Biology subjects

Zeng, H.

Publications and source records attributed to Zeng, H..

At least 199 records · Page 11Linked to original sources

bioRxiv2019

RecV recombinase system for spatiotemporally controlled light-inducible genomic modifications.

Brain circuits are composed of vast numbers of intricately interconnected neurons with diverse molecular, anatomical and physiological properties. To allow highly specific targeting of individual neurons for structural and functional studies, we modified three site-specific DNA recombinases, Cre, Dre and Flp, by combining them with a fungal light-inducible protein, Vivid, so that their recombinase activities can be driven by blue light. We generated viral vectors to express these light-inducible recombinases and demonstrated that they can induce genomic modifications in dense or sparse populations of neurons in live mouse brains controlled by one-photon or two-photon light induction. As an important application, we showed that light-inducible recombinases can produce highly targeted, sparse and strong labeling of individual neurons thereby enabling whole-brain morphological reconstruction to identify their axonal projection specificity. In addition to targeting cortical brain areas, we applied the method in deep targets, with a demonstration of functional calcium imaging. These molecular tools enable spatiotemporally-precise, targeted genomic modifications that will greatly facilitate detailed analysis of neural circuits and linking genetic identity, morphology, connectivity and function.

neuroscience↗

bioRxiv2019

Prospective, brain-wide labeling of neuronal subclasses with enhancer-driven AAVs

The rapid pace of cell type identification by new single-cell analysis methods has not been met with efficient experimental access to the newly discovered types. To enable flexible and efficient access to specific neural populations in the mouse cortex, we collected chromatin accessibility data from individual cells and clustered the single-cell data to identify enhancers specific for cell classes and subclasses. When cloned into adeno-associated viruses (AAVs) and delivered to the brain by retro-orbital injections, these enhancers drive transgene expression in specific cell subclasses in the cortex. We characterize several enhancer viruses in detail to show that they result in labeling of different projection neuron subclasses in mouse cortex, and that one of them can be used to label the homologous projection neuron subclass in human cortical slices. To enable the combinatorial labeling of more than one cell type by enhancer viruses, we developed a three-color Cre-, Flp- and Nigri-recombinase dependent reporter mouse line, Ai213. The delivery of three enhancer viruses driving these recombinases via a single retroorbital injection into a single Ai213 transgenic mouse results in labeling of three different neuronal classes/subclasses in the same brain tissue. This approach combines unprecedented flexibility with specificity for investigation of cell types in the mouse brain and beyond.

neuroscience↗

bioRxiv2019

Multimodal cell type correspondence by intersectional mFISH in intact tissues

Defining a complete set of cell types within the cortex requires reconciling disparate results achieved through diverging methodologies. To address this correspondence problem, multiple methodologies must be applied to the same cells across multiple single-cell experiments. Here we present a new approach applying spatial transcriptomics using multiplexed fluorescence in situ hybridization, (mFISH) to brain tissue previously interrogated through two photon optogenetic mapping of synaptic connectivity. This approach can resolve the anatomical, transcriptomic, connectomic, electrophysiological, and morphological characteristics of single cells within the mouse cortex.

neuroscience↗

bioRxiv2019

Transcriptomic evidence for dense peptidergic neuromodulation networks in mouse cortex

