Biology subjects

Ehling, R. A.

Publications and source records attributed to Ehling, R. A..

11 recordsLinked to original sources

bioRxiv2025

Predicting TCR antigen specificity at proteome-scale with synthetic immune cells and machine learning

TCR specificity to peptide-HLA antigens is central to immunology, impacting responses in infection, autoimmunity and cancer. Achieving precise recognition while avoiding off-target reactivity is critical for effective immunity and safe therapeutic interventions. Comprehensive, proteome-wide specificity profiling of TCRs is challenging with current methods, which notably lack integrated machine learning for large-scale analysis. Here, we report a synthetic immune cell system coupled with machine learning to enable TCR functional and specificity mapping of peptide-HLA antigens at proteome-scale. Multi-step immunogenomic engineering of synthetic antigen-presenting cells (APCs) was performed to enable stable mono-allelic integration and precise display of peptide antigens and HLA class I from a defined genomic locus, ensuring genomically-encoded antigen presentation. Compatible with a synthetic TCR displaying T cell system, this platform incorporates a fluorescent reporter of cytokine-mediated signaling for real-time activation detection in both synthetic APCs and T cells. We combined this screening with diverse peptide antigen libraries and deep sequencing to train supervised machine learning models. These models were applied to predict TCR specificity to peptide-HLA antigens across the entire human proteome. Experimental validation confirmed novel off-targets for therapeutic TCR candidates, including for a clinically-approved TCR therapeutic. This integrated synthetic immune cell and machine learning approach provides unprecedented proteome-wide peptide-HLA specificity mapping to support the development of safer TCR-based therapies. One sentence summaryWe present a synthetic immune cell platform integrated with machine learning that enables prediction of TCR specificity to peptide-HLA antigens at proteome-scale.

immunology↗

bioRxiv2024

Synthetic coevolution reveals adaptive mutational trajectories of neutralizing antibodies and SARS-CoV-2

The Covid-19 pandemic showcases a coevolutionary race between the human immune system and SARS-CoV-2, mirroring the Red Queen hypothesis of evolutionary biology. The immune system generates neutralizing antibodies targeting the SARS-CoV-2 spike proteins receptor binding domain (RBD), crucial for host cell invasion, while the virus evolves to evade antibody recognition. Here, we establish a synthetic coevolution system combining high-throughput screening of antibody and RBD variant libraries with protein mutagenesis, surface display, and deep sequencing. Additionally, we train a protein language machine learning model that predicts antibody escape to RBD variants. Synthetic coevolution reveals antagonistic and compensatory mutational trajectories of neutralizing antibodies and SARS-CoV-2 variants, enhancing the understanding of this evolutionary conflict.

synthetic biology↗

bioRxiv2022

Omicron sublineage BA.2.75.2 exhibits extensive escape from neutralising antibodies

Several sublineages of omicron have emerged with additional mutations that may afford further antibody evasion. Here, we characterise the sensitivity of emerging omicron sublineages BA.2.75.2, BA.4.6, and BA.2.10.4 to antibody-mediated neutralisation, and identify extensive escape by BA.2.75.2. BA.2.75.2 was resistant to neutralisation by Evusheld (tixagevimab + cilgavimab), but remained sensitive to bebtelovimab. In recent serum samples from blood donors in Stockholm, Sweden, BA.2.75.2 was neutralised, on average, at titers approximately 6.5-times lower than BA.5, making BA.2.75.2 the most neutralisation resistant variant evaluated to date. These data raise concerns that BA.2.75.2 may effectively evade humoral immunity in the population.

immunology↗

bioRxiv2022

Evasion of neutralizing antibodies by Omicron sublineage BA.2.75

An emerging SARS-CoV-2 Omicron sublineage, BA.2.75, is increasing in frequency in India and has been detected in at least 15 countries as of 19 July 2022. Relative to BA.2, BA.2.75 carries nine additional mutations in spike. Here we report the sensitivity of the BA.2.75 spike to neutralization by a panel of clinically-relevant and pre-clinical monoclonal antibodies, as well as by serum from blood donated in Stockholm, Sweden, before and after the BA.1/BA.2 infection wave. BA.2.75 largely maintains sensitivity to bebtelovimab, despite a slight reduction in potency, and exhibits moderate susceptibility to tixagevimab and cilgavimab. For sera sampled both before and after the BA.1/BA.2 infection wave, BA.2.75 does not show significantly greater antibody evasion than the currently-dominating BA.5.

immunology↗

bioRxiv2021

Variable loss of antibody potency against SARS-CoV-2 B.1.1.529 (Omicron)

