Biology subjects

Tan, P.

Publications and source records attributed to Tan, P..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Upregulation of DEK Expression in Uterine Myomas and Cervical Cancer as a Potential Prognostic Factor

The aim of this pilot study is to investigate the role of the DEK protein as a potential prognostic marker in gynecological tumors, specifically focusing on uterine myomas and cervical cancer. The study cohort comprised Chinese female patients manifesting with menorrhagia and pelvisalgia, from whom neoplastic and adjacent non-neoplastic tissue specimens were procured during surgical intervention for either leiomyomas or cervical carcinoma. DEK protein and messenger RNA (mRNA) levels were measured across normal uterine tissue, uterine myomas, and cervical cancer tissues using Western blotting, immunohistochemistry, and quantitative real time polymerase chain reaction (qRT-PCR). Results revealed a marked increase in DEK protein expression in cervical cancer tissues, moderate expression in uterine myomas, and minimal levels in normal uterine tissues. Statistical analyses confirmed significant differences in DEK protein expression between tissue types, though mRNA expression differences did not reach statistical significance. These findings suggest DEKs involvement in tumor development and suppression, making it a promising biomarker for early detection in gynecological tumors. Further research is needed to elucidate DEKs mechanisms in gynecological tumorigenesis and its potential as an early biomarker, addressing critical need in womens health.

cancer biology↗

bioRxiv2024

Identifying Alzheimer's disease-related pathways based on whole-genome sequencing data

Alzheimers disease (AD) is a highly inheritable neurodegenerative disorder for which pathway-specific genetic profiling provides insights into its key biological mechanisms and potential treatment targets. Traditional disease-pathway analyses for AD have certain limitations, such as environmental interference and arbitrary sample division. We present a comprehensive framework that starts with genome data, avoiding these drawbacks and offering intrinsic pathway-specific genetic profiling for AD. Whole genome sequencing data from 173 individuals were used to quantify transcriptomes in 14 brain regions, estimate individual-level pathway variant scores, and analyze AD risk for each patient. These results were combined to identify AD-related pathways and quantify their interactions. The predicted expression levels were consistent with previous findings, and the estimated AD risk showed a significant correlation with Braak/Thal scores. A total of 3,798 pathways were identified as potentially associated with AD, with about 19.7% previously reported. Key pathways, including NF-{kappa}B signaling and GSK3{beta} activation, were linked to AD pathogenesis. The interactions among pathways highlighted shared gene functions in AD. In summary, we provided an effective framework for disease-pathway analysis, revealing the interdependence or compensatory effects of pathways in AD.

bioinformatics↗

bioRxiv2024

Integrated single-cell RNA-seq analysis revealed PTN secreted by fibroblasts acting on itself and macrophages via SDC4 ligand in myocardial hypertrophy

BackgroundHypertrophic cardiomyopathy (HCM) is characterized by massive myocardial hypertrophy, which is the most frequent cause of sudden death and can lead to heart failure (HF) or stroke. The objective of this study was to explore the communication network among various cells in the heart of pathological HCM derived from transverse aortic constriction (TAC) mouse model, and investigate the potential mechanism through data mining, biological informatics analysis, and experimental validation. Methods and ResultsThe integrated analyses including CellChat, Seurat, gene ontology (GO), pseudo-time trajectory analysis, and weighted gene co-expression network analysis (WGCNA) were performed based on the single-cell RNA-seq data (scRNA-seq). In vitro tests were conducted to verify bioinformatic analysis findings through enzyme-linked immunosorbent assay (ELISA), real-time quantitative PCR (RT-qPCR), Edu staining, and transwell assay. In vivo tests were also performed to further verify bioinformatic analysis findings by western blot and immunofluorescence assays based on our established TAC mouse model with myocardial hypertrophy. Our results showed that in the heart of TAC mouse, the interaction between cardiac fibroblasts and macrophages was most common, and the increasing pleiotrophin (PTN) secreted by cardiac fibroblasts could promote themselves proliferation or invasion as well as stimulate macrophage activation to release inflammatory cytokines, such as TNF-, IL-6, Cox-2, Cd83, Egr2, and IL-10 through acting on its ligand recombinant Syndecan 4 (SDC4), which may affect cardiomyocyte normal function and eventually cause HCM. This study first demonstrated that PTN derived from cardiac fibroblasts may act on SDC4 to play crucial role in myocardial hypertrophy, which may be a potential therapeutic targets for patients with pathological HCM. ConclusionsIn this study, the complex interaction network between cardiac fibroblasts and macrophages of TAC mice based on the scRNA-seq data was investigated, and we found that the increasing PTN secreted by cardiac fibroblasts under cardiac pressure overload could promote themselves proliferation or invasion as well as stimulate macrophage activation to release inflammatory cytokines through acting on SDC4 ligand, which may affect cardiomyocyte normal function and eventually cause HCM. In addition, our study suggested that PTN derived from cardiac fibroblasts may act on SDC4 ligand to play crucial role in myocardial hypertrophy, which may be a potential therapeutic targets for patients with pathological HCM.

