Problematic bacterial proteins, better base editing, finding gene transcription's starting points, and more.
By Broad Communications
Welcome to the June 8, 2018 installment of Research Roundup, a recurring snapshot of recent studies published by scientists at the Broad Institute and their collaborators.
Effector detectors
Many proteins that are injected into host cells by pathogenic bacteria, often referred to as “effectors,” aren’t easily characterized by traditional loss-of-function assays. A team led by Broad associate member Cammie Lesser and Xiangyu Mou (both at Massachusetts General Hospital) developed a synthetic “bottom-up” platform to perform gain-of-function screens to elucidate roles of individual Shigella effectors in intestinal infections. Reporting in PNAS, the researchers found previously missed effectors that prevent the host’s immune system from triggering the death of infected epithelial cells. The work sheds new light on how Shigella effectors evade the host immune response and thrive within infected cells.
Advances in base editing
Base editing is a genome editing technology pioneered by core institute member and Merkin Institute for Transformative Technologies director David Liu that lets researchers change individual base pairs in the genome without having to cut DNA. In this week's Nature Communications, Liu, Wei-Hsi (Ariel) Yeh, Massachusetts Eye and Ear’s Albert Edge, and colleagues revealed that base editing works in non-dividing cells in vivo, in contrast with another genome editing method called homology-directed repair, which struggles in such cells. Separately, in Nature Biotechnology, Liu, Luke Koblan, and colleagues unveiled three upgraded base editors, BE4max, AncBE4max, and ABEmax, with greatly increased editing efficiency.
CAGE is good for starts
A gene can have multiple start sites for transcription, the first step of gene expression. Specialized RNA-seq methods can detect these transcription start sites (TSSs) and help understand gene function in human disease. In a study published in Nature Methods, Xian Adiconis, Adam Haber, Sean Simmons, Stanley Center for Psychiatric Research group leader Joshua Levin, core institute member and Klarman Cell Observatory director Aviv Regev and colleagues compared six RNA-seq methods and found that cap analysis for gene expression (CAGE) is best for identifying TSSs from messenger RNA. Applying CAGE to brain-related samples, the team identified differences in which TSSs were being used, and noted a genome-wide shift in their use between fetal and adult brain cells.
Towards more organ-like organoids
Accurate model systems are critical to uncovering relevant therapeutic insights in the lab. In this week’s BMC Biology, a team led by Broad associate member Jeffrey Karp and Benjamin Mead (both at Brigham and Women's Hospital), collaborating with associate member Alex Shalek at Massachusetts Institute of Technology (MIT), institute member James Collins, and Jose Ordovas-Montanes (also at MIT), used single-cell transcriptomics to assess how faithfully intestinal organoids recapitulate their in vivo counterparts. The researchers identified several key differences, particularly within Paneth cells (implicated in Crohn’s disease), and targeted specific molecular pathways to better align the model cell type with its tissue counterpart. The team’s framework can further be applied to systematically generate more realistic models in other systems.