The recently-emerged SARS-CoV-2 B.1.1.529 variant (Omicron) is spreading rapidly in many countries, with a spike that is highly diverged from the pandemic founder, raising fears that it may evade neutralizing antibody responses. We cloned the Omicron spike from a diagnostic sample which allowed us to rapidly establish an Omicron pseudotyped virus neutralization assay, sharing initial neutralization results only 13 days after the variant was first reported to the WHO, 8 days after receiving the sample. Here we show that Omicron is substantially resistant to neutralization by several monoclonal antibodies that form part of clinical cocktails. Further, we find neutralizing antibody responses in pooled reference sera sampled shortly after infection or vaccination are substantially less potent against Omicron, with neutralizing antibody titers reduced by up to 45 fold compared to those for the pandemic founder. Similarly, in a cohort of convalescent sera prior to vaccination, neutralization of Omicron was low to undetectable. However, in recent samples from two cohorts from Stockholm, Sweden, antibody responses capable of cross-neutralizing Omicron were prevalent. Sera from infected-then-vaccinated healthcare workers exhibited robust cross-neutralization of Omicron, with an average potency reduction of only 5-fold relative to the pandemic founder variant, and some donors showing no loss at all. A similar pattern was observed in randomly sampled recent blood donors, with an average 7-fold loss of potency. Both cohorts showed substantial between-donor heterogeneity in their ability to neutralize Omicron. Together, these data highlight the extensive but incomplete evasion of neutralizing antibody responses by the Omicron variant, and suggest that increasing the magnitude of neutralizing antibody responses by boosting with unmodified vaccines may suffice to raise titers to levels that are protective.

immunology↗

bioRxiv2021

Predictive profiling of SARS-CoV-2 variants by deep mutational learning

The continual evolution of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and the emergence of variants that show resistance to vaccines and neutralizing antibodies (1-4) threaten to prolong the coronavirus disease 2019 (COVID-19) pandemic (5). Selection and emergence of SARS-CoV-2 variants are driven in part by mutations within the viral spike protein and in particular the ACE2 receptor-binding domain (RBD), a primary target site for neutralizing antibodies. Here, we develop deep mutational learning (DML), a machine learning-guided protein engineering technology, which is used to interrogate a massive sequence space of combinatorial mutations, representing billions of RBD variants, by accurately predicting their impact on ACE2 binding and antibody escape. A highly diverse landscape of possible SARS-CoV-2 variants is identified that could emerge from a multitude of evolutionary trajectories. DML may be used for predictive profiling on current and prospective variants, including highly mutated variants such as omicron (B.1.1.529), thus supporting decision making for public heath as well as guiding the development of therapeutic antibody treatments and vaccines for COVID-19.

synthetic biology↗

bioRxiv2021

B cell clonal expansion is correlated with antigen-specificity in young but not old mice

Murine models of immunization have played a major role in discovering antibody candidates against therapeutic targets. It nevertheless remains time-consuming and expensive to identify antibodies with diverse binding modalities against druggable candidate molecules. Although new genomics-based pipelines have potential to augment antibody discovery, these methods remain in their infancy due to an incomplete understanding of the selection process that governs B cell clonal selection, expansion and antigen specificity. Furthermore, it remains unknown how factors such as aging and reduction of tolerance influence B cell selection in murine models of immunization. Here we perform single-cell sequencing of antibody repertoires and transcriptomes of B cells following immunizations with a model therapeutic antigen target (human Tumor necrosis factor receptor 2, TNFR2). We determine the relationship between antibody repertoires, gene expression signatures and antigen specificity across 100,000 B cells. Recombinant expression and characterization of 227 monoclonal antibodies revealed the existence of clonally expanded and class-switched antigen-specific B cells that were more frequent in young mice. Although integrating multiple repertoire features such as germline gene usage, somatic hypermutation, and transcriptional signatures failed to distinguish antigen-specific from non-specific B cells, other features such as IgG-subtype and sequence composition correlated with antigen-specificity. This work provides a single-cell resource for B cells relating antibody repertoires, transcriptomes and antigen specificity.

immunology↗

bioRxiv2021

Phenotypic determinism and stochasticity in antibody repertoires of clonally expanded plasma cells

The capacity of humoral B cell-mediated immunity to effectively respond to and protect against pathogenic infections is largely driven by the presence of a diverse repertoire of polyclonal antibodies in the serum, which are produced by plasma cells (PCs).1,2 Recent studies have started to reveal the balance between deterministic mechanisms and stochasticity of antibody repertoires on a genotypic level (i.e., clonal diversity, somatic hypermutation, germline gene usage).3-8 However, it remains unclear if clonal selection and expansion of PCs follows any deterministic rules or is stochastic with regards to phenotypic antibody properties (i.e., antigen-binding, affinity, epitope specificity). Here we report on the in-depth genotypic and phenotypic characterization of clonally expanded PC antibody repertoires following protein immunization. We find that there is only a strong correlation with antigen-specificity among the most expanded clones (top ~ 10), whereas among the rest of the clonal repertoire antigen-specificity is stochastic. Furthermore, we report both on a polyclonal repertoire and clonal lineage level that antibody-antigen binding affinity does not correlate with clonal expansion or somatic hypermutation. Lastly, we provide evidence for convergence towards dominant epitopes despite clonal sequence diversity among the most expanded clones. Our results highlight the extent to which clonal expansion can be ascribed to antigen binding, affinity and epitope specificity and they have implications for the assessment of effective vaccines. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/452687v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@e907c1org.highwire.dtl.DTLVardef@fc45b6org.highwire.dtl.DTLVardef@44bd91org.highwire.dtl.DTLVardef@f98f3e_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2021

