Biology subjects

O'Donovan, B. D.

Publications and source records attributed to O'Donovan, B. D..

3 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↗

bioRxiv2018

Exploration of Anti-Yo and Anti-Hu paraneoplastic neurological disorders by PhIP-Seq reveals a highly restricted pattern of antibody epitopes

Paraneoplastic neurological disorders (PNDs) are immune-mediated diseases of the nervous system understood to manifest as part of a misdirected anti-tumor immune response. Identifying PND-associated autoantibodies and their cognate antigens can assist with proper diagnosis and treatment while also enhancing our understanding of tumor-associated immune processes, triggers for autoimmune disease, and the functional significance of onconeuronal proteins. Here, we employed an enhanced version of phage display immunoprecipitation and sequencing (PhIP-Seq) leveraging a library of over 731,000 unique phage clones tiling across the entire human proteome to detect autoantibodies and create high-resolution epitope profiles in serum and CSF samples from patients suffering from two common PNDs, the anti-Yo (n = 36 patients) and anti-Hu syndromes (n = 44 patients). All patient samples positive for anti-Yo antibody by a validated clinical assay yielded polyspecific enrichment of phage presenting peptides from the canonical anti-Yo (CDR2 and CDR2L) antigens, while 38% of anti-Hu patients (17/44) had a serum and/or CSF sample that significantly enriched peptides deriving from the ELAVL family of proteins, the anti-Hu autoantigenic target. The anti-Hu antibodies showed a remarkably convergent antigenic signature across 15/17 patients corresponding to residues surrounding and including the degenerate motif, RLDxLL, shared by ELAVL2, 3 and 4. Lastly, PhIP-Seq identified several known and novel autoantigens in these same patient samples, representing potential biomarkers that could aid in the diagnosis and prognosis of PND and cancer.

immunology↗

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↗