Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn.

We investigate a relatively underexplored component of the gut-immune axis by profiling the antibody response to gut phages using Phage Immunoprecipitation Sequencing (PhIP-Seq). To cover large antigenic spaces, we develop Dolphyn, a method that uses machine learning to select peptides from protein sets and compresses the proteome through epitope-stitching. Dolphyn compresses the size of a peptide library by 78% compared to traditional tiling, increasing the antibody-reactive peptides from 10% to 31%. We find that the immune system develops antibodies to human gut bacteria-infecting viruses, particularly E.coli-infecting Myoviridae. Cost-effective PhIP-Seq libraries designed with Dolphyn enable the assessment of a wider range of proteins in a single experiment, thus facilitating the study of the gut-immune axis.

Epitope Mapping of SARS-CoV-2 Spike Antibodies in Vaccinated Kidney Transplant Recipients Reveals Poor Spike Coverage Compared to Healthy Controls.

Kidney transplant recipients (KTRs) develop decreased antibody titers to SARS-CoV-2 vaccination compared to healthy controls (HCs), but whether KTRs generate antibodies against key epitopes associated with neutralization is unknown. Plasma from 78 KTRs from a clinical trial of third doses of SARS-CoV-2 vaccines and 12 HCs underwent phage display immunoprecipitation and sequencing (PhIP-Seq) to map antibody responses against SARS-CoV-2. KTRs had lower antibody reactivity to SARS-CoV-2 than HCs, but KTRs and HCs recognized similar epitopes associated with neutralization. Thus, epitope gaps in antibody breadth of KTRs are unlikely responsible for decreased efficacy of SARS-CoV-2 vaccines in this immunosuppressed population.

Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn.

We investigated a relatively underexplored component of the gut-immune axis by profiling the antibody response to gut phages using Phage Immunoprecipitation Sequencing (PhIP-Seq). To enhance this approach, we developed Dolphyn, a novel method that uses machine learning to select peptides from protein sets and compresses the proteome through epitope-stitching. Dolphyn improves the fraction of gut phage library peptides bound by antibodies from 10% to 31% in healthy individuals, while also reducing the number of synthesized peptides by 78%. In our study on gut phages, we discovered that the immune system develops antibodies to bacteria-infecting viruses in the human gut, particularly E.coli-infecting Myoviridae. Cost-effective PhIP-Seq libraries designed with Dolphyn enable the assessment of a wider range of proteins in a single experiment, thus facilitating the study of the gut-immune axis.

Unbiased discovery of autoantibodies associated with severe COVID-19 via genome-scale self-assembled DNA-barcoded protein libraries.

Pathogenic autoreactive antibodies that may be associated with life-threatening coronavirus disease 2019 (COVID-19) remain to be identified. Here, we show that self-assembled genome-scale libraries of full-length proteins covalently coupled to unique DNA barcodes for analysis by sequencing can be used for the unbiased identification of autoreactive antibodies in plasma samples. By screening 11,076 DNA-barcoded proteins expressed from a sequence-verified human ORFeome library, the method, which we named MIPSA (for Molecular Indexing of Proteins by Self-Assembly), allowed us to detect circulating neutralizing type-I and type-III interferon (IFN) autoantibodies in five plasma samples from 55 patients with life-threatening COVID-19. In addition to identifying neutralizing type-I IFN-α and IFN-ω autoantibodies and other previously known autoreactive antibodies in patient plasma, MIPSA enabled the detection of as yet unidentified neutralizing type-III anti-IFN-λ3 autoantibodies that were not seen in healthy plasma samples or in convalescent plasma from ten non-hospitalized individuals with COVID-19. The low cost and simple workflow of MIPSA will facilitate unbiased high-throughput analyses of protein-antibody, protein-protein and protein-small-molecule interactions.

Insulin Dosing and Glycemic Outcomes Among Steroid-treated Hospitalized Patients.

