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Wang, J.

Publications and source records attributed to Wang, J..

At least 1,009 records · Page 56Linked to original sources

Spatiotemporal Single-Cell Roadmap of Human Skin Wound Healing

Wound healing is vital for human health, yet the details of cellular dynamics and coordination in human wound repair remain largely unexplored. To address this, we conducted single-cell and spatial transcriptomics analyses on human skin and acute wound tissues through inflammation, proliferation, and remodeling phases of wound repair from the same individuals, monitoring the cellular and molecular dynamics of human skin wound healing at an unprecedented spatiotemporal resolution. This singular roadmap reveals the cellular architecture of the wound margin and identifies FOSL1 as a critical driver of re-epithelialization. It shows that pro-inflammatory macrophages and fibroblasts sequentially support keratinocyte migration like a relay race across different healing stages. Comparison with single-cell data from venous and diabetic foot ulcers uncovers a link between failed keratinocyte migration and impaired inflammatory response in chronic wounds. Additionally, comparing human and mouse acute wound transcriptomes underscores the indispensable value of this roadmap in bridging basic research with clinical innovations. HighlightsO_LIA spatiotemporal atlas to explore human in vivo gene expression across wound healing C_LIO_LIWound margin architecture unveils a model for human re-epithelialization C_LIO_LIDistinct healing challenges in venous ulcers and diabetic foot ulcers C_LIO_LIUnique human healing traits emerge in cellular heterogeneity and gene expression C_LI

cell biology↗

Dissociation of putative open loop circuit from ventral putamen to motor cortical areas in humans I: high-resolution connectomics

Human movement is partly organized and executed by cortico-basal ganglia-thalamic closed-loop circuits (CLCs), wherein motor cortical areas both send inputs to and receive feedback from the basal ganglia, particularly the dorsal putamen (PUTd). These networks are compromised in Parkinsons disease (PD) due to neurodegeneration of dopaminergic inputs primarily to PUTd. Yet, fluid movement in PD can sporadically occur, especially when induced by emotionally arousing events. Rabies virus tracing in non-human primates has identified a potential alternative motor pathway, wherein the ventral putamen (PUTv) receives inputs from subcortical limbic areas (such as amygdala nuclei) and sends outputs to motor cortical areas putatively via the nucleus basalis of Meynert (NBM). We hypothesize that this separable open loop circuit (OLC) may exist in humans and explain the preservation of movement after CLC degradation. Here, we provide evidence for the normal human OLC with ultra-high field (7T), multi-echo functional magnetic resonance imaging. We acquired resting-state functional connectivity (FC) scans from 21 healthy adults (avg. age = 29, 12M/9F, all right-handed) and mapped left-hemisphere seed-to-voxel connectivity to assess PUTv FC with putative subcortical nodes and motor cortical areas. We found that putative OLC node (basolateral amygdala, NBM) FC was greater with PUTv (p < 0.05), while CLC subcortical seed (ventrolateral nucleus of thalamus) FC was greater with PUTd (p<0.01). Striatal FC patterns varied across cortical motor areas, with cingulate (p < 0.0001) and supplementary (p < 0.0001) motor areas showing greater FC with PUTv vs. nucleus accumbens. SMA had greater FC with PUTd vs. PUTv (p < 0.0001), while cingulate and primary motor areas showed no significant differences in FC between PUTd and PUTv (p > 0.1). Collectively, these results suggest that PUTv is functionally connected to motor cortical areas and may be integrated into a separable motor OLC with subcortical limbic inputs.

neuroscience↗

Evaluating computational approaches for comparison of protein expression across cancer indications

