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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2017

Deep Sequencing Reveals Transient Segregation of T Cell Repertoires in Splenic T Cell Zones During an Immune Response

Immunological differences between hosts, such as diverse T-cell receptor (TCR) repertoires, are widely credited for reducing the risk of pathogen spread and adaptation in a population. Within-host immunological diversity might likewise be important for robust pathogen control, but to what extent naive TCR repertoires differ across different locations in the same host is unclear. T-cell zones (TCZs) in secondary lymphoid organs provide secluded micro-environmental niches. By harboring distinct TCRs, such niches could enhance within-host immunological diversity. On the other hand, rapid T cell migration is expected to dilute such diversity. Here, we combined tissue micro-dissection and deep sequencing of the TCR {beta} chain to examine the extent to which TCR repertoires differ between TCZs in murine spleens. In the absence of antigen, we found little evidence for differences between different TCZs of the same spleen. Yet, three days after immunization with sheep red blood cells, we observed a >10-fold rise in the number of clones that appeared to localize to individual zones. Remarkably, these differences largely disappeared at 4 days after immunization, when hallmarks of an ongoing immune response were still observed. These data suggest that in the absence of antigen, any repertoire differences observed between TCZs of the same host can largely be attributed to random clone distribution. Upon antigen challenge, segregated TCR compartments appear and disappear within days. Such \"transient mosaic\" dynamics could be an important barrier for pathogen adaptation and spread during an immune response.

immunology↗
bioRxiv2018

Improved CD4 T-cell profile and inflammatory levels in HIV-infected subjects on maraviroc-containing therapy is associated with better responsiveness to HBV vaccination.

IntroductionWe previously found that a maraviroc-containing combined antiretroviral therapy (MVC-cART) was associated with a better response to the Hepatitis B Virus (HBV) vaccine in HIV-infected subjects younger than 50 years old. We aimed here to extend our previous analysis including immunological parameters related to inflammation, T-cell and dendritic cell (DC) subsets phenotype and to explore the impact of MVC-cART on these parameters.\n\nMethodsWe analyzed baseline samples of vaccinated subjects under 50 years old (n=41). We characterized CD4 T-cells according to the distribution of their maturational subsets and the expression of activation, senescence and prone-to-apoptosis markers; we also quantified Treg-cells and main DC subsets. Linear regressions were performed to determine the impact of these variables on the magnitude of vaccine response. Binary logistic regressions were explored to analyze the impact of MVC-cART on immunological parameters. Correlations with the time of MVC exposure were also explored.\n\nResultsMVC-cART remained independently associated with HBV-vaccine responsiveness even after adjusting by immunological variables. The %CD4+CD25hiFoxP3+ki67+ and %pDCs were also independently associated. Moreover, HIV-infected subjects on MVC-containing therapy prior to vaccination showed lower inflammatory levels, activated CD4 T-cells and frequency of Treg cells and higher frequency of recent thymic emigrants.\n\nConclusionTreg-cell levels negatively impacted the HBV-vaccine response, whereas higher pDCs levels and a MVC-cART prior to vaccination were associated with better responsiveness. These factors together with the improved phenotypic CD4 T-cell profile and the lower inflammatory levels found in subjects with a MVC-cART prior HBV vaccination could contribute to their enhanced vaccine response.

immunology↗
bioRxiv2018

Characterising antibody kinetics from multiple influenza infection and vaccination events in ferrets

