Biology subjects

Song, D.

Publications and source records attributed to Song, D..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

A brain-shuttled antibody targeting alpha synuclein aggregates for the treatment of synucleinopathies

Parkinsons disease and multiple system atrophy are members of a class of devastating neurodegenerative diseases called synucleinopathies, which are characterized by the presence of alpha-synuclein (-Syn) rich aggregates in the brains of patients. Passive immunotherapy targeting these aggregates is an attractive disease-modifying strategy. Such an approach must not only demonstrate target selectivity towards -Syn aggregates, but also achieve appropriate brain exposure to have the desired therapeutic effect. Here we present preclinical data for a next-generation antibody for the treatment of synucleinopathies. SAR446159 (ABL301) is a bispecific antibody composed of an -Syn-binding immunoglobulin (IgG) and an engineered insulin-like growth factor receptor 1 (IGF1R) binding single-chain variable fragment (scFv), acting as a shuttle to transport an antibody across the blood-brain barrier (BBB). SAR446159 binds tightly and preferentially to -Syn aggregates and prevents their seeding capacity in vitro and in vivo. Incubation with SAR446159 reduced -Syn preformed fibrils (PFFs) uptake in neurons and facilitated uptake and clearance by microglia. In wild type mice injected in the striatum with -Syn PFFs, treatment with SAR446159 reduced the spread of aSyn pathology as measured by phosphorylated -Syn staining and lessened the severity of motor phenotypes. Additionally, in 9-month-old transgenic mice overexpressing -Syn (mThy1--Syn, Line 61), repeated treatment with SAR446159 reduced markers of -Syn aggregation in the brain. SAR446159 had significantly higher brain and CSF penetration over a sustained period than its monospecific counterpart (1E4) in rats and monkeys. The binding properties of SAR446159 combined with its brain-shuttle technology make it a potent, next-generation immunotherapeutic for treating synucleinopathies.

neuroscience↗

bioRxiv2024

Spatial Single-Cell Mapping of Transcriptional Differences Across Genetic Backgrounds in Mouse Brains

Genetic variation can alter organ structure and, in turn, function. Comparative statistical analysis of organs across genetic backgrounds requires spatial, single-cell, atlas-scale data in replicates, which current technologies do not provide at scale. We introduce Atlas-scale Transcriptome Localization using Aggregate Signatures (ATLAS), a scalable tissue mapping method. ATLAS learns transcriptional signatures from scRNAseq data, encodes them in situ with tens of thousands of oligonucleotide probes, and decodes them to infer cell types and imputed transcriptomes. We validated ATLAS in the mouse brain by comparing its cell type inferences with direct MERFISH measurements of marker genes and quantitative comparisons to four other technologies. Using ATLAS, we mapped the central brains of five male and five female C57BL/6J (B6) mice and five male BTBR T+ tf/J (BTBR) mice, an idiopathic model of autism, collectively profiling over 40 million cells across over 400 coronal sections. Our analysis revealed over 40 significant differences in cell type distributions and identified 16 regional composition changes across male-female and B6-BTBR comparisons. ATLAS thus enables systematic comparative studies, facilitating organ-level structure-function analysis of disease models.

genomics↗

bioRxiv2024

Hepatic aldose reductase drives a Warburg effect-like metabolic reprogramming to promote insulin resistance, fatty liver and obesity

