Digital wearable insole-based identification of knee arthropathies and gait signatures using machine learning

Gait is impaired in musculoskeletal conditions, such as knee arthropathy. Gait analysis is used in clinical practice to inform diagnosis and to monitor disease progression or intervention response. However, clinical gait analysis relies on subjective visual observation of walking, as objective gait analysis has not been possible within clinical settings due to the expensive equipment, large-scale facilities, and highly trained staff required. Relatively low-cost wearable digital insoles may offer a solution to these challenges. In this work, we demonstrate how a digital insole measuring osteoarthritis-specific gait signatures yields similar results to the clinical gait-lab standard. To achieve this, we constructed a machine learning model, trained on force plate data collected in participants with knee arthropathy and controls. This model was highly predictive of force plate data from a validation set (area under the receiver operating characteristics curve [auROC] = 0.86; area under the precision-recall curve [auPR] = 0.90) and of a separate, independent digital insole dataset containing control and knee osteoarthritis subjects (auROC = 0.83; auPR = 0.86). After showing that digital insole derived gait characteristics are comparable to traditional gait measurements, we next showed that a single stride of raw sensor time series data could be accurately assigned to each subject, highlighting that individuals using digital insoles can be identified by their gait characteristics. This work provides a framework for a promising alternative to traditional clinical gait analysis methods, adds to the growing body of knowledge regarding wearable technology analytical pipelines, and supports clinical development of at-home gait assessments, with the potential to improve the ease, frequency, and depth of patient monitoring.

Differential modulation of allergic rhinitis nasal transcriptome by dupilumab and allergy immunotherapy

BACKGROUND

Nasal epithelial cells are important regulators of barrier function and immune signaling; however, in allergic rhinitis (AR) these functions can be disrupted by inflammatory mediators. We aimed to better discern AR disease mechanisms using transcriptome data from nasal brushing samples from individuals with and without AR.

METHODS

Data were drawn from a feasibility study of individuals with and without AR to Timothy grass and from a clinical trial evaluating 16 weeks of treatment with the following: dupilumab, a monoclonal antibody that binds interleukin (IL)-4Rα and inhibits type 2 inflammation by blocking signaling of both IL-4/IL-13; subcutaneous immunotherapy with Timothy grass (SCIT), which inhibits allergic responses through pleiotropic effects; SCIT + dupilumab; or placebo. Using nasal brushing samples from these studies, we defined distinct gene signatures in nasal tissue of AR disease and after nasal allergen challenge (NAC) and assessed how these signatures were modulated by study drug(s).

RESULTS

Treatment with dupilumab (normalized enrichment score [NES] = -1.73, p = .002) or SCIT + dupilumab (NES = -2.55, p < .001), but not SCIT alone (NES = +1.16, p = .107), significantly repressed the AR disease signature. Dupilumab (NES = -2.55, p < .001), SCIT (NES = -2.99, p < .001), and SCIT + dupilumab (NES = -3.15, p < .001) all repressed the NAC gene signature.

CONCLUSION

These results demonstrate type 2 inflammation is an important contributor to the pathophysiology of AR disease and that inhibition of the type 2 pathway with dupilumab may normalize nasal tissue gene expression.

TRAPnSeq allows high-throughput profiling of antigen-specific antibody-secreting cells

Following activation by cognate antigen, B cells undergo fine-tuning of their antigen receptors and may ultimately differentiate into antibody-secreting cells (ASCs). While antigen-specific B cells that express surface receptors (B cell receptors [BCRs]) can be readily cloned and sequenced following flow sorting, antigen-specific ASCs that lack surface BCRs cannot be easily profiled. Here, we report an approach, TRAPnSeq (antigen specificity mapping through immunoglobulin [Ig] secretion TRAP and Sequencing), that allows capture of secreted antibodies on the surface of ASCs, which in turn enables high-throughput screening of single ASCs against large antigen panels. This approach incorporates flow cytometry, standard microfluidic platforms, and DNA-barcoding technologies to characterize antigen-specific ASCs through single-cell V(D)J, RNA, and antigen barcode sequencing. We show the utility of TRAPnSeq by profiling antigen-specific IgG and IgE ASCs from both mice and humans and highlight its capacity to accelerate therapeutic antibody discovery from ASCs.