BackgroundThe National Cancer Institutes Clinical Proteomic Tumor Analysis Consortium (CPTAC) recently generated harmonized genomic, transcriptomic, proteomic, and clinical data for over 1,000 tumors across 10 cohorts to facilitate pan-cancer discovery research. However, protein expression comparison across CPTAC cohorts remains challenging due to non-uniform missing data and varying protein expression distribution patterns across tumor types. Here, we present our efforts to evaluate various missing data handling and normalization strategies to create a normalized pan-cancer protein expression dataset. ResultsFirst, we developed a novel algorithm to select robustly expressed proteins in tumors within any CPTAC cohort. Second, we applied a cohort hybrid imputation approach to protein abundance values from FragPipe within each cohort based on protein expression distribution patterns. Third, we calculated intensity-based absolute quantification using protein abundance values and applied both global and smooth quantile normalization methods. Our results indicate that global quantile normalization ensured identical distribution across cohorts for both tumor and normal tissues, while smooth quantile normalization preserved distribution differences between biological conditions. We assessed our method by comparing differential protein expression analysis results with and without normalization. Additionally, we examined the ranks of protein expression in the normalized CPTAC dataset for selected proteins with high protein-to-RNA expression correlation across CPTAC cohorts. We then compared these protein expression ranks with their RNA expression ranks across corresponding cohorts in The Cancer Genome Atlas (TCGA). Differential protein expression analysis revealed a high level of agreement in the fold change of tumor versus normal tissue within cohorts before and after normalization. Furthermore, our results indicate that global quantile normalization resulted in the highest cohort rank correlation between CPTAC and TCGA for selected proteins. ConclusionsIn summary, our thorough analysis demonstrates that global quantile normalization surpasses both smooth quantile normalization and no normalization, as evidenced by its higher rank correlation across cancer cohorts between CPTAC and TCGA for selected proteins. The findings suggest that combining cohort hybrid imputation with global quantile normalization is an effective method for creating a normalized CPTAC pan-cancer protein dataset, which can facilitate the study of protein expression across different cancer types.

bioinformatics↗

Haplotype-resolved genome assembly of upland switchgrass provides insights into cold tolerance

Switchgrass (Panicum virgatum L.) is a bioenergy and forage crop. Upland switchgrass exhibits superior cold tolerance than lowland ecotype, but the underlying molecular mechanisms remain unclear. Here, we presented a high-quality haplotype-resolved genome of the upland ecotype Jingji31 and conducted multi-omics analysis to understand its cold tolerance. The divergence between upland and lowland ecotypes of switchgrass occurred after the differentiation of the two subgenomes (K and N). Under cold stress, the K subgenome has more differentially expressed genes (DEGs). Transcriptome analysis revealed ecotype-specific differential expressions among members of the cold-responsive (COR) gene families. Specifically, certain members of the AFB1, ATL80, HOS10, and STRS2 gene families exhibited opposite expression changes between the two ecotypes, potentially contributing to their differential cold tolerance. By using haplotype-resolved genome, we identified more cold-induced allele-specific expressions (ASEs) in the upland ecotype, and these ASEs were significantly enriched in the COR gene families. Genome-wide association study detected an association signal on Chr3K related to overwintering rate, which overlapped with a selective sweep region and contained a cytochrome P450 (CYP450) gene highly expressed under cold stress. Heterologous overexpression of CYP450 in rice alleviated leaf wilting and improved cold tolerance. Our study provides a high-quality haplotype-resolved genome of upland switchgrass, to advance conceptual understanding of plant cold tolerance for breeding crops with enhanced cold adaptation.

genomics↗

SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection.

Recent advances in spatial transcriptomics have significantly deepened our understanding of biology. A primary focus has been identifying spatially variable genes (SVGs) which are crucial for downstream tasks like spatial domain detection. Traditional methods often use all or a set number of top SVGs for this purpose. However, in diverse datasets with many SVGs, this approach may not ensure accurate results. Instead, grouping SVGs by expression patterns and using all SVG groups in downstream analysis can improve accuracy. Furthermore, classifying SVGs in this manner is akin to identifying cell type marker genes, offering valuable biological insights. The challenge lies in accurately categorizing SVGs into relevant clusters, aggravated by the absence of prior knowledge regarding the number and spectrum of spatial gene patterns. Addressing this challenge, we propose SPACE, SPatially variable gene clustering Adjusting for Cell type Effect, a framework that classifies SVGs based on their spatial patterns by adjusting for confounding effects caused by shared cell types, to improve spatial domain detection. This method does not require prior knowledge of gene cluster numbers, spatial patterns, or cell type information. Our comprehensive simulations and real data analyses demonstrate that SPACE is an efficient and promising tool for spatial transcriptomics analysis. Key PointsO_LISPACE eliminates the need for prior knowledge about the number of gene clusters, known cell types, or the quantity of SVGs to identify clusters for downstream analysis. C_LIO_LISPACE offers a method to effectively leverage SVGs for low-dimensional embedding within each cluster to improve the accuracy of spatial domain detection. C_LIO_LIThe efficiency and utility of the SPACE algorithm have been validated across multiple datasets and simulations, demonstrating its effectiveness in producing meaningful and interpretable results. C_LI

genomics↗

Effects of lambda-cyhalothrin on gut microbiota and related bile acid metabolism in mice