cell biology↗

bioRxiv2024

Detection of Nontoxic BoNT/A Levels in Post-Facial Botox Injection Breastmilk using a Multi-technique Approach

BackgroundThe use of cosmetic Botox (Botulinum Neurotoxin Type A, BoNT/A ) has become increasingly prevalent. Particularly after pregnancy, postpartum depression represents one major factor motivating women to use Botox even during the lactation and breastfeeding period. Currently, there is limited understanding of the impact of Botox on lactation and the potential of its active component passing into breastmilk and affecting the infant. MethodsBreastmilk samples were acquired from five women aged between 28 - 45 through a clinic in Suzhou, Jiangsu, P.R. China. Three sample sets ranged from 1 hour to 1 year after facial Botox treatments (64 U), whereas the remaining two sample sets were from women who never received Botox treatment. BoNT/A concentrations in samples were detected using standard Enzyme-Linked Immunosorbent Assay (ELISA), unreduced and reduced Western Blotting, confocal micro-Raman Spectroscopy, and Mass Spectrometry(LC-MS). FindingsFrom ELISA, breastmilk BoNT/A concentrations peaked at 33.4 pg/mL 4 days after Botox injection. BoNT/A concentrations were highest overall in the first week and around two months after injection. While non-reducing polyacrylamide gel electrophoresis (PAGE) showed a protein band of 150 kDa peaking at 48 hours, reduced SDS-PAGE detected a 100 kDa protein first peaking at 72 hours, then re-emerging after 7 days, respectively, and in line with previous observations by others. Interestingly, micro-Raman spectroscopy indicated additional Raman peaks at 6 hours and 48 hours that were not present in other breastmilk samples which were evaluated in this study. However, no clear indication of BoNT/A was detected in Mass Spectrometry (LC-MS). InterpretationThe amount of BoNT/A in breastmilk peaks around 48 hours, and at 2 months after facial injection. Even over a year after injection, BoNT/A can be detected. However, all quantities of BoNT/A detected in this study are highly likely to be safe for infants. Additionally, our study suggests that alternative methods, besides ELISA, may be utilized for the rapid detection of low concentrations of BoNT/A in body fluid samples. FundingDuke Kunshan University Start-Up funds, Duke Kunshan University Undergraduate Studies Signature Work Research Grant, Synear and Wang-Cai Biochemistry grants, and Kunshan Municipal Government research funding. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/595434v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@fcdd11org.highwire.dtl.DTLVardef@11591daorg.highwire.dtl.DTLVardef@11ab30eorg.highwire.dtl.DTLVardef@1e19311_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIBoNT/A was detected in the breastmilk of 3 women after facial Botox injections of 64 U. C_LIO_LIToxin levels peaked in the first week and at around 2 months after injection. C_LIO_LIAll detected levels (up to 33.40 pg/mL) were significantly below the lethal dose for newborns. C_LI