Seeking new insights into the homeostasis, modulation and plasticity of cortical synaptic networks, we have analyzed results from a single-cell RNA-seq study of 22,439 mouse neocortical neurons. Our analysis exposes transcriptomic evidence for dozens of molecularly distinct neuropeptidergic modulatory networks that directly interconnect all cortical neurons. This evidence begins with a discovery that transcripts of one or more neuropeptide precursor (NPP) and one or more neuropeptide-selective G-protein-coupled receptor (NP-GPCR) genes are highly abundant in all, or very nearly all, cortical neurons. Individual neurons express diverse subsets of NP signaling genes from palettes encoding 18 NPPs and 29 NP-GPCRs. These 47 genes comprise 37 cognate NPP/NP-GPCR pairs, implying the likelihood of local neuropeptide signaling. Here we use neuron-type-specific patterns of NP gene expression to offer specific, testable predictions regarding 37 peptidergic neuromodulatory networks that may play prominent roles in cortical homeostasis and plasticity.\n\nImpactSingle-cell mRNA sequencing data from mouse neocortex expose evidence for peptidergic neuromodulatory networks that locally interconnect every cortical neuron\n\nData HighlightsO_LIAt least 97% of mouse neocortical neurons express one or more of 18 neuropeptide precursor proteins (NPP) genes at very high levels\nC_LIO_LIAt least 98% of cortical neurons express one or more of 29 neuropeptide-selective G-protein-coupled receptor (NP-GPCR) genes cognate to the 18 highly expressed NPP genes\nC_LIO_LINeocortical expression of these 18 NPP and 29 NP-GPCR genes is highly neuron-type-specific and their expression patterns differentiate transcriptomic neuron types with exceptional power\nC_LIO_LINeuron-type taxonomy and type-specific expression of 37 cognate NPP / NP-GPCR gene pairs generate testable predictions of at least 37 local intracortical neuromodulation networks\nC_LI

neuroscience↗

bioRxiv2018

Activation of neuromodulatory axon projections in primary visual cortex during periods of locomotion and pupil dilation

Neuromodulators such as acetylcholine, noradrenaline (norepinephrine), and serotonin are released into the cortex by axons ascending from subcortical nuclei. These neuromodulators have been hypothesized to influence cortical function during behavioral periods such as arousal, locomotion, exploration, and attention. To determine when these neuromodulatory projections were active, we expressed the genetically-encoded calcium sensor GCaMP6 in neuromodulatory axons which project to the mouse primary visual cortex and performed two-photon microscopy to monitor their activity in vivo. We observed that the fluorescence of both cholinergic and noradrenergic axons increased during periods of pupil dilation, with the fluorescence of the axons rising less than one second before eye pupil dilation. We also observed increases in cholinergic and noradrenergic axon fluorescence periods of locomotion, which was accompanied by pupil dilation and nasal (forward) movement of both pupils. Locomotion was preceded by a rise in axonal fluorescence with a timing and amplitude that matched the subsequent pupil dilation, but axon fluorescence was more sustained than expected from the pupil dilation, suggesting that there is an additional physiological factor that affects cholinergic and noradrenergic axon activity in primary visual cortex during locomotion.

neuroscience↗

bioRxiv2018

The Markov link method: a nonparametric approach to combine observations from multiple experiments

This paper studies measurement linkage. An example from cell biology helps explain the problem: imagine for a given cell we can either sequence the cells RNA or we can examine its morphology, but not both. Given a cells morphology, what do we expect to see in its RNA? Given a cells RNA, what do we expect in its morphology? More broadly, given a measurement of one type, can we predict measurements of the other type? This measurement linkage problem arises in many scientific and technological fields. To solve this problem, we develop a nonparametric approach we dub the \"Markov link method\" (MLM). The MLM makes a conditional independence assumption that holds in many multi-measurement contexts and provides a way to estimate the link, the conditional probability of one type of measurement given the other. We derive conditions under which the MLM estimator is consistent and we use simulated data to show that it provides accurate measures of uncertainty. We evaluate the MLM on real data generated by a pair of single-cell RNA sequencing techniques. The MLM characterizes the link between them and helps connect the two notions of cell type derived from each technique. Further, the MLM reveals that some aspects of the link cannot be determined from the available data, and suggests new experiments that would allow for better estimates.\n\nSignificance StatementNovel experimental techniques are developing quickly, and each technique gives new perspectives. Ideally we would build theories that account for many perspectives at once. This is not easy. One challenge is that many experiments use measurement techniques that alter or destroy the subject, making it impossible to measure the same subject with both techniques and difficult to combine data from different experiments. In this paper we develop the Markov Link Method, a new tool that overcomes this challenge.

