Biology subjects

Ding, L.

Publications and source records attributed to Ding, L..

At least 109 records · Page 6Linked to original sources

bioRxiv2021

Brain-wide neural co-activations in resting human

Spontaneous neural activity in human as assessed with resting-state functional magnetic resonance imaging (fMRI) exhibits brain-wide coordinated patterns in the frequency of <0.1Hz. However, fast brain-wide networks at the timescales of neuronal events (milliseconds to sub-seconds) and their spatial, spectral, and propagational characteristics remain unclear due to the temporal constraints of hemodynamic signals. With milli-second resolution and whole-head coverage, scalp-based electroencephalography (EEG) provides a unique window into brain-wide networks with neuronal-timescale dynamics, shedding light on the organizing principles of brain function. Using state-of-the-art signal processing techniques, we reconstructed cortical neural tomography from resting-state EEG and extracted component-based co-activation patterns (cCAPs). These cCAPs revealed brain-wide intrinsic networks and their dynamics, indicating the configuration/reconfiguration of resting human brains into recurring and propagating functional states, which are featured with the prominent spatial phenomena of global patterns and anti-state pairs of co-(de)activations. Rich oscillational structures across a wide frequency band (i.e., 0.6Hz, 5Hz, and 10Hz) were embedded in the dynamics of these functional states. We further identified a superstructure that regulated between-state propagations and governed a significant aspect of brain-wide network dynamics. These findings demonstrated how resting-state EEG data can be functionally decomposed using cCAPs to reveal rich structures of brain-wide human neural activations.

neuroscience↗

bioRxiv2021

SC2MeNetDrug: A computational tool to uncover inter-cell signaling targets and identify relevant drugs based on single cell RNA-seq data

Single-cell RNA sequencing (scRNA-seq) is a powerful technology to investigate the transcriptional programs in stromal, immune, and disease cells, like tumor cells or neurons within the Alzheimers Disease (AD) brain or tumor microenvironment (ME) or niche. Cell-cell communications within ME play important roles in disease progression and immunotherapy response and are novel and critical therapeutic targets. Though many tools of scRNA-seq analysis have been developed to investigate the heterogeneity and sub-populations of cells, few were designed for uncovering cell-cell communications of ME and predicting the potentially effective drugs to inhibit the communications. Moreover, the data analysis processes of discovering signaling communication networks and effective drugs using scRNA-seq data are complex and involve a set of critical analysis processes and external supportive data resources, which are difficult for researchers who have no strong computational background and training in scRNA-seq data analysis. To address these challenges, in this study, we developed a novel open-source computational tool, sc2MeNetDrug (https://fuhaililab.github.io/sc2MeNetDrug/). It was specifically designed using scRNA-seq data to identify cell types within disease MEs, uncover the dysfunctional signaling pathways within individual cell types and interactions among different cell types, and predict effective drugs that can potentially disrupt cell-cell signaling communications. sc2MeNetDrug provided a user-friendly graphical user interface to encapsulate the data analysis modules, which can facilitate the scRNA-seq data-based discovery of novel inter-cell signaling communications and novel therapeutic regimens.

bioinformatics↗

bioRxiv2021

Macrophage proliferation machinery leads to PDAC progression, but susceptibility to innate immunotherapy.