OBJECTIVE: To determine the optimal insulin-to-steroid dose ratio for the attainment of glycemic control in hospitalized patients. METHODS: We retrospectively studied data collected from the electronic health records within an academic medical center from 18 599 patient-days where patients were treated concurrently with insulin and steroids. Multivariate logistic regression analyses, which included demographic and clinical variables, were performed to assess the relationships between the exposures of total and basal insulin-to-steroid ratios and the outcomes of glycemic control (all blood glucose readings on the following patient-day were >70 and ≤180 mg/dL) and hypoglycemia within 3 subgroups of steroid dosing: low (≤10-mg prednisone equivalent dose [PED]), medium (from >10-mg to ≤40-mg PED), and high (>40-mg PED). RESULTS: Increased insulin-to-steroid ratio was associated with increased odds of both glycemic control and hypoglycemia. The optimal total insulin-to-steroid ratio for attaining glycemic control was 0.294 U/kg/10-mg PED in the low-dose subgroup, 0.257 U/kg/10-mg PED in the medium-dose subgroup, and 0.085 U/kg/10-mg PED in the high-dose subgroup. The optimal basal insulin-to-steroid ratio was 0.215 U/kg/10-mg PED in the low-dose subgroup, 0.126 U/kg/10-mg PED in the medium-dose subgroup, and 0.036 U/kg/10-mg PED in the high-dose subgroup. CONCLUSION: Increasing insulin-to-steroid ratios are positively associated with glycemic control and hypoglycemia. Our study suggests that approximately 0.3 U/kg/10-mg PED is an optimal dose for low- and medium-dose steroids, whereas approximately 0.1 U/kg/10-mg PED is an optimal dose for high-dose steroids. Further prospective studies are needed to identify insulin regimens that will optimize glycemic control in steroid-treated patients while minimizing the risk of hypoglycemia.

Pharmacokinetics of high-titer anti-SARS-CoV-2 human convalescent plasma in high-risk children.

BACKGROUNDWhile most children who contract COVID-19 experience mild disease, high-risk children with underlying conditions may develop severe disease, requiring interventions. Kinetics of antibodies transferred via COVID-19 convalescent plasma early in disease have not been characterized.METHODSIn this study, high-risk children were prospectively enrolled to receive high-titer COVID-19 convalescent plasma (>1:320 anti-spike IgG; Euroimmun). Passive transfer of antibodies and endogenous antibody production were serially evaluated for up to 2 months after transfusion. Commercial and research ELISA assays, virus neutralization assays, high-throughput phage-display assay utilizing a coronavirus epitope library, and pharmacokinetic analyses were performed.RESULTSFourteen high-risk children (median age, 7.5 years) received high-titer COVID-19 convalescent plasma, 9 children within 5 days (range, 2-7 days) of symptom onset and 5 children within 4 days (range, 3-5 days) after exposure to SARS-CoV-2. There were no serious adverse events related to transfusion. Antibodies against SARS-CoV-2 were transferred from the donor to the recipient, but antibody titers declined by 14-21 days, with a 15.1-day half-life for spike protein IgG. Donor plasma had significant neutralization capacity, which was transferred to the recipient. However, as early as 30 minutes after transfusion, recipient plasma neutralization titers were 6.2% (range, 5.9%-6.7%) of donor titers.CONCLUSIONConvalescent plasma transfused to high-risk children appears to be safe, with expected antibody kinetics, regardless of weight or age. However, current use of convalescent plasma in high-risk children achieves neutralizing capacity, which may protect against severe disease but is unlikely to provide lasting protection.Trial registrationClinicalTrials.gov NCT04377672.FundingThe state of Maryland, Bloomberg Philanthropies, and the NIH (grants R01-AI153349, R01-AI145435-A1, K08-AI139371-A1, and T32-AI052071).

Neutralizing IFNL3 Autoantibodies in Severe COVID-19 Identified Using Molecular Indexing of Proteins by Self-Assembly.

