Biology subjects

Jiang, C.

Publications and source records attributed to Jiang, C..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

Kun-peng: an ultra-memory-efficient, fast, and accurate pan-domain taxonomic classifier for all

Comprehensive metagenomic sequence classification of diverse environmental samples faces significant computing memory challenges due to exponentially expanding genome databases. Here, we present Kun-peng, featuring a unique ordered 4GB block database design for ultra-efficient resource management, faster processing, and higher accuracy. When benchmarked on mock communities (Amos HiLo, Mixed, and NIST) against Kraken2, Centrifuge, and Sylph. Kun-peng matched Sylph, achieving the highest precision and lowest false-positive rates while demonstrating superior time and memory efficiency among all tested tools. Furthermore, Kun-pengs efficient database architecture enables the practical utilization of large-scale reference databases that were previously computationally prohibitive. In comprehensive testing across 586 air, water, soil, and human metagenomic samples using an expansive pan-domain database (204,477 genomes, 4.3TB), Kun-peng classified 69.78-94.29% of reads, achieving 38-43% higher classification rates than Kraken2 with the standard database. Unexpectedly, Sylph failed to classify any reads in air samples and left > 99.85% of reads unclassified in water and soil samples. In terms of computational efficiency, Kun-peng processed each sample in 0.2[~]11.2 minutes using only 4.0[~]35.4GB peak memory. Remarkably, these processing times were comparable to Kraken2 using the standard database (81GB, 5% of the pan-domain database). Memory-wise, Kun-peng required only 35.4GB peak memory with the pan-domain database, representing a 473-fold reduction compared to Kraken2. When compared to Sylph, Kun-peng processes samples up to 46.3 times faster while using up to 20.6 times less memory. Overall, Kun-peng offers an ultra-memory-efficient, fast, and accurate solution for pan-domain metagenomic classifications.

bioinformatics↗

bioRxiv2024

Recovery of highly contiguous genomes from complex terrestrial habitats reveals over 15,000 novel prokaryotic species and expands characterization of soil and sediment microbial communities

Genomes are fundamental to understanding microbial ecology and evolution. The emergence of high-throughput, long-read DNA sequencing has enabled recovery of microbial genomes from environmental samples at scale. However, expanding the microbial genome catalogue of soils and sediments has been challenging due to the enormous complexity of these environments. Here, we performed deep, long-read Nanopore sequencing of 154 soil and sediment samples collected across Denmark and through an optimised bioinformatics pipeline, we recovered genomes of 15,314 novel microbial species, including 4,757 high-quality genomes. The recovered microbial genomes span 1,086 novel genera and provide the first high-quality reference genomes for 612 previously known genera, expanding the phylogenetic diversity of the prokaryotic tree of life by 8 %. The long-read assemblies also enabled the recovery of thousands of complete rRNA operons, biosynthetic gene clusters and CRISPR-Cas systems, all of which were underrepresented and highly fragmented in previous terrestrial genome catalogues. Furthermore, the incorporation of the recovered MAGs into public genome databases significantly improved species-level classification rates for soil and sediment metagenomic datasets, thereby enhancing terrestrial microbiome characterization. With this study, we demonstrate that long-read sequencing and optimised bioinformatics, allows cost-effective recovery of high-quality microbial genomes from highly complex ecosystems, which remain the largest untapped source of biodiversity for expanding genome databases and filling in the gaps of the tree of life.

bioinformatics↗

bioRxiv2024

The comprehensive detection of hemoglobinopathy variants via long-read sequencing

BACKGROUNDThe genetic complexity of hemoglobin genes, characterized by high GC content and homologous sequences, poses significant challenges for detecting hemoglobin variants in clinical settings. METHODSA long-read indexed PCR method utilizing the novel CycloneSEQ nanopore sequencing platform was developed to detect all variant types, including single nucleotide variants (SNVs), deletions, structural variants (SVs) in HBA, HBB, HBD, and HBG genes. The method was validated using 507 clinical samples to assess its performance. RESULTSThe long-read indexed PCR system employed 13 primers targeting the hemoglobin gene clusters. This design enabled the detection of 37 types of HBA deletions, 5 SV (3 multicopies (, anti3.7, anti4.2) and 2 fusion allele (HK and anti-HK)), 37 HBB deletions, and all SNVs in the targeted regions. Validation across 507 samples (84 with HBA variants, 60 with HBB variants, 256 with both HBA and HBB variants, and 107 with no known variants) demonstrated 100.0% sensitivity and specificity. Additionally, the long-read sequencing enabled phasing of variants within hemoglobin genes, providing insights critical for clinical interpretation. CONCLUSIONSThe long-read indexed PCR method, combined with the CycloneSEQ nanopore sequencing platform, proved to be a robust and efficient solution for detecting hemoglobinopathy variants. The integration of indexed primers and barcoding enhances scalability, making this method ideal for large-scale population screening programs in the future.