molecular biology↗

bioRxiv2024

Genetic regulation of lncRNA expression in the whole human brain

Long non-coding RNAs (lncRNAs) play a key role in the human brain, and genetic variants regulate their expression. Herein, the expression quantitative trait loci (eQTL) of lncRNAs encompassing ten brain regions from 134 individuals was analyzed, and novel variants influencing lncRNA expression (eSNPs) and the respective affected lncRNAs (elncRNAs) were identified. The eSNPs are proximate to their corresponding elncRNAs, enriched in the non-coding genome, and have a high minor allele frequency. The elncRNAs exhibit a high-level and complex pattern of expression. The genetic regulation is more tissue-specific for lncRNAs than for protein-coding genes, with notable differences between cerebrum and cerebellum. However, it shows relatively similar patterns across the cortex regions. Furthermore, we observed a significant enrichment of eSNPs among variants associated with neurological disorders, especially insomnia, and identified insomnia-related lncRNAs involved in immune response functions. Moreover, the present study offers an improved tool for lncRNA quantification, a novel approach for lncRNA function analysis, and a database of lncRNA expression regulation in the human brain. These findings and resources will advance the research on non-coding gene expression regulation in neuroscience.

bioinformatics↗

bioRxiv2024

Spatially Resolved Tumor Ecosystems and Cell States in Gastric Adenocarcinoma Progression and Evolution

Gastric cancer (GC) is a major cause of global cancer mortality with high heterogeneity levels. To explore geospatial interactions in tumor ecosystems, we integrated 1,563 spatial transcriptomic regions-of-interest (ROIs) with 152,423 single-cell expression profiles across 130 GC samples from 70 patients. We observed pervasive expression-based intratumor heterogeneity, recapitulating tumor progression through spatially localized and functionally ordered subgroups with specific immune microenvironments and immune checkpoint profiles. Evolutionary phylogenetic analysis revealed two different evolutionary trajectories (branched evolution and diaspora evolution) associated with distinct molecular subtypes, clinical prognoses, stromal neighborhoods including VWF+ ACKR1+ endothelial cells, and genetic drivers such as SOX9. Spatial analysis of tumor-stromal interfaces across multiple GCs highlighted new ecosystem states not attributable to mere tumor/stroma admixture, landmarked by increased GREM1 expression. Our results provide insights into how the cellular ecosystems of individual GCs are sculpted by tumor intrinsic and extrinsic selective pressures, culminating in individualized patient-specific cancer cartographies.

cancer biology↗

bioRxiv2024

DeProt: A protein language model with quantizied structure and disentangled attention

Protein language models (PLMs) have shown remarkable capabilities in various protein function prediction tasks. However, while protein function is intricately tied to structure, most existing PLMs do not incorporate protein structure information. To address this issue, we introduce ProSST, a Transformer-based protein language model that seamlessly integrates both protein sequences and structures. ProSST incorporates a structure quantization module and a Transformer architecture with disentangled attention. The structure quantization module translates a 3D protein structure into a sequence of discrete tokens by first serializing the protein structure into residue-level local structures and then embeds them into dense vector space. These vectors are then quantized into discrete structure tokens by a pre-trained clustering model. These tokens serve as an effective protein structure representation. Furthermore, ProSST explicitly learns the relationship between protein residue token sequences and structure token sequences through the sequence-structure disentangled attention. We pre-train ProSST on millions of protein structures using a masked language model objective, enabling it to learn comprehensive contextual representations of proteins. To evaluate the proposed ProSST, we conduct extensive experiments on the zero-shot mutation effect prediction and several supervised downstream tasks, where ProSST achieves the state-of-the-art performance among all baselines. Our code and pretrained models are publicly available 2.

bioinformatics↗

bioRxiv2024

Spatially resolved niche and tumor microenvironmental alterations in gastric cancer peritoneal metastases

