Search

Conjugative plasmids play a key role in the dissemination of antimicrobial resistance (AMR) genes across bacterial pathogens. AMR plasmids are widespread in clinical settings, but their distribution is not random, and certain associations between plasmids and bacterial clones are particularly successful. For example, the globally spread carbapenem resistance plasmid pOXA-48 can use a wide range of enterobacterial species as hosts, but it is usually associated with a small number of specific Klebsiella pneumoniae clones. These successful associations represent an important threat for hospitalized patients. However, knowledge remains limited about the factors determining AMR plasmid distribution in clinically relevant bacteria. Here, we combined in vitro and in vivo experimental approaches to analyze pOXA-48-associated AMR levels and conjugation dynamics in a collection of wild-type enterobacterial strains isolated from hospitalized patients. Our results revealed significant variability in these traits across different bacterial hosts, with Klebsiella spp. strains showing higher pOXA-48-mediated AMR and conjugation frequencies than Escherichia coli strains. Using experimentally determined parameters, we developed a simple mathematical model to interrogate the contribution of AMR levels and conjugation permissiveness to plasmid distribution in bacterial communities. The simulations revealed that a small subset of clones, combining high AMR levels and conjugation permissiveness, play a critical role in stabilizing the plasmid in different polyclonal microbial communities. These results help to explain the preferential association of plasmid pOXA-48 with K. pneumoniae clones in clinical settings. More generally, our study reveals that species and strain-specific variability in plasmid-associated phenotypes shape AMR evolution in clinically relevant bacterial communities. [ABSTRACT FROM AUTHOR]

Despite the ubiquity and importance of microbial communities, understanding the population dynamics of mixed cultures in structured environments remains a fundamental problem in microbial ecology. Identifying bacterial strains within a complex microbial community represents a challenging technical problem. We describe a low-cost optomechanical device designed to acquire multi-channel timelapse images of bacterial colonies growing in agar plates. This device uses a system of addressable LEDs and fluorescence filters to estimate the spatio-temporal distribution of different fluorescently-tagged cells from time-lapse images obtained using a standard DSLR camera with a macro lens. We demonstrate the potential of this device with a range of applications from experimental microbiology. [ABSTRACT FROM AUTHOR]

Abstract Background The essential Escherichia coli gene ygjD belongs to a universally conserved group of genes whose function has been the focus of a number of recent studies. Here, we put ygjD under control of an inducible promoter, and used time-lapse microscopy and single cell analysis to investigate the phenotypic consequences of the depletion of YgjD protein from growing cells. Results We show that loss of YgjD leads to a marked decrease in cell size and termination of cell division. The transition towards smaller size occurs in a controlled manner: cell elongation and cell division remain coupled, but cell size at division decreases. We also find evidence that depletion of YgjD leads to the synthesis of the intracellular signaling molecule (p)ppGpp, inducing a cellular reaction resembling the stringent response. Concomitant deletion of the relA and spoT genes - leading to a strain that is uncapable of synthesizing (p)ppGpp - abrogates the decrease in cell size, but does not prevent termination of cell division upon YgjD depletion. Conclusions Depletion of YgjD protein from growing cells leads to a decrease in cell size that is contingent on (p)ppGpp, and to a termination of cell division. The combination of single-cell timelapse microscopy and statistical analysis can give detailed insights into the phenotypic consequences of the loss of essential genes, and can thus serve as a new tool to study the function of essential genes.

Metabolic syndrome is a group of disorders which include obesity, diabetes, dyslipidemias, and hypertension. This condition is rapidly increasing in an aging population. The rates of surgery in older patients is also growing and a wide range of operations including minimally invasive procedures is now available for this segment of the population. The number of patients suffering from postoperative adhesions is therefore correspondingly increasing. In addition to preventing and treating the metabolic disease itself, improved therapeutic strategies for the prevention of surgical adhesions have to be developed. Here we review the existing and novel treatment options. [ABSTRACT FROM AUTHOR]

Can we exploit our burgeoning understanding of molecular evolution to slow the progress of drug resistance? One role of an infection clinician is exactly that: to foresee trajectories to resistance during antibiotic treatment and to hinder that evolutionary course. But can this be done at a hospital-wide scale? Clinicians and theoreticians tried to when they proposed two conflicting behavioral strategies that are expected to curb resistance evolution in the clinic, these are known as "antibiotic cycling" and "antibiotic mixing." However, the accumulated data from clinical trials, now approaching 4 million patient days of treatment, is too variable for cycling or mixing to be deemed successful. The former implements the restriction and prioritization of different antibiotics at different times in hospitals in a manner said to "cycle" between them. In antibiotic mixing, appropriate antibiotics are allocated to patients but randomly. Mixing results in no correlation, in time or across patients, in the drugs used for treatment which is why theorists saw this as an optimal behavioral strategy. So while cycling and mixing were proposed as ways of controlling evolution, we show there is good reason why clinical datasets cannot choose between them: by re-examining the theoretical literature we show prior support for the theoretical optimality of mixing was misplaced. Our analysis is consistent with a pattern emerging in data: neither cycling or mixing is a priori better than the other at mitigating selection for antibiotic resistance in the clinic. [ABSTRACT FROM AUTHOR]