Biology subjects

Crawford, E.

Publications and source records attributed to Crawford, E..

7 recordsLinked to original sources

bioRxiv2022

A family of novel immune systems targets early infection of nucleus-forming jumbo phages

Jumbo bacteriophages of the [ovbar]KZ-like family are characterized by large genomes (>200 kb) and the remarkable ability to assemble a proteinaceous nucleus-like structure. The nucleus protects the phage genome from canonical DNA-targeting immune systems, such as CRISPR-Cas and restriction-modification. We hypothesized that the failure of common bacterial defenses creates selective pressure for immune systems that target the unique jumbo phage biology. Here, we identify the "jumbo phage killer" (Juk) immune system that is deployed by a clinical isolate of Pseudomonas aeruginosa to resist [ovbar]KZ. Juk immunity rescues the cell by preventing early phage transcription, DNA replication, and nucleus assembly. Phage infection is first sensed by JukA (formerly YaaW), which localizes rapidly to the site of phage infection at the cell pole, triggered by ejected phage factors. The effector protein JukB is recruited by JukA, which is required to enable immunity and the subsequent degradation of the phage DNA. JukA homologs are found in several bacterial phyla and are associated with numerous other putative effectors, many of which provided specific anti-[ovbar]KZ activity when expressed in P. aeruginosa. Together, these data reveal a novel strategy for immunity whereby immune factors are recruited to the site of phage protein and DNA ejection to prevent phage progression and save the cell.

microbiology↗

bioRxiv2022

A Graph Coarsening Algorithm for Compressing Representations of Single-Cell Data with Clinical or Experimental Attributes

Graph-based algorithms have become essential in the analysis of single-cell data for numerous tasks, such as automated cell-phenotyping and identifying cellular correlates of experimental perturbations or disease states. In large multi-patient, multi-sample single-cell datasets, the analysis of cell-cell similarity graphs representations of these data becomes computationally prohibitive. Here, we introduce cytocoarsening, a novel graph-coarsening algorithm that significantly reduces the size of single-cell graph representations, which can then used as input to downstream bioinformatics algorithms for improved computational efficiency. Uniquely, cytocoarsening considers both phenotypical similarity of cells and similarity of cells associated clinical or experimental attributes in order to more readily identify condition-specific cell populations. The resulting coarse graph representations were evaluated based on both their structural correctness and the capacity of downstream algorithms to uncover the same biological conclusions as if the full graph had been used. Cytocoarsening is provided as open source code at https://github.com/ChenCookie/cytocoarsening.

bioinformatics↗

bioRxiv2020

Sensitive, highly multiplexed sequencing of microhaplotypes from the Plasmodium falciparum heterozygome

BackgroundTargeted next generation sequencing offers the potential for consistent, deep coverage of information rich genomic regions to characterize polyclonal Plasmodium falciparum infections. However, methods to identify and sequence these genomic regions are currently limited. MethodsA bioinformatic pipeline and multiplex methods were developed to identify and simultaneously sequence 100 targets and applied to dried blood spot (DBS) controls and field isolates from Mozambique. For comparison, WGS data were generated for the same controls. ResultsUsing publicly available genomes, 4465 high diversity genomic regions suited for targeted sequencing were identified, representing the P. falciparum heterozygome. For this study, 93 microhaplotypes with high diversity (median HE = 0.7) were selected along with 7 drug resistance loci. The sequencing method achieved very high coverage (median 99%), specificity (99.8%) and sensitivity (90% for haplotypes with 5% within sample frequency in DBS with 100 parasites/{micro}L). In silico analyses revealed that microhaplotypes provided much higher resolution to discriminate related from unrelated polyclonal infections than biallelic SNP barcodes. DiscussionThe bioinformatic and laboratory methods outlined here provide a flexible tool for efficient, low-cost, high throughput interrogation of the P. falciparum genome, and can be tailored to simultaneously address multiple questions of interest in various epidemiological settings.

molecular biology↗

bioRxiv2019

A minimal CRISPR-Cas3 system for genome engineering

CRISPR-Cas technologies have provided programmable gene editing tools that have revolutionized research. The leading CRISPR-Cas9 and Cas12a enzymes are ideal for programmed genetic manipulation, however, they are limited for genome-scale interventions. Here, we utilized a Cas3-based system featuring a processive nuclease, expressed endogenously or heterologously, for genome engineering purposes. Using an optimized and minimal CRISPR-Cas3 system (Type I-C) programmed with a single crRNA, large deletions ranging from 7 - 424 kb were generated in Pseudomonas aeruginosa with high efficiency and speed. By comparison, Cas9 yielded small deletions and point mutations. Cas3-generated deletion boundaries were variable in the absence of a homology-directed repair (HDR) template, and successfully and efficiently specified when present. The minimal Cas3 system is also portable; large deletions were induced with high efficiency in Pseudomonas syringae and Escherichia coli using an "all-in-one" vector. Notably, Cas3 generated bi-directional deletions originating from the programmed cut site, which was exploited to iteratively reduce a P. aeruginosa genome by 837 kb (13.5%) using 10 distinct crRNAs. We also demonstrate the utility of endogenous Cas3 systems (Type I-C and I-F) and develop an "anti-anti-CRISPR" strategy to circumvent endogenous CRISPR-Cas inhibitor proteins. CRISPR-Cas3 could facilitate rapid strain manipulation for synthetic biological and metabolic engineering purposes, genome minimization, and the analysis of large regions of unknown function.

