A neural network model of flexible grasp movement generation, bioRxiv, 2019-08-25
AbstractOne of the main ways we interact with the world is using our hands. In macaques, the circuit formed by the anterior intraparietal area, the hand area of the ventral premotor cortex, and the primary motor cortex is necessary for transforming visual information into grasping movements. We hypothesized that a recurrent neural network mimicking the multi-area structure of the anatomical circuit and trained to transform visual features into the muscle fiber velocity required to grasp objects would recapitulate neural data in the macaque grasping circuit. While a number of network architectures produced the required kinematics, modular networks with visual input and activity that was encouraged to be biologically realistic best matched neural data and the inter-area differences present in the biological circuit. Network dynamics could be explained by simple rules that also allowed the correct prediction of kinematics and neural responses to novel objects, providing a potential mechanism for flexibly generating grasping movements.
biorxiv neuroscience 200-500-users 2019An easy-to-assemble, robust, and lightweight drive implant for chronic tetrode recordings in freely moving animals, bioRxiv, 2019-08-25
AbstractTetrode arrays are the gold-standard method for neuronal recordings in many studies with behaving animals, especially for deep structures and chronic recordings. Here we outline an improved drive design for use in freely behaving animals. Our design makes use of recently developed technologies to reduce the complexity and build time of the drive while maintaining a low weight. The design also presents an improvement over many existing designs in terms of robustness and ease of use. We describe two variants a 16 tetrode implant weighing ∼2 g for mice, bats, tree shrews and similar animals, and a 64 tetrode implant weighing ∼16 g for rats, and similar animals.These designs were co-developed and optimized alongside a new class of drive-mounted feature-rich amplifier boards with ultra-thin RF tethers, as described in an upcoming paper (Newman, Zhang et al., in prep). This design significantly improves the data yield of chronic electrophysiology experiments.
biorxiv neuroscience 0-100-users 2019Galactose-modified duocarmycin prodrugs as senolytics, bioRxiv, 2019-08-25
SUMMARYSenescence is a stable growth arrest that impairs the replication of damaged, old or preneoplastic cells, therefore contributing to tissue homeostasis. Senescent cells accumulate during ageing and are associated with diseases, such as cancer, fibrosis and many age-related pathologies. Recent evidence suggests that the selective elimination of senescent cells can be effective on the treatment of many of these senescence-associated diseases. A universal characteristic of senescent cells is that they display elevated activity of the lysosomal β-galactosidase this has been exploited as a marker for senescence (senescence-associated β-galactosidase activity). Consequently, we hypothesised that galactose-modified cytotoxic prodrugs will be preferentially processed by senescent cells, resulting in their selective killing. Here, we show that different galactose-modified duocarmycin (GMD) derivatives preferentially kill senescent cells. GMD prodrugs induce selective apoptosis of senescent cells in a lysosomal β-galactosidase (GLB1)-dependent manner. GMD prodrugs can eliminate a broad range of senescent cells in culture, and treatment with a GMD prodrug enhances the elimination of bystander senescent cells that accumulate upon whole body irradiation or doxorubicin treatment of mice. Moreover, taking advantage of a mouse model of human adamantinomatous craniopharyngioma (ACP), we show that treatment with a GMD pro-drug result selectively reduced the number of β-catenin-positive preneoplastic senescent cells, what could have therapeutic implications. In summary, the above results show that galactose-modified duocarmycin prodrugs behave as senolytics, suggesting that they could be used to treat a wide range of senescence-related pathologies.
biorxiv cell-biology 0-100-users 2019Chromosome-level assemblies of multiple Arabidopsis genomes reveal hotspots of rearrangements with altered evolutionary dynamics, bioRxiv, 2019-08-23
AbstractWe report chromosome-level, reference-quality assemblies of seven Arabidopsis thaliana accessions selected across the global range of this predominately ruderal plant. Each genome revealed between 13-17 Mb rearranged and 5-6 Mb novel sequence introducing copy-number changes in ∼5,000 genes, including ∼1,900 genes which are not part of the current reference annotation. Analyzing the collinearity between the genomes revealed ∼350 regions (4.1% of the euchromatin) where accession-specific tandem duplications destroyed the syntenic gene order between the genomes. These hotspots of rearrangements were characterized by the loss of meiotic recombination in hybrids within these regions and the enrichment of genes implicated in biotic stress response. Together this suggests that hotspots of rearrangements are governed by altered evolutionary dynamics as compared to the rest of the genome, which are based on new mutations and not on the recombination of existing variation, and thereby enable a quick response to the ever-evolving challenges of biotic stress.
biorxiv genetics 100-200-users 2019Deep learning at base-resolution reveals motif syntax of the cis-regulatory code, bioRxiv, 2019-08-22
AbstractGenes are regulated through enhancer sequences, in which transcription factor binding motifs and their specific arrangements (syntax) form a cis-regulatory code. To understand the relationship between motif syntax and transcription factor binding, we train a deep learning model that uses DNA sequence to predict base-resolution binding profiles of four pluripotency transcription factors Oct4, Sox2, Nanog, and Klf4. We interpret the model to accurately map hundreds of thousands of motifs in the genome, learn novel motif representations and identify rules by which motifs and syntax influence transcription factor binding. We find that instances of strict motif spacing are largely due to retrotransposons, but that soft motif syntax influences motif interactions at protein and nucleosome range. Most strikingly, Nanog binding is driven by motifs with a strong preference for ∼10.5 bp spacings corresponding to helical periodicity. Interpreting deep learning models applied to high-resolution binding data is a powerful and versatile approach to uncover the motifs and syntax of cis-regulatory sequences.
biorxiv genomics 100-200-users 2019Deep Learning-Based Point-Scanning Super-Resolution Imaging, bioRxiv, 2019-08-22
Point scanning imaging systems (e.g. scanning electron or laser scanning confocal microscopes) are perhaps the most widely used tools for high resolution cellular and tissue imaging. Like all other imaging modalities, the resolution, speed, sample preservation, and signal-to-noise ratio (SNR) of point scanning systems are difficult to optimize simultaneously. In particular, point scanning systems are uniquely constrained by an inverse relationship between imaging speed and pixel resolution. Here we show these limitations can be mitigated via the use of deep learning-based super-sampling of undersampled images acquired on a point-scanning system, which we termed point-scanning super-resolution (PSSR) imaging. Oversampled, high SNR ground truth images acquired on scanning electron or Airyscan laser scanning confocal microscopes were crappified to generate semi-synthetic training data for PSSR models that were then used to restore real-world undersampled images. Remarkably, our EM PSSR model could restore undersampled images acquired with different optics, detectors, samples, or sample preparation methods in other labs. PSSR enabled previously unattainable 2 nm resolution images with our serial block face scanning electron microscope system. For fluorescence, we show that undersampled confocal images combined with a multiframe PSSR model trained on Airyscan timelapses facilitates Airyscan-equivalent spatial resolution and SNR with ~100x lower laser dose and 16x higher frame rates than corresponding high-resolution acquisitions. In conclusion, PSSR facilitates point-scanning image acquisition with otherwise unattainable resolution, speed, and sensitivity.
biorxiv bioinformatics 200-500-users 2019