William DeWitt

Immunosequencing identifies signatures of cytomegalovirus exposure history and HLA-mediated effects on the T cell repertoire

An individuals T cell repertoire dynamically encodes their pathogen exposure history. To determine whether pathogen exposure signatures can be identified by documenting public T cell receptors (TCRs), we profiled the T cell repertoire of 666 subjects with known cytomegalovirus (CMV) serostatus by immunosequencing. We developed a statistical classification framework that could diagnose CMV status from the resulting catalog of TCRβ sequences with high specificity and sensitivity in both the original cohort and a validation cohort of 120 different subjects. We also confirmed that three of the identified CMV-associated TCRβ molecules bind CMV in vitro, and, moreover, we used this approach to accurately predict the HLA-A and HLA-B alleles of most subjects in the first cohort. As all memory T cell responses are encoded in the common format of somatic TCR recombination, our approach could potentially be generalized to a wide variety of disease states, as well as other immunological phenotypes, as a highly parallelizable diagnostic strategy.

Dynamics of the Cytotoxic T Cell Response to a Model of Acute Viral Infection

ABSTRACT A detailed characterization of the dynamics and breadth of the immune response to an acute viral infection, as well as the determinants of recruitment to immunological memory, can greatly contribute to our basic understanding of the mechanics of the human immune system and can ultimately guide the design of effective vaccines. In addition to neutralizing antibodies, T cells have been shown to be critical for the effective resolution of acute viral infections. We report the first in-depth analysis of the dynamics of the CD8+ T cell repertoire at the level of individual T cell clonal lineages upon vaccination of human volunteers with a single dose of YF-17D. This live attenuated yellow fever virus vaccine yields sterile, long-term immunity and has been previously used as a model to understand the immune response to a controlled acute viral infection. We identified and enumerated unique CD8+ T cell clones specifically induced by this vaccine through a combined experimental and statistical approach that included high-throughput sequencing of the CDR3 variable region of the T cell receptor β-chain and an algorithm that detected significantly expanded T cell clones. This allowed us to establish that (i) on average, ∼2,000 CD8+ T cell clones were induced by YF-17D, (ii) 5 to 6% of the responding clones were recruited to long-term memory 3 months postvaccination, (iii) the most highly expanded effector clones were preferentially recruited to the memory compartment, and (iv) a fraction of the YF-17D-induced clones could be identified from peripheral blood lymphocytes solely by measuring clonal expansion. IMPORTANCE The exhaustive investigation of pathogen-induced effector T cells is essential to accurately quantify the dynamics of the human immune response. The yellow fever vaccine (YFV) has been broadly used as a model to understand how a controlled, self-resolving acute viral infection induces an effective and long-term protective immune response. Here, we extend this previous work by reporting the identity of activated effector T cell clones that expand in response to the YFV 2 weeks postvaccination (as defined by their unique T cell receptor gene sequence) and by tracking clones that enter the memory compartment 3 months postvaccination. This is the first study to use high-throughput sequencing of immune cells to characterize the breadth of the antiviral effector cell response and to determine the contribution of unique virus-induced clones to the long-lived memory T cell repertoire. Thus, this study establishes a benchmark against which future vaccines can be compared to predict their efficacy.

A Public Database of Memory and Naive B-Cell Receptor Sequences.

The vast diversity of B-cell receptors (BCR) and secreted antibodies enables the recognition of, and response to, a wide range of epitopes, but this diversity has also limited our understanding of humoral immunity. We present a public database of more than 37 million unique BCR sequences from three healthy adult donors that is many fold deeper than any existing resource, together with a set of online tools designed to facilitate the visualization and analysis of the annotated data. We estimate the clonal diversity of the naive and memory B-cell repertoires of healthy individuals, and provide a set of examples that illustrate the utility of the database, including several views of the basic properties of immunoglobulin heavy chain sequences, such as rearrangement length, subunit usage, and somatic hypermutation positions and dynamics.

Nonlinear behaviors of contrast agents relevant to diagnostic and therapeutic applications

The nonlinear properties of an encapsulated microbubble of a contrast agent were studied theoretically and experimentally. A modified nonlinear differential equation (Herring equation) was used to describe the radial oscillation of the microbubble and solved numerically. It was found that the nonlinear resonance frequency, at which the peak radial oscillation amplitude occurs, was a decreasing function of the acoustic amplitude of a driving ultrasonic pulse. Optical images of the contrast agent microbubbles under various ultrasonic exposure conditions: 1. sham exposure; 2. 2-MHz spatial peak acoustic pressure = 200 kPa, I(SATA) = 260 mW/cm(2), duty cycle = 7.5%, repetition period = 0.0266 ms; 3. 0.5-MHz spatial peak acoustic pressure = 200 kPa, I(SATA) = 130 mW/cm(2), duty cycle = 7.5%, repetition period = 0.1067 ms; have also shown that the lower-frequency ultrasound (US) excitation (0.5 MHz) is more effective in disruption of the microbubbles due to acoustic inertial cavitation than the higher frequency US (2 MHz).

