Neurons derived from the same progenitor may acquire different fates according to their birth timing/order. To reveal temporally guided cell fates, we must determine neuron types as well as their lineage relationships and times of birth. Recent advances in genetic lineage analysis and fate mapping are facilitating such studies. For example, high-resolution lineage analysis can identify each sequentially derived neuron of a lineage and has revealed abrupt temporal identity changes in diverse Drosophila neuronal lineages. In addition, fate mapping of mouse neurons made from the same pool of precursors shows production of specific neuron types in specific temporal patterns. The tools used in these analyses are helping to further our understanding of the genetics of neuronal temporal identity.

Characterizing the identity and types of neurons in the brain, as well as their associated function, requires a means of quantifying and comparing 3D neuron morphology. Presently, neuron comparison methods are based on statistics from neuronal morphology such as size and number of branches, which are not fully suitable for detecting local similarities and differences in the detailed structure. We developed BlastNeuron to compare neurons in terms of their global appearance, detailed arborization patterns, and topological similarity. BlastNeuron first compares and clusters 3D neuron reconstructions based on global morphology features and moment invariants, independent of their orientations, sizes, level of reconstruction and other variations. Subsequently, BlastNeuron performs local alignment between any pair of retrieved neurons via a tree-topology driven dynamic programming method. A 3D correspondence map can thus be generated at the resolution of single reconstruction nodes. We applied BlastNeuron to three datasets: (1) 10,000+ neuron reconstructions from a public morphology database, (2) 681 newly and manually reconstructed neurons, and (3) neurons reconstructions produced using several independent reconstruction methods. Our approach was able to accurately and efficiently retrieve morphologically and functionally similar neuron structures from large morphology database, identify the local common structures, and find clusters of neurons that share similarities in both morphology and molecular profiles.

Significance: Genetically encoded calcium ion (Ca2+) indicators (GECIs) are powerful tools for monitoring intracellular Ca2+ concentration changes in living cells and model organisms. In particular, GECIs have found particular utility for monitoring the transient increase of Ca2+concentration that is associated with the neuronal action potential. However, the palette of highly optimized GECIs for imaging of neuronal activity remains relatively limited. Expanding the selection of available GECIs to include new colors and distinct photophysical properties could create new opportunities for in vitro and in vivo fluorescence imaging of neuronal activity. In particular, blue-shifted variants of GECIs are expected to have enhanced two-photon brightness, which would facilitate multiphoton microscopy.

Aim: We describe the development and applications of T-GECO1-a high-performance blue-shifted GECI based on the Clavularia sp.-derived mTFP1.

Approach: We use protein engineering and extensive directed evolution to develop T-GECO1. We characterize the purified protein and assess its performance in vitro using one-photon excitation in cultured rat hippocampal neurons, in vivo using one-photon excitation fiber photometry in mice, and ex vivo using two-photon Ca2+ imaging in hippocampal slices.

Results: The Ca2+-bound state of T-GECO1 has an excitation peak maximum of 468 nm, an emission peak maximum of 500 nm, an extinction coefficient of 49,300M−1cm−1, a quantum yield of 0.83, and two-photon brightness approximately double that of EGFP. The Ca2+-dependent fluorescence increase is 15-fold, and the apparent Kd for Ca2+ is 82 nM. With two-photon excitation conditions at 850 nm, T-GECO1 consistently enabled the detection of action potentials with higher signal-to-noise (SNR) than a late generation GCaMP variant.

Conclusions: T-GECO1 is a high-performance blue-shifted GECI that, under two-photon excitation conditions, provides advantages relative to late generation GCaMP variants.

Keywords: blue-shifted fluorescence; genetically encoded calcium ion indicator; neuronal activity imaging; protein engineering; two-photon excitation.

