Biology subjects

Schaffer, D.

Publications and source records attributed to Schaffer, D..

4 recordsLinked to original sources

bioRxiv2026

Expression-linked promoter selection (ELiPS) engineers short, strong ubiquitous promoters for gene therapy applications

Adeno-associated virus (AAV)-based gene therapy has made steady progress towards efficient delivery to numerous target cell populations, yet the viruss 5 kb packaging limit remains a challenge for effective and in some cases cell-selective cargo expression. Here, we introduce Expression-Linked Promoter Selection (ELiPS), a high-throughput platform for generating and functionally screening >106 engineered, short promoter variants using an AAV expression platform. ELiPS relies on a Golden Gate cloning method to build random oligomers of selected transcription factor binding sites (TFBSs) upstream of a minimal promoter, GFP, and a unique 3 barcode. As a proof of concept, to engineer short ([~]250 bp), synthetic, ubiquitous promoters, we applied ELiPS to build two libraries composed of TFBSs for ubiquitously expressed transcription factors (TFs) and screened them via AAV-mediated transduction in vitro. This strategy identified promoters with expression surpassing human cytomegalovirus (CMV) and CAG in vitro, and one variant was capable of driving therapeutic expression of B-domain-deleted Factor VIII (BDDFVIII) in vivo at levels comparable to a liver-specific promoter benchmark. ELiPS thus establishes a scalable framework for promoter discovery, enabling the design of compact, ubiquitous or cell-selective expression cassettes that enable further precision and efficacy in AAV-based gene therapies.

bioengineering↗

bioRxiv2026

Fine-mapping candidate neuropsychiatric regulatory variants using cell type-aware comparative genomics

AbstractMeasures of nucleotide sequence conservation across species are useful for identifying functional genomic loci, but can fail when regulatory function is maintained, often in a cell type-specific manner, even when sequence is not. We introduce CTACIT, the Cell Type-Aware Conservation Inference Toolkit, to identify trait-associated regulatory variants. CTACIT integrates sequence conservation scores with cell type-specific open chromatin data collected from a few mammalian species to impute function for hundreds more. Applying CTACIT to neuropsychiatric trait loci identifies higher heritability enrichment and more fine-mapped variants than nucleotide conservation and human chromatin data alone. Our in vivo reporter assays validate predictions for enhancers with risk variants near the DRD2 schizophrenia risk locus. By integrating genome conservation and multi-species open chromatin data, CTACIT prioritizes variants within regions of conserved regulatory function for in vivo characterization and addresses a major challenge in translating disease associations to mechanistic understanding. One-Sentence SummaryRegulatory functions conserved across mammals underlying caudate cell type evolution reveal functions of human risk variants.

genomics↗

bioRxiv2022

Synaptic scale dopamine disruption in Huntington's Disease model mice imaged with near infrared catecholamine nanosensors

Dopamine neuromodulation is a critical process that facilitates learning, motivation, and motor control. Disruption of these processes has been implicated in several neurological and psychiatric disorders including Huntingtons Disease (HD). While several treatments for physical and psychiatric HD symptoms target dopaminergic neuromodulation, the mechanism by which dopaminergic dysfunction occurs during HD is unknown. This is partly due to limited capability to visualize dopamine dynamics at the spatiotemporal resolution of both neuromodulator release (ms) and dopaminergic boutons ({micro}m). Here we employ near-infrared fluorescent catecholamine nanosensors (nIRCats) to image dopamine release within the brain striatum of R6/2 Huntingtons Disease Model (R6/2) mice. We find that stimulated dorsal striatal dopamine release decreases with progressive motor degeneration and that these decreases are primarily driven by a decrease in the number of dopamine hotspots combined with decreased release intensity and decreased release fidelity. Using nIRCats high spatial resolution, we show that dopamine hotspots in late HD show increased ability to add new dopamine hotspots at high extracellular calcium concentrations and track individual dopamine hotspots over repeated stimulations and pharmacological wash to measure dopamine hotspots release fidelity. Compellingly, we demonstrate that antagonism of D2-autoreceptors using Sulpiride and direct blocking of Kv1.2 channels using 4-Aminopyradine (4-AP) increases the fidelity of dopamine hotspot activity in WT striatum but not in late HD striatum, indicating that D2-autoreceptor regulation of dopamine release through Kv1.2 channels is compromised in late HD. These findings, enabled by nIRCats, provide a more detailed look into how dopamine release is disrupted and dysregulated during Huntingtons Disease to alter the coverage of dopamine modulation across the dorsal striatum. SIGNIFICANCE STATEMENTHuntingtons Disease (HD) is a neurodegenerative disorder with no cure. Dysfunction of dopamine signaling is known to deteriorate in HD but has not been studied at the spatial level of individual release sites. Here, we image dopamine release from individual hotspots in brain slices from R6/2 HD mice at early and late disease timepoints with dopamine nanosensors. We track single dopamine hotspots and find that dopamine hotspot number, release intensity, and release fidelity decrease in HD, and demonstrate that changes in D2-autoreceptor regulation manifest through changes in hotspot release fidelity thus compromising dopamine coverage across the dorsal lateral striatum. These findings highlight dopaminergic neurons in cortico-striatal signaling during HD as a promising new therapeutic target for HD treatment.

neuroscience↗

bioRxiv2021

The Functional Order (FunOrder) tool - Identification of essential biosynthetic genes through computational molecular co-evolution

Secondary metabolites (SMs) are a vast group of compounds with different structures and properties. Humankind uses SMs as drugs, food additives, dyes, and as monomers for novel plastics. In many cases, the biosynthesis of SMs is catalysed by enzymes whose corresponding genes are co-localized in the genome in biosynthetic gene clusters (BGCs). Notably, BGCs may contain so-called gap genes, that are not involved in the biosynthesis of the SM. Current genome mining tools can identify BGCs but they have problems with distinguishing essential genes from gap genes and defining the borders of a BGC. This can and must be done by expensive, laborious, and time-consuming comparative genomic approaches or co-expression analyses. In this study, we developed a novel tool that allows automated identification of essential genes in a BGC based solely on genomic data. The Functional Order (FunOrder) tool - Identification of essential biosynthetic genes through computational molecular co-evolution - searches for co-evolutionary linked genes in the BGCs. In light of the growing number of genomic data available, this will contribute to the studies of BGCs in native hosts and facilitate heterologous expression in other organisms with the aim of the discovery of novel SMs, including antibiotics and other pharmaceuticals.

bioinformatics↗