Using high-resolution microscopy data to generate realistic structures for electromagnetic FDTD simulations from complex biological models.

Finite-difference time-domain (FDTD) electromagnetic simulations are a computational method that has seen much success in the study of biological optics; however, such simulations are often hindered by the difficulty of faithfully replicating complex biological microstructures in the simulation space. Recently, we designed simulations to calculate the trajectory of electromagnetic light waves through realistically reconstructed retinal photoreceptors and found that cone photoreceptor mitochondria play a substantial role in shaping incoming light. In addition to vision research and ophthalmology, such simulations are broadly applicable to studies of the interaction of electromagnetic radiation with biological tissue. Here, we present our method for discretizing complex 3D models of cellular structures for use in FDTD simulations using MEEP, the MIT Electromagnetic Equation Propagation software, including subpixel smoothing at mesh boundaries. Such models can originate from experimental imaging or be constructed by hand. We also include sample code for use in MEEP. Implementation of this algorithm in new code requires understanding of 3D mathematics and may require several weeks of effort, whereas use of our sample code requires knowledge of MEEP and C++ and may take up to a few hours to prepare a model of interest for 3D FDTD simulation. In all cases, access to a facility supercomputer with parallel processing capabilities is recommended. This protocol offers a practical solution to a significant challenge in the field of computational electrodynamics and paves the way for future advancements in the study of light interaction with biological structures.

Neurexin 3 is required for the specific S-cone to S-cone bipolar cell synapse in the mammalian retina.

Specific wiring is essential for sensory systems to precisely relay information to higher brain regions. The retina, an approachable part of the brain, is an ideal model for studying neural circuits due to its well-organized structure. In the retina, S-cone photoreceptors sense and relay short-wavelength (e.g., blue) light signals for encoding color information and other environmental cues. S-cones usually account for less than 10% of cones and are precisely connected to S-cone bipolar cells (SCBCs). This connection is ancient and highly conserved across species, indicating essential functions. How this wiring specificity is formed and maintained, however, is not understood. To unveil the molecular mechanisms underlying this highly specific connection, we sequenced the transcriptomes of thirteen-lined ground squirrel (TLGS) photoreceptors. We chose TLGS for their cone-rich retina and the absence of cones that co-express multiple opsin proteins, as compared to mice. We used a targeted SMART-seq approach to obtain high-resolution transcriptomes from S- and M-cone photoreceptors and identified a cell-adhesion molecule, Nrxn3, as a potential candidate mediating the S-cone to SCBC connection. Given the limitations of genetic manipulation in TLGS, we utilized mouse models to study the function of Nrxn3 in S-cones. In 'true' S-cones (S-opsin+/M-opsin-) that lack Nrxn3 expression, the number of connections with SCBCs was drastically reduced, indicating a critical role of Nrxn3 for this synapse. While neurexins are well known for their diverse roles in regulating various synapses, this study is the first to document its crucial role in mediating or maintaining a specific synapse in the central nervous system. In addition, the differentially expressed genes identified here provide a valuable resource for further investigating cone subtype-specific functions.

Mitochondria in cone photoreceptors act as microlenses to enhance photon delivery and confer directional sensitivity to light.

Mammalian photoreceptors aggregate numerous mitochondria, organelles chiefly for energy production, in the ellipsoid region immediately adjacent to the light-sensitive outer segment to support the high metabolic demands of phototransduction. However, these complex, lipid-rich organelles are also poised to affect light passage into the outer segment. Here, we show, via live imaging and simulations, that despite this risk of light scattering or absorption, these tightly packed mitochondria "focus" light for entry into the outer segment and that mitochondrial remodeling affects such light concentration. This "microlens"-like feature of cone mitochondria delivers light with an angular dependence akin to the Stiles-Crawford effect (SCE), providing a simple explanation for this essential visual phenomenon that improves resolution. This new insight into the optical role of mitochondria is relevant for the interpretation of clinical ophthalmological imaging, lending support for the use of SCE as an early diagnostic tool in retinal disease.

