3D visualization processes for recreating and studying organismal form.

The study of biological form is a vital goal of evolutionary biology and functional morphology. We review an emerging set of methods that allow scientists to create and study accurate 3D models of living organisms and animate those models for biomechanical and fluid dynamic analyses. The methods for creating such models include 3D photogrammetry, laser and CT scanning, and 3D software. New multi-camera devices can be used to create accurate 3D models of living animals in the wild and captivity. New websites and virtual reality/augmented reality devices now enable the visualization and sharing of these data. We provide examples of these approaches for animals ranging from large whales to lizards and show applications for several areas: Natural history collections; body condition/scaling, bioinspired robotics, computational fluids dynamics (CFD), machine learning, and education. We provide two datasets to demonstrate the efficacy of CFD and machine learning approaches and conclude with a prospectus.

Computer design of microfluidic mixers for protein/RNA folding studies.

Kinetic studies of biological macromolecules increasingly use microfluidic mixers to initiate and monitor reaction progress. A motivation for using microfluidic mixers is to reduce sample consumption and decrease mixing time to microseconds. Some applications, such as small-angle x-ray scattering, also require large (>10 micron) sampling areas to ensure high signal-to-noise ratios and to minimize parasitic scattering. Chaotic to marginally turbulent mixers are well suited for these applications because this class of mixers provides a good middle ground between existing laminar and turbulent mixers. In this study, we model various chaotic to marginally turbulent mixing concepts such as flow turning, flow splitting, and vortex generation using computational fluid dynamics for optimization of mixing efficiency and observation volume. Design iterations show flow turning to be the best candidate for chaotic/marginally turbulent mixing. A qualitative experimental test is performed on the finalized design with mixing of 10 M urea and water to validate the flow turning unsteady mixing concept as a viable option for RNA and protein folding studies. A comparison of direct numerical simulations (DNS) and turbulence models suggests that the applicability of turbulence models to these flow regimes may be limited.

Advances in turbulent mixing techniques to study microsecond protein folding reactions.

Recent experimental and computational advances in the protein folding arena have shown that the readout of the one-dimensional sequence information into three-dimensional structure begins within the first few microseconds of folding. The initiation of refolding reactions has been achieved by several means, including temperature jumps, flash photolysis, pressure jumps, and rapid mixing methods. One of the most commonly used means of initiating refolding of chemically denatured proteins is by turbulent flow mixing with refolding dilution buffer, where greater than 99% mixing efficiency has been achieved within 10's of microseconds. Successful interfacing of turbulent flow mixers with complementary detection methods, including time-resolved Fluorescence Spectroscopy (trFL), Förster Resonance Energy Transfer, Circular Dichroism, Small-Angle X-ray Scattering, Hydrogen Exchange followed by Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy, Infrared Spectroscopy (IR), and Fourier Transform IR Spectroscopy, has made this technique very attractive for monitoring various aspects of structure formation during folding. Although continuous-flow (CF) mixing devices interfaced with trFL detection have a dead time of only 30 µs, burst phases have been detected in this time scale during folding of peptides and of large proteins (e.g., CheY and TIM barrels). Furthermore, a major limitation of the CF mixing technique has been the requirement of large quantities of sample. In this brief communication, we will discuss the recent flurry of activity in micromachining and microfluidics, guided by computational simulations, which are likely to lead to dramatic improvements in time resolution and sample consumption for CF mixers over the next few years.