Biology subjects

Schuetz, M.

Publications and source records attributed to Schuetz, M..

9 recordsLinked to original sources

bioRxiv2025

Stathmin 1 regulates mitophagy and cellular function in hematopoietic stem cells

Stathmin 1 is a cytoplasmic phosphoprotein that regulates microtubule dynamics via promotion of microtubule catastrophe and sequestration of free tubulin heterodimers. Stathmin 1 is highly expressed in hematopoietic stem cells (HSCs), and overexpressed in leukemic cells, however its role in HSCs is not known. Herein, we found that loss of Stathmin 1 is associated with altered microtubule architecture in HSCs, and markedly impaired HSC function. Transcriptomic studies suggested alterations in oxidative phosphorylation in Stmn1-/- HSCs, and further mechanistic studies revealed defective mitochondrial structure and function in the absence of Stathmin 1 with increased ROS production. Microtubules associate with mitochondria and lysosomes to facilitate autophagosome formation and mitophagy, and indeed we found that this critical mitochondrial quality control process is impaired in Stathmin 1-deficient HSCs. Finally, stimulation of autophagy improved the colony forming ability of Stmn1-/- hematopoietic stem and progenitor cells. Together, our data identify Stathmin 1 as a novel regulator of mitophagy and mitochondrial health in HSCs. Key PointsO_LIThe microtubule regulating protein Stathmin 1 is highly expressed in HSPCs and promotes normal microtubule architecture. C_LIO_LILoss of Stathmin 1 in HSPCs leads to impaired autophagy with abnormal mitochondrial morphology, decreased respiratory capacity, and impaired cellular function. C_LI

cell biology↗

bioRxiv2024

DFCP1 is a Regulator of ATGL-mediated Lipid Droplet Lipolysis

Lipid droplets (LDs) are transient lipid storage organelles that can be readily tapped to resupply cells with energy or lipid building blocks, and therefore play a central role in cellular metabolism. Double FYVE Domain Containing Protein 1 (DFCP1/ZFYV1) has emerged as a key regulator of LD metabolism, where the nucleotide-dependent accumulation of DFCP1 on LDs influences their size, number, and dynamics. Here we show that DFCP1 regulates lipid metabolism by directly modulating the activity of Adipose Triglyceride Lipase (ATGL/PNPLA2), the rate-limiting lipase driving the catabolism of LDs. We show through pharmacological inhibition of key enzymes associated with LD metabolism that DFCP1 specifically regulates lipolysis and, to a lesser extent, lipophagy. Consistent with this observation, DFCP1 interacts with and recruits ATGL to LDs in starved cells, irrespective of known regulatory factors of ATGL. We further establish that this interaction prevents dynamic disassociation of ATGL from LDs and thereby impedes the rate of LD lipolysis. Collectively, our findings indicate that DFCP1 primes ATGL on LDs to promote rapid LD catabolism.

cell biology↗

bioRxiv2022

The uncharacterized protein YgfB contributes to β-lactam resistance in Pseudomonas aeruginosa by inhibiting the expression of the amidase AmpDh3

YgfB-mediated {beta}-lactam resistance was recently identified in multi drug resistant Pseudomonas aeruginosa. We show that YgfB upregulates expression of the {beta}-lactamase AmpC by repressing the function of the regulator of the programmed cell death pathway AlpA. In response to DNA damage, the antiterminator AlpA induces expression of the alpBCDE autolysis genes and of the peptidoglycan amidase AmpDh3. YgfB interacts with AlpA and represses the ampDh3 expression. Thus, YgfB indirectly prevents AmpDh3 from reducing the levels of cell wall-derived 1,6-anhydro-N-acetylmuramyl-peptides, required to induce the transcriptional activator AmpR in promoting the ampC expression and {beta}-lactam resistance. Ciprofloxacin-mediated DNA damage induces AlpA-dependent production of AmpDh3 as previously shown, which should reduce {beta}-lactam resistance. YgfB, however, counteracts the {beta}-lactam enhancing activity of ciprofloxacin by repressing ampDh3 expression and lowering the benefits of this drug combination. Altogether, YgfB represents a new player in the complex regulatory network of AmpC regulation.

microbiology↗

bioRxiv2022

Functional traits trade-offs define plant population stability worldwide

O_LIEcological theory posits that temporal stability patterns in plant populations are associated with differences in species ecological strategies. However, empirical evidence is lacking about which traits, or trade-offs, underlie species stability, specially across different ecosystems. C_LIO_LITo address this, we compiled a global collection of long-term permanent vegetation records (>7000 plots from 78 datasets) from a wide range of habitats and combined this with existing trait databases. We tested whether the observed inter-annual variability in species abundance (coefficient of variation) was related to multiple individual traits and multivariate axes of trait variations (PCoA axes). C_LIO_LIWe found that species with greater leaf dry matter content and seed mass were consistently more stable over time (lower variability in species abundance) although other leaf traits played a significant role as well, albeit weaker. Using multivariate axes did not improve predictions by specific traits. C_LIO_LIOur results confirm existing theory, providing compelling empirical evidence on the importance of specific traits, which point at ecological trade-offs in different resource use and dispersal strategies, on the stability of plant populations worldwide. C_LI

ecology↗

bioRxiv2021

LOTVS: a global collection of permanent vegetation plots

Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long-term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng-Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time-series derived from the regular monitoring of vascular plants in permanent plots. With 79 datasets from five continents and 7789 vegetation time-series monitored for at least six years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine-grained vegetation time-series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology.

ecology↗

bioRxiv2021

Multiple resource limitations explain biomass-precipitation relationships in grasslands