The strength and breadth of an individuals antibody repertoire are important predictors of their response to influenza infection or vaccination. Although progress has been made in understanding qualitatively how repeated exposures shape the antibody mediated immune response, quantitative understanding remains limited. We developed a set of mathematical models describing short-term antibody kinetics following influenza infection or vaccination and fit them to haemagglutination inhibition (HI) titres from 5 groups of ferrets which were exposed to different combinations of trivalent inactivated influenza vaccine (TIV with or without adjuvant), priming inoculation with A/H3N2 and post-vaccination inoculation with A/H1N1. Based on the parameter estimates of the best supported model, we describe a number of key immunological features. We found quantifiable differences in the degree of homologous and cross-reactive antibody boosting elicited by different exposure types. Infection and adjuvanted vaccination generally resulted in strong, broadly reactive responses whereas unadjuvanted vaccination resulted in a weak, narrow response. We found that the order of exposure mattered: priming with A/H3N2 improved subsequent vaccine response, and the second dose of adjuvanted vaccination resulted in substantially greater antibody boosting than the first. Although there was considerable uncertainty in our estimates of antibody waning parameters, our results suggest that both short and long term waning were present and would be identifiable with a larger set of experiments. These results highlight the potential use of repeat exposure animal models in revealing short-term, strain-specific immune dynamics of influenza.\n\nAuthor summaryDespite most individuals having some preexisting immunity from past influenza infections and vaccinations, a significant proportion of the human population is infected with influenza each year. Predicting how an individuals antibody profile will change following exposure is therefore useful for evaluating which populations are at greatest risk and how effective vaccination strategies might be. However, interpretation of antibody data from humans is complicated by immunological interactions between all previous, unobserved exposures in an individuals life. We developed a mathematical model to describe short-term antibody kinetics that are important in building an individuals immune profile but are difficult to observe in human populations. We validated this model using antibody data from ferrets with known, varied infection and vaccination histories. We were able to quantify the independent contributions of various exposures and immunological mechanisms in generating observed antibody titres. These results suggest that data from experimental systems may be included in models of human antibody dynamics, which may improve predictions of vaccination strategy effectiveness and how population susceptibility changes over time.

immunology↗
bioRxiv2018

Interfacial actin protrusions mechanically potentiate killing by cytotoxic T cells

Cytotoxic T lymphocytes (CTLs) kill by forming immunological synapses with target cells and secreting toxic proteases and the pore forming protein perforin into the intercellular space. Immunological synapses are highly dynamic structures that potentiate perforin activity by applying mechanical force against the target cell. Here, we employed high-resolution imaging and microfabrication to investigate how CTLs exert synaptic forces and coordinate their mechanical output with perforin secretion. Using micropatterned stimulatory substrates that enable synapse growth in three dimensions, we found that perforin release occurs at the base of actin-rich protrusions that extend from central and intermediate locations within the synapse. These protrusions, which depended on the cytoskeletal regulator WASP and the Arp2/3 actin nucleation complex, were required for synaptic force exertion and efficient killing. They also mediated physical distortion of the target cell surface during CTL-target cell interactions. Our results reveal the mechanical basis of cellular cytotoxicity and highlight the functional importance of dynamic, three-dimensional architecture in immune cell-cell interfaces.\n\nOne sentence summaryCytotoxic T lymphocytes use F-actin-rich protrusions at the immunological synapse to potentiate perforin-and granzyme-mediated target cell killing.

immunology↗
bioRxiv2016

Tuberculosis susceptibility and vaccine protection are independently controlled by host genotype

The outcome of Mycobacterium tuberculosis (Mtb) infection and the immunological response to the Bacille Calmette Guerin (BCG) vaccine are highly variable in humans. Deciphering the relative importance of host genetics, environment, and vaccine preparation on BCG efficacy has proven difficult in natural populations. We developed a model system that captures the breadth of immunological responses observed in outbred individuals, which can be used to understand the contribution of host genetics to vaccine efficacy. This system employs a panel of highly-diverse inbred mouse strains, consisting of the founders and recombinant progeny of the \"Collaborative Cross\". Unlike natural populations, the structure of this panel allows the serial evaluation of genetically-identical individuals and quantification of genotype-specific effects of interventions such as vaccination. When analyzed in the aggregate, our panel resembled natural populations in several important respects; the animals displayed a broad range of Mtb susceptibility, varied in their immunological response to infection, and were not durably protected by BCG vaccination. However, when analyzed at the genotype level, we found that these phenotypic differences were heritable. Mtb susceptibility varied between lines, from extreme sensitivity to progressive Mtb clearance. Similarly, only a minority of the genotypes was protected by vaccination. BCG efficacy was genetically separable from susceptibility, and the lack of efficacy in the aggregate analysis was driven by nonresponsive lines that mounted a qualitatively distinct response to infection. These observations support an important role for host genetic diversity in determining BCG efficacy, and provide a new resource to rationally develop more broadly efficacious vaccines.\n\nImportance: Tuberculosis (TB) remains an urgent global health crisis, and the efficacy of the currently used TB vaccine, M. bovis BCG, is highly variable. The design of more broadly-efficacious vaccines depends on understanding the factors that limit the protection imparted by BCG. While these complex factors are difficult to disentangle in natural populations, we used a model population of mice to understand the role of host genetic composition to BCG efficacy. We found that the ability of BCG to protect an individual genotype was remarkably variable. BCG efficacy did not depend on the intrinsic susceptibility of the animal, but instead correlated with qualitative differences in the immune response to the pathogen. These studies suggest that host genetic polymorphism is a critical determinant of vaccine efficacy and provides a model system to develop interventions that will be useful in genetically diverse populations.

