Acinetobacter baumannii has emerged as a highly troublesome pathogen for many institutions globally. As a consequence of its immense ability to acquire or upregulate antibiotic drug resistance determinants, it has justifiably been propelled to the forefront of scientific attention. Apart from its predilection for the seriously ill within intensive care units, A. baumannii has more recently caused a range of infectious syndromes in military personnel injured in the Iraq and Afghanistan conflicts. This review details the significant advances that have been made in our understanding of this remarkable organism over the last 10 years, including current taxonomy and species identification, issues with susceptibility testing, mechanisms of antibiotic resistance, global epidemiology, clinical impact of infection, host-pathogen interactions, and infection control and therapeutic considerations.

Acinetobacter baumannii: Emergence of a Successful Pathogen

http://web.mit.edu/biophysics/papers/CELL2008.pdf

Nature, Nurture, or Chance: Stochastic Gene Expression and Its Consequences

Genetically identical cells exposed to the same environmental conditions can show significant variation in molecular content and marked differences in phenotypic characteristics. This variability is linked to stochasticity in gene expression, which is generally viewed as having detrimental effects on cellular function with potential implications for disease. However, stochasticity in gene expression can also be advantageous. It can provide the flexibility needed by cells to adapt to fluctuating environments or respond to sudden stresses, and a mechanism by which population heterogeneity can be established during cellular differentiation and development.

/pdf/stochasticity-in-gene-expression-from-theories-to-phenotypes-32urfuz0k3.pdf

Stochasticity in gene expression: from theories to phenotypes

A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations

Biofilms contain bacterial cells that are in a wide range of physiological states. Within a biofilm population, cells with diverse genotypes and phenotypes that express distinct metabolic pathways, stress responses and other specific biological activities are juxtaposed. The mechanisms that contribute to this genetic and physiological heterogeneity include microscale chemical gradients, adaptation to local environmental conditions, stochastic gene expression and the genotypic variation that occurs through mutation and selection. Here, we discuss the processes that generate chemical gradients in biofilms, the genetic and physiological responses of the bacteria as they adapt to these gradients and the techniques that can be used to visualize and measure the microscale physiological heterogeneities of bacteria in biofilms.

Physiological heterogeneity in biofilms.

A fraction of a genetically homogeneous microbial population may survive exposure to stress such as antibiotic treatment. Unlike resistant mutants, cells regrown from such persistent bacteria remain sensitive to the antibiotic. We investigated the persistence of single cells of Escherichia coli with the use of microfluidic devices. Persistence was linked to preexisting heterogeneity in bacterial populations because phenotypic switching occurred between normally growing cells and persister cells having reduced growth rates. Quantitative measurements led to a simple mathematical description of the persistence switch. Inherent heterogeneity of bacterial populations may be important in adaptation to fluctuating environments and in the persistence of bacterial infections.

https://science.sciencemag.org/content/sci/305/5690/1622.full.pdf

Bacterial Persistence as a Phenotypic Switch

Antibiotic resistance can evolve through the sequential accumulation of multiple mutations. To study such gradual evolution, we developed a selection device, the 'morbidostat', that continuously monitors bacterial growth and dynamically regulates drug concentrations, such that the evolving population is constantly challenged. We analyzed the evolution of resistance in Escherichia coli under selection with single drugs, including chloramphenicol, doxycycline and trimethoprim. Over a period of ∼20 days, resistance levels increased dramatically, with parallel populations showing similar phenotypic trajectories. Whole-genome sequencing of the evolved strains identified mutations both specific to resistance to a particular drug and shared in resistance to multiple drugs. Chloramphenicol and doxycycline resistance evolved smoothly through diverse combinations of mutations in genes involved in translation, transcription and transport. In contrast, trimethoprim resistance evolved in a stepwise manner, through mutations restricted to the gene encoding the enzyme dihydrofolate reductase (DHFR). Sequencing of DHFR over the time course of the experiment showed that parallel populations evolved similar mutations and acquired them in a similar order.

/pdf/evolutionary-paths-to-antibiotic-resistance-under-3usx75jf07.pdf

Evolutionary paths to antibiotic resistance under dynamically sustained drug selection

Exposure of an isogenic bacterial population to a cidal antibiotic typically fails to eliminate a small fraction of refractory cells. Historically, fractional killing has been attributed to infrequently dividing or nondividing "persisters." Using microfluidic cultures and time-lapse microscopy, we found that Mycobacterium smegmatis persists by dividing in the presence of the drug isoniazid (INH). Although persistence in these studies was characterized by stable numbers of cells, this apparent stability was actually a dynamic state of balanced division and death. Single cells expressed catalase-peroxidase (KatG), which activates INH, in stochastic pulses that were negatively correlated with cell survival. These behaviors may reflect epigenetic effects, because KatG pulsing and death were correlated between sibling cells. Selection of lineages characterized by infrequent KatG pulsing could allow nonresponsive adaptation during prolonged drug exposure.

https://science.sciencemag.org/content/sci/339/6115/91.full.pdf

Dynamic Persistence of Antibiotic-Stressed Mycobacteria

A key aspect of bacterial survival is the ability to evolve while migrating across spatially varying environmental challenges. Laboratory experiments, however, often study evolution in well-mixed systems. Here, we introduce an experimental device, the microbial evolution and growth arena (MEGA)–plate, in which bacteria spread and evolved on a large antibiotic landscape (120 × 60 centimeters) that allowed visual observation of mutation and selection in a migrating bacterial front. While resistance increased consistently, multiple coexisting lineages diversified both phenotypically and genotypically. Analyzing mutants at and behind the propagating front, we found that evolution is not always led by the most resistant mutants; highly resistant mutants may be trapped behind more sensitive lineages. The MEGA-plate provides a versatile platform for studying microbial adaption and directly visualizing evolutionary dynamics.

/pdf/spatiotemporal-microbial-evolution-on-antibiotic-landscapes-3tnnmj9sgi.pdf

Spatiotemporal microbial evolution on antibiotic landscapes

Multidrug combinations are increasingly important in combating the spread of antibiotic-resistance in bacterial pathogens. On a broader scale, such combinations are also important in understanding microbial ecology and evolution. Although the effects of multidrug combinations on bacterial growth have been studied extensively, relatively little is known about their impact on the differential selection between sensitive and resistant bacterial populations. Normally, the presence of a drug confers an advantage on its resistant mutants in competition with the sensitive wild-type population. Here we show, by using a direct competition assay between doxycycline-resistant and doxycycline-sensitive Escherichia coli, that this differential selection can be inverted in a hyper-antagonistic class of drug combinations. Used in such a combination, a drug can render the combined treatment selective against the drug's own resistance allele. Further, this inversion of selection seems largely insensitive to the underlying resistance mechanism and occurs, at sublethal concentrations, while maintaining inhibition of the wild type. These seemingly paradoxical results can be rationalized in terms of a simple geometric argument. Our findings demonstrate a previously unappreciated feature of the fitness landscape for the evolution of resistance and point to a trade-off between the effect of drug interactions on absolute potency and the relative competitive selection that they impose on emerging resistant populations.

Remy Chait

Papers

Bacterial Persistence as a Phenotypic Switch

Evolutionary paths to antibiotic resistance under dynamically sustained drug selection

Dynamic Persistence of Antibiotic-Stressed Mycobacteria

Spatiotemporal microbial evolution on antibiotic landscapes

Antibiotic interactions that select against resistance