Sensing and guiding cell-state transitions by using genetically encoded endoribonuclease-mediated microRNA sensors.

Precisely sensing and guiding cell-state transitions via the conditional genetic activation of appropriate differentiation factors is challenging. Here we show that desired cell-state transitions can be guided via genetically encoded sensors, whereby endogenous cell-state-specific miRNAs regulate the translation of a constitutively transcribed endoribonuclease, which, in turn, controls the translation of a gene of interest. We used this approach to monitor several cell-state transitions, to enrich specific cell types and to automatically guide the multistep differentiation of human induced pluripotent stem cells towards a haematopoietic lineage via endothelial cells as an intermediate state. Such conditional activation of gene expression is durable and resistant to epigenetic silencing and could facilitate the monitoring of cell-state transitions in physiological and pathological conditions and eventually the 'rewiring' of cell-state transitions for applications in organoid-based disease modelling, cellular therapies and regenerative medicine.

Modular and Single-Cell Sensors of Bacterial Ser/Thr Kinase Activity.

At the single-cell level, protein kinase activity is typically inferred from downstream transcriptional reporters. However, promoters are often coregulated by several pathways, making the activity of a specific kinase difficult to deconvolve. Here, we present modular, direct, and specific sensors of bacterial kinase activity, including FRET-based sensors, as well as a synthetic transcription factor based on the lactose repressor (LacI) that has been engineered to respond to phosphorylation. We demonstrate the utility of these sensors in measuring the activity of PrkC, a conserved bacterial Ser/Thr kinase, in different growth conditions from single cells to colonies. We also show that PrkC activity increases in response to a cell-wall active antibiotic that blocks the late steps in peptidoglycan synthesis (cefotaxime), but not the early steps (fosfomycin). These sensors have a modular design that should generalize to other bacterial signaling systems in the future.

The l-Alanosine Gene Cluster Encodes a Pathway for Diazeniumdiolate Biosynthesis.

N-Nitroso-containing natural products are bioactive metabolites with antibacterial and anticancer properties. In particular, compounds containing the diazeniumdiolate (N-nitrosohydroxylamine) group display a wide range of bioactivities ranging from cytotoxicity to metal chelation. Despite the importance of this structural motif, knowledge of its biosynthesis is limited. Herein we describe the discovery of a biosynthetic gene cluster in Streptomyces alanosinicus ATCC 15710 responsible for producing the diazeniumdiolate natural product l-alanosine. Gene disruption and stable isotope feeding experiments identified essential biosynthetic genes and revealed the source of the N-nitroso group. Additional biochemical characterization of the biosynthetic enzymes revealed that the non-proteinogenic amino acid l-2,3-diaminopropionic acid (l-Dap) is synthesized and loaded onto a free-standing peptidyl carrier protein (PCP) domain in l-alanosine biosynthesis, which we propose may be a mechanism of handling unstable intermediates generated en route to the diazeniumdiolate. These discoveries will facilitate efforts to determine the biochemistry of diazeniumdiolate formation.

Publisher Correction: Continuous evolution of base editors with expanded target compatibility and improved activity.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Continuous evolution of base editors with expanded target compatibility and improved activity.

Base editors use DNA-modifying enzymes targeted with a catalytically impaired CRISPR protein to precisely install point mutations. Here, we develop phage-assisted continuous evolution of base editors (BE-PACE) to improve their editing efficiency and target sequence compatibility. We used BE-PACE to evolve cytosine base editors (CBEs) that overcome target sequence context constraints of canonical CBEs. One evolved CBE, evoAPOBEC1-BE4max, is up to 26-fold more efficient at editing cytosine in the GC context, a disfavored context for wild-type APOBEC1 deaminase, while maintaining efficient editing in all other sequence contexts tested. Another evolved deaminase, evoFERNY, is 29% smaller than APOBEC1 and edits efficiently in all tested sequence contexts. We also evolved a CBE based on CDA1 deaminase with much higher editing efficiency at difficult target sites. Finally, we used data from evolved CBEs to illuminate the relationship between deaminase activity, base editing efficiency, editing window width and byproduct formation. These findings establish a system for rapid evolution of base editors and inform their use and improvement.