Unbiased antibody profiling can identify the targets of an immune reaction. A number of likely pathogenic autoreactive antibodies have been associated with life-threatening SARS-CoV-2 infection; yet, many additional autoantibodies likely remain unknown. Here we present Molecular Indexing of Proteins by Self Assembly (MIPSA), a technique that produces ORFeome-scale libraries of proteins covalently coupled to uniquely identifying DNA barcodes for analysis by sequencing. We used MIPSA to profile circulating autoantibodies from 55 patients with severe COVID-19 against 11,076 DNA-barcoded proteins of the human ORFeome library. MIPSA identified previously known autoreactivities, and also detected undescribed neutralizing interferon lambda 3 (IFN-λ3) autoantibodies. At-risk individuals with anti- IFN-λ3 antibodies may benefit from interferon supplementation therapies, such as those currently undergoing clinical evaluation.

Antibody responses to endemic coronaviruses modulate COVID-19 convalescent plasma functionality.

SARS-CoV-2 (CoV2) antibody therapies, including COVID-19 convalescent plasma (CCP), monoclonal antibodies, and hyperimmune globulin, are among the leading treatments for individuals with early COVID-19 infection. The functionality of convalescent plasma varies greatly, but the association of antibody epitope specificities with plasma functionality remains uncharacterized. We assessed antibody functionality and reactivities to peptides across the CoV2 and the 4 endemic human coronavirus (HCoV) genomes in 126 CCP donations. We found strong correlation between plasma functionality and polyclonal antibody targeting of CoV2 spike protein peptides. Antibody reactivity to many HCoV spike peptides also displayed strong correlation with plasma functionality, including pan-coronavirus cross-reactive epitopes located in a conserved region of the fusion peptide. After accounting for antibody cross-reactivity, we identified an association between greater alphacoronavirus NL63 antibody responses and development of highly neutralizing antibodies against CoV2. We also found that plasma preferentially reactive to the CoV2 spike receptor binding domain (RBD), versus the betacoronavirus HKU1 RBD, had higher neutralizing titer. Finally, we developed a 2-peptide serosignature that identifies plasma donations with high anti-spike titer, but that suffer from low neutralizing activity. These results suggest that analysis of coronavirus antibody fine specificities may be useful for selecting desired therapeutics and understanding the complex immune responses elicited by CoV2 infection.

An In Vivo Screen Identifies PYGO2 as a Driver for Metastatic Prostate Cancer.

Advanced prostate cancer displays conspicuous chromosomal instability and rampant copy number aberrations, yet the identity of functional drivers resident in many amplicons remain elusive. Here, we implemented a functional genomics approach to identify new oncogenes involved in prostate cancer progression. Through integrated analyses of focal amplicons in large prostate cancer genomic and transcriptomic datasets as well as genes upregulated in metastasis, 276 putative oncogenes were enlisted into an in vivo gain-of-function tumorigenesis screen. Among the top positive hits, we conducted an in-depth functional analysis on Pygopus family PHD finger 2 (PYGO2), located in the amplicon at 1q21.3. PYGO2 overexpression enhances primary tumor growth and local invasion to draining lymph nodes. Conversely, PYGO2 depletion inhibits prostate cancer cell invasion in vitro and progression of primary tumor and metastasis in vivo In clinical samples, PYGO2 upregulation associated with higher Gleason score and metastasis to lymph nodes and bone. Silencing PYGO2 expression in patient-derived xenograft models impairs tumor progression. Finally, PYGO2 is necessary to enhance the transcriptional activation in response to ligand-induced Wnt/ß-catenin signaling. Together, our results indicate that PYGO2 functions as a driver oncogene in the 1q21.3 amplicon and may serve as a potential prognostic biomarker and therapeutic target for metastatic prostate cancer.Significance: Amplification/overexpression of PYGO2 may serve as a biomarker for prostate cancer progression and metastasis. Cancer Res; 78(14); 3823-33. ©2018 AACR.