Biology subjects

Gould, J.

Publications and source records attributed to Gould, J..

18 recordsLinked to original sources

bioRxiv2026

SCALLOPS: a scalable, integrated computational framework for Optical Pooled Screens

Optical pooled screens (OPS) link pooled genetic perturbations to high-dimensional image-based phenotypes at scale, but their widespread adoption is hindered by computational bottlenecks in processing terabyte-scale, multimodal image data. We present SCALLOPS, a unified, modular, and cloud-native computational framework that overcomes these bottlenecks. SCALLOPS implements a "well-centric" processing strategy that integrates robust stitching with a non-linear two-stage registration strategy, enabling accurate alignment of multi-magnification images, reliable single-cell genotype-phenotype linkage, and efficient morphological feature extraction. Benchmarking with public and newly-generated datasets demonstrated SCALLOPS superior performance over existing solutions. Crucially, SCALLOPS uniquely enables robust processing of 4x magnification in situ sequencing data, accelerating image acquisition by around six-fold. We applied SCALLOPS to an optical pooled screen investigating the estrogen receptor (ER) degrader vepdegestrant in a breast cancer cell line, successfully recovering its known mechanism of action, highlighting the value of OPS in translational research. SCALLOPS provides a scalable end-to-end solution, making large-scale OPS routine.

bioinformatics↗

bioRxiv2026

Simultaneous brain-wide single-cell recording resolves spatiotemporal memory architecture

Many fundamental mammalian brain functions emerge from the coordinated activity of cells distributed across large, brain-wide networks. To understand these processes in healthy and diseased states, ideally one would simultaneously measure and analyze single-cell activity at the brain-wide scale, an enduring challenge for live-measurement approaches that often face an inherent tradeoff between spatial resolution and scale. Here, we present GLOBE (sinGle-cell spatiotemporaL recOrding Brain-widE), a technology for brain-wide single-cell recording of cellular activity in vivo with spatiotemporal resolution, physiological sensitivity, and parallelization-accelerated readout. GLOBE leverages genetically encoded intracellular protein tape recorders and a high-throughput computational platform for integrated image and signal analysis. GLOBE records analog signal amplitudes across a continuous time axis, requires only standard light microscopy for in situ readout, and is compatible with expansion microscopy and RNA readouts. We applied GLOBE to simultaneously record transcriptional activity of the immediate early gene Fos in up to 219,703 neurons simultaneously across a single mouse brain over 5.5 continuous days, with a timestamp precision of 3.1-6.7 hours (median absolute error), a local recording density of 69-90% of neurons per imaging field of view, and a post-mortem imaging readout speed of 2.9 seconds per neuron on average. GLOBE resolves the brain-wide spatiotemporal structure of single-cell activity, revealing that Fos transcriptional dynamics associated with fear learning and memory retrieval are distributed across the brain with region-specific temporal heterogeneity, and that the variance of this structure scales down as the number of sampled cells increases. We envision GLOBE to have broad applications for dissecting and decoding physiological and pathological processes at the brain-wide scale.

neuroscience↗

bioRxiv2025

Pathogenic Viruses, Genome Integrations, and Viral::Human Chimeric Transcripts Detected by VirusIntegrationFinder Across >30k Human Tumor and Normal Samples

Viruses are a leading cause of human morbidity and mortality. Certain viruses, including human papillomaviruses (HPVs), play a significant role in the etiology of cancer. Detection of viral DNA insertions in the human genome from next generation sequencing data defines viral associations with cancer and other diseases, identifies impacted organs and tissues, provides insights into disease mechanisms and has the potential to enhance clinical evaluations. In this study, we developed VirusIntegrationFinder (CTAT-VIF), a tool for surveying human genome insertions of various human viruses using both DNA and RNA sequencing data. We applied CTAT-VIF to analyze a dataset of over 30,000 tumor and normal samples, as well as more than 1,000 cancer cell lines. This effort resulted in the compilation of a catalog of over 30,0000 virus-human DNA or RNA junctions at more than 20,000 insertion loci and reassessed viral cancer-insertion hotspots across the human genome. Furthermore, we characterized the functional impacts of insertions with respect to human copy number alterations, effects on the expression of flanking human genes, and the identification of potentially oncogenic chimeric human and human/virus fusion transcripts at insertion loci. In addition to confirming known viral associations with specific tumor types, our study revealed both shared and virus-specific insertion hotspots in addition to variable functional impacts based on virus type. Besides some rare events of interest, we also found evidence for sequencing contamination, which underscores the need for vigilance when studying viral content or genome integrations.

