Biology subjects

Cai, D.

Publications and source records attributed to Cai, D..

At least 73 records · Page 4Linked to original sources

bioRxiv2020

MicroRNA840 accelerates leaf senescence by targeting the overlapping 3'UTRs of PPR and WHIRLY3 in Arabidopsis

MicroRNAs (miRNAs) negatively regulate gene expression by cleaving the target mRNA and/or impairing its translation, thereby playing a crucial role in plant development and environmental stress responses. In Arabidopsis, MIR840 is located within the overlapping 3UTR of PPR and WHIRLY3 (WHY3), both being predicted targets of miR840. Gain- and loss-of-function of miR840 in Arabidopsis resulted in opposite senescent phenotypes. Highest expression of pri-miR840 is observed at senescence initiation, and is negatively correlated with a significant reduction of PPR transcripts but not of WHY3. Although WHY3 transcript levels were not significantly affected by miR840 overexpression, its protein synthesis was strongly reduced. Mutating the cleavage sites or replacing the target sequences abolishes the miR840-mediated degradation of PPR transcripts and inhibition of WHY3 translation. In support for this, concurrent knock-down of both PPR and WHY3 in the WT resulted in the senescent phenotype resembling that of the miR840-overexpressing mutant. This indicates that both PRR and WHY3 are targets in the miR840-regulated senescent pathway. Moreover, single knockout mutant of PPR or WHY3 shows a convergent up-regulated subset of senescence-associated genes, which are also found among those induced by miR840 overexpression. Our data provide evidences for a regulatory role of miR840 in plant senescence. HighlightMicroRNA840 (miR840) has a unique miRNA-target configuration regulating PPR and WHIRLY3 genes in Arabidopsis. MiR840 is highly expressed at the onset of plant senescent stage. Both PPR and WHIRLY3 transcripts are specifically targeted in vivo within their 3UTR region by mature miR840 or its star strand in vivo. Interestingly, PPR expression is mainly repressed on mRNA transcript level by cleavage, while WHIRLY3 is predominantly translationally inhibited. We conclude that miR840 enhances plant senescence via post transcriptional gene silencing of PPR and WHIRLY3, which appear to be novel negative joint regulators of plant senescence. Footnote: The author(s) responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the intructions for Authors is: Ying Miao (ymiao@fafu.edu.cn)

molecular biology↗

bioRxiv2020

A multi-informatic description of neural differentiation in the Drosophila type-II neuroblast lineages

To adopt terminal neural fates, neural progenitors respond to a combination of molecular factors, the interplay between which remains difficult to untangle. In this work, we interrogated the type-II neuroblast lineages in the developing Drosophila brain using targeted single-cell mRNA sequencing. We used pseudotime analysis to group cells by their differentiation state and subsequently used marker gene analysis to identify genes that may play a role in neural fate specification. To aid the candidate gene selection process, we created MiCV, a scRNA-seq data visualization web tool that integrates results from the multifaceted analysis, displays the co-expression pattern of multiple genes, and provides an automated gene function curating feature. In situ profiling of these mRNAs further recovered the spatial information lacking in the single-cell data. Combining prior knowledge, in silico analysis, and in situ evidence, we characterize the molecular landscape of the developing Drosophila type-II neuroblast lineages and provide a roadmap for navigating the more complex brains.

neuroscience↗

bioRxiv2020

Unsupervised Neural Tracing in Densely Labeled Multispectral Brainbow Images

Reconstructing neuron morphology is central to uncovering the complexity of the nervous system. That is because the morphology of a neuron essentially provides the physical constraints to its intrinsic electrophysiological properties and its connectivity. Recent advances in imaging technologies generated large quantities of high-resolution 3D images of neurons in the brain. Furthermore, the multispectral labeling technology, Brainbow permits unambiguous differentiation of neighboring neurons in a densely labeled brain, therefore enables for the first time the possibility of studying the connectivity between many neurons from a light microscopy image. However, lack of reliable automated neuron morphology reconstruction makes data analysis the bottleneck of extracting rich informatics in neuroscience. Supervoxel-based neuron segmentation methods have been proposed to solve this problem, however, the use of previous approaches has been impeded by the large numbers of errors which arise in the final segmentation. In this paper, we present a novel unsupervised approach to trace neurons from multispectral Brainbow images, which prevents segmentation errors and tracing continuity errors using two innovations. First, we formulate a Gaussian mixture model-based clustering strategy to improve the separation of segmented color channels that provides accurate skeletonization results for the following steps. Next, a skeleton graph approach is proposed to allow the identification and correction of discontinuities in the neuron tree topology. We find that these innovations allow our approach to outperform current state-of-the-art approaches, which results in more accurate neuron tracing as a tree representation close to human expert annotation.

