VIPR: A probabilistic algorithm for analysis of microbial detection microarrays

<p>Abstract</p> <p>Background</p> <p>All infectious disease oriented clinical diagnostic assays in use today focus on detecting the presence of a single, well defined target agent or a set of agents. In recent years, microarray-based diagnostics have been developed that greatly facilitate the highly parallel detection of multiple microbes that may be present in a given clinical specimen. While several algorithms have been described for interpretation of diagnostic microarrays, none of the existing approaches is capable of incorporating training data generated from positive control samples to improve performance.</p> <p>Results</p> <p>To specifically address this issue we have developed a novel interpretive algorithm, VIPR (<b>V</b>iral <b>I</b>dentification using a <b>PR</b>obabilistic algorithm), which uses Bayesian inference to capitalize on empirical training data to optimize detection sensitivity. To illustrate this approach, we have focused on the detection of viruses that cause hemorrhagic fever (HF) using a custom HF-virus microarray. VIPR was used to analyze 110 empirical microarray hybridizations generated from 33 distinct virus species. An accuracy of 94% was achieved as measured by leave-one-out cross validation. <it>Conclusions</it></p> <p>VIPR outperformed previously described algorithms for this dataset. The VIPR algorithm has potential to be broadly applicable to clinical diagnostic settings, wherein positive controls are typically readily available for generation of training data.</p

E-Predict: a computational strategy for species identification based on observed DNA microarray hybridization patterns

DNA microarrays may be used to identify microbial species present in environmental and clinical samples. However, automated tools for reliable species identification based on observed microarray hybridization patterns are lacking. We present an algorithm, E-Predict, for microarray-based species identification. E-Predict compares observed hybridization patterns with theoretical energy profiles representing different species. We demonstrate the application of the algorithm to viral detection in a set of clinical samples and discuss its relevance to other metagenomic applications

Microarray detection of human parainfluenzavirus 4 infection associated with respiratory failure in an immunocompetent adult.

A pan-viral DNA microarray, the Virochip (University of California, San Francisco), was used to detect human parainfluenzavirus 4 (HPIV-4) infection in an immunocompetent adult presenting with a life-threatening acute respiratory illness. The virus was identified in an endotracheal aspirate specimen, and the microarray results were confirmed by specific polymerase chain reaction and serological analysis for HPIV-4. Conventional clinical laboratory testing using an extensive panel of microbiological tests failed to yield a diagnosis. This case suggests that the potential severity of disease caused by HPIV-4 in adults may be greater than previously appreciated and illustrates the clinical utility of a microarray for broad-based viral pathogen screening

Spinal fluid IgG antibodies from patients with demyelinating diseases bind multiple sclerosis-associated bacteria

ABSTRACT: A panel of 10 IgG enzyme-linked immunosorbent assays (ELISAs) were developed for the detection of anti-microbial immune responses in the cerebrospinal fluid (CSF) of patients with demyelinating diseases (DD). The anti-microbial ELISA assays follow on prior human brain tissue RNA sequencing studies that established multiple sclerosis (MS) microbial candidates. Lysates included in the ELISA panel were derived from Akkermansia muciniphila, Atopobium vaginae, Bacteroides fragilis, Lactobacillus paracasei, Odoribacter splanchnicus, Pseudomonas aeruginosa, Cutibacterium (Propionibacterium) acnes, Fusobacterium necrophorum, Porphyromonas gingivalis, and Streptococcus mutans. CSF responses from patients with demyelinating diseases (DD, N = 14) were compared to those with other neurological diseases (OND, N = 8) and controls (N = 13). Commercial positive and negative control CSF specimens were run with each assay. ELISA index values were derived for each specimen against each of the 10 bacterial lysates. CSF reactivity was significantly higher in the DD group compared to the controls against Akkermansia, Atopobium, Bacteroides, Lactobacillus, Odoribacter, and Fusobacterium. Four of the 11 tested DD group subjects had elevated antibody indexes against at least one of the 10 bacterial species, suggesting intrathecal antibody production. This CSF serological study supports the hypothesis that several of the previously identified MS candidate microbes contribute to demyelination in some patients. KEY MESSAGES: A panel of 10 IgG enzyme-linked immunosorbent assays (ELISAs) were developed for the detection of anti-microbial immune responses in the cerebrospinal fluid (CSF) of patients with demyelinating diseases, including multiple sclerosis and acute disseminated encephalomyelitis. CSF reactivity was significantly higher in the demyelination group compared to the controls against the bacteria Akkermansia, Atopobium, Bacteroides, Lactobacillus, Odoribacter, and Fusobacterium. Several of the demyelination subjects had elevated antibody indexes against at least one of the 10 antigens, suggesting at least limited intrathecal production of anti-bacterial antibodies. This CSF serological study supports the hypothesis that several of the previously identified MS candidate microbes contribute to demyelination in some patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00109-021-02085-z

Recovery of divergent avian bornaviruses from cases of proventricular dilatation disease: Identification of a candidate etiologic agent

<p>Abstract</p> <p>Background</p> <p>Proventricular dilatation disease (PDD) is a fatal disorder threatening domesticated and wild psittacine birds worldwide. It is characterized by lymphoplasmacytic infiltration of the ganglia of the central and peripheral nervous system, leading to central nervous system disorders as well as disordered enteric motility and associated wasting. For almost 40 years, a viral etiology for PDD has been suspected, but to date no candidate etiologic agent has been reproducibly linked to the disease.</p> <p>Results</p> <p>Analysis of 2 PDD case-control series collected independently on different continents using a pan-viral microarray revealed a bornavirus hybridization signature in 62.5% of the PDD cases (5/8) and none of the controls (0/8). Ultra high throughput sequencing was utilized to recover the complete viral genome sequence from one of the virus-positive PDD cases. This revealed a bornavirus-like genome organization for this agent with a high degree of sequence divergence from all prior bornavirus isolates. We propose the name avian bornavirus (ABV) for this agent. Further specific ABV PCR analysis of an additional set of independently collected PDD cases and controls yielded a significant difference in ABV detection rate among PDD cases (71%, n = 7) compared to controls (0%, n = 14) (P = 0.01; Fisher's Exact Test). Partial sequence analysis of a total of 16 ABV isolates we have now recovered from these and an additional set of cases reveals at least 5 distinct ABV genetic subgroups.</p> <p>Conclusion</p> <p>These studies clearly demonstrate the existence of an avian reservoir of remarkably diverse bornaviruses and provide a compelling candidate in the search for an etiologic agent of PDD.</p

Non-standard neutrino interactions in IceCube

Non-standard neutrino interactions (NSI) may arise in various types of new physics. Their existence would change the potential that atmospheric neutrinos encounter when traversing Earth matter and hence alter their oscillation behavior. This imprint on coherent neutrino forward scattering can be probed using high-statistics neutrino experiments such as IceCube and its low-energy extension, DeepCore. Both provide extensive data samples that include all neutrino flavors, with oscillation baselines between tens of kilometers and the diameter of the Earth. DeepCore event energies reach from a few GeV up to the order of 100 GeV - which marks the lower threshold for higher energy IceCube atmospheric samples, ranging up to 10 TeV. In DeepCore data, the large sample size and energy range allow us to consider not only flavor-violating and flavor-nonuniversal NSI in the μ−τ sector, but also those involving electron flavor. The effective parameterization used in our analyses is independent of the underlying model and the new physics mass scale. In this way, competitive limits on several NSI parameters have been set in the past. The 8 years of data available now result in significantly improved sensitivities. This improvement stems not only from the increase in statistics but also from substantial improvement in the treatment of systematic uncertainties, background rejection and event reconstruction