genomics↗

bioRxiv2024

PTTG1-Mediated Pericyte Dysfunction Drives Diabetes-Induced Microvascular Dysfunction

BackgroundPericytes are crucial for the development, stabilization, and functional regulation of microvasculature, especially in the retina. In diabetic retinopathy (DR), early loss of pericytes is a key event that drives microvascular dysfunction. Despite their critical role, the mechanisms underlying the functional heterogeneity of pericytes in DR remain poorly understood, impeding the development of effective therapeutic strategies. MethodsWe employed single-cell RNA sequencing to construct a comprehensive single- cell atlas of non-diabetic and diabetic retinas. Using bioinformatic clustering and subcluster analysis, we identified a specific pericyte subcluster associated with diabetic microvascular complications. Differential gene expression analysis and immunofluorescence validation highlighted PTTG1 as a potential key regulator of pericyte dysfunction. To investigate its functional role, we emplyed CRISPR/Cas9 and adenoviral vectors to modulate PTTG1 expression in vitro and in vivo. Combined transcriptomic and metabolomic approaches were used to explore the mechanistic pathways through which PTTG1 influences pericyte biology and vascular function. ResultsWe identified a novel pericyte subcluster characterized by elevated expression of PTTG1, which was strongly correlated with diabetic microvascular dysfunction. Silencing PTTG1 using CRISPR/Cas9 and siRNA in vitro mitigated pericyte dysfunction under high- glucose conditions. Targeted knockdown of PTTG1 using viral vectors improved retinal vascular integrity and reduced neovascularization in diabetic mice. Transcriptomic and untargeted metabolomic analyses revealed that PTTG1 knockdown reprogrammed pericyte energy metabolism by modulating glycolysis pathway genes, reducing oxidative stress, and restoring pericyte function, ultimately alleviating microvascular dysfunction in DR. ConclusionsPTTG1 plays a critical role in regulating pericyte dysfunction and maintaining vascular homeostasis in diabetic retinopathy. By modulating key metabolic pathways and pericyte phenotypes, PTTG1 represents a promising therapeutic target for treating diabetic microvascular complications. These insights offer a novel molecular framework for developing targeted therapies aimed at restoring retinal vascular health in diabetic patients.

molecular biology↗

bioRxiv2024

Circuit mechanisms underlying sexually dimorphic outcomes of early life stress

Stress during early life influences brain development and can affect social, motor, and emotional processes. We describe a striking sex difference in the effects of early life stress (ELS), which produces anhedonia and anxiety-like behaviors in female adolescent mice, as reported previously, but repetitive behavioral pathology and social deficits in male adolescent mice. Notably, this parallels sex differences seen in the prevalence of psychiatric symptoms: depression and anxiety disorders are more common in girls and women, whereas neurodevelopmental disorders like autism spectrum disorder and Tourette syndrome are markedly more common in boys and men. We characterized the effects of ELS on the medial prefrontal cortex (mPFC) and on its projections to the dorsal striatum (dStr) and lateral septum (LS). ELS males, but not females, developed hyperactivity in the cortico-striatal circuit and hypoactivity in the cortico-septal circuit. Chemogenetic manipulation of cortico-striatal projection neurons modulates repetitive behavioral pathology and social behaviors in stressed males, and anhedonia in stressed females. Activation of cortico-septal projection neurons rescues social deficits in stressed males. We conclude that early life stress produces sexually dimorphic behavioral effects, with potential relevance to human psychiatric symptoms, through its differential effects on cortico-striatal and cortico-septal circuits.

