Biology subjects

Walther, G.

Publications and source records attributed to Walther, G..

7 recordsLinked to original sources

bioRxiv2024

Non-Caloric Sweeteners combined with glucose affect hypothalamic glucose sensing-induced insulin secretion, food re-intake through neuronal cellular metabolism: An in vivo and in vitro approaches

1Changes in brain activity associated with deleterious metabolic effects of non-caloric sweeteners (NCS) have been demonstrated in humans, particularly when their intake is concomitant with that of glucose. Here, we have focused on hypothalamic glucose sensing in rats, detecting increases in circulating glucose levels and in turn triggering various physiological controls. The identification of sweet-taste receptors in the hypothalamus has suggested that they participate in glucosensing mechanism, but the existence of a dialogue between different pathways has never been studied. Here, we tested the acute effects of hypothalamic glucosensing combined with a NCS (sucralose or acesulfame potassium (aceK)), the latter binding only to sweet-taste receptors, without producing energy. Our working hypothesis was that the concomitance of two contradictory signals (energetic, sweet glucose vs. non-energetic, sweet NCS) could be responsible for deleterious physiological effects. After validation that sweet taste receptors and their signaling expressions were indeed present in the rat hypothalamus, insulin secretion induced by hypothalamic glucosensing (increased glucose level) in the presence of sucralose and aceK was examined. Insulin release was reduced compared to glucose alone, while the two NCS alone have no effect. Regarding the satiety-inducing effect of glucose, concomitant injection of each NCS with glucose produced the opposite effect to that observed with glucose alone, with food intake being increased, an effect also present with NCS injected alone. Using the GT1-7 hypothalamic cell line expressing sweet-taste receptors, we showed that the ATP concentration which normally increases with rising glucose levels was dose-dependently decreased in the presence of NCS, an effect which is inhibited in the presence of gurmarin, a specific inhibitor of sweet-taste receptors. The increase in ROS production in response to rising glucose levels was enhanced in the presence of NCS, an effect that was blocked in the presence of gurmarin. In both cases, NCS have an inhibitory effect on stimulated mitochondrial respiration. Taken together, these results suggest that NCS via sweet-taste receptors interfere with mitochondrial signaling and/or energy production during hypothalamic glucose sensing.

neuroscience↗

bioRxiv2024

Automatic Phenotyping Using Exhaustive Projection Pursuit

One of the most common objectives in the analysis of flow cytometry data is the identification and delineation of phenotypes, distinct populations of cells with shared characteristics in the measurement dimensions. We have developed an automated tool to comprehensively identify these cell populations by Exhaustive Projection Pursuit (EPP). The method evaluates all two-dimensional projections among the suitable data dimensions and creates an optimized sequence of statistically significant gating regions that identify all phenotypes supported by the data. We evaluate the results of EPP on four well characterized data sets from the literature. The C++ code for EPP can be called from any computing environment. We illustrate this with a MATLAB utility that integrates EPP with FlowJo. All source code is freely available.

bioinformatics↗

bioRxiv2024

Obesity induces phenotypic switching of gastric smooth muscle cells through the activation of the PPARD/PDK4/ANGPTL4 pathway

ObjectiveClinical research has identified stomach dysmotility as a common feature of obesity. However, the specific mechanisms driving gastric emptying dysfunction in patients with obesity remain largely unknown. In this study, we investigated potential mechanisms by focusing on the homeostasis of gastric smooth muscle, using tissue samples from both patient and mice, as well as human cell culture system. DesignTissue samples were collected from patients who underwent sleeve gastrectomy for obesity, as well as from control subjects with standard weight who were undergoing treatment for gastric or esophageal carcinoma. Stomach tissues were harvested from mice after 12 weeks on a High-Fat Diet (HFD). Differentiated human gastric smooth muscle cells (SMCs) were treated with lipids, siRNA-peptide-based nanoparticles and/or pharmaceutical compounds. All experimental conditions were analyzed for their effects on SMC differentiation using stage-specific smooth muscle markers. Additionally, lipidomic and RNA sequencing analyses were performed on human gastric SMC cultures. The findings were assessed in patients with obesity to evaluate their clinical relevance. ResultsThe smooth muscle layers in gastric tissue from both patients with obesity and mice fed on a HFD exhibited altered differentiation status. Treatment of differentiated human gastric SMCs with lipids phenocopies these alterations and is associated with increased expression of PDK4 and ANGPTL4. Inhibition of PDK4 or ANGPTL4 upregulation prevents these lipid-induced modifications. Mechanistically, lipid treatment activates PPARD, which regulates PDK4 and ANGPTL4 upregulation, leading to SMC dedifferentiation. Notably, PDK4 and ANGPTL4 levels correlate with immaturity and alteration of gastric smooth muscle in patients with obesity. ConclusionObesity triggers a phenotypic change in gastric SMCs, driven by the activation of the PPARD/PDK4/ANGPTL4 pathway. These mechanistic insights offer potential biomarkers for diagnosing stomach dysmotility in patients with obesity.

