02212nas a2200373   4500000000100000000000100001008004100002260001200043653002000055653003000075653002400105653001600129100002900145700002000174700002000194700001800214700002000232700002100252700001900273700001900292700001800311700001700329700002100346700002200367700001800389700001800407700002100425245012000446856005500566300001400621490000700635520118200642022001401824       2025                            d  c2025-0710aGene regulation10aHigh-throughput screening10aInfectious diseases10aMutagenesis1 aMaria Letizia Di Martino1 aLaura Jenniches1 aAnjeela Bhetwal1 aJens Eriksson1 aAna C. C. Lopes1 aAngelika Ntokaki1 aMartina Pasqua1 aMagnus Sundbom1 aMartin Skogar1 aWilhelm Graf1 aDominic-Luc Webb1 aPer M. Hellström1 aAndré Mateus1 aLars Barquist1 aMikael E. Sellin00aA scalable gut epithelial organoid model reveals the genome-wide colonization landscape of a human-adapted pathogen  uhttps://www.nature.com/articles/s41588-025-02218-x  a1730-17410 v573 aStudying the pathogenesis of human-adapted microorganisms is challenging, since small animal models often fail to recapitulate human physiology. Hence, the comprehensive genetic and regulatory circuits driving the infection process of principal human pathogens such as Shigella flexneri remain to be defined. We combined large-scale Shigella infections of enteroids and colonoids with transposon-directed insertion sequencing and Bayesian statistical modeling to address infection bottlenecks, thereby establishing the comprehensive genome-wide map of Shigella genes required to infect human intestinal epithelium. This revealed the Shigella virulence effectors essential for epithelial cell colonization across geometries and intestinal segments, identified over 100 chromosomal genes involved in the process and uncovered a post-transcriptional mechanism whereby tRNA-modification enzymes and differential codon usage exert global control of a bacterial virulence program. Our findings provide a broadly applicable framework for combining advanced organotypic tissue culture with functional genomics and computational tools to map human–microorganism interactions at scale.  a1546-1718