Biology subjects

Scuderi, G. J.

Publications and source records attributed to Scuderi, G. J..

3 recordsLinked to original sources

bioRxiv2025

Multiscale Spatial Mapping of Microbial Communities for Biotherapeutic Development

Live biotherapeutic products (LBPs) are emerging as powerful tools to modulate the microbiome using well-defined microbial communities. Yet, designing, manufacturing, and delivering LBPs remains challenging, in part due to a lack of technologies capable of analyzing LBPs as complete, spatially organized consortia. Conventional sequencing-based methods lack sensitivity and specificity and do not provide critical spatial information. To address this, we present high-phylogenetic-resolution spatial mapping platform (HiPR-Map), a state-of-the-art spectral imaging technology that enables precise enumeration and spatial localization of microbial cells at species-level within complex communities. Through these advantages, HiPR-Map provides unique insights for LBP discovery and development. Applying HiPR-Map to an LBP designed to complement immune checkpoint therapy, we profiled over 1.8 million microbial cells engrafted in the murine gut. Our analysis revealed distinctive microbial spatial organization, underscoring the power of imaging-based microbiome profiling to optimize LBP design and characterization. This work highlights the transformative potential of spatial microbiome analysis for next-generation LBP development.

microbiology↗

bioRxiv2020

Uncovering Transcriptional Dark Matter via Gene Annotation Independent Single-Cell RNA Sequencing Analysis

Single-cell RNA sequencing (scRNA-seq) enables the study of cell biology with high resolution. scRNA-seq expression analyses rely on the availability of a high quality annotation of genes in the genome. Yet, as we show here with scRNA-seq experiments and analyses spanning human, mouse, chicken, mole rat, lemur and sea urchin, gene annotations often fail to cover the full transcriptome of every cell type at every stage of development, in particular for organisms that are not routinely studied. To overcome this hurdle, we created a scRNA-seq analysis routine that recovers biologically relevant information beyond the scope of the best available gene annotation. This is achieved by performing single-cell expression analysis on any region in the genome for which transcriptional products are detected. Our routine identifies transcriptionally active regions (TARs) using a hidden Markov model, generates a matrix of expression levels for all TARs across all cells in a dataset, performs single-cell TAR expression analysis to identify TARs that are biologically significant, and then annotates biologically significant TARs using gene homology analysis. This procedure leverages single-cell expression analyses as a filter to direct annotation efforts to biologically significant transcripts in complex tissues and thereby uncovers biology to which scRNA-seq would otherwise be in the dark.

bioinformatics↗

bioRxiv2020

Spatiotemporal single-cell RNA sequencing of developing hearts reveals interplay between cellular differentiation and morphogenesis

Single-cell RNA sequencing is a powerful tool to study developmental biology but does not preserve spatial information about cellular interactions and tissue morphology. Here, we combined single-cell and spatial transcriptomics with new algorithms for data integration to study the early development of the chicken heart. We collected data from four key ventricular development stages, ranging from the early chamber formation stage to the late four-chambered stage. We created an atlas of the diverse cellular lineages in developing hearts, their spatial organization, and their interactions during development. Spatial mapping of differentiation transitions revealed the intricate interplay between cellular differentiation and morphogenesis in cardiac cellular lineages. Using spatially resolved expression analysis, we identified anatomically restricted gene expression programs. Last, we discovered a stage-dependent role for the small secreted peptide, thymosin beta-4, in the coordination of multi-lineage cellular populations. Overall, our study identifies key stage-specific regulatory programs that govern cardiac development.

genomics↗