Efficient Calculation of Steady State Probability Distribution for Stochastic Biochemical Reaction Network.

The Steady State (SS) probability distribution is an important quantity needed to characterize the steady state behavior of many stochastic biochemical networks. In this paper, we propose an efficient and accurate approach to calculating an approximate SS probability distribution from solution of the Chemical Master Equation (CME) under the assumption of the existence of a unique deterministic SS of the system. To find the approximate solution to the CME, a truncated state-space representation is used to reduce the state-space of the system and translate it to a finite dimension. The subsequent ill-posed eigenvalue problem of a linear system for the finite state-space can be converted to a well-posed system of linear equations and solved. The proposed strategy yields efficient and accurate estimation of noise in stochastic biochemical systems. To demonstrate the approach, we applied the method to characterize the noise behavior of a set of biochemical networks of ligand-receptor interactions for Bone Morphogenetic Protein (BMP) signaling. We found that recruitment of type II receptors during the receptor oligomerization by itself doesn\u27t not tend to lower noise in receptor signaling, but regulation by a secreted co-factor may provide a substantial improvement in signaling relative to noise. The steady state probability approximation method shortened the time necessary to calculate the probability distributions compared to earlier approaches, such as Gillespie\u27s Stochastic Simulation Algorithm (SSA) while maintaining high accuracy

Model-Based Analysis for Qualitative Data: An Application in Drosophila Germline Stem Cell Regulation.

Discovery in developmental biology is often driven by intuition that relies on the integration of multiple types of data such as fluorescent images, phenotypes, and the outcomes of biochemical assays. Mathematical modeling helps elucidate the biological mechanisms at play as the networks become increasingly large and complex. However, the available data is frequently under-utilized due to incompatibility with quantitative model tuning techniques. This is the case for stem cell regulation mechanisms explored in the Drosophila germarium through fluorescent immunohistochemistry. To enable better integration of biological data with modeling in this and similar situations, we have developed a general parameter estimation process to quantitatively optimize models with qualitative data. The process employs a modified version of the Optimal Scaling method from social and behavioral sciences, and multi-objective optimization to evaluate the trade-off between fitting different datasets (e.g. wild type vs. mutant). Using only published imaging data in the germarium, we first evaluated support for a published intracellular regulatory network by considering alternative connections of the same regulatory players. Simply screening networks against wild type data identified hundreds of feasible alternatives. Of these, five parsimonious variants were found and compared by multi-objective analysis including mutant data and dynamic constraints. With these data, the current model is supported over the alternatives, but support for a biochemically observed feedback element is weak (i.e. these data do not measure the feedback effect well). When also comparing new hypothetical models, the available data do not discriminate. To begin addressing the limitations in data, we performed a model-based experiment design and provide recommendations for experiments to refine model parameters and discriminate increasingly complex hypotheses

Label-Free Imaging of Lipid-Droplet Intracellular Motion in Early Drosophila Embryos Using Femtosecond-Stimulated Raman Loss Microscopy

AbstractLipid droplets are complex organelles that exhibit highly dynamic behavior in early Drosophila embryo development. Imaging lipid droplet motion provides a robust platform for the investigation of shuttling by kinesin and dynein motors, but methods for imaging are either destructive or deficient in resolution and penetration to study large populations of droplets in an individual embryo. Here we report real-time imaging and quantification of droplet motion in live embryos using a recently developed technique termed “femtosecond-stimulated Raman loss” microscopy. We captured long-duration time-lapse images of the developing embryo, tracked single droplet motion within large populations of droplets, and measured the velocity and turning frequency of each particle at different apical-to-basal depths and stages of development. To determine whether the quantities for speed and turning rate measured for individual droplets are sufficient to predict the population distributions of droplet density, we simulated droplet motion using a velocity-jump model. This model yielded droplet density distributions that agreed well with experimental observations without any model optimization or unknown parameter estimation, demonstrating the sufficiency of a velocity-jump process for droplet trafficking dynamics in blastoderm embryos

Analysis of Gap Gene Regulation in a 3D Organism-Scale Model of the Drosophila melanogaster Embryo

The axial bodyplan of Drosophila melanogaster is determined during a process called morphogenesis. Shortly after fertilization, maternal bicoid mRNA is translated into Bicoid (Bcd). This protein establishes a spatially graded morphogen distribution along the anterior-posterior (AP) axis of the embryo. Bcd initiates AP axis determination by triggering expression of gap genes that subsequently regulate each other's expression to form a precisely controlled spatial distribution of gene products. Reaction-diffusion models of gap gene expression on a 1D domain have previously been used to infer complex genetic regulatory network (GRN) interactions by optimizing model parameters with respect to 1D gap gene expression data. Here we construct a finite element reaction-diffusion model with a realistic 3D geometry fit to full 3D gap gene expression data. Though gap gene products exhibit dorsal-ventral asymmetries, we discover that previously inferred gap GRNs yield qualitatively correct AP distributions on the 3D domain only when DV-symmetric initial conditions are employed. Model patterning loses qualitative agreement with experimental data when we incorporate a realistic DV-asymmetric distribution of Bcd. Further, we find that geometry alone is insufficient to account for DV-asymmetries in the final gap gene distribution. Additional GRN optimization confirms that the 3D model remains sensitive to GRN parameter perturbations. Finally, we find that incorporation of 3D data in simulation and optimization does not constrain the search space or improve optimization results

