Biology subjects

Benz, F.

Publications and source records attributed to Benz, F..

6 recordsLinked to original sources

bioRxiv2024

Drivers of ecological success for Escherichia coli vary among human gut microbiome samples from different individuals

Gut microbial community composition varies from one person to another. Potentially, this means the ecological interactions experienced by individual strains or species also vary among microbiomes of different people. However, testing this directly in human microbiomes and identifying ecological drivers involved is challenging. Here, we use replicated anaerobic microcosms to quantify variability of population growth for a key commensal species among microbiome samples from different individuals, and to identify underlying intra- and interspecific interactions. In a reciprocal transplant experiment, both absolute and relative growth performance of different Escherichia coli strains varied among gut microbiome samples from healthy individuals. This was partly explained by intraspecific competition: ecological success of individual E. coli strains was associated with displacement of resident conspecifics. However, the determinants of E. coli growth varied among samples. In one microbiome sample with a distinctive taxonomic composition, culture acidification by resident microbes impaired growth of all E. coli strains. We identified a strain of Clostridium butyricum contributing to this effect, and showed that transferring it into other microbiomes predictably altered pH, fermentation product profiles (butyrate accumulation and acetate/lactate depletion) and population growth of other species including E. coli, thereby reshaping overall taxonomic composition. Our results suggest natural inter-individual gut microbiome variation translates to variable ecological interactions with incoming bacteria, but these dynamics can be manipulated by a generalizable interspecies interaction. Significance statementGut-microbiome variation among healthy individuals is widely documented, yet its impact on the success of incoming bacterial strains and its implications for microbiome-targeted interventions remain unclear. Here, we test this experimentally by cultivating stool samples from healthy individuals and transplanting strains across samples. We reveal a functional relationship between microbiome variation and growth performance of individual strains. This underscores the challenge of predicting colonization outcomes. Yet, we identify a taxon contributing to the distinct functional profile of one of the samples, and show that its transplantion into other microbiome samples reproducibly alters key properties, including pH and population growth of other bacteria, revealing a common ecological control point. These findings advance our ability to explain and manipulate human gut-microbiome variation.

microbiology↗

bioRxiv2024

Effectiveness of CRISPR-Cas in Sensitizing Bacterial Populations with Plasmid-Encoded Antimicrobial Resistance

The spread of bacteria resistant to antibiotics poses a serious threat to human health. Genes that encode antibiotic resistance are often harbored on plasmids, extra-chromosomal DNA molecules found in bacteria. The emergence of multiresistance plasmids is particularly problematic and demands the development of new antibiotics and alternative strategies. CRISPR-Cas derived tools with their sequence specificity offer a promising new approach to combating antibiotic resistance. By introducing CRISPR-Cas encoding plasmids that target antibiotic resistance genes on plasmids, the susceptibility of bacteria to conventional antibiotics can be restored. However, genetic variation within bacterial populations can hinder the effectiveness of such CRISPR-Cas tools by allowing some mutant plasmids to evade CRISPR-mediated cleaving or gene silencing. In this study, we develop a model to test the effectiveness of CRISPR-Cas in sensitizing bacterial populations carrying resistance on non-transmissible plasmids and assess the success probability of a subsequent treatment with conventional antibiotics. abstract hgt We evaluate this probability according to the target interference mechanism, the copy number of the resistance-encoding plasmid, and its compatibility with the CRISPR-Cas encoding plasmid. Our results identify promising approaches to revert antibiotic resistance with CRISPR-Cas encoding plasmids: A DNA-cleaving CRISPR-Cas system on a plasmid incompatible with the targeted plasmid is most effective for low copy numbers, while for resistance plasmids with higher copy numbers gene silencing by CRISPR-Cas systems encoded on compatible plasmids is the superior solution.

evolutionary biology↗

bioRxiv2023

Type IV-A3 CRISPR-Cas systems drive inter-plasmid conflicts by acquiring spacers in trans

Type IV-A CRISPR-Cas systems are primarily encoded on plasmids and form multi-subunit ribonucleoprotein complexes with unknown biological functions. In contrast to other CRISPR-Cas types, they lack the archetypical CRISPR acquisition module and encode a DinG helicase instead of a nuclease component. Type IV-A3 systems are carried by large conjugative plasmids that often harbor multiple antibiotic-resistance genes. Although their CRISPR array contents suggest a role in inter-plasmid conflicts, this function and the underlying mechanisms have remained unexplored. Here, we demonstrate that a plasmid-encoded type IV-A3 CRISPR-Cas system co-opts the type I-E adaptation machinery from its clinical Klebsiella pneumoniae host to update its CRISPR array. Furthermore, we demonstrate that robust interference of conjugative plasmids and phages is elicited through CRISPR RNA-dependent transcriptional repression. By targeting plasmid core functions, type IV-A3 can prevent the uptake of incoming plasmids, limit their horizontal transfer, and destabilize co-residing plasmids, altogether supporting type IV-A3s involvement in plasmid competition. Collectively, our findings shed light on the molecular mechanisms and ecological function of type IV-A3 systems and have broad implications for understanding and countering the spread of antibiotic resistance in clinically relevant strains.

