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Monocytes are associated with human cardiovascular disease progression. Monocytes are segregated into three major subsets: classical (cMo), intermediate (iMo), and nonclassical (nMo). Recent studies have identified heterogeneity within each of these main monocyte classes, yet the extent to which these subsets contribute to heart disease progression is not known. Peripheral blood mononuclear cells (PBMC) were obtained from 61 human subjects within the Coronary Assessment of Virginia (CAVA) Cohort. Coronary atherosclerosis severity was quantified using the Gensini Score (GS). We employed high-dimensional single-cell transcriptome and protein methods to define how human monocytes differ in subjects with low to severe coronary artery disease. We analyzed 487 immune-related genes and 49 surface proteins at the single-cell level using Antibody-Seq (Ab-Seq). We identified six subsets of myeloid cells (cMo, iMo, nMo, plasmacytoid DC, classical DC, and DC3) at the single-cell level based on surface proteins, and we associated these subsets with coronary artery disease (CAD) incidence based on Gensini score (GS) in each subject. Only frequencies of iMo were associated with high CAD (GS > 32), adj.p = 0.024. Spearman correlation analysis with GS from each subject revealed a positive correlation with iMo frequencies (r = 0.314, p = 0.014) and further showed a robust sex-dependent positive correlation in female subjects (r = 0.663, p = 0.004). cMo frequencies did not correlate with CAD severity. Key gene pathways differed in iMo among low and high CAD subjects and between males and females. Further single-cell analysis of iMo revealed three iMo subsets in human PBMC, distinguished by the expression of HLA-DR, CXCR3, and CD206. We found that the frequency of immunoregulatory iMo_HLA-DR+CXCR3+CD206+ was associated with CAD severity (adj.p = 0.006). The immunoregulatory iMo subset positively correlated with GS in both females (r = 0.660, p = 0.004) and males (r = 0.315, p = 0.037). Cell interaction analyses identified strong interactions of iMo with CD4+ effector/memory T cells and Tregs from the same subjects. This study shows the importance of iMo in CAD progression and suggests that iMo may have important functional roles in modulating CAD risk, particularly among females.

Background: Monoclonal antibodies play an important role in therapeutic and analytical applications. For recombinant expression, the coding sequences of the variable regions of the heavy and light chains are required. In addition, cloning antibody sequences, including constant regions, reduces the impact of hybridoma cell loss and ensures preservation of the naturally occurring full antibody sequence. Method: We combined amplification of IgG antibody variable regions from hybridoma mRNA with an advanced method for full-length cloning of monoclonal antibodies in a simple two-step workflow. Following Sanger sequencing and evaluation of consensus sequences, the best matching variable, diversity, and joining (V-(D-)J) gene segments were identified according to identity scores from IgBLAST reference sequences. Simultaneously, the mouse IgG subclass was determined at the DNA level based on isotype-specific sequence patterns in the CH1 domain. Knowing the DNA sequence of V-(D-)J recombination responsible for the complementary determining region 3 (CDR 3), variable region-specific primers were designed and used to amplify the corresponding antibody constant regions. Results: To verify the approach, we applied it to the hybridoma clone BAM-CCMV-29-81 and obtained identical full-length antibody sequences as with RNA Illumina sequencing. Further validation at the protein level using an established MALDI-TOF MS-fingerprinting protocol showed that five out of six genetically encoded CDR domains of the monoclonal antibody BAM-CCMV-29-81 could be efficiently correlated. Conclusion: This simple, streamlined method enables the cost-effective determination of the full-length sequence of monoclonal antibodies from hybridoma cell lines, with the added benefit of obtaining the DNA sequence of the antibody ready for recombinant expression.

Background Advances in next-generation sequencing (NGS) of antibody repertoires have led to an explosion in B cell receptor sequence data from donors with many different disease states. These data have the potential to detect patterns of immune response across populations. However, to this point it has been difficult to interpret such patterns of immune response between disease states in the absence of functional data. There is a need for a robust method that can be used to distinguish general patterns of immune responses at the antibody repertoire level. Results We developed a method for reducing the complexity of antibody repertoire datasets using principal component analysis (PCA) and refer to our method as “repertoire fingerprinting.” We reduce the high dimensional space of an antibody repertoire to just two principal components that explain the majority of variation in those repertoires. We show that repertoires from individuals with a common experience or disease state can be clustered by their repertoire fingerprints to identify common antibody responses. Conclusions Our repertoire fingerprinting method for distinguishing immune repertoires has implications for characterizing an individual disease state. Methods to distinguish disease states based on pattern recognition in the adaptive immune response could be used to develop biomarkers with diagnostic or prognostic utility in patient care. Extending our analysis to larger cohorts of patients in the future should permit us to define more precisely those characteristics of the immune response that result from natural infection or autoimmunity.

