Next-Generation Serology by Mass Spectrometry: Readout of the SARS-CoV-2 Antibody Repertoire.
Ontology highlight
ABSTRACT:
SUBMITTER: Melani RD
PROVIDER: S-EPMC8673472 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Methods of antibody detection are used to assess exposure or immunity to a pathogen. Here, we present Ig-MS, a novel serological readout that captures the immunoglobulin (Ig) repertoire at molecular resolution, including complete variable regions in Ig light and heavy chains. Ig-MS uses new advances in protein mass spectrometry (MS) for multi-parametric readout of antibodies, with new metrics like Ion Titer (IT) and degree of clonality (DoC) capturing the heterogeneity and relative abundance of individual clones without DNA/RNA sequencing of B cells. We apply Ig-MS to plasma from subjects with severe & mild COVID-19, using the receptor binding domain (RBD) of the spike protein of SARS-CoV-2 as the bait for antibody capture. Importantly, we report a new data type for human serology, with compatibility to any recombinant antigen to gauge our immune responses to vaccination, pathogens, or autoimmune disorders.
2021-05-27 | MSV000087529 | MassIVE
Project description:Methods of antibody detection are used to assess exposure or immunity to a pathogen. Here, we present Ig-MS, a novel serological readout that captures the immunoglobulin (Ig) repertoire at molecular resolution, including entire variable regions in Ig light and heavy chains. Ig-MS uses new advances in protein mass spectrometry (MS) for multi-parametric readout of antibodies, with new metrics like Ion Titer (IT) and degree of clonality (DoC) capturing the heterogeneity and relative abundance of individual clones without sequencing of B cells. We apply Ig-MS to plasma from subjects with severe & mild COVID-19, using the receptor-binding domain (RBD) of the spike protein of SARS-CoV-2 as the bait for antibody capture. Importantly, we report a new data type for human serology, with compatibility to any recombinant antigen to gauge our immune responses to vaccination, pathogens, or autoimmune disorders.
2022-09-24 | PXD028627 | panorama
Project description:To gain insight into the functional antibody repertoire of rabbits, the VH and VL repertoires of bone marrow (BM) and spleen (SP) of a naïve New Zealand White rabbit (NZW; Oryctolagus cuniculus) and that of lymphocytes collected from a NZW rabbit immunized (IM) with a 16-mer peptide were deep-sequenced. Two closely related genes, IGHV1S40 (VH1a3) and IGHV1S45 (VH4), were found to dominate (~90%) the VH repertoire of BM and SP, whereas, IGHV1S69 (VH1a1) contributed significantly (~40%) to IM. BM and SP antibodies recombined predominantly with IGHJ4. A significant proportion (~30%) of IM sequences recombined with IGHJ2. The VK repertoire was encoded by nine IGKV genes recombined with one IGKJ gene, IGKJ1. No significant bias in the VK repertoire of the BM, SP and IM samples was observed. The complementarity-determining region (CDR)-H3 and -L3 length distributions were similar in the three samples following a Gaussian curve with average length of 12.2 ± 2.4 and 11.1 ± 1.1 amino acids, respectively. The amino acid composition of the predominant CDR-H3 and -L3 loop lengths was similar to that of humans and mice, rich in Tyr, Gly, Ser and, in some specific positions, Asp. The average number of mutations along the IGHV/KV genes was similar in BM, SP and IM; close to 12 and 15 mutations for VH and VL, respectively. A monoclonal antibody specific for the peptide used as immunogen was obtained from the IM rabbit. The CDR-H3 sequence was found in 1,559 of 61,728 (2.5%) sequences, at position 10, in the rank order of the CDR-H3 frequencies. The CDR-L3 was found in 24 of 11,215 (0.2%) sequences, ranking 102. No match was found in the BM and SP samples, indicating positive selection for the hybridoma sequence. Altogether, these findings lay foundations for engineering of rabbit V regions to enhance their potential as therapeutics, i.e., design of strategies for selection of specific rabbit V regions from NGS data mining, humanization and design of libraries for affinity maturation campaigns.