BackgroundSince the gut microbiota plays a crucial role in host metabolism and homeostasis, its alterations induced by xenobiotics, such as pesticides, could pose a risk to host health. Our previous in vitro fermentation study showed that pyrethroid pesticides could affect the mouse bacterial community and related bile acid profiles. Hence in the present study, the effects of the selected pyrethroid lambda-cyhalothrin on the intestinal microbial community and its related bile acid metabolism were evaluated in male and female mice. ResultsThe total amount of bile acids in plasma and fecal samples from lambda-cyhalothrin treated mice markedly increased compared to controls, which could be mainly ascribed to the significantly raised proportions of taurine conjugated bile acids in plasma, and the increase in fecal secondary bile acids. In gut microbial profiles, a significantly increased richness of Prevotellacea and a depletion of Lachnospiraceae were found at the family level upon the treatment with lambda-cyhalothrin. ConclusionTreatment of mice with lambda-cyhalothrin affected the gut microbiota with accompanying changes in bile acid homeostasis. The effects on fecal bile acid profiles were in line with those previously observed in our in vitro study and corroborate that pyrethroid pesticides could affect gut microbiota and related bile acid profiles.

microbiology↗

Large Serine Integrase Off-target Discovery and Validation for Therapeutic Genome Editing

While numerous technologies for the characterization of potential off-target editing by CRISPR/Cas9 have been described, the development of new technologies and analytical methods for off-target recombination by Large Serine Integrases (LSIs) are required to advance the application of LSIs for therapeutic gene integration. Here we describe a suite of off-target recombination discovery technologies and a hybrid capture validation approach as a comprehensive framework for off-target characterization of LSIs. HIDE- Seq (High-throughput Integrase-mediated DNA Event Sequencing) is a PCR-free unbiased genome-wide biochemical assay capable of discovering sites with LSI- mediated free DNA ends (FDEs) and off-target recombination events. Cryptic-Seq is a PCR-based unbiased genome-wide biochemical or cellular-based assay that is more sensitive than HIDE-Seq but is limited to the discovery of sites with off-target recombination. HIDE-Seq and Cryptic-Seq discovered 38 and 44,311 potential off-target sites respectively. 2,455 sites were prioritized for validation by hybrid capture NGS in LSI- edited K562 cells and off-target integration was detected at 52 of the sites. We benchmarked the sensitivity of our LSI off-target characterization framework against unbiased whole genome sequencing (WGS) on LSI-edited samples, and off-target integration was detected at 5 sites with an average genome coverage of 40x. This reflects a greater than 10-fold increase in sensitivity for off-target detection compared to WGS, however only 4 of the 5 sites detected by WGS were also validated by hybrid capture NGS. The dissemination of these technologies will help advance the application of LSIs in therapeutic genome editing by establishing methods and benchmarks for the sensitivity of off-target detection.

genomics↗

Blocking Toxin Function and Modulating the Gut Microbiota: Caffeic Acid and its Derivatives as Potential Treatments for Clostridioides difficile Infection

