Biology subjects

Seligmann, B.

Publications and source records attributed to Seligmann, B..

4 recordsLinked to original sources

bioRxiv2026

Arp2/3 complex-dependent actin remodeling is required for efficient RSV uncoating in A549 cells

Productive human respiratory syncytial virus (RSV) cell-entry requires coordinated interactions between viral proteins and host-cell factors at the plasma membrane-actin cortex interface. Branched actin networks remodel this interface, but their precise contribution to the early stages of RSV infection remains unclear. Here, we interfered with Arp2/3 complex-dependent actin filament branching by generating A549 cell lines disrupted for expression of the essential Arp2 subunit by CRISPR/Cas9. Permanent loss of Arp2 reduced the infection of the RSV long GFP reporter virus as quantified over the first 24 h post-infection. Compromised infection efficiency in Arp2 knockout cells persisted at later time points and also resulted in reduced syncytia formation. Notably, these infection phenotypes were not accompanied by obvious changes in viral host cell attachment. Moreover, photoactivated localization microscopy (PALM) studies revealed comparable receptor diffusion and clustering in cells stably expressing mEos3.2-tagged insulin-like growth factor I receptor (IGF1R). Although Arp2/3-deficient cells displayed fewer albeit larger macropinosomes as compared to WT cells, no changes were observed for internalized RSV genome levels. In contrast, Arp2-deficient cells appeared suppressed in viral uncoating efficiency. Consequently, viral mRNA expression and the cellular type III interferon response were reduced. Together, these data reveal that Arp2/3 complex-dependent, branched actin networks contribute to the efficiency of RSV uncoating. ImportanceHuman respiratory syncytial virus (RSV) is a major cause of severe respiratory disease. The infection initiates at the plasma membrane-actin cortex interface, yet the role of actin in productive RSV entry has remained unclear. Using CRISPR/Cas9 disruption of the essential Arp2/3 complex subunit Arp2 in A549 cells, we show that branched actin networks are required for efficient RSV infection. Despite actin network remodeling, photoactivated localization microscopy showed unchanged diffusion and clustering of the RSV receptor IGF1R. Although macropinocytosis was affected in Arp2-deficient cells, RSV attachment and internalization were not influenced. In contrast, a {beta}-lactamase virus-like-particle-based assay revealed a defect in uncoating, followed by reduced viral gene expression and a weaker type III interferon response. These findings define Arp2/3 complex-dependent branched actin networks as a host determinant of RSV uncoating and provide a practical approach to quantify uncoating without engineering the RSV genome.

microbiology↗

bioRxiv2025

Production of the anticancer drug intermediate strictosidinic acid in engineered yeast

Strictosidinic acid is a key intermediate in the biosynthetic pathway of camptothecin, a plant alkaloid that serves as a precursor for semisynthetic anticancer drugs. At the moment, camptothecin is mainly sourced from trees, causing limited supply and high costs. Improving access to strictosidinic acid would help to elucidate yet unknown biosynthetic steps and in the long term enable sustainable production of camptothecin in heterologous hosts. While structurally similar to the common monoterpene indole alkaloid precursor strictosidine, strictosidinic acid has not been the target of metabolic engineering efforts before. Here, we present a strategy to produce strictosidinic acid from glucose and tryptophan in engineered yeast. First, we create a basic strain that generates 75 mg/L strictosidine. We further optimise this strain by introducing a membrane steroid binding protein and a second copy of the farnesyl pyrophosphate synthase mutant gene ERG20WW, boosting strictosidine levels by 5.5-fold to 398 mg/L. At these higher titres, a previously overlooked shunt product, (2E,6E)-2,6-dimethylocta-2,6-dienedioic acid (DOA), was identified that diverts flux from the pathway. Lastly, we reprogrammed our strictosidine strain to strictosidinic acid production by four genomic modifications. Final fed-batch cultivation in shake flasks resulted in 843 mg/L strictosidine or 548 mg/L strictosidinic acid, respectively, after 168 hours. Taken together, our work now grants access to strictosidinic acid by metabolic engineering, while revealing strategies to further enhance the production of strictosidine and related monoterpene indole alkaloids. These findings will help to produce plant alkaloids in microbial cell factories in the future at scale.