A single-cell atlas of lymphocyte adaptive immune repertoires and transcriptomes reveals age-related differences in convalescent COVID-19 patients

COVID-19 disease outcome is highly dependent on adaptive immunity from T and B lymphocytes, which play a critical role in the control, clearance and long-term protection against SARS-CoV-2. To date, there is limited knowledge on the composition of the T and B cell immune receptor repertoires [T cell receptors (TCRs) and B cell receptors (BCRs)] and transcriptomes in convalescent COVID-19 patients of different age groups. Here, we utilize single-cell sequencing (scSeq) of lymphocyte immune repertoires and transcriptomes to quantitatively profile the adaptive immune response in COVID-19 patients of varying age. We discovered highly expanded T and B cells in multiple patients, with the most expanded clonotypes coming from the effector CD8+ T cell population. Highly expanded CD8+ and CD4+ T cell clones show elevated markers of cytotoxicity (CD8: PRF1, GZMH, GNLY; CD4: GZMA), whereas clonally expanded B cells show markers of transition into the plasma cell state and activation across patients. By comparing young and old convalescent COVID-19 patients (mean ages = 31 and 66.8 years, respectively), we found that clonally expanded B cells in young patients were predominantly of the IgA isotype and their BCRs had incurred higher levels of somatic hypermutation than elderly patients. In conclusion, our scSeq analysis defines the adaptive immune repertoire and transcriptome in convalescent COVID-19 patients and shows important age-related differences implicated in immunity against SARS-CoV-2.

immunology↗

bioRxiv2021

Single-cell sequencing of plasma cells from COVID-19 patients reveals highly expanded clonal lineages produce specific and neutralizing antibodies to SARS-CoV-2

Isolation and characterization of antibodies in COVID-19 patients has largely focused on memory B cells, however it is the antibody-secreting plasma cells that are directly responsible for the production of serum antibodies, which play a critical role in controlling and resolving SARS-CoV-2 infection. To date there is little known about the specificity of plasma cells in COVID-19 patients. This is largely because plasma cells lack surface antibody expression, which complicates their screening. Here, we describe a technology pipeline that integrates single-cell antibody repertoire sequencing and high-throughput mammalian display screening to interrogate the specificity of plasma cells from 16 convalescent COVID-19 patients. Single-cell sequencing allows us to profile antibody repertoire features in these patients and identify highly expanded clonal lineages. Mammalian display screening is employed to reveal that 37 antibodies (out of 132 candidates) derived from expanded plasma cell clonal lineages are specific for SARS-CoV-2 antigens, including antibodies that target the receptor binding domain (RBD) with high affinity and exhibit potent neutralization of SARS-CoV-2. One Sentence SummarySingle-cell antibody repertoire sequencing and high-throughput screening identifies highly expanded plasma cells from convalescent COVID-19 patients that produce SARS-CoV-2-specific antibodies capable of potent neutralization.

immunology↗

bioRxiv2019

Molecular design, optimization and genomic integration of chimeric B cell receptors in murine B cells

Immune cell therapies based on the integration of synthetic antigen receptors provide a powerful strategy for the treatment of diverse diseases, most notably retargeting T cells engineered to express chimeric antigen receptors (CAR) for cancer therapy. In addition to T lymphocytes, B lymphocytes may also represent valuable immune cells that can be engineered for therapeutic purposes such as protein replacement therapy or recombinant antibody production. In this article, we report a promising concept for the molecular design, optimization and genomic integration of a novel class of synthetic antigen receptors, chimeric B cell receptors (CBCR). We initially optimized CBCR expression and detection by modifying the extracellular surface tag, the transmembrane regions and intracellular signaling domains. For this purpose, we stably integrated a series of CBCR variants into immortalized B cell hybridomas using CRISPR-Cas9. Subsequently, we developed a reliable and consistent pipeline to precisely introduce cassettes of several kilobases size into the genome of primary murine B cells, again via CRISPR-Cas9 induced HDR. Finally, we were able to show the robust surface expression and antigen recognition of a synthetic CBCR in primary B cells. We anticipate that CBCRs and our approach for engineering primary B cells will be a valuable tool for the advancement of future B cell-based immune therapies.

immunology↗