Many rigorous studies have shown that early childhood infections leave a lasting imprint on the immune system. The understanding of this phenomenon has expanded significantly since 1960, when Dr. Thomas Francis Jr first coined the term “original antigenic sin”, to account for all previous pathogen exposures, rather than only the first. Now more commonly referred to as “immune imprinting”, this effect most often focuses on how memory B-cell responses are shaped by prior antigen exposure, and the resultant antibodies produced after subsequent exposure to antigenically similar pathogens. Although imprinting was originally observed within the context of influenza viral infection, it has since been applied to the pandemic coronavirus SARS-CoV-2. To fully comprehend how imprinting affects the evolution of antibody responses, it is necessary to compare responses elicited by pathogenic strains that are both antigenically similar and dissimilar to strains encountered previously. To accomplish this, we must be able to measure the antigenic distance between strains, which can be easily accomplished using data from multidimensional immunological assays. The knowledge of imprinting, combined with antigenic distance measures, may allow for improvements in vaccine design and development for both influenza and SARS-CoV-2 viruses.

We describe the use of classical and metric multidimensional scaling methods for graphical representation of the proximity between collections of data consisting of cases characterized by multidimensional attributes. These methods can preserve metric differences between cases, while allowing for dimensional reduction and projection to two or three dimensions ideal for data exploration. We demonstrate these methods with three datasets for: (i) the immunological similarity of influenza proteins measured by a multidimensional assay; (ii) influenza protein sequence similarity; and (iii) reconstruction of airport-relative locations from paired proximity measurements. These examples highlight the use of proximity matrices, eigenvalues, eigenvectors, and linear and nonlinear mappings using numerical minimization methods. Some considerations and caveats for each method are also discussed, and compact Mathematica programs are provided.

Background: Hypoxia is a potent molecular signal for cellular metabolism, mitochondrial function, and migration. Conditions of low oxygen tension trigger regulatory cascades mediated via the highly conserved HIF-1 α post-translational modification system. In the adaptive immune response, B cells (Bc) are activated and differentiate under hypoxic conditions within lymph node germinal centers, and subsequently migrate to other compartments. During migration, they traverse through changing oxygen levels, ranging from 1-5% in the lymph node to 5-13% in the peripheral blood. Interestingly, the calcineurin inhibitor cyclosporine A is known to stimulate prolyl hydroxylase activity, resulting in HIF-1 α destabilization and may alter Bc responses directly. Over 60% of patients taking calcineurin immunosuppressant medications have hypo-gammaglobulinemia and poor vaccine responses, putting them at high risk of infection with significantly increased morbidity and mortality. Results: We demonstrate that O ₂ tension is a previously unrecognized Bc regulatory switch, altering CXCR4 and CXCR5 chemokine receptor signaling in activated Bc through HIF-1 α expression, and controlling critical aspects of Bc migration. Our data demonstrate that calcineurin inhibition hinders this O ₂ regulatory switch in primary human Bc. Conclusion: This previously unrecognized effect of calcineurin inhibition directly on human Bc has significant and direct clinical implications.

Coordinated migration of B cells within and between secondary lymphoid tissues is required for robust antibody responses to infection or vaccination. Secondary lymphoid tissues normally expose B cells to a low O${}_2$ (hypoxic) environment. Recently, we have shown that human B cell migration is modulated by an O${}_2$-dependent molecular switch, centrally controlled by the hypoxia-induced (transcription) factor-1$\alpha$ (HIF1A), which can be disrupted by the immunosuppressive calcineurin inhibitor, cyclosporine A (CyA). However, the mechanisms by which low O${}_2$ environments attenuate B cell migration remain poorly defined. Proteomics analysis has linked CXCR4 chemokine receptor signaling to cytoskeletal rearrangement. We now hypothesize that the pathways linking the O${}_2$ sensing molecular switch to chemokine receptor signaling and cytoskeletal rearrangement would likely contain phosphorylation events, which are typically missed in traditional transcriptomic and/or proteomic analyses. Hence, we have performed a comprehensive phosphoproteomics analysis of human B cells treated with CyA after engagement of the chemokine receptor CXCR4 with CXCL12. Statistical analysis of the separate and synergistic effects of CyA and CXCL12 revealed 116 proteins whose abundance is driven by a synergistic interaction between CyA and CXCL12. Further, we used our previously described algorithm BONITA to reveal a critical role for Lymphocyte Specific Protein 1 (LSP1) in cytoskeletal rearrangement. LSP1 is known to modulate neutrophil migration. Validating these modeling results, we show experimentally that LSP1 levels in B cells increase with low O${}_2$ exposure, and CyA treatment results in decreased LSP1 protein levels. This correlates with the increased chemotactic activity observed after CyA treatment. Lastly, we directly link LSP1 levels to chemotactic capacity, as shRNA knock-down of LSP1 results in significantly increased B cell chemotaxis at low O${}_2$ levels. These results directly link CyA to LSP1-dependent cytoskeletal regulation, demonstrating a previously unrecognized mechanism by which CyA modulates human B cell migration. Data are available via ProteomeXchange with identifier PXD036167.

