Biology subjects

Vorholt, J. A.

Publications and source records attributed to Vorholt, J. A..

11 recordsLinked to original sources

bioRxiv2026

Metal toxicity contributes to the structuring of bacterial communities in the Arabidopsis leaf phyllosphere

O_LIThe causal factors shaping plant-associated microbiota are incompletely known. Elevated concentrations of the micronutrients zinc (Zn), manganese (Mn) and copper (Cu), and exposure to non-essential trace elements including cadmium (Cd) and arsenic (As), can be toxic. Here we explored whether differences in metal(loid) sensitivity between plants and bacteria influence phyllosphere bacterial community composition. C_LIO_LI224 representative Arabidopsis thaliana phyllosphere bacterial strains were screened on metal(loid) concentration series in synthetic media. We obtained leaf apoplastic fluid ionomes for comparisons with bacteriotoxicity profiles, and tested for relationships between strain-wise metal(loid) tolerances, phylogeny and gene content. C_LIO_LILeaf apoplastic Zn2+ and Cd2+ concentrations were the most likely to arrest growth of metal-sensitive bacteria in planta. Soil bacterial strains were several-fold more sensitive to both these metals than leaf strains, consistent with selection for increased bacterial Zn and Cd tolerance in the phyllosphere. Strains known to govern bacterial community structure were metal-sensitive, with only minor influences of between-metal and between-strain interactions. Bacterial genus explained considerable proportions of the variances in metal(loid)-related gene content and tolerance phenotypes. Bacterial Cd tolerance correlated with the presence and copy number of known Cd-related genes. C_LIO_LIOur results suggest that plant metal homeostasis contributes to structuring bacterial communities in the leaf endosphere. C_LI

plant biology↗

bioRxiv2025

ProbeST: a custom probe design pipeline for Spatial Transcriptomics

Probe-based Spatial Transcriptomics profiles spatially-resolved transcriptomes using gene-specific probe pairs for both Formalin-fixed paraffin-embedded (FFPE) and Fresh Frozen samples. However, its applicability is restricted to human and mouse studies, due to commercial probe set availability. Here, we present ProbeST, an open-source computational pipeline for designing custom probe sets for any organism of interest. We validated ProbeST on FFPE mouse enteroids infected with Salmonella enterica serovar Typhimurium, using custom pathogen probes with the available mouse probe panel. We simultaneously detected host and pathogen transcripts, demonstrating high probe specificity and enabling identification of inflammatory response host genes Mefv, Tnf, and Anxa1 colocalizing to pathogen genes. The reproducible ProbeST workflow expands probe-based Spatial Transcriptomics to studies of non-model organisms and host-pathogen interactions.

bioinformatics↗

bioRxiv2025

The Gfr uptake system provides a context-dependent fitness advantage to Salmonella Typhimurium SL1344 during the initial gut colonization phase

Salmonella enterica serovar Typhimurium (S. Tm) is a major cause of foodborne diarrhea. However, in healthy individuals, the microbiota typically restricts the growth of incoming pathogens, a protective mechanism termed colonization resistance (CR). To circumvent CR, Salmonella strains can utilize private nutrients that remain untapped by the resident microbiota. However, the metabolic pathways and environmental niches promoting pathogen growth are still not completely understood. Here, we investigate the significance of the gfr operon in gut colonization of S. Tm, which is essential for the utilization of fructoselysine (FL) and glucoselysine (GL). These Amadori compounds are present in heated foods with high protein and carbohydrate contents, particularly in Western-type diets. We detected FL in both mouse chow and the intestinal tract of mice and showed that gfr mutants are attenuated during the initial phase of colonization in the murine model. Experiments in gnotobiotic mice and competition experiments with Escherichia coli suggest that gfr-dependent fitness advantage is context-dependent. We conclude that dietary Amadori products like FL can support S. Tm gut colonization, depending on the metabolic capacities of the microbiota.

microbiology↗

bioRxiv2023

mBARq: a versatile and user-friendly framework for the analysis of DNA barcodes from transposon insertion libraries, knockout mutants and isogenic strain populations

DNA barcoding has become a powerful tool for assessing the fitness of strains in a variety of studies, including random transposon mutagenesis screens, attenuation of site-directed mutants, and population dynamics of isogenic strain pools. However, the statistical analysis, visualization and contextualization of the data resulting from such experiments can be complex and require bioinformatic skills. Here, we developed mBARq, a user-friendly tool designed to simplify these steps for diverse experimental setups. The tool is seamlessly integrated with an intuitive web app for interactive data exploration via the STRING and KEGG databases to accelerate scientific discovery.

bioinformatics↗

bioRxiv2023

Dysbiosis of a leaf microbiome is caused by enzyme secretion of opportunistic Xanthomonas strains