Microbiology↗
bioRxiv2016

Profiling adaptive immune repertoires across multiple human tissues by RNA Sequencing

Assay-based approaches provide a detailed view of the adaptive immune system by profiling T and B cell receptor repertoires. However, these methods come at a high cost and lack the scale of standard RNA sequencing (RNA-seq). Here we report the development of ImReP, a novel computational method for rapid and accurate profiling of the adaptive immune repertoire from regular RNA-Seq data. We applied it to 8,555 samples across 544 individuals from 53 tissues from the Genotype-Tissue Expression (GTEx v6) project. ImReP is able to efficiently extract TCR- and BCR- derived reads from the RNA-Seq data and accurately assemble the complementarity determining regions 3 (CDR3s), the most variable regions of B- and T-cell receptors determining their antigen specificity. Using ImReP, we have created the systematic atlas of immunological sequences for B- and T-cell repertoires across a broad range of tissue types, most of which have not been studied for B and T cell receptor repertoires. We have also examined the compositional similarities of clonal populations between the GTEx tissues to track the flow of T- and B- clonotypes across immune-related tissues, including secondary lymphoid organs and organs encompassing mucosal, exocrine, and endocrine sites. The atlas of T- and B-cell receptor receptors, freely available at https://sergheimangul.wordpress.com/atlas-immune-repertoires/, is the largest collection of CDR3 sequences and tissue types. We anticipate this recourse will enhance future studies in areas such as immunology and advance development of therapies for human diseases. ImReP is freely available at https://sergheimangul.wordpress.com/imrep/.

immunology↗
bioRxiv2018

Synthetic standards combined with error and bias correction improves the accuracy and quantitative resolution of antibody repertoire sequencing in human and naive memory B cells

High-throughput sequencing of immunoglobulin repertoires (Ig-seq) is a powerful method for quantitatively interrogating B cell receptor sequence diversity. When applied to human repertoires, Ig-seq provides insight into fundamental immunological questions, and can be implemented in diagnostic and drug discovery projects. However, a major challenge in Ig-seq is ensuring accuracy, as library preparation protocols and sequencing platforms can introduce substantial errors and bias that compromise immunological interpretation. Here, we have established an approach for performing highly accurate human Ig-seq by combining synthetic standards with a comprehensive error and bias correction pipeline. First, we designed a set of 85 synthetic antibody heavy chain standards (in vitro transcribed RNA) to assess correction workflow fidelity. Next, we adapted a library preparation protocol that incorporates unique molecular identifiers (UIDs) for error and bias correction which, when applied to the synthetic standards, resulted in highly accurate data. Finally, we performed Ig-seq on purified human circulating B cell subsets (naive and memory), combined with a cellular replicate sampling strategy. This strategy enabled robust and reliable estimation of key repertoire features such as clonotype diversity, germline segment and isotype subclass usage, and somatic hypermutation (SHM). We anticipate that our standards and error and bias correction pipeline will become a valuable tool for researchers to validate and improve accuracy in human Ig-seq studies, thus leading to potentially new insights and applications in human antibody repertoire profiling.