Interannual variability in grassland primary production is strongly driven by precipitation, nutrient availability and herbivory, but there is no general consensus on the mechanisms linking these variables. If grassland biomass is limited by the single most limiting resource at a given time, then we expect that nutrient addition will not affect biomass production at arid sites. We conducted a distributed experiment manipulating nutrients and herbivores at 44 grassland sites in 8 regions around the world, spanning a broad range in aridity. We estimated the effects of 5-11 years of nutrient addition and herbivore exclusion treatments on precipitation sensitivity of biomass (proportional change in biomass relative to proportional change in rainfall among years), and the biomass in the driest year (to measure treatment effects when water was most limiting) at each site. Grazer exclusion did not interact with nutrients to influence driest year biomass or sensitivity. Nutrient addition increased driest year biomass by 74% and sensitivity by 0.12 (proportional units), and that effect did not change across the range of aridity spanned by our sites. Grazer exclusion did not interact with nutrients to influence sensitivity or driest year biomass. At almost half of our sites, the previous year's rainfall explained as much variation in biomass as current year precipitation. Overall, our distributed fertilization experiment detected co-limitation between nutrients and water governing grasslands, with biomass sensitivity to precipitation being limited by nutrient availability irrespective of site aridity and herbivory. Our findings refute the classical ideas that grassland plant performance is limited by the single most limiting resource at a site. This suggests that nutrient eutrophication will destabilize grassland ecosystems through increased sensitivity to precipitation variation.

ecology↗

bioRxiv2020

Model-based prediction of bacterial population dynamics in gastrointestinal infection

The complex interplay of a pathogen with the host immune response and the endogenous microbiome determines the course and outcome of gastrointestinal infection (GI). Expansion of a pathogen within the gastrointestinal tract implies an increased risk to develop systemic infection. Through computational modeling, we aimed to calculate bacterial population dynamics in GI in order to predict infection course and outcome. For the implementation and parameterization of the model, oral mouse infection experiments with Yersinia enterocolitica were used. Our model takes into account pathogen specific characteristics, such as virulence, as well as host properties, such as microbial colonization resistance or immune responses. We were able to confirm the model calculations in these scenarios by experimental mouse infections and show that it is possible to computationally predict the infection course. Far future clinical application of computational modeling of infections may pave the way for personalized treatment and prevention strategies of GI.

microbiology↗

bioRxiv2019

Chemical biofilm dislodgement with chelating and reducing agents in comparison to sonication: implications for the diagnosis of implant associated infection

Sonication of removed devices improved the microbiological diagnosis of infection. Recently, chemical agents have been investigated for dislodgement of biofilms, including the chelating agent ethylenediaminetetraacetic acid (EDTA) and the reducing agent dithiothreitol (DTT). We compared the efficacy of chemical methods (EDTA and DTT) to sonication for biofilm dislodgement. Staphylococcus epidermidis (ATCC 35984) and Pseudomonas aeruginosa (ATCC 53278) biofilms were grown on porous glass beads for 3 days. After biofilm formation, beads were exposed to 0.9% saline, sonication and/or chemical agents. Quantitative and qualitative biofilm analyses were performed by colony counting (CFU/ml), isothermal microcalorimetry and scanning electron microscopy. The colony counts after treatment with EDTA and DTT were similar to those after exposure to 0.9% saline (6.3, 6.1 and 6.0 log CFU/ml, respectively) for S. epidermidis biofilms, and (5.1, 5.2 and 5.0 log CFU/ml, respectively) for P. aeruginosa biofilm. Sonication detected higher CFU counts (7.5 log CFU/ml) for S. epidermidis; (p<0.05) and 6.5 log for P. aeruginosa biofilm (p <0.05). Concordant results were detected with isothermal microcalorimetry and scanning electron microscopy. In conclusion, the CFU count after treatment of S. epidermidis or P. aeruginosa biofilms with EDTA and DTT was similar to those observed after 0.9% saline used as control. In contrast, sonication was superior to chemical methods for biofilm dislodgment and detection of microorganisms in sonication fluid. In conclusion, our study showed that sonication is superior to chemical method to dislodge bacterial biofilm from artificial surface and should be considered as standard diagnostic method for biofilm detection in implant-associated infections.

microbiology↗

bioRxiv2018

Multi-omics approach identifies novel pathogen-derived prognostic biomarkers in patients with Pseudomonas aeruginosa bloodstream infection

Pseudomonas aeruginosa is a human pathogen that causes health-care associated blood stream infections (BSI). Although P. aeruginosa BSI are associated with high mortality rates, the clinical relevance of pathogen-derived prognostic biomarker to identify patients at risk for unfavorable outcome remains largely unexplored. We found novel pathogen-derived prognostic biomarker candidates by applying a multi-omics approach on a multicenter sepsis patient cohort. Multi-level Cox regression was used to investigate the relation between patient characteristics and pathogen features (2298 accessory genes, 1078 core protein levels, 107 parsimony-informative variations in reported virulence factors) with 30-day mortality. Our analysis revealed that presence of the helP gene encoding a putative DEAD-box helicase was independently associated with a fatal outcome (hazard ratio 2.01, p = 0.05). helP is located within a region related to the pathogenicity island PAPI-1 in close proximity to a pil gene cluster, which has been associated with horizontal gene transfer. Besides helP, elevated protein levels of the bacterial flagellum protein FliL (hazard ratio 3.44, p < 0.001) and of a bacterioferritin-like protein (hazard ratio 1.74, p = 0.003) increased the risk of death, while high protein levels of a putative aminotransferase were associated with an improved outcome (hazard ratio 0.12, p < 0.001). The prognostic potential of biomarker candidates and clinical factors was confirmed with different machine learning approaches using training and hold-out datasets. The helP genotype appeared the most attractive biomarker for clinical risk stratification due to its relevant predictive power and ease of detection.

microbiology↗