bioengineering↗

bioRxiv2025

Decoding Cellular Stress States for Toxicology Using Single-Cell Transcriptomics

We applied the TempO-LINC(R) platform to generate single-cell transcriptomic (SCTr) profiles of [~]40,000 HepaRG cells exposed to etoposide, brefeldin A, cycloheximide, rotenone, tBHQ, troglitazone, and tunicamycin at three concentrations for 24 hours. SCTr enabled a detailed analysis of adaptive stress response pathways (SRPs), including the unfolded protein response (UPR), oxidative stress response (OSR), heat shock response (HSR), and DNA damage response (DDR). Troglitazone upregulated lipid metabolism genes (PLIN2, ACOX1) along with HSR and UPR activation, with co-expression of DNAJA1, HSP90AA1, and DDIT3 in subsets of cells. Brefeldin A and tunicamycin strongly induced UPR markers (HSPA5, SYVN1, LMF2, PDIA4) in subsets of cells, with some also expressing apoptotic (DDIT3, CASP8) and autophagic (SQSTM1) genes, indicating diverse stress responses. Rotenone activated GDF15, TRIB3, and DDIT3 in a fraction of cells, accompanied by PLIN2 and mild UPR induction, reflecting heterogeneous mitochondrial stress responses. We scored individual cells using literature-derived SRP gene signatures to characterize overall stress phenotypes and clustered them using a generalized Jaccard metric. The clustering revealed five phenotypic groups spanning cell states associated with homeostasis, adaptive responses, terminal outcomes, autophagy, and apoptosis. By systematically analyzing the distributions of cells in different states across treatments, we visualized dynamic shifts in cellular subpopulations responding to chemicals, revealing early stress responses and potential transitions to cell death. Our findings suggest the utility of SCTr in decoding stress states that could provide possible insights into transitions between cellular adaptive and terminal transitions involved in toxicity.

pharmacology and toxicology↗

bioRxiv2024

High-throughput gene expression analysis with TempO-LINC sensitively resolves complex brain, lung and kidney heterogeneity at single-cell resolution

We report the development and performance of a novel genomics platform, TempO-LINC, for conducting high-throughput transcriptomic analysis on single cells and nuclei. TempO-LINC works by adding cell-identifying molecular barcodes onto highly selective and high-sensitivity gene expression probes within fixed cells, without having to first generate cDNA. Using an instrument-free combinatorial-indexing approach, all probes within the same fixed cell receive an identical barcode, enabling the reconstruction of single-cell gene expression profiles across as few as several hundred cells and up to 100,000+ cells per run. The TempO-LINC approach is easily scalable based on the number of barcodes and rounds of barcoding performed; however, for the experiments reported in this study, the assay utilized over 5.3 million unique barcodes. TempO-LINC has a robust protocol for fixing and banking cells and displays high-sensitivity gene detection from multiple diverse sample types. We show that TempO-LINC has an observed multiplet rate of less than 1.1% and a cell capture rate of [~]50%. Although the assay can accurately profile the whole transcriptome (19,683 human or 21,400 mouse genes), it can be targeted to measure only actionable/informative genes and molecular pathways of interest - thereby reducing sequencing requirements. In this study, we applied TempO-LINC to profile the transcriptomes of 89,722 cells across multiple sample types, including nuclei from mouse lung, kidney and brain tissues. The data demonstrated the ability to identify and annotate at least 50 unique cell populations and positively correlate expression of cell type-specific molecular markers within them. TempO-LINC is a robust new single-cell technology that is ideal for large-scale applications/studies across thousands of samples with high data quality.

genomics↗