Superbugs: How They Evolve and Minimize the Cost of Resistance

Feedstock-dependent antibiotic resistance gene patterns and expression profiles in industrial scale biogas plants revealed by meta-omics technology

This study investigated antimicrobial resistance in the anaerobic digesters of two industrial-scale biogas plants processing agricultural biomass and municipal wastewater sludge. A combination of deep sequencing and genome-centric workflow was implemented for metagenomic and metatranscriptomics data analysis to comprehensively examine potential antimicrobial resistance in microbial communities. Anaerobic microbes were found to harbour numerous antibiotic resistance genes (ARGs), with 58.85% of the metagenome-assembled genomes (MAGs) harbouring antibiotic resistance. A moderately positive correlation was observed between the abundance and expression of ARGs. ARGs were located primarily on bacterial chromosomes. A higher expression of resistance genes was observed on plasmids than on chromosomes. Risk index assessment suggests that most ARGs identified posed a significant risk to human health. However, potentially pathogenic bacteria showed lower ARG expression than non-pathogenic ones, indicating that anaerobic treatment is effective against pathogenic microbes. Resistomes at the gene category level were associated with various antibiotic resistance categories, including multidrug resistance, beta-lactams, glycopeptides, peptides, and macrolide-lincosamide-streptogramin (MLS). Differential expression analysis revealed specific genes associated with potential pathogenicity, emphasizing the importance of active gene expression in assessing the risks associated with ARGs.

Evolutionary rescue of resistant mutants is governed by a balance between radial expansion and selection in compact populations

Mutation-mediated treatment resistance is one of the primary challenges for modern antibiotic and anti-cancer therapy. Yet, many resistance mutations have a substantial fitness cost and are subject to purifying selection. How emerging resistant lineages may escape purifying selection via subsequent compensatory mutations is still unclear due to the difficulty of tracking such evolutionary rescue dynamics in space and time. Here, we introduce a system of fluorescence-coupled synthetic mutations to show that the probability of evolutionary rescue, and the resulting long-term persistence of drug resistant mutant lineages, is dramatically increased in dense microbial populations. By tracking the entire evolutionary trajectory of thousands of resistant lineages in expanding yeast colonies we uncover an underlying quasi-stable equilibrium between the opposing forces of radial expansion and natural selection, a phenomenon we term inflation-selection balance. Tailored computational models and agent-based simulations corroborate the fundamental nature of the observed effects and demonstrate the potential impact on drug resistance evolution in cancer. The described phenomena should be considered when predicting multi-step evolutionary dynamics in any mechanically compact cellular population, including pathogenic microbial biofilms and solid tumors. The insights gained will be especially valuable for the quantitative understanding of response to treatment, including emerging evolution-based therapy strategies.

Antibiotic use in critical illness

OBJECTIVE

To provide a review on the current use of antimicrobials with a discussion on the pharmacokinetic and pharmacodynamic profiles of antimicrobials in critically ill patients, the challenges of drug resistance, the use of diagnostic testing to direct therapy, and the selection of the most likely efficacious antimicrobial protocol.

ETIOLOGY

Patients in the intensive care unit often possess profound pathophysiologic changes that can complicate antimicrobial therapy. Although many antimicrobials have known pharmacodynamic profiles, critical illness can cause wide variations in their pharmacokinetics. The two principal factors affecting pharmacokinetics are volume of distribution and drug clearance. Understanding the interplay between critical illness, drug pharmacokinetics, and antimicrobial characteristics (ie, time-dependent vs concentration-dependent) may improve antimicrobial efficacy and patient outcome.

DIAGNOSIS

Utilizing bacterial culture and susceptibility can aid in identifying drug resistant infections, selecting the most appropriate antimicrobials, and hindering the future development of drug resistance.

THERAPY

Having a basic knowledge of antimicrobial function and how to use diagnostics to direct therapeutic treatment is paramount in managing this patient population. Diagnostic testing is not always available at the time of initiation of antimicrobial therapy, so empiric selections are often necessary. These empiric choices should be made based on the location of the infection and the most likely infecting bacteria.