True S-cones are concentrated in the ventral mouse retina and wired for color detection in the upper visual field.

Color, an important visual cue for survival, is encoded by comparing signals from photoreceptors with different spectral sensitivities. The mouse retina expresses a short wavelength-sensitive and a middle/long wavelength-sensitive opsin (S- and M-opsin), forming opposing, overlapping gradients along the dorsal-ventral axis. Here, we analyzed the distribution of all cone types across the entire retina for two commonly used mouse strains. We found, unexpectedly, that 'true S-cones' (S-opsin only) are highly concentrated (up to 30% of cones) in ventral retina. Moreover, S-cone bipolar cells (SCBCs) are also skewed towards ventral retina, with wiring patterns matching the distribution of true S-cones. In addition, true S-cones in the ventral retina form clusters, which may augment synaptic input to SCBCs. Such a unique true S-cone and SCBC connecting pattern forms a basis for mouse color vision, likely reflecting evolutionary adaptation to enhance color coding for the upper visual field suitable for mice's habitat and behavior.

Many primates, including humans, can see color better than most other mammals. This difference is due to the variety of light-detecting proteins ­ called opsins ­ that are produced in the eye by cells known as cones. While humans have three, mice only have two different opsins, known as S and M, which detect blue/UV and green light, respectively. Mouse cones produce either S-opsins, M-opsins or both. Fewer than 10 percent of cone cells in mice produce just the S-opsin, and these cells are essential for color vision. Mice are commonly used in scientific research, and so their vision has been well studied. However, previous research has produced conflicting results. Some studies report that cone cells that contain only S-opsin are evenly spread out across the retina. Other evidence suggests that color vision in mice exists only for the upper field of their vision, in other words, that mice can only distinguish colors that appeared above them. Nadal-Nicolás et al. set out to understand how to reconcile these contrasting findings. Molecular tools were used to detect S- and M-opsin in the retina of mice and revealed large differences between the lower part, known as the ventral retina, and the upper part, known as the dorsal retina. The ventral retina detects light coming from above the animal, and about a third of cone cells in this region produced exclusively S-opsin, compared to only 1 percent of cones in the dorsal retina. These S-opsin cone cells in the ventral retina group into clusters, where they connect with a special type of nerve cells that transmit this signal. To better understand these findings, Nadal-Nicolás et al. also studied albino mice. Although albino mice have a different distribution of S-opsin protein in the retina, the cone cells producing only S-opsin are similarly clustered in the ventral retina. This suggests that the concentration of S-opsin cone cells in the ventral retina is an important feature in mouse sight. This new finding corrects the misconception that S-opsin-only cone cells are evenly spread throughout the retina and supports the previous evidence that mouse color vision is greatest in the upper part of their field of vision. Nadal-Nicolás et al. suggest this arrangement could help the mice to detect predators that may attack them from above during the daytime. Together, these new findings could help to improve the design of future studies involving vision in mice and potentially other similar species.

iPSCs from a Hibernator Provide a Platform for Studying Cold Adaptation and Its Potential Medical Applications.

Hibernating mammals survive hypothermia (<10°C) without injury, a remarkable feat of cellular preservation that bears significance for potential medical applications. However, mechanisms imparting cold resistance, such as cytoskeleton stability, remain elusive. Using the first iPSC line from a hibernating mammal (13-lined ground squirrel), we uncovered cellular pathways critical for cold tolerance. Comparison between human and ground squirrel iPSC-derived neurons revealed differential mitochondrial and protein quality control responses to cold. In human iPSC-neurons, cold triggered mitochondrial stress, resulting in reactive oxygen species overproduction and lysosomal membrane permeabilization, contributing to microtubule destruction. Manipulations of these pathways endowed microtubule cold stability upon human iPSC-neurons and rat (a non-hibernator) retina, preserving its light responsiveness after prolonged cold exposure. Furthermore, these treatments significantly improved microtubule integrity in cold-stored kidneys, demonstrating the potential for prolonging shelf-life of organ transplants. Thus, ground squirrel iPSCs offer a unique platform for bringing cold-adaptive strategies from hibernators to humans in clinical applications. VIDEO ABSTRACT.