cancer biology↗

bioRxiv2023

Highly multiplexed, image-based pooled screens in primary cells and tissues with PerturbView

Optical pooled screening (OPS) is a highly scalable method for linking image-based phenotypes with cellular perturbations. However, it has thus far been restricted to relatively low-plex phenotypic readouts in cancer cell lines in culture, due to limitations associated with in situ sequencing (ISS) of perturbation barcodes. Here, we developed PerturbView, an OPS technology that leverages in vitro transcription (IVT) to amplify barcodes prior to ISS, enabling screens with highly multiplexed phenotypic readouts across diverse systems, including primary cells and tissues. We demonstrate PerturbView in iPSC-derived neurons, primary immune cells, and tumor tissue sections from animal models. In a screen of immune signaling pathways in primary bone marrow-derived macrophages, PerturbView uncovered both known and novel regulators of NF{kappa}B signaling. Furthermore, we combined PerturbView with spatial transcriptomics in tissue sections from a mouse xenograft model, paving the way to in vivo screens with rich optical and transcriptomic phenotypes. PerturbView broadens the scope of OPS to a wide range of models and applications.

systems biology↗

bioRxiv2023

A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain

The mammalian brain is composed of millions to billions of cells that are organized into numerous cell types with specific spatial distribution patterns and structural and functional properties. An essential step towards understanding brain function is to obtain a parts list, i.e., a catalog of cell types, of the brain. Here, we report a comprehensive and high-resolution transcriptomic and spatial cell type atlas for the whole adult mouse brain. The cell type atlas was created based on the combination of two single-cell-level, whole-brain-scale datasets: a single- cell RNA-sequencing (scRNA-seq) dataset of [~]7 million cells profiled, and a spatially resolved transcriptomic dataset of [~]4.3 million cells using MERFISH. The atlas is hierarchically organized into five nested levels of classification: 7 divisions, 32 classes, 306 subclasses, 1,045 supertypes and 5,200 clusters. We systematically analyzed the neuronal, non-neuronal, and immature neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell type organization in different brain regions, in particular, a dichotomy between the dorsal and ventral parts of the brain: the dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. We also systematically characterized cell-type specific expression of neurotransmitters, neuropeptides, and transcription factors. The study uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types across the brain, suggesting they mediate a myriad of modes of intercellular communications. Finally, we found that transcription factors are major determinants of cell type classification in the adult mouse brain and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole-mouse-brain transcriptomic and spatial cell type atlas establishes a benchmark reference atlas and a foundational resource for deep and integrative investigations of cell type and circuit function, development, and evolution of the mammalian brain.

neuroscience↗

bioRxiv2022

STOmicsDB: a database of Spatial Transcriptomic data

Recent technological development in spatial transcriptomics allows researchers to measure gene expression of cells and their spatial locations at the almost single-cell level, which generates detailed biological insight into biological processes. However, specialized spatial transcriptomics databases are rare. Here, we present the Spatial TranscriptOmics DataBase (STOmicsDB), a user-friendly database with multifunctions including search of relevant publications and tools, public dataset visualization, customized specialized databases, new data archive, and online analysis. The current version of STOmicsDB consists of 141 curated spatial transcript datasets covering 12 species, and includes 5,618 spatial multi-omics publications and 674 tools. STOmicsDB is freely accessible at https://db.cngb.org/stomics/.

genomics↗

bioRxiv2020

Single-nucleus and spatial transcriptomics of archival pancreatic cancer reveals multi-compartment reprogramming after neoadjuvant treatment

Pancreatic ductal adenocarcinoma (PDAC) remains a treatment-refractory disease. Characterizing PDAC by mRNA profiling remains particularly challenging. Previously identified bulk expression subtypes were influenced by contaminating stroma and have not yet informed clinical management, whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for frozen archival PDAC specimens and used it to study both untreated tumors and those that received neoadjuvant chemotherapy and radiotherapy (CRT). Gene expression programs learned across untreated malignant cell and fibroblast profiles uncovered a clinically relevant molecular taxonomy with improved prognostic stratification compared to prior classifications. Moreover, in the increasingly-adopted neoadjuvant treatment context, there was a depletion of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states, which may be more resilient to cytotoxic treatment. Spatially-resolved transcriptomics revealed an association between malignant cells expressing these basal-like programs and higher immune infiltration with increased lymphocytic content, whereas those exhibiting classical-like programs were linked to sparser macrophage-predominant microniches, perhaps pointing to susceptibility to distinct therapeutic strategies. Our refined molecular taxonomy and spatial resolution can help advance precision oncology in PDAC through informative stratification in clinical trials and insights into differential therapeutic targeting leveraging the immune system.

