Extrafollicular IgD+ B cells generate IgE antibody secreting cells in the nasal mucosa.

Increased IgE is a typical feature of allergic rhinitis. Local class-switch recombination has been intimated but B cell precursors and mechanisms remain elusive. Here we describe the dynamics underlying the generation of IgE-antibody secreting cells (ASC) in human nasal polyps (NP), mucosal tissues rich in ASC without germinal centers (GC). Using VH next generation sequencing, we identified an extrafollicular (EF) mucosal IgD+ naïve-like intermediate B cell population with high connectivity to the mucosal IgE ASC. Mucosal IgD+ B cells, express germline epsilon transcripts and predominantly co-express IgM. However, a small but significant fraction co-express IgG or IgA instead which also show connectivity to ASC IgE. Phenotypically, NP IgD+ B cells display an activated profile and molecular evidence of BCR engagement. Transcriptionally, mucosal IgD+ B cells reveal an intermediate profile between naïve B cells and ASC. Single cell IgE ASC analysis demonstrates lower mutational frequencies relative to IgG, IgA, and IgD ASC consistent with IgE ASC derivation from mucosal IgD+ B cell with low mutational load. In conclusion, we describe a novel mechanism of GC-independent, extrafollicular IgE ASC formation at the nasal mucosa whereby activated IgD+ naïve B cells locally undergo direct and indirect (through IgG and IgA), IgE class switch.

Characterization of Donor Variability for γδ T Cell ex vivo Expansion and Development of an Allogeneic γδ T Cell Immunotherapy.

Gamma delta (γδ) T cells recently emerged as an attractive candidate for cancer immunotherapy treatments due to their inherent cytotoxicity against both hematological and solid tumors. Moreover, γδ T cells provide a platform for the development of allogeneic cell therapies, as they can recognize antigens independent of MHC recognition and without the requirement for a chimeric antigen receptor. However, γδ T cell adoptive cell therapy depends on ex vivo expansion to manufacture sufficient cell product numbers, which remains challenging and limited by inter-donor variability. In the current study, we characterize the differences in expansion of γδ T cells from various donors that expand (EX) and donors that fail to expand, i.e., non-expanders (NE). Further, we demonstrate that IL-21 can be used to increase the expansion potential of NE. In order to reduce the risk of graft vs. host disease (GVHD) induced by an allogeneic T cell product, αß T cell depletions must be considered due to the potential for HLA mismatch. Typically, αß T cell depletions are performed at the end of expansion, prior to infusion. We show that γδ T cell cultures can be successfully αß depleted on day 6 of expansion, providing a better environment for the γδ T cells to expand, and that the αß T cell population remains below clinically acceptable standards for T cell-depleted allogeneic stem cell products. Finally, we assess the potential for a mixed donor γδ T cell therapy and characterize the effects of cryopreservation on γδ T cells. Collectively, these studies support the development of an improved allogeneic γδ T cell product and suggest the possibility of using mixed donor γδ T cell immunotherapies.

Differential transcriptome and development of human peripheral plasma cell subsets.

Human antibody-secreting cells (ASCs) triggered by immunization are globally recognized as CD19loCD38hiCD27hi. Yet, different vaccines give rise to antibody responses of different longevity, suggesting ASC populations are heterogeneous. We define circulating-ASC heterogeneity in vaccine responses using multicolor flow cytometry, morphology, VH repertoire, and RNA transcriptome analysis. We also tested differential survival using a human cell-free system that mimics the bone marrow (BM) microniche. In peripheral blood, we identified 3 CD19+ and 2 CD19- ASC subsets. All subsets contributed to the vaccine-specific responses and were characterized by in vivo proliferation and activation. The VH repertoire demonstrated strong oligoclonality with extensive interconnectivity among the 5 subsets and switched memory B cells. Transcriptome analysis showed separation of CD19+ and CD19- subsets that included pathways such as cell cycle, hypoxia, TNF-α, and unfolded protein response. They also demonstrated similar long-term in vitro survival after 48 days. In summary, vaccine-induced ASCs with different surface markers (CD19 and CD138) are derived from shared proliferative precursors yet express distinctive transcriptomes. Equal survival indicates that all ASC compartments are endowed with long-lived potential. Accordingly, in vivo survival of peripheral long-lived plasma cells may be determined in part by their homing and residence in the BM microniche.

Author Correction: Factors of the bone marrow microniche that support human plasma cell survival and immunoglobulin secretion.

The original version of this Article omitted a declaration from the Competing Interests statement, which should have included the following: 'A patent has been applied for by Emory University with F.E.L, I.S. and D.C. N. as named inventors. The patent application number is PCT/US2016/036650'. This has now been corrected in both the PDF and HTML versions of the Article.

Factors of the bone marrow microniche that support human plasma cell survival and immunoglobulin secretion.

Human antibody-secreting cells (ASC) in peripheral blood are found after vaccination or infection but rapidly apoptose unless they migrate to the bone marrow (BM). Yet, elements of the BM microenvironment required to sustain long-lived plasma cells (LLPC) remain elusive. Here, we identify BM factors that maintain human ASC > 50 days in vitro. The critical components of the cell-free in vitro BM mimic consist of products from primary BM mesenchymal stromal cells (MSC), a proliferation-inducing ligand (APRIL), and hypoxic conditions. Comparative analysis of protein-protein interactions between BM-MSC proteomics with differential RNA transcriptomics of blood ASC and BM LLPC identify two major survival factors, fibronectin and YWHAZ. The MSC secretome proteins and hypoxic conditions play a role in LLPC survival utilizing mechanisms that downregulate mTORC1 signaling and upregulate hypoxia signatures. In summary, we identify elements of the BM survival niche critical for maturation of blood ASC to BM LLPC.

