Biology subjects

Bohn, E.

Publications and source records attributed to Bohn, E..

10 recordsLinked to original sources

bioRxiv2026

Restoring Antibiotic Sensitivity via Metabolic Pathway Manipulation in Pseudomonas aeruginosa

Stopping antimicrobial multidrug resistance (AMR) is essential to maintain the efficacy of current treatments and sustain modern medicine, but current control relies on a coordinated One Health approach involving stewardship, infection prevention and other control measures, without direct actionable mechanisms against resistance itself. Here, integrating proteomics and metabolomics with high-throughput Caenorhabditis elegans infection models, we show that unique synergy of biotin biosynthesis inhibition with metformin uncouples virulence from bacterial viability shutting down major Pseudomonas aeruginosa (PA) virulence mechanisms that impair host survival. Under directed evolution induced by central carbon metabolic stress, laboratory and clinical PA strain isolates acquire mutations in the MexAB-OprM multidrug efflux pump, leading to reversal of the AMR phenotype and restored susceptibility to multiple legacy and last-resort antibiotics such as meropenem. Our findings reveal a previously unexploited vulnerability in PA, its co-dependence on biotin biosynthesis and energy metabolism for virulence and resistance. This work establishes a conceptual framework in which metabolic co-targeting can abolish pathogenesis and drive reversal of antimicrobial resistance. It lays the foundation for first-in-class, non-antibiotic PA-selective anti-virulence and resistance-reversing therapies, key to extending the lifesaving duration of existing antibiotics.

microbiology↗

bioRxiv2026

H4K20me3 and CTCF act reciprocally at TAD boundaries to regulate cell state transitions

Reversible transitions between proliferative and quiescent cell states involve widespread gene expression changes despite stable topologically associating domain (TAD) boundaries. We report a reciprocal antagonism between TAD boundary element CTCF and histone modification H4K20me3 as a central mechanism governing the proliferation-quiescence transition. Genome-wide studies and functional perturbations reveal that elevated H4K20me3 in quiescent fibroblasts displaces CTCF at specific TAD boundaries while CTCF binding predominates in proliferating cells. Increased H4K20me3 reversibly induces a compact chromatin state, elliptical nuclear morphology, and transcriptional programs associated with quiescence. Conversely, elevated CTCF binding drives open chromatin, proliferative gene expression, and cell division despite quiescence signals. Fibroblasts lacking H4K20me3 methyltransferase KMT5C/Suv4-20h2 are hyper-proliferative and KMT5C-deficient mice are larger. Our findings provide a mechanistic framework for how architectural and epigenetic regulators exchange at TAD boundaries to coordinate reversible cell state transitions, a finding with implications for organismal development and diseases of dysregulated proliferation.

cell biology↗

bioRxiv2025

Sequence based prediction of cell type specific microRNA binding and mRNA degradation for therapeutic discovery

MicroRNAs and RNA binding proteins are crucial elements of post-transcriptional gene regulation, which governs the fate of mRNA molecules in the cell. However, the landscape of these regulatory interactions, particularly across different mammalian cell types, remains underexplored. We describe REPRESS, a deep learning model that predicts cell-type-specific microRNA binding and mRNA degradation directly from RNA sequence. REPRESS was trained on AGO2-CLIP, miR-eCLIP and Degradome-Seq data profiling millions of microRNA binding and mRNA degradation sites across multiple cell types in human and mouse. It reveals biology that other state-of-the-art methods did not, such as identifying repressive non-canonical miRNA target sites and decoding the regulatory effects of sequence context and miRNA binding site multiplicity. REPRESS outperforms other advanced methods and neural architectures on a comprehensive suite of seven orthogonal tasks, including identifying genetic variants that affect microRNA binding, predicting out-of-distribution data from massively parallel reporter assays, and predicting canonical and non-canonical miRNA mediated repression. To demonstrate the general utility of REPRESS, we show that it provides insights into novel biology and the design of RNA therapeutics. Code is available at : https://github.com/deepgenomics/repress

genomics↗

bioRxiv2024

The T4bSS of Legionella features a two-step secretion pathway with an inner membrane intermediate for secretion of transmembrane effectors

To promote intracellular survival and infection, Legionella spp. translocate hundreds of effector proteins into eukaryotic host cells using a type IV b protein secretion system (T4bSS). T4bSS are well known to translocate soluble as well as transmembrane domain-containing effector proteins (TMD-effectors) but the mechanisms of secretion are still poorly understood. Herein we investigated the secretion of hydrophobic TMD-effectors, of which about 80 were previously reported to be encoded by L. pneumophila. A proteomic analysis of fractionated membranes revealed that TMD-effectors are targeted to and inserted into the bacterial inner membranes of L. pneumophila independent of the presence of a functional T4bSS. While the T4bSS chaperones IcmS and IcmW were critical for secretion of all tested TMD-effectors, they did not influence inner membrane targeting of these proteins. As for soluble effector proteins, translocation of TMD-effectors into host cells depended on a C-terminal secretion signal and this signal needed to be presented towards the cytoplasmic side of the inner membrane. A different secretion behavior of TMD- and soluble effectors and the need for small periplasmic loops within TMD-effectors provided strong evidence that TMD-effectors are secreted in a two-step secretion process: Initially, an inner membrane intermediate is formed, that is extracted towards the cytoplasmic side, possibly by the help of the type IV coupling protein complex and subsequently secreted into eukaryotic host cells by the T4bSS core complex. Overall, our study highlights the amazing versatility of T4bSS to secrete soluble and TMD-effectors from different subcellular locations of the bacterial cell.