immunology↗
bioRxiv2018

Predicting humoral alloimmunity from differences in donor-recipient HLA surface electrostatic potential

In transplantation, development of humoral alloimmunity against donor HLA is a major cause of organ transplant failure but our ability to assess the immunological risk associated with a potential donor-recipient HLA combination is limited. We hypothesised that the capacity of donor HLA to induce a specific alloantibody response depends on their structural and physicochemical dissimilarity compared to recipient HLA. To test this hypothesis, we first developed a novel computational scoring system that enables quantitative assessment of surface electrostatic potential differences between donor and recipient HLA molecules at the tertiary structure level (electrostatic mismatch score-three dimensional; EMS-3D). We then examined humoral alloimmune responses in healthy females subjected to a standardised injection of donor lymphocytes from their male partner. This analysis showed a strong association between the EMS-3D of donor HLA and donor-specific alloantibody development; this relationship was strongest for HLA-DQ alloantigens. In the clinical transplantation setting, the immunogenic potential of HLA-DRB1 and -DQ mismatches expressed on donor kidneys, as assessed by their EMS-3D, was an independent predictor of development of donor-specific alloantibody after graft failure. Collectively, these findings demonstrate the translational potential of our approach to improve immunological risk assessment and to decrease the burden of humoral alloimmunity in organ transplantation.

immunology↗
bioRxiv2018

Performance of an IAVI-African Network of Clinical Research Laboratories in Standardized ELISpot and Peripheral Blood Mononuclear Cell Processing in Support of HIV Vaccine Clinical Trials

Immunological assays performed in different laboratories participating in multi-centre clinical trials must be standardized in order to generate comparable and reliable data. This entails standardized procedures for sample collection, processing, freezing and storage. The International AIDS Vaccine Initiative (IAVI) partnered with local institutions to establish Good Clinical Laboratory Practice (GCLP)-accredited laboratories to support clinical trials in Africa, Europe and Asia. Here we report on the performance of seven laboratories based in Africa and Europe in the interferon-gamma enzyme-linked immunospot (IFN-{gamma} ELISpot) assay and peripheral blood mononuclear cell (PBMC) processing over four years. Characterized frozen PBMC samples from 48 volunteer blood packs processed at a central laboratory were sent to participating laboratories. For each stimulus, there were 1751 assays performed over four years. 98% of these ELISpot data were within acceptable ranges with low responses to mock stimuli. There were no significant differences in ELISpot responses at five laboratories actively conducting immunological analyses in support of IAVI sponsored clinical trials or HIV research. In a separate study, 1,297 PBMC samples isolated from healthy HIV-1 negative participants in clinical trials of two prophylactic HIV vaccine candidates were analysed for PBMC yield from fresh blood and cell recovery and viability following freezing and thawing. 94 % and 96 % of samples had fresh PBMC viabilities and cell yields within the pre-defined acceptance criteria while for frozen PBMC, 99 % and 96 % of samples had acceptable viabilities and cell recoveries respectively, along with acceptable ELISpot responses in 95%. These findings demonstrate the competency of laboratories across different continents to generate comparable and reliable data in support of clinical trials.\n\nImportanceThere is a need for the establishment of an African network of laboratories to support large clinical trials across the continent to support and further the development of vaccine candidates against emerging infectious diseases such as Ebola, Zika and dengue viruses and the continued HIV-1 pandemic. This is particularly true in sub-Saharan Africa where the HIV-1 pandemic is most severe. In this report we have demonstrated by using standardized SOPs, training, equipment and reagents that GCLP-accredited clinical trial laboratories based in Africa and Europe can process clinical trial samples and maintain cell integrity and functionality demonstrated by IFN-{gamma} ELISpot testing, producing comparable and reliable data.

immunology↗
bioRxiv2018

Human T cell receptor occurrence patterns encode immune history, genetic background, and receptor specificity