molecular biology↗

bioRxiv2019

Modulating pathogenesis with Mobile-CRISPRi

Pathogens express a set of proteins required for establishing and maintaining an infection, termed virulence life-style genes (VLGs). Due to their outsized importance in pathogenesis, VLG products are attractive targets for the next generation of antimicrobials. However, precise manipulation of VLG expression in the context of infection is technically challenging, limiting our ability to understand the roles of VLGs in pathogenesis and accordingly design effective inhibitors. We previously developed a suite of gene knockdown tools that are transferred by conjugation and stably integrate into pathogen genomes that we call \"Mobile-CRISPRi\". Here we show the efficacy of Mobile-CRISPRi in controlling VLG expression in a murine infection model. We optimize Mobile-CRISPRi in Pseudomonas aeruginosa for use in a murine model of pneumonia by tuning the expression of CRISPRi components to avoid non-specific toxicity. As a proof of principle, we demonstrate that knockdown of a VLG encoding the type III secretion system (T3SS) activator ExsA blocks effector protein secretion in culture and attenuates virulence in mice. We anticipate that Mobile-CRISPRi will be a valuable tool to probe the function of VLGs across many bacterial species and pathogenesis models.\n\nImportanceAntibiotic resistance is a growing threat to global health. To optimize the use of our existing antibiotics and identify new targets for future inhibitors, understanding the fundamental drivers of bacterial growth in the context of the host immune response is paramount. Historically these genetic drivers have been difficult to manipulate, as they are requisite for pathogen survival. Here, we provide the first application of Mobile-CRISPRi to study virulence life-style genes in mouse models of lung infection through partial gene perturbation. We envision the use of Mobile-CRISPRi in future pathogenesis models and antibiotic target discovery efforts.

microbiology↗

bioRxiv2018

Integrating Host Response and Unbiased Microbe Detection for Lower Respiratory Tract Infection Diagnosis in Critically Ill Adults

Lower respiratory tract infections (LRTI) lead to more deaths each year than any other infectious disease category(1). Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests(2). In critically ill patients, non-infectious inflammatory syndromes resembling LRTI further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the lung microbiome and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed rules-based and logistic regression models (RBM, LRM) in a derivation cohort of 20 patients with LRTI or non-infectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with non-infectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an AUC of 0.96 (95% CI = 0.86 - 1.00), the diversity metric with an AUC of 0.80 (95% CI = 0.63 - 0.98), and the host transcriptional classifier with an AUC of 0.91 (95% CI = 0.80 - 1.00). Combining all three achieved an AUC of 0.99 (95% CI = 0.97 - 1.00) and negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome and host transcriptome may hold promise as a novel tool for LRTI diagnosis.\n\nSIGNIFICANCE STATEMENTLower respiratory tract infections (LRTI) are the leading cause of infectious disease-related death worldwide yet remain challenging to diagnose because of limitations in existing microbiologic tests. In critically ill patients, non-infectious respiratory syndromes that resemble LRTI further complicate diagnosis and confound targeted treatment. To address this, we developed a novel metagenomic sequencing-based approach that simultaneously interrogates three core elements of acute airway infections: the pathogen, lung microbiome and host response. We studied this approach in a prospective cohort of critically ill patients with acute respiratory failure and found that combining pathogen, microbiome and host gene expression metrics achieved accurate LRTI diagnosis and identified etiologic pathogens in patients with clinically identified infections but otherwise negative testing.\n\nFundingNHLBI K12HL119997 (Langelier C), NHLBI K23HL123778 (Christensen S), NIAID P01AI091575 and the Chan Zuckerberg Biohub (DeRisi JL), NHLBI K23 HL136844 (Moazed F), NHLBI R01HL110969, K24HL133390, R35HL140026 (Calfee C), Gladstone Institutes (Pollard KS).

genomics↗

bioRxiv2017

Optogenetic Characterization Of CeA CRF Pathways In Alcohol Dependence

Alcohol withdrawal activates a neuronal ensemble in the central nucleus of the amygdala (CeA) that is responsible for high levels of uncontrolled alcohol drinking. However, the neuronal phenotypes and circuits controlled by these neurons are unknown. We investigated the cellular identity of this CeA neuronal ensemble and found that most neurons expressed corticotropin-releasing factor (CRF). Using Crh-Cre transgenic rats combined with in vivo optogenetics, we tested the role of CeA CRF neurons and their projections in excessive alcohol self-administration during withdrawal. Rats were injected with AAV-DIO-NpHR-eYFP or AAV-DIO-eYFP and implanted with optical fibers over the CeA. Animals were then exposed to chronic intermittent ethanol vapor to induce alcohol dependence. Inactivation of CeA CRF neurons decreased alcohol drinking in dependent rats to non-dependent levels and completely suppressed activation of the CeA neuronal ensemble (Fos+ neurons) during withdrawal. No effects were observed on water or saccharin self-administration. In a second experiment, CeA CRF neurons were infected with AAV-DIO-NpHR-eYFP and optical fibers were implanted into downstream projection regions, including the bed nucleus of the stria terminalis (BNST), lateral hypothalamus (LH), parasubthalamic nucleus (pSTN), substantia innominata (SI), and parabrachial nuclei (PBN). Optogenetic inactivation of CRF terminals in the BNST reduced alcohol drinking and withdrawal signs, whereas inactivation of all other projections had no effect. These results demonstrate that CeA CRF neurons and their projections to the BNST drive excessive alcohol drinking and withdrawal in dependent rats.

neuroscience↗