Polyglutamine (polyQ) expansion in exon1 (XN1) of the huntingtin protein is linked to Huntington's disease. When the number of glutamines exceeds a threshold of approximately 36–40 repeats, XN1 can readily form amyloid aggregates similar to those associated with disease. Many experiments suggest that misfolding of monomeric XN1 plays an important role in the length-dependent aggregation. Elucidating the misfolding of a XN1 monomer can help determine the molecular mechanism of XN1 aggregation and potentially help develop strategies to inhibit XN1 aggregation. The flanking sequences surrounding the polyQ region can play a critical role in determining the structural rearrangement and aggregation mechanism of XN1. Few experiments have studied XN1 in its entirety, with all flanking regions. To obtain structural insights into the misfolding of XN1 toward amyloid aggregation, we perform molecular dynamics simulations on monomeric XN1 with full flanking regions, a variant missing the polyproline regions, which are hypothesized to prevent aggregation, and an isolated polyQ peptide (Qn). For each of these three constructs, we study glutamine repeat lengths of 23, 36, 40 and 47. We find that polyQ peptides have a positive correlation between their probability to form a β-rich misfolded state and their expansion length. We also find that the flanking regions of XN1 affect its probability to^x_page_count=28 form a β-rich state compared to the isolated polyQ. Particularly, the polyproline regions form polyproline type II helices and decrease the probability of the polyQ region to form a β-rich state. Additionally, by lengthening polyQ, the first N-terminal 17 residues are more likely to adopt a β-sheet conformation rather than an α-helix conformation. Therefore, our molecular dynamics study provides a structural insight of XN1 misfolding and elucidates the possible role of the flanking sequences in XN1 aggregation.

Summary Actin regulators facilitate cell migration by controlling cell protrusion architecture and dynamics. As the behavior of individual actin regulators becomes clear, we must address why cells require multiple regulators with similar functions and how they cooperate to create diverse protrusions. We characterized Diaphanous and Enabled as a model, using complementary approaches: cell culture, biophysical analysis, and Drosophila morphogenesis. We found Dia and Ena have distinct biochemical properties that contribute to the different protrusion morphologies each induces. Dia is a more processive, faster elongator, paralleling the long, stable filopodia it induces in vivo, while Ena promotes filopodia with more dynamic changes in number, length and lifetime. Acting together, Ena and Dia induce protrusions distinct from those induced by either alone, with Ena reducing Dia-driven protrusion length and number. Consistent with this, EnaEVH1 binds Dia directly and inhibits DiaFH1FH2-mediated nucleation in vitro. Finally, Ena rescues hemocyte migration defects caused by activated Dia.

Biofilms formed in the middle ear by nontypeable Haemophilus influenzae (NTHI) are central to the chronicity, recurrence, and refractive nature of otitis media (OM). However, mechanisms that underlie the emergence of specific NTHI biofilm structures are unclear. We combined computational analysis tools and in silico modeling rooted in statistical physics with confocal imaging of NTHI biofilms formed in vitro during static culture in order to identify mechanisms that give rise to distinguishing morphological features. Our analysis of confocal images of biofilms formed by NTHI strain 86-028NP using pair correlations of local bacterial densities within sequential planes parallel to the substrate showed the presence of fractal structures of short length scales (≤10 μm). The in silico modeling revealed that extracellular DNA (eDNA) and type IV pilus (Tfp) expression played important roles in giving rise to the fractal structures and allowed us to predict a substantial reduction of these structures for an isogenic mutant (ΔcomE) that was significantly compromised in its ability to release eDNA into the biofilm matrix and had impaired Tfp function. This prediction was confirmed by analysis of confocal images of in vitro ΔcomE strain biofilms. The fractal structures potentially generate niches for NTHI survival in the hostile middle ear microenvironment by dramatically increasing the contact area of the biofilm with the surrounding environment, facilitating nutrient exchange, and by generating spatial positive feedback to quorum signaling.

The ability to detect a chemical gradient is fundamental to many cellular processes. In multicellular organisms gradient sensing plays an important role in many physiological processes such as wound healing and development. Unicellular organisms use gradient sensing to move (chemotaxis) or grow (chemotropism) towards a favorable environment. Some cells are capable of detecting extremely shallow gradients, even in the presence of significant molecular-level noise. For example, yeast have been reported to detect pheromone gradients as shallow as 0.1 nM/μm. Noise reduction mechanisms, such as time-averaging and the internalization of pheromone molecules, have been proposed to explain how yeast cells filter fluctuations and detect shallow gradients. Here, we use a Particle-Based Reaction-Diffusion model of ligand-receptor dynamics to test the effectiveness of these mechanisms and to determine the limits of gradient sensing. In particular, we develop novel simulation methods for establishing chemical gradients that not only allow us to study gradient sensing under steady-state conditions, but also take into account transient effects as the gradient forms. Based on reported measurements of reaction rates, our results indicate neither time-averaging nor receptor endocytosis significantly improves the cell’s accuracy in detecting gradients over time scales associated with the initiation of polarized growth. Additionally, our results demonstrate the physical barrier of the cell membrane sharpens chemical gradients across the cell. While our studies are motivated by the mating response of yeast, we believe our results and simulation methods will find applications in many different contexts.