bioinformatics↗

bioRxiv2018

HiAlc Klebsiella pneumonia, one of potential chief culprits of non-alcoholic fatty liver disease: through generation of endogenous ethanol

Non-alcoholic fatty liver disease (NAFLD), a prelude of cirrhosis and hepatocellular carcinoma, is the most common chronic liver disease worldwide. NAFLD has been considerated to be associated with the composition of gut microbiota. However, causal relationship between change of gut microbiome and NAFLD remains unclear. Here we show that Klebsiella pneumoniae was significantly associated with NAFLD through inducing generation of endogenous ethanol. A strain of high alcohol-producing Klebsiella pneumoniae (HiAlc Kpn) was initially isolated from fecal samples of patient with non-alcoholic steatohepatitis (NASH) accompanied with auto-brewery syndrome (ABS). Gavage of HiAlc Kpn was capable of inducing murine model of fatty liver disease (FLD) in which had typical pathological changes of hepatic steatosis and similar liver gene expression profiles to those of alcohol intake in mice. Data derived from germ-free mice by gnotobiotic gavage further demonstrated that the HiAlc Kpn is the major cause of the changes in FLD mice. Furthermore, using proteomic and metabolitic analysis, we found that HiAlc Kpn induced generation of endogenous alcohol through the 2,3-butanediol fermentation pathway. More interestingly, the blood alcohol concentration was elevated in FLD mice induced by HiAlc Kpn after glucose intake. Clinical analysis showed that HiAlc Kpn were observed in up to 60% of patients with NAFLD. Our results suggested that HiAlc Kpn make important contribution to NAFLD, possibly through generation of the endogenous alcohol. Thus, targeting these bacteria might provide a novel therapeutic for clinical treatment of NAFLD.\n\nIn BriefFatty liver disease induced by high alcohol-producing Klebsiella pneumoniae\n\nCompeting Financial Interest StatementThe authors declare no conflicts of interest.

microbiology↗

bioRxiv2018

Connectional architecture of a mouse hypothalamic circuit node controlling social behavior

Type 1 Estrogen receptor-expressing neurons in the ventrolateral subdivision of the ventromedial hypothalamus (VMHvlEsr1) play a causal role in the control of social behaviors including aggression. Here we use six different viral-genetic tracing methods to map the connectional architecture of VMHvlEsr1 neurons. These data reveal a high level of input convergence and output divergence (\"fan-in/fan-out\") from and to over 30 distinct brain regions, with a high degree (~90%) of recurrence. Unlike GABAergic populations in other hypothalamic nuclei controlling feeding and parenting behavior, VMHvlEsr1 glutamatergic neurons collateralize to multiple targets. However, we identify two anatomically distinct subpopulations with anterior vs. posterior biases in their collateralization patterns. Surprisingly, these two subpopulations receive indistinguishable inputs. These studies suggest an overall system architecture in which an anatomically feed-forward sensory-to-motor processing stream is integrated with a dense, highly recurrent central processing circuit. This architecture differs from the \"brain-inspired\" feed-forward circuits used in certain types of artificial intelligence networks.\n\nSIGNIFICANCEHow the cellular heterogeneity of brain nuclei maps onto circuit connectivity, the relationship of this anatomical mapping to behavioral function, and whether there are general principles underlying this relationship, remains poorly understood. Here we systematically map the connectivity of estrogen receptor-1-expressing neurons in the ventromedial hypothalamus (VMHvlEsr1), which control aggression and other social behaviors. We find that a relatively sparse, anatomically feed-forward sensory-to-motor processing stream is integrated with a dense, highly recurrent central processing circuit. Further, the VMHvl contains at least two subpopulations of Esr1+ neurons with different cell body characteristics and locations, with distinct patterns of collateralization to downstream targets. Nevertheless, these projection-defined subpopulations receive similar inputs. This input-output organization appears distinct from those described in other hypothalamic nuclei.