| S-EPMC4011907 | biostudies-other
Project description:ObjectivesAs the world transitions into a new era of the COVID-19 pandemic in which vaccines become available, there is an increasing demand for rapid reliable serological testing to identify individuals with levels of immunity considered protective by infection or vaccination.MethodsWe used 34 SARS-CoV-2 samples to perform a rapid surrogate virus neutralisation test (sVNT), applicable to many laboratories as it circumvents the need for biosafety level-3 containment. We correlated results from the sVNT with five additional commonly used SARS-CoV-2 serology techniques: the microneutralisation test (MNT), in-house ELISAs, commercial Euroimmun- and Wantai-based ELISAs (RBD, spike and nucleoprotein; IgG, IgA and IgM), antigen-binding avidity, and high-throughput multiplex analyses to profile isotype, subclass and Fc effector binding potential. We correlated antibody levels with antibody-secreting cell (ASC) and circulatory T follicular helper (cTfh) cell numbers.ResultsAntibody data obtained with commercial ELISAs closely reflected results using in-house ELISAs against RBD and spike. A correlation matrix across ten measured ELISA parameters revealed positive correlations for all factors. The frequency of inhibition by rapid sVNT strongly correlated with spike-specific IgG and IgA titres detected by both commercial and in-house ELISAs, and MNT titres. Multiplex analyses revealed strongest correlations between IgG, IgG1, FcR and C1q specific to spike and RBD. Acute cTfh-type 1 cell numbers correlated with spike and RBD-specific IgG antibodies measured by ELISAs and sVNT.ConclusionOur comprehensive analyses provide important insights into SARS-CoV-2 humoral immunity across distinct serology assays and their applicability for specific research and/or diagnostic questions to assess SARS-CoV-2-specific humoral responses.
| S-EPMC7916820 | biostudies-literature
Project description:Histology-directed imaging mass spectrometry (IMS) is a spatially targeted IMS acquisition method informed by expert annotation that provides rapid molecular characterization of select tissue structures. The expert annotations are usually determined on digital whole slide images of histological stains where the staining preparation is incompatible with optimal IMS preparation, necessitating serial sections: one for annotation, one for IMS. Registration is then used to align staining annotations onto the IMS tissue section. Herein, we report a next-generation histology-directed platform implementing IMS-compatible autofluorescence (AF) microscopy taken prior to any staining or IMS. The platform enables two histology-directed workflows, one that improves the registration process between two separate tissue sections using automated, computational monomodal AF-to-AF microscopy image registration, and a registration-free approach that utilizes AF directly to identify ROIs and acquire IMS on the same section. The registration approach is fully automated and delivers state of the art accuracy in histology-directed workflows for transfer of annotations (?3-10 ?m based on 4 organs from 2 species) while the direct AF approach is registration-free, allowing targeting of the finest structures visible by AF microscopy. We demonstrate the platform in biologically relevant case studies of liver stage malaria and human kidney disease with spatially targeted acquisition of sparsely distributed (composing less than one tenth of 1% of the tissue section area) malaria infected mouse hepatocytes and glomeruli in the human kidney case study.
| S-EPMC6309458 | biostudies-literature
Project description:MotivationIn mass spectrometry-based proteomics, XML formats such as mzML and mzXML provide an open and standardized way to store and exchange the raw data (spectra and chromatograms) of mass spectrometric experiments. These file formats are being used by a multitude of open-source and cross-platform tools which allow the proteomics community to access algorithms in a vendor-independent fashion and perform transparent and reproducible data analysis. Recent improvements in mass spectrometry instrumentation have increased the data size produced in a single LC-MS/MS measurement and put substantial strain on open-source tools, particularly those that are not equipped to deal with XML data files that reach dozens of gigabytes in size.ResultsHere we present a fast and versatile parsing library for mass spectrometric XML formats available in C++ and Python, based on the mature OpenMS software framework. Our library implements an API for obtaining spectra and chromatograms under memory constraints using random access or sequential access functions, allowing users to process datasets that are much larger than system memory. For fast access to the raw data structures, small XML files can also be completely loaded into memory. In addition, we have improved the parsing speed of the core mzML module by over 4-fold (compared to OpenMS 1.11), making our library suitable for a wide variety of algorithms that need fast access to dozens of gigabytes of raw mass spectrometric data.AvailabilityOur C++ and Python implementations are available for the Linux, Mac, and Windows operating systems. All proposed modifications to the OpenMS code have been merged into the OpenMS mainline codebase and are available to the community at https://github.com/OpenMS/OpenMS.
| S-EPMC4416046 | biostudies-literature
Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of an ongoing pandemic that has infected over 36 million and killed over 1 million people. Informed implementation of government public health policies depends on accurate data on SARS-CoV-2 immunity at a population scale. We hypothesized that detection of SARS-CoV-2 salivary antibodies could serve as a noninvasive alternative to serological testing for monitoring of SARS-CoV-2 infection and seropositivity at a population scale. We developed a multiplex SARS-CoV-2 antibody immunoassay based on Luminex technology that comprised 12 CoV antigens, mostly derived from SARS-CoV-2 nucleocapsid (N) and spike (S). Saliva and sera collected from confirmed coronavirus disease 2019 (COVID-19) cases and from the pre-COVID-19 era were tested for IgG, IgA, and IgM to the antigen panel. Matched saliva and serum IgG responses (n = 28) were significantly correlated. The salivary anti-N IgG response resulted in the highest sensitivity (100%), exhibiting a positive response in 24/24 reverse transcription-PCR (RT-PCR)-confirmed COVID-19 cases sampled at >14 days post-symptom onset (DPSO), whereas the salivary anti-receptor binding domain (RBD) IgG response yielded 100% specificity. Temporal kinetics of IgG in saliva were consistent with those observed in blood and indicated that most individuals seroconvert at around 10 DPSO. Algorithms employing a combination of the IgG responses to N and S antigens result in high diagnostic accuracy (100%) by as early as 10 DPSO. These results support the use of saliva-based antibody testing as a noninvasive and scalable alternative to blood-based antibody testing.