Muscular hydrostats (such as mollusks), and fluid-filled animals (such as annelids), can exploit their constant-volume tissues to transfer forces and displacements in predictable ways, much as articulated animals use hinges and levers. Although larval insects contain pressurized fluids, they also have internal air tubes that are compressible and, as a result, they have more uncontrolled degrees of freedom. Therefore, the mechanisms by which larval insects control their movements are expected to reveal useful strategies for designing soft biomimetic robots. Using caterpillars as a tractable model system, it is now possible to identify the biomechanical and neural strategies for controlling movements in such highly deformable animals. For example, the tobacco hornworm, Manduca sexta, can stiffen its body by increasing muscular tension (and therefore body pressure) but the internal cavity (hemocoel) is not iso-barometric, nor is pressure used to directly control the movements of its limbs. Instead, fluid and tissues flow within the hemocoel and the body is soft and flexible to conform to the substrate. Even the gut contributes to the biomechanics of locomotion; it is decoupled from the movements of the body wall and slides forward within the body cavity at the start of each step. During crawling the body is kept in tension for part of the stride and compressive forces are exerted on the substrate along the axis of the caterpillar, thereby using the environment as a skeleton. The timing of muscular activity suggests that crawling is coordinated by proleg-retractor motoneurons and that the large segmental muscles produce anterograde waves of lifting that do not require precise timing. This strategy produces a robust form of locomotion in which the kinematics changes little with orientation. In different species of caterpillar, the presence of prolegs on particular body segments is related to alternative kinematics such as "inching." This suggests a mechanism for the evolution of different gaits through changes in the usage of prolegs, rather than, through extensive alterations in the motor program controlling the body wall. Some of these findings are being used to design and test novel control-strategies for highly deformable robots. These "softworm" devices are providing new insights into the challenges faced by any soft animal navigating in a terrestrial environment.

Inside the cell, proteins essential for signaling, morphogenesis, and migration navigate the complex, ever-changing environment through vesicular trafficking or microtubule-driven mechanisms. However, the mechanisms by which soluble proteins reach their target destinations remain unknown. Here, we show that soluble proteins are directed toward the cell’s advancing edge by advection, diffusion facilitated by fluid flow. The advective transport mechanism operates in a compartment at the front of the cell isolated from the rest of the cytoplasm by a semi-permeable actin-myosin barrier that restricts protein mixing between the compartment and the rest of the cytoplasm. Contraction at the barrier generates a molecularly non-specific fluid flow that propels treadmilling actin monomer, actin-binding, adhesion, and even inert proteins forward. Changes in the dynamic local curvature of the barrier direct the flow, targeting proteins toward the protruding regions of the leading edge, effectively coordinating the distribution of proteins needed for local changes in cellular dynamics. Outside the compartment, diffusion is the primary mode of soluble protein transport. Our findings suggest that cells possess previously unrecognized organizational strategies for managing soluble protein concentration and distributing them efficiently for activities such as protrusion and adhesion.

Brain-derived neurotrophic factor (BDNF) plays an important role in hippocampus-dependent learning and memory. Canonically, this has been ascribed to an enhancing effect on neuronal excitability and synaptic plasticity in the CA1 region. However, it is the pyramidal neurons in the subiculum that form the primary efferent pathways conveying hippocampal information to other areas of the brain, and yet the effect of BDNF on these neurons has remained unexplored. We present new data that BDNF regulates neuronal excitability and cellular plasticity in a much more complex manner than previously suggested. Subicular pyramidal neurons can be divided into two major classes, which have different electrophysiological and morphological properties, different requirements for the induction of plasticity and different extra-hippocampal projections. We found that BDNF increases excitability in one class of subicular pyramidal neurons, yet decreases excitability of the other class. Further, while endogenous BDNF was necessary for the induction of synaptic plasticity in both cell types, BDNF enhanced intrinsic plasticity in one class of pyramidal neurons, yet suppressed intrinsic plasticity in the other. Taken together, these data suggest a novel role for BDNF signaling, as it appears to dynamically and bidirectionally regulate the output of hippocampal information to different regions of the brain.

Two-photon imaging and optogenetic stimulation rely on high illumination powers, particularly for state-of-the-art applications that target deeper structures, achieve faster measurements, or probe larger brain areas. However, little information is available on heating and resulting damage induced by high-power illumination in the brain. Here we used thermocouple probes and quantum dot nanothermometers to measure temperature changes induced by two-photon microscopy in the neocortex of awake and anaesthetized mice. We characterized heating as a function of wavelength, exposure time, and distance from the center of illumination. Although total power is highest near the surface of the brain, heating was most severe hundreds of microns below the focal plane, due to heat dissipation through the cranial window. Continuous illumination of a 1mm2 area produced a peak temperature increase of approximately 1.8°C/100mW. Continuous illumination with powers above 250 mW induced lasting damage, detected with immunohistochemistry against Iba1, GFAP, heat shock proteins, and activated Caspase-3. Higher powers were usable in experiments with limited duty ratios, suggesting an approach to mitigate damage in high-power microscopy experiments.