Oxygen (O2) regulated pathways modulate B cell activation, migration and proliferation during infection, vaccination, and other diseases. Modeling these pathways in health and disease is critical to understand B cell states and ways to mediate them. To characterize B cells by their activation of O2 regulated pathways we develop pathway specific discrete state models using previously published single-cell RNA-sequencing (scRNA-seq) datasets from isolated B cells. Specifically, Single Cell Boolean Omics Network Invariant-Time Analysis (scBONITA) was used to infer logic gates for known pathway topologies. The simplest inferred set of logic gates that maximized the number of "OR" interactions between genes was used to simulate B cell networks involved in oxygen sensing until they reached steady network states (attractors). By focusing on the attractors that best represented sequenced cells, we identified genes critical in determining pathway specific cellular states that corresponded to diseased and healthy B cell phenotypes. Specifically, we investigate the transendothelial migration, regulation of actin cytoskeleton, HIF1A, and Citrate Cycle pathways. Our analysis revealed attractors that resembled the state of B cell exhaustion in HIV+ patients as well as attractors that promoted anerobic metabolism, angiogenesis, and tumorigenesis in breast cancer patients, which were eliminated after neoadjuvant chemotherapy (NACT). Finally, we investigated the attractors to which the Azimuth-annotated B cells mapped and found that attractors resembling B cells from HIV+ patients encompassed a significantly larger number of atypical memory B cells than HIV- attractors. Meanwhile, attractors resembling B cells from breast cancer patients post NACT encompassed a reduced number of atypical memory B cells compared to pre-NACT attractors.

Background: The global COVID-19 pandemic has resulted in approximately 7 million deaths and a historic vaccination effort, with over 13.6 billion doses administered. Despite this, understanding of immune responses in vulnerable populations, such as transplant recipients (TR) and hemodialysis patients (HD), remains limited, especially outside the US and Europe. Methods: To address this gap, we analyzed blood samples and deidentified data from the Instituto Nacional de Coordinación de Trasplante (INCORT) in The Dominican Republic, measuring antibody levels to SARS-CoV-2 post-infection and vaccination with BNT162b2 (Pfizer-BioNTech) and Sinovac-CoronaVac (Sinovac) in TR, HD, and healthy controls (CO). Using a fluorescent multiplex assay (mPlex-CoV) and mixed-effects modeling, we assessed variations in anti-S, anti-RBD, and anti-N IgG antibodies. Results: The results indicate that the CO group experienced an early peak in anti-S and anti-RBD antibodies, followed by stabilization. In contrast, the TR and HD groups showed a slower, gradual increase in antibodies. Despite fluctuations in the HD group, both the TR and HD groups maintained high anti-S and anti-RBD IgG levels, indicating a back-boosting effect from vaccination. However, elevated anti-N IgG levels in the TR and HD groups suggest potential reinfections. Additionally, prior SARS-CoV-2 infection led to higher anti-S IgG levels, with BNT162b2 associated with higher anti-S IgG and CoronaVac associated with higher anti-N IgG levels. Conclusion: These findings highlight the variability in antibody responses and the need for targeted public health strategies to diverse immunological profiles.