Clostridioides difficile infection (CDI) is the leading cause of hospital-acquired diarrhea that seriously threatens public health. The disruption of normal gut microbiota by the use of broad-spectrum antimicrobial agents enables C. difficile to proliferate in the colon. The emergence and prevalence of hypervirulent C. difficile strains result in increased morbidity, mortality, and high recurrence rates of CDI, thus creating a pressing need for novel therapeutics. The multi-domain toxins TcdA and TcdB are the primary determinants of CDI pathogenesis, rendering them ideal drug targets in the anti-virulence paradigm. In this study, we identified caffeic acid and its derivatives from natural compounds library as active inhibitors of TcdB via a cell-based high-throughput phenotypic screening. Further mechanistic investigations revealed that caffeic acid phenethyl ester (CAPE) could directly bind to TcdB, thus suppressing InsP6-induced autoproteolysis and inhibiting glucosyltransferase activity. CAPE treatment remarkably reduces the pathology of CDI in a murine infection model in terms of alleviated diarrhea symptoms, decreased bacterial colonization, and relieved histopathological lesions. Moreover, CAPE treatment of C. difficile-challenged mice induces a remarkable increase in the diversity and composition of the gut microbiota and alterations of gut metabolites (e.g., adenosine, D-proline, and melatonin), which might partially contribute to the therapeutic outcomes of CAPE against CDI. Our results reveal the potential of CAPE as a therapeutic for the management of CDI, or CAPE might serve as a lead compound for the development of antivirulence drugs targeting TcdB.

microbiology↗

A single-molecule nanopore sequencing platform

Nanopore sequencing, a third-generation sequencing technology, has revolutionized the gene sequencing industry with its advantages of long reads, fast speed, real-time sequencing and analysis, and potential in detecting base modifications. This technology allows researchers to sequence longer DNA fragments in a single read, providing more comprehensive genomic information compared to previous methods. Nanopore sequencing operates on electrical signals generated by a nanopore embedded in a membrane separating two electrolyte-filled chambers. When single-stranded DNA (ssDNA) passes through the nanopore, it creates variations in the current that correspond to different DNA bases. By analyzing these current fluctuations with machine learning algorithms, the DNA sequence can be determined. In this study, we introduced several improvements to nanopore sequencing, including nanopore local chemistry sequencing, novel motor and pore proteins, chip design, and basecalling algorithms. Our new nanopore sequencing platform, CycloneSEQ, demonstrated long-duration sequencing (107 hours) on a single chip with high yield (>50 Gb). In human genomic DNA sequencing, CycloneSEQ was able to produce long reads with N50 33.6 kb and modal identity 97.0%. Preliminary findings on human whole-genome de novo assembly, variant calling, metagenomics sequencing, and single-cell RNA sequencing have further highlighted CycloneSEQs potential across different areas of genomics.

genomics↗

Three-dimension transcriptomics maps of whole mouse embryo during organogenesis

Understanding mammalian development heavily relies on classical animal models like the house mouse (Mus musculus). Advanced spatial transcriptomics has enabled biologists to break new ground in studies of molecular dynamics and cellular patterning during embryonic development with spatiotemporal resolution. To construct a comprehensive developmental trajectory, current three-dimensional (3D) spatial transcriptomic profiling leverages mouse embryos from gastrulation (E5.5) to organogenesis (E13.5) in continuity. However, a crucial phase for early organogenesis between E9.5 and E11.5 was deficient. To unveil the mystery of this stage, we present the 3D transcriptomics of mouse embryos at E9.5 and E11.5, with a widely applicable reconstruction workflow that bypasses sophisticated bioinformatic calculations. As our 3D atlas is generated at single-cell resolution, we demonstrate how organogenetic processes can be interpreted at different levels of granularity, from local cellular interactions to whole embryonic regionalization. We release the open-access database MOSTA3D (Mouse Organogenesis Spatiotemporal Transcriptomic Atlas in Three-dimensional) and hope a broader community will contribute to extending this framework from conception to senility in the near future.

developmental biology↗

Ground nesting of soft eggs by extinct birds and a new parity mode switch hypothesis for the evolution of animal reproduction

Nearshore ground nesting of soft eggs by extinct birds is demonstrated here, providing a new explanation for the abundance of bird fossils in early Cretaceous lacustrine environments, where humidity conditions required for soft egg incubation would have been present. This reinforces recent findings of Archaeopteryx soft eggs near Jurassic marine environments, the possibility that wings and elongated feathers developed primarily in association with nest protection on the ground and only secondarily with flight, and the origin of flight from the ground up. Notably, soft eggs preceded rigid eggs in evolution, but both crocodiles, whose ancestors seem to have antedated bird precursors, and extant birds reproduce exclusively via hard-shelled eggs. Therefore, an explanation is in order for how reproduction via soft eggs could have occurred in the bird lineage in-between two evolutionary moments of reproduction via rigid eggs. In alternative to the commonly accepted convergent evolution of viviparity and rigid eggshells, a parity mode switch hypothesis is presented here. It postulates the existence, since the rise of animals, of an inherited ancestral parity mode switch between viviparity and oviparity. This switch would have evolved to embrace hard-shelled oviparity after rigid eggshells appeared in evolution. Commitment to a particular parity mode or eggshell type may have conditioned survival of entire animal groups, especially during major extinction events, explaining, among others, the extinction of all birds that reproduced via soft eggshells.

