Biology subjects

Caldera, S.

Publications and source records attributed to Caldera, S..

5 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

Investigating Transfusion-Related Sepsis using Culture-Independent Metagenomic Sequencing

BackgroundTransfusion-related sepsis remains an important hospital infection control challenge. Investigating septic transfusion events is often restricted by the limitations of bacterial culture in terms of time requirements and low yield in the setting of prior antibiotic administration.\n\nMethodsIn three Gram-negative septic transfusion cases, we performed mNGS of direct clinical blood specimens in addition to standard culture-based approaches utilized for infection control investigations. Pathogen detection leveraged IDSeq, a new open-access microbial bioinformatics portal. Phylogenetic analysis was performed to assess microbial genetic relatedness and understand transmission events.\n\nResultsmNGS of direct clinical blood specimens afforded precision detection of pathogens responsible for each case of transfusion-related sepsis, and enabled discovery of a novel Acinetobacter species in a platelet product that had become contaminated despite photochemical pathogen reduction. In each case, longitudinal assessment of pathogen burden elucidated the temporal sequence of events associated with each transfusion-transmitted infection. We found that informative data could be obtained from culture-independent mNGS of residual platelet products and leftover blood specimens that were either unsuitable or unavailable for culture, or that failed to grow due to prior antibiotic administration. We additionally developed methods to enhance accuracy for detecting transfusion-associated pathogens sharing taxonomic similarity to contaminants commonly found in mNGS library preparations.\n\nConclusionsCulture-independent mNGS of blood products afforded rapid and precise assessment of pathogen identity, abundance and genetic relatedness. Together, these challenging cases demonstrated the potential for metagenomics to advance existing methods for investigating transfusion-transmitted infections.

microbiology↗

bioRxiv2018

Microbiome and Antimicrobial Resistance Gene Dynamics in International Travelers

We engaged metagenomic next generation sequencing to longitudinally assess the gut microbiota and antimicrobial resistomes of international travelers to understand global exchange of resistant organisms. Travel resulted in an increase in antimicrobial resistance genes and a greater proportion of Escherichia species within gut microbial communities without impacting diversity.

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↗