Tumor-associated macrophages (TAMs) are involved in many aspects of cancer progression and correlate with poor clinical outcomes in many cancer types, including pancreatic ductal adenocarcinomas (PDACs). Previous studies have shown that TAMs can populate PDAC tumors not only by monocyte recruitment but also by local proliferation. However, the impact local proliferation might have on macrophage phenotype and cancer progression is unknown. Here, we utilized genetically engineered cancer models, single-cell RNA-sequencing data, and in vitro systems to show that proliferation of TAMs was driven by colony stimulating factor-1 (CSF1) produced by cancer-associated fibroblasts. CSF1 induced high levels of p21 in macrophages, which regulated both TAM proliferation and phenotype. TAMs in human and mouse PDACs with high levels of p21 had more inflammatory and immunosuppressive phenotypes. The p21 expression in TAMs was induced by both stromal interaction and/or chemotherapy treatment. Finally, by modeling p21 expression levels in TAMs, we found that p21-driven macrophage immunosuppression in vivo drove tumor progression. Serendipitously, the same p21-driven pathways that drive tumor progression, also drive response to CD40 agonist. These data suggest that stromal or therapy-induced regulation of cell cycle machinery can regulate both macrophage-mediated immune suppression and susceptibility to innate immunotherapy. SummaryTAMs are indicative of poor clinical outcomes and in PDAC their number is sustained in part by local proliferation. This study shows that stromal desmoplasia drives local proliferation of TAMs, and induces their immunosuppressive ability through altering cell cycle machinery, including p21 expression. Serendipitously, these changes in p21 in TAMs also potentially render tumors more sensitive to CD40 agonist therapy.

cancer biology↗

bioRxiv2021

PDXNet Portal: Patient-Derived Xenograft model, data, workflow, and tool discovery

We created the PDX Network (PDXNet) Portal (https://portal.pdxnetwork.org/) to centralize access to the National Cancer Institute-funded PDXNet consortium resources (i.e., PDX models, sequencing data, treatment response data, and bioinformatics workflows), to facilitate collaboration among researchers, and to make resources easily available for research. The portal includes sections for resources, analysis results, metrics for PDXNet activities, data processing protocols, and training materials for processing PDX data. The initial portal release highlights PDXNet model and data resources, including 334 new models across 33 cancer types. Tissue samples of these models were deposited in the NCIs Patient-Derived Model Repository (PDMR) for public access. These models have 2,822 associated sequencing files from 873 samples across 307 patients, which are hosted on the Cancer Genomics Cloud powered by Seven Bridges and the NCI Cancer Data Service for long-term storage and access with dbGaP permissions. The portal also includes results from standardized analysis workflows on PDXNet sequencing files and PDMR data (2,594 samples from 463 patients across 78 disease types). These 15 analysis workflows for whole-exome and RNA-Seq data are freely available, robust, validated, and standardized. The model and data lists will grow substantially over the next two years and will be continuously updated as new data are available. PDXNet models support multi-agent treatment studies, determination of sensitivity and resistance mechanisms, and preclinical trials. The PDXNet portal is a centralized location for these data and resources, which we expect to be of significant utility for the cancer research community.

cancer biology↗

bioRxiv2021

UCHL1 inhibited by A1 astrocytes facilitates aggregates clearance to promote neural stem cells activation after spinal cord injury

Activation of endogenous neural stem cells (NSCs) is critically important for the adult neurogenesis. However, NSC activation is extremely limited after spinal cord injury (SCI). Recent evidence suggests that accumulation of protein aggregates impedes quiescent NSC activation. Here, we found ubiquitin c-terminal hydrolase l-1 (UCHL1), an important deubiquitinating enzyme, functioned to facilitate NSC activation by clearing protein aggregations through ubiquitin-proteasome approach. Upregulation of UCHL1 enhanced NSC proliferation in the spinal cord after injury. Based on protein microarray analysis of SCI cerebrospinal fluid, it is further revealed that C3+ neurotoxic reactive astrocytes negatively regulated UCHL1 and aggresome clearance through C3/C3aR signaling, resulting in reduced capacity of NSC to activate. Furthermore, blockade of reactive astrocytes or C3/C3aR pathway led to enhanced NSC activation post-SCI. Together, this study elucidated a mechanism regulating NSC activation in the adult spinal cord involving the UCHL1-proteasome approach, which may provide potential molecular targets for NSC fate regulation.

neuroscience↗

bioRxiv2021

Cell-adaptable dynamic hydrogel reinforced with stem cells improves the functional repair of spinal cord injury by alleviating neuroinflammation