genomics↗

bioRxiv2020

Quality versus quantity: The balance between egg and clutch size among Australian amphibians is related to life history and environmental conditions

An inverse relationship between egg and clutch size has been found repeatedly across animal groups, including birds, reptiles and amphibians, and is considered to be a result of resource limitations and physical constraints on the reproducing female. However, few studies have contextualised this relationship with respect to various environmental selecting pressures and life history traits that have also likely influenced the selection of an optimal egg/clutch size combination, while even fewer have tested these interrelationships using robust natural history datasets. In this study, we aimed to test current hypothesises regarding these relationships on both egg and clutch sizes among the Australian Anurans, which to date have not received this kind of investigation. Specifically, we looked at the influence of environmental selecting pressures (egg laying location, environment persistence and bioregion) and life history traits (adult female body size, egg development type, parental care level, breeding period and temporal breeding pattern). As expected, a clear inverse relationship was found between egg and clutch size, while female body size was positively related to both. Generally speaking, smaller clutches of larger eggs tended to be produced by species that i) oviposit terrestrially, ii) showcase direct development and iii) possess high levels of parental care. Temporal breeding pattern was strongly related to clutch size only, with large clutches occurring in explosive breeding species, while breeding habitat was strongly related to egg size only, with large eggs sizes occurring in terrestrial species. Altogether, these findings indicate that numerous factors have likely influenced the evolution of an optimal clutch type in this group, highlighting the importance of incorporating such variables into animal studies on egg and clutch sizes.

ecology↗

bioRxiv2020

Build me up to break me down: Frothed spawn in the sandpaper frog, Lechriodus fletcheri, is formed by female parents and later broken down by their offspring

Several genera of anuran amphibians deposit their eggs within mucous secretions that have been aerated by the parents to produce a foam or bubble spawn body. This is a dynamic medium for embryo development given that is gradually breaks down over time, and one that has been hypothesised to serve a variety of purposes including protecting embryos from external stresses. In this study, I provide additional details of bubble spawn production in the sandpaper frog, Lechriodus fletcheri. Field and laboratory observations showed that females aerate spawn while in inguinal amplexus, using flanged fingers to transport air bubbles into the mucous. While the frothed spawn is initially resistant to breakup, it gradually loses bubbles and flattens out into a film. This temporal shift in structure is likely to be adaptive, as the resultant increase in surface area allows embryos to come in direct contact with the open water, which may accommodate their increased oxygen demands or facilitate hatching. I provide evidence that this process is controlled by the residing embryos, given that spawn in their absence does not breakdown, highlighting the ability of offspring to modify their immediate environment even before hatching to ensure conditions remain suitable for their changing needs.

zoology↗

bioRxiv2019

Cumulus: a cloud-based data analysis framework for large-scale single-cell and single-nucleus RNA-seq

Massively parallel single-cell and single-nucleus RNA-seq (sc/snRNA-seq) have opened the way to systematic tissue atlases in health and disease, but as the scale of data generation is growing, so does the need for computational pipelines for scaled analysis. Here, we developed Cumulus, a cloud-based framework for analyzing large scale sc/snRNA-seq datasets. Cumulus combines the power of cloud computing with improvements in algorithm implementations to achieve high scalability, low cost, user-friendliness, and integrated support for a comprehensive set of features. We benchmark Cumulus on the Human Cell Atlas Census of Immune Cells dataset of bone marrow cells and show that it substantially improves efficiency over conventional frameworks, while maintaining or improving the quality of results, enabling large-scale studies.

bioinformatics↗

bioRxiv2019

A single-cell and single-nucleus RNA-seq toolbox for fresh and frozen human tumors

Single cell genomics is essential to chart the complex tumor ecosystem. While single cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumor tissues, single nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each strategy requires modifications to fit the unique characteristics of different tissue and tumor types, posing a barrier to adoption. Here, we developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We tested eight tumor types of varying tissue and sample characteristics (resection, biopsy, ascites, and orthotopic patient-derived xenograft): lung cancer, metastatic breast cancer, ovarian cancer, melanoma, neuroblastoma, pediatric sarcoma, glioblastoma, pediatric high-grade glioma, and chronic lymphocytic leukemia. Analyzing 212,498 cells and nuclei from 39 clinical samples, we evaluated protocols by cell quality, recovery rate, and cellular composition. We optimized protocols for fresh tissue dissociation for different tumor types using a decision tree to account for the technical and biological variation between clinical samples. We established methods for nucleus isolation from OCT embedded and fresh-frozen tissues, with an optimization matrix varying mechanical force, buffer, and detergent. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types and intrinsic expression profiles, but at different proportions. Our work provides direct guidance across a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

genomics↗

bioRxiv2019

Diving beetle offspring oviposited in amphibian spawn prey on the tadpoles upon hatching