Studying the antibody response to infection or vaccination is essential for developing more effective vaccines and therapeutics. Advances in high-throughput antibody sequencing technologies and immunoinformatic tools now allow the fast and comprehensive analysis of antibody repertoires at high resolution in any species. Here, we detail a flexible and customizable suite of methods from flow cytometry, single cell sorting, heavy and light chain amplification to antibody sequencing in cattle. These methods were used successfully, including adaptation to the 10x Genomics platform, to isolate native heavy–light chain pairs. When combined with the Ig-Sequence Multi-Species Annotation Tool, this suite represents a powerful toolkit for studying the cattle antibody response with high resolution and precision. Using three workflows, we processed 84, 96, and 8313 cattle B cells from which we sequenced 24, 31, and 4756 antibody heavy–light chain pairs, respectively. Each method has strengths and limitations in terms of the throughput, timeline, specialist equipment, and cost that are each discussed. Moreover, the principles outlined here can be applied to study antibody responses in other mammalian species.

Monoclonal antibody light chain proteins secreted by clonal plasma cells cause tissue damage due to amyloid deposition and other mechanisms. The unique protein sequence associated with each case contributes to the diversity of clinical features observed in patients. Extensive work has characterized many light chains associated with multiple myeloma, light chain amyloidosis and other disorders, which we have collected in the publicly accessible database, AL-Base. However, light chain sequence diversity makes it difficult to determine the contribution of specific amino acid changes to pathology. Sequences of light chains associated with multiple myeloma provide a useful comparison to study mechanisms of light chain aggregation, but relatively few monoclonal sequences have been determined. Therefore, we sought to identify complete light chain sequences from existing high throughput sequencing data. We developed a computational approach using the MiXCR suite of tools to extract complete rearranged sequences from untargeted RNA sequencing data. This method was applied to whole-transcriptome RNA sequencing data from 766 newly diagnosed patients in the Multiple Myeloma Research Foundation CoMMpass study. Monoclonal sequences were defined as those where >50% of assigned or reads from each sample mapped to a unique sequence. Clonal light chain sequences were identified in 705/766 samples from the CoMMpass study. Of these, 685 sequences covered the complete region. The identity of the assigned sequences is consistent with their associated clinical data and with partial sequences previously determined from the same cohort of samples. Sequences have been deposited in AL-Base. Our method allows routine identification of clonal antibody sequences from RNA sequencing data collected for gene expression studies. The sequences identified represent, to our knowledge, the largest collection of multiple myeloma-associated light chains reported to date. This work substantially increases the number of monoclonal light chains known to be associated with non-amyloid plasma cell disorders and will facilitate studies of light chain pathology.

Monoclonal antibodies (mAbs) encoded by IGHV3-53 (VH3-53) targeting the spike receptor-binding domain (RBD) have been isolated from different COVID-19 patients. However, the existence and prevalence of shared VH3-53-encoded antibodies in the antibody repertoires is not clear. Using antibody repertoire sequencing, we found that the usage of VH3-53 increased after SARS-CoV-2 infection. A highly shared VH3-53-J6 clonotype was identified in 9 out of 13 COVID-19 patients. This clonotype was derived from convergent gene rearrangements with few somatic hypermutations and was evolutionary conserved. We synthesized 34 repertoire-deduced novel VH3-53-J6 heavy chains and paired with a common IGKV1-9 light chain to produce recombinant mAbs. Most of these recombinant mAbs (23/34) possess RBD binding and virus-neutralizing activities, and recognize ACE2 binding site via the same molecular interface. Our computational analysis, validated by laboratory experiments, revealed that VH3-53 antibodies targeting RBD are commonly present in COVID-19 patients' antibody repertoires, indicating many people have germline-like precursor sequences to rapidly generate SARS-CoV-2 neutralizing antibodies. Moreover, antigen-specific mAbs can be digitally obtained through antibody repertoire sequencing and computational analysis.