Functional HIV-1/HCV cross-reactive antibodies isolated from a chronically co-infected donor

Despite prolific efforts to characterize the antibody response to human immunodeficiency virus type 1 (HIV-1) and hepatitis C virus (HCV) mono-infections, the response to chronic co-infection with these two ever-evolving viruses is poorly understood. Here, we investigate the antibody repertoire of a chronically HIV-1/HCV co-infected individual using linking B cell receptor to antigen specificity through sequencing (LIBRA-seq). We identify five HIV-1/HCV cross-reactive antibodies demonstrating binding and functional cross-reactivity between HIV-1 and HCV envelope glycoproteins. All five antibodies show exceptional HCV neutralization breadth and effector functions against both HIV-1 and HCV. One antibody, mAb688, also cross-reacts with influenza and coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We examine the development of these antibodies using next-generation sequencing analysis and lineage tracing and find that somatic hypermutation established and enhanced this reactivity. These antibodies provide a potential future direction for therapeutic and vaccine development against current and emerging infectious diseases. More broadly, chronic co-infection represents a complex immunological challenge that can provide insights into the fundamental rules that underly antibody-antigen specificity.

High-Throughput B Cell Epitope Determination by Next-Generation Sequencing

Development of novel technologies for the discovery of human monoclonal antibodies has proven invaluable in the fight against infectious diseases. Among the diverse antibody repertoires elicited by infection or vaccination, often only rare antibodies targeting specific epitopes of interest are of potential therapeutic value. Current antibody discovery efforts are capable of identifying B cells specific for a given antigen; however, epitope specificity information is usually only obtained after subsequent monoclonal antibody production and characterization. Here we describe LIBRA-seq with epitope mapping, a next-generation sequencing technology that enables residue-level epitope determination for thousands of single B cells simultaneously. By utilizing an antigen panel of point mutants within the HIV-1 Env glycoprotein, we identified and confirmed antibodies targeting multiple sites of vulnerability on Env, including the CD4-binding site and the V3-glycan site. LIBRA-seq with epitope mapping is an efficient tool for high-throughput identification of antibodies against epitopes of interest on a given antigen target.

Sequence and functional characterization of a public HIV-specific antibody clonotype

Public antibody clonotypes shared among multiple individuals have been identified for several pathogens. However, little is known about the determinants of antibody "publicness". Here, we characterize the sequence and functional properties of antibodies from a public clonotype targeting the CD4 binding site on HIV-1 Env. Our results showed that HIV-1 specificity for the public antibodies studied here, comprising sequences from three individuals, was modulated by the VH, but not VL, germline gene. Non-native pairing of public heavy and light chains from different individuals suggested functional complementation of sequences within this public antibody clonotype. The strength of antigen recognition appeared to be dependent on the specific antibody light chain used, but not on other sequence features such as native-antibody or germline sequence identity. Understanding the determinants of antibody clonotype "publicness" can provide insights into the fundamental rules of host-pathogen interactions at the population level, with implications for clonotype-specific vaccine development.

Efficient discovery of potently neutralizing SARS-CoV-2 antibodies using LIBRA-seq with ligand blocking

SARS-CoV-2 therapeutic antibody discovery efforts have met with notable success but have been associated with a generally inefficient process, requiring the production and characterization of exceptionally large numbers of candidates for the identification of a small set of leads. Here, we show that incorporating antibody-ligand blocking as part of LIBRA-seq, the high-throughput sequencing platform for antibody discovery, results in efficient identification of ultra-potent neutralizing antibodies against SARS-CoV-2. LIBRA-seq with ligand blocking is a general platform for functional antibody discovery targeting the disruption of antigen-ligand interactions.

