Biology subjects

Huang, J.

Publications and source records attributed to Huang, J..

At least 325 records · Page 18Linked to original sources

bioRxiv2023

Differential effects of IL4I1 protein on lymphocytes from healthy and multiple sclerosis patients

Multiple sclerosis (MS) is a chronic inflammatory disease characterized by immune mediated demyelination of the central nervous system, resulting in extensive neurological deficit and remyelination impairment. We have previously found that interleukin-four induced one (IL4I1) protein modulates CNS inflammation and enhances remyelination in mouse models of experimental demyelination. However, it remained unclear if IL4I1 regulates lymphocyte activity in MS. To assess the therapeutic potential of IL4I1 in MS, we investigated the impact of IL4I1 treatment on human lymphocytes from peripheral blood mononuclear cells (PBMCs) obtained from healthy individuals and MS patients. We found that IL4I1 increased the relative densities of Th2 and regulatory T-cells, while reducing Th17 cell density in healthy control samples. Furthermore, IL4I1-treated lymphocytes promoted CNS remyelination when grafted into demyelinated spinal cord lesions in mice. We found that baseline endogenous IL4I1 expression was reduced in people with MS. However, unlike healthy controls, IL4I1 treatment had no significant effect on IL17 or TOB1 expression in lymphocytes derived from MS patients. These results suggest that IL4I1 skews CD4+ T-cells to a regulatory state in healthy human lymphocytes, which may be essential for promoting remyelination. However, IL4I1 appears unable to exert its influence on lymphocytes in MS, indicating that impaired IL4I1-mediated activity may underlie MS pathology.

neuroscience↗

bioRxiv2023

Nuclear Lipid Droplets Exit to the Cytoplasm: A Novel Mechanism of non-nuclear pore-dependent material exchange

In cellular biology, the extrusion of large molecular complexes from the nucleus has consistently represented a considerable challenge. In this investigation, we reveal a hitherto unexplored mechanism facilitating the efflux of nuclear lipid droplets (nLDs) from the nucleus directly into the cytoplasm, a process integral to comprehending cellular processes and nuclear dynamics. Through high-throughput sequencing, immunoprecipitation, and immunofluorescence experimentation, we demonstrated that the type I nucleoplasmic reticulum engages with nLDs, enabling the dynamic protein Rab8as transfer to the nLDs and fostering their translocation to the nuclear membrane. Phosphorylation of LMNA/C at the S392 site, adjacent to the nLD-nuclear membrane contact site, induces local depolymerization of lamins, creating an aperture that enables gradual nuclear exit of nLDs. Following this, nLDs, carrying DNA fragments, are released into the cytoplasm through budding and subsequently undergo autophagy-mediated degradation. Furthermore, we demonstrate that RhoA-PKC signaling enhances nLD movement and LMNA/C phosphorylation, while its inhibition impedes nuclear nLD efflux. Our groundbreaking investigation illuminates non-nuclear pore-dependent mechanisms of material exchange and offers fresh perspectives on nuclear metabolic pathways. In Brief O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/556761v1_ufig1.gif" ALT="Figure 1"> View larger version (107K): org.highwire.dtl.DTLVardef@38a213org.highwire.dtl.DTLVardef@1898caorg.highwire.dtl.DTLVardef@d7270forg.highwire.dtl.DTLVardef@14582a2_HPS_FORMAT_FIGEXP M_FIG C_FIG In this study, Jin et al. elucidate a novel mechanism for the expulsion of nuclear lipid droplets (nLDs) from the nucleus. They demonstrate that the activation of RhoA within the nucleus recruits Rab8a to the surface of nLDs. Concurrently, PKC phosphorylation triggers the phosphorylation of LMNA/C at the S392 site, leading to a localized depolymerization of lamins. This creates an aperture that allows for the gradual exit of nLDs from the nucleus. The efflux process of nLDs involves three sequential steps: rupture of the nuclear fibril layer, fusion of nLDs with the inner nuclear membrane (INM), and subsequent fusion with the outer nuclear membrane (ONM). This enables nLDs to enter the cytoplasm, shedding light on a previously unknown process of large molecular entity expulsion from the nucleus.

