Biology subjects

Kallenberger, S. M.

Publications and source records attributed to Kallenberger, S. M..

4 recordsLinked to original sources

bioRxiv2026

Hierarchical classification of immune cell transcriptomes at population-scale

Accurate immune cell classification is essential for interpreting single-cell RNA sequencing (scRNA-seq) data. However, progress in automating cell type annotation is constrained by the lack of independent, high-resolution benchmarks, as routine data integration introduces statistical dependencies that inflate model generalizability. Here, we present the single-cell universal classification omnibus (Suco), a resource of independent, uniform expert annotations, and Compocyte, a modular hierarchical classifier. Together, they establish a framework that substantially outperforms existing classifiers while facilitating expert review of ambiguous annotations. Applying Compocyte across 50 studies, including three newly generated datasets, we classified 15.6 million leukocytes from 3,965 patients. Within this cohort, we identified a new tumor-associated resorptive macrophage phenotype, a non-canonical monocyte subtype in subclinical cytokine release syndrome, and the programmatic erosion of T cell memory stemness across metastatic sites. Suco and Compocyte thus provide a generalizable framework to uncover the principles governing human immunity at population scale. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/728980v2_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@13a6e4borg.highwire.dtl.DTLVardef@11f1626org.highwire.dtl.DTLVardef@1e72bd4org.highwire.dtl.DTLVardef@1ee799b_HPS_FORMAT_FIGEXP M_FIG C_FIG In briefThe single-cell universal classification omnibus and the modular hierarchical classifier Compocyte enable annotating single cell RNA sequencing data from 3,965 patients, revealing novel resorptive macrophage and vaccination-associated monocyte states, alongside the erosion of T cell memory stemness as a hallmark of solid tumor metastases. HighlightsO_LISuco, a benchmark enabling novel single cell artificial intelligence models C_LIO_LICompocyte, a hierarchical cell type classifier outperforming current architectures C_LIO_LIMacrophages adopt osteoclast-like gene expression states across cancer types C_LIO_LIStem-like programs erode in metastasis-infiltrating T memory cells across tumors C_LI

bioinformatics↗

bioRxiv2023

GADD34 mRNA turnover controls the molecular memory of cellular stress experience

The integrated stress response (ISR) is a key cellular signaling pathway activated by environmental alterations that represses protein synthesis to restore homeostasis. To prevent sustained damage, the ISR is counteracted by the upregulation of Growth Arrest and DNA Damage inducible 34 (GADD34), a stress-induced regulatory subunit of protein phosphatase 1 that mediates translation reactivation and stress recovery. Here, we uncover a novel ISR regulatory mechanism that post-transcriptionally controls the stability of PPP1R15A mRNA encoding GADD34. We established that the 3 untranslated region of PPP1R15A mRNA contains an active AU-rich element recognized by proteins of the ZFP36 family, promoting its rapid decay under normal conditions and stabilization for efficient expression of GADD34 in response to stress. We identify the tight temporal control of PPP1R15A mRNA turnover as a key step in establishing the ISR molecular memory, which sets the threshold for cellular responsiveness and mediates adaptation to repeated stress conditions.

cell biology↗

bioRxiv2022

Temporal control of the integrated stress response by a stochastic molecular switch

Stress granules (SGs) are formed in the cytosol as an acute response to environmental cues and activation of the integrated stress response (ISR), a central signaling pathway controlling protein synthesis. Using chronic virus infection as stress model, we previously uncovered a unique temporal control of the ISR resulting in recurrent phases of SG assembly and disassembly. Here, we elucidate the molecular network generating this fluctuating stress response, by integrating quantitative experiments with mathematical modeling, and find that the ISR operates as a stochastic switch. Key elements controlling this switch are the cooperative activation of the stress-sensing kinase PKR, the ultrasensitive response of SG formation to the phosphorylation of the translation initiation factor eIF2, and negative feedback via GADD34, a stress-induced subunit of protein phosphatase 1. We identify GADD34 mRNA levels as the molecular memory of the ISR that plays a central role in cell adaptation to acute and chronic stress.

cell biology↗

bioRxiv2021

Dynamics of SARS-CoV-2 host cell interactions inferred from transcriptome analyses

The worldwide spread of severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) caused an urgent need for an in-depth understanding of interactions between the virus and its host. Here, we dissected the dynamics of virus replication and the host cell transcriptional response to SARS-CoV-2 infection at a systems level by combining time-resolved RNA sequencing with mathematical modeling. We observed an immediate transcriptional activation of inflammatory pathways linked to the anti-viral response followed by increased expression of genes involved in ribosome and mitochondria function, thus hinting at rapid alterations in protein production and cellular energy supply. At later stages, metabolic processes, in particular those depending on cytochrome P450 enzymes, were downregulated. To gain a deeper understanding of the underlying transcriptional dynamics, we developed an ODE model of SARS-CoV-2 infection and replication. Iterative model reduction and refinement revealed that a negative feedback from virus proteins on the expression of anti-viral response genes was essential to explain our experimental dataset. Our study provides insights into SARS-CoV-2 virus-host interaction dynamics and facilitates the identification of druggable host pathways supporting virus replication.

systems biology↗