Emergence of reward expectation signals in identified dopamine neurons, bioRxiv, 2017-12-23
AbstractCoherent control of purposive actions emerges from the coordination of multiple brain circuits during learning. Dissociable brain circuits and cell-types are thought to preferentially participate in distinct learning mechanisms. For example, the activity of midbrain dopamine (mDA) neurons is proposed to primarily, or even exclusively, reflect reward prediction error signals in well-trained animals. To study the specific contribution of individual circuits requires observing changes before tight functional coordination is achieved. However, little is known about the detailed timing of the emergence of reward-related representations in dopaminergic neurons. Here we recorded activity of identified dopaminergic neurons as naïve mice learned a novel stimulus-reward association. We found that at early stages of learning mDA neuron activity reflected both external (sensory) and internal (action initiation) causes of reward expectation. The increasingly precise correlation of action initiation with sensory stimuli rather than an evaluation of outcomes governed mDA neuron activity. Thus, our data demonstrate that mDA neuron activity early in learning does not reflect errors, but is more akin to a Hebbian learning signal - providing new insight into a critical computation in a highly conserved, essential learning circuit.
biorxiv neuroscience 100-200-users 2017Cell “hashing” with barcoded antibodies enables multiplexing and doublet detection for single cell genomics, bioRxiv, 2017-12-22
ABSTRACTDespite rapid developments in single cell sequencing technology, sample-specific batch effects, detection of cell doublets, and the cost of generating massive datasets remain outstanding challenges. Here, we introduce cell “hashing”, where oligo-tagged antibodies against ubiquitously expressed surface proteins are used to uniquely label cells from distinct samples, which can be subsequently pooled. By sequencing these tags alongside the cellular transcriptome, we can assign each cell to its sample of origin, and robustly identify doublets originating from multiple samples. We demonstrate our approach by pooling eight human PBMC samples on a single run of the 10x Chromium system, substantially reducing our per-cell costs for library generation. Cell “hashing” is inspired by, and complementary to, elegant multiplexing strategies based on genetic variation, which we also leverage to validate our results. We therefore envision that our approach will help to generalize the benefits of single cell multiplexing to diverse samples and experimental designs.
biorxiv genomics 100-200-users 2017NanoPack visualizing and processing long read sequencing data, bioRxiv, 2017-12-22
AbstractSummary Here we describe NanoPack, a set of tools developed for visualization and processing of long read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences.Availability and Implementation The NanoPack tools are written in Python3 and released under the GNU GPL3.0 Licence. The source code can be found at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpsgithub.comwdecosternanopack>httpsgithub.comwdecosternanopack<jatsext-link>, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for linux and are available as a graphical user interface, a web service at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpnanoplot.bioinf.be>httpnanoplot.bioinf.be<jatsext-link> and command line tools.Contactwouter.decoster@molgen.vib-ua.beSupplementary information Supplementary tables and figures are available at Bioinformatics online.
biorxiv bioinformatics 100-200-users 2017The essential genome of Escherichia coli K-12, bioRxiv, 2017-12-22
ABSTRACTTransposon-Directed Insertion-site Sequencing (TraDIS) is a high-throughput method coupling transposon mutagenesis with short-fragment DNA sequencing. It is commonly used to identify essential genes. Single gene deletion libraries are considered the gold standard for identifying essential genes. Currently, the TraDIS method has not been benchmarked against such libraries and therefore it remains unclear whether the two methodologies are comparable. To address this, a high density transposon library was constructed in Escherichia coli K-12. Essential genes predicted from sequencing of this library were compared to existing essential gene databases. To decrease false positive identification of essential gene candidates, statistical data analysis included corrections for both gene length and genome length. Through this analysis new essential genes and genes previously incorrectly designated as essential were identified. We show that manual analysis of TraDIS data reveals novel features that would not have been detected by statistical analysis alone. Examples include short essential regions within genes, orientation-dependent effects and fine resolution identification of genome and protein features. Recognition of these insertion profiles in transposon mutagenesis datasets will assist genome annotation of less well characterized genomes and provides new insights into bacterial physiology and biochemistry.IMPORTANCEIncentives to define lists of genes that are essential for bacterial survival include the identification of potential targets for antibacterial drug development, genes required for rapid growth for exploitation in biotechnology, and discovery of new biochemical pathways. To identify essential genes in E. coli, we constructed a very high density transposon mutant library. Initial automated analysis of the resulting data revealed many discrepancies when compared to the literature. We now report more extensive statistical analysis supported by both literature searches and detailed inspection of high density TraDIS sequencing data for each putative essential gene for the model laboratory organism, Escherichia coli. This paper is important because it provides a better understanding of the essential genes of E. coli, reveals the limitations of relying on automated analysis alone and a provides new standard for the analysis of TraDIS data.
biorxiv microbiology 100-200-users 2017Coherent representations of subjective spatial position in primary visual cortex and hippocampus, bioRxiv, 2017-12-19
A major role of vision is to guide navigation, and navigation is strongly driven by vision1-4. Indeed, the brain’s visual and navigational systems are known to interact5, 6, and signals related to position in the environment have been suggested to appear as early as in visual cortex6, 7. To establish the nature of these signals we recorded in primary visual cortex (V1) and in the CA1 region of the hippocampus while mice traversed a corridor in virtual reality. The corridor contained identical visual landmarks in two positions, so that a purely visual neuron would respond similarly in those positions. Most V1 neurons, however, responded solely or more strongly to the landmarks in one position. This modulation of visual responses by spatial location was not explained by factors such as running speed. To assess whether the modulation is related to navigational signals and to the animal’s subjective estimate of position, we trained the mice to lick for a water reward upon reaching a reward zone in the corridor. Neuronal populations in both CA1 and V1 encoded the animal’s position along the corridor, and the errors in their representations were correlated. Moreover, both representations reflected the animal’s subjective estimate of position, inferred from the animal’s licks, better than its actual position. Indeed, when animals licked in a given location – whether correct or incorrect – neural populations in both V1 and CA1 placed the animal in the reward zone. We conclude that visual responses in V1 are tightly controlled by navigational signals, which are coherent with those encoded in hippocampus, and reflect the animal’s subjective position in the environment. The presence of such navigational signals as early as in a primary sensory area suggests that these signals permeate sensory processing in the cortex.
biorxiv neuroscience 100-200-users 2017Muscle specific stress fibers give rise to sarcomeres and are mechanistically distinct from stress fibers in non-muscle cells, bioRxiv, 2017-12-19
AbstractThe sarcomere is the basic contractile unit within cardiomyocytes driving heart muscle contraction. We sought to test the mechanisms regulating thin (i.e., actin) and thick (i.e., myosin) filament assembly during sarcomere formation. Thus, we developed an assay using human cardiomyocytes to test de novo sarcomere assembly. Using this assay, we report a population of muscle-specific stress fibers are essential sarcomere precursors. We show sarcomeric actin filaments arise directly from these muscle stress fibers. This process requires formin-mediated but not Arp23-mediated actin polymerization and nonmuscle myosin IIB but not non-muscle myosin IIA. Furthermore, we show a short species of β cardiac myosin II filaments grows to form ~1.5 long filaments that then “stitch” together to form the stack of filaments at the core of the sarcomere (i.e., A-band). Interestingly, these are different from mechanisms that have previously been reported during stress fiber assembly in non-muscle cells. Thus, we provide a new model of cardiac sarcomere assembly based on distinct mechanisms of stress fiber regulation between non-muscle and muscle cells.
biorxiv cell-biology 100-200-users 2017