Spinal cord injury (SCI) is one of the most challenging clinical issues. It is characterized by the disruption of neural circuitry and connectivity, resulting in neurological disability. Adipose-derived stem cells (ADSCs) serve as a promising source of therapeutic cells for SCI treatment. However, the therapeutic outcomes of direct ADSCs transplantation are limited in the presence of an inflammatory microenvironment. Herein, a cell-adaptable neurogenic (CaNeu) hydrogel was developed as a delivery vehicle for ADSCs to promote neuronal regeneration after SCI. The dynamic network of CaNeu hydrogel loaded with ADSCs provides a cell-infiltratable matrix that enhances axonal growth and eventually leads to improved motor evoked potential, hindlimb strength, and coordination of complete spinal cord transection in rats. Furthermore, the CaNeu hydrogel also establishes an anti-inflammatory microenvironment by inducing a shift in the polarization of the recruited macrophages toward the pro-regeneration (M2) phenotype. Our study showed that the CaNeu-hydrogel-mediated ADSCs delivery resulted in significantly suppressed neuroinflammation and apoptosis, and that this phenomenon involved the PI3K/Akt signaling pathway. Our findings indicate that the CaNeu hydrogel is a valuable delivery vehicle to assist stem cell therapy for SCI, providing a promising strategy for central nervous system diseases.

bioengineering↗

bioRxiv2021

A deep generative model of 3D single-cell organization

1 AbstractWe introduce a framework for end-to-end integrative modeling of 3D single-cell multi-channel fluorescent image data of diverse subcellular structures. We employ stacked conditional {beta}-variational autoencoders to first learn a latent representation of cell morphology, and then learn a latent representation of subcellular structure localization which is conditioned on the learned cell morphology. Our model is flexible and can be trained on images of arbitrary subcellular structures and at varying degrees of sparsity and reconstruction fidelity. We train our full model on 3D cell image data and explore design trade-offs in the 2D setting. Once trained, our model can be used to impute structures in cells where they were not imaged and to quantify the variation in the location of all subcellular structures by generating plausible instantiations of each structure in arbitrary cell geometries. We apply our trained model to a small drug perturbation screen to demonstrate its applicability to new data. We show how the latent representations of drugged cells differ from unperturbed cells as expected by on-target effects of the drugs. 2 Author summaryIts impossible to acquire all the information we want about every cell were interested in in a single experiment. Even just limiting ourselves to imaging, we can only image a small set of subcellular structures in each cell. If we are interested in integrating those images into a holistic picture of cellular organization directly from data, there are a number of approaches one might take. Here, we leverage the fact that of the three channels we image in each cell, two stay the same across the data set; these two channels assess the cells shape and nuclear morphology. Given these two reference channels, we learn a model of cell and nuclear morphology, and then use this as a reference frame in which to learn a representation of the localization of each subcellular structure as measured by the third channel. We use {beta}-variational autoencoders to learn representations of both the reference channels and representations of each subcellular structure (conditioned on the reference channels of the cell in which it was imaged). Since these models are both probabilistic and generative, we can use them to understand the variation in the data from which they were trained, to generate instantiations of new cell morphologies, and to generate imputations of structures in real cell images to create an integrated model of subcellular organization.

cell biology↗

bioRxiv2021

Rapid Biomarker Screening of Alzheimer's Disease by Machine Learning and Graphene-Assisted Raman Spectroscopy

As the most common cause of dementia, the study of Alzheimers disease (AD) faces challenges in terms of understanding the cause, monitoring the pathogenesis, and developing early diagnosis and effective treatment. Rapid and accurate identification of AD biomarkers in the brain is critical to provide key insights into AD and facilitate the development of early diagnosis methods. In this work, we developed a platform that enables a rapid screening of AD biomarkers by employing graphene-assisted Raman spectroscopy and machine learning interpretation in AD transgenic animal brains. Specifically, we collected Raman spectra on slices of mouse brains with and without AD and used machine learning to classify AD and non-AD spectra. By contacting monolayer graphene with the brain slices, the accuracy was significantly increased from 77% to 98% in machine learning classification. Further, using linear supporting vector machine (SVM), we identified a spectral feature importance map that reveals the importance of each Raman wavenumber in classifying AD and non-AD spectra. Based on this spectral feature importance map, we identified AD biomarkers including A{beta} and tau proteins, and other potential biomarkers, such as triolein, phosphatidylcholine, and actin, which have been confirmed by other biochemical studies. Our Raman-machine learning integrated method with interpretability is promising to greatly accelerate the study of AD and can be extended to other tissues, biofluids, and for various other diseases.