Background & AimsEmerging evidence suggest that abnormal activation of aldose reductase/the polyol pathway (Ar/PP) is associated with the pathogenesis or development of fatty liver, obesity and metabolic syndrome. However, the underlying mechanisms were unclear. In this study, we investigated the metabolic reprogramming following activation or inhibition of Ar, the first and the rate-limiting enzyme of PP. We also investigated the long-term effects of Ar/PP-mediated metabolic shift in vivo. MethodsMetabolomic analyses were performed with the AB-SCIE QTRAP-5500 LC-MS/MS System for control mouse hepatocytes and hepatocytes stably overexpressing Ar and exposed to 25 mM glucose. Glycolysis stress tests and mitochondrial stress tests were performed using the Seahorse Bioscience Extracellular Flux Analyzer. The in vivo long-term effects of Ar overexpression and inhibition were evaluated in either transgenic mice overexpressing AR or a line of double transgenic mice carrying an Ar-null mutation and an Agouti-yellow Ay mutation. ResultsAbnormal activation of Ar in hepatocytes was found to trigger and drive a drastic Warburg effect-like metabolic reprogramming, induce de novo lipogenesis, and alter insulin and AMP-activated protein kinase signaling. In glucose-fed AR-overexpressing transgenic mice, AR activation causes systemic alterations in physiological parameters and the development of overt phenotypes of insulin resistance, fatty liver, obesity. In the yellow obese syndrome mice, Ar deficiency greatly improves Agouti Ay mutation-induced abnormalities. ConclusionsCollectively, the results highlight the important contribution of Ar/PP or the putative pseudo-glycolysis in hepatic metabolic homeostasis and the development of metabolic diseases. These findings have profound implications for the development of therapeutic strategies or drugs against metabolic diseases and cancer. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/614395v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@de91ddorg.highwire.dtl.DTLVardef@3a801corg.highwire.dtl.DTLVardef@b0cf35org.highwire.dtl.DTLVardef@1f3c1c1_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIActivation of aldose reductase triggers and drives a Warburg effect-like metabolic eprogramming in hepatocytes. C_LIO_LILiver-specific activation of the polyol pathway leads to insulin resistance, fatty liver and obesity. C_LIO_LIInhibition of aldose reductase greatly ameliorates Agouti Ay-induced metabolic abnormalities. C_LI Impact and implicationsThis study reveals that abnormal activation of Ar/PP will trigger and drive a Warburg effect-like metabolic reprogramming in hepatocytes. In normal subjects, Ar/PP mediated metabolic reprogramming tends to promote lipogenesis, insulin resistance, fatty liver and obesity. In cancer cells, Ar/PP mediated metabolic reprogramming will be part of the Warburg effect to support the growth and proliferation of cancer cells. These findings imply that Ar and its down-stream metabolic enzymes are important therapeutic targets for cancers and metabolic diseases.

biochemistry↗

bioRxiv2024

Phenotype Prediction Using BEN-Based Predictive Modeling (BPM)

Functional connectivity (FC) has been successfully used to predict cognitive functions, behaviors, and other phenotypes using connectome-based predictive modeling (CPM). One limitation is that FC reflects the covariation or synchrony relationship of the temporal profile in two regions and neglects the local temporal features of the brain activity. In this study, we used brain entropy (BEN) mapping to characterize regional brain activity and developed a BEN-Based Predictive Modeling (BPM) to predict phenotype. BEN measures the disorder and complexity of brain activity and has been shown to effectively capture brain activity features related to cognition and neurological disorders. Using data from the HCP 7T fMRI and corresponding 3T structural images, we calculated gray matter volume (GMV) as well as BEN from resting state and movie-watching data. We constructed prediction models based on BEN and GMV using different numbers of parcellation of the brain atlas, applying 10-fold cross-validation. Our results indicated that the BEN-based predictive model not only outperformed GMV-based predictive modeling but also achieved prediction accuracy comparable to that of CPM. Our study demonstrates that BEN can capture extensive brain activity information for accurate phenotype prediction, providing information at least as valuable as that from connectome. Additionally, our research lays the groundwork for future applications of BPM in developmental and clinical practice.

neuroscience↗

bioRxiv2024

Neurotransmitters Contribute Structure-Function Coupling: Evidence from Grey Matter Volume (GMV) and Brain Entropy (BEN)

