Biology subjects

Obermayer, B.

Publications and source records attributed to Obermayer, B..

At least 19 recordsLinked to original sources

bioRxiv2026

Kiosc: an integrated platform for managing bioinformatics data analysis containers

In many bioinformatic data analysis projects, it is convenient to visualize plots and results through an interactive web app or dashboard. These interactive reports can then be shared with customers, collaborators, or the general public. Publishing and sharing these apps is not straightforward, becoming especially cumbersome when the number of projects and customers start growing. Docker containers offer a convenient way to package, distribute, and run interactive web apps, and their use is already widespread in the bioinformatics community. We developed Kiosc to simplify the orchestration of containerized web apps, organize them into projects, and regulate access control. We implemented it as a web server based on the Django framework, with a user- and admin-friendly interface as well as a REST API for programmatic tasks. Users can select Docker containers packaging apps like Plotly Dash, Shiny, or Quarto, and configure them to display the results of their analysis. Kiosc runs the containers with the appropriate network configuration and acts as a proxy to the web services running inside the containers. We have been maintaining a Kiosc instance for more than 5 years, serving 321 containers in 150 projects across multiple institutions. In this article, we introduce the main functionality in Kiosc and describe four use-cases that show how Kiosc can prove helpful to the broader bioinformatics community, such as configuring and running web apps for the interactive visualization of workflow results, and publishing companion apps for scientific articles. Kiosc is a self-hosted platform for publishing web apps, which doesn't require significant expertise in either Docker or network administration to be deployed. It provides a similar service to Kubernetes, but with a convenient web interface and much lower administration overhead.

bioinformatics↗

bioRxiv2026

Translating multi-omics complexity into sparse prognostic biomarkers for multiple myeloma

Multiple myeloma (MM) exhibits profound molecular heterogeneity, yet current risk stratification relies on cytogenetics or single-omics signatures that often fail to capture cross-layer regulatory complexity. We re-analyzed a multi-omics dataset integrating copy-number, transcriptomic, proteomic, and phosphoproteomic data to dissect how common genomic driver alterations propagate through the molecular cascade. Supervised classification demonstrated that downstream layers, particularly the proteome and phosphoproteome, classify genomic events more accurately than primary genomic or transcriptomic data. Intriguingly, trans-acting features alone were sufficient for classification, indicating that while direct dosage effects manifest at the RNA level, downstream network responses dominate the proteomic state. Multi-omics factor analysis (MOFA2) identified a continuous latent axis predicting progression-free and overall survival independent of R-ISS. This factor captured a gain(1q)/del(13q) axis modulated by immune infiltration and NSD2 expression, integrating variance across all four modalities. To enable clinical translation, we derived sparse, single-modality proxies using elastic net regression. An RNA proxy faithfully recapitulated the multi-omic factor and validated independently in published microarray and RNAseq cohorts, demonstrating robust prognostic utility across treatment eras. These findings reveal that multi-omics integration uncovers hidden prognostic axes obscured by single-omics analyses, and that sparse proxies can bridge the gap between complex discovery and clinical implementation.

cancer biology↗

bioRxiv2025

Central T3 deprivation disturbs cortical cilia formation, oligodendrocyte lineage and neuronal cell-cell-communication in a MCT8/OATP1C1 deficient Allan-Herndon-Dudley Syndrome mouse model