molecular biology↗

bioRxiv2023

Systems genetics analysis of human body fat distribution genes identifies Wnt signaling and mitochondrial activity in adipocytes

BACKGROUNDExcess fat in the abdomen is a sexually dimorphic risk factor for cardio-metabolic disease. The relative storage between abdominal and lower-body subcutaneous adipose tissue depots is approximated by the waist-to-hip ratio adjusted for body mass index (WHRadjBMI). Genome-wide association studies (GWAS) identified 346 loci near 495 genes associated with WHRadjBMI. Most of these genes have unknown roles in fat distribution, but many are expressed and putatively act in adipose tissue. We aimed to identify novel sex- and depot-specific drivers of WHRadjBMI using a systems genetics approach. METHODSWe used two independent cohorts of adipose tissue gene expression with 362 - 444 males and 147 - 219 females, primarily of European ancestry. We constructed sex- and depot- specific Bayesian networks to model the gene-gene interactions from 8,492 adipose tissue genes. Key driver analysis identified genes that, in silico and putatively in vitro, regulate many others, including the 495 WHRadjBMI GWAS genes. Key driver gene function was determined by perturbing their expression in human subcutaneous pre-adipocytes using lenti-virus or siRNA. RESULTS51 - 119 key drivers in each network were replicated in both cohorts. We used single-cell expression data to select replicated key drivers expressed in adipocyte precursors and mature adipocytes, prioritized genes which have not been previously studied in adipose tissue, and used public human and mouse data to nominate 53 novel key driver genes (10 - 21 from each network) that may regulate fat distribution by altering adipocyte function. In other cell types, 23 of these genes are found in crucial adipocyte pathways: Wnt signaling or mitochondrial function. We selected seven genes whose expression is highly correlated with WHRadjBMI to further study their effects on adipogenesis/Wnt signaling (ANAPC2, PSME3, RSPO1, TYRO3) or mitochondrial function (C1QTNF3, MIGA1, PSME3, UBR1). Adipogenesis was inhibited in cells overexpressing ANAPC2 and RSPO1 compared to controls. RSPO1 results are consistent with a positive correlation between gene expression in the subcutaneous depot and WHRadjBMI, therefore lower relative storage in the subcutaneous depot. RSPO1 inhibited adipogenesis by increasing {beta}-catenin activation and Wnt-related transcription, thus repressing PPARG and CEBPA. PSME3 overexpression led to more adipogenesis than controls. In differentiated adipocytes, MIGA1 and UBR1 downregulation led to mitochondrial dysfunction, with lower oxygen consumption than controls; MIGA1 knockdown also lowered UCP1 expression. SUMMARYANAPC2, MIGA1, PSME3, RSPO1, and UBR1 affect adipocyte function and may drive body fat distribution.

systems biology↗

bioRxiv2023

Natural genomic variation in rice blast genomes is associated with specific heterochromatinmodifications

Genome organization in eukaryotes exhibits non-random patterns tied to transcription, replication, and chromatin. However, the driving forces across these processes, and their impacts on genome evolution remain unclear. To address this, we analyzed sequence data from 86 Magnaporthe oryzae isolates, a globally important plant pathogenic fungus, alongside new reference genomes, to investigate DNA sequence variation and the epigenome. Histone modification profiles were obtained through genome-wide chromatin immunoprecipitation-sequencing of the four new reference strains, which revealed that repressive histone marks (H3K27me3, H3K9me3) were associated with SNP and INDEL frequency. Densely grouped SNPs were found to reside in heterochromatin, often outside transposable elements, highlighting the link between heterochromatin and DNA variation. Even when controlling for selection, silent SNP frequency/kb was higher in H3K27me3-associated genes. Effector genes, key to pathogenicity, also displayed this trend. Comparing the reference strains, euchromatic regions were often syntenic, while heterochromatic regions trended towards non-syntenic. Heterochromatin emerged as a major factor associated with diverse DNA variations in M. oryzae populations, even when accounting for selective pressure. This underscores heterochromatins pivotal role in shaping genetic diversity in these mainly asexually reproducing fungi.