physiology↗

bioRxiv2024

RNAi epimutations conferring antifungal drug resistance are inheritable

Epimutations modify gene expression and lead to phenotypic variation while the encoding DNA sequence remains unchanged. Epimutations mediated by RNA interference (RNAi) and/or chromatin modifications can confer antifungal drug resistance and may impact virulence traits in fungi. However, whether these epigenetic modifications can be transmitted across generations following sexual reproduction was unclear. This study demonstrates that RNAi epimutations conferring antifungal drug resistance are transgenerationally inherited in the human fungal pathogen Mucor circinelloides. Our research revealed that RNAi-based antifungal resistance follows a DNA sequence-independent, non-Mendelian inheritance pattern. Small RNAs (sRNAs) are the exclusive determinants of inheritance, transmitting drug resistance independently of other known repressive epigenetic modifications. Unique sRNA signature patterns can be traced through inheritance from parent to progeny, further supporting RNA as an alternative molecule for transmitting information across generations. Understanding how epimutations occur, propagate, and confer resistance may enable their detection in other eukaryotic pathogens, provide solutions for challenges posed by rising antimicrobial drug resistance (AMR), and advance research on phenotypic adaptability and its evolutionary implications.

microbiology↗

bioRxiv2024

Lifting the curse from high dimensional data: Automated projection pursuit clustering for the variety of biological data modalities

Unsupervised clustering is a powerful machine-learning technique widely used to analyze high-dimensional biological data. It plays a crucial role in uncovering patterns, structure, and inherent relationships within complex datasets without relying on predefined labels. In the context of biology, high-dimensional data may include transcriptomics, proteomics, and a variety of single-cell omics data. Most existing clustering algorithms operate directly in the high-dimensional space, and their performance may be negatively affected by the phenomenon known as the curse of dimensionality. Here, we show an alternative clustering approach that alleviates the curse by sequentially projecting high-dimensional data into a low-dimensional representation. We validated the effectiveness of our approach, named APP, across various biological data modalities, including flow and mass cytometry data, scRNA-seq, multiplex imaging data, and T-cell receptor repertoire data. APP efficiently recapitulated experimentally validated cell-type definitions and revealed new biologically meaningful patterns.

bioinformatics↗

bioRxiv2024

Spirolactone, an unprecedented antifungal β-lactone spiroketal macrolide from Streptomyces iranensis

Fungal infections pose a great threat to public health and there are limited antifungal medicaments. Streptomyces is an important source of antibiotics, represented by the clinical drug amphotericin B. The rapamycin-producer Streptomyces iranensis harbors an unparalleled Type I polyketide synthase, which codes for a novel antifungal macrolide alligamycin A (1), the structure of which was confirmed by NMR, MS, and X-ray crystallography. Alligamycin A harbors an undescribed carbon skeleton with 13 chiral centers, featuring a ({beta}-lactone moiety, a [6,6]-spiroketal ring, and an unprecedented 7-oxo-octylmalonyl-CoA extender unit incorporated by a potential novel crotonyl-CoA carboxylase/reductase. The ali biosynthetic gene cluster was confirmed through CRISPR-based gene editing. Alligamycin A displayed profound antifungal effects against numerous clinically relevant filamentous fungi, including Talaromyces and Aspergillus species. ({beta}-Lactone ring is essential for the antifungal activity and alligamycin B (2) with disruption in the ring abolished the antifungal effect. Proteomics analysis revealed alligamycin A potentially disrupted the integrity of fungal cell walls and induced the expression of stress-response proteins in Aspergillus niger. Alligamycins represent a new class of potential drug candidate to combat fungal infections.

biochemistry↗

bioRxiv2023

RNA-based sensitive fungal pathogen detection

Detecting fungal pathogens, a major cause of severe systemic infections, remains challenging due to the difficulty and time-consuming nature of diagnostic methods. This delay in identification hinders targeted treatment decisions and may lead to unnecessary use of broad-spectrum antibiotics. To expedite treatment initiation, one promising approach is to directly detect pathogen nucleic acids such as DNA, which is often preferred to RNA because of its inherent stability. However, a higher number of RNA molecules per cell makes RNA a more promising diagnostic target which is particularly prominent for highly expressed genes such as rRNA. Here, we investigated the utility of a minimal input-specialized reverse transcription protocol to increase diagnostic sensitivity. This proof-of-concept study demonstrates that fungal rRNA detection by the minimal input protocol is drastically more sensitive compared to detection of genomic DNA even with high levels of human RNA background. This approach can detect several of the most relevant human pathogenic fungal genera, such as Aspergillus, Candida, and Fusarium and thus represents a powerful, cheap, and easily adaptable addition to currently available diagnostic assays.

microbiology↗