BackgroundThe Allan-Herndon-Dudley syndrome (AHDS) is a rare, X-linked human genetic disorder caused by mutations in the monocarboxylate transporter 8 (MCT8), essential for thyroid hormone (TH) transport across the blood-brain-barrier. The resulting central TH deprivation disrupts brain maturation and function, leading to intellectual disability and movement disorders. Cortical development, highly dependent on TH, is particularly affected and contributes significantly to AHDS pathologies. MethodsTo elucidate disrupted cortical processes, we conducted single nucleus RNA sequencing in a mouse model engineered to mimic the central TH deficiency characteristic of human AHDS. This murine AHDS model features the concomitant deletion of both MCT8 and OATP1C1, a T4 transporter largely absent in human brain capillaries that in mice plays a role in TH transport. The phenotype of dKO mice bears striking resemblance to the pathologies observed in human AHDS patients. ResultsSingle nuclei were isolated from the cortex and attached striatum of 21-day old WT and MCT8/OATP1C1 dKO mice and sequenced using the 10x Genomics workflow. Cell proportion analyses on the resulting 48 clusters suggested elevated numbers of GABAergic striatal D1 and D2 neurons in the dKO mice. Diminished levels of mature oligodendrocytes coincided with a bifurcation within the oligodendrocyte lineage trajectory, leading to distinct subpopulations of WT and dKO oligodendrocytes. Differentially expressed gene (DEG) patterns align poorly with Slc16a2 and Slco1c1 mRNA levels in the respective clusters, but closely with prior published cortical bulk RNAseq data of mice with systemic hypothyroidism or MCT8/OATP1C1 deficiency. These parallels confirm the reliability of our data and provide new insights by pinpointing TH-responsive DEGs to specific cellular clusters. Moreover, inferred cell-cell communication using NeuronChat suggested a disbalance in GABAergic versus glutamatergic signaling. We further uncovered perturbed primary cilia formation in several GABAergic and glutamatergic clusters of the dKO cortex. DiscussionMolecular signatures and perturbations uncovered by our snRNAseq study reveal new molecular characteristics of the AHDS. The imbalance in GABAergic versus glutamatergic cell-cell-communication, perturbed primary cilia formation, and bifurcation of the oligodendrocyte lineage align with pathologies observed in AHDS patients and highlight the role of TH signaling in maintaining neuronal network homeostasis in the cortex.

neuroscience↗

bioRxiv2025

Cryo-mtscATAC-seq for single-cell mitochondrial DNA genotyping and clonal tracing in archived human tissues

High-throughput clonal tracing of primary human samples relies on naturally occurring barcodes, such as somatic mitochondrial DNA (mtDNA) mutations detected via single-cell ATAC-seq (mtscATAC-seq). Fresh-frozen clinical specimens preserve tissue architecture but compromise cell integrity, thereby precluding their use in multi- omic approaches such as mitochondrial genotyping at single-cell resolution. Here, we introduce Cryo-mtscATAC-seq, a broadly applicable method for diverse pathophysiological contexts to isolate nuclei with their associated mitochondria ("CryoCells") from frozen samples for high-throughput clonal analysis. We applied Cryo-mtscATAC-seq to the neurodegenerated human brain, glioblastoma (GBM), pediatric neuroblastoma, and human aorta, and implemented mitobender, a computational tool to reduce ambient mtDNA in single-cell assays. Our approach revealed regional clonal gliogenesis and microglial expansions in amyotrophic lateral sclerosis (ALS), persistence of oligodendrocyte progenitor cell (OPC)-like clones in GBM recurrence, mtDNA depth heterogeneity after neuroblastoma chemotherapy, and oligoclonal proliferation of smooth muscle cells in human aorta. In conclusion, Cryo-mtscATAC-seq broadly extends mtDNA genotyping to archival frozen specimens across tissue types, opening new avenues for investigation of cell state- informed clonality in human health and disease.

systems biology↗

bioRxiv2025

circVDJ-seq for T cell clonotype detection in single-cell and spatial multi-omics

Monitoring T cell repertoires in human tissues provides important insights into immune response mechanisms in cancer, infectious diseases, and autoimmunity. However, retrieving VDJ information from single-cell and spatial transcriptomics workflows with 3-barcoding of cDNA remains resource-intensive or requires specialized sequencing equipment. Here, we introduce circVDJ-seq for simplified and cost-efficient T cell receptor (TCR) profiling from 3-directed workflows like single-cell or single-nucleus RNA sequencing, ATAC+RNA multi-omics, and spatial transcriptomics. Application of circVDJ-seq to freshly resected neuroblastomas and postmortem lymph nodes affected by pneumonia or COVID-19 reveals distinct immune microenvironments and T cell clonality patterns, highlighting broad utility across diverse clinical contexts.

genomics↗

bioRxiv2025

An autologous human iPSC-derived 3D organoid infection model for preclinical testing of antiviral T cells