evolutionary biology↗

bioRxiv2023

Stratification of enterochromaffin cells by single-cell expression analysis

Dynamic interactions between gut mucosal cells and the external environment are essential to maintain gut homeostasis. Enterochromaffin (EC) cells transduce both chemical and mechanical signals and produce 5-hydroxytryptamine (5-HT) to mediate disparate physiological responses. However, the molecular and cellular basis for functional diversity of ECs remains to be adequately defined. Here, we integrated single-cell transcriptomics with spatial image analysis to identify fourteen EC clusters that are topographically organized along the gut. Subtypes predicted to be sensitive to the chemical environment and mechanical forces were identified that express distinct transcription factors and hormones. A Piezo2+ population in the distal colon was endowed with a distinctive neuronal signature. Using a combination of genetic, chemogenetic and pharmacological approaches, we demonstrated Piezo2+ ECs are required for normal colon motility. Our study constructs a molecular map for ECs and offers a framework for deconvoluting EC cells with pleiotropic functions.

cell biology↗

bioRxiv2023

EZH2 synergizes with BRD4-NUT to drive NUT carcinoma growth through silencing of key tumor suppressor genes

NUT carcinoma (NC) is an aggressive carcinoma driven by the BRD4-NUT fusion oncoprotein, which activates chromatin to promote expression of pro-growth genes. BET bromodomain inhibitors (BETi) impede BRD4-NUTs ability to activate genes and are thus a promising treatment but limited as monotherapy. The role of gene repression in NC is unknown. Here, we demonstrate that EZH2, which silences genes through establishment of repressive chromatin, is a dependency in NC. Inhibition of EZH2 with the clinical compound tazemetostat (taz) potently blocked growth of NC cells. Epigenetic and transcriptomic analysis revealed that taz reversed the EZH2-specific H3K27me3 silencing mark, and restored expression of multiple tumor suppressor genes while having no effect on key oncogenic BRD4- NUT-regulated genes. CDKN2A was identified as the only gene amongst all taz-derepressed genes to confer resistance to taz in a CRISPR-Cas9 screen. Combined EZH2 inhibition and BET inhibition synergized to downregulate cell proliferation genes resulting in more pronounced growth arrest and differentiation than either inhibitor alone. In pre-clinical models, combined taz and BETi synergistically blocked growth and prolonged survival of NC-xenografted mice, with all mice cured in one cohort. STATEMENT OF SIGNIFICANCEIdentification of EZH2 as a dependency in NC substantiates the reliance of NC tumor cells on epigenetic dysregulation of functionally opposite, yet highly complementary chromatin regulatory pathways to maintain NC growth. In particular, repression of CDKN2A expression by EZH2 provides a mechanistic rationale for combining EZH2i with BETi for the clinical treatment of NC.

cancer biology↗

bioRxiv2023

Search and Match across Spatial Omics Samples at Single-cell Resolution

Spatial omics technologies characterize tissue molecular properties with spatial information, but integrating and comparing spatial data across different technologies and modalities is challenging. A comparative analysis tool that can search, match, and visualize both similarities and differences of molecular features in space across multiple samples is lacking. To address this, we introduce CAST (Cross-sample Alignment of SpaTial omics), a deep graph neural network (GNN)-based method enabling spatial-to-spatial searching and matching at the single-cell level. CAST aligns tissues based on intrinsic similarities of spatial molecular features and reconstructs spatially resolved single-cell multi-omic profiles. CAST enables spatially resolved differential analysis ({Delta}Analysis) to pinpoint and visualize disease-associated molecular pathways and cell-cell interactions, and single-cell relative translational efficiency (scRTE) profiling to reveal variations in translational control across cell types and regions. CAST serves as an integrative framework for seamless single-cell spatial data searching and matching across technologies, modalities, and disease conditions, analogous to BLAST in sequence alignment.