neuroscience↗

bioRxiv2020

Cellular-scale silicon probes for high-density, precisely-localized neurophysiology

Neural implants with large numbers of electrodes have become an important tool for examining brain functions. However, these devices typically displace a large intracranial volume compared to the neurons they record. This large size limits the density of implants, provokes tissue reactions that degrade chronic performance, and impedes the ability to accurately visualize recording sites within intact circuits. Here we report next-generation silicon-based neural probes at cellular-scale (5x10{micro}m cross-section), with ultra-high-density packing (as little as 66{micro}m between shanks) and 64 or 256 closely-spaced recording sites per probe. We show that these probes can be inserted into superficial or deep brain structures and maintain high-quality spike recordings in freely behaving rats for many weeks. Finally, we demonstrate a slice-in-place approach for the precise registration of recording sites relative to nearby neurons and anatomical features, including striatal {micro}-opioid receptor patches. This scalable technology provides a valuable tool for examining information processing within neural circuits, and potentially for human brain-machine interfaces.

bioengineering↗

bioRxiv2020

Superior Colliculus-Projected GABAergic Retinal Ganglion Cells Mediate Looming-Evoked Flight Response

The looming stimulus-evoked flight response is an experimental paradigm for studying innate defensive behaviors. However, how the visual looming stimulus is transmitted from the retina to the brain remains poorly understood. Here, we report that superior colliculus (SC)-projecting RGCs transmit the looming signal from the retina to the brain to mediate the looming-evoked flight behavior by releasing GABA. In the mouse retina, GABAergic RGCs are capable of projecting to many brain areas, including the SC. Superior colliculus (SC)-projecting GABAergic RGCs (spgRGCs) are mono-synaptically connected to the parvalbumin-positive SC neurons known to be required for the looming-evoked flight response. Optogenetic activation of spgRGCs triggers GABA-mediated inhibition in SC neurons. The ablation or silence of spgRGCs compromises looming-evoked flight response but not image-forming functions. Therefore, this study shows that spgRGCs control the looming-evoked flight response by regulating SC neurons via GABA, providing novel insight into the regulation of innate defensive behaviors.

neuroscience↗

bioRxiv2020

Dual located WHIRLY1 affects salicylic acid homeostasis via coordination of ICS1, 1 PAL1 and BSMT1 during Arabidopsis plant aging

Salicylic acid (SA) homeostasis determines also developmental senescence and is spatiotemporally controlled by various mechanisms, including biosynthesis, transport and conjugate formation. The alteration of WHIRLY1 (WHY1), a repressor of leaf natural senescence, with respect to allocation in the nucleus or chloroplast causes a perturbation in SA homeostasis, resulting in adverse plant senescence phenotypes. Loss of WHY1 resulted in a 5 days earlier SA peak compared to wild type plants which accumulated SA at 42 days after germination. SA accumulation coincided with an early leaf senescence phenotype, which could be prevented by ectopic expression of the nuclear WHY1 isoform (nWHY1). However, expressing the plastid WHY1 isoform (pWHY1) greatly enhanced cellular SA levels. A global transcriptional analysis in WHY1 loss-of-function background by expressing either pWHY1 or nWHY1 indicated that hormone metabolism related genes were most significantly altered. The pWHY1 isoform predominantly affected stress related gene expression, while the nWHY1 controlled rather developmental gene expression. Chromatin immunoprecipitation-qPCR (ChIP-qPCR) assays indicated that nWHY1 directly binds to the promoter region of isochorismate synthase (ICS1) to activate its expression at later stage, but indirectly activated S-adenosyl-L-methionine-dependent methyltransferase (BSMT1) gene expression via ethylene response factor 109 (ERF109), while repressing phenylalanine ammonia lyase (PAL1) expression via R2R3-MYB member 15 (MYB15) at the early stage of development. Interestingly, rising SA levels exerted a feedback effect by inducing nWHY1 modification and pWHY1 accumulation. Thus, the alteration of WHY1 organelle isoforms and the feedback of SA intervened in a circularly integrated regulatory network during developmental or stress-induced senescence in Arabidopsis.