Immunocompromised patients, such as those undergoing hematopoietic stem cell or solid organ transplantation, are highly susceptible to viral complications. Given the limitations and side effects of available antiviral therapies, adoptive transfer of antiviral T cells offers a promising alternative by restoring immune defense. However, existing models for evaluating antiviral T cell therapies lack physiological relevance, limiting accurate predictions of efficacy and safety. There is a critical need for in vitro human infection platforms that support personalized assessment of therapeutic responses. To address this, we developed antiviral T cell products (TCPs) targeting Influenza A virus (IAV)-infected cells, alongside an autologous human induced pluripotent stem cell (iPSC)-derived 3D lung organoid infection platform. This model recapitulates key immunological responses and is compatible with a new 3D high-throughput, high-content imaging pipeline. Our study provides the first proof-of-concept for assessing T cell-mediated cytotoxicity in a 3D in vitro lung infection model, advancing personalized antiviral immunotherapy development.

immunology↗

bioRxiv2024

High-confidence calling of normal epithelial cells allows identification of a novel stem-like cell state in the colorectal cancer microenvironment

Single-cell analyses can be confounded by assigning unrelated groups of cells to common developmental trajectories. For instance, cancer cells and admixed normal epithelial cells could potentially adopt similar cell states thus complicating analyses of their developmental potential. Here, we develop and benchmark CCISM (for Cancer Cell Identification using Somatic Mutations) to exploit genomic single nucleotide variants for the disambiguation of cancer cells from genomically normal non-cancer epithelial cells in single-cell data. In colorectal cancer datasets, we find that our method and others based on gene expression or allelic imbalances identify overlapping sets of cancer versus normal epithelial cells, depending on molecular characteristics of individual cancers. Further, we define consensus cell identities of normal and cancer epithelial cells with higher transcriptome cluster homogeneity than those derived using existing tools. Using the consensus identities, we identify significant shifts of cell state distributions in genomically normal epithelial cells developing in the cancer microenvironment, with immature states increased at the expense of terminal differentiation throughout the colon, and a novel stem-like cell state arising in the left colon. Trajectory analyses show that the new cell state extends the pseudo-time range of normal colon stem-like cells in a cancer context. We identify cancer-associated fibroblasts as sources of WNT and BMP ligands potentially contributing to increased plasticity of stem cells in the cancer microenvironment. Our analyses advocate careful interpretation of cell heterogeneity and plasticity in the cancer context and the consideration of genomic information in addition to gene expression data when possible. Novelty and ImpactSingle-cell analyses have become standard to assess cell heterogeneity and developmental hierarchies in cancer tissues. However, these datasets are complex and contain cancer and non-cancer lineage cells. Here, we develop and systematically benchmark tools to distinguish between cancer and non-cancer single-cell transcriptomes, based on gene expression or different levels of genomic information. We provide strategies to combine results of different tools into consensus calls tailored to the biology and genetic characteristics of the individual cancer.

cancer biology↗

bioRxiv2024

Identifying cancer cells from calling single-nucleotide variants in scRNA-seq data

Single cell RNA sequencing (scRNA-seq) data is widely used to study cancer cell states and their heterogeneity. However, the tumour microenvironment is usually a mixture of healthy and cancerous cells and it can be difficult to fully separate these two populations based on transcriptomics alone. If available, somatic single nucleotide variants (SNVs) observed in the scRNA-seq data could be used to identify the cancer population. However, calling somatic SNVs in scRNA-seq data is a challenging task, as most variants seen in the short read data are not somatic, but can instead be germline variants, RNA edits or transcription, sequencing or processing errors. Additionally, only variants present in actively transcribed regions for each individual cell will be seen in the data. To address these challenges, we develop CCLONE (Cancer Cell Labelling On Noisy Expression), an interpretable tool adapted to handle the uncertainty and sparsity of SNVs called from scRNA-seq data. CCLONE jointly identifies cancer clonal populations, and their associated variants. We apply CCLONE on two acute myeloid leukaemia datasets and one lung adenocarcinoma dataset and show that CCLONE captures both genetic clones and somatic events for multiple patients. These results show how CCLONE can be used to gather insight into the course of the disease and the origin of cancer cells in scRNA-seq data.