bioinformatics↗

bioRxiv2023

Cigarette smoking promotes the spread of antimicrobial resistance in the human lung and the environment

While immediate health risks of cigarette smoking are well-established, indirect health impacts of cigarette-derived pollutants through proliferation of antimicrobial resistance (AMR) among bacteria remain understudied. Here, exposure to cigarette smoke condensate at relevant concentrations resulted in >2-fold elevated transfer rates of a multi-drug-resistance encoding plasmid between Pseudomonas strains in artificial lung sputum medium. This effect was connected to elevated reactive oxygen species production as part of the bacterial stress response when exposed to cigarette-derived toxicants. Similar results were obtained under exposure to cigarette ash leachate in environmental medium. Further, used cigarette filters enriched in toxic residues were submerged in a wastewater stream, and colonized by altered microbial communities compared to unused filters. These communities were significantly enriched in pathogens and AMR. Hence, filters could facilitate hitchhiking of high-risk bacteria to novel environments. We demonstrate that cigarette-derived compounds can promote the spread of AMR within the human lung and natural environments.

microbiology↗

bioRxiv2023

OBMeta: a comprehensive web server to analyze and validate gut microbial features and biomarkers for obesity-associated metabolic diseases

Gut dysbiosis is closely associated with obesity and related metabolic diseases including type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD). The gut microbial features and biomarkers have been increasingly investigated in recent studies, which require further validation due to the limited sample size and various confounding factors that may affect microbial compositions. So far, it lacks a comprehensive bioinformatics pipeline providing automated statistical analysis and integrating independent studies for cross validation simultaneously. OBMeta aims to streamline the standard metagenomics data analysis from diversity analysis, comparative analysis, functional analysis, to co-abundance network analysis. In addition, a curated database has been established with a total of 88 public research projects, covering three different phenotypes (Obesity, T2D, and NAFLD) and more than five different intervention strategies (exercise, diet, probiotics, medication, and surgery). With OBMeta, users can not only analyze their own research projects, but also search and match public datasets of interest for cross-project validation. Moreover, OBMeta provides cross-phenotype and cross-intervention-based advanced validation that maximally supports preliminary findings from an individual study. To summarize, OBMeta is a comprehensive web server to analyze and validate gut microbial features and biomarkers for obesity-associated metabolic diseases. OBMeta is freely available at: http://obmeta.met-bioinformatics.cn/. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/552363v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1b58a9borg.highwire.dtl.DTLVardef@19efa47org.highwire.dtl.DTLVardef@418597org.highwire.dtl.DTLVardef@1a9bc3c_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2023

Can Protein Structure Prediction Methods Capture Alternative Conformations of Membrane Proteins?

Understanding the conformational dynamics of proteins, such as the inward-facing (IF) and outward-facing (OF) transition observed in transporters, is vital for elucidating their functional mechanisms. Despite significant advances in protein structure prediction (PSP) over the past three decades, most efforts have been focused on single-state prediction, leaving multi-state or alternative conformation prediction (ACP) relatively unexplored. This discrepancy has led to the development of highly accurate PSP methods such as AlphaFold, yet their capabilities for ACP remain limited. To investigate the performance of current PSP methods in ACP, we curated a dataset, named IOMemP, consisting of 32 experimentally determined high-resolution IF and OF structures of 16 membrane proteins. We benchmarked 12 representative PSP methods, along with two recent multi-state methods based on AlphaFold, against this dataset. Our findings reveal an escalating bias towards one specific state in deep learning-based methods and a remarkably consistent preference for specific states across various PSP methods. We elucidated how coevolution information in MSAs influences the state preference. Moreover, we showed that AlphaFold, when excluding coevolution information, estimated similar energies between the experimental IF and OF conformations, indicating that the energy model learned by AlphaFold is not biased towards any particular state. Our IOMemP dataset and benchmark results are anticipated to advance the development of robust ACP methods.

