Biology subjects

Cusanovich, D. A.

Publications and source records attributed to Cusanovich, D. A..

8 recordsLinked to original sources

bioRxiv2024

Cell-based high-content approach for SARS-CoV-2 neutralization identifies unique monoclonal antibodies and PI3K pathway inhibitors.

The sudden rise of the SARS-CoV-2 virus and the delay in the development of effective therapeutics to mitigate it made evident a need for ways to screen for compounds that can block infection and prevent further pathogenesis and spread. Yet, identifying effective drugs efficacious against viral infection and replication with minimal toxicity for the patient can be difficult. Monoclonal antibodies were shown to be effective, yet as the SARS-CoV-2 mutated, these antibodies became ineffective. Small molecule antivirals were identified using pseudovirus constructs to recapitulate infection in non-human cells, such as Vero E6 cells. However, the impact was limited due to poor translation of these compounds in the clinical setting. This is partly due to the lack of similarity of screening platforms to the in vivo physiology of the patient and partly because drugs effective in vitro showed dose-limiting toxicities. In this study, we performed two high-throughput screens in human lung adenocarcinoma cells with authentic SARS-CoV-2 virus to identify both monoclonal antibodies that neutralize the virus and clinically useful kinase inhibitors to block the virus and prioritize minimal host toxicity. Using high-content imaging combined with single-cell and multidimensional analysis, we identified antibodies and kinase inhibitors that reduce virus infection without affecting the host. Our screening technique uncovered novel antibodies and overlooked kinase inhibitors (i.e. PIK3i, mTORi, multiple RTKi) that could be effective against SARS-CoV-2 virus. Further characterization of these molecules will streamline the repurposing of compounds for the treatment of future pandemics and uncover novel mechanisms viruses use to hijack and infect host cells.

pharmacology and toxicology↗

bioRxiv2023

txci-ATAC-seq, a massive-scale single-cell technique to profile chromatin accessibility

Measuring chromatin accessibility is a powerful method to identify cell types and states. Performed at single-cell resolution, this assay has generated catalogs of genome-wide DNA regulatory sites, whole-organism cell atlases, and dynamic chromatin reorganization through development. However, the limited throughput of current single-cell approaches poses a challenge for implementing proper study designs, population-scale profiling, and/or very deep profiling of complex samples. To this end, we developed a 10X-compatible combinatorial indexing ATAC sequencing ("txci-ATAC-seq"), which is a combinatorial indexing framework that initially indexes ("pre-indexes") chromatin within nuclei with barcoded transposases followed by encapsulation and further barcoding using a commercialized droplet-based microfluidics platform (10X Genomics). Leveraging this molecular hashing strategy, we demonstrate that txci-ATAC-seq enables the indexing of up to 200,000 nuclei across multiple samples in a single emulsion reaction, representing a [~]22-fold increase in throughput compared to the standard workflow at the same collision rate. To improve the efficiency of this new technique, we further developed a faster version of the protocol ("Fast-txci-ATAC-seq") that separates sample pre-processing from library generation and has the potential to profile up to 96 samples simultaneously. We initially benchmarked our assay by generating chromatin accessibility profiles for 230,018 cells from five native tissues across three experiments, including human cortex (28,513 cells), mouse brain (48,997 cells), human lung (15,799 cells), mouse lung (73,280 cells), and mouse liver (63,429 cells). We also applied our method to a club cell secretory protein knockout (CC16-/-) mouse model to examine the biological and technical limitations of the mouse line. By characterizing DNA regulatory landscapes in 76,498 wild-type and 77,638 CC16-/- murine lung nuclei, our investigations uncovered previously unappreciated residual genetic deviations from the reference strain that resulted from the method of gene targeting, which employed embryonic stem cells from the 129 strain. We found that these genetic remnants from the 129 strain led to profound cell-type-specific changes in chromatin accessibility in regulatory elements near a host of genes. Collectively, we defined single-cell chromatin signatures in 384,154 nuclei from 13 primary samples across different species, organs, biological replicates, and genetic backgrounds, establishing txci-ATAC-seq as a robust, high-quality, and highly multiplexable single-cell assay for large-scale chromatin studies.