Phenotypical microRNA screen reveals a noncanonical role of CDK2 in regulating neutrophil migration

Neutrophil migration is essential for inflammatory responses to kill pathogens; however, excessive neutrophilic inflammation also leads to tissue injury and adverse effects. To discover novel therapeutic targets that modulate neutrophil migration, we performed a neutrophil-specific microRNA (miRNA) overexpression screen in zebrafish and identified 8 miRNAs as potent suppressors of neutrophil migration. Among those, miR-199 decreases neutrophil chemotaxis in zebrafish and human neutrophil-like cells. Intriguingly, in terminally differentiated neutrophils, miR-199 alters the cell cycle-related pathways and directly suppresses cyclin-dependent kinase 2 (Cdk2), whose known activity is restricted to cell cycle progression and cell differentiation. Inhibiting Cdk2, but not DNA replication, disrupts cell polarity and chemotaxis of zebrafish neutrophils without inducing cell death. Human neutrophil-like cells deficient in CDK2 fail to polarize and display altered signaling downstream of the formyl peptide receptor. Chemotaxis of primary human neutrophils is also reduced upon CDK2 inhibition. Furthermore, miR-199 overexpression or CDK2 inhibition significantly improves the outcome of lethal systemic inflammation challenges in zebrafish. Our results therefore reveal previously unknown functions of miR-199 and CDK2 in regulating neutrophil migration and provide directions in alleviating systemic inflammation

An Automated Workflow for Quantifying RNA Transcripts in Individual Cells in Large Data-sets

Advanced molecular probing techniques such as single molecule fluorescence in situ hybridization (smFISH) or RNAscope can be used to assess the quantity and spatial location of mRNA transcripts within cells. Quantifying mRNA expression in large image sets usually involves automated counting of fluorescent spots. Though conventional spot counting algorithms may suffice, they often lack high-throughput capacity and accuracy in cases of crowded signal or excessive noise. Automatic identification of cells and processing of many images is still a challenge. We have developed a method to perform automatic cell boundary identification while providing quantitative data about mRNA transcript levels across many images. Comparisons of mRNA transcript levels identified by the method highly correlate to qPCR measurements of mRNA expression in Drosophila genotypes with different levels of Rhodopsin 1 transcript. We also introduce a graphical user interface to facilitate analysis of large data sets. We expect these methods to translate to model systems where automated image processing can be harnessed to obtain single-cell data. The described method: Provides relative intensity measurements that scale directly with the number of labeled transcript probes within individual cells. Allows quantitative assessment of single molecule data from images with crowded signal and moderate signal to noise ratios

Vibrational Photoacoustic Microscopy for Depth-resolved Bond-selective Imaging of Tissues and Organisms

We realize vibrational photoacoustic microscopy (VPA) using molecular excitation of overtone vibration and acoustic detection of the resultant pressure transients. We demonstrate 3-D VPA imaging of lipid-rich atherosclerotic plaques and lipid bodies in living Drosophila larvae by exciting 2nd overtone of the CH bond stretch around 8300 cm^(−1). Depth-resolved spectral analysis and a penetration depth of several mm are available

An Automated Workflow for Quantifying RNA Transcripts in Individual Cells in Large Data-sets

Advanced molecular probing techniques such as single molecule fluorescence in situ hybridization (smFISH) or RNAscope can be used to assess the quantity and spatial location of mRNA transcripts within cells. Quantifying mRNA expression in large image sets usually involves automated counting of fluorescent spots. Though conventional spot counting algorithms may suffice, they often lack high-throughput capacity and accuracy in cases of crowded signal or excessive noise. Automatic identification of cells and processing of many images is still a challenge. We have developed a method to perform automatic cell boundary identification while providing quantitative data about mRNA transcript levels across many images. Comparisons of mRNA transcript levels identified by the method highly correlate to qPCR measurements of mRNA expression in Drosophila genotypes with different levels of Rhodopsin 1 transcript. We also introduce a graphical user interface to facilitate analysis of large data sets. We expect these methods to translate to model systems where automated image processing can be harnessed to obtain single-cell data. The described method: • Provides relative intensity measurements that scale directly with the number of labeled transcript probes within individual cells.• Allows quantitative assessment of single molecule data from images with crowded signal and moderate signal to noise ratios

Label-Free Bond-Selective Imaging by Listening to Vibrationally Excited Molecules

We report the realization of vibrational photoacoustic (VPA) microscopy using optical excitation of molecular overtone vibration and acoustic detection of the resultant pressure transients. Our approach eliminates the tissue scattering problem encountered in near-infrared spectroscopy and enables depth-resolved signal collection. The 2nd overtone of the CH bond stretch around 8300  cm^(−1), where blood interference is minimal, is excited. We demonstrate 3D VPA imaging of lipid-rich atherosclerotic plaques by excitation from the artery lumen, and lipid storage in live Drosophila larvae, with millimeter-scale penetration depth