Biology subjects

Sprague, D.

Publications and source records attributed to Sprague, D..

6 recordsLinked to original sources

bioRxiv2026

G protein-coupled receptor SmGPCR9 interacts with neuropeptides and controls spermatogenesis in Schistosoma mansoni

Schistosomiasis is a neglected tropical disease caused by parasitic flatworms of the genus Schistosoma, impacting hundreds of millions of people and animals globally. Disease pathology primarily originates from host immune responses to parasite eggs, which are produced only when female schistosomes are continuously paired with males. Past research focused on pairing-dependent female sexual maturation, while scarce data exist for the males reproductive biology. In this study, we characterized the G protein-coupled receptor Smgpcr9 (Smp_244240), an orphan Class A (Rhodopsin-like) GPCR with a testis-preferential and pairing-influenced expression profile in S. mansoni males. Previous bulk RNA-seq analyses of adult worms and their isolated gonads revealed that Smgpcr9 belongs to a subgroup of GPCR genes with abundant testis-preferential and pairing-influenced transcript levels in males but low and extremely low expression in unpaired and paired females, respectively. This male-/unpaired female-biased expression pattern mirrors that of neuropeptide (npp) genes of S. mansoni such as Smnpp26 and Smnpp41. In a deorphanization approach using yeast-two-hybrid analyses, GPCR internalization experiments, bioluminescence resonance energy transfer assays, and by modeling and docking analyses, we provide first evidence that both NPPs can interact with SmGPCR9. Furthermore, we optimized a GPCR RNAi approach and achieved efficient transcript knockdown (> 90%) enabling robust functional characterization of Smgpcr9. Following RNAi, physiological and morphological analyses revealed that SmGPCR9 regulates key aspects of male reproductive biology like testis morphology and spermatogenesis. Remarkably, ovary structure and egg production were also affected in paired females post RNAi. We observed similar phenotypes plus motility constraints and reduced stem-cell proliferation in both sexes upon RNAi of Smnpp26 and Smnpp41. In all cases, RNAi downstream analyses by RT-qPCR of marker genes substantiated the observed phenotypic effects. These results strongly indicate the importance of SmGPCR9, SmNPP26, and SmNPP41 for spermatogenesis and further physiological processes in male and female S. mansoni. Author SummaryResearch of the reproductive biology of schistosomes focused mainly on females so far, which upon pairing sexually mature to produce eggs that are important for the life cycle maintenance but also for the pathogenesis of schistosomiasis, the infectious disease caused by these parasites. We investigated a yet unknown G protein-coupled receptor, Smgpcr9, which showed a testis-preferential and pairing-influenced expression profile in Schistosoma mansoni males. To this end, we optimized an RNA interference (RNAi) approach for knockdown analysis, identified neuropeptides (NPPs) as potential ligands by different biochemical approaches and modeling and docking analyses, and we investigated the roles of SmGPCR9 and two interacting NPPs, SmNPP26 and SmNPP41, by physiological, microscopical, and molecular techniques. Our results strongly suggest that SmGPCR9 and both NPPs regulate spermatogenesis. Furthermore, we detected effects on ovary morphology, egg production, and stem-cell proliferation of paired females post RNAi. Taken together, we deorphanized SmGPCR9 and showed for the first time the essential role of a so far uncharacterized GPCR and two interacting neuropeptides for spermatogenesis. Our results shed first light on spermatogenesis regulatory processes controlled by GPCRs and neuropeptides in male S. mansoni and thus expand our understanding of the roles of GPCR-NPP signaling for schistosome reproductive biology.

molecular biology↗

bioRxiv2025

WormID-Benchmark: Extracting Whole-Brain Neural Dynamics of C. elegans At the Neuron Resolution

The nematode C. elegans is a premier model organism for studying neural circuit function due to its fully mapped connectome and genetically identifiable neurons. Recent advances in 3D light microscopy and fluorescent protein tagging have enabled whole-brain imaging at single-neuron resolution. However, extracting meaningful neural dynamics from these high-resolution recordings requires addressing three fundamental challenges: (i) accurate detection of individual neurons in fluorescence images, (ii) precise identification of neuron classes based on anatomical and colorimetric cues, and (iii) robust tracking of neurons over time in calcium imaging videos. To systematically evaluate these challenges, we introduce WormID-Bench, a large-scale, multi-laboratory dataset comprising 118 worms from five distinct research groups, along with standardized evaluation metrics for detection, identification, and tracking. Our benchmark reveals that existing computational approaches show substantial room for improvement in sensitivity, specificity, and generalization across diverse experimental conditions. By providing an open and reproducible benchmarking framework1, WormID-Bench aims to accelerate the development of high-throughput and scalable computational tools for whole-brain neural dynamics extraction in C. elegans, setting the stage for broader advancements in functional connectomics.

neuroscience↗

bioRxiv2024

A novel HLA Class II presentation prediction algorithm deciphers immunogenic CD4 epitopes specific to KRAS G12C