The emergence of human brain function from macroscopic anatomical structures and its relationship with the coupling of structure and function have long been pivotal questions in neuroscience. Neurotransmitter receptors are critical in signal transmission, regulating brain function, and potentially enhancing the coupling between brain structure and function. Recent research suggests that neurotransmitter systems facilitate this coupling between structural and functional networks. However, the mechanisms of how neurotransmitters adapt to local anatomical structures and drive functional emergence are not yet fully understood. This study explores these mechanisms using gray matter volume (GMV) and brain entropy (BEN). BEN reflects the irregularity, unpredictability, and complexity of brain activity, and functional MRI (fMRI)-based BEN has identified its distribution in the normal human brain. BEN is correlated to cognitive and task performance, and aberrant BEN patterns link to various brain disorders. Notably, BEN can indicate neuroplasticity through non-invasive brain stimulation, and pharmacological intervention. We analyzed structural imaging data, as well as 7T resting-state and movie-watching fMRI data from 176 participants in the Human Connectome Project (HCP), to calculate GMV, resting-state BEN (rsBEN), and movie-watching BEN (mvBEN). By integrating data from the publicly available neurotransmitter receptors database, we evaluated the role of neurotransmitters in the coupling between GMV and rsBEN, GMV and mvBEN, and rsBEN and mvBEN. Our findings reveal that neurotransmitters significantly contribute to structural and functional coupling and influence the transition from task-free to movie-watching conditions.

neuroscience↗

bioRxiv2024

Human erythroid progenitors express antigen presentation machinery

Early-life immune exposures can profoundly impact lifelong health. However, functional mechanisms underlying fetal immune development remain incomplete. Erythrocytes are not typically considered active immune mediators, primarily because erythroid precursors discard their organelles as they mature, thus losing the ability to alter gene expression in response to stimuli. Erythroid progenitors and precursors circulate in human fetuses and neonates. Although there is limited evidence that erythroid precursors are immunomodulatory, our understanding of the underlying mechanisms remains inadequate. To define the immunobiological role of fetal and perinatal erythroid progenitors and precursors, we analyzed single cell RNA-sequencing data and found that transcriptomics support erythroid progenitors as putative immune mediators. Unexpectedly, we discovered that human erythroid progenitors constitutively express Major Histocompatibility Complex (MHC) class II antigen processing and presentation machinery, which are hallmarks of specialized antigen presenting immune cells. Furthermore, we demonstrate that erythroid progenitors internalize and cleave foreign proteins into peptide antigens. Unlike conventional antigen presenting cells, erythroid progenitors express atypical costimulatory molecules and immunoregulatory cytokines that direct the development of regulatory T cells, which are critical for establishing maternal-fetal tolerance. Expression of MHC II in definitive erythroid progenitors begins during the second trimester, coinciding with the appearance of mature T cells in the fetus, and is absent in primitive progenitors. Lastly, we demonstrate physical and molecular interaction potential of erythroid progenitors and T cells in the fetal liver. Our findings shed light on a unique orchestrator of fetal immunity and provide insight into the mechanisms by which erythroid cells contribute to host defense.

immunology↗

bioRxiv2024

FADS and semi-rational design modified T7 RNA polymerase reduced dsRNA production, with lower terminal transferase and RDRP activities

T7 RNA polymerase (T7 RNAP) is the preferred tool for in vitro transcription (IVT), it synthesizes mRNA while accompanied by the generation of dsRNA by-products. This undesirable dsRNA triggers immune stress responses, compromises therapeutic efficacy, and raises safety concerns. To evolve T7 RNAP for reduced dsRNA, we pursued two complementary strategies. Firstly, the FADS (fluorescence-activated droplet sorting) based on molecular beacons was used to screen random libraries with diversity exceeding 105. Secondly, we constructed several single-site saturated libraries to facilitate the transition of T7 RNAP from the initiation to the elongation conformation. These libraries were screened using the traditional microplate-based dual-probe screening technique. Both approaches identified two dominant variants: Mut1 (V214A) and Mut7 (F162S/A247T) from FADS, Mut11 (K180E) and Mut14 (A70Q) from saturated libraries. Furthermore, the combinatorial mutant Mut17 (A70Q/F162S/K180E), generated via DNA shuffling, exhibited significantly reduced dsRNA production compared to the wild-type under various conditions, ranging from 0.18% to 1.80%, with a minimum value of 0.5 pg/g. Cell experiments confirmed that variants generated capped-mRNA with similar quality and quantity to the wild-type, while significantly reducing immune stress response in cells. These results indicate the compatibility and broad potential applications of these mutations. We then observed a close correlation between the production of dsRNA and the activities of T7 RNAP in terminal transferase and RDRP. Particularly, the terminal transferase activity appears to play a critical role in dsRNA generation. These findings align with the mechanism of dsRNA formation during IVT and provide new screening criteria for further evolution of T7 RNAP.

