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Biology subjects

Forrest, W. S.

Publications and source records attributed to Forrest, W. S..

2 recordsLinked to original sources

Oblique Line Scan Illumination Enables Expansive, Accurate and Sensitive Single Protein Measurements in Solution and in Living Cells

Single-molecule localization microscopy (SMLM) techniques, such as single-molecule tracking (SMT), enable in situ measurements in cells from which data-rich metrics can be extracted. SMT has been successfully applied to a variety of biological questions and model systems, aiming to unravel the spatiotemporal regulation of molecular mechanisms that govern protein function, downstream pathway effects, and cellular function. While powerful, SMLM often suffers from low throughput and illumination inhomogeneity, along with microscope and user-induced technical biases. Due to technical limitations in scaling SMLM techniques, a tradeoff between spatiotemporal resolution and throughput has been made historically, restricting broad application of these technologies. Here we address these limitations using Oblique Line Scan (OLS), a robust single-objective light-sheet based illumination and detection modality that achieves nanoscale spatial resolution and sub-millisecond temporal resolution across a 250 x 190 m field of view. We demonstrate OLS-enabled SMT on Halo-Tagged proteins in living cells capturing protein motion up to 14 m2 /s. By exploiting the adaptability of the acquisition frame rate and the improved rejection of out of focus light, we extend the utility of OLS beyond cellular compartments with in-solution SMT (isSMT) for single-molecule measurement of ligand-protein interactions and disruption of protein-protein interactions (PPI). We illustrate the versatility of OLS by showcasing two-color SMT, STORM, and single molecule fluorescence recovery after photobleaching (FRAP). OLS expands the range of SMLM applications and paves the way for robust, high-throughput single-molecule investigations of protein dynamics required for drug screening and systems biology studies, both in cells and in solution.

biophysics↗

NLoed: A Python package for nonlinear optimal experimental design in systems biology

MotivationModelling in systems and synthetic biology relies on accurate parameter estimates and predictions. Accurate model calibration relies, in turn, on data, and on how well-suited the available data is to a particular modelling task. Optimal experimental design (OED) techniques can be used to identify experiments and data collection procedures that will most efficiently contribute to a given modelling objective. However, implementation of OED is limited by currently available software tools that are not well-suited for the diversity of nonlinear models and non-normal data commonly encountered in biological research. Moreover, existing OED tools do not make use of the state-of-the-art numerical tools, resulting in inefficient computation. ResultsHere we present the NLoed software package. NLoed is an open-source Python library providing convenient access to OED methods, with particular emphasis on experimental design for systems biology research. NLoed supports a wide variety of nonlinear, multi-input/output, and dynamic models, and facilitates modelling and design of experiments over a wide variety of data types. To support OED investigations, the NLoed package implements maximum likelihood fitting and diagnostic tools, providing a comprehensive modelling workflow. NLoed offers an accessible, modular, and flexible OED tool-set suited to the wide variety of experimental scenarios encountered in systems biology research. We demonstrate NLOEDs capabilities by applying it to experimental design for characterization of a bacterial optogenetic system. AvailabilityNLoed is available via pip from the PyPi repository; https://pypi.org/project/nloed/. Source code, documentation and examples can be found on Github at https://github.com/ingallslab/NLoed. Contactbingalls@uwaterloo.ca Supplementary informationSupplementary materials are available online.

systems biology↗