bioinformatics↗

bioRxiv2023

Multimodal profiling of peripheral blood identifies proliferating circulating effector CD4+ T cells as predictors for response to integrin α4β7-blocking therapy in patients with inflammatory bowel disease

Despite the success of biological therapies in inflammatory bowel disease (IBD), patient management remains challenging due to a lack of therapy response predictors. Here we prospectively sampled two cohorts of IBD patient cohorts receiving the anti-integrin 4{beta}7 antibody vedolizumab. Samples were subjected to mass cytometry, single-cell RNA sequencing, single-cell V(D)J sequencing, serum proteomics, and multidimensional flow cytometry to comprehensively assess vedolizumab-induced immunological changes in the peripheral blood and their potential associations with treatment response. Vedolizumab induced changes in the abundance of both circulating innate and adaptive immune cell compartments and modified the T cell receptor diversity of circulating gut-homing CD4+ memory T cells. Through integration of multimodal parameters and machine learning, we identify that pretreatment activated proliferating CD4+ memory T cell abundance is associated with treatment failure, independent of clinical variables, thereby providing a reliable predictive classifier with significant implications for the personalized management of IBD patients.

immunology↗

bioRxiv2023

The pleiotropic functions of Pri smORF peptides synchronise leg development regulators

The last decade witnesses the emergence of the abundant family of smORF peptides, encoded by small ORF (<100 codons), whose biological functions remain largely unexplored. Bioinformatic analyses here identify hundreds of putative smORF peptides expressed in Drosophila imaginal leg discs. Thanks to a functional screen in legs, we found smORF peptides involved in morphogenesis, including the pioneer smORF peptides Pri. Since we identified its target Ubr3 in the epidermis and pri was known to control leg development through misunderstood mechanisms, we investigated the role of Ubr3 in mediating pri function in legs. We found that pri play several roles during leg development both in patterning and in cell survival. At larval pupal transition, Pri peptides cooperate with Ubr3 to insure cell survival and leg morphogenesis. Earlier, during larval stage, pri activates independently of Ubr3 tarsal transcriptional programs and Notch and EGFR signalling pathways. Our results highlight Ubr3 dependent and independent functions of Pri peptides and their pleiotropy. Moreover, we reveal that the smORF peptide family is a reservoir of overlooked developmental regulators, displaying distinct molecular functions and orchestrating leg development. Summary statementPri smORF peptides activate multiple actors regulating signalling pathways, transcription and apoptosis by distinct mechanisms to insure tarsal patterning and epithelial morphogenesis during leg development.

developmental biology↗

bioRxiv2023

Prdm16 mutation determines sex-specific cardiac metabolism and identifies two novel cardiac metabolic regulators