Dysbiosis is characterized by a perturbed microbiota associated with host disease. In both plants and animals, the innate immune system contributes to maintain microbiota homeostasis in healthy organisms, with NADPH oxidases playing a crucial role. In Arabidopsis thaliana, the absence of NADPH oxidase RBOHD can lead to an altered leaf microbiota, including an enrichment of opportunistic Xanthomonas pathogens. It is currently unclear whether the microbiota change occurs independently of the opportunistic pathogens or is caused by the latter, and which virulence factors of Xanthomonas are essential for its opportunistic lifestyle. Here, we found that the opportunistic Xanthomonas strains secrete a cocktail of cell wall degrading enzymes via the type-2 secretion system (T2SS) that degrade leaf tissue and promote Xanthomonas growth during plant infection. Both disease severity and leaf degradation activity were increased in rbohD compared to Col-0 plants, attesting to the opportunistic behaviour of the Xanthomonas strains on immune compromised plants. Using gnotobiotic plant experiments with a synthetic bacterial community of more than 100 commensal strains and drop-in of Xanthomonas wildtype or mutant strains revealed that T2SS-dependent virulence is required for plant disease and for the shift in microbiota composition. Overall, our data indicate that a single opportunistic pathogen can drive community shifts, here caused by tissue damage in leaves, creating an environment in which specific commensal bacteria can thrive.

plant biology↗

bioRxiv2023

C-di-AMP levels modulate Staphylococcus aureus cell wall thickness as well as virulence and contribute to antibiotic resistance and tolerance

Beta-lactam antibiotics are widely used to treat infections caused by the important human pathogen Staphylococcus aureus. Resistance to beta-lactams, as found in methicillin-resistant S. aureus (MRSA), renders effective treatment difficult. The second messenger cyclic di-3',5'- adenosine monophosphate (c-di-AMP) promotes beta-lactam resistance in clinical S. aureus isolates. C-di-AMP plays a crucial role in the regulation of cellular processes such as virulence, cell wall homeostasis and resistance to beta-lactams in many bacterial species. In S. aureus, c-di-AMP synthesis is mediated by the diadenylate cyclase DacA, while its degradation is carried out by the phosphodiesterases GdpP and Pde2. In this work, we assessed the effect of altered c-di-AMP levels due to mutations in cacA, gdpP or gdpP/pde2 on virulence determinants. We report that a previously described growth defect in bacteria producing high c-di-AMP levels is mainly attributable to smaller cell size. High c-di-AMP levels also led to decreased survival upon oxidative stress, reduced production of the antioxidant staphyloxanthin, increased oxacillin and fosfomycin resistance and increased cell wall thickness. While resistance to ceftaroline was not affected, high c-di-AMP levels promoted tolerance to this antibiotic. In response to cell wall stress induced by antibiotics, the three-component regulatory system VraTSR mediates an increase in cell wall synthesis via the cell wall stress stimulon (CWSS). Increased c-di-AMP levels led to an activation of the CWSS. Upon deletion of vraR, resistance to oxacillin and fosfomycin as well as cell wall thickness diminished in the {Delta}gdpP mutant, indicating a contribution of the VraTSR system to the cell wall related phenotypes. ImportanceAntibiotic resistance and tolerance are substantial health-care related problems, hampering effective treatment of bacterial infections. Mutations in the phosphodiesterase GdpP, which degrades cyclic di-3', 5'-adenosine monophosphate (c-di-AMP), have recently been associated with resistance to beta-lactam antibiotics in clinical Staphylococcus aureus isolates. In this study, we show that high c-di-AMP levels decreased the cell size and increased the cell wall thickness in S. aureus mutant strains. As a consequence, an increase in resistance to cell wall targeting antibiotics such as oxacillin and fosfomycin as well as in tolerance to ceftaroline, a cephalosporine used to treat MRSA infections, were observed. These findings underline the importance of investigating the role of c-di-AMP in the development of tolerance and resistance to antibiotics in order to optimize treatment in the clinical setting.

microbiology↗

bioRxiv2022

Dashing Growth Curves - a web application for rapid and interactive analysis of microbial growth curves

BackgroundRecording and analyzing microbial growth is a routine task in the life sciences. Microplate readers that record dozens to hundreds of growth curves simultaneously are increasingly used for this task, raising the demand for their rapid and reliable analysis. ResultsHere, we present Dashing Growth Curves, an interactive web application (http://dashing-growth-curves.ethz.ch/) that enables researchers to quickly visualize and analyze growth curves without coding knowledge and independent of operating system. Growth curves can be fitted with Logistic or Gompertz growth models, or manually by selecting the linear growth phase in a logarithmic plot. Furthermore, Dashing Growth Curves automatically groups replicate samples and generates downloadable plots for extracted growth parameters such as growth rate or lag time. ConclusionsDashing Growth Curves is an open-source web application that reduces the time required to analyze microbial growth curves from hours to minutes.

bioinformatics↗

bioRxiv2021

Mitochondria transplantation between living cells

Mitochondria and the complex endomembrane system are hallmarks of eukaryotic cells. To date, it has been difficult to manipulate organelle structures within single live cells. We developed a FluidFM-based approach to extract, inject and transplant organelles from and into living cells with subcellular spatial resolution. The approach enabled the transfer of controlled quantities of mitochondria into cells while maintaining their viability and monitoring their fate in new host cells. Transplantation of healthy and drug-impaired mitochondria into primary keratinocytes allowed real-time tracking of mitochondrial subpopulation rescue. Fusion with the mitochondrial network of recipient cells occurred 20 min after transplantation and continued for over 16 hours. After transfer of mitochondria and cell propagation over generations, we show that donor mtDNA was replicated in recipient cells without the need for selection pressure. The approach opens new prospects for the study of organelle physiology and homeostasis, but also for mechanobiology, synthetic biology, and therapy.