Accurate prediction of peptide presentation by HLA molecules is important for generation of effective individualized cancer vaccines and immunotherapies. While presentation prediction algorithms for HLA class I have been successfully applied in the context of such therapies, improved prediction algorithms for class II are needed. EDGE-II is a novel algorithm based on a protein large language model that has a learned allele deconvolution network trained on existing and new immunopeptidomics data. It delivers state-of-the-art performance on prediction of peptide presentation by HLA class II and immunogenicity elicited by CD4+ T-cell epitopes. In a patient with a KRAS G12C positive tumor treated with a KRAS G12C targeting immunotherapy, EDGE-II identified KRAS G12C class II neoantigens that elicited clonally expanded CD4+ T cells with cytotoxic transcriptional profiles post-vaccination. EDGE-II could play an important role in the development of effective cancer immunotherapies by elucidating an enriched understanding of the immunopeptidome.

bioinformatics↗

bioRxiv2021

Sex dependent glial-specific changes in the chromatin accessibility landscape in late-onset Alzheimer's disease brains

In the post-GWAS era, there is an unmet need to decode the underpinning genetic etiologies of late-onset Alzheimers disease (LOAD) and translate the associations to causation. Toward that goal, we conducted ATAC-seq profiling using neuronal nuclear protein (NeuN) sorted-nuclei from 40 frozen brain tissues to determine LOAD-specific changes in chromatin accessibility landscape in a cell-type specific manner. We identified 211 LOAD-specific differential chromatin accessibility sites in neuronal-nuclei, four of which overlapped with LOAD-GWAS regions ({+/-}100kb of SNP). While the non-neuronal nuclei did not show LOAD-specific differences, stratification by sex identified 842 LOAD-specific chromatin accessibility sites in females. Seven of these sex-dependent sites in the non-neuronal samples overlapped LOAD-GWAS regions including APOE. LOAD loci were functionally validated using single-nuclei RNA-seq datasets. In conclusion, using brain sorted-nuclei enabled the identification of sex-dependent cell type-specific LOAD alterations in chromatin structure. These findings enhance the interpretation of LOAD-GWAS discoveries, provide potential pathomechanisms, and suggest novel LOAD-loci. Furthermore, our results convey mechanistic insights into sex differences in LOAD risk and clinicopathology. GRAPHICAL ABSTRACT O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

neuroscience↗

bioRxiv2021

improv: A flexible software platform for adaptive neuroscience experiments

Current neuroscience research is often limited to testing predetermined hypotheses and post hoc analysis of already collected data. Adaptive experimental designs, in which modeling drives ongoing data collection and selects experimental manipulations, offer a promising alternative. Still, tight integration between models and data collection requires coordinating diverse hardware configurations and complex computations under real-time constraints. Here, we introduce improv, a software platform that allows users to fully integrate custom modeling, analysis, and visualization with data collection and experimental control. We demonstrate both in silico and in vivo how improv enables more efficient experimental designs for discovery and validation across various model organisms and data types. Improv can orchestrate custom real-time behavioral analyses, rapid functional typing of neural responses from large populations via calcium microscopy, and optimal visual stimulus selection. We incorporate real-time machine learning methods for dimension reduction and predictive modeling of latent neural and behavioral features. Finally, we demonstrate how improv can perform model-driven interactive imaging and simultaneous optogenetic photostimulation of visually responsive neurons in the larval zebrafish brain expressing GCaMP6s and the red-shifted opsin rsChRmine. Together, these results demonstrate the power of improv to integrate modeling with data collection and experimental control to achieve next-generation adaptive experiments.

neuroscience↗

bioRxiv2019

Non-linear sequence similarity between the Xist and Rsx long noncoding RNAs suggests shared functions of tandem repeat domains

The marsupial inactive X chromosome expresses a long noncoding RNA (lncRNA) called Rsx that has been proposed to be the functional analogue of eutherian Xist. Despite the possibility that Xist and Rsx encode related functions, the two lncRNAs harbor no linear sequence similarity. However, both lncRNAs harbor domains of tandemly repeated sequence. In Xist, these repeat domains are known to be critical for function. Using k-mer based comparison, we show that the repeat domains of Xist and Rsx unexpectedly partition into two major clusters that each harbor substantial levels of non-linear sequence similarity. Xist Repeats B, C and D were most similar to each other and to Rsx Repeat 1, whereas Xist Repeats A and E were most similar to each other and to Rsx Repeats 2, 3, and 4. Similarities at the level of k-mers corresponded to domain-specific enrichment of protein-binding motifs. Within individual domains, protein-binding motifs were often enriched to extreme levels. Our data support the hypothesis that Xist and Rsx encode similar functions through different spatial arrangements of functionally analogous protein-binding domains. We propose that the two clusters of repeat domains in Xist and Rsx function in part to cooperatively recruit PRC1 and PRC2 to chromatin. The physical manner in which these domains engage with protein cofactors may be just as critical to the function of the domains as the protein cofactors themselves. The general approaches we outline in this report should prove useful in the study of any set of RNAs.

genetics↗