genomics↗

bioRxiv2023

SGRN: A Cas12a-driven Synthetic Gene Regulatory Network System

Gene regulatory networks, which control gene expression patterns in development and in response to stimuli, use regulatory logic modules to coordinate inputs and outputs. One example of a regulatory logic module is the gene regulatory cascade (GRC), where a series of transcription factor genes turn on in order. Synthetic biologists have derived artificial systems that encode regulatory rules, including GRCs. Furthermore, the development of single-cell approaches has enabled the discovery of gene regulatory modules in a variety of experimental settings. However, the tools available for validating these observations remain limited. Based on a synthetic GRC using DNA cutting-defective Cas9 (dCas9), we designed and implemented an alternative synthetic GRC utilizing DNA cutting-defective Cas12a (dCas12a). Comparing the ability of these two systems to express a fluorescent reporter, the dCas9 system was initially more active, while the dCas12a system was more streamlined. Investigating the influence of individual components of the systems identified nuclear localization as a major driver of differences in activity. Improving nuclear localization for the dCas12a system resulted in 1.5-fold more reporter-positive cells and a 15-fold increase in reporter intensity relative to the dCas9 system. We call this optimized system the "Synthetic Gene Regulatory Network" (SGRN, pronounced "sojourn").

synthetic biology↗

bioRxiv2022

Mapping fetal myeloid differentiation in airway samples from premature neonates with single-cell profiling

Single-cell genomic technologies hold great potential to advance our understanding of development and disease. A major limitation lies in isolating intact cells from primary tissues for profiling. Sampling methods compatible with current clinical interventions could enable longitudinal studies, the enrollment of large cohorts, and even the development of novel diagnostics. To explore single-cell RNA-seq (scRNA-seq) profiling of the cell types present at birth in the airway lumen of extremely premature (<28 weeks gestation) neonates, we isolated cells from endotracheal aspirates collected from intubated neonates within the first hour after birth. We generated data on 10 subjects, providing a rich view of airway luminal biology at a critical developmental period. Our results show that cells present in the airways of premature neonates primarily represent a continuum of myeloid differentiation, including fetal monocytes (25% of all cells), intermediate myeloid populations (48% of cells), and macrophages (2.6% of cells). To our knowledge, this is the first single-cell transcriptomic characterization of human monocytes in the neonatal airway isolated within an hour of birth. Applying trajectory analysis to the premature neonate myeloid populations, we identified two trajectories consistent with the developmental stages of interstitial and alveolar macrophages, as well as a third trajectory presenting a potential alternative pathway bridging these terminal macrophage states. While the three trajectories share many dynamic genes (5,451), they also have distinct transcriptional changes (259 alveolar-specific genes, 666 interstitial-specific genes, and 285 bridging-specific genes). Overall, our results define high quality single-cell data from cells isolated within the so-called "golden hour of birth" in extremely premature neonate airways representing complex lung biology and can be utilized in studies of human development and disease.

developmental biology↗

bioRxiv2019

Single cell ATAC-seq in human pancreatic islets and deep learning upscaling of rare cells reveals cell-specific type 2 diabetes regulatory signatures

ObjectiveType 2 diabetes (T2D) is a complex disease characterized by pancreatic islet dysfunction, insulin resistance, and disruption of blood glucose levels. Genome wide association studies (GWAS) have identified >400 independent signals that encode genetic predisposition. More than 90% of the associated single nucleotide polymorphisms (SNPs) localize to non-coding regions and are enriched in chromatin-defined islet enhancer elements, indicating a strong transcriptional regulatory component to disease susceptibility. Pancreatic islets are a mixture of cell types that express distinct hormonal programs, and so each cell type may contribute differentially to the underlying regulatory processes that modulate T2D-associated transcriptional circuits. Existing chromatin profiling methods such as ATAC-seq and DNase-seq, applied to islets in bulk, produce aggregate profiles that mask important cellular and regulatory heterogeneity.\n\nMethodsWe present genome-wide single cell chromatin accessibility profiles in >1,600 cells derived from a human pancreatic islet sample using single-cell-combinatorial-indexing ATAC-seq (sci-ATAC-seq). We also developed a deep learning model based on the U-Net architecture to accurately predict open chromatin peak calls in rare cell populations.\n\nResultsWe show that sci-ATAC-seq profiles allow us to deconvolve alpha, beta, and delta cell populations and identify cell-type-specific regulatory signatures underlying T2D. Particularly, we find that T2D GWAS SNPs are significantly enriched in beta cell-specific and cross cell-type shared islet open chromatin, but not in alpha or delta cell-specific open chromatin. We also demonstrate, using less abundant delta cells, that deep-learning models can improve signal recovery and feature reconstruction of rarer cell populations. Finally, we use co-accessibility measures to nominate the cell-specific target genes at 104 non-coding T2D GWAS signals.\n\nConclusionsCollectively, we identify the islet cell type of action across genetic signals of T2D predisposition and provide higher-resolution mechanistic insights into genetically encoded risk pathways.