The T cell receptor (TCR) repertoire encodes immune exposure history through the dynamic formation of immunological memory. Statistical analysis of repertoire sequencing data has the potential to decode disease associations from large cohorts with measured phenotypes. However, the repertoire perturbation induced by a given immunological challenge is conditioned on genetic background via major histocompatibility complex (MHC) polymorphism. We explore associations between MHC alleles, immune exposures, and shared TCRs in a large human cohort. Using a previously published repertoire sequencing dataset augmented with high-resolution MHC genotyping, our analysis reveals rich structure: striking imprints of common pathogens, clusters of co-occurring TCRs that may represent markers of shared immune exposures, and substantial variations in TCR-MHC association strength across MHC loci. Guided by atomic contacts in solved TCR:peptide-MHC structures, we identify sequence covariation between TCR and MHC. These insights and our analysis framework lay the groundwork for further explorations into TCR diversity.

immunology↗
bioRxiv2018

Late B lymphocyte action in dysfunctional tissue repair following kidney injury and transplantation

The mechanisms initiating the late immune response to allografts are poorly understood. Through transcriptome analysis of serial protocol biopsies in kidney transplant recipients, we found a tight correlation between the initial response to kidney injury and a late B lymphocyte signature associated with renal dysfunction and fibrosis, suggesting a link between dysfunctional repair and immunoreactivity. To specifically investigate the immunological consequences of dysfunctional repair, we followed the mouse kidney up to 18 months after ischemia/reperfusion. Even in the absence of foreign antigens we identified a sustained immune response in conjunction with the transition to chronic kidney damage. This tissue-driven immunological process involved both the innate and the adaptive immune system and eventually induced an antigen-driven proliferation, selection and maturation of B lymphocytes into broadly-reacting antibody secreting cells. These findings reveal an unappreciated role of dysfunctional tissue repair on local immunoregulation with a particular relevance for late transplantation immunobiology.

immunology↗
bioRxiv2018

An ODE-based mixed modelling approach for B- and T-cell dynamics induced by Varicella-Zoster Virus vaccines in adults shows higher T-cell proliferation with Shingrix compared to Varilrix

Clinical trials covering the immunogenicity of a vaccine aim to study the longitudinal dynamics of certain immune cells after vaccination. The corresponding immunogenicity datasets are mainly analyzed by the use of statistical (mixed effects) models. This paper proposes the use of mathematical ordinary differential equation (ODE) models, combined with a mixed effects approach. ODE models are capable of translating underlying immunological post vaccination processes into mathematical formulas thereby enabling a testable data analysis. Mixed models include both population-averaged parameters (fixed effects) and individual-specific parameters (random effects) for dealing with inter-and intra-individual variability, respectively.\n\nThis paper models B-cell and T-cell datasets of a phase I/II, open-label, randomized, parallel-group study in which the immunogenicity of a new Herpes Zoster vaccine (Shingrix) is compared with the original Varicella Zoster Virus vaccine (Varilrix).\n\nSince few significant correlations were assessed between the B-cell datasets and T-cell datasets, each dataset was modeled separately. By following a general approach to both the formulation of several different models and the procedure of selecting the most suitable model, we were able propose a mathematical ODE mixed-effects model for each dataset. As such, the use of ODE-based mixed effects models offers a suitable framework for handling longitudinal vaccine immunogenicity data. Moreover, it is possible to test differences in immunological processes between the two vaccines.\n\nWe found that the Shingrix vaccination schedule led to a more pronounced proliferation of T-cells, without a difference in T-cell decay rate compared to the Varilrix vaccination schedule.\n\nAuthor summaryUpon vaccination, B-cells and T-cells are activated to induce an immune response against the vaccine antigen at hand. In this paper, we study and compare the longitudinal dynamics of the specific immune response based on a vaccine trial in which the immunogenicity of a new Herpes Zoster vaccine (Shingrix) is compared with the original Varicella Zoster Virus vaccine (Varilrix). We combine the use of ordinary differential equations (ODEs), i.e. mathematical models which are used to describe the dynamics of the immune response, with advanced regression analyses enabling us to infer the model parameters describing these dynamics. The resulting ODE-based mixed effects models enable describing the immune response dynamics allowing for both inter-and intra-individual variability; comparing the dynamics induced by the two vaccines and studying the B-and T-cell interactions. We found a more pronounced proliferation of T-cells for the Shingrix vaccination schedule as compared to the Varilrix vaccination schedule. The proposed methodology offers a suitable framework for better understanding the immunogenicity of vaccines.

