Biology subjects

Ehinger, E.

Publications and source records attributed to Ehinger, E..

5 recordsLinked to original sources

bioRxiv2026

IL-27 induces a cytotoxic state in CD4+ T cells distinct from the Th1 lineage

CD4+ cytotoxic T lymphocytes (CD4-CTLs) are understudied immune mediators with ambiguous origins. Despite expressing RUNX3, granzyme B (GZMB), and perforin (PRF1), CD4-CTLs are frequently classified as Th1 extensions due to shared interferon-{gamma} (IFN{gamma}) and T-BET expression. Here, we identify interleukin-27 (IL-27) as a independent inducer of a distinct CD4-CTL program. Proteomics reveals that while IL-27-polarized CD4+ T cells share protein signatures with conventional Th1s and CD8+ T cells, they possess a unique molecular landscape with re-wired cytokine signaling networks and a potent cytotoxic protein profile. Mechanistically, this program requires STAT1 and T-BET but operates independently of the autocrine IFN{gamma} feedback that sustains Th1 cells. During acute murine cytomegalovirus infection, IL-27 receptor signaling contributes to CD4-CTL differentiation in vivo, as its loss leads to reduced GZMB expression and skews CD4+ T cells toward IFN{gamma}+ and FOXP3+ subsets. Together, these findings establish IL-27 as a potent and previously unappreciated inducer of CD4-CTLs.

immunology↗

bioRxiv2026

Reversible control of T cell exhaustion by NR4A transcription factors revealed through targeted protein degradation

Tumor-infiltrating CD8+ T cells (TILs) show progressive loss of effector function and upregulation of inhibitory receptors. NR4A transcription factors have emerged as key regulators of this dysfunctional state. Here we developed degron-based systems enabling rapid degradation of endogenous NR4A proteins in both mouse and primary human T cells. We demonstrate that the continuous presence of each NR4A protein is required to maintain suppression of effector cytokines and expression of co-inhibitory receptors; degradation of individual NR4A proteins rapidly restored these functional features, with each NR4A protein exerting prominent effects on distinct as well as overlapping subsets of genes and surface markers associated with effector, memory and exhaustion programs. Transcriptional profiling of phenotypically defined populations revealed both shared and unique gene programs across NR4A family members. Through CRISPR-mediated endogenous gene editing in primary human CD8+ T cells, we show that targeted degradation of NR4A proteins with a small molecule degrader can maintain cytokine expression and suppress inhibitory receptor expression in cells subjected to chronic stimulation, providing a framework for a powerful strategy for therapeutic intervention. One Sentence SummaryTargeted degradation of endogenous NR4A proteins reveals that individual family members maintain features of T cell dysfunction through overlapping as well as non-redundant mechanisms, providing a therapeutic strategy to restore anti-tumor function.

immunology↗

bioRxiv2020

Combined protein and transcript single cell RNA sequencing reveals cardiovascular disease and HIV signatures

Cryopreserved peripheral blood mononuclear cells (PBMCs) are frequently collected and provide disease- and treatment-relevant data in clinical studies. Here, we developed combined protein (40 antibodies) and transcript single cell (sc)RNA sequencing in PBMCs. Among 31 participants in the WIHS Study, we sequenced 41,611 cells. Using Boolean gating followed by Seurat UMAPs and Louvain clustering, we identified 58 subsets among CD4 T, CD8 T, B, NK cells and monocytes. This resolution was superior to flow cytometry, mass cytometry or scRNA-sequencing without antibodies. Since the transcriptome was not needed for cell identification, combined protein and transcript scRNA-Seq allowed for the assessment of disease-related changes in transcriptomes and cell type proportion. As a proof-of-concept, we showed such differences between healthy and matched individuals living with HIV with and without cardiovascular disease. In conclusion, combined protein and transcript scRNA sequencing is a suitable and powerful method for clinical investigations using PBMCs.

immunology↗

bioRxiv2019

Bone marrow transplantation rescues monocyte recruitment defect and improves cystic fibrosis in mice

One Sentence SummaryIn this study, we demonstrate that correcting the monocyte adhesion defect in CFTR{Delta}F508 mice (CF mice) by bone marrow transplantation significantly improved survival and reduced inflammation.\n\nAbstractCystic fibrosis (CF) is an inherited life-threatening disease accompanied by repeated lung infections and multi-organ inflammation that affects tens of thousands of people worldwide. The causative gene, cystic fibrosis transmembrane conductance regulator (CFTR), is mutated in CF patients. Monocytes from CF patients show a deficiency in integrin activation and adhesion. Since monocytes play critical roles in controlling infections, defective monocyte function may contribute to CF progression. In this study, we demonstrate that monocytes from CFTR{Delta}F508 mice (CF mice) show defective adhesion under flow. Transplanting CF mice with wild-type bone marrow after sublethal irradiation replaced most (60-80%) CF monocytes with wild-type monocytes, significantly improved survival, and reduced inflammation. Wild-type/CF mixed bone marrow chimeras directly demonstrated defective CF monocyte recruitment to the bronchoalveolar lavage and the intestinal lamina propria in vivo. Our findings show that providing wild-type monocytes by bone marrow transfer rescues gastrointestinal (GI) mortality in CF mice, suggesting that wild-type bone marrow stem cells might mitigate CF inflammation.

immunology↗

bioRxiv2018

PRESTO, a new tool for integrating large-scale -omics data and discovering disease-specific signatures

BackgroundCohesive visualization and interpretation of hyperdimensional, large-scale -omics data is an ongoing challenge, particularly for biologists and clinicians involved in current highly complex sequencing studies. Multivariate studies are often better suited towards non-linear network analysis than differential expression testing. Here, we present PRESTO, a PREdictive Stochastic neighbor embedding Tool for Omics, which allows unsupervised dimensionality reduction of multivariate data matrices with thousands of subjects or conditions. PRESTO is intuitively integrated into an interactive user interface that helps to visualize the multidimensional patterns in genome-wide transcriptomic data from basic science and clinical studies.\n\nResultsPRESTO was tested with multiple input omics platforms, including microarray and proteomics from both mouse and human clinical datasets. PRESTO can analyze up to tens of thousands of genes and shows no increase in processing time with a large number of samples or patients. In complex datasets, such as those with multiple time points, several patient groups, or diverse mouse strains, PRESTO outperformed conventional methods. Core co-expressed gene networks were intuitively grouped in clusters, or gates, after dimensionality reduction and remained consistent across users. Networks were identified and assigned to physiological and pathological functions that cannot be gleaned from conventional bioinformatics analyses. PRESTO detected gene networks from the natural variations among mouse macrophages and human blood leukocytes. We applied PRESTO to clinical transcriptomic and proteomic data from large patient cohorts and detected disease-defining signatures in antibody-mediated kidney transplant rejection, renal cell carcinoma, and relapsing acute myeloid leukemia (AML). In AML, PRESTO confirmed a previously described gene signature and found a new signature of 10 genes that is highly predictive of patient outcome.\n\nConclusionsPRESTO offers an important integration of powerful bioinformatics tools with an interactive user interface that increases data analysis accessibility beyond bioinformaticians and coders. Here, we show that PRESTO out performs conventional methods, such as DE analysis, in multi-dimensional datasets and can identify biologically relevant co-expression gene networks. In paired samples or time points, co-expression networks could be compared for insight into longitudinal regulatory mechanisms. Additionally, PRESTO identified disease-specific signatures in clinical datasets with highly significant diagnostic and prognostic potential.

bioinformatics↗