Brian A. Kidd

Structural Basis for Mechanical Force Regulation of the Adhesin FimH via Finger Trap-like β Sheet Twisting

The Escherichia coli fimbrial adhesive protein, FimH, mediates shear-dependent binding to mannosylated surfaces via force-enhanced allosteric catch bonds, but the underlying structural mechanism was previously unknown. Here we present the crystal structure of FimH incorporated into the multiprotein fimbrial tip, where the anchoring (pilin) domain of FimH interacts with the mannose-binding (lectin) domain and causes a twist in the beta sandwich fold of the latter. This loosens the mannose-binding pocket on the opposite end of the lectin domain, resulting in an inactive low-affinity state of the adhesin. The autoinhibition effect of the pilin domain is removed by application of tensile force across the bond, which separates the domains and causes the lectin domain to untwist and clamp tightly around the ligand like a finger-trap toy. Thus, beta sandwich domains, which are common in multidomain proteins exposed to tensile force in vivo, can undergo drastic allosteric changes and be subjected to mechanical regulation.

FimH Forms Catch Bonds That Are Enhanced by Mechanical Force Due to Allosteric Regulation

The bacterial adhesive protein, FimH, is the most common adhesin of Escherichia coli and mediates weak adhesion at low flow but strong adhesion at high flow. There is evidence that this occurs because FimH forms catch bonds, defined as bonds that are strengthened by tensile mechanical force. Here, we applied force to single isolated FimH bonds with an atomic force microscope in order to test this directly. If force was loaded slowly, most of the bonds broke up at low force (<60 piconewtons of rupture force). However, when force was loaded rapidly, all bonds survived until much higher force (140–180 piconewtons of rupture force), behavior that indicates a catch bond. Structural mutations or pretreatment with a monoclonal antibody, both of which allosterically stabilize a high affinity conformation of FimH, cause all bonds to survive until high forces regardless of the rate at which force is applied. Pretreatment of FimH bonds with intermediate force has the same strengthening effect on the bonds. This demonstrates that FimH forms catch bonds and that tensile force induces an allosteric switch to the high affinity, strong binding conformation of the adhesin. The catch bond behavior of FimH, the amount of force needed to regulate FimH, and the allosteric mechanism all provide insight into how bacteria bind and form biofilms in fluid flow. Additionally, these observations may provide a means for designing antiadhesive mechanisms.

Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records

Secondary use of electronic health records (EHRs) promises to advance clinical research and better inform clinical decision making. Challenges in summarizing and representing patient data prevent widespread practice of predictive modeling using EHRs. Here we present a novel unsupervised deep feature learning method to derive a general-purpose patient representation from EHR data that facilitates clinical predictive modeling. In particular, a three-layer stack of denoising autoencoders was used to capture hierarchical regularities and dependencies in the aggregated EHRs of about 700,000 patients from the Mount Sinai data warehouse. The result is a representation we name “deep patient”. We evaluated this representation as broadly predictive of health states by assessing the probability of patients to develop various diseases. We performed evaluation using 76,214 test patients comprising 78 diseases from diverse clinical domains and temporal windows. Our results significantly outperformed those achieved using representations based on raw EHR data and alternative feature learning strategies. Prediction performance for severe diabetes, schizophrenia, and various cancers were among the top performing. These findings indicate that deep learning applied to EHRs can derive patient representations that offer improved clinical predictions, and could provide a machine learning framework for augmenting clinical decision systems.

Proteomic analysis of secreted proteins in early rheumatoid arthritis: anti-citrulline autoreactivity is associated with up regulation of proinflammatory cytokines