Peritoneal metastases (PM) in gastric cancer (GC) portend a poor prognosis, yet our understanding of tumor microenvironmental (TME) characteristics associated with GCPM remain limited. Here, we analyzed intrinsic genomic alterations and transcriptomic programs predictive of GCPM in a prospective cohort of 248 patients, identifying CDH1, PIGR, and ELF3 mutations as predictors. By inspecting the spatial dynamics of the TME, we find that tumor compartment infiltration of pro-tumorigenic cell types such as inflammatory cancer-associated fibroblasts (CAFs) predict peritoneal recurrence. Next, in a cross-sectional study of 205 samples from 55 patients, distinct pathways and immune compositions in GCPM relative to liver metastases highlight the TMEs significance in transcoelomic metastases. Notably, several putative therapeutic targets exhibited distinct expression patterns between PTs and PMs. We also observed increased immune infiltration in GCPMs treated with systemic immunotherapy and intraperitoneal chemotherapy. Our findings highlight transcriptomic variations and niche reprogramming in the GCPM peritoneal environment, revealing roles of myeloid dendritic cells, effector memory CD8+ T cells, and CAFs in metastatic progression. Statement of significanceComprehensive molecular profiling of gastric cancer primary and peritoneal tumors unveils crucial insights into the distinct molecular and immune landscape of peritoneal metastases. Identifying predictive markers and therapeutic targets emphasizes the significance of tumor microenvironment alterations in guiding future therapies for gastric cancer peritoneal metastasis.

cancer biology↗

bioRxiv2023

Host-derived oxidized phospholipids initiate effector-triggered immunity fostering lethality upon microbial encounter.

Macrophages detect invading microorganisms via pattern recognition receptors that recognize pathogen-associated molecular patterns, or via sensing the activity of virulence factors that initiates effector-triggered immunity (ETI). Tissue damage that follows pathogen encounter leads to the release of host-derived factors that participate to inflammation. How these self-derived molecules are sensed by macrophages and their impact on immunity remain poorly understood. Here we demonstrate that, in mice and humans, host-derived oxidized phospholipids (oxPLs) are formed upon microbial encounter. oxPL blockade restricts inflammation and prevents the death of the host, without affecting pathogen burden. Mechanistically, oxPLs bind and inhibit AKT, a master regulator of immunity and metabolism. AKT inhibition potentiates the methionine cycle, and epigenetically dampens Il10, a pluripotent anti-inflammatory cytokine. Overall, we found that host-derived inflammatory cues act as "self" virulence factors that initiate ETI and that their activity can be targeted to protect the host against excessive inflammation upon microbial encounter.

immunology↗

bioRxiv2023

Decoupling of the Onset of Anharmonicity between a Protein and Its Surface Water around 200 K

The protein dynamical transition at [~] 200 K, where the biomolecule transforms from a harmonic, non-functional form to an anharmonic, functional state, has been thought to be slaved to the thermal activation of dynamics in its surface hydration water. Here, by selectively probing the dynamics of protein and hydration water using elastic neutron scattering and isotopic labelling, we found that the onset of anharmonicity in the two components around 200 K are decoupled. The one in protein is an intrinsic transition, whose characteristic temperature is independent of the instrumental resolution time, but varies with the biomolecular structure and the amount of hydration, while the one of water is merely a resolution effect.

biophysics↗

bioRxiv2023

Quantification of circulating tumor DNA using deep learning

Quantification of circulating tumor DNA (ctDNA) levels in blood enables non-invasive surveillance of cancer progression. Fragle is an ultra-fast deep learning-based method for ctDNA quantification directly from cell-free DNA fragment length profiles. We developed Fragle using low-pass whole genome sequence (lpWGS) data from multiple cancer types and healthy control cohorts, demonstrating high accuracy, and improved lower limit of detection in independent cohorts as compared to existing tumor-naive methods. Uniquely, Fragle is also compatible with targeted sequencing data, exhibiting high accuracy across both research and commercial targeted gene panels. We used this method to study longitudinal plasma samples from colorectal cancer patients, identifying strong concordance of ctDNA dynamics and treatment response. Furthermore, prediction of minimal residual disease in resected lung cancer patients demonstrated significant risk stratification beyond a tumor-naive gene panel. Overall, Fragle is a versatile, fast, and accurate method for ctDNA quantification with potential for broad clinical utility.

