Biology subjects

Teufel, A.

Publications and source records attributed to Teufel, A..

3 recordsLinked to original sources

bioRxiv2026

C3a receptor signalling in ObRb-expressing neurons promotes leptin resistance and obesity-associated cardiac remodelling

Obesity is associated with hypothalamic inflammation, leptin resistance and increased cardiometabolic risk, but the neuroimmune signals linking nutrient excess to these outcomes remain incompletely defined. Here we show that diet-induced obesity is accompanied by local complement activation in the mouse hypothalamus, leading to C3a generation that signals through C3a receptor (C3aR) on leptin receptor (ObRb)-expressing neurons and blunts leptin signaling. Deletion of C3aR in ObRb-expressing neurons preserves leptin responsiveness, reduces food intake and weight gain, and improves glucose homeostasis during dietary challenge. Systemic pharmacological C3aR targeting induces weight loss and improves leptin responsiveness in established obesity. Genetic or pharmacological C3aR targeting also attenuates obesity-associated diastolic dysfunction and myocardial fibrosis; pair-feeding experiments reveal an additional component of cardiac protection beyond reduced weight gain, associated with lower cardiac sympathetic innervation. In humans, circulating complement activation markers are elevated in obesity and decline after bariatric surgery. Together, our findings identify C3aR signaling in ObRb-expressing neurons as a neuroimmune pathway contributing to hypothalamic leptin resistance and obesity-associated cardiac remodeling, highlighting complement signaling as a potential therapeutic target in cardiometabolic disease.

immunology↗

bioRxiv2021

RASSF1A independence and early Galectin-1 upregulation in PIK3CA induced hepatocarcinogenesis: new therapeutic venues

Aberrant activation of the PI3K/AKT/mTOR and Ras/Mitogen-Activated Protein Kinase pathways is a hepatocarcinogenesis hallmark. In a subset of hepatocellular carcinomas (HCC), PI3K/AKT/mTOR signaling dysregulation depends on PIK3CA mutations, while RAS/MAPK activation is partly attributed to promoter methylation of the tumor suppressor RASSF1A. To evaluate a possible co-carcinogenic effect of PIK3CA activation and RASSF1A knockout, plasmids expressing oncogenic forms of PIK3CA (E545K or H1047R mutants) were delivered to the liver of RASSF1A knockout and wildtype mice by hydrodynamic tail vein injection combined with Sleeping Beauty-mediated somatic integration. Transfection of either PIK3CA E545K or H1047R mutants sufficed to induce hepatocellular carcinomas in mice irrespective of RASSF1A mutational background. The related tumors displayed a lipogenic phenotype with upregulation of Fatty acid synthase and Stearoyl-CoA desaturase-1 (SCD1). Galectin-1, which was commonly upregulated in preneoplastic lesions and tumors, emerged as a regulator of SCD1. Co-inhibitory treatment with PIK3CA inhibitors and the Galectin-1 inhibitor OTX-008 resulted in synergistic cytotoxicity in human HCC cell lines, suggesting novel therapeutic venues. Graphical AbstractHydrodynamic tail vein injection of Phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA) mutant forms E545K and H1047R induces stepwise hepatocarcinogenesis in mice, independent of Ras association domain-containing protein 1 (RASSF1A) status. Gene expression analyses revealed an early increase in Galectin-1, which regulates the lipogenic enzyme Stearoyl-CoA desaturase-1 (SCD1). PIK3CA- and Galectin1 inhibitors act synergistically, pointing at novel therapeutic strategies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/448477v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@3e6292org.highwire.dtl.DTLVardef@1b994b5org.highwire.dtl.DTLVardef@d22411org.highwire.dtl.DTLVardef@3e05a5_HPS_FORMAT_FIGEXP M_FIG C_FIG

pathology↗

bioRxiv2017

Beyond thermodynamic constraints: Evolutionary history shapes protein sequence variation

Biological evolution generates a surprising amount of site-specific variability in protein sequences. Yet attempts at modeling this process have been only moderately successful, and current models based on protein structural metrics explain, at best, 60% of the observed variation. Surprisingly, simple measures of protein structure, such as solvent accessibility, are often better predictors of site-specific variability than more complex models employing all-atom energy functions and detailed structural modeling. We suggest here that these more complex models perform poorly because they lack consideration of the evolutionary process that is in part captured by the simpler metrics. We compare protein sequences that are computationally designed to sequences that are computationally evolved using the same protein-design energy function and to homologous natural sequences. We find that by a wide variety of metrics, evolved sequences are much more similar to natural sequences than are designed sequences. In particular, designed sequences are too conserved on the protein surface relative to natural sequences whereas evolved sequences are not. Our results suggest that evolutionary simulation produces a realistic sampling of sequence space. By contrast, protein design--at least as currently implemented--does not. Existing energy functions seem to be sufficiently accurate to correctly describe the key thermodynamic constraints acting on protein sequences, but they need to be paired with realistic sampling schemes to generate realistic sequence alignments.

evolutionary biology↗