Biology subjects

Khan, L. M.

Publications and source records attributed to Khan, L. M..

5 recordsLinked to original sources

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

Unbiased metagenomic sequencing for pediatric meningitis in Bangladesh reveals neuroinvasive Chikungunya virus outbreak and other unrealized pathogens

The disease burden due to meningitis in low and middle-income countries remains significant and failure to determine an etiology impedes appropriate treatment for patients and evidence-based policy decisions for populations. Broad-range pathogen surveillance using metagenomic next-generation sequencing (mNGS) of RNA isolated from cerebral spinal fluid (CSF) provides an unbiased assessment for possible infectious etiologies. In this study, our objective was to use mNGS to identify etiologies of pediatric meningitis in Bangladesh.\n\nWe conducted a retrospective case-control mNGS study on CSF from patients with known neurologic infections (n=36), idiopathic meningitis (n=25), without infection (n=30) and six environmental samples collected between 2012-2018. Using an open-access, cloud-based bioinformatics pipeline (IDseq) and machine learning, we identified potential pathogens which were confirmed through qPCR and Sanger sequencing. These cases were followed-up through phone/home-visits. The CSF samples were collected from children with WHO-defined meningeal signs during prospective meningitis surveillance at the largest pediatric referral hospital in Bangladesh.\n\nThe 91 participants (42% female) ranged in age from 0-160 months (median: 9 months). In samples with known infectious causes of meningitis and without infections (n=66), there was 83% concordance between mNGS and conventional testing. In idiopathic cases (n=25), mNGS identified a potential etiology in 40% (n=10), including bacterial and viral pathogens. There were three instances of neuroinvasive Chikungunya virus (CHIKV). The CHIKV genomes were >99% identical to each other and to a Bangladeshi strain only previously recognized to cause systemic illness in 2017. CHIKV qPCR of all remaining stored CSF samples from children who presented with idiopathic meningitis in 2017 at the same hospital (n=472) revealed 17 additional CHIKV meningitis cases. Orthogonal molecular confirmation of each mNGS-identified infection, case-based clinical data, and follow-up of patients substantiated the key findings.\n\nUsing mNGS, we obtained a microbiological diagnosis for 40% of idiopathic meningitis cases and identified a previous unappreciated pediatric CHIKV meningitis outbreak. Case-control CSF mNGS surveys can complement conventional diagnostic methods to identify etiologies of meningitis and facilitate informed policy decisions.

genomics↗

bioRxiv2018

Miniaturization and optimization of 384-well compatible metagenomic sequencing library preparation

Preparation of high-quality sequencing libraries is a costly and time-consuming component of metagenomic next generation sequencing (mNGS). While the overall cost of sequencing has dropped significantly over recent years, the reagents needed to prepare sequencing samples are likely to become the dominant expense in the process. Furthermore, libraries prepared by hand are subject to human variability and needless waste due to limitations of manual pipetting volumes. Reduction of reaction volumes, combined with sub-microliter automated dispensing of reagents without consumable pipette tips, has the potential to provide significant advantages. Here, we describe the integration of several instruments, including the Labcyte Echo 525 acoustic liquid handler and the iSeq and NovaSeq Illumina sequencing platforms, to miniaturize and automate mNGS library preparation, significantly reducing the cost and the time required to prepare samples. Through the use of External RNA Controls Consortium (ERCC) spike-in RNAs, we demonstrated the fidelity of the miniaturized preparation to be equivalent to full volume reactions. Furthermore, detection of viral and microbial species from cell culture and patient samples was also maintained in the miniaturized libraries. For 384-well mNGS library preparations, we achieved a savings of over 80% in materials and reagents alone, and reduced preparation time by 90% compared to manual approaches, without compromising quality or representation within the library.

molecular biology↗

bioRxiv2018

Pediatric Brainstem Encephalitis Outbreak Investigation with Metagenomic Next-Generation Sequencing