bioinformatics↗

bioRxiv2023

Spatiotemporal Genomic Profiling of Intestinal Metaplasia Reveals Clonal Dynamics of Gastric Cancer Progression

Intestinal metaplasia (IM) is a pre-malignant condition of the gastric mucosa associated with increased gastric cancer (GC) risk. We analyzed 1256 gastric samples (1152 IMs) from 692 subjects through a prospective 10-year study. We identified 26 IM driver genes in diverse pathways including chromatin regulation (ARID1A) and intestinal homeostasis (SOX9), largely occurring as small clonal events. Analysis of clonal dynamics between and within subjects, and also longitudinally across time, revealed that IM clones are likely transient but increase in size upon progression to dysplasia, with eventual transmission of somatic events to paired GCs. Single-cell and spatial profiling highlighted changes in tissue ecology and lineage heterogeneity in IM, including an intestinal stem-cell dominant cellular compartment linked to early malignancy. Expanded transcriptome profiling revealed expression-based molecular subtypes of IM, including a body-resident "pseudoantralized" subtype associated with incomplete histology, antral/intestinal cell types, ARID1A mutations, inflammation, and microbial communities normally associated with the healthy oral tract. We demonstrate that combined clinical- genomic models outperform clinical-only models in predicting IMs likely to progress. Our results raise opportunities for GC precision prevention and interception by highlighting strategies for accurately identifying IM patients at high GC risk and a role for microbial dysbiosis in IM progression.

cancer biology↗

bioRxiv2023

Vangl2 suppresses NF-κB signaling and ameliorates sepsis by targeting p65 for NDP52-mediated autophagic degradation

Van Gogh-like 2 (Vangl2), a core planar cell polarity (PCP) component, plays an important role in polarized cellular and tissue morphology induction, growth development and cancer. However, its role in regulating inflammatory responses remains elusive. Here, we report that Vangl2 is upregulated in patients with sepsis and identify Vangl2 as a negative regulator of NF-{kappa}B signaling by regulating the protein stability and activation of the core transcription component p65. Mice with myeloid-specific deletion of Vangl2 (Vangl2{Delta}M) are hypersusceptible to lipopolysaccharide (LPS)-induced septic shock. Vangl2 deficient myeloid cells exhibit enhanced phosphorylation and expression of p65, therefore, promoting the secretion of pro-inflammatory cytokines after LPS stimulation. Mechanistically, NF-{kappa}B signaling-induced-Vangl2 recruits E3 ubiquitin ligase PDLIM2 to catalyze K63-linked ubiquitination on p65, which serves as a recognition signal for cargo receptor NDP52-mediated selective autophagic degradation. Taken together, these findings demonstrate Vangl2 as a suppressor of NF-{kappa}B mediated inflammation and provide insights into the crosstalk between autophagy and inflammatory diseases.

immunology↗

bioRxiv2022

Effects of breast fibroepithelial tumor associated retinoic acid receptor alpha ligand binding domain mutations on receptor function and retinoid signaling

Point mutations in the ligand binding domain of retinoic acid receptor alpha (RAR) have been implicated in breast fibroepithelial tumors development. However, their role in the tumorigenesis of solid tumors is currently unknown. In this study, using a combination of biochemical and cellular assays, we evaluated the functional consequences of known tumor associated RAR mutations on retinoic acid signaling. All of the clinically associated mutants tested showed diminished transcriptional activities compared to wild type RAR. These mutants also exhibited a dominant negative effect, an activity which has previously been linked to developmental defects and tumor formation in mice. X-ray crystallography showed that mutants remain relatively intact structurally and the loss of transcriptional activity is due to altered co-activator recruitment. In agreement with our biochemical analyses, transcriptomics and cell growth analysis showed that the mutant RAR proteins confer resistance to growth inhibition in the presence of its ligand in phyllodes tumor cells. Although the mutations impair the receptor responses to retinoic acid, certain mutant RAR are partially reactivatable with alternative synthetic agonists. Our data provide insights into the mechanisms by which RAR mutations impact tumorigenesis.

