Biology subjects

Kiefer, P.

Publications and source records attributed to Kiefer, P..

3 recordsLinked to original sources

bioRxiv2023

The Legionella autoinducer LAI-1 is delivered by outer membrane vesicles to promote inter-bacterial and inter-kingdom signaling

Legionella pneumophila is an environmental bacterium, which replicates in amoeba but also in macrophages, and causes a life-threatening pneumonia called Legionnaires disease. The opportunistic pathogen employs the -hydroxyketone compound LAI-1 (Legionella autoinducer-1) for intra-species and inter-kingdom signaling. LAI-1 is produced by the autoinducer synthase LqsA, but it is not known, how LAI-1 is released by the pathogen. Here, we use a V. cholerae luminescence reporter strain and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to detect bacteria-produced and synthetic LAI-1. Ectopic production of LqsA in E. coli generated LAI-1, which partitions to outer membrane vesicles (OMVs), and slightly reduces OMV size. These E. coli OMVs trigger luminescence of the V. cholerae reporter strain and inhibit the migration of Dictyostelium discoideum amoeba. Overexpression of lqsA in L. pneumophila under the control of strong stationary phase promoters (PflaA or P6SRNA), but not under control of its endogenous promoter (PlqsA), produces LAI-1, which is detected in purified OMVs. These L. pneumophila OMVs trigger luminescence of the Vibrio reporter strain and inhibit D. discoideum migration. L. pneumophila OMVs are smaller upon overexpression of lqsA or upon addition of LAI-1 to growing bacteria, and therefore, LqsA affects OMV production. The overexpression of lqsA but not a catalytically inactive mutant promotes intracellular replication of L. pneumophila in macrophages, indicating that intracellularly produced LA1-1 modulates the interaction in favour of the pathogen. Taken together, we provide evidence that L. pneumophila LAI-1 is secreted through OMVs and promotes inter-bacterial communication as well as interactions with eukaryotic host cells. Originality - Significance StatementInter-kingdom signaling involving low molecular weight bacterial compounds that are detected by eukaryotic cells represents an important, yet incompletely understood aspect of pathogen-host interactions. In many cases, the small signaling molecules are produced in only little amounts, their secretion mechanism is not known, and their effects on eukaryotic host cells are barely studied. Here, we reveal that the -hydroxyketone compound LAI-1 of L. pneumophila is released from the bacteria by outer membrane vesicles, which promote inter-bacterial communication as well as inter-kingdom signaling.

microbiology↗

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↗

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↗