microbiology↗

bioRxiv2022

Host-specific plasmid evolution explains the variable spread of clinical antibiotic-resistance plasmids

Antibiotic resistance encoded on plasmids is a pressing global health problem. Predicting which plasmids spread/decline in the long term remains a huge challenge, even though some key parameters influencing plasmid stability have been identified, such as plasmid growth costs and horizontal transfer rates. Here, we show these parameters evolve in a strain-specific way among clinical plasmids/bacteria, and this occurs rapidly enough to alter the relative likelihoods of different bacterium-plasmid combinations spreading/declining. We used experiments with Escherichia coli and antibiotic-resistance plasmids isolated from patients, paired with a mathematical model, to show long-term plasmid stability (beyond antibiotic exposure) was better explained by evolutionary changes in plasmid-stability traits than by initial variation among bacterium-plasmid combinations. Evolutionary trajectories were specific to particular bacterium-plasmid combinations. Genome sequencing and genetic manipulation helped explain this, revealing epistatic (here, strain-dependent) effects of key genetic changes affecting horizontal plasmid transfer. Several genetic changes involved mobile elements and pathogenicity islands. Rapid strain-specific evolution can thus outweigh ancestral phenotypes as a predictor of plasmid stability. Accounting for strain-specific plasmid evolution in natural populations could improve our ability to anticipate and manage successful bacterium-plasmid combinations.

evolutionary biology↗

bioRxiv2020

Estimating the rate of plasmid transfer in liquid mating cultures

Plasmids are important vectors for the spread of genes among diverse populations of bacteria. However, there is no standard method to determine the rate at which they spread horizontally via conjugation. Here, we compare commonly used methods on simulated and experimental data, and show that the resulting conjugation rate estimates often depend strongly on the time of measurement, the initial population densities, or the initial ratio of donor to recipient populations. Differences in growth rate, e.g. induced by sub-lethal antibiotic concentrations or temperature, can also significantly bias conjugation rate estimates. We derive a new end-point measure to estimate conjugation rates, which extends the well-known Simonsen method to include the effects of differences in population growth and conjugation rates from donors and transconjugants. We further derive analytical expressions for the parameter range in which these approximations remain valid. We present an easy to use R package and web interface which implement both new and previously existing methods to estimate conjugation rates. The result is a set of tools and guidelines for accurate and comparable measurement of plasmid conjugation rates. HighlightsO_LIWe present an R package and Shiny app to estimate conjugation rates from experimental data C_LIO_LIWe highlight the diversity of existing measures used to estimate conjugation rates C_LIO_LIWe show these measures are biased for populations with differing growth and conjugation rates from donors or transconjugants C_LIO_LIWe develop a new end-point measure which accounts for such differences in growth and conjugation rates C_LI

microbiology↗

bioRxiv2019

Extended-spectrum beta-lactamase antibiotic resistance plasmids have diverse transfer rates and can be spread in the absence of selection

Horizontal gene transfer, mediated by conjugative plasmids, is a major driver of the global spread of antibiotic resistance. However, the relative contributions of factors that underlie the spread of clinically relevant plasmids are unclear. Here, we quantified conjugative transfer dynamics of Extended Spectrum Beta-Lactamase (ESBL) producing plasmids in the absence of antibiotics. We showed that clinical Escherichia coli strains natively associated with ESBL-plasmids conjugate efficiently with three distinct E. coli strains and one Salmonella enterica serovar Typhimurium strain, reaching final transconjugant frequencies of up to 1% within 24 hours in vitro. The variation of final transconjugant frequencies varied among plasmids, donors and recipients and was better explained by variation in conjugative transfer efficiency than by variable clonal expansion. We identified plasmid-specific genetic factors, specifically the presence/absence of transfer genes, that influenced final transconjugant frequencies. Finally, we investigated plasmid spread within the mouse intestine, demonstrating qualitative agreement between plasmid spread in vitro and in vivo. This suggests a potential for the prediction of plasmid spread in the gut of animals and humans, based on in vitro testing. Altogether, this may allow the identification of resistance plasmids with high spreading potential and help to devise appropriate measures to restrict their spread.

microbiology↗