BackgroundMutation of the PRDM16 gene has been associated with human cardiomyopathy. The PRDM16 protein is a transcriptional regulator affecting cardiac development via Tbx5 and Hand1 regulating myocardial structure. Biallelic Prdm16 inactivation induces severe cardiac dysfunction with postnatal lethality and hypertrophy in mice. Early pathological events upon Prdm16 inactivation have not been explored. MethodsThis study performed in depth pathophysiological and molecular analysis of male and female Prdm16csp1/wt mice carrying systemic, monoallelic Prdm16 gene inactivation. We systematically assessed early molecular changes with transcriptomics, proteomics, and metabolomics. Kinetic modelling of the cardiac metabolism was undertaken in silico with CARDIOKIN. ResultsPrdm16csp1/wt mice are viable up to 8 months, develop hypoplastic hearts, and diminished systolic performance that is more pronounced in female mice. Prdm16csp1/wt hearts demonstrate moderate alterations of specific transcripts and protein levels with consistent upregulation of pyridine nucleotide-disulphide oxidoreductase domain 2 (Pyroxd2) and the transcriptional regulator pre B-cell leukemia transcription factor interacting protein 1 (Pbxip1). The strongest concordant transcriptional upregulation was detected for Prdm16 itself probably by an autoregulatory mechanism. Prdm16csp1/wt cardiac tissue showed reduction of metabolites associated with amino acid as well as glycerol metabolism, glycolysis, and tricarboxylic acid cycle. Global lipid metabolism was also affected with accumulation of triacylglycerides detected in male Prdm16csp1/wt hearts. In addition, Prdm16csp1/wt cardiac tissue revealed diminished glutathione (GSH) and increased inosine monophosphate (IMP) levels indicating oxidative stress and a dysregulated energetics, respectively. Metabolic modelling in silico suggested lowered fatty acid utilization in male and reduced glucose utilization in female Prdm16csp1/wt cardiac tissue. ConclusionsMonoallelic Prdm16 mutation restricts cardiac performance in Prdm16csp1/wt mice. Metabolic alterations precede transcriptional dysregulation in Prdm16csp1/wt cardiac tissue. Female Prdm16csp1/wt mice develop a more pronounced phenotype indicating a sexual dimorphism at this early pathological window. This study suggests that metabolic dysregulation is an early event in PRDM16 associated cardiac pathology. Novelty and SignificanceO_ST_ABSWhat Is Known?C_ST_ABS- Mutation of the PRDM16 gene has been associated with human cardiomyopathy. - Biallelic inactivation of Prdm16 in mice induces severe cardiac dysfunction with early postnatal lethality. - Prdm16 cooperates with transcription factors such as Tbx5 and Hand1 to activate transcriptional programs that define the development of the compacted myocardium. What New Information Does This Article Contribute?- Systemic, monoallelic inactivation in Prdm16csp1/wt mice induces cardiac dysfunction with normal survival. - Metabolic alterations are the leading pathophysiological consequences and induce cardiac hypoplasia. On the molecular level this is associated with upregulation of metabolic regulators Pyroxd2 and Pbxip1. - Metabolic response after Prdm16 inactivation occurs in a sex specific manner.

pathology↗

bioRxiv2022

HDAC7 controls anti-viral and anti-tumor immunity by CD8+ T cells

Class II histone deacetylases (HDAC) orchestrate T cell-dependent immune responses via the epigenetic control of genes and via the post-translational modification of cytoplasmic and nuclear proteins. However, the contribution of single HDAC family members to the differentiation and function of peripheral CD8+ T cells remains elusive. We here demonstrate that HDAC7-deficiency leads to the upregulation of immune checkpoint molecules, decreased calcium influx as well as increased apoptosis of peripheral murine CD8+ T cells, which we could link to a MEF2D-dependent induction of FasL expression ultimately deterring the survival of HDAC7-deficient CD8+ T cells. Likewise, we observed in mouse models of lymphoma, that mice with a T cell specific-deletion of Hdac7 harbor impaired anti-tumor immune responses in syngeneic transfer models of lymphoma and we found that HDAC7 is required for CD8+ T cell-dependent memory recall responses in models of lymphocytic choriomeningitis virus infection. Taken together, we identify HDAC7 as a central regulator of cellular exhaustion and apoptosis of peripheral CD8+ T cells, controlling CD8+ T cell dependent anti-tumor and anti-viral immunity in mice. SignificanceAlthough HDAC7 was identified as an important regulator of thymocyte development and survival, its role in the homeostasis and the functions of adult CD8+ T cells is not fully understood. Here, we identify HDAC7 as a critical regulator of peripheral CD8+ T cells since its deletion impairs anti-tumor and anti-viral immune responses in mouse models of LCMV infection and transfer models of lymphoma. We attribute this phenotype to impaired survival, calcium homeostasis as well as deterred memory function and increased exhaustion of HDAC7-deficient CD8+ T cells. Our findings are of clinical relevance regarding potential immune suppressive side effects of HDAC inhibitors that are currently under clinical trials for the treatment of autoimmune diseases and cancers.

immunology↗

bioRxiv2021

Transcriptomic responses of the human kidney to acute injury at single cell resolution