Mechanisms of memory storage in a model perirhinal network.

The perirhinal cortex supports recognition and associative memory. Prior unit recording studies revealed that recognition memory involves a reduced responsiveness of perirhinal cells to familiar stimuli whereas associative memory formation is linked to increasing perirhinal responses to paired stimuli. Both effects are thought to depend on perirhinal plasticity but it is unclear how the same network could support these opposite forms of plasticity. However, a recent study showed that when neocortical inputs are repeatedly activated, depression or potentiation could develop, depending on the extent to which the stimulated neocortical activity recruited intrinsic longitudinal connections. We developed a biophysically realistic perirhinal model that reproduced these phenomena and used it to investigate perirhinal mechanisms of associative memory. These analyzes revealed that associative plasticity is critically dependent on a specific subset of neurons, termed conjunctive cells (CCs). When the model network was trained with spatially distributed but coincident neocortical inputs, CCs acquired excitatory responses to the paired inputs and conveyed them to distributed perirhinal sites via longitudinal projections. CC ablation during recall abolished expression of the associative memory. However, CC ablation during training did not prevent memory formation because new CCs emerged, revealing that competitive synaptic interactions governs the formation of CC assemblies.

Entropy and convexity for nonlinear partial differential equations.

Partial differential equations are ubiquitous in almost all applications of mathematics, where they provide a natural mathematical description of many phenomena involving change in physical, chemical, biological and social processes. The concept of entropy originated in thermodynamics and statistical physics during the nineteenth century to describe the heat exchanges that occur in the thermal processes in a thermodynamic system, while the original notion of convexity is for sets and functions in mathematics. Since then, entropy and convexity have become two of the most important concepts in mathematics. In particular, nonlinear methods via entropy and convexity have been playing an increasingly important role in the analysis of nonlinear partial differential equations in recent decades. This opening article of the Theme Issue is intended to provide an introduction to entropy, convexity and related nonlinear methods for the analysis of nonlinear partial differential equations. We also provide a brief discussion about the content and contributions of the papers that make up this Theme Issue.

Generation and preservation of the slow underlying membrane potential oscillation in model bursting neurons.

The underlying membrane potential oscillation of both forced and endogenous slow-wave bursting cells affects the number of spikes per burst, which in turn affects outputs downstream. We use a biophysical model of a class of slow-wave bursting cells with six active currents to investigate and generalize correlations among maximal current conductances that might generate and preserve its underlying oscillation. We propose three phases for the underlying oscillation for this class of cells: generation, maintenance, and termination and suggest that different current modules coregulate to preserve the characteristics of each phase. Coregulation of I(Burst) and I(A) currents within distinct boundaries maintains the dynamics during the generation phase. Similarly, coregulation of I(CaT) and I(Kd) maintains the peak and duration of the underlying oscillation, whereas the calcium-activated I(KCa) ensures appropriate termination of the oscillation and adjusts the duration independent of peak.

Coregulation of ion channel conductances preserves output in a computational model of a crustacean cardiac motor neuron.

Similar activity patterns at both neuron and network levels can arise from different combinations of membrane and synaptic conductance values. A strategy by which neurons may preserve their electrical output is via cell type-dependent balances of inward and outward currents. Measurements of mRNA transcripts that encode ion channel proteins within motor neurons in the crustacean cardiac ganglion recently revealed correlations between certain channel types. To determine whether balances of intrinsic currents potentially resulting from such correlations preserve certain electrical cell outputs, we developed a nominal biophysical model of the crustacean cardiac ganglion using biological data. Predictions from the nominal model showed that coregulation of ionic currents may preserve the key characteristics of motor neuron activity. We then developed a methodology of sampling a multidimensional parameter space to select an appropriate model set for meaningful comparison with variations in correlations seen in biological datasets.