Immunosequencing reveals diagnostic signatures of chronic viral infection in T cell memory

B and T cells expand clonally in response to pathogenic infection, and their descendants, which share the same receptor sequence, can persist for years, forming the basis of immunological memory. While most T cell receptor (TCR) sequences are seen very rarely, ‘public’ TCRs are present in many individuals. Using a combination of high throughput immunosequencing, statistical association of particular TCRs with disease status, and machine learning, we identified of a set of public TCRs that discriminates cytomegalovirus (CMV) infection status with high accuracy. This pathogen-specific diagnostic tool uses a very general assay that relies only on a training cohort coupled with immunosequencing and sophisticated data analysis. Since all memory T cell responses are encoded in the common format of somatic TCR rearrangements, a key advantage of reading T cell memory to predict disease status is that this approach should apply to a wide variety of diseases. The underlying dataset is the largest collection of TCRs ever published, including ∼300 gigabases of sequencing data and ∼85 million unique TCRs across 640 HLA-typed individuals, which constitutes by far the largest such collection ever published. We expect these data to be a valuable public resource for researchers studying the TCR repertoire.

Using Genotype Abundance to Improve Phylogenetic Inference

Abstract Modern biological techniques enable very dense genetic sampling of unfolding evolutionary histories, and thus frequently sample some genotypes multiple times. This motivates strategies to incorporate genotype abundance information in phylogenetic inference. In this article, we synthesize a stochastic process model with standard sequence‐based phylogenetic optimality, and show that tree estimation is substantially improved by doing so. Our method is validated with extensive simulations and an experimental single‐cell lineage tracing study of germinal center B cell receptor affinity maturation.

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.

A Diverse Lipid Antigen–Specific TCR Repertoire Is Clonally Expanded during Active Tuberculosis

Human T cells that recognize lipid Ags presented by highly conserved CD1 proteins often express semi-invariant TCRs, but the true diversity of lipid Ag–specific TCRs remains unknown. We use CD1b tetramers and high-throughput immunosequencing to analyze thousands of TCRs from ex vivo–sorted or in vitro–expanded T cells specific for the mycobacterial lipid Ag, glucose monomycolate. Our results reveal a surprisingly diverse repertoire resulting from editing of germline-encoded gene rearrangements analogous to MHC-restricted TCRs. We used a distance-based metric (TCRDist) to show how this diverse TCR repertoire builds upon previously reported conserved motifs by including subject-specific TCRs. In a South African cohort, we show that TCRDist can identify clonal expansion of diverse glucose monomycolate–specific TCRs and accurately distinguish patients with active tuberculosis from control subjects. These data suggest that similar mechanisms govern the selection and expansion of peptide and lipid Ag–specific T cells despite the nonpolymorphic nature of CD1.

Unbiased Definition Of A Shared T-Cell Receptor Motif Enables Population-Based Studies Of Tuberculosis

Peptide-specific T cells that are restricted by highly polymorphic major histocompatibility complex (MHC) proteins express diverse T-cell receptors (TCRs) that are rarely shared among unrelated individuals. T-cells can also recognize bacterial lipid antigens that bind the relatively non-polymorphic CD1 family of proteins. However, genetic variation in human CD1 genes and TCR diversity expressed by CD1-restricted T-cells have not been quantitatively determined. Here, we show that CD1B is nearly nucleotide-identical across all five continental ancestry groups, providing evidence for purifying selection during human evolution. We used CD1B tetramers loaded with a mycobacterial glycolipid antigen to isolate T-cells from four genetically unrelated South African adults and cataloged thousands of TCRs from in-vitro expanded T-cells using immunosequencing. We identified highly conserved motifs that were co-expressed as a functional heterodimer and significantly enriched among tetramer-positive T-cells sorted directly from peripheral blood. Finally, we show that frequencies of these TCR motifs are increased in the blood of patients with active tuberculosis compared to uninfected controls, a finding that is confirmed by ex-vivo frequencies of tetramer-positive T-cells determined by flow cytometry. These data provide a framework for unbiased definition of TCRs targeting lipid antigens, which can be tested for clinical associations independently of host genetic background. Brief Summary We used human genetics and immunosequencing to define a shared T-cell receptor motif that is specific for a mycobacterial lipid antigen and associated with tuberculosis independently of host genetic background.

Imaging Protein Statistical Substate Occupancy in a Spectrum-Function Phase Space

Hemeprotein ligand rebinding studies reveal varying IR absorbance and rebinding functions across a cryogenic ensemble. Since IR-active vibrations and rebinding barriers couple to structural coordinates, spectral and functional heterogeneity arise from conformational heterogeneity. Modeling rebinding data as a spectrally resolved superposition of first-order rate processes and employing maximum entropy regularization, protein heterogeneity is imaged as an ensemble occupancy of a spectrum-function phase space. Results from myoglobin rebinding carbon monoxide are discussed.