neuroscience↗

bioRxiv2021

Thrombopoietin from hepatocytes promotes hematopoietic stem cell regeneration after myeloablation

The bone marrow niche plays a critical role in hematopoietic recovery and hematopoietic stem cell (HSC) regeneration after myeloablation. However, it is not clear whether systemic factors beyond the local niche are required for these essential processes in vivo. Thrombopoietin (TPO) is a critical cytokine promoting hematopoietic rebound after myeloablation and its transcripts are expressed by multiple cellular sources. The upregulation of bone marrow-derived TPO has been proposed to be crucial for hematopoietic recovery and HSC regeneration after stress. Nonetheless, the cellular source of TPO in stress has never been investigated genetically. We assessed the functional sources of TPO following two common myeloablative perturbations: 5-fluorouracil (5-FU) administration and irradiation. Using a Tpo translational reporter, we found that the liver but not the bone marrow is the major source of TPO protein after myeloablation. Mice with conditional Tpo deletion from osteoblasts or bone marrow stromal cells showed normal recovery of HSCs and hematopoiesis after myeloablation. In contrast, mice with conditional Tpo deletion from hepatocytes showed significant defects in HSC regeneration and hematopoietic rebound after myeloablation. Thus, systemic TPO from the liver is necessary for HSC regeneration and hematopoietic recovery in myeloablative stress conditions.

cell biology↗

bioRxiv2021

ILK play a key role in partial bladder outler obstruction (PBOO) by regulation TLR4/NF-κB(p65) pathway

AimThe purpose of this research was to discuss the effects and relative mechanisms of ILK in PBOO by vivo and vitro study. Materials and methodsThe SD rats were divided into Normal, Sham and Model groups. Collecting Bladder outlet tissue, observation pathology and fibrosis levels by H&E and Masson staining. Measuring cell apoptosis and cell viability by TUNEL and p-histone H3 staining, ILK protein were evaluated by WB and IHC assay in Bladder outlet tissue. Using TGF-{beta}1 stimulating BSMC cell to make PBOO cell model. Measuring cell proliferation by CCK-8 assay; Relative gene and proteins expression were evaluated by immunofluorescence, WB and RT-qPCR assay. ResultsCompared with Normal group, bladder weight, collage fiber area, apoptosis cell number and cell viability were significantly difference with ILK protein significantly increasing in bladder outer tissues of Model group (P < 0.05, respectively). In vitro cell experiment, ILK overexpression had effects to stimulate cell proliferation via TLR4/NF-{kappa}B(p65) pathway; however, with ILK knockdown, the cell proliferation was significantly depressed via regulation TLR4/NF-{kappa}B(p65). ConclusionILK play an important role in PBOO induced cell proliferation, ILK knockdown had effects to improve PBOO induced cell hyper-proliferation via depressing TLR4/NF-{kappa}B(p65) pathway.

genetics↗

bioRxiv2021

Interleukin-15 Receptor α Chain Knockout NOD-SCID mice have reduced numbers of NK cells, develop thymic lymphomas and fail to engraft human hematopoietic cells

