An integrated approach to the characterization of immune repertoires using AIMS: An Automated Immune Molecule Separator.

The adaptive immune system employs an array of receptors designed to respond with high specificity to pathogens or molecular aberrations faced by the host organism. Binding of these receptors to molecular fragments-collectively referred to as antigens-initiates immune responses. These antigenic targets are recognized in their native state on the surfaces of pathogens by antibodies, whereas T cell receptors (TCR) recognize processed antigens as short peptides, presented on major histocompatibility complex (MHC) molecules. Recent research has led to a wealth of immune repertoire data that are key to interrogating the nature of these molecular interactions. However, existing tools for the analysis of these large datasets typically focus on molecular sets of a single type, forcing researchers to separately analyze strongly coupled sequences of interacting molecules. Here, we introduce a software package for the integrated analysis of immune repertoire data, capable of identifying distinct biophysical differences in isolated TCR, MHC, peptide, antibody, and antigen sequence data. This integrated analytical approach allows for direct comparisons across immune repertoire subsets and provides a starting point for the identification of key interaction hotspots in complementary receptor-antigen pairs. The software (AIMS-Automated Immune Molecule Separator) is freely available as an open access package in GUI or command-line form.

Diversity in recognition and function of human γδ T cells.

As interest increases in harnessing the potential power of tissue-resident cells for human health and disease, γδ T cells have been thrust into the limelight due to their prevalence in peripheral tissues, their sentinel-like phenotypes, and their unique antigen recognition capabilities. This review focuses primarily on human γδ T cells, highlighting their distinctive characteristics including antigen recognition, function, and development, with an emphasis on where they differ from their αß T cell comparators, as well as from γδ T cell populations in the mouse. We review the antigens that have been identified thus far to regulate members of the human Vδ1 population and discuss what players are involved in transducing phosphoantigen-mediated signals to human Vγ9Vδ2 T cells. We also briefly review distinguishing features of these cells in terms of TCR signaling, use of coreceptor and costimulatory molecules and their development. These cells have great potential to be harnessed in a clinical setting, but caution must be taken to understand their unique capabilities and how they differ from the populations to which they are commonly compared.

Alpaca (Vicugna pacos), the first nonprimate species with a phosphoantigen-reactive Vγ9Vδ2 T cell subset.

Vγ9Vδ2 T cells are a major γδ T cell population in the human blood expressing a characteristic Vγ9JP rearrangement paired with Vδ2. This cell subset is activated in a TCR-dependent and MHC-unrestricted fashion by so-called phosphoantigens (PAgs). PAgs can be microbial [(E)-4-hydroxy-3-methyl-but-2-enyl pyrophosphate, HMBPP] or endogenous (isopentenyl pyrophosphate, IPP) and PAg sensing depends on the expression of B7-like butyrophilin (BTN3A, CD277) molecules. IPP increases in some transformed or aminobisphosphonate-treated cells, rendering those cells a target for Vγ9Vδ2 T cells in immunotherapy. Yet, functional Vγ9Vδ2 T cells have only been described in humans and higher primates. Using a genome-based study, we showed in silico translatable genes encoding Vγ9, Vδ2, and BTN3 in a few nonprimate mammalian species. Here, with the help of new monoclonal antibodies, we directly identified a T cell population in the alpaca (Vicugna pacos), which responds to PAgs in a BTN3-dependent fashion and shows typical TRGV9- and TRDV2-like rearrangements. T cell receptor (TCR) transductants and BTN3-deficient human 293T cells reconstituted with alpaca or human BTN3 or alpaca/human BTN3 chimeras showed that alpaca Vγ9Vδ2 TCRs recognize PAg in the context of human and alpaca BTN3. Furthermore, alpaca BTN3 mediates PAg recognition much better than human BTN3A1 alone and this improved functionality mapped to the transmembrane/cytoplasmic part of alpaca BTN3. In summary, we found remarkable similarities but also instructive differences of PAg-recognition by human and alpaca, which help in better understanding the molecular mechanisms controlling the activation of this prominent population of γδ T cells.