bioinformatics↗

bioRxiv2023

Chrombus-XMBD: A Graph Generative Model Predicting 3D-Genome, ab initio from Chromatin Features

AbstractsThe landscape of 3D-genome is crucial for transcription regulation. But capturing the dynamics of chromatin conformation is costly and technically challenging. Here we described "Chrombus-XMBD", a graph generative model capable of predicting chromatin interactions ab inito based on available chromatin features. Chrombus employes dynamic edge convolution with QKV attention setup, which maps the relevant chromatin features to a learnable embedding space thereby generate genomewide 3D-contactmap. We validated Chrombus predictions with published databases of topological associated domains (TAD), eQTLs and gene-enhancer interactions. Chrombus outperforms existing algorithms in efficiently predicting long-range chromatin interactions. Chrombus also exhibits strong generalizability across different cell lineage and species. Additionally, the parameter sets of Chrombus inform the biological processes underlying 3D-genome. Our model provides a new perspective towards interpretable AI-modeling of the dynamics of chromatin interactions and better understanding of cis-regulation of gene expression.

bioinformatics↗

bioRxiv2023

Interpreting SNP heritability in admixed populations

SNP heritability [Formula] is defined as the proportion of phenotypic variance explained by genotyped SNPs and is believed to be a lower bound of heritability (h2), being equal to it if all causal variants are genotyped. Despite the simple intuition behind [Formula], its interpretation and equivalence to h2 is unclear, particularly in the presence of admixture and assortative mating. Here we use analytical theory and simulations to describe the behavior of h2 and three widely used random-effect estimators of [Formula] Genome-wide restricted maximum likelihood (GREML), Haseman-Elston (HE) regression, and LD score regression (LDSC) - in admixed populations. We show that [Formula] estimates can be biased in admixed populations, even if all causal variants are genotyped and in the absence of confounding due to shared environment. This is largely because admixture generates directional LD, which contributes to the genetic variance, and therefore to heritability. Random-effect estimators of [Formula], because they assume that SNP effects are independent, do not capture the contribution, which can be positive or negative depending on the genetic architecture, leading to under- or over-estimates of [Formula] relative to h2. For the same reason, estimates of local ancestry heritability [Formula] are also biased in the presence of directional LD. We describe this bias in [Formula] and [Formula] as a function of admixture history and the genetic architecture of the trait, clarifying their interpretation and implication for genome-wide association studies and polygenic prediction in admixed populations.

genetics↗

bioRxiv2023

Cuprizone drives divergent neuropathological changes in different mouse models of Alzheimer's disease

