Precision arbovirus serology with a pan-arbovirus peptidome.

Arthropod-borne viruses represent a crucial public health threat. Current arboviral serology assays are either labor intensive or incapable of distinguishing closely related viruses, and many zoonotic arboviruses that may transition to humans lack any serologic assays. In this study, we present a programmable phage display platform, ArboScan, that evaluates antibody binding to overlapping peptides that represent the proteomes of 691 human and zoonotic arboviruses. We confirm that ArboScan provides detailed antibody binding information from animal sera, human sera, and an arthropod blood meal. ArboScan identifies distinguishing features of antibody responses based on exposure history in a Colombian cohort of Zika patients. Finally, ArboScan details epitope level information that rapidly identifies candidate epitopes with potential protective significance. ArboScan thus represents a resource for characterizing human and animal arbovirus antibody responses at cohort scale.

Evaluation of multi-assay algorithms for cross-sectional HIV incidence estimation in settings with universal antiretroviral treatment.

BACKGROUND: Multi-assay algorithms (MAAs) are used to estimate population-level HIV incidence and identify individuals with recent infection. Many MAAs use low viral load (VL) as a biomarker for long-term infection. This could impact incidence estimates in settings with high rates of early HIV treatment initiation. We evaluated the performance of two MAAs that do not include VL. METHODS: Samples were collected from 219 seroconverters (infected < 1 year) and 4376 non-seroconverters (infected > 1 year) in the HPTN 071 (PopART) trial; 28.8% of seroconverter samples and 73.2% of non-seroconverter samples had VLs ≤ 400 copies/mL. Samples were tested with the Limiting Antigen Avidity assay (LAg) and JHU BioRad-Avidity assays. Antibody reactivity to two HIV peptides was measured using the MSD U-PLEX assay. Two MAAs were evaluated that do not include VL: a MAA that includes the LAg-Avidity assay and BioRad-Avidity assay (LAg + BR) and a MAA that includes the LAg-Avidity assay and two peptide biomarkers (LAg + PepPair). Performance of these MAAs was compared to a widely used MAA that includes LAg and VL (LAg + VL). RESULTS: The incidence estimate for LAg + VL (1.29%, 95% CI: 0.97-1.62) was close to the observed longitudinal incidence (1.34% 95% CI: 1.17-1.53). The incidence estimates for the other two MAAs were higher (LAg + BR: 2.56%, 95% CI 2.01-3.11; LAg + PepPair: 2.84%, 95% CI: 1.36-4.32). LAg + BR and LAg + PepPair also misclassified more individuals infected > 2 years as recently infected than LAg + VL (1.2% [42/3483 and 1.5% [51/3483], respectively, vs. 0.2% [6/3483]). LAg + BR classified more seroconverters as recently infected than LAg + VL or LAg + PepPair (80 vs. 58 and 50, respectively) and identified ~ 25% of virally suppressed seroconverters as recently infected. CONCLUSIONS: The LAg + VL MAA produced a cross-sectional incidence estimate that was closer to the longitudinal estimate than two MAAs that did not include VL. The LAg + BR MAA classified the greatest number of individual seroconverters as recently infected but had a higher false recent rate.

A top scoring pairs classifier for recent HIV infections.

Accurate incidence estimation of HIV infection from cross-sectional biomarker data is crucial for monitoring the epidemic and determining the impact of HIV prevention interventions. A key feature of cross-sectional incidence testing methods is the mean window period, defined as the average duration that infected individuals are classified as recently infected. Two assays available for cross-sectional incidence estimation, the BED capture immunoassay, and the Limiting Antigen (LAg) Avidity assay, measure a general characteristic of antibody response; performance of these assays can be affected and biased by factors such as viral suppression, resulting in sample misclassification and overestimation of HIV incidence. As availability and use of antiretroviral treatment increase worldwide, algorithms that do not include HIV viral load and are not impacted by viral suppression are needed for cross-sectional HIV incidence estimation. Using a phage display system to quantify antibody binding to over 3300 HIV peptides, we present a classifier based on top scoring peptide pairs that identifies recent infections using HIV antibody responses alone. Based on plasma samples from individuals with known dates of seroconversion, we estimated the mean window period for our classifier to be 217 days (95% confidence interval 183 to 257 days), compared to the estimated mean window period for the LAg-Avidity protocol of 106 days (76 to 146 days). Moreover, each of the four peptide pairs correctly classified more of the recent samples than the LAg-Avidity assay alone at the same classification accuracy for non-recent samples.

Protease Activity Profiling via Programmable Phage Display of Comprehensive Proteome-Scale Peptide Libraries.

Endopeptidases catalyze the internal cleavage of proteins, playing pivotal roles in protein turnover, substrate maturation, and the activation of signaling cascades. A broad range of biological functions in health and disease are controlled by proteases, yet assays to characterize their activities at a proteomic scale do not exist. To address this unmet need, we developed Sensing EndoPeptidase Activity via Release and recapture using flAnking Tag Epitopes (SEPARATE), which uses a monovalent phage display of the human proteome at a 90-aa peptide resolution. We demonstrate that SEPARATE is compatible with several human proteases from distinct catalytic classes, including caspase-1, ADAM17, and thrombin. Both well-characterized and newly identified substrates of these enzymes were detected in the assay. SEPARATE was used to discover a non-canonical caspase-1 substrate, the E3 ubiquitin ligase HUWE1, a key mediator of apoptotic cell death. SEPARATE enables efficient, unbiased assessment of endopeptidase activity by using a phage-displayed proteome. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.

Chronic Dengue Virus Panencephalitis in a Patient with Progressive Dementia with Extrapyramidal Features.

OBJECTIVE: To determine the underlying etiology in a patient with progressive dementia with extrapyramidal signs and chronic inflammation referred to the National Institutes of Health Undiagnosed Diseases Program. METHODS: Extensive investigations included metabolic profile, autoantibody panel, infectious etiologies, genetic screening, whole exome sequencing, and the phage-display assay, VirScan, for viral immune responses. An etiological diagnosis was established postmortem. RESULTS: Using VirScan, enrichment of dengue viral antibodies was detected in cerebrospinal fluid as compared to serum. No virus was detected in serum or cerebrospinal fluid, but postmortem analysis confirmed dengue virus in the brain by immunohistochemistry, in situ hybridization, quantitative polymerase chain reaction, and sequencing. Dengue virus was also detectable by polymerase chain reaction and sequencing from brain biopsy tissue collected 33 months antemortem, confirming a chronic infection despite a robust immune response directed against the virus. Immunoprofiling and whole exome sequencing of the patient did not reveal any immunodeficiency, and sequencing of the virus demonstrated wild-type dengue virus in the central nervous system. INTERPRETATION: Dengue virus is the most common arbovirus worldwide and represents a significant public health concern. Infections with dengue virus are usually self-limiting, and chronic dengue infections have not been previously reported. Our findings suggest that dengue virus infections may persist in the central nervous system causing a panencephalitis and should be considered in patients with progressive dementia with extrapyramidal features in endemic regions or with relevant travel history. Furthermore, this work highlights the utility of comprehensive antibody profiling assays to aid in the diagnosis of encephalitis of unknown etiology. ANN NEUROL 2019;86:695-703.