NOD-SCID IL2r{gamma}cnull (NSG) mice are widely used to model human immune cell development because they are more permissive for human hematopoietic cell engraftment and reconstitution than NOD-SCID mice. While increased human reconstitution in the blood of NSG mice has been attributed to the absence of mouse NK cells, deletion of the common gamma chain ({gamma}c) limits development of lymphoid tissue inducer cells and precludes development of normal secondary lymphoid structures. The disorganized lymphoid tissue leads to compromised human T cell-B cell interactions and results in variable human immune cell function in human immune system (HIS) NSG compared to NOD-SCID mice. We attempted to remove mouse NK cells from NOD-SCID mice while retaining other {gamma}c-dependent cytokine responses by targeted disruption of the mouse genomic IL15RA locus with CRISPR/Cas9. IL15R is required for the development, function and survival of NK cells. NOD-SCID IL15R-/- mice showed reductions in NK cells and NK cell function. However, NOD-SCID IL15R-/- mice demonstrated accelerated thymic lymphomagenesis and showed earlier mortality compared to NOD-SCID mice. This result suggests that mouse NK cells are important to delay lymphoma development in NOD-SCID mice. We transplanted thymectomized NOD-SCID ILl5R-/- mice with human fetal liver CD34+ cells and thymus to determine if these mice supported engraftment and development of a transplanted HIS. Surprisingly, we found that peripheral human engraftment was inferior (mean 0.05% of lymphocytes) to that in both NOD-SCID (mean, 10.5% of lymphocytes) and NSG (mean, 54% of lymphocytes) mice. These results indicate that NOD-SCID IL15R-/- mice are not permissive for human CD34+ cell engraftment.

immunology↗

bioRxiv2021

Genome annotation with long RNA reads reveals new patterns of gene expression in an ant brain

Functional genomic analyses rely on high-quality genome assemblies and annotations. Highly contiguous genome assemblies have become available for a variety of species, but accurate and complete annotation of gene models, inclusive of alternative splice isoforms and transcription start and termination sites remains difficult with traditional approaches. Here, we utilized full-length isoform sequencing (Iso-Seq), a long-read RNA sequencing technology, to obtain a comprehensive annotation of the transcriptome of the ant Harpegnathos saltator. The improved genome annotations include additional splice isoforms and extended 3 untranslated regions for more than 4,000 genes. Reanalysis of RNA-seq experiments using these annotations revealed several genes with caste-specific differential expression and tissue-or caste-specific splicing patterns that were missed in previous analyses. The extended 3 untranslated regions afforded great improvements in the analysis of existing single-cell RNA-seq data, resulting in the recovery of the transcriptomes of 18% more cells. The deeper single-cell transcriptomes obtained with these new annotations allowed us to identify additional markers for several cell types in the ant brain, as well as genes differentially expressed across castes in specific cell types. Our results demonstrate that Iso-Seq is an efficient and effective approach to improve genome annotations and maximize the amount of information that can be obtained from existing and future genomic datasets in Harpegnathos and other organisms.

genomics↗

bioRxiv2021

Adipsin promotes bone marrow adiposity by priming mesenchymal stem cells

BackgroundBone marrow (BM) adipose tissue (BMAT) has been shown to be vital for regulating metabolism and maintaining skeletal homeostasis in the marrow niche. As a reflection of BM remodeling, BMAT is highly responsive to nutrient fluctuations, hormonal changes and metabolic disturbances such as obesity and diabetes mellitus. Expansion of BMAT has also been strongly associated with bone loss in mice and humans. However, the regulation of BM plasticity remains poorly understood, as does the mechanism that links changes in marrow adiposity with bone remodeling. MethodsUsing C57BL/6 mice as a model, we employed the bone-protected PPAR{gamma} constitutive deacetylation (2KR), Adipsin, and its downstream effector, C3, knockout mice. These mice were challenged to thiazolidinedione treatment, calorie restriction, or aging in order to induce bone loss and MAT expansion. Analysis of bone density and marrow adiposity was performed using a CT scanner and by RNA analysis to assess adipocyte and osteoblast markers. For in vitro studies, primary bone marrow stromal cells (BMSCs) were isolated and subjected to osteoblastogenic or adipogenic differentiation or chemical treatment followed by morphological and molecular analyses. Clinical data was obtained from samples of a previous clinical trial of fasting and high calorie diet in healthy human volunteers. ResultsWe have shown that Adipsin is the most up-regulated adipokine during BMAT expansion in mice and humans, in a PPAR{gamma} acetylation-dependent manner. Ablation of Adipsin in mice specifically inhibited BMAT expansion but not peripheral adipose depots, and improved bone mass during calorie restriction, thiazolidinedione treatment, and aging. These effects were mediated through its downstream effector, complement component C3, to prime common progenitor cells toward adipogenesis rather than osteoblastogenesis through inhibiting Wnt/{beta}- catenin signaling. ConclusionsAdipsin promotes new adipocyte formation and affects skeletal remodeling in the BM niche. Our study reveals a novel mechanism whereby the BM sustains its own plasticity through paracrine and endocrine actions of a unique adipokine. FundingThis work was supported by the National Institutes of Health T32DK007328 (NA), F31DK124926 (NA), R01DK121140 (JCL), R01AR068970 (BZ), R01AR071463 (BZ), R01DK112943 (LQ), and P01HL087123 (LQ).