Myelin degradation is a normal feature of brain aging that accelerates in Alzheimers disease (AD). To date, however, the underlying biological basis of this correlation remains elusive. The amyloid cascade hypothesis predicts that demyelination is caused by increased levels of the {beta}-amyloid (A{beta}) peptide. Here we report on work supporting the alternative hypothesis that early demyelination is upstream of amyloid. We challenged two different mouse models of AD (R1.40 and APP/PS1) using cuprizone-induced demyelination and tracked the responses with both neuroimaging and neuropathology. In oppose to amyloid cascade hypothesis, R1.40 mice, carrying only a single human mutant APP (Swedish; APPSWE) transgene, showed a more abnormal changes of magnetization transfer ratio and diffusivity than in APP/PS1 mice, which carry both APPSWE and a second PSEN1 transgene (delta exon 9; PSEN1dE9). Although cuprizone targets oligodendrocytes (OL), magnetic resonance spectroscopy and targeted RNA-seq data in R1.40 mice suggested a possible metabolic alternation in axons. In support of alternative hypotheses, cuprizone induced significant intraneuronal amyloid deposition in young APP/PS1, but not in R1.40 mice, and it suggested the presence of PSEN deficiencies, may accelerate A{beta} deposition upon demyelination. In APP/PS1, mature OL is highly vulnerable to cuprizone with significant DNA double strand breaks (53BP1+) formation. Despite these major changes in myelin, OLs, and A{beta} immunoreactivity, no cognitive impairment or hippocampal pathology was detected in APP/PS1 mice after cuprizone treatment. Together, our data supports the hypothesis that myelin loss can be the cause, but not the consequence, of AD pathology. SIGNIFICANCE STATEMENTThe causal relationship between early myelin loss and the progression of Alzheimers disease remains unclear. Using two different AD mouse models, R1.40 and APP/PS1, our study supports the hypothesis that myelin abnormalities are upstream of amyloid production and deposition. We find that acute demyelination initiates intraneuronal amyloid deposition in the frontal cortex. Further, the loss of oligodendrocytes, coupled with the accelerated intraneuronal amyloid deposition, interferes with myelin tract diffusivity at a stage before any hippocampus pathology or cognitive impairments occur. We propose that myelin loss could be the cause, not the consequence, of amyloid pathology during the early stages of Alzheimers disease.

neuroscience↗

bioRxiv2023

CysQuant: simultaneous quantification of cysteine oxidation and protein abundance using data dependent or independent acquisition mass spectrometry

Protein cysteinyl thiols are susceptible to reduction-oxidation reactions that can influence protein function. Accurate quantification of cysteine oxidation is therefore crucial for decoding protein redox regulation. Here, we present CysQuant, a novel approach for simultaneous quantification of cysteine oxidation degrees and protein abundancies. CysQuant involves light/heavy iodoacetamide isotopologues for differential labeling of reduced and reversibly oxidized cysteines analyzed by data-dependent acquisition (DDA) or data-independent acquisition mass spectrometry (DIA-MS). Using plexDIA with in silico predicted spectral libraries, we quantified an average of 18% cysteine oxidation in Arabidopsis thaliana by DIA-MS, including a subset of highly oxidized cysteines forming disulfide bridges in AlphaFold2 predicted structures. Applying CysQuant to Arabidopsis seedlings exposed to excessive light, we successfully quantified the well-established increased reduction of Calvin-Benson cycle enzymes and discovered yet uncharacterized redox-sensitive disulfides in chloroplastic enzymes. Overall, CysQuant is a highly versatile tool for assessing the cysteine modification status that can be widely applied across various mass spectrometry platforms and organisms.

molecular biology↗

bioRxiv2023

Extracting herbicide and antibiotic natural products from a plant-microbe interaction system

Plants and their associated microbes live in complicated, changeable, and unpredictable environments. They usually interact with each other in many ways by proceeding in multi-dimensional, multi-scale and multi-level coupling manners, leading to challenges of the co-existence of randomness and determinism, or continuity and discreteness. Gaining a deeper understanding of these diverse interaction mechanisms can facilitate the development of new data mining theories and methods for complex systems, new coupled modelling for the system with different spatiotemporal scales and functional properties, or even universal theory of information and information interactions. In this study, we use a "close-loop" model to present a plant-microbe interaction system and describe the probable functions from the microbial natural products. Specifically, we report a rhizosphere species, Streptomyces ginsengnesis G7, which produces polyketide lydicamycins and other active metabolites. Interestingly, these distinct molecules have the potential to function both as antibiotics and herbicides for crop protection. Detailed laboratory experiments combined with comprehensive bioinformatics analysis allow us to rationalise a model for this specific plant-microbe interaction process. Our work reveals the benefits of exploring otherwise neglectable resources for the identification of novel functional molecules and provides a good reference to better understand the system biology in the complex ecosystems.