plant biology↗

bioRxiv2020

Bitbow: a digital format of Brainbow enables highly efficient neuronal lineage tracing and morphology reconstruction in single brains

Identifying the cellular origins and mapping the dendritic and axonal arbors of neurons have been century old quests to understand the heterogeneity among these brain cells. Classical chemical and genetic methods take advantage of light microscopy and sparse labeling to unambiguously, albeit inefficiently, trace a few neuronal lineages or reconstruct their morphologies in each sampled brain. To improve the analysis throughput, we designed Bitbow, a digital format of Brainbow which exponentially expands the color palette to provide tens of thousands of spectrally resolved unique labels. We generated transgenic Bitbow Drosophila lines, established statistical tools, and streamlined sample preparation, image processing and data analysis pipelines to allow conveniently mapping neural lineages, studying neuronal morphology and revealing neural network patterns with an unprecedented speed, scale and resolution.

neuroscience↗

bioRxiv2020

Light microscopy based approach for mapping connectivity with molecular specificity

Mapping neuroanatomy is a foundational goal towards understanding brain function. Electron microscopy (EM) has been the gold standard for connectivity analysis because nanoscale resolution is necessary to unambiguously resolve chemical and electrical synapses. However, molecular information that specifies cell types is often lost in EM reconstructions. To address this, we devised a light microscopy approach for connectivity analysis of defined cell types called spectral connectomics. We combined multicolor genetic labeling (Brainbow) of neurons with a multi-round immunostaining Expansion Microscopy (miriEx) strategy to simultaneously interrogate morphology, molecular markers, and connectivity in the same brain section. We applied our multimodal profiling strategy to directly link inhibitory neuron cell types with their network morphologies. Furthermore, we showed that correlative Brainbow and endogenous synaptic machinery immunostaining can be used to define putative synaptic connections between spectrally unique neurons, as well as map putative inhibitory and excitatory inputs. We envision that spectral connectomics can be applied routinely in neurobiology labs to gain insights into normal and pathophysiological neuroanatomy across multiple animals and time points.

neuroscience↗

bioRxiv2020

The origin of domestication genes in goats

Goat domestication was critical for agriculture and civilization, but its underlying genetic changes and selection regimes remain unclear. Here we analyze the genomes of worldwide domestic goats, wild caprid species and historical remains, providing evidence of an ancient introgression event from a West Caucasian tur-like species to the ancestor of domestic goats. One introgressed locus with a strong signature of selection harbors the MUC6 gene which encodes a gastrointestinally secreted mucin. Experiments revealed that the nearly fixed introgressed haplotype confers enhanced immune resistance to gastrointestinal pathogens. Another locus with a strong signal of selection may be related to behavior. The selected alleles at these two loci emerged in domestic goats at least 7,200 and 8,100 years ago, respectively, and increased to high frequencies concurrent with the expansion of the ubiquitous modern mitochondrial haplogroup A. Tracking these archaeologically cryptic evolutionary transformations provides new insights into the mechanism of animal domestication. One Sentence SummaryGoat domestication mainly focused on immune and neural genes, with adaptive leaps driven by introgression and selection.

genomics↗

bioRxiv2019

RFEX: Simple Random Forest Model and Sample Explainer for non-Machine Learning experts

Machine Learning (ML) is becoming an increasingly critical technology in many areas. However, its complexity and its frequent non-transparency create significant challenges, especially in the biomedical and health areas. One of the critical components in addressing the above challenges is the explainability or transparency of ML systems, which refers to the model (related to the whole data) and sample explainability (related to specific samples). Our research focuses on both model and sample explainability of Random Forest (RF) classifiers. Our RF explainer, RFEX, is designed from the ground up with non-ML experts in mind, and with simplicity and familiarity, e.g. providing a one-page tabular output and measures familiar to most users. In this paper we present significant improvement in RFEX Model explainer compared to the version published previously, a new RFEX Sample explainer that provides explanation of how the RF classifies a particular data sample and is designed to directly relate to RFEX Model explainer, and a RFEX Model and Sample explainer case study from our collaboration with the J. Craig Venter Institute (JCVI). We show that our approach offers a simple yet powerful means of explaining RF classification at the model and sample levels, and in some cases even points to areas of new investigation. RFEX is easy to implement using available RF tools and its tabular format offers easy-to-understand representations for non-experts, enabling them to better leverage the RF technology.