BackgroundAcute kidney injury (AKI) occurs frequently in critically ill patients and is associated with adverse outcomes. Cellular mechanisms underlying AKI and kidney cell responses to injury remain incompletely understood. MethodsWe performed single-nuclei transcriptomics, bulk transcriptomics, molecular imaging studies, and conventional histology on kidney tissues from 8 individuals with severe AKI (stage 2 or 3 according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria). Specimens were obtained within 1-2 hours after individuals had succumbed to critical illness associated with respiratory infections, with 4 of 8 individuals diagnosed with COVID-19. Control kidney tissues were obtained post-mortem or after nephrectomy from individuals without AKI. ResultsHigh-depth single cell-resolved gene expression data of human kidneys affected by AKI revealed enrichment of novel injury-associated cell states within the major cell types of the tubular epithelium, in particular in proximal tubules, thick ascending limbs and distal convoluted tubules. Four distinct, hierarchically interconnected injured cell states were distinguishable and characterized by transcriptome patterns associated with oxidative stress, hypoxia, interferon response, and epithelial-to-mesenchymal transition, respectively. Transcriptome differences between individuals with AKI were driven primarily by the cell type-specific abundance of these four injury subtypes rather than by private molecular responses. AKI-associated changes in gene expression between individuals with and without COVID-19 were similar. ConclusionThe study provides an extensive resource of the cell type-specific transcriptomic responses associated with critical illness-associated AKI in humans, highlighting recurrent disease-associated signatures and inter-individual heterogeneity. Personalized molecular disease assessment in human AKI may foster the development of tailored therapies.

molecular biology↗

bioRxiv2021

The single-cell transcriptional landscape of lung carcinoid tumors

Lung carcinoid tumors, also referred to as pulmonary neuroendocrine tumors or lung carcinoids, are rare neoplasms of the lung with a more favorable prognosis than other subtypes of lung cancer. Still, some patients suffer from relapsed disease and metastatic spread while no consensus treatment exists for metastasized carcinoids. Several recent single-cell studies have provided detailed insights into the cellular heterogeneity of more common lung cancers, such as adeno- and squamous cell carcinoma. However, the characteristics of lung carcinoids on the single-cell level are yet completely unknown. To study the cellular composition and single-cell gene expression profiles in lung carcinoids, we applied single-cell RNA sequencing to three lung carcinoid tumor samples and normal lung tissue. The single-cell transcriptomes of carcinoid tumor cells reflected intertumoral heterogeneity associated with clinicopathological features, such as tumor necrosis and proliferation index. The immune microenvironment was specifically enriched in noninflammatory monocyte-derived myeloid cells. Tumor-associated endothelial cells were characterized by distinct gene expression profiles. A spectrum of vascular smooth muscle cells and pericytes predominated the stromal microenvironment. We found a small proportion of myofibroblasts exhibiting features reminiscent of cancer-associated fibroblasts. Stromal and immune cells exhibited potential paracrine interactions which may shape the microenvironment via NOTCH, VEGF, TGF{beta} and JAK/STAT signaling. Moreover, single-cell gene signatures of pericytes and myofibroblasts demonstrated prognostic value in bulk gene expression data. Here, we provide first comprehensive insights into the cellular composition and single-cell gene expression profiles in lung carcinoids, demonstrating the non-inflammatory and vessel-rich nature of their tumor microenvironment, and outlining relevant intercellular interactions which could serve as future therapeutic targets.

cancer biology↗

bioRxiv2021

Spermidine reduces neuroinflammation and soluble amyloid beta in an Alzheimer's disease mouse model

Deposition of amyloid beta (A{beta}) along with glia cell-mediated neuroinflammation are prominent pathogenic hallmarks of Alzheimers disease (AD). In recent years, impairment of autophagy has been found to be another important feature, contributing to AD progression and aging. Therefore, we assessed the effect of the autophagy activator Spermidine, a small body-endogenous polyamine often used as dietary supplement and known to promote longevity, on glia cell-mediated neuroinflammation. Spermidine reduced TLR3- and TLR4- mediated inflammatory processes in microglia and astrocytes by decreasing cytotoxicity, inflammasome activity and NF-{kappa}B signaling. In line with these anti-inflammatory effects, oral treatment of the amyloid prone AD-like APPPS1 mice with Spermidine reduced neuroinflammation and neurotoxic soluble A{beta}. Mechanistically, single nuclei sequencing revealed microglia as one of the main targets of Spermidine treatment, with increased expression of genes implicated in cell motility and phagocytosis. Thus, Spermidine provides a promising therapeutic potential to target glia cells in AD progression.