cell biology↗

bioRxiv2023

OrtR regulates the oxidative stress response of Streptococcus mutans

Dental caries is the most common chronic infectious diseases around the world and disproportionately affects the marginalized socioeconomic group. Streptococcus mutans, considered a primary etiological agent of caries, must depend on the coordinated physiological response to tolerate the oxidative stress generated by commensal species within dental plaque, which is a critical aspect of its pathogenicity. Here, we identified and characterized a novel TetR family regulator SMU_1361c, encoded by the TnSmu2 operon, which appears to be acquired by the bacteria via horizontal genes transfer. Surprisingly, smu_1361c functions as a transcriptional repressor to regulate gene expression outside its operon, involved in the oxidative stress response of S. mutans. The smu_1361c overexpression strain UA159/pDL278-1361c was more susceptible to oxidative stress and less competitive against hydrogen peroxide generated by commensal species Streptococcus gordonii and Streptococcus sanguinis. Transcriptomics analysis revealed that smu_1361c overexpression resulted in the significant downregulation of 22 genes mainly belonging to three gene clusters responsible for the oxidative stress response. The conversed DNA binding motif of SMU_1361c was determined by electrophoretic mobility shift and DNase I footprinting assay with purified SMU_1361c protein, therefore, smu_1361c is directly involved in gene transcription related to the oxidative stress response. Crucially, our finding provides a new understanding of how S. mutans deals with the oxidative stress that is required for pathogenesis and will facilitate the development of new and improved therapeutic approaches for dental caries.

microbiology↗

bioRxiv2023

Flow cytometric isolation of drug-like conformational antibodies specific for amyloid fibrils

Antibodies that recognize specific protein conformational states are broadly important for research, diagnostic and therapeutic applications, yet they are difficult to generate in a predictable and systematic manner using either immunization or in vitro antibody display methods. This problem is particularly severe for conformational antibodies that recognize insoluble antigens such as amyloid fibrils associated with many neurodegenerative disorders. Here we report a quantitative fluorescence-activated cell sorting (FACS) method for directly selecting high-quality conformational antibodies against different types of insoluble (amyloid fibril) antigens using a single, off-the-shelf human library. Our approach uses quantum dots functionalized with antibodies to capture insoluble antigens, and the resulting quantum dot conjugates are used in a similar manner as conventional soluble antigens for multi-parameter FACS selections. Notably, we find that this approach is robust for isolating high-quality conformational antibodies against tau and -synuclein fibrils from the same human library with combinations of high affinity, high conformational specificity and, in some cases, low off-target binding that rival or exceed those of clinical-stage antibodies specific for tau (zagotenemab) and -synuclein (cinpanemab). This approach is expected to enable conformational antibody selection and engineering against diverse types of protein aggregates and other insoluble antigens (e.g., membrane proteins) that are compatible with presentation on the surface of antibody-functionalized quantum dots.

bioengineering↗

bioRxiv2023

Mitigating autocorrelation during spatially resolved transcriptomics data analysis

Several computational methods have recently been developed for characterizing molecular tissue regions in spatially resolved transcriptomics (SRT) data. However, each method fundamentally relies on spatially smoothing transcriptomic features across neighboring cells. Here, we demonstrate that smoothing increases autocorrelation between neighboring cells, causing latent space to encode physical adjacency rather than spatial transcriptomic patterns. We find that randomly sub-sampling neighbors before smoothing mitigates autocorrelation, improving the performance of existing methods and further enabling a simpler, more efficient approach that we call spatial integration (SPIN). SPIN leverages the conventional single-cell toolkit, yielding spatial analogies to each tool: clustering identifies molecular tissue regions; differentially expressed gene analysis calculates region marker genes; trajectory inference reveals continuous, molecularly defined ana tomical axes; and integration allows joint analysis across multiple SRT datasets, regardless of tissue morphology, spatial resolution, or experimental technology. We apply SPIN to SRT datasets from mouse and marmoset brains to calculate shared and species-specific region marker genes as well as a molecularly defined neocortical depth axis along which several genes and cell types differ across species.

bioinformatics↗