Purpose Most individuals with antibody deficiency (hypogammaglobulinemia) need immunoglobulin replacement therapy (IgG-RT) from healthy plasma donors to stay clear of infections. However, a small subset of hypogammaglobulinemic patients do not require this substitution therapy. We set out to investigate this clinical conundrum by asking whether the peripheral B cell receptor repertoires differ between antibody-deficient patients who do and do not need IgG-RT. Methods We sequenced and analyzed IgG and IgM heavy chain B cell receptor repertoires from peripheral blood mononuclear cells (PBMCs) isolated from patients with low serum IgG concentrations who did or did not require IgG-RT. Results Compared to the patients who did not need IgG-RT, those who needed IgG-RT had higher numbers of IgG antibody clones, higher IgM diversity, and less oligoclonal IgG and IgM repertoires. The patient cohorts had different heavy chain variable gene usage, and the patients who needed IgG-RT had elevated frequencies of IgG clones with higher germline identity (i.e., fewer somatic hypermutations). Conclusion Antibody-deficient patients with infection susceptibility who needed IgG-RT had more diverse peripheral antibody repertoires that were less diverged from germline and thus may not be as optimal for targeting pathogens, possibly contributing to infection susceptibility.

Coagulase-positive Staphylococci express protein A, which binds to host antibodies, to evade the immune system. Taking advantage of its specific binding to antibodies, protein A from Staphylococcus aureus , which is called SpA, is commonly used as an affinity chromatography ligand for human therapeutic antibodies. However, among four canine IgG subclasses (A, B, C, and D), only IgG-B binds to SpA strongly and establishing an efficient and robust purification scheme for canine therapeutic antibodies whose IgG subclass is A, C, or D remains difficult and depends on finding a suitable substitute to SpA. S . pseudintermedius , a major coagulase-positive Staphylococci found in dogs, expresses spsQ gene which is orthologous to S . aureus spa . We hypothesized that to serve S . pseudintermedius to better adapt to the dog immune system, SpsQ would bind to canine IgGs stronger than SpA, making it a better affinity chromatography ligand for canine therapeutic antibodies. To characterize SpsQ, we first determined the spsQ nucleotide sequence from S . pseudintermedius isolates. Based on the identified sequence, we prepared recombinant proteins containing the immunoglobulin-binding domains of SpA (r-SpA) and SpsQ (r-SpsQ) and determined their binding capacity for each canine IgG subclass. The binding capacity of r-SpsQ for IgG-B was almost as high as that of r-SpA. Interestingly, while both r-SpsQ and r-SpA showed no binding to IgG-C, the binding capacity of r-SpsQ for IgG-A and IgG-D was significantly higher than that of r-SpA. Finally, we performed affinity chromatography using r-SpsQ- or r-SpA-immobilized resin and revealed that the recovery rates of IgG-A and IgG-D using r-SpsQ were significantly higher than those using r-SpA. Our findings indicate that SpsQ has a strong potential to be used as an affinity chromatography ligand for canine therapeutic antibodies of subclass A, B, and D.

Antibody VRC01 is a human immunoglobulin that neutralizes about 90% of HIV-1 isolates. To understand how such broadly neutralizing antibodies develop, we used x-ray crystallography and 454 pyrosequencing to characterize additional VRC01-like antibodies from HIV-1—infected individuals. Crystal structures revealed a convergent mode of binding for diverse antibodies to the same CD4-binding-site epitope. A functional genomics analysis of expressed heavy and light chains revealed common pathways of antibody-heavy chain maturation, confined to the IGHV1-2*02 lineage, involving dozens of somatic changes, and capable of pairing with different light chains. Broadly neutralizing HIV-1 immunity associated with VRC01-like antibodies thus involves the evolution of antibodies to a highly affinity-matured state required to recognize an invariant viral structure, with lineages defined from thousands of sequences providing a genetic roadmap of their development.

Mining the antibody repertoire of plasma cells and plasmablasts could enable the discovery of useful antibodies for therapeutic or research purposes 1 . We present a method for high-throughput, single-cell screening of IgG-secreting primary cells to characterize antibody binding to soluble and membrane-bound antigens. Celli GO is a droplet microfluidics system that combines high-throughput screening for IgG activity, using fluorescence-based in-droplet single-cell bioassays 2 , with sequencing of paired antibody V genes, using in-droplet single-cell barcoded reverse transcription. We analyzed IgG repertoire diversity, clonal expansion and somatic hypermutation in cells from mice immunized with a vaccine target, a multifunctional enzyme or a membrane-bound cancer target. Immunization with these antigens yielded 100–1,000 IgG sequences per mouse. We generated 77 recombinant antibodies from the identified sequences and found that 93% recognized the soluble antigen and 14% the membrane antigen. The platform also allowed recovery of ~450–900 IgG sequences from ~2,200 IgG-secreting activated human memory B cells, activated ex vivo, demonstrating its versatility. Millions of primary IgG-secreting cells from mouse and human are characterized for activity and antibody sequence at the single-cell level.