The microvasculature underlies the supply networks that support neuronal activity within heterogeneous brain regions. What are common versus heterogeneous aspects of the connectivity, density, and orientation of capillary networks? To address this, we imaged, reconstructed, and analyzed the microvasculature connectome in whole adult mice brains with sub-micrometer resolution. Graph analysis revealed common network topology across the brain that leads to a shared structural robustness against the rarefaction of vessels. Geometrical analysis, based on anatomically accurate reconstructions, uncovered a scaling law that links length density, i.e., the length of vessel per volume, with tissue-to-vessel distances. We then derive a formula that connects regional differences in metabolism to differences in length density and, further, predicts a common value of maximum tissue oxygen tension across the brain. Last, the orientation of capillaries is weakly anisotropic with the exception of a few strongly anisotropic regions; this variation can impact the interpretation of fMRI data.

BACKGROUND: Structural MRI has demonstrated brain alterations in depression pathology and antidepressants treatment. While synaptic plasticity has been previously proposed as the potential underlying mechanism of MRI findings at a cellular and molecular scale, there is still insufficient evidence to link the MRI findings and synaptic plasticity mechanisms in depression pathology.

METHODS: In this study, a Wistar-Kyoto (WKY) depression rat model was treated with antidepressants (citalopram or Jie-Yu Pills) and tested in a series of behavioral tests and a 7.0 MRI scanner. We then measured dendritic spine density within altered brain regions. We also examined expression of synaptic marker proteins (PSD-95 and SYP).

RESULTS: WKY rats exhibited depression-like behaviors in the sucrose preference test (SPT) and forced swim test (FST), and anxiety-like behaviors in the open field test (OFT). Both antidepressants reversed behavioral changes in SPT and OFT but not in FST. We found a correlation between SPT performance and brain volumes as detected by MRI. All structural changes were consistent with alterations of the corpus callosum (white matter), dendritic spine density, as well as PSD95 and SYP expression at different levels. Two antidepressants similarly reversed these macro- and micro-changes.

LIMITATIONS: The single dose of antidepressants was the major limitation of this study. Further studies should focus on the white matter microstructure changes and myelin-related protein alterations, in addition to comparing the effects of ketamine.

CONCLUSION: Translational evidence links structural MRI changes and synaptic plasticity alterations, which promote our understanding of SPT mechanisms and antidepressant response in WKY rats.

Advances in brain connectomics have demonstrated the extraordinary complexity of neural circuits. Developing neurons encounter the axons and dendrites of many different neuron types and form synapses with only a subset of them. During circuit assembly, neurons express cell-type-specific repertoires comprising many cell adhesion molecules (CAMs) that can mediate interactions between developing neurites. Many CAM families have been shown to contribute to brain wiring in different ways. It has been challenging, however, to identify receptor-ligand pairs directly matching neurons with their synaptic targets. Here, we integrated the synapse-level connectome of the neural circuit with the developmental expression patterns and binding specificities of CAMs on pre- and postsynaptic neurons in the Drosophila visual system. To overcome the complexity of neural circuits, we focus on pairs of genetically related neurons that make differential wiring choices. In the motion detection circuit, closely related subtypes of T4/T5 neurons choose between alternative synaptic targets in adjacent layers of neuropil. This choice correlates with the matching expression in synaptic partners of different receptor-ligand pairs of the Beat and Side families of CAMs. Genetic analysis demonstrated that presynaptic Side-II and postsynaptic Beat-VI restrict synaptic partners to the same layer. Removal of this receptor-ligand pair disrupts layers and leads to inappropriate targeting of presynaptic sites and postsynaptic dendrites. We propose that different Side/Beat receptor-ligand pairs collaborate with other recognition molecules to determine wiring specificities in the fly brain. Combining transcriptomes, connectomes, and protein interactome maps allow unbiased identification of determinants of brain wiring.