genomics↗

bioRxiv2017

The cis-regulatory dynamics of embryonic development at single cell resolution

Single cell measurements of gene expression are providing new insights into lineage commitment, yet the regulatory changes underlying individual cell trajectories remain elusive. Here, we profiled chromatin accessibility in over 20,000 single nuclei across multiple stages of Drosophila embryogenesis. Our data reveal heterogeneity in the regulatory landscape prior to gastrulation that reflects anatomical position, a feature that aligns with future cell fate. During mid embryogenesis, tissue granularity emerges such that cell types can be inferred by their chromatin accessibility, while maintaining a signature of their germ layer of origin. We identify over 30,000 distal elements with tissue-specific accessibility. Using transgenic embryos, we tested the germ layer specificity of a subset of predicted enhancers, achieving near-perfect accuracy. Overall, these data demonstrate the power of shotgun single cell profiling of embryos to resolve dynamic changes in open chromatin during development, and to uncover the cis-regulatory programs of germ layers and cell types.

genomics↗

bioRxiv2017

Comprehensive single cell transcriptional profiling of a multicellular organism by combinatorial indexing

Conventional methods for profiling the molecular content of biological samples fail to resolve heterogeneity that is present at the level of single cells. In the past few years, single cell RNA sequencing has emerged as a powerful strategy for overcoming this challenge. However, its adoption has been limited by a paucity of methods that are at once simple to implement and cost effective to scale massively. Here, we describe a combinatorial indexing strategy to profile the transcriptomes of large numbers of single cells or single nuclei without requiring the physical isolation of each cell (Single cell Combinatorial Indexing RNA-seq or sci-RNA-seq). We show that sci-RNA-seq can be used to efficiently profile the transcriptomes of tens-of-thousands of single cells per experiment, and demonstrate that we can stratify cell types from these data. Key advantages of sci-RNA-seq over contemporary alternatives such as droplet-based single cell RNA-seq include sublinear cost scaling, a reliance on widely available reagents and equipment, the ability to concurrently process many samples within a single workflow, compatibility with methanol fixation of cells, cell capture based on DNA content rather than cell size, and the flexibility to profile either cells or nuclei. As a demonstration of sci-RNA-seq, we profile the transcriptomes of 42,035 single cells from C. elegans at the L2 stage, effectively 50-fold \"shotgun cellular coverage\" of the somatic cell composition of this organism at this stage. We identify 27 distinct cell types, including rare cell types such as the two distal tip cells of the developing gonad, estimate consensus expression profiles and define cell-type specific and selective genes. Given that C. elegans is the only organism with a fully mapped cellular lineage, these data represent a rich resource for future methods aimed at defining cell types and states. They will advance our understanding of developmental biology, and constitute a major step towards a comprehensive, single-cell molecular atlas of a whole animal.

genomics↗

bioRxiv2016

Paired CRISPR/Cas9 guide-RNAs enable high-throughput deletion scanning (ScanDel) of a Mendelian disease locus for functionally critical non-coding elements

The extent to which distal non-coding mutations contribute to Mendelian disease remains a major unknown in human genetics. Given that a genes in vivo function can be appropriately modeled in vitro, CRISPR/Cas9 genome editing enables the large-scale perturbation of distal non-coding regions to identify functional elements in their native context. However, early attempts at such screens have relied on one individual guide RNA (gRNA) per cell, resulting in sparse mutagenesis with minimal redundancy across regions of interest. To address this, we developed a system that uses pairs of gRNAs to program thousands of kilobase-scale deletions that scan across a targeted region in a tiling fashion (\"ScanDel\"). As a proof-of-concept, we applied ScanDel to program 4,342 overlapping 1- and 2- kilobase (Kb) deletions that tile a 206 Kb region centered on HPRT1, the gene underlying Lesch-Nyhan syndrome, with median 27-fold redundancy per base. Programmed deletions were functionally assayed by selecting for loss of HPRT1 function with 6-thioguanine. HPRT1 exons served as positive controls, and all were successfully identified as functionally critical by the screen. Remarkably, HPRT1 function appeared robust to deletion of any intergenic or deeply intronic non-coding region across the 206 Kb locus, indicating that proximal regulatory sequences are sufficient for its expression. A sparser mutagenesis screen of the same 206 Kb with individual gRNAs also failed to identify critical distal regulatory elements. Although our screen did find programmed deletions and individual gRNAs with putative functional consequences that targeted exon-proximal non-coding sequences (e.g. the promoter), long-read sequencing revealed that this signal was driven almost entirely by rare, unexpected deletions that extended into exonic sequence. These targeted validation experiments defined a small region surrounding the transcriptional start site as the only non-coding sequence essential to HPRT1 function. Overall, our results suggest that distal regulatory elements are not critical for HPRT1 expression, and underscore the necessity of comprehensive edited-locus genotyping for validating the results of CRISPR screens. The application of ScanDel to additional loci will enable more insight into the extent to which the disruption of distal non-coding elements contributes to Mendelian diseases. In addition, dense, redundant, large-scale deletion scanning with gRNA pairs will facilitate a deeper understanding of endogenous gene regulation in the human genome.

genomics↗