cancer biology↗

bioRxiv2022

RAPTOR: A Five-Safes approach to a secure, cloud native and serverless genomics data repository

Genomic researchers are increasingly utilizing commercial cloud platforms (CCPs) to manage their data and analytics needs. Commercial clouds allow researchers to grow their storage and analytics capacity on demand, keeping pace with expanding project data footprints and enabling researchers to avoid large capital expenditures while paying only for IT capacity consumed by their project. Cloud computing also allows researchers to overcome common network and storage bottlenecks encountered when combining or re-analysing large datasets. However, cloud computing presents a new set of challenges. Without adequate security controls, the risk of unauthorised access may be higher for data stored on the cloud. In addition, regulators are increasingly mandating data access patterns and specific security protocols on the storage and use of genomic data to safeguard rights of the study participants. While CCPs provide tools for security and regulatory compliance, utilising these tools to build the necessary controls required for cloud solutions is not trivial as such skill sets are not commonly found in a genomics lab. The Research Assets Provisioning and Tracking Online Repository (RAPTOR) by the Genome Institute of Singapore is a cloud native genomics data repository and analytics platform focusing on security and regulatory compliance. Using a "five-safes" framework (Safe Purpose, Safe People, Safe Settings, Safe Data and Safe Output), RAPTOR provides security and governance controls to data contributors and users leveraging cloud computing for sharing and analysis of large genomic datasets without the risk of security breaches or running afoul of regulations. RAPTOR can also enable data federation with other genomic data repositories using GA4GH community-defined standards, allowing researchers to boost the statistical power of their work and overcome geographic and ancestry limitations of data sets

genomics↗

bioRxiv2022

An optimised method for bacterial nucleic acid extraction from positive blood culture broths for whole genome sequencing, resistance phenotype prediction and downstream molecular applications

BackgroundA prerequisite to rapid molecular detection of pathogens causing bloodstream infections is an efficient, cost effective and robust DNA extraction solution. We describe methods for microbial DNA extraction direct from positive blood culture broths, suitable for metagenomic sequencing and the application of machine-learning based tools to predict antimicrobial susceptibility. MethodsProspectively collected culture-positive blood culture broths with Gram-negative bacteria, were directly extracted using various commercially available kits. We compared methods for efficient inhibitor removal, avoidance of DNA shearing or degradation, to achieve DNA of high quality and purity. Bacterial species identified via whole-genome metagenomic sequencing (Illumina, MiniSeq) from blood culture extracts were compared to conventional methods from cultured isolates (Vitek MS). A machine-learning algorithm (AREScloud) was used to predict susceptibility against commercially available antibiotics, compared to susceptibility testing (Vitek 2) and other commercially available rapid diagnostic instruments (Accelerate Pheno and BCID). ResultsA two-kit method using a modified MolYsis Basic kit (for host DNA depletion) and extraction using Qiagen DNeasy UltraClean microbial kits resulted in optimal extractions appropriate for multiple molecular applications, including PCR, short-read and long-read sequencing. DNA extracts from 40 blood culture broths were included. Taxonomic profiling by direct metagenomic sequencing matched species identification by conventional methods in 38/40 (95%) of samples, with two showing agreement to genus level. In two polymicrobial samples, a second organism was missed by sequencing. Whole genome sequencing antimicrobial susceptibility testing (WGS-AST) models were able to accurately infer profiles for 6 common pathogens against 17 antibiotics. Overall categorical agreement (CA) was 95%, with 11% very major errors (VME) and 3.9% major errors (ME). CA for WGS-AST was >95% for 5/6 of the most common pathogens (E. coli, K. pneumoniae, P. mirabilis, P. aeruginosa and C. jejuni) while it was lower for K. oxytoca (66.7%), likely due to the presence of inducible cephalosporinases. Performance of WGS-AST was sub-optimal for uncommon pathogens (e.g. Elizabethkingia) and some combination antibiotic compounds (e.g. ticarcillin-clavulanate). Time to pathogen identification and resistance gene detection was fastest with BCID (1 h from blood culture positivity). Accelerate Pheno provided a rapid MIC result in approximately 8 h. While Illumina based direct metagenomic sequencing did not result in faster turn-around times compared conventional methods, use of real-time nanopore sequencing may allow faster data acquisition. ConclusionsThe application of direct metagenomic sequencing from positive blood culture broths is a feasible approach and solves some of the challenges of sequencing from low-bacterial load samples. Machine-learning based algorithms are also accurate for common pathogen / drug combinations, although additional work is required to optimise algorithms for uncommon species and more complex resistance genotypes, as well as streamlining methods to provide more rapid sequencing results.