molecular biology↗

bioRxiv2024

Single-Molecule Imaging Reveals the Mechanism of Bidirectional Replication Initiation in Metazoa

Metazoan genomes are copied bidirectionally from thousands of replication origins. Replication initiation entails the assembly and activation of two CMG (Cdc45*Mcm2-7*GINS) helicases at each origin. This requires several firing factors (including TopBP1, RecQL4, DONSON) whose exact roles remain unclear. How two helicases are correctly assembled and activated at every single origin is a long-standing question. By visualizing the recruitment of GINS, Cdc45, TopBP1, RecQL4, and DONSON in real time, we uncovered a surprisingly dynamic picture of initiation. Firing factors transiently bind origins but do not travel with replisomes. Two Cdc45 simultaneously arrive at each origin and two GINS are recruited together, even though neither protein can dimerize. The synchronized delivery of two GINS is mediated by DONSON, which acts as a dimerization scaffold. We show that RecQL4 promotes DONSON dissociation and facilitates helicase activation. The high fidelity of bidirectional origin firing can be explained by a Hopfield-style kinetic proofreading mechanism.

molecular biology↗

bioRxiv2023

Benchmarking computational methods to identify spatially variable genes and peaks

Spatially resolved transcriptomics offers unprecedented insight by enabling the profiling of gene expression within the intact spatial context of cells, effectively adding a new and essential dimension to data interpretation. To efficiently detect spatial structure of interest, an essential step in analyzing such data involves identifying spatially variable genes. Despite researchers having developed several computational methods to accomplish this task, the lack of a comprehensive benchmark evaluating their performance remains a considerable gap in the field. Here, we present a systematic evaluation of 14 methods using 60 simulated datasets generated by four different simulation strategies, 12 real-world transcriptomics, and three spatial ATAC-seq datasets. We find that spatialDE2 consistently outperforms the other benchmarked methods, and Morans I achieves competitive performance in different experimental settings. Moreover, our results reveal that more specialized algorithms are needed to identify spatially variable peaks.

bioinformatics↗

bioRxiv2023

Synthetic mucus barrier arrays as a nanoparticle formulation screening platform

A mucus gel layer lines the luminal surface of tissues throughout the body to protect them from infectious agents and particulates. As a result, nanoparticle drug delivery systems delivered to these sites may become trapped in mucus and subsequently cleared before they can reach target cells. As such, optimizing the properties of nanoparticle delivery vehicles, such as their surface chemistry and size, is essential to improving their penetration through the mucus barrier. In previous work, we developed a mucin-based hydrogel that has viscoelastic properties like that of native mucus which can be further tailored to mimic specific mucosal tissues and disease states. Using this biomimetic hydrogel system, a 3D-printed array containing synthetic mucus barriers was created that is compatible with a 96-well plate enabling its use as a high-throughput screening platform for nanoparticle drug delivery applications. To validate this system, we evaluated several established design parameters to determine their impact on nanoparticle penetration through synthetic mucus barriers. Consistent with the literature, we found nanoparticles of smaller size and coated with a protective PEG layer more efficiently penetrated through synthetic mucus barriers. In addition, we evaluated a mucolytic (tris (2-carboxyethyl) phosphine, TCEP) for use as a permeation enhancer for mucosal drug delivery. In comparison to N-acetyl cysteine (NAC), we found TCEP significantly improved nanoparticle penetration through a disease-like synthetic mucus barrier. Overall, our results establish a new high-throughput screening approach using synthetic mucus barrier arrays to identify promising nanoparticle formulation strategies for drug delivery to mucosal tissues.

