Computational framework for single-cell spatiotemporal dynamics of optogenetic membrane recruitment

We describe a modular computational framework for analyzing cell-wide spatiotemporal signaling dynamics in single-cell microscopy experiments that accounts for the experiment-specific geometric and diffractive complexities that arise from heterogeneous cell morphologies and optical instrumentation. Inputs are unique cell geometries and protein concentrations derived from confocal stacks and spatiotemporally varying environmental stimuli. After simulating the system with a model of choice, the output is convolved with the microscope point-spread function for direct comparison with the observable image. We experimentally validate this approach in single cells with BcLOV4, an optogenetic membrane recruitment system for versatile control over cell signaling, using a three-dimensional non-linear finite element model with all parameters experimentally derived. The simulations recapitulate observed subcellular and cell-to-cell variability in BcLOV4 signaling, allowing for inter-experimental differences of cellular and instrumentation origins to be elucidated and resolved for improved interpretive robustness. This single-cell approach will enhance optogenetics and spatiotemporally resolved signaling studies.

Fostering bioinformatics education through skill development of professors: Big Genomic Data Skills Training for Professors

Bioinformatics has become an indispensable part of life science over the past 2 decades. However, bioinformatics education is not well integrated at the undergraduate level, especially in liberal arts colleges and regional universities in the United States. One significant obstacle pointed out by the Network for Integrating Bioinformatics into Life Sciences Education is the lack of faculty in the bioinformatics area. Most current life science professors did not acquire bioinformatics analysis skills during their own training. Consequently, a great number of undergraduate and graduate students do not get the chance to learn bioinformatics or computational biology skills within a structured curriculum during their education. To address this gap, we developed a module-based, week-long short course to train small college and regional university professors with essential bioinformatics skills. The bioinformatics modules were built to be adapted by the professor-trainees afterward and used in their own classes. All the course materials can be accessed at https://github.com/TheJacksonLaboratory/JAXBD2K-ShortCourse.

Synthetic cell-like membrane interfaces for probing dynamic protein-lipid interactions

The ability to rapidly screen interactions between proteins and membrane-like interfaces would aid in establishing the structure-function of protein-lipid interactions, provide a platform for engineering lipid-interacting protein tools, and potentially inform the signaling mechanisms and dynamics of membrane-associated proteins. Here, we describe the preparation and application of water-in-oil (w/o) emulsions with lipid-stabilized droplet interfaces that emulate the plasma membrane inner leaflet with tunable composition. Fluorescently labeled proteins are easily visualized in these synthetic cell-like droplets on an automated inverted fluorescence microscope, thus allowing for both rapid screening of relative binding and spatiotemporally resolved analyses of for example, protein-interface association and dissociation dynamics and competitive interactions, using commonplace instrumentation. We provide protocols for droplet formation, automated imaging assays and analysis, and the production of the positive control protein BcLOV4, a natural photoreceptor with a directly light-regulated interaction with anionic membrane phospholipids that is useful for optogenetic membrane recruitment.

Functional and topological diversity of LOV domain photoreceptors

Light-oxygen-voltage sensitive (LOV) flavoproteins are ubiquitous photoreceptors that mediate responses to environmental cues. Photosensory inputs are transduced into signaling outputs via structural rearrangements in sensor domains that consequently modulate the activity of an effector domain or multidomain clusters. Establishing the diversity in effector function and sensor-effector topology will inform what signaling mechanisms govern light-responsive behaviors across multiple kingdoms of life and how these signals are transduced. Here, we report the bioinformatics identification of over 6,700 candidate LOV domains (including over 4,000 previously unidentified sequences from plants and protists), and insights from their annotations for ontological function and structural arrangements. Motif analysis identified the sensors from ∼42 million ORFs, with strong statistical separation from other flavoproteins and non-LOV members of the structurally related Per-aryl hydrocarbon receptor nuclear translocator (ARNT)-Sim family. Conserved-domain analysis determined putative light-regulated function and multidomain topologies. We found that for certain effectors, sensor-effector linker length is discretized based on both phylogeny and the preservation of α-helical heptad repeats within an extended coiled-coil linker structure. This finding suggests that preserving sensor-effector orientation is a key determinant of linker length, in addition to ancestry, in LOV signaling structure-function. We found a surprisingly high prevalence of effectors with functions previously thought to be rare among LOV proteins, such as regulators of G protein signaling, and discovered several previously unidentified effectors, such as lipases. This work highlights the value of applying genomic and transcriptomic technologies to diverse organisms to capture the structural and functional variation in photosensory proteins that are vastly important in adaptation, photobiology, and optogenetics.