immunology↗
bioRxiv2018

Quantitative network organization of interactions emerging from the evolution of sequence and structure space of antibodies: the RADARS model

Adaptive immunity in vertebrates represents a complex self-organizing network of protein interactions that develops throughout the lifetime of an individual. While deep sequencing of the immune-receptor repertoire may reveal clonal relationships, functional interpretation of such data is hampered by the inherent limitations of converting sequence to structure to function. In this paper a novel model of antibody interaction space and network, termed radial adjustment of system resolution, RADARS, is proposed. The model is based on the radial growth of interaction affinity of antibodies towards an infinity of directions in structure space, each direction representing particular shapes of antigen epitopes. Levels of interaction affinity appear as free energy shells of the system, where hierarchical B-cell development and differentiation takes place. Equilibrium in this immunological thermodynamic system can be described by a power-law distribution of antibody free energies with an ideal network degree exponent of phi square, representing a scale-free fractal network of antibody interactions. Plasma cells are network hubs, memory B cells are nodes with intermediate degrees and B1 cells represent nodes with minimal degree. Thus, the RADARS model implies that antibody structure space develops against an infinite antigen structure space via interactions that are individually immunologically controlled, but on a systems level are organized by thermodynamic probability distributions. The network of interactions, which control B-cell development and differentiation, represent pathways of antigen removal on systems level. Understanding such quantitative network properties of the system should help the organization of sequence-derived structural data, offering the possibility to relate sequence to function in a complex, self-organizing biological system. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/438804v7_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@883eb7org.highwire.dtl.DTLVardef@cd7d5forg.highwire.dtl.DTLVardef@e225eeorg.highwire.dtl.DTLVardef@1286b49_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG

immunology↗
bioRxiv2016

Toxicity Management in CAR T cell therapy for B-ALL: Mathematical modelling as a new avenue for improvement.

Advances in genetic engineering have made it possible to reprogram individual immune cells to express receptors that recognise markers on tumour cell surfaces. The process of re-engineering T cell lymphocytes to express Chimeric Antigen Receptors (CARs), and then re-infusing the CAR-modified T cells into patients to treat various cancers is referred to as CAR T cell therapy. This therapy is being explored in clinical trials - most prominently for B Cell Acute Lymphoblastic Leukaemia (B-ALL), a common B cell malignancy, for which CAR T cell therapy has led to remission in up to 90% of patients. Despite this extraordinary response rate, however, potentially fatal inflammatory side effects occur in up to 10% of patients who have positive responses. Further, approximately 50% of patients who initially respond to the therapy relapse. Significant improvement is thus necessary before the therapy can be made widely available for use in the clinic.\n\nTo inform future development, we develop a mathematical model to explore interactions between CAR T cells, inflammatory toxicity, and individual patients tumour burdens in silico. This paper outlines the underlying system of coupled ordinary differential equations designed based on well-known immunological principles and widely accepted views on the mechanism of toxicity development in CAR T cell therapy for B-ALL - and reports in silico outcomes in relationship to standard and recently conjectured predictors of toxicity in a heterogeneous, randomly generated patient population. Our initial results and analyses are consistent with and connect immunological mechanisms to the clinically observed, counterintuitive hypothesis that initial tumour burden is a stronger predictor of toxicity than is the dose of CAR T cells administered to patients.\n\nWe outline how the mechanism of action in CAR T cell therapy can give rise to such non-standard trends in toxicity development, and demonstrate the utility of mathematical modelling in understanding the relationship between predictors of toxicity, mechanism of action, and patient outcomes.