microbiology↗

bioRxiv2022

Spatial Atlas of the Mouse Central Nervous System at Molecular Resolution

Spatially charting molecular cell types at single-cell resolution across the three-dimensional (3D) volume of the brain is critical for illustrating the molecular basis of the brain anatomy and functions. Single-cell RNA sequencing (scRNA-seq) has profiled molecular cell types in the mouse brain1, 2, but cannot capture their spatial organization. Here, we employed an in situ sequencing technique, STARmap PLUS3, 4, to map more than one million high-quality cells across the whole adult mouse brain and the spinal cord, profiling 1,022 genes at subcellular resolution with a voxel size of 194 X 194 X 345 nm in 3D. We developed computational pipelines to segment, cluster, and annotate 231 molecularly defined cell types and 64 tissue regions with single-cell resolution. To create a transcriptome-wide spatial atlas, we further integrated the STARmap PLUS measurements with a published scRNA-seq atlas1, imputing 11,844 genes at the single-cell level. Finally, we engineered a highly expressed RNA barcoding system to delineate the tropism of a brain-wide transgene delivery tool, AAV-PHP.eB5, 6, revealing its single-cell resolved transduction efficiency across the molecular cell types and tissue regions of the whole mouse brain. Together, our datasets and annotations provide a comprehensive, high-resolution single-cell resource that integrates a spatial molecular atlas, cell taxonomy, brain anatomy, and genetic manipulation accessibility of the mammalian central nervous system (CNS).

neuroscience↗

bioRxiv2021

The genome of an apodid holothuroid (Chiridota heheva) provides insights into its adaptation to deep-sea reducing environment

Cold seeps and hydrothermal vents are deep-sea reducing environments that are characterized by a lack of oxygen, photosynthesis-derived nutrients and a high concentration of reducing chemicals. Apodida is an order of deep-sea echinoderms lacking tube feet and complex respiratory trees, which are commonly found in holothurians. Chiridota heheva Pawson & Vance, 2004 (Apodida: Chiridotidae) is one of the few echinoderms that resides in deep-sea reducing environments. Unlike most cold seep and hydrothermal vent-dwelling animals, C. heheva does not survive by maintaining an epi- or endosymbiotic relationship with chemosynthetic microorganisms. The species acquires nutrients by extracting organic components from sediment detritus and suspended material. Here, we report a high-quality genome of C. heheva as a genomic reference for echinoderm adaptation to reducing environments. Chiridota heheva likely colonized its current habitats in the early Miocene. The expansion of the aerolysin-like protein family in C. heheva compared with other echinoderms might be involved in the disintegration of microbes during digestion, which in turn facilitates the species adaptation to cold seep environments. Moreover, several hypoxia-related genes were subject to positive selection in the genome of C. heheva, which contributes to their adaptation to hypoxic environments.

genomics↗