PROGNOSIS

Studies have demonstrated the importance of moving away from a "one dose fits all" approach to antimicrobial therapy. Instead there has been a move toward an individualized approach that takes into consideration the pharmacokinetic and pharmacodynamic variabilities that can occur in critically ill patients.

Escaping an evolutionary lobster trap: drug resistance and compensatory mutation in a fluctuating environment

The fitness landscape concept aids intuition on adaptive evolution through low fitness genotypes. Evolutionary processes become complex when environments and therefore fitnesses fluctuate. Antibiotic resistance evolution in bacteria is an important example of such dynamics. Resistance bears a cost in the drug-free environment, but compensatory mutation can lower this cost, creating a fitness valley. With the drug present, the valley becomes a hill that is easily climbed. Once a population is dominated by resistant-compensated genotypes, reversion to sensitivity is difficult: this phenomenon has been described as an evolutionary lobster trap. With increasing frequencies of drug resistance among pathogenic bacteria, it is critical to understand how this trap can be escaped. Here, we develop stochastic models to investigate these dynamics. The residual fitness cost (the cost remaining after compensatory mutation has occurred) is a key parameter. Reversion to sensitivity is favored when the time spent in the absence of the drug relative to its presence is high compared to the residual fitness cost. Population sizes are also important: in large populations, resistant-compensated mutants appear in resistant-uncompensated or sensitive-compensated genotypes without fixation of these intermediates. This stochastic tunneling effect occurs when sufficient time is allowed by the rates of environmental fluctuation.

The antibacterial principle of Caesalpina sappan

Using a bioassay-directed purification scheme, the active antibacterial principle from Caesalpina sappan was isolated and identified to be brasilin. This compound showed potent activity against antibiotic-resistant bacteria, notably methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE), multi-drug resistant Burkholderia cepacia as well as a number of other bacteria. The minimal inhibitory concentrations ranged from 4 to 32 microg/mL. The results from time-kill studies showed that brasilin is bactericidal against MRSA. The addition of brasilin to growing MRSA cells resulted in a rapid inhibition of incorporation of [(3)H] thymidine or [(3)H] serine into DNA and proteins, respectively. Exposure of MRSA to a sub-MIC level of brasilin for ten consecutive subcultures did not induce resistance to the compound. The Trypan blue dye exclusion test showed that brasilin lacked cytotoxicity against Vero cells. In conclusion, brasilin is an antibacterial principle from C. sappan and it has the potential to be developed into an antibiotic.

Mechanisms of resistance among respiratory tract pathogens

Antimicrobial resistance among respiratory tract pathogens represents a significant health care threat. Identifying the antimicrobial agents that remain effective in the presence of resistance, and knowing why, requires a thorough understanding of the mechanisms of action of the various agents as well as the mechanisms of resistance demonstrated among respiratory tract pathogens. The primary goal of antimicrobial therapy is to eradicate the pathogen, via killing or inhibiting bacteria, from the site of infection; the defenses of the body are required for killing any remaining bacteria. Targeting a cellular process or function specific to bacteria and not to the host limits the toxicity to patients. Currently, there are four general cellular targets to which antimicrobials are targeted: cell wall formation and maintenance, protein synthesis, DNA replication, and folic acid metabolism. Resistance mechanisms among respiratory tract pathogens have been demonstrated for all four targets. In general, the mechanisms of resistance used by these pathogens fall into one of three categories: enzymatic inactivation of the antimicrobial, prevention of intracellular accumulation, and modification of the target site to which agents bind to exert an antimicrobial effect. Resistance to some agents can be overcome by modifying the dosage regimens (e.g., using high-dose therapy) or inhibiting the resistance mechanism (e.g., b-lactamase inhibitors), whereas other mechanisms of resistance can only be overcome by using an agent from a different class. Understanding the mechanisms of action of the various agents and the mechanisms of resistance used by respiratory tract pathogens can help clinicians identify the agents that will increase the likelihood of achieving optimal outcomes.