Cancer Biology↗
bioRxiv2016

A Zika virus-associated microcephaly case with background exposure to STORCH agents

We present a case of microcephaly associated with Zika virus (ZIKV) in a chronological, multimodal imaging approach, illustrating the hallmarks of this disease on intrauterine morphological ultrasound, transfontanelar ultrasound, computed tomography (CT) and magnetic resonance imaging (MRI). We also determined the serological e immunological status of the mother and newborn. Noticeably, there was evidence for maternal infection by ZIKV, cytomegalovirus (CMV), herpes simplex virus (HSV), dengue virus (DENV) and Toxoplasma gondii, which indicates a possible role of previous exposures to STORCH agents and possibly comorbidities in the severe fetal congenital manifestation.\n\nAuthor SummaryZika virus (ZIKV) is an emerging mosquito-borne arbovirus causing dengue-like symptoms. In humans the illness is characterized by malaise and cutaneous rash and absent or short-termed fever. Recently, the Brazilian Ministry of Health reported an outbreak of microcephaly in Brazil as a delayed effect of the 2014-2015 outbreak of ZIKV in the Northeast of Brazil. A 20-fold increase in the notifications of newborns with microcephaly was documented during the second semester of 2015. This increase was almost immediately found to be associated with ZIKV infections, both in Brazil and, retrospectively, in French Polynesia. Herein we report a case of microcephaly associated with ZIKV and we also present evidence of other maternal infections. Our results indicated that, both mother and microcephaly infant had immunologic status compatible with previous exposure (in the mother) by STORCH agents. These indicate a possible role of previous exposures and possibly comorbidities in the severe fetal congenital manifestation. {square}

Microbiology↗
bioRxiv2016

PhysiCell: an Open Source Physics-Based Cell Simulator for 3-D Multicellular Systems

Many multicellular systems problems can only be understood by studying how cells move, grow, divide, interact, and die. Tissue-scale dynamics emerge from systems of many interacting cells as they respond to and influence their microenvironment. The ideal \"virtual laboratory\" for such multicellular systems simulates both the biochemical microenvironment (the \"stage\") and many mechanically and biochemically interacting cells (the \"players\" upon the stage).\n\nPhysiCell--physics-based multicellular simulator--is an open source agent-based simulator that provides both the stage and the players for studying many interacting cells in dynamic tissue microenvironments. It builds upon a multi-substrate biotransport solver to link cell phenotype to multiple diffusing substrates and signaling factors. It includes biologically-driven sub-models for cell cycling, apoptosis, necrosis, solid and fluid volume changes, mechanics, and motility \"out of the box.\" The C++ code has minimal dependencies, making it simple to maintain and deploy across platforms. PhysiCell has been parallelized with OpenMP, and its performance scales linearly with the number of cells. Simulations up to 105-106 cells are feasible on quad-core desktop workstations; larger simulations are attainable on single HPC compute nodes.\n\nWe demonstrate PhysiCell by simulating the impact of necrotic core biomechanics, 3-D geometry, and stochasticity on the dynamics of hanging drop tumor spheroids and ductal carcinoma in situ (DCIS) of the breast. We demonstrate stochastic motility, chemical and contact-based interaction of multiple cell types, and the extensibility of PhysiCell with examples in synthetic multicellular systems (a \"cellular cargo delivery\" system, with application to anti-cancer treatments), cancer heterogeneity, and cancer immunology. PhysiCell is a powerful multicellular systems simulator that will be continually improved with new capabilities and performance improvements. It also represents a significant independent code base for replicating results from other simulation platforms. The PhysiCell source code, examples, documentation, and support are available under the BSD license at http://PhysiCell.MathCancer.org and http://PhysiCell.sf.net.\n\nAuthor SummaryThis paper introduces PhysiCell: an open source, agent-based modeling framework for 3-D multicellular simulations. It includes a standard library of sub-models for cell fluid and solid volume changes, cycle progression, apoptosis, necrosis, mechanics, and motility. PhysiCell is directly coupled to a biotransport solver to simulate many diffusing substrates and cell-secreted signals. Each cell can dynamically update its phenotype based on its microenvironmental conditions. Users can customize or replace the included sub-models.\n\nPhysiCell runs on a variety of platforms (Linux, OSX, and Windows) with few software dependencies. Its computational cost scales linearly in the number of cells. It is feasible to simulate 500,000 cells on quad-core desktop workstations, and millions of cells on single HPC compute nodes. We demonstrate PhysiCell by simulating the impact of necrotic core biomechanics, 3-D geometry, and stochasticity on hanging drop tumor spheroids (HDS) and ductal carcinoma in situ (DCIS) of the breast. We demonstrate contact- and chemokine-based interactions among multiple cell types with examples in synthetic multicellular bioengineering, cancer heterogeneity, and cancer immunology.\n\nWe developed PhysiCell to help the scientific community tackle multicellular systems biology problems involving many interacting cells in multi-substrate microenvironments. PhysiCell is also an independent, cross-platform codebase for replicating results from other simulators.