In highly ephemeral freshwater habitats, predatory vertebrates are typically unable to become established, leaving an open niche often filled by macroinvertebrate predators. However, these predators are faced with the challenge of finding sufficient food sources as the rapid rate of desiccation prevents the establishment of extended food chains and limits the number of prey species present. It could therefore be advantageous for adults to oviposit their offspring in the presence of future prey within sites of extreme ephemerality. We report the first case of adult diving beetles ovipositing their eggs within spawn of the sandpaper frog, Lechriodus fletcheri. This behaviour was found among several pools used by L. fletcheri for reproduction. Beetle eggs oviposited in frog spawn were found to hatch within 24 hours of the surrounding L. fletcheri eggs, with the larvae becoming voracious consumers of the hatched tadpoles. Although it has yet to be established experimentally whether this is an adaptive behaviour, the laying of eggs among potential future tadpole prey in this instance should confer significant fitness benefits for the offspring upon hatching, ensuring that they are provided an immediate source of food at the start of their development and potentially throughout. This oviposition behaviour may be common among diving beetles and could form a significant predatory threat for amphibians with a free-swimming larval stage in ephemeral freshwater habitats.

zoology↗

bioRxiv2019

High-density spatial transcriptomics arrays for in situ tissue profiling

Tissue function relies on the precise spatial organization of cells characterized by distinct molecular profiles. Single-cell RNA-Seq captures molecular profiles but not spatial organization. Conversely, spatial profiling assays either lack global transcriptome information or are not at the single-cell level. Here, we develop High-Density Spatial Transcriptomics (HDST), a method for RNA-seq at high spatial resolution. Spatially barcoded reverse transcription oligonucleotides are coupled to beads that are then randomly deposited in individual wells on a slide. The barcoded beads are decoded and coupled to a specific spatial address. We then capture and spatially in situ label RNA from the same histological tissue sections placed on the bead array slide. HDST recovers hundreds of thousands of transcript-coupled barcodes per experiment at 2 m resolution. We demonstrate HDST in the mouse brain, use it to resolve spatial expression patterns and cell types, and show how to combine it with histological stains to relate expression patterns to tissue architecture and anatomy. HDST opens the way to 2D spatial analysis of tissues at high resolution.

genomics↗

bioRxiv2019

Adhesive defence mucus secretions in the red triangle slug (Triboniophorus graeffei) can incapacitate adult frogs

Gastropods are known to secrete mucus for a variety of purposes, including locomotion, reproduction, adhesion to surfaces, and lubrication. A less commonly known function of mucus secretion in this group involves its use as a defence against predation. Among the terrestrial slugs, mucus that serves this particular purpose has been studied for only a handful of species under laboratory conditions, where it is thought to be produced for self-fouling or to make individuals difficult to consume. However, the mechanisms of how these defensive secretions operate and their effectiveness in deterring predation in the natural world have not be described in much detail. In this study, we provide evidence of adhesive mucus secretions in the red triangle slug (Triboniophorus graeffei) as an adaptation against predation. Field observations of a large red-eyed green tree frog (Litoria chloris) trapped in the mucus secretions of a nearby T. graeffei revealed that this mucus serves to incapacitate predators rather than just simply as an overall deterrence. Mechanical stimulation of T. graeffei under laboratory conditions revealed that adhesive secretions were produced from discrete sections of the dorsal surface when disturbed, leading to the production of a highly sticky and elastic mucus that was unlike the thin and slippery mucus used during locomotion. The adhesiveness of the defensive secretions was strengthened and reactivated when in contact with water. This appears to not only be the first description of defensive mucus production in this slug species but one of the first natural observations of the use of adhesive defence secretions to incapacitate a predator. The biomechanical properties of this mucus and its ability to maintain and strengthen its hold under wet conditions make it potentially useful in the development of new adhesive materials.

animal behavior and cognition↗

bioRxiv2019

scSVA: an interactive tool for big data visualization and exploration in single-cell omics

We present scSVA (single-cell Scalable Visualization and Analytics), a lightweight R package for interactive two- and three-dimensional visualization and exploration of massive single-cell omics data. Building in part of methods originally developed for astronomy datasets, scSVA is memory efficient for more than hundreds of millions of cells, can be run locally or in a cloud, and generates high-quality figures. In particular, we introduce a numerically efficient method for single-cell data embedding in 3D which combines an optimized implementation of diffusion maps with a 3D force-directed layout, enabling generation of 3D data visualizations at the scale of a million cells. To facilitate reproducible research, scSVA supports interactive analytics in a cloud with containerized tools. scSVA is available online at https://github.com/klarman-cell-observatory/scSVA.