bioinformatics↗

bioRxiv2019

Multistep metabolic engineering of Bacillus licheniformis to improve pulcherriminic acid production

Pulcherriminic acid, a cyclodipeptide, possesses the excellent antibacterial activities by chelating iron ions from environment, however, the low yield has hindered its application. In this study, high-level production of pulcherriminic acid was achieved by the multistep metabolic engineering of Bacillus licheniformis DWc9n*. Firstly, leucine (Leu) supply was increased by overexpressing the genes ilvBHC-leuABCD and ilvD involved in the Leu synthetic pathway and deleting the gene bkdAB encoding a branched-chain -keto acid dehydrogenase. The intracellular Leu content and pulcherriminic acid yield of strain W2 reached 147.4 mg/g DCW and 189.9 mg/L respectively, which corresponded to a 226.7% and 49.1% higher than those of DWc9n*. Secondly, the strain W3 was obtained by overexpressing leucyl-tRNA synthase LeuS in W2, which lead to a 190% improvement compared to DWc9n*, pulcherriminic acid yield increase to 367.7 mg/L. Thirdly, overexpression of the cytochrome synthase gene cluster yvmC-cypX further increased the yield of pulcherriminic acid to 507.4 mg/L. Finally, the secretion capability was improved by overexpressing the pulcherriminic acid transporter gene yvmA. This resulted in the 556.1 mg/L pulcherriminic acid was produced in W4/pHY-yvmA, increased by 340% as compared with DWc9n*, and it is the highest pulcherriminic acid production currently reported. Taken together, this study provided an efficient strategy for enhancing pulcherriminic acid production and might also be applied for high-level production of other cyclodipeptides.\n\nImportancePulcherriminic acid is a cyclodipeptide that derived from cyclo(L-Leu-L-Leu), which has the same iron chelation group with hydroxamate siderophores. Pulcherriminic acid producing strains can inhibit the growths of various bacteria and plant pathogenic fungi. However, the expected pulcherriminic acid yield was not achieved. This study reports efficient microbial production of pulcherriminic acid in Bacillus licheniformis DWc9n* via multistep metabolic engineering strategies. The combination of these interventions resulted in the establishment of a pulcherriminic acid overproducing strain. In combination with bioprocess engineering efforts, pulcherriminic acid was produced at a final yield of 556 mg/L in a shake flask. This is the highest pulcherriminic acid yield ever reported so far using rationally engineered microbial cell factories.

bioengineering↗

bioRxiv2019

Molecular Networks and Key Regulators of the Dysregulated Neuronal System in Alzheimer’s Disease

To study the molecular mechanisms driving the pathogenesis and identify novel therapeutic targets of late onset Alzheimers Disease (LOAD), we performed an integrative network analysis of whole-genome DNA and RNA sequencing profiling of four cortical areas, including the parahippocampal gyrus, across 364 donors spanning the full spectrum of LOAD-related cognitive and neuropathological disease severities. Our analyses revealed thousands of molecular changes and uncovered for the first-time multiple neuron specific gene subnetworks most dysregulated in LOAD. ATP6V1A, a critical subunit of vacuolar-type H+-ATPase (v-ATPase), was predicted to be a key regulator of one neuronal subnetwork and its role in disease-related processes was evaluated through CRISPR-based manipulation of human induced pluripotent stem cell derived neurons and RNAi-based knockdown in transgenic Drosophila models. This study advances our understanding of LOAD pathogenesis by providing the global landscape and detailed circuits of complex molecular interactions and regulations in several key brain regions affected by LOAD and the resulting network models provide a blueprint for developing next generation therapeutics against LOAD.