neuroscience↗

bioRxiv2021

A kinetic error filtering mechanism for enzyme-free copying of nucleic acid sequences

Accurate copying of nucleic acid sequences is essential for self-replicating systems. Modern cells achieve error ratios as low as 10-9 with sophisticated enzymes capable of kinetic proofreading. In contrast, experiments probing enzyme-free copying of RNA and DNA as potential prebiotic replication processes find error ratios on the order of 10%. Given this low intrinsic copying fidelity, plausible scenarios for the spontaneous emergence of molecular evolution require an accuracy-enhancing mechanism. Here, we study a kinetic error filtering scenario that dramatically boosts the likelihood of producing exact copies of nucleic acid sequences. The mechanism exploits the observation that initial errors in template-directed polymerization of both DNA and RNA are likely to trigger a cascade of consecutive errors and significantly stall downstream extension. We incorporate these characteristics into a mathematical model with experimentally estimated parameters, and leverage this model to probe to what extent accurate and faulty polymerization products can be kinetically discriminated. While limiting the time window for polymerization prevents completion of erroneous strands, resulting in a pool in which full-length products show an enhanced accuracy, this comes at the price of a concomitant reduction in yield. We show that this fidelity-yield trade-off can be circumvented via repeated copying attempts in cyclically varying environments such as the temperature cycles occurring naturally in the vicinity of hydrothermal systems. This setting could produce exact copies of sequences as long as 50mers within their lifetime, facilitating the emergence and maintenance of catalytically active oligonucleotides.

evolutionary biology↗

bioRxiv2020

Longitudinal omics in Syrian hamsters integrated with human data unravel complexity of moderate immune responses to SARS-CoV-2

In COVID-19, the immune response largely determines disease severity and is key to therapeutic strategies. Cellular mechanisms contributing to inflammatory lung injury and tissue repair in SARS-CoV-2 infection, particularly endothelial cell involvement, remain ill-defined. We performed detailed spatiotemporal analyses of cellular and molecular processes in SARS-CoV-2 infected Syrian hamsters. Comparison of hamster single-cell sequencing and proteomics with data sets from COVID-19 patients demonstrated inter-species concordance of cellular and molecular host-pathogen interactions. In depth vascular and pulmonary compartment analyses (i) supported the hypothesis that monocyte-derived macrophages dominate inflammation, (ii) revealed endothelial inflammation status and T-cell attraction, and (iii) showed that CD4+ and CD8+ cytotoxic T-cell responses precede viral elimination. Using the Syrian hamster model of self-limited moderate COVID-19, we defined the specific roles of endothelial and epithelial cells, among other myeloid and non-myeloid lung cell subtypes, for determining the disease course.

immunology↗

bioRxiv2020

Single-cell RNA sequencing reveals distinct tumor microenvironmental patterns in lung adenocarcinoma

Recent developments in immuno-oncology demonstrate that not only cancer cells, but also features of the tumor microenvironment guide precision medicine. Still, the relationship between tumor and microenvironment remains poorly understood. To overcome this limitation and identify clinically relevant microenvironmental and cancer features, we applied single-cell RNA sequencing to lung adenocarcinomas. While the highly heterogeneous carcinoma cell transcriptomes reflected histological grade and activity of relevant oncogenic pathways, our analysis revealed two distinct microenvironmental patterns. We identified a prognostically unfavorable group of tumors with a microenvironment composed of cancer-associated myofibroblasts, exhausted CD8+ T cells, proinflammatory monocyte-derived macrophages and plasmacytoid dendritic cells (CEP2 pattern) and a prognostically favorable group characterized by myeloid dendritic cells, anti-inflammatory monocyte-derived macrophages, normal-like myofibroblasts, NK cells and conventional T cells (MAN2C pattern). Our results show that single-cell gene expression profiling allows to identify patient subgroups based on the tumor microenvironment beyond cancer cell-centric profiling.

cancer biology↗