Human antibodies neutralize enterovirus D68 and protect against infection and paralytic disease

Enterovirus D68 (EV-D68) causes outbreaks of respiratory illness, and there is increasing evidence that it causes outbreaks of acute flaccid myelitis (AFM). There are no licensed therapies to prevent or treat EV-D68 infection or AFM disease. We isolated a panel of EV-D68-reactive human monoclonal antibodies that recognize diverse antigenic variants from participants with prior infection. One potently neutralizing cross-reactive antibody, EV68-228, protected mice from respiratory and neurologic disease when given either before or after infection. Cryo-electron microscopy studies revealed that EV68-228 and another potently neutralizing antibody (EV68-159) bound around the fivefold or threefold axes of symmetry on virion particles, respectively. The structures suggest diverse mechanisms of action by these antibodies. The high potency and effectiveness observed in vivo suggest that antibodies are a mechanistic correlate of protection against AFM disease and are candidates for clinical use in humans with EV-D68 infection.

NFPws: a web server for delineating broadly neutralizing antibody specificities from serum HIV-1 neutralization data

MOTIVATION

A better understanding of antibody responses to HIV-1 infection in humans can provide novel insights for the development of an effective HIV-1 vaccine. Neutralization fingerprinting (NFP) is an efficient and accurate algorithm for delineating the epitope specificities found in polyclonal antibody responses to HIV-1 infection. Here, we report the development of NFPws, a web server implementation of the NFP algorithm. The server takes as input serum neutralization data for a set of diverse viral strains, and uses a mathematical model to identify similarities between the serum neutralization pattern and the patterns for known broadly neutralizing monoclonal antibodies (bNAbs), in order to predict the prevalence of bNAb epitope specificities in the given serum. In addition, NFPws also computes and displays a number of estimates related to prediction confidence, as well as the likelihood of presence of novel, previously uncharacterized, antibody specificities in a given serum. NFPws also implements a JSmol viewer for molecular structure visualization of the prediction results. Overall, the NFPws server will be an important tool for the identification and analysis of epitope specificities of bNAb responses against HIV-1.

AVAILABILITY AND IMPLEMENTATION

NFPws is freely available to access at (http://iglab.accre.vanderbilt.edu/NFPws). The webserver is developed using html, CSS, javascript and perl CGI scripts. The NFP algorithm is implemented with scripts written in octave, linux shell and perl. JSmol is implemented to visualize the prediction results on a representative 3D structure of an HIV-1 antigen.

Spontaneous Glycan Reattachment Following N-Glycanase Treatment of Influenza and HIV Vaccine Antigens

In cells, asparagine/N-linked glycans are added to glycoproteins cotranslationally, in an attachment process that supports proper folding of the nascent polypeptide. We found that following pruning of N-glycan by the amidase PNGase F, the principal influenza vaccine antigen and major viral spike protein hemagglutinin (HA) spontaneously reattached N-glycan to its de-N-glycosylated positions when the amidase was removed from solution. This reaction, which we term N-glycanation, was confirmed by site-specific analysis of HA glycoforms by mass spectrometry prior to PNGase F exposure, during exposure to PNGase F, and after amidase removal. Iterative rounds of de-N-glycosylation followed by N-glycanation could be repeated at least three times and were observed for other viral glycoproteins/vaccine antigens, including the envelope glycoprotein (Env) from HIV. Covalent N-glycan reattachment was nonenzymatic as it occurred in the presence of metal ions that inhibit PNGase F activity. Rather, N-glycanation relied on a noncovalent assembly between protein and glycan, formed in the presence of the amidase, where linearization of the glycoprotein prevented this retention and subsequent N-glycanation. This reaction suggests that under certain experimental conditions, some glycoproteins can organize self-glycan addition, highlighting a remarkable self-assembly principle that may prove useful for re-engineering therapeutic glycoproteins such as influenza HA or HIV Env, where glycan sequence and structure can markedly affect bioactivity and vaccine efficacy.