neuroscience↗

bioRxiv2024

Self-Authenticating Genomic Materials with Advanced Genome Signatures

The authenticity and integrity of synthetic genomic materials containing valuable intellectual property are essential for advancing scientific knowledge and enhancing biosafety. Existing DNA tags and watermarks, however, have limited efficacy due to low mutation tolerance and inadequate digital encoding capacity. Here, we present "Genome Signature", a biochemically stable and tamper-resistant DNA labeling system that enables the creation of self-authenticating genomes. Central to this system is a novel Golomb-ruler-derived Genome-Comb, which efficiently maps extensive nucleotide sequences onto limited codons within endogenous genes, significantly improving error correction and data encoding across millions of nucleotides. Our method successfully recorded a 4.5 million-nucleotide genome in living E. coli. The Genome Signature autonomously identifies and corrects mutations and effectively encodes data within codon orders, ensuring genome integrity and authenticity. Furthermore, it allows precise tracking of sequences across different cells, potentially revolutionizing the development of reliable genomic materials in synthetic biology.

synthetic biology↗

bioRxiv2024

Citalopram exhibits immune-dependent anti-tumor effects by modulating C5aR1+ TAMs and CD8+ T cells

Administration of selective serotonin reuptake inhibitors (SSRIs) is associated with a reduced cancer risk and shows significant anti-tumor effects across multiple tumor types, suggesting the potential for repurposing SSRIs in cancer therapy. Nonetheless, the specific molecular target and mechanism of action of SSRIs remain to be fully elucidated. Here, we reveal that citalopram exerts an immune-dependent anti-tumor effects in hepatocellular carcinoma (HCC). Interestingly, the anti-HCC effects of citalopram are not reliant on its conventional target, the serotonin transporter. Through various drug repurposing approaches, including global reverse gene expression profiling, drug affinity responsive target stability assay, and molecular docking, the complement component 5a receptor 1 (C5aR1) is identified as a new target of citalopram. C5aR1 is predominantly expressed by tumor-associated macrophages (TAMs), and citalopram treatment enhances local macrophage phagocytosis and elicits CD8+ T anti-tumor immunity. C5aR1 deficiency or depletion of CD8+ T cells hinders the anti-HCC effects of citalopram. Collectively, our study reveals the immunomodulatory roles of citalopram in inducing anti-tumor immunity, and provides a basis for considering the repurposing of SSRIs as promising anticancer agents for HCC treatment.

cancer biology↗

bioRxiv2024

Multi-omics investigation of spontaneous T2DM macaque reveals gut microbiota promote T2DM by up-regulating the absorption of excess palmitic acid

Although gut microbiota and lipid metabolites have been suggested to be closely associated with type 2 diabetes mellitus (T2DM), the interactions between gut microbiota, lipid metabolites and the host in T2DM development remains unclear. Rhesus macaques may be the best animal model to investigate these relationships given their spontaneous development of T2DM. We identified eight spontaneous T2DM macaques and conducted a comprehensive study investigating the relationships using multi-omics sequencing technology. Our results from 16S rRNA, metagenome, metabolome and transcriptome analyses identified that gut microbiota imbalance, tryptophan metabolism and fatty acid {beta} oxidation disorders, long-chain fatty acid (LCFA) accumulation, and inflammation occurred in T2DM macaques. We verified the accumulation of palmitic acid (PA) and activation of inflammation in T2DM macaques. Importantly, mice transplanted with spontaneous T2DM macaque fecal microbiota and fed a high PA diet developed prediabetes within 120 days. We determined that gut microbiota mediated the absorption of excess PA in the ileum, resulting in the accumulation of PA in the serum consequently leading to T2DM in mice. In particular, we demonstrated that the specific microbiota composition was probably involved in the process. This study provides new insight into interactions between microbiota and metabolites and confirms causative effect of gut microbiota on T2DM development.

microbiology↗

bioRxiv2024

High aspect ratio graphene oxide: a highly efficient plasmid DNA deliverer for plant seed

Plant genetic engineering plays a central role in crop improvement and the biosynthesis of natural products. However, the plant cell wall serves as a natural barrier that restricts the efficient delivery of exogenous biomolecules, particularly the direct transfer of plasmid DNA into plant seeds. Here, we introduce a novel form of graphene oxide characterized by a high aspect ratio, synthesized through low-voltage, low-current, and prolonged electrochemical oxidation in a 0.5 mol/L NaOH aqueous solution. The high aspect ratio graphene oxide (HARGO) can effectively deliver plasmid DNA to Poa crymophila Keng seeds, achieving a 90% success rate. Furthermore, it is effective for both wheat and rice seeds. The underlying mechanism of this efficient delivery is that HARGO can physically absorb plasmid DNA and transport the adsorbed plasmid DNA into plant cells and deeper tissues through passive transport, eliminating the need for chemical modification of polyethylene glycol (PEG) and polyethyleneimine (PEI). These findings offer a dependable non-integrating plasmid DNA delivery tool for plant genetic engineering, which will significantly impact the advancement of plant biotechnology.