| S-EPMC7771435 | biostudies-literature
Project description:Non-invasive SARS-CoV-2 antibody testing is urgently needed to estimate the incidence and prevalence of SARS-CoV-2 infection at the general population level. Precise knowledge of population immunity could allow government bodies to make informed decisions about how and when to relax stay-at-home directives and to reopen the economy. We hypothesized that salivary antibodies to SARS-CoV-2 could serve as a non-invasive alternative to serological testing for widespread monitoring of SARS-CoV-2 infection throughout the population. We developed a multiplex SARS-CoV-2 antibody immunoassay based on Luminex technology and tested 167 saliva and 324 serum samples, including 134 and 118 negative saliva and serum samples, respectively, collected before the COVID-19 pandemic, and 33 saliva and 206 serum samples from participants with RT-PCR-confirmed SARS-CoV-2 infection. We evaluated the correlation of results obtained in saliva vs. serum and determined the sensitivity and specificity for each diagnostic media, stratified by antibody isotype, for detection of SARS-CoV-2 infection based on COVID-19 case designation for all specimens. Matched serum and saliva SARS-CoV-2 antigen-specific IgG responses were significantly correlated. Within the 10-plex SARS-CoV-2 panel, the salivary anti-nucleocapsid (N) protein IgG response resulted in the highest sensitivity for detecting prior SARS-CoV-2 infection (100% sensitivity at ≥10 days post-SARS-CoV-2 symptom onset). The salivary anti-receptor binding domain (RBD) IgG response resulted in 100% specificity. Among individuals with SARS-CoV-2 infection confirmed with RT-PCR, the temporal kinetics of IgG, IgA, and IgM in saliva were consistent with those observed in serum. SARS-CoV-2 appears to trigger a humoral immune response resulting in the almost simultaneous rise of IgG, IgM and IgA levels both in serum and in saliva, mirroring responses consistent with the stimulation of existing, cross-reactive B cells. SARS-CoV-2 antibody testing in saliva can play a critically important role in large-scale 'sero'-surveillance to address key public health priorities and guide policy and decision-making for COVID-19.
| S-EPMC7273305 | biostudies-literature
Project description:Next-generation sequencing of the Ig gene repertoire (Ig-seq) produces large volumes of information at the nucleotide sequence level. Such data have improved our understanding of immune systems across numerous species and have already been successfully applied in vaccine development and drug discovery. However, the high-throughput nature of Ig-seq means that it is afflicted by high error rates. This has led to the development of error-correction approaches. Computational error-correction methods use sequence information alone, primarily designating sequences as likely to be correct if they are observed frequently. In this work, we describe an orthogonal method for filtering Ig-seq data, which considers the structural viability of each sequence. A typical natural Ab structure requires the presence of a disulfide bridge within each of its variable chains to maintain the fold. Our Ab Sequence Selector (ABOSS) uses the presence/absence of this bridge as a way of both identifying structurally viable sequences and estimating the sequencing error rate. On simulated Ig-seq datasets, ABOSS is able to identify more than 99% of structurally viable sequences. Applying our method to six independent Ig-seq datasets (one mouse and five human), we show that our error calculations are in line with previous experimental and computational error estimates. We also show how ABOSS is able to identify structurally impossible sequences missed by other error-correction methods.
| S-EPMC6485405 | biostudies-literature
Project description:Disease-specific antibodies can serve as highly effective biomarkers but have been identified for only a relatively small number of autoimmune diseases. A method was developed to identify disease-specific binding motifs through integration of bacterial display peptide library screening, next-generation sequencing (NGS) and computational analysis. Antibody specificity repertoires were determined by identifying bound peptide library members for each specimen using cell sorting and performing NGS. A computational algorithm, termed Identifying Motifs Using Next- generation sequencing Experiments (IMUNE), was developed and applied to discover disease- and healthy control-specific motifs. IMUNE performs comprehensive pattern searches, identifies patterns statistically enriched in the disease or control groups and clusters the patterns to generate motifs. Using celiac disease sera as a discovery set, IMUNE identified a consensus motif (QPEQPF[PS]E) with high diagnostic sensitivity and specificity in a validation sera set, in addition to novel motifs. Peptide display and sequencing (Display-Seq) coupled with IMUNE analysis may thus be useful to characterize antibody repertoires and identify disease-specific antibody epitopes and biomarkers.
| S-EPMC4969583 | biostudies-literature