molecular biology↗

bioRxiv2021

High-content screening of coronavirus genes for innate immune suppression revealsenhanced potency of SARS-CoV-2 proteins

Suppression of the host intracellular innate immune system is an essential aspect of viral replication. Here, we developed a suite of medium-throughput high-content cell-based assays to reveal the effect of individual coronavirus proteins on antiviral innate immune pathways. Using these assays, we screened the 196 protein products of seven coronaviruses (SARS-CoV-2, SARS-CoV-1, 229E, NL63, OC43, HKU1 and MERS). This includes a previously unidentified gene in SARS-CoV-2 encoded within the Spike gene. We observe immune-suppressing activity in both known host-suppressing genes (e.g., NSP1, Orf6, NSP3, and NSP5) as well as other coronavirus genes, including the newly identified SARS-CoV-2 protein. Moreover, the genes encoded by SARS-CoV-2 are generally more potent immune suppressors than their homologues from the other coronaviruses. This suite of pathway-based and mechanism-agnostic assays could serve as the basis for rapid in vitro prediction of the pathogenicity of novel viruses based on provision of sequence information alone.

systems biology↗

bioRxiv2021

Spatially Interacting Phosphorylation Sites and Mutations in Cancer

Advances in mass-spectrometry have generated increasingly large-scale proteomics datasets containing tens of thousands of phosphorylation sites (phosphosites) that require prioritization. We develop a bioinformatics tool called HotPho and systematically discover 3D co-clustering of phosphosites and cancer mutations on protein structures. HotPho identifies 474 such hybrid clusters containing 1,255 co-clustering phosphosites, including RET p.S904/Y928, the conserved HRAS/KRAS p.Y96, and IDH1 p.Y139/IDH2 p.Y179 that are adjacent to recurrent mutations on protein structures not found by linear proximity approaches. Hybrid clusters, enriched in histone and kinase domains, frequently include expression-associated mutations experimentally shown as activating and conferring genetic dependency. Approximately 300 co-clustering phosphosites are verified in patient samples of 5 cancer types or previously implicated in cancer, including CTNNB1 p.S29/Y30, EGFR p.S720, MAPK1 p.S142, and PTPN12 p.S275. In summary, systematic 3D clustering analysis highlights nearly 3,000 likely functional mutations and over 1,000 cancer phosphosites for downstream investigation and evaluation of potential clinical relevance.