Objectives: To identify peripheral blood autoantibody and cytokine profiles that characterise clinically relevant subgroups of patients with early rheumatoid arthritis using arthritis antigen microarrays and a multiplex cytokine assay. Methods: Serum samples from 56 patients with a diagnosis of rheumatoid arthritis of <6 months’ duration were tested. Cytokine profiles were also determined in samples from patients with psoriatic arthritis (PsA) and ankylosing spondylitis (n = 21), and from healthy individuals (n = 19). Data were analysed using Kruskal–Wallis test with Dunn’s adjustment for multiple comparisons, linear correlation tests, significance analysis of microarrays (SAM) and hierarchical clustering software. Results: Distinct antibody profiles were associated with subgroups of patients who exhibited high serum levels of tumour necrosis factor (TNF)α, interleukin (IL)1β, IL6, IL13, IL15 and granulocyte macrophage colony-stimulating factor. Significantly increased autoantibody reactivity against citrullinated epitopes was observed in patients within the cytokine “high” subgroup. Increased levels of TNFα, IL1α, IL12p40 and IL13, and the chemokines eotaxin/CCL11, monocyte chemoattractant protein-1 and interferon-inducible protein 10, were present in early rheumatoid arthritis as compared with controls (p<0.001). Chemokines showed some of the most impressive differences. Only IL8/CXCL8 concentrations were higher in patients with PsA/ankylosing spondylitis (p = 0.02). Conclusions: Increased blood levels of proinflammatory cytokines are associated with autoantibody targeting of citrullinated antigens and surrogate markers of disease activity in patients with early rheumatoid arthritis. Proteomic analysis of serum autoantibodies, cytokines and chemokines enables stratification of patients with early rheumatoid arthritis into molecular subgroups.

Phase 2 trial of a DNA vaccine encoding myelin basic protein for multiple sclerosis

To evaluate the efficacy and safety of BHT‐3009 in relapsing‐remitting multiple sclerosis (MS) and to confirm that BHT‐3009 causes immune tolerance.

combinatorial tetramer staining and mass cytometry analysis facilitate t -cell epitope mapping and characterization

It is currently not possible to predict which epitopes will be recognized by T cells in different individuals. This is a barrier to the thorough analysis and understanding of T-cell responses after vaccination or infection. Here, by combining mass cytometry with combinatorial peptide–MHC tetramer staining, we have developed a method allowing the rapid and simultaneous identification and characterization of T cells specific for many epitopes. We use this to screen up to 109 different peptide–MHC tetramers in a single human blood sample, while still retaining at least 23 labels to analyze other markers of T-cell phenotype and function. Among 77 candidate rotavirus epitopes, we identified six T-cell epitopes restricted to human leukocyte antigen (HLA)-A*0201 in the blood of healthy individuals. T cells specific for epitopes in the rotavirus VP3 protein displayed a distinct phenotype and were present at high frequencies in intestinal epithelium. This approach should be useful for the comprehensive analysis of T-cell responses to infectious diseases or vaccines.

Cytomegalovirus infection enhances the immune response to influenza

Cytomegalovirus infection of young adult humans and mice enhances immune responses to influenza. CMV boosts immune response in the young Cytomegalovirus (CMV) has long been thought of as a sleeper agent—present in a latent form in most people but dangerous when activated in immunosuppressed individuals. Now, Furman et al. look more closely at the effects of CMV infection in young, healthy people. They find that in contrast to aged individuals where CMV infection decreased response to flu vaccine, CMV infection actually enhanced the response to flu vaccine in young adults. This beneficial effect was also seen in mice. These data suggest that latent CMV infection may be beneficial to the host, and provide a possible explanation for the prevalence of CMV infection worldwide. Cytomegalovirus (CMV) is a β-herpesvirus present in a latent form in most people worldwide. In immunosuppressed individuals, CMV can reactivate and cause serious clinical complications, but the effect of the latent state on healthy people remains elusive. We undertook a systems approach to understand the differences between seropositive and negative subjects and measured hundreds of immune system components from blood samples including cytokines and chemokines, immune cell phenotyping, gene expression, ex vivo cell responses to cytokine stimuli, and the antibody response to seasonal influenza vaccination. As expected, we found decreased responses to vaccination and an overall down-regulation of immune components in aged individuals regardless of CMV status. In contrast, CMV-seropositive young adults exhibited enhanced antibody responses to influenza vaccination, increased CD8+ T cell sensitivity, and elevated levels of circulating interferon-γ compared to seronegative individuals. Experiments with young mice infected with murine CMV also showed significant protection from an influenza virus challenge compared with uninfected animals, although this effect declined with time. These data show that CMV and its murine equivalent can have a beneficial effect on the immune response of young, healthy individuals, which may explain the ubiquity of CMV infection in humans and many other species.

