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Riordan, T.

Publications and source records attributed to Riordan, T..

2 recordsLinked to original sources

SPACE: spatially resolved multiomic analysis for high-throughput CRISPR screening in 3D models

Current spatial CRISPR screening technologies are limited by targeted readouts and high costs, restricting the scope of biological discovery. Here we present SPAtial Cell Exploration (SPACE), a spatial CRISPR screening platform that integrates whole-transcriptome profiling ([~]18,000 genes), multiplexed protein detection ([~]68 markers), and CRISPR perturbation mapping at subcellular resolution. SPACE significantly reduces whole-transcriptome profiling costs compared to sequencing methods while preserving spatial context. We demonstrate SPACE by screening 43 CRISPR knockouts (KOs) across [~]100,000 cells in hundreds of cancer-associated fibroblast (CAF)-tumor spheroids, obtaining whole-transcriptome and multiplexed protein readout from the same exact cells. SPACE revealed previously unknown regulatory mechanisms on tumor extracellular matrix (ECM) remodeling, and identified spatially-resolved ligand-receptor interactions and perturbation-specific spatial gene signatures that are not detectable with dissociation-based methods. This scalable, cost-effective platform provides a transformative framework for high-throughput spatial perturbation studies in complex tissue models.

cell biology↗

Hebb's Vision: The Structural Underpinnings of Hebbian Assemblies

1In 1949, Donald Hebb proposed that groups of neurons that activate stereotypically form the organizational building blocks of perception, cognition, and behavior. Finding the structural underpinning of such assemblies has been technically challenging, due to a lack of large-scale structure-activity maps. Here, we analyze this relation using a novel dataset that links in vivo optical physiology to connectivity using postmortem elec-tron microscopy (EM). From the fluorescence traces, we extract neural assemblies from higher-order correlations in neural activity. Physiologically, we show that these assemblies exhibit properties consistent with Hebbs theory, including more reliable responses to repeated natural movie inputs than size-matched random ensembles and superior decoding of visual stimuli. Structurally, we find that neurons that participate in assemblies are significantly more integrated into the structural network than those that do not. Contrary to Hebbs original prediction, we do not observe a marked increase in the strength of monosynaptic excitatory connections between cells participating in the same assembly. However, we find significantly stronger indirect feed-forward inhibitory connections targeting cells in other assemblies. These results show that assemblies can be useful components of perception, and, surprisingly, they are delineated by mutual inhibition.

neuroscience↗