microbiology↗

bioRxiv2023

Non-antibiotic drugs break colonization resistance against pathogenic Gammaproteobacteria

Non-antibiotic drugs can alter the composition of the gut microbiome, with largely undefined implications for human health. Here we compared the susceptibility of commensal and pathogenic bacteria to non-antibiotic drugs and found that pathogens show higher drug resistance, which could favor their expansion after treatment. We then developed a model system to screen for drug-microbiome interactions that increase the risk of enteropathogenic infections. Approximately 35% of the >50 drugs we tested increased the abundance of Salmonella Typhimurium in synthetic and human stool-derived microbial communities. This was due to direct effects of non-antibiotics on individual commensals, altered microbial interactions within communities and the potential of Salmonella to exploit different metabolic niches. Non-antibiotic drugs that favored Salmonella expansion in vitro also promoted other enteric pathogens and increased Salmonella loads in gnotobiotic and conventional mice. These findings may inform future strategies to control pathogen proliferation and to assess individual microbiota-drug-pathogen risks for infection.

microbiology↗

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

Bartonella taylorii: A model organism for studying Bartonella infection in vitro and in vivo

Bartonella spp. are Gram-negative facultative intracellular pathogens that infect diverse mammals and cause a long-lasting intra-erythrocytic bacteremia in their natural host. These bacteria translocate Bartonella effector proteins (Beps) into host cells via their VirB/VirD4 type 4 secretion system (T4SS) in order to subvert host cellular functions, thereby leading to the downregulation of innate immune responses. Most studies on the functional analysis of the VirB/VirD4 T4SS and the Beps were performed with the major zoonotic pathogen Bartonella henselae for which efficient in vitro infection protocols have been established. However, its natural host, the cat, is unsuitable as an experimental infection model. In vivo studies were mostly confined to rodent models using rodent-specific Bartonella species, while the in vitro infection protocols devised for B. henselae are not transferable for those pathogens. The disparities of in vitro and in vivo studies in different species has hampered progress in our understanding of Bartonella pathogenesis. Here we describe the murine-specific strain B. taylorii IBS296 as a new model organism facilitating the study of bacterial pathogenesis both in vitro in cell cultures and in vivo in laboratory mice. We implemented the split NanoLuc luciferase-based translocation assay to study BepD translocation through the VirB/VirD4 T4SS. We found increased effector-translocation into host cells if the bacteria were grown on tryptic soy agar (TSA) plates and experienced a temperature shift immediately before infection. The improved infectivity in vitro could be correlated to an upregulation of the VirB/VirD4 T4SS. Using our adapted infection protocols, we showed BepD-dependent immunomodulatory phenotypes in vitro. In mice, the implemented growth conditions enabled infection by a massively reduced inoculum without having an impact on the course of the intra-erythrocytic bacteremia. The established model opens new avenues to study the role of the VirB/VirD4 T4SS and the translocated Bep effectors in vitro and in vivo.

microbiology↗

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

A NanoLuc luciferase-based assay enabling the real-time analysis of protein secretion and injection by bacterial type III secretion systems

The elucidation of the molecular mechanisms of secretion through bacterial protein secretion systems is impeded by a lack of assays to quantitatively assess secretion kinetics. Also the analysis of the biological role of these secretion systems as well as the identification of inhibitors targeting these systems would greatly benefit from the availability of a simple, quick and quantitative assay to monitor principle secretion and injection into host cells. Here we present a versatile solution to this need, utilizing the small and very bright NanoLuc luciferase to assess secretion and injection through the type III secretion system encoded by Salmonella pathogenicity island 1. The NanoLuc-based secretion assay features a very high signal-to-noise ratio and sensitivity down to the nanoliter scale. The assay enables monitoring of secretion kinetics and is adaptable to a high throughput screening format in 384-well microplates. We further developed NanoLuc and split-NanoLuc-based assays that enable the monitoring of type III secretion-dependent injection of effector proteins into host cells.\n\nImportanceThe ability to secrete proteins to the bacterial cell surface, to the extracellular environment, or even into target cells is one of the foundations of interbacterial as well as pathogen-host interaction. While great progress has been made in elucidating assembly and structure of secretion systems, our understanding of their secretion mechanism often lags behind, not last because of the challenge to quantitatively assess secretion function. Here, we developed a luciferase-based assay to enable the simple, quick, quantitative, and high throughput-compatible assessment of secretion and injection through virulence-associated type III secretion systems. The assay allows detection of minute amounts of secreted substrate proteins either in the supernatant of the bacterial culture or within eukaryotic host cells. It thus provides an enabling technology to elucidate the mechanisms of secretion and injection of type III secretion systems and is likely adaptable to assay secretion through other bacterial secretion systems.

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↗