bioengineering↗

bioRxiv2023

Polymer Implantable Electrode Foundry: A shared resource for manufacturing polymer-based microelectrodes for neural interfaces

Large scale monitoring of neural activity at the single unit level can be achieved via electrophysiological recording using implanted microelectrodes. While neuroscience researchers have widely employed chronically implanted electrode-based interfaces for this purpose, a commonly encountered limitation is loss of highly resolved signals arising from immunological response over time. Next generation electrode-based interfaces improve longitudinal signal quality using the strategy of stabilizing the device-tissue interface with microelectrode arrays constructed from soft and flexible polymer materials. The limited availability of such polymer microelectrode arrays has restricted access to a small number of researchers able to build their own custom devices or who have developed specific collaborations with engineering researchers who can produce them. Here, a new technology resource model is introduced that seeks to widely increase access to polymer microelectrode arrays by the neuroscience research community. The Polymer Implantable Electrode (PIE) Foundry provides custom and standardized polymer microelectrode arrays as well as training and guidance on best-practices for implantation and chronic experiments.

neuroscience↗

bioRxiv2023

Decoding Heterogenous Single-cell Perturbation Responses

Understanding diverse responses of individual cells to the same perturbation is central to many biological and biomedical problems. Current methods, however, do not precisely quantify the strength of perturbation responses and, more importantly, reveal new biological insights from heterogeneity in responses. Here we introduce the perturbation-response score (PS), based on constrained quadratic optimization, to quantify diverse perturbation responses at a single-cell level. Applied to single-cell transcriptomes of large-scale genetic perturbation datasets (e.g., Perturb-seq), PS outperforms existing methods for quantifying partial gene perturbation responses. In addition, PS presents two major advances. First, PS enables large-scale, single-cell-resolution dosage analysis of perturbation, without the need to titrate perturbation strength. By analyzing the dose-response patterns of over 2,000 essential genes in Perturb-seq, we identify two distinct patterns, depending on whether a moderate reduction in their expression induces strong downstream expression alterations. Second, PS identifies intrinsic and extrinsic biological determinants of perturbation responses. We demonstrate the application of PS in contexts such as T cell stimulation, latent HIV-1 expression, and pancreatic cell differentiation. Notably, PS unveiled a previously unrecognized, cell-type-specific role of coiled-coil domain containing 6 (CCDC6) in guiding liver and pancreatic lineage decisions, where CCDC6 knockouts drive the endoderm cell differentiation towards liver lineage, rather than pancreatic lineage. The PS approach provides an innovative method for dose-to-function analysis and will enable new biological discoveries from single-cell perturbation datasets. One sentence summaryWe present a method to quantify diverse perturbation responses and discover novel biological insights in single-cell perturbation datasets.

bioinformatics↗

bioRxiv2023

Arrested Agonist Paradigm For Selective Radiosensitization of Prostate Cancer

As a prototypical nuclear hormone receptor, the androgen receptor (AR) signals via a sequential cascade triggered by binding to androgenic ligands such as testosterone and dihydrotestosterone (DHT). This cascade includes dimerization of the ligand-receptor complex, nuclear translocation, chromatin binding to response elements, recruitment of TOP2B and co-activator complexes, and induction of an effector transcriptional program. In prostate cancers, this AR signaling cascade is an essential driver of growth and survival, yet its activity confers potential vulnerabilities through transient TOP2B-mediated DNA double strand breaks. We investigated the ability of non-steroidal AR ligands to activate initial steps of the AR signaling cascade up to the point of AR- and TOP2B-mediated double strand breaks, with subsequent arrest of the signaling cascade to prevent induction of pro-growth/survival transcriptional programs in prostate cancer cells. We identified hydroxyflutamide (FLU) as such an androgen receptor arrested agonist; in androgen-deprived conditions, FLU induced AR nuclear translocation, chromatin binding, and TOP2B-mediated double strand breaks, but failed to induce AR target gene expression and prostate cancer cell growth. The FLU-mediated arrest in the signaling cascade could be attributed to the inability of FLU to allow association of AR with SMARCD2, a critical component of the BAF chromatin remodeling complex required for androgen induced AR co-activation. Interestingly, the FLU-induced, AR- and TOP2B-mediated double strand breaks could be used to selectively sensitize AR-positive prostate cancer cells to ionizing radiation in vitro and in vivo. These findings support a novel arrested agonist paradigm for selective radiosensitization of prostate cancer cells without inducing AR-mediated pro-growth and survival transcriptional programs.