evolutionary biology↗

ComBat-met: Adjusting Batch Effects in DNA Methylation Data

Integration of genomics data is routinely hindered by unwanted technical variations known as batch effects. Despite wide availability, existing batch correction methods often fall short in capturing the unique characteristics of DNA methylation data. We present ComBat-met, a beta regression framework to adjust batch effects in DNA methylation studies. Our method fits beta regression models to the data, calculates batch-free distributions, and maps the quantiles of the estimated distributions to their batch-free counterparts. Compared to traditional methods, ComBat-met followed by differential methylation analysis shows improved statistical power without compromising false positive rates based on simulated data. Additionally, we demonstrate the ability of ComBat-met to remove cross-batch variations and recover biological signals using data from The Cancer Genome Atlas.

bioinformatics↗

MYH11 rare variant augments aortic growth and induces cardiac hypertrophy and heart failure with pressure overload

Smooth muscle cell-specific myosin heavy chain, encoded by MYH11, is selectively expressed in smooth muscle cells (SMCs). Pathogenic variants in MYH11 predispose to a number of disorders, including heritable thoracic aortic disease associated with patent ductus arteriosus, visceral myopathy, and megacystis-microcolon-intestinal hypoperistalsis syndrome. Rare variants of uncertain significance occur throughout the gene, including MYH11 p.Glu1892Asp, and we sought to determine if this variant causes thoracic aortic disease in mice. Genomic editing was used to generate Myh11E1892D/E1892D mice. Wild-type (WT) and mutant mice underwent cardiovascular phenotyping and with transverse aortic constriction (TAC). Myh11E1892D/E1892D and WT mice displayed similar growth, blood pressure, root and ascending aortic diameters, and cardiac function up to 13 months of age, along with similar contraction and relaxation on myographic testing. TAC induced hypertension similarly in Myh11E1892D/E1892D and WT mice, but mutant mice showed augmented ascending aortic enlargement and increased elastic fragmentation on histology. Unexpectedly, male Myh11E1892D/E1892D mice two weeks post-TAC had decreased ejection fraction, stroke volume, fractional shortening, and cardiac output compared to similarly treated male WT mice. Importantly, left ventricular mass increased significantly due to primarily posterior wall thickening, and cardiac histology confirmed cardiomyocyte hypertrophy and increased collagen deposition in the myocardium and surrounding arteries. These results further highlight the clinical heterogeneity associated with MYH11 rare variants. Given that MYH11 is selectively expressed in SMCs, these results implicate a role of vascular SMCs in the heart contributing to cardiac hypertrophy and failure with pressure overload. Author SummaryIn this study, we explore the impact of a specific genetic variant, MYH11 p.Glu1892Asp, on the heart and blood vessels in mice. The MYH11 gene is crucial for smooth muscle cells, which are found in the walls of blood vessels and play an important role in various vascular diseases. We created mice with this genetic variant to see if it would lead to thoracic aortic disease, a condition affecting the main artery from the heart. We found that mice with the variant were similar to normal mice in many aspects, such as growth, blood pressure, and heart function, for up to 13 months. However, when we induced high blood pressure in the mice, the mutant mice showed more significant enlargement of the aorta and damage to the elastic fibers in the aortic walls. Interestingly, male mutant mice also developed heart problems, such as reduced heart pumping ability and increased heart muscle thickness, after the high blood pressure challenge. This was accompanied by signs of heart muscle cell enlargement and increased tissue stiffness. These findings suggest that this rare MYH11 variant can contribute to a range of heart and vascular issues, particularly under conditions of pressure overload, and highlight the importance of smooth muscle cells in the development of these problems.