neuroscience↗

bioRxiv2018

The claustrum is required for reward acquisition under high cognitive demand

The claustrum is proposed to mediate a variety of functions ranging from sensory binding to top-down cognitive control of action, but direct functional assessments of this telencephalic nucleus are lacking. Here we employ the guanine nucleotide-binding subunit beta-4 cre driver line in mice to selectively monitor and manipulate claustrum projection neurons. Using fiber photometry, we find elevated claustrum activity prior to an expected cue during correct performance on a cognitively demanding five-choice response assay relative to a less-demanding one-choice version of the task. Claustrum activity during reward acquisition is also enhanced when cognitive demand is higher. Furthermore, we use optogenetic inhibition of claustrum prior to the expected cue to demonstrate that claustrum is critical for accurate performance on the five-choice, but not the one-choice, task. These results suggest the claustrum supports a cognitive control function necessary for reward acquisition under cognitively demanding conditions.

neuroscience↗

bioRxiv2018

MLL1 minimal catalytic complex is a dynamic conformational ensemble susceptible to pharmacological allosteric disruption

Histone H3K4 methylation is an epigenetic mark associated with actively transcribed genes. This modification is catalyzed by the mixed lineage leukaemia (MLL) family of histone methyltransferases including MLL1, MLL2, MLL3, MLL4, SET1A and SET1B. Catalytic activity of MLL proteins is dependent on interactions with additional conserved proteins but the structural basis for subunit assembly and the mechanism of regulation is not well understood. We used a hybrid methods approach to study the assembly and biochemical function of the minimally active MLL1 complex (MLL1, WDR5 and RbBP5). A combination of small angle X-ray scattering (SAXS), cross-linking mass spectrometry (XL-MS), NMR spectroscopy, and computational modeling were used to generate a dynamic ensemble model in which subunits are assembled via multiple weak interaction sites. We identified a new interaction site between the MLL1 SET domain and the WD40 repeat domain of RbBP5, and demonstrate the susceptibility of the catalytic function of the complex to disruption of individual interaction sites.

biophysics↗

bioRxiv2018

Sparse recurrent excitatory connectivity in the cortical microcircuit of the adult mouse and human

Generating a comprehensive description of cortical networks requires a large-scale, systematic approach. To that end, the Allen Institute is engaged in a pipeline project using multipatch electrophysiology, supplemented with 2-photon optogenetics, to characterize connectivity and synaptic signaling between classes of neurons in adult mouse and human cortex. We focus on producing results detailed enough for the generation of computational models and enabling comparison with future studies. Here we report our examination of intralaminar connectivity within each of several classes of excitatory neurons. We find that connections are sparse but present among all excitatory cell types and layers we sampled, with the most sparse connections in layers 5 and 6. Almost all mouse synapses exhibited short-term depression with similar dynamics. Synaptic signaling between a subset of layer 2/3 neurons; however, exhibited facilitation. These results contribute to a body of evidence describing recurrent excitatory connectivity as a conserved feature of cortical microcircuits.

neuroscience↗

bioRxiv2018

The organization of intracortical connections by layer and cell class in the mouse brain

The mammalian cortex is a laminar structure composed of many cell types densely interconnected in complex ways. Recent systematic efforts to map the mouse mesoscale connectome provide comprehensive projection data on interareal connections, but not at the level of specific cell classes or layers within cortical areas. We present here a significant expansion of the Allen Mouse Brain Connectivity Atlas, with [~]1,000 new axonal projection mapping experiments across nearly all isocortical areas in 49 Cre driver lines. Using 13 lines selective for cortical layer-specific projection neuron classes, we identify the differential contribution of each layer/class to the overall intracortical connectivity patterns. We find layer 5 (L5) projection neurons account for essentially all intracortical outputs. L2/3, L4, and L6 neurons contact a subset of the L5 cortical targets. We also describe the most common axon lamination patterns in cortical targets. Most patterns are consistent with previous anatomical rules used to determine hierarchical position between cortical areas (feedforward, feedback), with notable exceptions. While diverse target lamination patterns arise from every source layer/class, L2/3 and L4 neurons are primarily associated with feedforward type projection patterns and L6 with feedback. L5 has both feedforward and feedback projection patterns. Finally, network analyses revealed a modular organization of the intracortical connectome. By labeling interareal and intermodule connections as feedforward or feedback, we present an integrated view of the intracortical connectome as a hierarchical network.