neuroscience↗

bioRxiv2019

TraceMontage: a Method for Merging Multiple Independent Neuronal Traces

BackgroundThe ability to reconstruct neuronal networks, local microcircuits, or the entire connectome is a central goal of modern neuroscience. Recently, advancements in sample preparation (e.g., sample expansion and Brainbow labeling) and optical (e.g., confocal and light sheet) techniques have enabled the imaging of increasingly large neural systems with high contrast. Tracing neuronal structures from these images proves challenging, however, necessitating tools that integrate multiple neuronal traces, potentially derived by various methods, into one combined (montaged) result.\n\nNew MethodHere, we present TraceMontage, an ImageJ/Fiji plugin for the combination of multiple neuron traces of a single image, either redundantly or non-redundantly. Internally, it uses graph theory to connect topological patterns in the 3-D spatial coordinates of neuronal trees. The software generates a single output tracing file containing the montage traces of the input tracing files and provides several measures of consistency analysis among multiple tracers.\n\nResults and Comparison to existing method(s)To our knowledge, our software is the first dedicated method for the combination of tracing results. Combining multiple tracers increases the accuracy and speed of tracing of densely-labeled samples by harnessing collaborative effort. This utility is demonstrated using fluorescence microscope images from the hippocampus and primary visual cortex (V1) in Brainbow-labeled mice.\n\nConclusionsTraceMontage provides researchers the ability to combine neuronal tracing data generated by either the same or different method(s). As datasets become larger, the ability to trace images in this parallel manner will help connectomics scale to increasingly larger neural systems.

neuroscience↗

bioRxiv2019

Isoform specificity of PKMs during long-term facilitation in Aplysia is mediated through stabilization by KIBRA

Persistent activity of protein kinase M (PKM), the truncated form of protein kinase C (PKC), can maintain long-term changes in synaptic strength in many systems including the hermaphrodite marine mollusk, Aplysia californica. Moreover, different types of long-term facilitation (LTF) in cultured Aplysia sensorimotor synapses rely on the activities of different PKM isoforms in the presynaptic sensory neuron and postsynaptic motor neuron. When the atypical PKM isoform was required, the kidney and brain expressed adaptor protein (KIBRA) was also required. Here, we explore how this isoform specificity is established. We find that PKM overexpression in the motor neuron, but not the sensory neuron, is sufficient to increase synaptic strength and that this activity is not isoform specific. KIBRA is not the rate-limiting step in facilitation since overexpression of KIBRA is neither sufficient to increase synaptic strength, nor to prolong a form of PKM-dependent intermediate synaptic facilitation. However, the isoform specificity of dominant negative (DN)-PKMs to erase LTF is correlated with isoform specific competition for stabilization by KIBRA. We identify a new conserved region of KIBRA. Different splice isoforms in this region stabilize different PKMs based on the isoform-specific sequence of an alpha-helix handle in the PKMs. Thus, specific stabilization of distinct PKMs by different isoforms of KIBRA can explain the isoform specificity of PKMs during LTF in Aplysia.\n\nSignificance StatementLong lasting changes in synaptic plasticity associated with memory formation are maintained by persistent protein kinases. We have previously shown in the Aplysia sensorimotor model that distinct isoforms of persistently active protein kinase Cs (PKMs) maintain distinct forms of long-lasting synaptic changes, even when both forms are expressed in the same motor neuron. Here, we show that, while the effects of overexpression of PKMs in not isoform specific, isoform specificity is defined by a handle helix in PKMs that confers stabilization by distinct splice forms in a previously undefined domain of the adaptor protein KIBRA. Thus, we define new regions in both KIBRA and PKMs that define the isoform specificity for maintaining synaptic strength in distinct facilitation paradigms.

neuroscience↗

bioRxiv2019

Identification of neuronal lineages in the Drosophila peripheral nervous system with a novel multi-spectral lineage tracing system

Elucidating cell lineages provides crucial understanding of development. Recently developed sequencing-based techniques enhance the scale of lineage tracing but eliminate the spatial information offered by conventional approaches. Multispectral labeling techniques, such as Brainbow, have the potential to identify lineage-related cells in situ. Here, we report Lineage Tracker Bitbow, a \"digital\" version of Brainbow that greatly expands the color diversity, and a suite of statistical methods for quantifying the lineage relationship of any two cells. Applying these tools to Drosophila peripheral nervous system, we determined lineage relationship between all neuronal pairs. Based on the refined lineage map, we explored whether distinct cis-regulatory elements are used in controlling the expression of a terminal selector gene in distinct lineage patterns. This study demonstrates LT-Bitbow as an efficient tool for in-situ lineage mapping and its potential in studying molecular mechanisms in the lineage context.

neuroscience↗

bioRxiv2018

Phase Separation of YAP Reprograms Cells for Long-term YAP Target Gene Expression