High-Throughput Mapping of B Cell Receptor Sequences to Antigen Specificity

B cell receptor (BCR) sequencing is a powerful tool for interrogating immune responses to infection and vaccination, but it provides limited information about the antigen specificity of the sequenced BCRs. Here, we present LIBRA-seq (linking B cell receptor to antigen specificity through sequencing), a technology for high-throughput mapping of paired heavy- and light-chain BCR sequences to their cognate antigen specificities. B cells are mixed with a panel of DNA-barcoded antigens so that both the antigen barcode(s) and BCR sequence are recovered via single-cell next-generation sequencing. Using LIBRA-seq, we mapped the antigen specificity of thousands of B cells from two HIV-infected subjects. The predicted specificities were confirmed for a number of HIV- and influenza-specific antibodies, including known and novel broadly neutralizing antibodies. LIBRA-seq will be an integral tool for antibody discovery and vaccine development efforts against a wide range of antigen targets.

Antibody cross-reactivity in chronic HIV/HCV co-infection

HIV/HCV co-infected individuals fair worse than their mono-infected counterparts, experiencing rapid progression to fibrosis, and increased chance of liver damage due to HAART. Given this, novel antibody therapeutic and rational vaccine design for both viruses have become top priorities worldwide. This study seeks to understand the antibody response in chronic HIV/HCV co-infection. Normally selected against, antibodies that recognize diverse antigens confer a selective advantage against highly mutable pathogens, such as HIV and HCV. We hypothesized that chronic co-infection leads to the development of antibodies that can recognize both viruses.

In collaboration with the Vanderbilt HIV cohort, we obtained patient PBMCs from a single HIV/HCV co-infected African American man, at four timepoints between 0.5 – 3 years post HIV infection (ypi). For 0.5, and 1.5 ypi we performed antigen-specific B cell sorting and deep B cell receptor sequencing. Notably, we used fluorescently-labeled envelope proteins from each virus to isolate virus-specific B cells from infected peripheral blood. We identified multiple unique B cells positive for both HIV and HCV antigens, which we then expressed as recombinant antibodies to characterize. Intriguingly, we see antibody-mediated neutralization of diverse viral strains, suggesting a common mode of antiviral protection. Matching single cell sequencing and functional to next-generation sequencing data allows for powerful delineation and characterization of virus-specific antibody responses. Furthermore, this study presents the first evidence of antibody cross-reactivity between genetically unrelated viruses, which could have great impact on future vaccine design efforts.

Prediction of VRC01 neutralization sensitivity by HIV-1 gp160 sequence features

The broadly neutralizing antibody (bnAb) VRC01 is being evaluated for its efficacy to prevent HIV-1 infection in the Antibody Mediated Prevention (AMP) trials. A secondary objective of AMP utilizes sieve analysis to investigate how VRC01 prevention efficacy (PE) varies with HIV-1 envelope (Env) amino acid (AA) sequence features. An exhaustive analysis that tests how PE depends on every AA feature with sufficient variation would have low statistical power. To design an adequately powered primary sieve analysis for AMP, we modeled VRC01 neutralization as a function of Env AA sequence features of 611 HIV-1 gp160 pseudoviruses from the CATNAP database, with objectives: (1) to develop models that best predict the neutralization readouts; and (2) to rank AA features by their predictive importance with classification and regression methods. The dataset was split in half, and machine learning algorithms were applied to each half, each analyzed separately using cross-validation and hold-out validation. We selected Super Learner, a nonparametric ensemble-based cross-validated learning method, for advancement to the primary sieve analysis. This method predicted the dichotomous resistance outcome of whether the IC50 neutralization titer of VRC01 for a given Env pseudovirus is right-censored (indicating resistance) with an average validated AUC of 0.868 across the two hold-out datasets. Quantitative log IC50 was predicted with an average validated R2 of 0.355. Features predicting neutralization sensitivity or resistance included 26 surface-accessible residues in the VRC01 and CD4 binding footprints, the length of gp120, the length of Env, the number of cysteines in gp120, the number of cysteines in Env, and 4 potential N-linked glycosylation sites; the top features will be advanced to the primary sieve analysis. This modeling framework may also inform the study of VRC01 in the treatment of HIV-infected persons.