neuroscience↗

bioRxiv2018

High resolution data-driven model of the mouse connectome

Knowledge of mesoscopic brain connectivity is important for understanding inter- and intra-region information processing. Models of structural connectivity are typically constructed and analyzed with the assumption that regions are homogeneous. We instead use the Allen Mouse Brain Connectivity Atlas to construct a model of whole brain connectivity at the scale of 100 {micro}m voxels. The dataset used consists of 366 anterograde tracing experiments in wild type C7BL/6 mice, mapping fluorescently-labeled neuronal projections brain-wide. Inferring spatial connectivity with this dataset remains underdetermined, since the approximately 2 x 105 source voxels outnumber the number of experiments. To address this, we assume that connection patterns and strengths vary smoothly across major brain divisions. We model the connectivity at each voxel as a radial basis kernel-weighted average of the projection patterns of nearby injections. The voxel model outperforms a previous regional model in predicting held-out experiments and compared to a human-curated dataset. This voxel-scale model of the mouse connectome permits researchers to extend their previous analyses of structural connectivity to unprecedented levels of resolution, and allows for comparison with functional imaging and other datasets.

neuroscience↗

bioRxiv2018

All-optical electrophysiology reveals brain-state dependent changes in hippocampal subthreshold dynamics and excitability

A technology to record membrane potential from multiple neurons, simultaneously, in behaving animals will have a transformative impact on neuroscience research1. Parallel recordings could reveal the subthreshold potentials and intercellular correlations that underlie network behavior2. Paired stimulation and recording can further reveal the input-output properties of individual cells or networks in the context of different brain states3. Genetically encoded voltage indicators are a promising tool for these purposes, but were so far limited to single-cell recordings with marginal signal to noise ratio (SNR) in vivo4-6. We developed improved near infrared voltage indicators, high speed microscopes and targeted gene expression schemes which enabled recordings of supra- and subthreshold voltage dynamics from multiple neurons simultaneously in mouse hippocampus, in vivo. The reporters revealed sub-cellular details of back-propagating action potentials, correlations in sub-threshold voltage between multiple cells, and changes in dynamics associated with transitions from resting to locomotion. In combination with optogenetic stimulation, the reporters revealed brain state-dependent changes in neuronal excitability, reflecting the interplay of excitatory and inhibitory synaptic inputs. These tools open the possibility for detailed explorations of network dynamics in the context of behavior.

neuroscience↗

bioRxiv2018

Flexible Learning-Free Segmentation and Reconstruction for Sparse Neuronal Circuit Tracing

Imaging is a dominant strategy for data collection in neuroscience, yielding stacks of images that often scale to gigabytes of data for a single experiment. Machine learning algorithms from computer vision can serve as a pair of virtual eyes that tirelessly processes these images, automatically constructing more complete and realistic circuits. In practice, such algorithms are often too error-prone and computationally expensive to be immediately useful. We address these shortcomings with a new fast, flexible, learning-free method for sparse segmentation and reconstruction of neural volumes. Unlike learning methods, our Flexible Learning-free Reconstruction of Imaged Neural volumes (FLoRIN) pipeline exploits structure-specific contextual clues and requires no training. This approach generalizes across different modalities, including serially-sectioned scanning electron microscopy (sSEM) of genetically labeled and contrast enhanced processes, spectral confocal reflectance (SCoRe) microscopy, and high-energy synchrotron X-ray microtomography (CT) of large tissue volumes. We deploy the FLoRIN pipeline on newly published and novel mouse datasets, demonstrating the high biological fidelity of the pipelines reconstructions, which are of sufficient quality for preliminary biological study. Compared to existing supervised learning methods, it is both significantly faster (up to several orders of magnitude) and produces high-quality reconstructions that are robust to noise and artifacts.

