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3869 Publications
Showing 51-60 of 3869 resultsVisualization of specific molecules and their assembly in real time and space is essential to delineate how cellular dynamics and signaling circuit are orchestrated during cell division cycle. Our recent studies reveal structural insights into human centromere-kinetochore core CCAN complex. Here we introduce a method for optically imaging trimeric and tetrameric protein interactions at nanometer spatial resolution in live cells using fluorescence complementation-based Förster resonance energy transfer (FC-FRET). Complementary fluorescent protein molecules were first used to visualize dimerization followed by FRET measurements. Using FC- FRET, we visualized centromere CENP-SXTW tetramer assembly dynamics in live cells, and dimeric interactions between CENP-TW dimer and kinetochore protein Spc24/25 dimer in dividing cells. We further delineated the interactions of monomeric CENP-T with Spc24/25 dimer in dividing cells. Surprisingly, our analyses revealed critical role of CDK1 kinase activity in the initial recruitment of Spc24/25 by CENP-T. However, interactions between CENP-T and Spc24/25 during chromosome segregation is independent of CDK1. Thus, FC-FRET provides a unique approach to delineate spatiotemporal dynamics of trimerized and tetramerized proteins at nanometer scale and establishes a platform to report the precise regulation of multimeric protein interactions in space and time in live cells.
The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preserving cell viability. Computational methods can help to address this challenge and are now shifting the boundaries of what is possible to capture in living systems. In this Review, we discuss these computational methods focusing on artificial intelligence-based approaches that can be layered on top of commonly used existing microscopies as well as hybrid methods that integrate computation and microscope hardware. We specifically discuss how computational approaches can improve the signal-to-noise ratio, spatial resolution, temporal resolution and multi-colour capacity of live-cell imaging.
Representation learning in neural networks may be implemented with supervised or unsupervised algorithms, distinguished by the availability of feedback. In sensory cortex, perceptual learning drives neural plasticity, but it is not known if this is due to supervised or unsupervised learning. Here we recorded populations of up to 90,000 neurons simultaneously from the primary visual cortex (V1) and higher visual areas (HVA), while mice learned multiple tasks as well as during unrewarded exposure to the same stimuli. Similar to previous studies, we found that neural changes in task mice were correlated with their behavioral learning. However, the neural changes were mostly replicated in mice with unrewarded exposure, suggesting that the changes were in fact due to unsupervised learning. The neural plasticity was concentrated in the medial HVAs and obeyed visual, rather than spatial, learning rules. In task mice only, we found a ramping reward prediction signal in anterior HVAs, potentially involved in supervised learning. Our neural results predict that unsupervised learning may accelerate subsequent task learning, a prediction which we validated with behavioral experiments.
Many motor control systems generate multiple movements using a common set of muscles. How are premotor circuits able to flexibly generate diverse movement patterns? Here, we characterize the neuronal circuits that drive the distinct courtship songs of Drosophila melanogaster. Male flies vibrate their wings towards females to produce two different song modes – pulse and sine song – which signal species identity and male quality. Using cell-type specific genetic reagents and the connectome, we provide a cellular and synaptic map of the circuits in the male ventral nerve cord that generate these songs and examine how activating or inhibiting each cell type within these circuits affects the song. Our data reveal that the song circuit is organized into two nested feed-forward pathways, with extensive reciprocal and feed-back connections. The larger network produces pulse song, the more complex and ancestral song form. A subset of this network produces sine song, the simpler and more recent form. Such nested organization may be a common feature of motor control circuits in which evolution has layered increasing flexibility on to a basic movement pattern.
Natural behaviors are a coordinated symphony of motor acts that drive reafferent (self-induced) sensory activation. Individual sensors cannot disambiguate exafferent (externally induced) from reafferent sources. Nevertheless, animals readily differentiate between these sources of sensory signals to carry out adaptive behaviors through corollary discharge circuits (CDCs), which provide predictive motor signals from motor pathways to sensory processing and other motor pathways. Yet, how CDCs comprehensively integrate into the nervous system remains unexplored. Here, we use connectomics, neuroanatomical, physiological, and behavioral approaches to resolve the network architecture of two pairs of ascending histaminergic neurons (AHNs) in Drosophila, which function as a predictive CDC in other insects. Both AHN pairs receive input primarily from a partially overlapping population of descending neurons, especially from DNg02, which controls wing motor output. Using Ca imaging and behavioral recordings, we show that AHN activation is correlated to flight behavior and precedes wing motion. Optogenetic activation of DNg02 is sufficient to activate AHNs, indicating that AHNs are activated by descending commands in advance of behavior and not as a consequence of sensory input. Downstream, each AHN pair targets predominantly non-overlapping networks, including those that process visual, auditory, and mechanosensory information, as well as networks controlling wing, haltere, and leg sensorimotor control. These results support the conclusion that the AHNs provide a predictive motor signal about wing motor state to mostly non-overlapping sensory and motor networks. Future work will determine how AHN signaling is driven by other descending neurons and interpreted by AHN downstream targets to maintain adaptive sensorimotor performance.
