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Lyden, A.

Publications and source records attributed to Lyden, A..

6 recordsLinked to original sources
bioRxiv2020

Designing and implementing programmable depletion in sequencing libraries with DASHit

Since Next-Generation Sequencing produces reads uniformly subsampled from an input library, highly abundant sequences may mask interesting low abundance sequences. The DASH (Depleting Abundant Sequences by Hybridization) technique takes advantage of the programmability of CRISPR/Cas9 to deplete unwanted high-abundance sequences. Because desired depletion targets vary by sample type, here we describe DASHit, software that outputs an optimal DASH target set given a sequencing dataset, an updated DASH protocol, and show depletion results with DASHit-designed targets for three different species.

microbiology↗
bioRxiv2019

Serological and metagenomic interrogation of cerebrospinal fluid implicates enteroviruses in pediatric acute flaccid myelitis

BackgroundSince 2014, the United States has experienced a biennial spike in pediatric acute flaccid myelitis (AFM). Epidemiologic evidence suggests non-polio enteroviruses (EVs) are a potential etiology, yet EV RNA is rarely detected in cerebrospinal fluid (CSF) and only inconsistently identified from the respiratory tract, serum, or stool.\n\nMethodsWe interrogated CSF from children with AFM (n=42) and pediatric controls with other neurologic diseases (OND) (n=58). Samples were incubated with T7 bacteriophage expressing 481,966 sixty-two amino acid peptides with a fourteen amino acid overlap tiled across all known vertebrate virus and arbovirus genomes, an adaption of the VirScan method. Antibody-bound phage were deep sequenced to quantify enriched peptides with normalized counts expressed as reads per hundred thousand (rpK). EV antibody findings were confirmed with ELISA using whole viral protein 1 (VP1) from contemporary enterovirus (EV) A71 and D68 strains. Separately, metagenomic next-generation sequencing (mNGS) of CSF RNA, both unbiased and with targeted enrichment for EVs, was performed.\n\nResultsThe most significantly enriched viral family by VirScan of CSF in AFM versus OND controls was Picornaviridae (mean rpK 11,266 versus mean rpK 950, p-adjusted < 0.001, Wilcoxon signed-rank test with Bonferroni adjustment). Enriched Picornaviridae peptides belonged almost entirely to the genus Enterovirus. The mean EV VP1 ELISA signal in AFM (mean OD 0.51) was significantly higher than OND controls (mean OD 0.08, p-value < 0.001, Mann-Whitney test). mNGS did not detect additional enterovirus RNA in CSF.\n\nConclusionDespite the rare detection of EV RNA in the CNS of patients with AFM, a pan-viral serologic assay identified high levels of CSF EV antibodies in AFM CSF compared to CSF from OND controls. These results provide further evidence for a causal role of non-polio enteroviruses in AFM.

microbiology↗
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

FLASH: A next-generation CRISPR diagnostic for multiplexed detection of antimicrobial resistance sequences

The growing prevalence of deadly microbes with resistance to previously life-saving drug therapies is a dire threat to human health. Detection of low abundance pathogen sequences remains a challenge for metagenomic Next Generation Sequencing (NGS). We introduce FLASH (Finding Low Abundance Sequences by Hybridization), a next-generation CRISPR/Cas9 diagnostic method that takes advantage of the efficiency, specificity and flexibility of Cas9 to enrich for a programmed set of sequences. FLASH-NGS achieves up to 5 orders of magnitude of enrichment and sub-attomolar gene detection with minimal background. We provide an open-source software tool (FLASHit) for guide RNA design. Here we applied it to detection of antimicrobial resistance genes in respiratory fluid and dried blood spots, but FLASH-NGS is applicable to all areas that rely on multiplex PCR.

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↗