Farah Mhamedi

Abstract It is estimated that only 0.02% of disseminated tumour cells are able to seed overt metastases 1 . While this suggests the presence of environmental constraints to metastatic seeding, the landscape of host factors controlling this process remains largely unclear. Here, combining transposon technology 2 and fluorescence niche labelling 3 , we developed an in vivo CRISPR activation screen to systematically investigate the interactions between hepatocytes and metastatic cells. We identify plexin B2 as a critical host-derived regulator of liver colonization in colorectal and pancreatic cancer and melanoma syngeneic mouse models. We dissect a mechanism through which plexin B2 interacts with class IV semaphorins on tumour cells, leading to KLF4 upregulation and thereby promoting the acquisition of epithelial traits. Our results highlight the essential role of signals from the liver parenchyma for the seeding of disseminated tumour cells before the establishment of a growth-promoting niche. Our findings further suggest that epithelialization is required for the adaptation of CRC metastases to their new tissue environment. Blocking the plexin-B2–semaphorin axis abolishes metastatic colonization of the liver and therefore represents a therapeutic strategy for the prevention of hepatic metastases. Finally, our screening approach, which evaluates host-derived extrinsic signals rather than tumour-intrinsic factors for their ability to promote metastatic seeding, is broadly applicable and lays a framework for the screening of environmental constraints to metastasis in other organs and cancer types.

Asymmetric subcellular mRNA localization allows spatial regulation of gene expression and functional compartmentalization. In neurons, localization of specific mRNAs to neurites is essential for cellular functioning. However, it is largely unknown how transcript sorting works in a sequence-specific manner. Here, we combined subcellular transcriptomics and massively parallel reporter assays and tested ∼50 000 sequences for their ability to localize to neurites. Mapping the localization potential of >300 genes revealed two ways neurite targeting can be achieved: focused localization motifs and broadly encoded localization potential. We characterized the interplay between RNA stability and localization and identified motifs able to bias localization towards neurite or soma as well as the trans-acting factors required for their action. Based on our data, we devised machine learning models that were able to predict the localization behavior of novel reporter sequences. Testing this predictor on native mRNA sequencing data showed good agreement between predicted and observed localization potential, suggesting that the rules uncovered by our MPRA also apply to the localization of native full-length transcripts.

Abstract Asymmetric subcellular localization of mRNA is a common cellular phenomenon that is thought to contribute to spatial gene regulation. In highly polar neurons, subcellular transcript localization and translation are thought to enhance cellular efficiency and timely responses to external cues. Although mRNA localization has been observed in many tissues and numerous examples of the functional importance of this process exist, we still lack a systematic understanding of how the transcript sorting machinery works in a sequence-specific manner. Here, we addressed these gaps by combining subcellular transcriptomics and rationally designed sequence libraries. We developed a massively parallel reporter assay (MPRA) for mRNA localization and tested ~50,000 sequences for their ability to drive RNA localization to neurites of neuronal cell lines. By scanning the 3’UTR of >300 genes we identified many previously unknown localization regions and mapped the localization potential of endogenous sequences. Our data suggest two ways the localization potential can be encoded in the 3’UTR: focused localization motifs and broadly encoded localization potential based on small contributions. We identified sequence motifs enriched in dendritically localized transcripts and tested the potential of these motifs to affect the localization behavior of an mRNA. This assay revealed sequence elements with the ability to bias localization towards neurite as well as soma. Depletion of RNA binding proteins predicted or experimentally shown to bind these motifs abolished the effect on localization, suggesting that these motifs act by recruiting specific RNA-binding proteins. Based on our dataset we developed machine learning models that accurately predict the localization behavior of novel sequences. Testing this predictor on native mRNA sequencing data showed good agreement between predicted and observed localization potential, suggesting that the rules uncovered by our MPRA also apply to the localization of native transcripts. Applying similar systematic high-throughput approaches to other cell types will open the door for a comparative perspective on RNA localization across tissues and reveal the commonalities and differences of this crucial regulatory mechanism.

BACKGROUND: Subcellular RNA localization is crucial for the spatio-temporal control of protein synthesis and underlies key processes during development, homeostasis, and disease. In epithelial cells, RNA can localize asymmetrically along the apico-basal axis. Yet, the localization of most transcripts as well as the diversity of patterns that they adopt remains unexplored. RESULTS: Here, we use APEX-seq for proximity labeling and MERFISH for spatial transcriptomics to map subcellular transcript localization in intestinal organoids and tissue from adult mice. Many transcripts present localization bias, often localizing in granular structures. We uncover intrinsic and environmental factors that influence the formation of these patterns. Additionally, we identify translation-dependent and -independent localization patterns and pinpoint the role of 3' untranslated regions and RNA-binding proteins. CONCLUSIONS: This subcellular RNA atlas presents a detailed resource for understanding intestinal physiology.