neuroscience↗

bioRxiv2018

Parallel holographic illumination enables sub-millisecond two-photon optogenetic activation in mouse visual cortex in vivo

Selective control of action potential generation in individual cells from a neuronal ensemble is desirable for dissecting circuit mechanisms underlying perception and behavior. Here, by using two-photon (2P) temporally focused computer-generated holography (TF-CGH), we demonstrate optical manipulation of neuronal excitability at the supragranular layers of anesthetized mouse visual cortex. Utilizing amplified laser-pulses delivered via a localized holographic spot, our optical system achieves suprathreshold activation by exciting either of the three optogenetic actuators, ReaChR, CoChR or ChrimsonR, with brief illumination ([≤] 10 ms) at moderate excitation power ((in average [≤] 0.2 mW/m2 corresponding to [≤] 25 mW/cell). Using 2P-guided whole-cell or cell-attached recordings in positive neurons expressing respective opsin in vivo, we find that parallel illumination induces spikes of millisecond temporal resolution and sub-millisecond precision, which are preserved upon repetitive illuminations up to tens of Hz. Holographic stimulation thus enables temporally precise optogenetic activation independently of opsins channel kinetics. Furthermore, we demonstrate that parallel optogenetic activation can be combined with functional imaging for all-optical control of a neuronal sub-population that co-expresses the photosensitive opsin ReaChR and the calcium indicator GCaMP6s. Parallel optical control of neuronal activity with cellular resolution and millisecond temporal precision should be advantageous for investigating neuronal connections and further yielding causal links between connectivity, microcircuit dynamics, and brain functions.

neuroscience↗

bioRxiv2017

Equivalent high-resolution identification of neuronal cell types with single-nucleus and single-cell RNA-sequencing

Transcriptional profiling of complex tissues by RNA-sequencing of single nuclei presents some advantages over whole cell analysis. It enables unbiased cellular coverage, lack of cell isolation-based transcriptional effects, and application to archived frozen specimens. Using a well-matched pair of single-nucleus RNA-seq (snRNA-seq) and single-cell RNA-seq (scRNA-seq) SMART-Seq v4 datasets from mouse visual cortex, we demonstrate that similarly high-resolution clustering of closely related neuronal types can be achieved with both methods if intronic sequences are included in nuclear RNA-seq analysis. More transcripts are detected in individual whole cells (~11,000 genes) than nuclei (~7,000 genes), but the majority of genes have similar detection across cells and nuclei. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues.

neuroscience↗

bioRxiv2017

Cell-nonautonomous local and systemic responses to cell arrest enable long-bone catch-up growth

Catch-up growth after insults to growing organs is paramount to achieving robust body proportions. In fly larvae, local injury is followed by local and systemic compensatory mechanisms that allow damaged tissues to regain proportions with other tissues. In vertebrates, local catch-up growth has been described after transient reduction of bone growth, but the underlying cellular responses are controversial. We developed an approach to study catch-up growth in foetal mice by inducing mosaic expression of the cell cycle suppressor p21 in the cartilage cells (chondrocytes) that drive long bone elongation. By specifically targeting the left hindlimb, the right limb served as an internal control. Strikingly, left-right limb symmetry was not altered, revealing deployment of compensatory mechanisms. Above a certain threshold of insult, an orchestrated response was triggered involving local enhancement of bone growth and systemic growth reduction that ensured body proportions were maintained. The local response entailed hyper-proliferation of spared left-limb chondrocytes that was associated with reduced chondrocyte density. The systemic effect involved impaired placental IGF signalling and function, revealing bone-placenta communication. Thus, vertebrates, much like invertebrates, can mount coordinated local and systemic responses to developmental insults to ensure normal body proportions are maintained.

developmental biology↗