bioinformatics↗

bioRxiv2017

The GCTx format and cmap{Py, R, M} packages: resources for the optimized storage and integrated traversal of dense matrices of data and annotations

MotivationComputational analysis of datasets generated by treating cells with pharmacological and genetic perturbagens has proven useful for the discovery of functional relationships. Facilitated by technological improvements, perturbational datasets have grown in recent years to include millions of experiments. While initial studies, such as our work on Connectivity Map, used gene expression readouts, recent studies from the NIH LINCS consortium have expanded to a more diverse set of molecular readouts, including proteomic and cell morphological signatures. Sharing these diverse data creates many opportunities for research and discovery, but the unprecedented size of data generated and the complex metadata associated with experiments have also created fundamental technical challenges regarding data storage and cross-assay integration.\n\nResultsWe present the GCTx file format and a suite of open-source packages for the efficient storage, serialization, and analysis of dense two-dimensional matrices. The utility of this format is not just theoretical; we have extensively used the format in the Connectivity Map to assemble and share massive data sets comprising 1.7 million experiments. We anticipate that the generalizability of the GCTx format, paired with code libraries that we provide, will stimulate wider adoption and lower barriers for integrated cross-assay analysis and algorithm development.\n\nAvailabilitySoftware packages (available in Matlab, Python, and R) are freely available at https://github.com/cmap\n\nSupplementary informationSupplementary information is available at clue.io/code.\n\nContactoana@broadinstitute.org

bioinformatics↗

bioRxiv2017

A Library of Phosphoproteomic and Chromatin Signatures for Characterizing Cellular Responses to Drug Perturbations

Though the added value of proteomic measurements to gene expression profiling has been demonstrated, profiling of gene expression on its own remains the dominant means of understanding cellular responses to perturbation. Direct protein measurements are typically limited due to issues of cost and scale; however, the recent development of high-throughput, targeted sentinel mass spectrometry assays provides an opportunity for proteomics to contribute at a meaningful scale in high-value areas for drug development. To demonstrate the feasibility of a systematic and comprehensive library of perturbational proteomic signatures, we profiled 90 drugs (in triplicate) in six cell lines using two different proteomic assays -- one measuring global changes of epigenetic marks on histone proteins and another measuring a set of peptides reporting on the phosphoproteome -- for a total of more than 3,400 samples. This effort represents a first-of-its-kind resource for proteomics. The majority of tested drugs generated reproducible responses in both phosphosignaling and chromatin states, but we observed differences in the responses that were cell line-and assay-specific. We formalized the process of comparing response signatures within the data using a concept called connectivity, which enabled us to integrate data across cell types and assays. Furthermore, it facilitated incorporation of transcriptional signatures. Consistent connectivity among cell types revealed cellular responses that transcended cell-specific effects, while consistent connectivity among assays revealed unexpected associations between drugs that were confirmed by experimental follow-up. We further demonstrated how the resource could be leveraged against public domain external datasets to recognize therapeutic hypotheses that are consistent with ongoing clinical trials for the treatment of multiple myeloma and acute lymphocytic leukemia (ALL). These data are available for download via the Gene Expression Omnibus (accession GSE101406), and web apps for interacting with this resource are available at https://clue.io/proteomics.\n\nHighlightsO_LIFirst-of-its-kind public resource of proteomic responses to systematically administered perturbagens\nC_LIO_LIDirect proteomic profiling of phosphosignaling and chromatin states in cells for 90 drugs in six different cell lines\nC_LIO_LIExtends Connectivity Map concept to proteomic data for integration with transcriptional data\nC_LIO_LIEnables recognition of unexpected, cell type-specific activities and potential translational therapeutic opportunities\nC_LI

systems biology↗

bioRxiv2017

A Next Generation Connectivity Map: L1000 Platform And The First 1,000,000 Profiles

We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io.\n\nHIGHLIGHTSO_LIA new gene expression profiling method, L1000, dramatically lowers cost\nC_LIO_LIThe Connectivity Map database now includes 1.3 million publicly accessible L1000 perturbational profiles\nC_LIO_LIThis expanded Connectivity Map facilitates discovery of small molecule mechanism of action and functional annotation of genetic variants\nC_LIO_LIThe work establishes feasibility and utility of a truly comprehensive Connectivity Map\nC_LI

genomics↗