cancer biology↗

bioRxiv2023

Photoswitchable binders enable temporal dissection of endogenous protein function

General methods for spatiotemporal control of specific endogenous proteins would be broadly useful for probing protein function in living cells. Synthetic protein binders that bind and inhibit endogenous protein targets can be obtained from nanobodies, designed ankyrin repeat proteins (DARPins), and other small protein scaffolds, but generalizable methods to control their binding activity are lacking. Here, we report robust single-chain photoswitchable DARPins (psDARPins) for bidirectional optical control of endogenous proteins. We created topological variants of the DARPin scaffold by computer-aided design so fusion of photodissociable dimeric Dronpa (pdDronpa) results in occlusion of target binding at baseline. Cyan light induces pdDronpa dissociation to expose the binding surface (paratope), while violet light restores pdDronpa dimerization and paratope caging. Since the DARPin redesign leaves the paratope intact, the approach was easily applied to existing DARPins for GFP, ERK, and Ras, as demonstrated by relocalizing GFP-family proteins and inhibiting endogenous ERK and Ras with optical control. Finally, a Ras-targeted psDARPin was used to determine that, following EGF-activation of EGFR, Ras is required for sustained EGFR to ERK signaling. In summary, psDARPins provide a generalizable strategy for precise spatiotemporal dissection of endogenous protein function.

biochemistry↗

bioRxiv2023

MiR-574-5p activates human TLR8 to promote autoimmune signaling and lupus

Endosomal single-stranded RNA-sensing Toll-like receptor-7/8 (TLR7/8) plays a pivotal role in inflammation and immune responses and autoimmune diseases. However, the mechanisms underlying the initiation of the TLR7/8-mediated autoimmune signaling remain to be fully elucidated. Here, we demonstrate that miR-574-5p is aberrantly upregulated in tissues of lupus prone mice and in the plasma of lupus patients, with its expression levels correlating with the disease activity. miR-574-5p binds to and activates human hTLR8 or its murine ortholog mTlr7 to elicit a series of MyD88-dependent immune and inflammatory responses. These responses include the overproduction of cytokines and interferons, the activation of STAT1 signaling and B lymphocytes, and the production of autoantigens. In a transgenic mouse model, the induction of miR-574-5p overexpression is associated with increased secretion of antinuclear and anti-dsDNA antibodies, increased IgG and C3 deposit in the kidney, elevated expression of inflammatory genes in the spleen. In lupus-prone mice, lentivirus-mediated silencing of miR-574-5p significantly ameliorates major symptoms associated with lupus and lupus nephritis. Collectively, these results suggest that the miR-574-5p-hTLR8/mTlr7 signaling is an important axis of immune and inflammatory responses, contributing significantly to the development of lupus and lupus nephritis.

immunology↗

bioRxiv2023

ClusterDE: a post-clustering differential expression (DE) method robust to false-positive inflation caused by double dipping