Nanodroplet Oligomers (NanDOs) of Aß40.

Using atomic force microscopy (AFM) and nuclear magnetic resonance (NMR), we describe small Aß40 oligomers, termed nanodroplet oligomers (NanDOs), which form rapidly and at Aß40 concentrations too low for fibril formation. NanDOs were observed in putatively monomeric solutions of Aß40 (e.g., by size exclusion chromatography). Video-rate scanning AFM shows rapid fusion and dissolution of small oligomer-sized particles, of which the median size increases with peptide concentration. In NMR (13C HSQC), a small number of chemical shifts changed with a change in peptide concentration. Paramagnetic relaxation enhancement NMR experiments also support the formation of NanDOs and suggest prominent interactions in hydrophobic domains of Aß40. Addition of Zn2+ to Aß40 solutions caused flocculation of NanDO-containing solutions, and selective loss of signal intensity in NMR spectra from residues in the N-terminal domain of Aß40. NanDOs may represent the earliest aggregated form of Aß40 in the aggregation pathway and are akin to premicelles in solutions of amphiphilies.

Butyrophilin3A proteins and Vγ9Vδ2 T cell activation.

Despite playing critical roles in the immune response and having significant potential in immunotherapy, γδ T cells have garnered little of the limelight. One major reason for this paradox is that their antigen recognition mechanisms are largely unknown, limiting our understanding of their biology and our potential to modulate their activity. One of the best-studied γδ subsets is the human Vγ9Vδ2T cell population, which predominates in peripheral blood and can combat both microbial infections and cancers. Although it has been known for decades that Vγ9Vδ2T cells respond to the presence of small pyrophosphate-based metabolites, collectively named phosphoantigens (pAgs), derived from microbial sources or malignant cells, the molecular basis for this response has been unclear. A major breakthrough in this area came with the identification of the Butyrophilin 3A (BTN3A) proteins, members of the Butyrophilin/Butyrophilin-like protein family, as mediators between pAgs and Vγ9Vδ2T cells. In this article, we review the most recent studies regarding pAg activation of human Vγ9Vδ2T cells, mainly focusing on the role of BTN3A as the pAg sensing molecule, as well as its potential impact on downstream events of the activation process.

Phosphoantigen-induced conformational change of butyrophilin 3A1 (BTN3A1) and its implication on Vγ9Vδ2 T cell activation.

Human Vγ9Vδ2 T cells respond to microbial infections as well as certain types of tumors. The key initiators of Vγ9Vδ2 activation are small, pyrophosphate-containing molecules called phosphoantigens (pAgs) that are present in infected cells or accumulate intracellularly in certain tumor cells. Recent studies demonstrate that initiation of the Vγ9Vδ2 T cell response begins with sensing of pAg via the intracellular domain of the butyrophilin 3A1 (BTN3A1) molecule. However, it is unknown how downstream events can ultimately lead to T cell activation. Here, using NMR spectrometry and molecular dynamics (MD) simulations, we characterize a global conformational change in the B30.2 intracellular domain of BTN3A1 induced by pAg binding. We also reveal by crystallography two distinct dimer interfaces in the BTN3A1 full-length intracellular domain, which are stable in MD simulations. These interfaces lie in close proximity to the pAg-binding pocket and contain clusters of residues that experience major changes of chemical environment upon pAg binding. This suggests that pAg binding disrupts a preexisting conformation of the BTN3A1 intracellular domain. Using a combination of biochemical, structural, and cellular approaches we demonstrate that the extracellular domains of BTN3A1 adopt a V-shaped conformation at rest, and that locking them in this resting conformation without perturbing their membrane reorganization properties diminishes pAg-induced T cell activation. Based on these results, we propose a model in which a conformational change in BTN3A1 is a key event of pAg sensing that ultimately leads to T cell activation.

CountASAP: A Lightweight, Easy to Use Python Package for Processing ASAPseq Data.