genetics↗

Serum Amyloid P Secreted by Bone Marrow Adipocytes Drives Skeletal Amyloidosis

The accumulation of amyloid fibrils has been identified in tissues outside the brain, yet little is understood about the formation of extracerebral amyloidosis and its impact on the aging process of these organs. Here, we demonstrate that both transgenic mice modeling Alzheimers disease (AD) and naturally aging mice exhibit accumulated senescent bone marrow adipocytes (BMAds), accompanied by amyloid deposits surrounding the BMAds. Senescent BMAds acquire a secretory phenotype, resulting in a marked increase in the secretion of serum amyloid P component (SAP), also known as pentraxin 2 (PTX2). SAP/PTX2 colocalizes with amyloid deposits around senescent BMAds in vivo and is sufficient to promote the formation of insoluble amyloid deposits from soluble A{beta} peptides in in vitro and ex vivo 3D BMAd-based culture experiments. Additionally, Combined treatment with SAP/PTX2 and A{beta} peptides promotes osteoclastogenesis but inhibits osteoblastogenesis of the precursor cells. Transplantation of senescent BMAds into the bone marrow cavity of healthy young mice is sufficient to induce bone loss. Finally, pharmacological depletion of SAP/PTX2 from aged mice abolishes bone marrow amyloid deposition and effectively rescues the low bone mass phenotype. Thus, senescent BMAds, through the secretion of SAP/PTX2, contribute to the age-associated development of skeletal amyloidosis and resultant bone deficits.

cell biology↗

NOK promotes tumorigenesis through coordinating epidermal growth factor receptor to boost the downstream signaling in breast cancer

BACKGROUNDEpidermal growth factor receptor (EGFR) forms a homodimer or heterodimer with other ErbB receptor family members to activate different downstream cytoplasmic signaling proteins during tumorigenesis. METHODSAdenovirus and lentivirus were used to overexpress or deplete NOK and/or EGFR to evaluate the phosphorylation of EGFR, the interaction of NOK-EGFR and their role in cell proliferation and metastasis. RESULTSEGFR heterodimerizes with NOK (also known as STYK1), a novel tyrosine kinase with a transmembrane domain, to promote tumorigenesis and metastasis of breast cancer cells. We found that NOK directly interacted with EGFR and formed a heterodimer complex. Depletion of NOK impaired, but over-expression of NOK increased, the phosphorylation of EGFR. NOK enhanced EGF signaling activation, in particular, the phosphorylation of STAT3, STAT5 and Erk1/2 via its juxtamembrane (JM) domain in promoting the proliferation and migration of breast cancer cells. Overexpression of NOK and EGFR synergistically induced the tumorigenesis of NIH-3T3 normal cells. We finally demonstrated that co-expression of NOK and EGFR correlated with tumor malignant stages in breast cancer patients. CONCLUSIONSOur findings uncover a mechanism by which NOK coordinates EGFR to enhance EGF signaling during tumorigenesis and metastasis and propose a potential strategy for targeting NOK-EGFR in breast cancer treatment. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/608018v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@17b0078org.highwire.dtl.DTLVardef@5bfe6forg.highwire.dtl.DTLVardef@19d3d15org.highwire.dtl.DTLVardef@155fc4_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIEGFR heterodimerizes with NOK/STYK1, a novel tyrosine kinase with a transmembrane domain, in a manner of cross interaction via their juxtamembrane (JM) domains and kinase domains. C_LIO_LINOK enhances EGF signaling activation, in particular, the phosphorylation of STAT3, STAT5 and Erk1/2 via its JM domain. C_LIO_LINOK and EGFR synergistically promote proliferation and migration of breast cancer cells and induce tumorigenesis of normal cells. C_LIO_LICo-expression of NOK and EGFR correlates with tumor malignant stages in breast cancer patients. C_LI