Post-clustering differential analysis is widely used across omics, including single-cell and spatial transcriptomics, multi-omics, population-scale bulk transcriptomics, and microbiome data. After a clustering algorithm finds clusters based on omics features as putative cell types, spatial domains, or subpopulations, statistical tests are typically applied to the same data to identify differential features as potential markers. Because the features that drive clustering are inherently more likely to appear differential, this clustering-induced bias can yield false-positive markers and mislead the interpretation of clusters as meaningful biological entities, especially when clusters are spurious, resulting in ambiguously defined cell types, spatial domains, or subpopulations. This dual challenge---determining whether clusters themselves are reliable and, if so, identifying their true markers---requires a unified statistical solution. To address this challenge, we propose ClusterDE, a statistical method designed to identify post-clustering differential features (with differentially expressed (DE) genes as a primary example) as reliable markers of cell types, spatial domains, or subpopulations while controlling the false discovery rate (FDR), regardless of clustering quality. The core of ClusterDE involves generating synthetic null data as an in silico negative control representing a single homogeneous group (such as a cell type, spatial domain, or population), allowing for the detection and removal of spurious markers caused by clustering-induced bias. In single-cell and spatial transcriptomics analyses, ClusterDE controls the FDR, prioritizes canonical cell-type and spatial-domain markers among the top discoveries, and de-prioritizes housekeeping genes, and it can refine underlying cell-type hierarchies by merging spurious or over-clustered groups. ClusterDE also mitigates spurious bifurcating trajectories in single-cell analyses that arise from over-clustering and retrospectively evaluates contested cell-type claims in high-profile studies, including a retracted human fetal cerebellum atlas and a challenged COVID-19 developing-neutrophil trajectory. At atlas scale, applying ClusterDE to the Allen Human Middle Temporal Gyrus taxonomy merges fine-grained clusters that are not statistically supported by single-cell transcriptomics, while preserving transcriptomically distinct and spatially supported cell types. Moreover, built-in synthetic null quality checks allow users to experiment with multiple state-of-the-art simulators and retain those that pass the diagnostics for their specific datasets. ClusterDE is compatible with widely used analysis pipelines such as Seurat and Scanpy and supports flexible, data-specific synthetic null generation, enhancing post-clustering inference across diverse omics modalities, with demonstrated efficacy in population-scale bulk transcriptomics and microbiome analyses.

bioinformatics↗

bioRxiv2023

DNA binding analysis of rare variants in homeodomains reveals novel homeodomain specificity-determining residues

Homeodomains (HDs) are the second largest class of DNA binding domains (DBDs) among eukaryotic sequence-specific transcription factors (TFs) and play important roles in regulating development, body patterning, and cellular differentiation. Here, we analyzed 92 human HD mutants, including disease-associated variants and variants of unknown significance (VUSs), for their effects on DNA binding activity. Many of the variants altered DNA binding affinity and/or specificity. Biochemical analysis and structural modeling identified 14 novel specificity-determining positions, 5 of which do not contact DNA. The same missense substitution at analogous positions within different HDs often exhibited different effects on DNA binding. Variant effect prediction tools perform moderately well in distinguishing variants with altered binding affinity, but poorly in identifying those with altered specificity. Our results highlight the need for biochemical assays of TF coding variants and prioritize dozens of variants for further investigations into their pathogenicity and development of clinical diagnostics and precision therapies.

genetics↗

bioRxiv2023

CTCF is essential for proper mitotic spindle structure and anaphase segregation

Mitosis is an essential process in which the duplicated genome is segregated equally into two daughter cells. CTCF has been reported to be present in mitosis but its importance for mitotic fidelity remains to be determined. To evaluate the importance of CTCF in mitosis, we tracked mitotic behaviors in wild type and two different CTCF CRISPR-based genetic knockdowns. We find that knockdown of CTCF results in prolonged mitoses and failed anaphase segregation via time lapse imaging of SiR-DNA. CTCF knockdown did not alter cell cycling or the mitotic checkpoint, which was activated upon nocodazole treatment. Immunofluorescence imaging of the mitotic spindle in CTCF knockdowns revealed disorganization via tri/tetrapolar spindles and chromosomes behind the spindle pole. Imaging of interphase nuclei showed that nuclear size increased drastically, consistent with failure to divide the duplicated genome in anaphase. Population measurements of nuclear shape in CTCF knockdowns do not display decreased circularity or increased nuclear blebbing relative to wild type. However, failed mitoses do display abnormal nuclear morphologies relative to successful mitoses, suggesting population images do not capture individual behaviors. Thus, CTCF is important for both proper metaphase organization and anaphase segregation which impacts the size and shape of the interphase nucleus.

cell biology↗