bioengineering↗

bioRxiv2024

Endosomal hyper-acidification via proton-activated chloride channel deletion in neurons impairs AMPA receptor endocytosis and LTD

Endosomal homeostasis is critical for neuronal function, including the post-synaptic trafficking of -amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs). Dynamic AMPAR trafficking is a major component of synaptic plasticity, such as hippocampal long-term potentiation (LTP) and long-term depression (LTD) and is thought to be required for learning and memory. Dramatic alteration of endosomal pH has been reported to negatively affect synaptic transmission and neural development, but the underlying mechanisms by which pH is involved in AMPAR trafficking are unclear. Here, we show that the proton-activated chloride (PAC) channel localizes to early and recycling endosomes along neuronal dendrites and prevents hyper-acidification of endosomes. To directly measure AMPAR endocytosis, we used a new method to assess LTD using HaloTag-GluA2 and found that the loss of PAC reduces AMPAR internalization during chemical LTD in primary neurons, while AMPAR trafficking in unstimulated cells or during chemical LTP is unaffected. Consistently, pyramidal neuron-specific PAC knockout mice had impaired hippocampal LTD, but not LTP, and performed poorly in the Morris water maze reversal test, exhibiting an inability to adapt to changing environments (also referred to as behavioral flexibility). We conclude that proper maintenance of pH by PAC is important during LTD to regulate AMPAR trafficking in a manner critical for animal physiology and behavior. SummaryThe ability to adapt to changing environments stems from the plasticity of neurons, which can modulate their synaptic strength in response to neural activity. We discovered a novel mechanism by which an endosomal proton-activated chloride channel (PAC) is involved in synaptic weakening, or long-term depression (LTD). To improve tools used to study LTD, we developed a live-cell imaging assay to directly observe -amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) endocytosis. PAC-deficient neurons have hyper-acidified endosomes and fail to endocytose AMPARs during LTD. Neuron-specific PAC knockout mice have impaired hippocampal LTD and fail to adapt to changes in their environment. The role of endosomal pH in synaptic function is understudied, and our results provide a novel mechanism whereby PAC can affect synaptic LTD.

neuroscience↗

bioRxiv2024

Systemic identification of functionally conserved lncRNA metabolic regulators in human and mouse livers

BACKGROUND & AIMSUnlike protein-coding genes, the majority of human long non-coding RNAs (lncRNAs) lack conservation based on their sequences, posing a challenge for investigating their role in a pathophysiological context for clinical translation. This study explores the hypothesis that non-conserved lncRNAs in human and mouse livers may share similar metabolic functions, giving rise to functionally conserved lncRNA metabolic regulators (fcLMRs). METHODSWe developed a sequence-independent strategy to select putative fcLMRs, and performed extensive analysis to determine the functional similarities of putative human and mouse LMR pairs (h/mLMRs). RESULTSWe found that several pairs of putative fcLMRs share similar functions in regulating gene expression. We further demonstrated that a pair of fcLMRs, h/mLMR1, robustly regulated triglyceride levels by modulating the expression of a similar set of lipogenic genes. Mechanistically, h/mLMR1 binds to PABPC1, a regulator of protein translation, via short motifs on either lncRNA with divergent sequences but similar structures. This interaction inhibits protein translation, activating an amino acid-mTOR-SREBP1 axis to regulate lipogenic gene expression. Intriguingly, PABPC1-binding motifs on each lncRNA fully rescued the functions of their corresponding LMRs in the opposite species. Given the elevated expression of h/mLMR1 in humans and mice with hepatic steatosis, the PABPC1-binding motif on hLMR1 emerges as a potential non-conserved human drug target whose functions can be fully validated in a physiologically relevant setting before clinical studies. CONCLUSIONSOur study supports that fcLMRs represent a novel and prevalent biological phenomenon, and deep phenotyping of genetic mLMR mouse models constitutes a powerful approach to understand the pathophysiological role of lncRNAs in the human liver.

physiology↗

bioRxiv2024

SSRI antidepressant citalopram reverses the Warburg effect to inhibit hepatocellular carcinoma by directly targeting GLUT1