bioinformatics↗

bioRxiv2021

Ferulic acid combined with skeletal stem cells to repair irradiated bone defect

The reconstruction of irradiated bone defects after settlement of skeletal tumors remains a significant challenge in clinical applications. In this study, we explored radiation-induced skeletal stem cell (SSC) stemness impairments and rescuing effects of ferulic acid (FA) on SSCs in vitro and in vivo. The immunophenotype, cell renewal, cell proliferation, and differentiation of SSCs in vitro after irradiation were investigated. Mechanistically, the changes in tissue regeneration-associated gene expression and MAPK pathway activation in irradiated SSCs were evaluated. The regenerative capacity of SSCs in the presence of FA in an irradiated bone defect mouse model was also investigated. We found that irradiation reduced CD140a- and CD105-positive cells in skeletal tissues and mouse-derived SSCs. Additionally, irradiation suppressed cell proliferation, colony formation, and osteogenic differentiation of SSCs. The RNA-Seq results showed that tissue regeneration-associated gene expression decreased, and the western blotting results demonstrated the suppression of phosphorylated p38/MAPK and ERK/MAPK in irradiated SSCs. Notably, FA significantly rescued the radiation-induced impairment of SSCs by activating the p38/MAPK and ERK/MAPK pathways. Moreover, the results of imaging and pathological analyses demonstrated that FA enhanced the bone repair effects of SSCs in an irradiated bone defect mouse model substantially. Importantly, inhibition of the p38/MAPK and ERK/MAPK pathways in SSCs by specific chemical inhibitors partially abolished the promotive effect of FA on SSC-mediated bone regeneration. In summary, our findings reveal a novel function of FA in repairing irradiated bone defects by maintaining SSC stemness and suggest that the p38/MAPK and ERK/MAPK pathways contribute to SSC-mediated tissue regeneration post-radiation. Significance StatementRadiotherapy combined with surgery for the settlement of skeletal tumors usually leads to large bone defects and hampers wound healing. Skeletal stem cells (SSCs) have been defined as tissue-specific stem cells in skeletons and are highlighted in bone development and regeneration. Ferulic acid is a phytochemical with a wide range of therapeutic effects, including alleviation of radiation-induced oxidative stress and promotion of tissue regeneration. In the current study, promising data based on an in vitro cell model and an in vivo animal model demonstrates that ferulic acid alleviates radiation-induced impairment of SSCs and promotes SSC-mediated bone regeneration post-radiation.

cell biology↗

bioRxiv2021

Petabyte-Scale Multi-Morphometry of Single Neurons for Whole Brains

Recent advances in neuroscience make the extraction of full neuronal morphology at whole brain dataset available. To produce quality morphometry at large scale, it is highly desirable but extremely challenging to efficiently handle petabyte-scale high-resolution whole brain imaging database. Here, we developed a multi-level method to produce high quality somatic, dendritic, axonal, and potential synaptic morphometry, which was made possible by utilizing necessary petabyte hardware and software platform to optimize both the data and workflow management. Our method also boosts data sharing and remote collaborative validation. We highlight a petabyte application dataset involving 62 whole mouse brains, from which we identified 50,233 somata of individual neurons, profiled the dendrites of 11,322 neurons, reconstructed the full 3-D morphology of more than one thousand neurons including their dendrites and full axons, and detected million scale putative synaptic sites derived from axonal boutons. Analysis and simulation of these data indicate the promise of this approach for modern large-scale morphology applications.

neuroscience↗

bioRxiv2020

Single-Cell Manifold Preserving Feature Selection (SCMER)

1AO_SCPLOWBSTRACTC_SCPLOWA key challenge in studying organisms and diseases is to detect rare molecular programs and rare cell populations (RCPs) that drive development, differentiation, and transformation. Molecular features such as genes and proteins defining RCPs are often unknown and difficult to detect from unenriched single-cell data, using conventional dimensionality reduction and clustering-based approaches. Here, we propose a novel unsupervised approach, named SCMER, which performs UMAP style dimensionality reduction via selecting a compact set of molecular features with definitive meanings. We applied SCMER in the context of hematopoiesis, lymphogenesis, tumorigenesis, and drug resistance and response. We found that SCMER can identify non-redundant features that sensitively delineate both common cell lineages and rare cellular states ignored by current approaches. SCMER can be widely used for discovering novel molecular features in a high dimensional dataset, designing targeted, cost-effective assays for clinical applications, and facilitating multi-modality integration.

bioinformatics↗