cell biology↗

bioRxiv2021

Genome-wide molecular recording using Live-seq

Single-cell transcriptomics (scRNA-seq) has greatly advanced our ability to characterize cellular heterogeneity in health and disease. However, scRNA-seq requires lysing cells, which makes it impossible to link the individual cells to downstream molecular and phenotypic states. Here, we established Live-seq, an approach for single-cell transcriptome profiling that preserves cell viability during RNA extraction using fluidic force microscopy. Based on cell division, functional responses and whole-cell transcriptome read-outs, we show that Live-seq does not induce major cellular perturbations and therefore can function as a transcriptomic recorder. We demonstrate this recording capacity by preregistering the transcriptomes of individual macrophage-like RAW 264.7 cells that were subsequently subjected to time-lapse imaging after lipopolysaccharide (LPS) exposure. This enabled the unsupervised, genome-wide ranking of genes based on their ability to impact macrophage LPS response heterogeneity, revealing basal NFKBIA expression level and cell cycle state as major phenotypic determinants. Furthermore, we show that Live-seq can be used to sequentially profile the transcriptomes of individual macrophages before and after stimulation with LPS, thus enabling the direct mapping of a cells trajectory. Live-seq can address a broad range of biological questions by transforming scRNA-seq from an end-point to a temporal analysis approach.

molecular biology↗

bioRxiv2020

A plant pathogen utilizes effector proteins for microbiome manipulation

During colonization of their hosts, pathogens secrete effector proteins to promote disease development through various mechanisms. Increasing evidence shows that the host microbiome plays a crucial role in health, and that hosts actively shape their microbiomes to suppress disease. We hypothesized that pathogens evolved to manipulate host microbiomes to their advantage in turn. Here, we show that the fungal plant pathogen Verticillium dahliae utilizes effector proteins for niche colonization through selective manipulation of host microbiomes by suppressing microbes with antagonistic activities. Moreover, we show that effector proteins are similarly exploited for microbiome manipulation in the soil environment, where the fungus resides in absence of a host. In conclusion, we demonstrate that pathogens utilize effector proteins to modulate microbiome compositions and propose that their effector catalogs represent an untapped resource for novel antibiotics.

microbiology↗

bioRxiv2019

ScalaFlux: a scalable approach to quantify fluxes in metabolic subnetworks

13C-metabolic flux analysis (13C-MFA) allows metabolic fluxes to be quantified in living organisms and is a major tool in biotechnology and systems biology. Current 13C-MFA approaches model label propagation starting from the extracellular 13C-labeled nutrient(s), which limits their applicability to the analysis of pathways close to this metabolic entry point. Here, we propose a new approach to quantify fluxes through any metabolic subnetwork of interest by modeling label propagation directly from the metabolic precursor(s) of this subnetwork. The flux calculations are thus purely based on information from within the subnetwork of interest, and no additional knowledge about the surrounding network (such as atom transitions in upstream reactions or the labeling of the extracellular nutrient) is required. This approach, termed ScalaFlux for SCALAble metabolic FLUX analysis, can be scaled up from individual reactions to pathways to sets of pathways. ScalaFlux has several benefits compared with current 13C-MFA approaches: greater network coverage, lower data requirements, independence from cell physiology, robustness to gaps in data and network information, better computational efficiency, applicability to rich media, and enhanced flux identifiability. We validated ScalaFlux using a theoretical network and simulated data. We also used the approach to quantify fluxes through the prenyl pyrophosphate pathway of Saccharomyces cerevisiae mutants engineered to produce phytoene, using a dataset for which fluxes could not be calculated using existing approaches. A broad range of metabolic systems can be targeted with minimal cost and effort, making ScalaFlux a valuable tool for the analysis of metabolic fluxes.\n\nAuthor SummaryMetabolism is a fundamental biochemical process that enables all organisms to operate and grow by converting nutrients into energy and building blocks. Metabolic flux analysis allows the quantification of metabolic fluxes in vivo, i.e. the actual rates of biochemical conversions in biological systems, and is increasingly used to probe metabolic activity in biology, biotechnology and medicine. Isotope labeling experiments coupled with mathematical models of large metabolic networks are the most commonly used approaches to quantify fluxes within cells. However, many biological questions only require flux information from a subset of reactions, not the full network. Here, we propose a new approach with three main advantages over existing methods: better scalability (fluxes can be measured through a single reaction, a metabolic pathway or a set of pathways of interest), better robustness to missing data and information gaps, and lower requirements in terms of measurements and computational resources. We validate our method both theoretically and experimentally. ScalaFlux can be used for high-throughput flux measurements in virtually any metabolic system and paves the way to the analysis of dynamic fluxome rearrangements.

systems biology↗