Metabolic modeling helps interpret transcriptomic changes during malaria.

Disease represents a specific case of malfunctioning within a complex system. Whereas it is often feasible to observe and possibly treat the symptoms of a disease, it is much more challenging to identify and characterize its molecular root causes. Even in infectious diseases that are caused by a known parasite, it is often impossible to pinpoint exactly which molecular profiles of components or processes are directly or indirectly altered. However, a deep understanding of such profiles is a prerequisite for rational, efficacious treatments. Modern omics methodologies are permitting large-scale scans of some molecular profiles, but these scans often yield results that are not intuitive and difficult to interpret. For instance, the comparison of healthy and diseased transcriptome profiles may point to certain sets of involved genes, but a host of post-transcriptional processes and regulatory mechanisms renders predictions regarding metabolic or physiological consequences of the observed changes in gene expression unreliable. Here we present proof of concept that dynamic models of metabolic pathway systems may offer a tool for interpreting transcriptomic profiles measured during disease. We illustrate this strategy with the interpretation of expression data of genes coding for enzymes associated with purine metabolism. These data were obtained during infections of rhesus macaques (Macaca mulatta) with the malaria parasite Plasmodium cynomolgi or P. coatneyi. The model-based interpretation reveals clear patterns of flux redistribution within the purine pathway that are consistent between the two malaria pathogens and are even reflected in data from humans infected with P. falciparum. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang.

A tree-like Bayesian structure learning algorithm for small-sample datasets from complex biological model systems.

BACKGROUND: There are increasing efforts to bring high-throughput systems biology techniques to bear on complex animal model systems, often with a goal of learning about underlying regulatory network structures (e.g., gene regulatory networks). However, complex animal model systems typically have significant limitations on cohort sizes, number of samples, and the ability to perform follow-up and validation experiments. These constraints are particularly problematic for many current network learning approaches, which require large numbers of samples and may predict many more regulatory relationships than actually exist. RESULTS: Here, we test the idea that by leveraging the accuracy and efficiency of classifiers, we can construct high-quality networks that capture important interactions between variables in datasets with few samples. We start from a previously-developed tree-like Bayesian classifier and generalize its network learning approach to allow for arbitrary depth and complexity of tree-like networks. Using four diverse sample networks, we demonstrate that this approach performs consistently better at low sample sizes than the Sparse Candidate Algorithm, a representative approach for comparison because it is known to generate Bayesian networks with high positive predictive value. We develop and demonstrate a resampling-based approach to enable the identification of a viable root for the learned tree-like network, important for cases where the root of a network is not known a priori. We also develop and demonstrate an integrated resampling-based approach to the reduction of variable space for the learning of the network. Finally, we demonstrate the utility of this approach via the analysis of a transcriptional dataset of a malaria challenge in a non-human primate model system, Macaca mulatta, suggesting the potential to capture indicators of the earliest stages of cellular differentiation during leukopoiesis. CONCLUSIONS: We demonstrate that by starting from effective and efficient approaches for creating classifiers, we can identify interesting tree-like network structures with significant ability to capture the relationships in the training data. This approach represents a promising strategy for inferring networks with high positive predictive value under the constraint of small numbers of samples, meeting a need that will only continue to grow as more high-throughput studies are applied to complex model systems.

The Patterns of Coevolution in Clade B HIV Envelope's N-Glycosylation Sites.

The co-evolution of the potential N-glycosylation sites of HIV Clade B gp120 was mapped onto the coevolution network of the protein structure using mean field direct coupling analysis (mfDCA). This was possible for 327 positions with suitable entropy and gap content. Indications of pressure to preserve the evolving glycan shield are seen as well as strong dependencies between the majority of the potential N-glycosylation sites and the rest of the structure. These findings indicate that although mainly an adaptation against antibody neutralization, the evolving glycan shield is structurally related to the core polypeptide, which, thus, is also under pressure to reflect the changes in the N-glycosylation. The map we propose fills the gap in previous attempts to tease out sequon evolution by providing a more general molecular context. Thus, it will help design strategies guiding HIV gp120 evolution in a rational way.

Carbohydrate targets in HIV vaccine research: lessons from failures.

Learning from the successes of other vaccines that enhance natural and existing protective responses to pathogens, the current effort in HIV vaccine research is directed toward inducing cytotoxic responses. Nevertheless, antibodies are fundamental players in vaccine development and are still considered in the context of passive specific immunotherapy of HIV, especially since several broadly neutralizing monoclonals are available. Special interest is directed toward antibodies binding to the glycan array on gp120 since they have the potential of broader reactivity and cross-clade neutralizing capacity. Humoral responses to carbohydrate antigens have proven effective against other pathogens, why not HIV? The variability of the epitope targets on HIV may not be the only problem to developing active or passive immunotherapeutic strategies. The dynamics of the infected immune system leads to ambiguous effects of most of the effector mechanisms calling for new approaches; some may already be available, while others are in the making.