Although there is growing appreciation for effective repurposing of selective serotonin reuptake inhibitors (SSRIs) for cancer therapy, particularly hepatocellular carcinoma (HCC), efforts are hampered by limited knowledge of their molecular targets and mechanism of action. Global inverse gene-expression profiling method, drug affinity responsive target stability assay, and in silico molecular docking analysis was performed to identify the targets of SSRIs. Murine subcutaneous, orthotopic models, and patient-derived xenograft were employed to explore the therapeutic effects and underlying mechanisms of SSRIs in HCC. The clinical relevance of SSRI use was verified with real world data. SSRIs exhibit significant anti-HCC effects independent of their known target serotonin reuptake transporter. The glucose transporter 1 (GLUT1) is identified as a new target of SSRIs. Citalopram binds to and antagonizes GLUT1, resulting in reduced glycolytic flux and ATP generation. Mutant GLUT1 in the binding site E380 of citalopram compromises the inhibitory effects of citalopram on the Warburg effect and tumor growth. In preclinical models, citalopram dampens the growth kinetics of GLUT1high liver tumors and displays a synergistic effect with anti-PD-1 therapy. Retrospective analysis of health records found that SSRIs use is associated with a lower risk of metastasis among HCC patients. Our study reveals an unprecedented role of SSRIs in cancer metabolism, and establishes a rationale for repurposing SSRIs as potential anticancer drugs for HCC.

cancer biology↗

bioRxiv2024

Single-Cell and Spatial Transcriptomic Analyses Deciphering the Three-Layer Architecture of Human Tuberculosis Granulomas

BackgroundGranulomas (defining tuberculosis histopathological feature) are central to the hosts defense against Mycobacterium tuberculosis, critically influencing patient outcomes. However, knowledge of human granulomas structure and function are incomplete. This study employs single-cell and spatial transcriptomics to dissect human granulomas cellular composition, structure, communication and function from 19 pulmonary, lymphatic and skeletal samples. ResultsOur study identified nine key immune-activated/signaling-active cell clusters. Notably, we delineated a three-layered granuloma structure: a core with macrophages (Macro-c09, Macro-c10) and occasional fibroblasts (Fib-c03); a fibroblast-rich (Fib-c01) periphery; and an immune-infiltrated intermediate layer comprising diverse immune-cells recruited by strong signaling-molecules (SPP1/MIF) from core/periphery cells. This study also shows granuloma heterogeneity across individuals and tissues. ConclusionsBy merging scRNA-seq with ST-seq, we offer an intricate single-cell perspective of granulomas spatial-structure and formation mechanisms, identify signaling-molecules and significantly changed genes as potential targets for host-directed tuberculosis immunotherapy, highlight fibroblasts crucial role in granuloma formation, and provide an important reference/improved understanding of TB.

microbiology↗

bioRxiv2024

NSP4 mutation T492I drives rapid evolution of SARS-CoV-2 toward Omicron

T492I, a mutation encountered in SARS-CoV-2 nonstructural protein 4 (NSP4), enhances viral replication and alters nonstructural protein cleavage, causing potential evolutionary impacts. Through comprehensive comparative analyses based on evolve-and-resequence experiments of SARS-CoV-2 wild-type and Delta strains with or without T492I, we demonstrate that NSP4 T492I not only increases the mutation rate, but also accelerates the emergence of many mutations characteristic for Omicron variants. Accordingly, viral populations that evolved from ancestors with T492I, show Omicron-biased selective forces and increases in viral replication, infectivity, immune evasion capacity, potentials for cross-species transmission and receptor-binding affinity. Aside from enhanced replication, we observed stronger epistasis regarding viral replication and infectivity in T492I than in S N501Y and NSP6 {Delta}SGF; this facilitates the regulation of mutation types, which can drive fast evolution of Omicron specific mutations. Our results highlight the role of an important replication-enhancing mutation in regulating the evolutionary rates and mutational trends of SARS-CoV-2.

evolutionary biology↗

bioRxiv2024

Probabilistic graph-based model uncovers previously unseen druggable vulnerabilities in major solid cancers