Multi-Donor Longitudinal Antibody Repertoire Sequencing Reveals the Existence of Public Antibody Clonotypes in HIV-1 Infection

Characterization of single antibody lineages within infected individuals has provided insights into the development of Env-specific antibodies. However, a systems-level understanding of the humoral response against HIV-1 is limited. Here, we interrogated the antibody repertoires of multiple HIV-infected donors from an infection-naive state through acute and chronic infection using next-generation sequencing. This analysis revealed the existence of "public" antibody clonotypes that were shared among multiple HIV-infected individuals. The HIV-1 reactivity for representative antibodies from an identified public clonotype shared by three donors was confirmed. Furthermore, a meta-analysis of publicly available antibody repertoire sequencing datasets revealed antibodies with high sequence identity to known HIV-reactive antibodies, even in repertoires that were reported to be HIV naive. The discovery of public antibody clonotypes in HIV-infected individuals represents an avenue of significant potential for better understanding antibody responses to HIV-1 infection, as well as for clonotype-specific vaccine development.

Sensing the heat stress by Mammalian cells

Background

The heat-shock response network controls the adaptation and survival of the cell against environmental stress. This network is highly conserved and is connected with many other signaling pathways. A key element of the heat-shock network is the heat-shock transcription factor-1 (HSF), which is transiently activated by elevated temperatures. HSF translocates to the nucleus upon elevated temperatures, forming homotrimeric complexes. The HSF homotrimers bind to the heat shock element on the DNA and control the expression of the hsp70 gene. The Hsp70 proteins protect cells from thermal stress. Thermal stress causes the unfolding of proteins, perturbing thus the pathways under their control. By binding to these proteins, Hsp70 allows them to refold and prevents their aggregation. The modulation of the activity of the hsp70-promoter by the intensity of the input stress is thus critical for cell's survival. The promoter activity starts from a basal level and rapidly increases once the stress is applied, reaches a maximum level and attenuates slowely back to the basal level. This phenomenon is the hallmark of many experimental studies and of all computational network analysis.

Results

The molecular construct used as a measure of the response to thermal stress is a Hsp70-GFP fusion gene transfected in Chinese hamster ovary (CHO) cells. The time profile of the GFP protein depends on the transient activity, Transient(t), of the heat shock system. The function Transient(t) depends on hsp70 promoter activity, transcriptional regulation and the translation initiation effects elicited by the heat stress. The GFP time profile is recorded using flow cytometry measurements, a technique that allows a quantitative measurement of the fluorescence of a large number of cells (10⁴). The GFP responses to one and two heat shocks were measured for 261 conditions of different temperatures and durations. We found that: (i) the response of the cell to two consecutive shocks (i.e., no recovery time in between shocks) depends on the order of the input shocks, that is the shocks do not commute; (ii) the responses may be classified as mild or severe, depending on the temperature level and the duration of the heat shock and (iii) the response is highly sensitive to small variations in temperature.

Conclusions

We propose a mathematical model that maps temperature into the transient activity using experimental data that describes the time course of the response to input thermal stress. The model is built on thermotolerance without recovery time, sharp sensitivity to small variations in temperature and the existence of mild and severe classes of stress responses. The theoretical predictions are tested against experimental data using a series of double-shock inputs. The theoretical structure is represented by a sequence of three cascade processes that transform the input stress into the transient activity. The structure of the cascade is nonlinear-linear-nonlinear (NLN). The first nonlinear system (N) from the NLN structure represents the amplification of small changes in the environmental temperature; the linear system (L) represents the thermotolerance without recovery time, whereas the last system (N) represents the transition of the cell's response from a mild to a severe shock.