Interdomain Interaction in the FimH Adhesin of Escherichia coli Regulates the Affinity to Mannose

FimH is a mannose-specific adhesin located on the tip of type 1 fimbriae of Escherichia coli that is capable of mediating shear-enhanced bacterial adhesion. FimH consists of a fimbria-associated pilin domain and a mannose-binding lectin domain, with the binding pocket positioned opposite the interdomain interface. By using the yeast two-hybrid system, purified lectin and pilin domains, and docking simulations, we show here that the FimH domains interact with one another. The affinity for mannose is greatly enhanced (up to 300-fold) in FimH variants in which the interdomain interaction is disrupted by structural mutations in either the pilin or lectin domains. Also, affinity to mannose is dramatically enhanced in isolated lectin domains or in FimH complexed with the chaperone molecule that is wedged between the domains. Furthermore, FimH with native structure mediates weak binding at low shear stress but shifts to strong binding at high shear, whereas FimH with disrupted interdomain contacts (or the isolated lectin domain) mediates strong binding to mannose-coated surfaces even under low shear. We propose that interactions between lectin and pilin domains decrease the affinity of the mannose-binding pocket via an allosteric mechanism. We further suggest that mechanical force at high shear stress separates the two domains, allowing the lectin domain to switch from a low affinity to a high affinity state. This shift provides a mechanism for FimH-mediated shear-enhanced adhesion by enabling the adhesin to form catch bond-like interactions that are longer lived at high tensile force.

Epitope spreading to citrullinated antigens in mouse models of autoimmune arthritis and demyelination

IntroductionAnti-citrullinated protein antibodies have a diagnostic role in rheumatoid arthritis (RA); however, little is known about their origins and contribution to pathogenesis. Citrullination is the post-translational conversion of arginine to citrulline by peptidyl arginine deiminase, and increased citrullination of proteins is observed in the joint tissue in RA and in brain tissue in multiple sclerosis (MS).MethodsWe applied synovial and myelin protein arrays to examine epitope spreading of B cell responses to citrullinated epitopes in both the collagen-induced arthritis (CIA) model for RA and the experimental autoimmune encephalomyelitis (EAE) model for MS. Synovial and myelin protein arrays contain a spectrum of proteins and peptides, including native and citrullinated forms, representing candidate autoantigens in RA and MS, respectively. We applied these arrays to characterise the specificity of autoantibodies in serial serum samples derived from mice with acute and chronic stages of CIA and EAE.ResultsIn samples from pre-disease CIA and acute-disease EAE, we observed autoantibody targeting of the immunising antigen and responses to a limited set of citrullinated epitopes. Over the course of diseases, the autoantibody responses expanded to target multiple citrullinated epitopes in both CIA and EAE. Using immunoblotting and mass spectrometry analysis, we identified citrullination of multiple polypeptides in CIA joint and EAE brain tissue that have not previously been described as citrullinated.ConclusionsOur results suggest that anti-citrulline antibody responses develop in the early stages of CIA and EAE, and that autoimmune inflammation results in citrullination of joint proteins in CIA and brain proteins in EAE, thereby creating neoantigens that become additional targets in epitope spreading of autoimmune responses.

Unifying immunology with informatics and multiscale biology.

The immune system is a highly complex and dynamic system. Historically, the most common scientific and clinical practice has been to evaluate its individual components. This kind of approach cannot always expose the interconnecting pathways that control immune-system responses and does not reveal how the immune system works across multiple biological systems and scales. High-throughput technologies can be used to measure thousands of parameters of the immune system at a genome-wide scale. These system-wide surveys yield massive amounts of quantitative data that provide a means to monitor and probe immune-system function. New integrative analyses can help synthesize and transform these data into valuable biological insight. Here we review some of the computational analysis tools for high-dimensional data and how they can be applied to immunology.