Over half cancer patients lack safe, effective, targeted therapies despite abundant molecular profiling data. Statistically recurrent cancer drivers have provided fertile ground for drug discovery where they exist. But in rare, complex, and heterogeneous cancers, strong driver signals are elusive. Moreover, therapeutically exploitable molecular vulnerabilities extend beyond classical drivers. Here we describe a novel, integrative, generalizable graph-based, cooperativity-led Markov chain model, A3D3as MVP (Adaptive AI-Augmented Drug Discovery and Development Molecular Vulnerability Picker), to identify and prioritize key druggable molecular vulnerabilities in cancer. The algorithm exploits cooperativity of weak signals within a cancer molecular network to enhance the signal of true molecular vulnerabilities. We apply A3D3as MVP to 19 solid cancer types and demonstrate that it outperforms standard approaches for target hypothesis generation by >3-fold as benchmarked against cell line genetic perturbation and drug screening data. Importantly, we demonstrate its ability to identify non-driver druggable vulnerabilities and highlight 43 novel or emergent druggable targets for these tumors.

cancer biology↗

bioRxiv2024

Spatiotemporal transcriptomic maps of mouse intracerebral hemorrhage at single-cell resolution

Intracerebral hemorrhage (ICH) is a severe and widespread disease that results in high mortality and morbidity. Despite significant advances made in clinical and preclinical research, the prognosis of ICH remains poor due to an incomplete understanding of the complex pathological responses. To address this challenge, we generated single-cell resolution spatiotemporal transcriptomic maps of mouse brain 1, 3, 7, 14, and 28 days after ICH. Our analysis revealed the cellular constituents and their dynamic responses following ICH. We found changes in gene expression that are indicative of active phagocytosis and lipid processing in the lesion core and identified genes associated with brain repair at the lesion border. Persistent lipid accumulation culminated in the phenotypic transition of macrophages into foam cells. Furthermore, our results demonstrate that ICH could stimulate neural stem cells in the subventricular zone, thereby enhancing neurogenesis in this niche. This study provides a spatiotemporal molecular atlas of mouse ICH that advances the understanding of both local and global responses of brain cells to ICH and offers a valuable resource that can aid the development of novel therapies for this devastating condition.

neuroscience↗

bioRxiv2024

Enhanced Recognition of a Herbal Compound Epiberberine by a DNA Quadruplex-Duplex Structure

The small molecule epiberberine (EPI) is a natural alkaloid with versatile bioactivities against several diseases, including cancer and bacterial infection. EPI can induce the formation of a unique binding pocket at the 5' side of a human telomeric G-quadruplex (HTG) sequence Q4, resulting in a nanomolar binding affinity (KD approximately 26 nM) with significant fluorescence enhancement upon binding. It is important to understand (1) how EPI binding affects HTG structural stability and (2) how enhanced EPI binding may be achieved through the engineering of the DNA binding pocket. In this work, the EPI binding-induced HTG structure stabilization effect was probed by a peptide nucleic acid (PNA) invasion assay in combination with a series of biophysical techniques. We show that the PNA invasion-based method may be useful for the characterization of compounds binding to DNA (and RNA) structures in physiological conditions without the need to vary the solution temperature or buffer components, which are typically needed for structural stability characterization. Importantly, the combination of theoretical modeling and experimental quantification allows us to successfully engineer the Q4 derivative Q4-ds-A by a simple extension of a duplex structure to Q4 at the 5' end. Q4-ds-A is a superb EPI binder with a KD of 8 nM, with the binding enhancement achieved through the preformation of a binding pocket and a reduced dissociation rate. The tight binding of Q4 and Q4-ds-A with EPI allows us to develop a novel magnetic bead-based affinity purification system to effectively extract EPI from Rhizoma coptidis (Huang Lian) extracts.

biochemistry↗

bioRxiv2024

Hypergraph Cortical Cytoarchitectonic Parcellation with Multimodal Canine Brain Atlas

Brain atlases are vital tools in exploring the brain structure-function relationship. The burgeoning cross-species atlases have significantly accelerated our understanding of human brain development, evolution, function, and diseases. However, the existing coarse-grained macroscopic canine brain atlases greatly constrain their utility as an animal model for neurocognition research. Finer-grained brain atlas and partitions are crucial for decoding brain spatial heterogeneity and topology at different scales. Therefore, we conduct macroscopic and microscopic brain imaging to construct an interactive online dataset of multimodal canine brain atlas. Additionally, we develop a pioneering method for cortical cytoarchitectonic partitioning based on hypergraph learning. By integrating high-dimensional cytoarchitectonic features and spatial connections between cortical columns, the method leads to fine-grained partitioning patterns. This innovative approach aims to decode the biological heterogeneity of cortical microstructures, contributing to the structural annotation of canine atlas as well as public human brain atlases. The study not only offers valuable resources but also presents a novel zonation approach to investigate the cellular organization pattern and topology of the cortex.

neuroscience↗