Rapid, inexpensive, and sensitive nucleic acid detection may aid point-of-care pathogen detection, genotyping, and disease monitoring. The RNA-guided, RNA-targeting CRISPR effector Cas13a (previously known as C2c2) exhibits a “collateral effect” of promiscuous RNAse activity upon target recognition. We combine the collateral effect of Cas13a with isothermal amplification to establish a CRISPR-based diagnostic (CRISPR-Dx), providing rapid DNA or RNA detection with attomolar sensitivity and single-base mismatch specificity. We use this Cas13a-based molecular detection platform, termed SHERLOCK (Specific High Sensitivity Enzymatic Reporter UnLOCKing), to detect specific strains of Zika and Dengue virus, distinguish pathogenic bacteria, genotype human DNA, and identify cell-free tumor DNA mutations. Furthermore, SHERLOCK reaction reagents can be lyophilized for cold-chain independence and long-term storage, and readily reconstituted on paper for field applications.

Living cells display complex signal processing behaviors, many of which are mediated by networks of proteins specialized for signal transduction. Here we focus on the question of how the remarkably diverse array of eukaryotic signaling circuits may have evolved. Many of the mechanisms that connect signaling proteins into networks are highly modular: The core catalytic activity of a signaling protein is physically and functionally separable from molecular domains or motifs that determine its linkage to both inputs and outputs. This high degree of modularity may make these systems more evolvable-in principle, novel circuits, and therefore highly innovative regulatory behaviors, can arise from relatively simple genetic events such as recombination, deletion, or insertion. In support of this hypothesis, recent studies show that such modular systems can be exploited to engineer nonnatural signaling proteins and pathways with novel behavior.

Dysregulation of the immune response to bacterial infection can lead to sepsis, a condition with high mortality. Multiple whole-blood gene expression studies have defined sepsis-associated molecular signatures but did not resolve changes in transcriptional states of specific cell types. Here, we used single-cell RNA sequencing to profile the blood of patients with sepsis (n = 29) across three clinical cohorts with corresponding controls (n = 36). We profiled total peripheral blood mononuclear cells (PBMCs, 106,545 cells) and dendritic cells (19,806 cells) across all patients and, based on clustering of their gene expression profiles, defined 16 immune cell states. We identified a unique CD14+ monocyte state that is expanded in septic patients and validated its power in discriminating septic patients from controls using public transcriptomic data from patients of different disease etiologies and multiple geographic locations (18 cohorts, n = 1,213 patients). We identified a panel of surface markers for isolation and quantification of the monocyte state, characterized its epigenomic and functional phenotypes, and propose a model for its induction from human bone marrow. This study demonstrates the utility of single cell genomics in discovering disease-associated cytologic signatures and provides insight into the cellular basis of immune dysregulation in bacterial sepsis.