Biofilms formed by nontypeable Haemophilus influenzae (NTHI) bacteria play an important role in multiple respiratory tract diseases. Visual inspection of the morphology of biofilms formed during chronic infections shows distinct differences from biofilms formed in vitro. To better understand these differences, we analyzed images of NTHI biofilms formed in the middle ears of Chinchilla lanigera and developed an in silico agent-based model of the formation of NTHI biofilms in vivo. We found that, as in vitro, NTHI bacteria are organized in self-similar patterns; however, the sizes of NTHI clusters in vivo are more than 10-fold smaller than their in vitro counterparts. The agent-based model reproduced these patterns and suggested that smaller clusters occur due to elimination of planktonic NTHI cells by the host responses. Estimation of model parameters by fitting simulation results to imaging data showed that the effects of several processes in the model change during the course of the infection. IMPORTANCE Multiple respiratory illnesses are associated with formation of biofilms within the human airway by NTHI. However, a substantial amount of our understanding of the mechanisms that underlie NTHI biofilm formation is obtained from in vitro studies. Our in silico model that describes biofilm formation by NTHI within the middle ears of Chinchilla lanigera will help isolate processes potentially responsible for the differences between the morphologies of biofilms formed in vivo versus those formed in vitro. Thus, the in silico model can be used to glean mechanisms that underlie biofilm formation in vivo and connect those mechanisms to those obtained from in vitro experiments. The in silico model developed here can be extended to investigate potential roles of specific host responses (e.g., mucociliary clearance) on NTHI biofilm formation in vivo. The developed computational tools can also be used to analyze and describe biofilm formation by other bacterial species in vivo.

Many compounds that appear promising in preclinical species, fail in human clinical trials due to safety concerns. The FDA has strongly encouraged the application of modeling in drug development to improve product safety. This study illustrates how DILIsym, a computational representation of liver injury, was able to reproduce species differences in liver toxicity due to PF‐04895162 (ICA‐105665). PF‐04895162, a drug in development for the treatment of epilepsy, was terminated after transaminase elevations were observed in healthy volunteers (NCT01691274). Liver safety concerns had not been raised in preclinical safety studies. DILIsym, which integrates in vitro data on mechanisms of hepatotoxicity with predicted in vivo liver exposure, reproduced clinical hepatotoxicity and the absence of hepatotoxicity observed in the rat. Simulated differences were multifactorial. Simulated liver exposure was greater in humans than rats. The simulated human hepatotoxicity was demonstrated to be due to the interaction between mitochondrial toxicity and bile acid transporter inhibition; elimination of either mechanism from the simulations abrogated injury. The bile acid contribution occurred despite the fact that the IC50 for bile salt export pump (BSEP) inhibition by PF‐04895162 was higher (311 µmol/L) than that has been generally thought to contribute to hepatotoxicity. Modeling even higher PF‐04895162 liver exposures than were measured in the rat safety studies aggravated mitochondrial toxicity but did not result in rat hepatotoxicity due to insufficient accumulation of cytotoxic bile acid species. This investigative study highlights the potential for combined in vitro and computational screening methods to identify latent hepatotoxic risks and paves the way for similar and prospective studies.

In clinical trials of cannabidiol (CBD) for the treatment of seizures in patients with Dravet syndrome, Lennox–Gastaut syndrome, and tuberous sclerosis complex, elevations in serum alanine aminotransferase (ALT) > 3× the upper limit of normal were observed in some patents, but the incidence was much greater in patients who were receiving treatment with valproate (VPA) before starting CBD. To explore potential mechanisms underlying this interaction, we used DILIsym, a quantitative systems toxicology model, to predict ALT elevations in a simulated human population treated with CBD alone, VPA alone, and when CBD dosing was starting during treatment with VPA. We gathered in vitro data assessing the potential for CBD, the two major CBD metabolites, and VPA to cause hepatotoxicity via inhibition of bile acid transporters, mitochondrial dysfunction, and production of reactive oxygen species (ROS). Physiologically‐based pharmacokinetic models for CBD and VPA were used to predict liver exposure. DILIsym simulations predicted dose‐dependent ALT elevations from CBD treatment and this was predominantly driven by ROS production from the parent molecule. DILIsym also predicted VPA treatment to cause ALT elevations which were transient when mitochondrial biogenesis was incorporated into the model. Contrary to the clinical experience, simulation of 2 weeks treatment with VPA prior to introduction of CBD treatment did not predict an increase of the incidence of ALT elevations relative to CBD treatment alone. We conclude that the marked increased incidence of CBD‐associated ALT elevations in patients already receiving VPA is unlikely to involve the three major mechanisms of direct hepatotoxicity.

Otitis media (OM) is a common polymicrobial infection of the middle ear in children under the age of fifteen years. A widely used experimental strategy to analyze roles of specific phenotypes of bacterial pathogens of OM is to study changes in co-infection kinetics of bacterial populations in animal models when a wild type bacterial strain is replaced by a specific isogenic mutant strain in the co-inoculating mixtures. Since relationships between the OM bacterial pathogens within the host are regulated by many interlinked processes, connecting the changes in the co-infection kinetics to a bacterial phenotype can be challenging. We investigated middle ear co-infections in adult chinchillas (Chinchilla lanigera) by two major OM pathogens: nontypeable Haemophilus influenzae (NTHi) and Moraxella catarrhalis (Mcat), as well as isogenic mutant strains in each bacterial species. We analyzed the infection kinetic data using Lotka-Volterra population dynamics, Maximum Entropy inference, and Akaike Information Criteria (AIC) based model selection. We found that changes in relationships between the bacterial pathogens that were not anticipated in the design of the co-infection experiments involving mutant strains are common and were strong regulators of the co-infecting bacterial populations. The framework developed here allows for a systematic analysis of host-host variations of bacterial populations and small sizes of animal cohorts in coinfection experiments to quantify the role of specific mutant strains in changing the infection kinetics. Our combined approach can be used to analyze the functional footprint of mutant strains in regulating co-infection kinetics in models of experimental OM and other polymicrobial diseases.