation and how different proteostasis mechanisms found in ER, mitochondria, and cytosol communicate with each other during ethanol/fermentative stress. Supporting this integrative view, transcriptome data analysis was applied using publicly available information for a lager yeast strain grown under in beer production conditions. The transcriptome data indicated upregulation of genes that encode chaperones, co-chaperones, unfolded protein response elements in ER and mitochondria, ubiquitin ligases, proteasome components, N-glycosylation quality control pathway proteins, and components of processing bodies (p-bodies) and stress granules (SGs) during lager beer fermentation. Thus, the main purpose of this hypothesis and theory manuscript is to provide a concise picture of how inter-organellar proteostasis mechanisms are connected with one another and with biological processes that may modulate the viability and/or vitality of yeast populations during HG/VHG beer fermentation and serial repitching.

In this work we study, at the single molecular level, the thermodynamic and dynamic characteristics of an enzymatic reaction comprising a rate limiting step. We investigate how the stability of the enzyme-state stationary probability distribution, the reaction velocity, and its efficiency of energy conversion depend on the system parameters. We employ in this study a recently introduced formalism for performing a multiscale thermodynamic analysis in continuous-time discrete-state stochastic systems.