systems biology↗
bioRxiv2016

Recent evolution of cestode growth suppression by threespine stickleback

Parasites can be a major cause of natural selection on hosts, which consequently evolve a variety of strategies to avoid, eliminate, or tolerate infection. When ecologically similar host populations present disparate infection loads, this natural variation can reveal immunological strategies underlying adaptation to infection and population divergence. For instance, the tapeworm Schistocephalus solidus persistently infects between 0% to 80% of threespine stickleback (Gasterosteus aculeatus) in lakes on Vancouver Island. To test whether these heterogeneous infection rates are due to evolved differences in immunity, we experimentally exposed lab-reared fish from high-and low-infection populations, which are not known to differ in natural exposure risk, to controlled doses of Schistocephalus. We observed heritable between-population differences in several immune traits: fish from the naturally uninfected population initiated a stronger granulocyte response to Schistocephalus infection, and their granulocytes constitutively generated threefold more reactive oxygen species (ROS). Despite these immunological differences, Schistocephalus was equally successful at establishing initial infections in both host populations. However, the low-infection fish dramatically suppressed tapeworm growth relative to high-infection fish, and parasite size was intermediate in F1 hybrid hosts. Our results show that stickleback recently evolved heritable variation in their capacity to suppress helminth growth. Comparative data from many from natural populations indicate that growth suppression is widespread but not universal and, when present, is associated with reduced infection prevalence. Host suppression of helminth somatic growth may be an important immune strategy that aids in parasite clearance, or in mitigating the fitness costs of persistent infection.\n\nSignificanceLarge parasites remain a persistent source of morbidity and mortality in humans, domesticated animals, and wildlife. Hosts are subject to strong natural selection to eliminate or tolerate these parasite infections. Here, we document the recent evolution of a striking form of resistance by a vertebrate host (threespine stickleback) against its cestode parasite (Schistocephalus solidus). After Pleistocene glacial retreat, marine stickleback colonized freshwater lakes, encountered Schistocephalus, and evolved varying levels of resistance to it. We show that a heavily-and a rarely-infected population of stickleback have similar resistance to Schistocephalus colonization, but rarely-infected fish suppress parasite growth by orders of magnitude. These populations represent ends of a natural continuum of cestode growth suppression, which is associated with reduced infection prevalence.

evolutionary biology↗
bioRxiv2017

Immuno-phenotypes of Pancreatic Ductal Adenocarcinoma: Metaanalysis of transcriptional subtypes

Pancreatic ductal adenocarcinoma (PDAC) is the most common malignancy of the pancreas and has one of the highest mortality rates of any cancer type with a 5-year survival rate of < 5% and median overall survival of typically six months from diagnosis. Recent transcriptional studies of PDAC have provided several competing stratifications of the disease. However, the development of therapeutic strategies will depend on a unique and coherent classification of PDAC. Here, we use an integrative meta-analysis of four different PDAC gene expression studies to derive the consensus PDAC classification. Despite the fact that immunotherapies have yet to have an impact in treatment of PDAC, the gene expression signatures that stratify PDAC across studies are immunologic. We define these as \"adaptive\", \"innate\" and \"immune-exclusion\" immunologic signatures, which are prognostic across independent cohorts. An appreciation of the immune composition of PDAC with prognostic significance is an opportunity to understand distinct immune escape mechanisms in development of the disease and design novel immune-oncology therapeutic strategies to overcome current barriers.

cancer biology↗