Declining sequencing costs coupled with the increasing availability of easy-to-use kits for the isolation of DNA and RNA transcripts from single cells have driven a rapid proliferation of studies centered around genomic and transcriptomic data. Simultaneously, a wealth of new techniques have been developed that utilize single cell technologies to interrogate a broad range of cell-biological processes. One recently developed technique, transposase-accessible chromatin with sequencing (ATAC) with select antigen profiling by sequencing (ASAPseq), provides a combination of chromatin accessibility assessments with measurements of cell-surface marker expression levels. While software exists for the characterization of these datasets, there currently exists no tool explicitly designed to reformat ASAP surface marker FASTQ data into a count matrix which can then be used for these downstream analyses. To address this, we created CountASAP, an easy-to-use Python package purposefully designed to transform FASTQ files from ASAP experiments into count matrices compatible with commonly-used downstream bioinformatic analysis packages. CountASAP takes advantage of the independence of the relevant data structures to perform fully parallelized matches of each sequenced read to user-supplied input ASAP oligos and unique cell-identifier sequences.

Conserved biophysical compatibility among the highly variable germline-encoded regions shapes TCR-MHC interactions.

T cells are critically important components of the adaptive immune system primarily responsible for identifying and responding to pathogenic challenges. This recognition of pathogens is driven by the interaction between membrane-bound T cell receptors (TCRs) and antigenic peptides presented on major histocompatibility complex (MHC) molecules. The formation of the TCR-peptide-MHC complex (TCR-pMHC) involves interactions among germline-encoded and hypervariable amino acids. Germline-encoded and hypervariable regions can form contacts critical for complex formation, but only interactions between germline-encoded contacts are likely to be shared across many of all the possible productive TCR-pMHC complexes. Despite this, experimental investigation of these interactions have focused on only a small fraction of the possible interaction space. To address this, we analyzed every possible germline-encoded TCR-MHC contact in humans, thereby generating the first comprehensive characterization of these largely antigen-independent interactions. Our computational analysis suggests that germline-encoded TCR-MHC interactions that are conserved at the sequence level are rare due to the high amino acid diversity of the TCR CDR1 and CDR2 loops, and that such conservation is unlikely to dominate the dynamic protein-protein binding interface. Instead, we propose that binding properties such as the docking orientation are defined by regions of biophysical compatibility between these loops and the MHC surface.

SARS-CoV-2 antibodies recognize 23 distinct epitopic sites on the receptor binding domain.

The COVID-19 pandemic and SARS-CoV-2 variants have dramatically illustrated the need for a better understanding of antigen (epitope)-antibody (paratope) interactions. To gain insight into the immunogenic characteristics of epitopic sites (ES), we systematically investigated the structures of 340 Abs and 83 nanobodies (Nbs) complexed with the Receptor Binding Domain (RBD) of the SARS-CoV-2 spike protein. We identified 23 distinct ES on the RBD surface and determined the frequencies of amino acid usage in the corresponding CDR paratopes. We describe a clustering method for analysis of ES similarities that reveals binding motifs of the paratopes and that provides insights for vaccine design and therapies for SARS-CoV-2, as well as a broader understanding of the structural basis of Ab-protein antigen (Ag) interactions.

SARS-CoV-2 antibodies recognize 23 distinct epitopic sites on the receptor binding domain.

The COVID-19 pandemic and SARS-CoV-2 variants have dramatically illustrated the need for a better understanding of antigen (epitope)-antibody (paratope) interactions. To gain insight into the immunogenic characteristics of epitopic sites (ES), we systematically investigated the structures of 340 Abs and 83 nanobodies (Nbs) complexed with the Receptor Binding Domain (RBD) of the SARS-CoV-2 spike protein. We identified 23 distinct ES on the RBD surface and determined the frequencies of amino acid usage in the corresponding CDR paratopes. We describe a clustering method for analysis of ES similarities that reveals binding motifs of the paratopes and that provides insights for vaccine design and therapies for SARS-CoV-2, as well as a broader understanding of the structural basis of Ab-protein antigen (Ag) interactions.