Yes-associated Protein (YAP) is a transcriptional co-activator that regulates cell proliferation and survival by binding to a selective set of enhancers for potent target gene activation, but how YAP coordinates these transcriptional responses is unknown. Here, we demonstrate that YAP forms liquid-like condensates in the nucleus in response to macromolecular crowding. Formed within seconds of hyperosmotic stress, YAP condensates compartmentalized YAPs DNA binding cofactor TEAD1 along with other YAP-related transcription co-activators, including TAZ, and subsequently induced transcription of YAP-specific proliferation genes. Super-resolution imaging using Assay for Transposase Accessible Chromatin with photoactivated localization microscopy (ATAC-PALM) revealed that YAP nuclear condensates were areas enriched in accessible chromatin domains organized as super-enhancers. Initially devoid of RNA Polymerase II (Pol II), the accessible chromatin domains later acquired Pol II, producing newly transcribed RNA. Removal of YAPs intrinsically-disordered transcription activation domain (TAD) prevented YAP condensate formation and diminished downstream YAP signaling. Thus, dynamic changes in genome organization and gene activation during YAP reprogramming is mediated by liquid-liquid phase separation.

cell biology↗

bioRxiv2018

Enhanced Synthesis of Poly Gamma Glutamic Acid by Increasing the Intracellular Reactive Oxygen Species in the Bacillus licheniformis Δ1-pyrroline-5-carboxylate Dehydrogenase Gene ycgN Deficient Strain

Poly gamma glutamic acid ({gamma}-PGA) is an anionic polyamide with numerous applications. Proline metabolism influences the formation of reactive oxygen species (ROS), and is involved in a wide range of cellular processes. However, the relation between proline metabolism and{gamma} -PGA synthesis has not yet been analyzed. In this study, our results indicated that the deletion of {Delta}1-pyrroline-5-carboxylate dehydrogenase encoded gene ycgN resulted in 85.22% higher yield of{gamma} -PGA in B. licheniformis WX-02. But the deletion of proline dehydrogenase encoded gene ycgM had no effect on{gamma} -PGA synthesis. Meanwhile, a 2.92-fold higher level of P5C was detected in ycgN deficient strain WX{Delta}ycgN, while the P5C levels in WX{Delta}ycgM and double mutant strain WX{Delta}ycgMN remained the same, compared to WX-02. The ROS level of WX{Delta}ycgN was 1.18-fold higher than that of WX-02, and the addition of n-acetylcysteine (antioxidant) into medium could decrease its ROS level, further reduced the{gamma} -PGA yield. Our results showed that proline catabolism played an important role in maintaining ROS homeostasis, and the deletion of ycgN caused P5C accumulation, which induced a transient ROS signal to promote{gamma} -PGA synthesis in B. licheniformis.\n\nImportance{gamma}-PGA is an anionic polyamide with various applications in biomedical and industrial fields. Proline metabolism influences the intracellular reactive oxygen species (ROS) and is involved in a wide range of cellular processes. Here, we report the effects of proline metabolism on{gamma} -PGA synthesis. Our results indicated that deletion of ycgN promoted the synthesis of{gamma} -PGA by increasing the intracellular levels of {Delta}1-pyrroline-5-carboxylate to generate a transient ROS signal in B. licheniformis WX-02. This study provides the valuable information that enhanced synthesis of{gamma} -PGA by knocking out of ycgN.

microbiology↗

bioRxiv2018

A Recurrent Neural Network Approach for Automated Neural Tracing in Multispectral 3D Images

Neuronal morphology reconstruction in fluorescence microscopy 3D images is essential for analyzing neuronal cell type and connectivity. Manual tracing of neurons in these images is time consuming and subjective. Automated tracing is highly desired yet is one of the foremost challenges in computational neuroscience. The multispectral labeling technique, Brainbow utilizes high dimensional spectral information to distinguish intermingled neuronal processes. It is particular interesting to develop new algorithms to include the spectral information into the tracing process. Recently, deep learning approaches achieved state-of-the-art in different computer vision and medical imaging applications. To benefit from the power of deep learning, in this paper, we propose an automated neural tracing approach in multispectral 3D Brainbow images based on recurrent neural net-work. We first adopt VBM4D approach to denoise multispectral 3D images. Then we generate cubes as training samples along the ground truth, manually traced paths. These cubes are the input to the recur-rent neural network. The proposed approach is simple and effective. The approach can be implemented with the deep learning toolbox Keras in 100 lines. Finally, to evaluate our approach, we computed the average and standard deviation of DIADEM metric from the ground truth results to our tracing results, and from our tracing results to the ground truth results. Extensive experimental results on the collected dataset demonstrate that the proposed approach performs well in Brainbow labeled mouse brain images.

neuroscience↗