cell biology↗

A novel functional coordination in UNC-13 regulates neurotransmitter release

Munc13 plays a crucial role in short-term synaptic plasticity by regulating synaptic vesicle (SV) exocytosis and neurotransmitter release at the presynaptic terminals. However, the intricate mechanisms governing these processes have remained elusive due to the presence of multiple functional domains within Munc13, each playing distinct roles in neurotransmitter release. Here we report a coordinated mechanism in the C. elegans Munc13 homolog UNC-13 that controls the functional switch of UNC-13 during synaptic transmission. Mutations disrupting the interactions of C1 and C2B with diacylglycerol (DAG) and phosphatidylinositol 4,5-bisphosphate (PIP2) on the plasma membrane induced the gain-of-function state of UNC-13L, the long UNC-13 isoform, resulting in enhanced SV release. Concurrent mutations in both domains counteracted this enhancement, highlighting the functional interdependence of C1 and C2B. Intriguingly, the individual C1 and C2B domains exhibited significantly stronger facilitation of SV release compared to the presence of both domains, supporting a mutual inhibition of C1 and C2B under basal conditions. Moreover, the N-terminal C2A and X domains exhibited opposite regulation on the functional switch of UNC-13L. Furthermore, we identified the polybasic motif in the C2B domain that facilitates SV release. Finally, we found that disruption of C1 and C2B membrane interaction in UNC-13S, the short isoform, leads to functional switch between gain-of-function and loss-of-function. Collectively, our findings provide a novel mechanism for SV exocytosis wherein UNC-13 undergoes functional switches through the coordination of its major domains, thereby regulating synaptic transmission and short-term synaptic plasticity.

neuroscience↗

Single-Molecule Barcoding Technology for Single-Cell Genomics

Recent advances in barcoding technologies have significantly enhanced the scalability of single-cell genomic experiments. However, large-scale experiments are still rare due to high costs, complex logistics, and laborintensive procedures. To facilitate the routine application of the largest scalability, it is critical to simplify the production and use of barcoding reagents. Here, we introduce AmpliDrop, a technology that initiates the barcoding process using a pool of inexpensive single-copy barcodes and integrates barcode multiplicity generation with tagging of cellular content into a single reaction driven by DNA polymerase during library preparation. The barcoding reactions are compartmentalized using an electronic pipette or a robotic or standalone liquid handling system. These innovations eliminate the need for barcoded beads and complex combinatorial indexing workflows and provide flexibility for a wide range of scales and tube formats, as well as compatibility with automation. We show that AmpliDrop is capable of capturing transcriptomes and chromatin accessibility, and it can also be adapted for user-customized applications, including antibody-based protein detection, bacterial or viral DNA detection, and CRISPR perturbations without dual guide RNA-expression vectors. We validated AmpliDrop by investigating the influence of short-term static culturing on cell composition in human forebrain organoids, revealing metabolic reprogramming in lineage progenitors.

molecular biology↗

Simplified and Rapid Workflow Enhances Throughput of De Novo Sequencing of COVID-19 Neutralizing Antibodies

During the current COVID-19 pandemic, precise antibody sequencing is crucial for the rapid development of broad-spectrum or pan-{beta}-coronavirus neutralizing antibodies (NAbs) to prevent new variants of the coronavirus and other highly pathogenic {beta}-coronaviruses. However, mass spectrometry-based de novo sequencing remains challenging due to its high cost, low throughput, and unexpected missing of certain ion information. We developed an innovative approach using solely bottom-up to provide a rapid, robust, and refined solution for the current de novo sequencing challenges. The methodology, referred to as SP-MEGD for Single-Pot and Multi-Enzymatic Gradient Digestion, capitalizes on a five-protease gradient digestion by sampling every two hours for a total of 6 hours in an integrative reactor. The SP-MEGD method could engender numerous missed cleavage events and produce various peptide products of diverse lengths with overlapping stretches of residues, enabling efficient database-free de novo sequencing. Antibody assembly for single or mixed COVID-19-NAbs with publicly available sequences and commercial antibodies with unknown sequences was efficiently deciphered using our previously proposed optimization method, Fusion assembler. Our innovative study represents the first successful simultaneous discrimination and achieving over 99% accurate sequence coverage of a mixture containing three humanized COVID-19-NAbs (S2P6LH, BD5514LH, and BD5840LH). Furthermore, we utilized SP-MEGD and Fusion to sequence commonly used anti-CD8 and anti-CD4, and successfully confirmed their impact on immune cell clearance through in vivo experiments. Overall, our developed workflow demonstrates promise in facilitating the discovery and development of vaccines and antibody therapeutics while providing deeper insights into monoclonal antibodies (mAbs).

bioengineering↗