In 2016, Catalonia experienced a pediatric brainstem encephalitis outbreak caused by enterovirus A71 (EV-A71). Conventional testing identified EV in peripheral body sites, but EV was rarely identified in cerebrospinal fluid (CSF). RNA was extracted from CSF (n=20), plasma (n=9), stool (n=15) and nasopharyngeal samples (n=16) from 10 children with brainstem encephalitis or encephalomyelitis and 10 contemporaneous pediatric controls with presumed viral meningitis or encephalitis. Unbiased complementary DNA libraries were sequenced, and microbial pathogens were identified using a custom bioinformatics pipeline. Full-length virus genomes were assembled for phylogenetic analyses. Metagenomic next-generation sequencing (mNGS) was concordant with qRT-PCR for all samples positive by PCR (n=25). In virus-negative samples (n=35), mNGS detected virus in 28.6% (n=10), including 5 CSF samples. mNGS co-detected EV-A71 and another EV in 5 patients. Overall, mNGS increased the proportion of EV-positive samples from 42% (25/60) to 57% (34/60) (McNemars test; p-value = 0.0077). For CSF, mNGS doubled the number of pathogen-positive samples (McNemars test; p-value = 0.074). Using phylogenetic analysis, the outbreak EV-A71 clustered with a neuroinvasive German EV-A71 isolate. Brainstem encephalitis specific, non-synonymous EV-A71 single nucleotide variants were not identified. mNGS demonstrated 100% concordance with clinical qRT-PCR of EV-related brainstem encephalitis and significantly increased the detection of enteroviruses. Our findings increase the probability that neurologic complications observed were virus-induced rather than para-infectious. A comprehensive genomic analysis confirmed that the EV-A71 outbreak strain was closely related to a neuroinvasive German EV-A71 isolate. There were no clear-cut viral genomic differences that discriminated between patients with differing neurologic phenotypes.

microbiology↗

bioRxiv2017

Metagenomics for chronic meningitis: clarifying interpretation and diagnosis

ImportanceIdentifying infectious causes of subacute and chronic meningitis can be challenging. Enhanced, unbiased diagnostic approaches are needed.\n\nObjectiveTo present a case series of patients with diagnostically challenging subacute and chronic meningitis in whom metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF), supported by a statistical framework generated from mNGS sequencing of non-infectious patients and environmental controls, identified a pathogen.\n\nDesignCase series. Using mNGS data from the CSF of 94 non-infectious neuroinflammatory cases and 24 water and reagent controls, we developed and implemented a weighted scoring metric based on z-scores at the species and genus level for both nucleotide and protein databases to prioritize and rank mNGS results. We performed mNGS on total RNA extracted from CSF of patients with subacute or chronic meningitis and highlight seven cases representing a diverse array of pathogens.\n\nSettingA multi-center study of mNGS pathogen discovery in patients with suspected neuroinflammatory conditions.\n\nParticipantsPatients with diagnostically challenging subacute or chronic meningitis enrolled in a research study of mNGS performed on CSF.\n\nInterventionmNGS was performed on total RNA extracted from CSF (0.25-0.5 mL). A weighted z-score was used to filter out environmental contaminants and facilitate efficient data triage and analysis.\n\nMain Outcomes1) Pathogens identified by mNGS and 2) ability of a statistical model to prioritize, rank, and simplify mNGS results.\n\nResultsmNGS identified parasitic worms, fungi and viruses in seven subjects: Taenia solium (n=2), Cryptococcus neoformans, human immunodeficiency virus-1, Aspergillus oryzae, Histoplasma capsulatum, and Candida dubliniensis. Evaluating mNGS data with a weighted z-score based scoring algorithm effectively separated bona fide pathogen sequences from spurious environmental sequences.\n\nConclusions and RelevancemNGS of CSF identified a diversity of microbial pathogens in patients with diagnostically challenging subacute or chronic meningitis, including a case of subarachnoid neurocysticercosis that defied diagnosis for one year, the first case of CNS vasculitis caused by Aspergillus oryzae, and the fourth reported case of Candida dubliniensis meningitis. Filtering metagenomic data with a scoring algorithm greatly clarified data interpretation and highlights the difficulties attributing biological significance to organisms that may be present in control samples used for metagenomic sequencing studies.\n\nKey PointsQuestion: How can metagenomic next-generation sequencing of cerebrospinal fluid be leveraged to aid in the diagnosis of patients with subacute or chronic meningitis?\n\nFindings: Metagenomic next-generation sequencing identified parasitic worms, fungi and viruses in a case series of seven subjects. A database of water-only and healthy patient controls enabled application of a z-score based scoring algorithm to effectively separate bona fide pathogen sequences from spurious environmental sequences.\n\nMeaning: Our scoring algorithm greatly simplified data interpretation in a series of patients with a wide range of challenging infectious causes of subacute or chronic meningitis identified by metagenomic next-generation sequencing.

microbiology↗