Biochemical and biophysical characterization of natural polyreactivity in antibodies.

To become specialized binders, antibodies undergo a process called affinity maturation to maximize their binding affinity. Despite this process, some antibodies retain low-affinity binding to diverse epitopes in a phenomenon called polyreactivity. Here we seek to understand the molecular basis of this polyreactivity in antibodies. Our results highlight that polyreactive antigen-binding fragments (Fabs) bind their targets with low affinities, comparable to T cell receptor recognition of autologous classical major histocompatibility complex. Extensive mutagenic studies find no singular amino acid residue or biochemical property responsible for polyreactive interaction, suggesting that polyreactive antibodies use multiple strategies for engagement. Finally, our crystal structures and all-atom molecular dynamics simulations of polyreactive Fabs show increased rigidity compared to their monoreactive relatives, forming a neutral and accessible platform for diverse antigens to bind. Together, these data support a cooperative strategy of rigid neutrality in establishing the polyreactive status of an antibody molecule.

Computational Assessment of Protein-Protein Binding Specificity within a Family of Synaptic Surface Receptors.

Atomic-level information is essential to explain the formation of specific protein complexes in terms of structure and dynamics. The set of Dpr and DIP proteins, which play a key role in the neuromorphogenesis in the nervous system of Drosophila melanogaster, offer a rich paradigm to learn about protein-protein recognition. Many members of the DIP subfamily cross-react with several members of the Dpr family and vice versa. While there exists a total of 231 possible Dpr-DIP heterodimer complexes from the 21 Dpr and 11 DIP proteins, only 57 "cognate" pairs have been detected by surface plasmon resonance (SPR) experiments, suggesting that the remaining 174 pairs have low or unreliable binding affinity. Our goal is to assess the performance of computational approaches to characterize the global set of interactions between Dpr and DIP proteins and identify the specificity of binding between each DIP with their corresponding Dpr binding partners. In addition, we aim to characterize how mutations influence the specificity of the binding interaction. In this work, a wide range of knowledge-based and physics-based approaches are utilized, including mutual information, linear discriminant analysis, homology modeling, molecular dynamics simulations, Poisson-Boltzmann continuum electrostatics calculations, and alchemical free energy perturbation to decipher the origin of binding specificity of the Dpr-DIP complexes examined. Ultimately, the results show that those two broad strategies are complementary, with different strengths and limitations. Biological inter-relations are more clearly revealed through knowledge-based approaches combining evolutionary and structural features, the molecular determinants controlling binding specificity can be predicted accurately with physics-based approaches based on atomic models.

Deaza-modification of MR1 ligands modulates recognition by MR1-restricted T cells.

MR1-restricted T (MR1T) cells recognize microbial small molecule metabolites presented on the MHC Class I-like molecule MR1 and have been implicated in early effector responses to microbial infection. As a result, there is considerable interest in identifying chemical properties of metabolite ligands that permit recognition by MR1T cells, for consideration in therapeutic or vaccine applications. Here, we made chemical modifications to known MR1 ligands to evaluate the effect on MR1T cell activation. Specifically, we modified 6,7-dimethyl-8-D-ribityllumazine (DMRL) to generate 6,7-dimethyl-8-D-ribityldeazalumazine (DZ), and then further derivatized DZ to determine the requirements for retaining MR1 surface stabilization and agonistic properties. Interestingly, the IFN-γ response toward DZ varied widely across a panel of T cell receptor (TCR)-diverse MR1T cell clones; while one clone was agnostic toward the modification, most displayed either an enhancement or depletion of IFN-γ production when compared with its response to DMRL. To gain insight into a putative mechanism behind this phenomenon, we used in silico molecular docking techniques for DMRL and its derivatives and performed molecular dynamics simulations of the complexes. In assessing the dynamics of each ligand in the MR1 pocket, we found that DMRL and DZ exhibit differential dynamics of both the ribityl moiety and the aromatic backbone, which may contribute to ligand recognition. Together, our results support an emerging hypothesis for flexibility in MR1:ligand-MR1T TCR interactions and enable further exploration of the relationship between MR1:ligand structures and MR1T cell recognition for downstream applications targeting MR1T cells.

Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of CDR loops.

Antibodies are critical components of adaptive immunity, binding with high affinity to pathogenic epitopes. Antibodies undergo rigorous selection to achieve this high affinity, yet some maintain an additional basal level of low affinity, broad reactivity to diverse epitopes, a phenomenon termed 'polyreactivity'. While polyreactivity has been observed in antibodies isolated from various immunological niches, the biophysical properties that allow for promiscuity in a protein selected for high-affinity binding to a single target remain unclear. Using a database of over 1000 polyreactive and non-polyreactive antibody sequences, we created a bioinformatic pipeline to isolate key determinants of polyreactivity. These determinants, which include an increase in inter-loop crosstalk and a propensity for a neutral binding surface, are sufficient to generate a classifier able to identify polyreactive antibodies with over 75% accuracy. The framework from which this classifier was built is generalizable, and represents a powerful, automated pipeline for future immune repertoire analysis.

To defend itself against bacteria and viruses, the body depends on a group of proteins known as antibodies. Each subset of antibodies undergoes a rigorous training regimen to ensure it recognizes a single epitope well ­ that is, one specific region on the surface of foreign, harmful organisms. Most antibodies stick extremely tightly to their one unique epitope, but some can also weakly bind to molecules that are vastly different from their main trained targets. This feature ­ known as polyreactivity ­ can in some cases help the immune system fight against multiple strains of viruses. On the other hand, when antibodies are designed in the laboratory to treat diseases, this characteristic can sometimes lead to the failure of pre-clinical trials. Yet it is currently unclear why some antibodies are polyreactive when others are not. To investigate this question, Boughter et al. compared over 1,000 polyreactive and non-polyreactive antibody sequences from a large database, revealing differences in the physical properties of the region of the antibodies that attaches to epitopes. Using these defining features, Boughter et al. went on to design a new piece of freely available, automated software that could predict which antibodies would be polyreactive more than 75% of the time. Such software could ultimately help to guide the design of antibody-based treatments, while bypassing the need for costly laboratory tests.

The Hypervariable Loops of Free TCRs Sample Multiple Distinct Metastable Conformations in Solution.

CD4+ and CD8+ αß T cell antigen recognition is determined by the interaction between the TCR Complementarity Determining Region (CDR) loops and the peptide-presenting MHC complex. These T cells are known for their ability to recognize multiple pMHC complexes, and for a necessary promiscuity that is required for their selection and function in the periphery. Crystallographic studies have previously elucidated the role of structural interactions in TCR engagement, but our understanding of the dynamic process that occurs during TCR binding is limited. To better understand the dynamic states that exist for TCR CDR loops in solution, and how this relates to their states when in complex with pMHC, we simulated the 2C T cell receptor in solution using all-atom molecular dynamics in explicit water and constructed a Markov State Model for each of the CDR3α and CDR3ß loops. These models reveal multiple metastable states for the CDR3 loops in solution. Simulation data and metastable states reproduce known CDR3ß crystal conformations, and reveal several novel conformations suggesting that CDR3ß bound states are the result of search processes from nearby pre-existing equilibrium conformational states. Similar simulations of the invariant, Type I Natural Killer T cell receptor NKT15, which engages the monomorphic, MHC-like CD1d ligand, demonstrate that iNKT TCRs also have distinct states, but comparatively restricted degrees of motion.

Influence of Cholesterol on Phospholipid Bilayer Structure and Dynamics.