Expression of the immediate early gene cFos modifies the epigenetic landscape of activated neurons with downstream effects on synaptic plasticity. The production of cFos is inhibited by a long-lived isoform of another Fos family gene, ΔFosB. It has been speculated that this negative feedback mechanism may be critical for protecting episodic memories from being overwritten by new information. Here, we investigate the influence of ΔFosB inhibition on cFos expression and memory. Hippocampal neurons in slice culture produce more cFos on the first day of stimulation compared to identical stimulation on the following day. This downregulation affects all hippocampal subfields and requires histone deacetylation. Overexpression of ΔFosB in individual pyramidal neurons effectively suppresses cFos, indicating that accumulation of ΔFosB is the causal mechanism. Water maze training of mice over several days leads to accumulation of ΔFosB in granule cells of the dentate gyrus, but not in CA3 and CA1. Because the dentate gyrus is thought to support pattern separation and cognitive flexibility, we hypothesized that inhibiting the expression of ΔFosB would affect reversal learning, i.e., the ability to successively learn new platform locations in the water maze. The results indicate that pharmacological HDAC inhibition, which prevents cFos repression, impairs reversal learning, while learning and memory of the initial platform location remain unaffected. Our study supports the hypothesis that epigenetic mechanisms tightly regulate cFos expression in individual granule cells to orchestrate the formation of time-stamped memories.
The adaptive dynamics of evolving microbial populations takes place on a complex fitness landscape generated by epistatic interactions. The population generically consists of multiple competing strains, a phenomenon known as clonal interference. Microscopic epistasis and clonal interference are central aspects of evolution in microbes, but their combined effects on the functional form of the population’s mean fitness are poorly understood. Here, we develop a computational method that resolves the full microscopic complexity of an evolving population subject to a standard serial dilution protocol. We find that stronger microscopic epistasis gives rise to fitness trajectories with slower growth independent of the number of competing strains, which we quantify with power-law fits and understand mechanistically via a random walk model that neglects dynamical correlations between genes. We show that clonal interference leads to fitness trajectories with faster growth (in functional form) without microscopic epistasis, but has a negligible effect when epistasis is sufficiently strong, indicating that the role of clonal interference depends intimately on the underlying fitness landscape.
The accelerating pace of technological advancements necessitates specialised expertise and cutting-edge instruments to maintain competitive research in life sciences. Core facilities - collaborative laboratories equipped with state-of-the-art tools and staffed by expert personnel - are vital resources that support diverse scientific endeavours. However, their adoption in lower-income communities has been comparatively stagnant due to both financial and cultural challenges. This paper explores the perils of not supporting core facilities on national research enterprises, underscoring the need for balanced investments in discovery science and crucial infrastructure support. We explore the implications from the perspectives of funders, university leaders and lab heads. We advocate for a paradigm shift to recognise these facilities as essential components of national research efforts. Core facilities are positioned not as optional but as strategic investments that can catalyse breakthroughs, particularly in environments with limited resources.
The endoplasmic reticulum (ER) is an important regulator of Ca2+ in cells and dysregulation of ER calcium homeostasis can lead to numerous pathologies. Understanding how various pharmacological and genetic perturbations of ER Ca2+ homeostasis impacts cellular physiology would likely be facilitated by more quantitative measurements of ER Ca2+ levels that allow easier comparisons across conditions. Here, we developed a ratiometric version of our original ER-GCaMP probe that allows for more quantitative comparisons of the concentration of Ca2+ in the ER across cell types and sub-cellular compartments. Using this approach we show that the resting concentration of ER Ca2+ in primary dissociated neurons is substantially lower than that in measured in embryonic fibroblasts.
The nervous system evolved to enable navigation throughout the environment in the pursuit of resources. Evolutionarily newer structures allowed increasingly complex adaptations but necessarily added redundancy. A dominant view of movement neuroscientists is that there is a one-to-one mapping between brain region and function. However, recent experimental data is hard to reconcile with the most conservative interpretation of this framework, suggesting a degree of functional redundancy during the performance of well-learned, constrained behaviors. This apparent redundancy likely stems from the bidirectional interactions between the various cortical and subcortical structures involved in motor control. We posit that these bidirectional connections enable flexible interactions across structures that change depending upon behavioral demands, such as during acquisition, execution or adaptation of a skill. Observing the system across both multiple actions and behavioral timescales can help isolate the functional contributions of individual structures, leading to an integrated understanding of the neural control of movement.