In this study, the influence of cholesterol on lipid bilayers is investigated by changing phospholipid headgroup, cholesterol concentration, chain saturation, and temperature. Molecular dynamics (MD) simulations were used to characterize bilayers containing phosphatidylcholine (PC) head groups with either fully saturated dimyristoyl (DM) or monounsaturated dioleoyl (DO) acyl chains and cholesterol concentrations ranging from 5 to 50%. To further explore the effects of cholesterol on bilayers with different head groups, we also performed MD simulations of bilayer systems having 15% cholesterol with phosphatidic acid (PA), phosphatidylethanolamine (PE), phosphatidylglycerol (PG), phosphatidylinositol (PI), and phosphatidylserine (PS), each having DM chains and at a temperature above the solid gel phase transition. Additionally, bilayers of DMPA, DMPE, and DMPS with 15% cholesterol were simulated at temperatures below the solid gel phase transition temperatures. Compared to membranes without cholesterol, cholesterol in the model bilayers increases chain order in bilayers with the highest order in the liquid ordered and solid gel phases. Head group properties and acyl chain saturation are also found to critically impact bilayer dynamics, largely through the formation of hydrogen bonds between membrane components. These results provide a better understanding of the basic characteristics on structure and dynamics of cholesterol-containing membranes by revealing molecular details of interactions between cholesterol and phospholipids as well as add to the library of simulation data necessary for the MD community to accurately represent relevant models of atomic-scale systems.

A simple approach to spectrally resolved fluorescence and bright field microscopy over select regions of interest.

A standard wide field inverted microscope was converted to a spatially selective spectrally resolved microscope through the addition of a polarizing beam splitter, a pair of polarizers, an amplitude-mode liquid crystal-spatial light modulator, and a USB spectrometer. The instrument is capable of simultaneously imaging and acquiring spectra over user defined regions of interest. The microscope can also be operated in a bright-field mode to acquire absorption spectra of micron scale objects. The utility of the instrument is demonstrated on three different samples. First, the instrument is used to resolve three differently labeled fluorescent beads in vitro. Second, the instrument is used to recover time dependent bleaching dynamics that have distinct spectral changes in the cyanobacteria, Synechococcus leopoliensis UTEX 625. Lastly, the technique is used to acquire the absorption spectra of CH3NH3PbBr3 perovskites and measure differences between nanocrystal films and micron scale crystals.

Mesoscale inhomogeneities in aqueous solutions of small amphiphilic molecules.

Small amphiphilic molecules, also known as hydrotropes, are too small to form micelles in aqueous solutions. However, aqueous solutions of nonionic hydrotropes show the presence of a dynamic, loose, non-covalent clustering in the water-rich region, This clustering can be viewed as "micelle-like structural fluctuations". Although these fluctuations are short ranged (approximately 1 nm) and short lived (10 ps-50 ps), they may lead to thermodynamic anomalies. In addition, many experiments on aqueous solutions of hydrotropes show the occasional presence of mesoscale (approximately 100 nm) inhomogeneities. We have combined results obtained from molecular dynamics simulations, small-angle neutron scattering, and dynamic light-scattering experiments carried out on tertiary butyl alcohol (hydrotrope)-water solutions and on tertiary butyl alcohol-water-cyclohexane (hydrophobe) solutions to elucidate the nature and structure of these inhomogeneities. We have shown that stable mesoscale inhomogeneities occur in aqueous solutions of nonionic hydrotropes only when the solution contains a third, more hydrophobic, component. Moreover, these inhomogeneities exist in ternary systems only in the concentration range where structural fluctuations and thermodynamic anomalies are observed in the binary water-hydrotrope solutions. Addition of a hydrophobe seems to stabilize the water-hydrotrope structural fluctuations, and leads to the formation of larger (mesoscopic) droplets. The structure of these mesoscopic droplets is such that they have a hydrophobe-rich core, surrounded by a hydrogen-bonded shell of water and hydrotrope molecules. These droplets can be extremely long-lived, being stable for over a year. We refer to the phenomenon of formation of mesoscopic droplets in aqueous solutions of nonionic hydrotropes containing hydrophobes, as mesoscale solubilization. This phenomenon may represent a ubiquitous feature of nonionic hydrotropes that exhibit clustering in water, and may have important practical applications in areas, such as drug delivery, where the replacement of traditional surfactants may be necessary.