Presentation on theme: "Is there another (unifying) layer of complexity? Ongoing research suggests that while antibacterials target various biochemical processes, they might all."— Presentation transcript:
Is there another (unifying) layer of complexity? Ongoing research suggests that while antibacterials target various biochemical processes, they might all also stimulate a bacterial suicide process that amplifies the effect. Reactive peroxides (hydroxyl radicals) accumulate upon introduction of the antibacterial, which lead to the breakdown of nearby macromolecules. Treatment of E. coli with molecules that block formation of hydroxyl radicals almost completely protects it from, for example, quinolones. In contrast, when protective enzymes that protect against hydroxyl radicals are missing, antibiotics become even more lethal. Thus, the idea is emerging that lethal signals caused by the antibiotic trigger a cascade of hydroxyl radicals that are responsible for much of the cell death. Moreover, the protective enzymes are a promising (yet untapped) new drug target.
It all started here… Cell 130, , 2007
Three major conclusions ABSTRACT: Antibiotic mode-of-action classification is based upon drug-target interaction and whether the resultant inhibition of cellular function is lethal to bacteria. Here we show that the three major classes of bactericidal antibiotics, regardless of drug-target interaction, stimulate the production of highly deleterious hydroxyl radicals in Gram-negative and Gram-positive bacteria, which ultimately contribute to cell death. We also show, in contrast, that bacteriostatic drugs do not produce hydroxyl radicals. We demonstrate that the mechanism of hydroxyl radical formation induced by bactericidal antibiotics is the end product of an oxidative damage cellular death pathway involving the tricarboxylic acid cycle, a transient depletion of NADH, destabilization of iron-sulfur clusters, and stimulation of the Fenton reaction. Our results suggest that all three major classes of bactericidal drugs can be potentiated by targeting bacterial systems that remediate hydroxyl radical damage, including proteins involved in triggering the DNA damage response, e.g., RecA.
Why does drug development cost so much? The clinical phase involves three or four steps: Phase I trials, usually in healthy volunteers, determine safety and dosing. Phase II trials are used to get an initial reading of efficacy and further explore safety in small numbers of sick patients. Phase III trials are large, pivotal trials to determine safety and efficacy in sufficiently large numbers of patients. (Phase 4): These are post-approval trials that are sometimes a condition attached by the FDA, also called post-market surveillance studies. Success rates: Candidates for a new drug to treat a disease might theoretically include 10 4 chemical compounds. On average about 250 of these will show sufficient promise for further evaluation using laboratory tests, mice and other test animals. A study conducted by the Tufts Center for the Study of Drug Development covering the 1980s and 1990s found that only 21.5 percent of drugs that start phase I trials are eventually approved for marketing.
Drug recalls Most drugs that have been withdrawn from the market were done so due to risks to the patients. Usually this has been prompted by unexpected adverse effects that were not detected during Phase III clinical trials and were only apparent from postmarketing surveillance data from the wider patient community. The drug combination fenfluramine/phentermine, usually called fen- phen, was an anti-obesity treatment that utilized two anorectics. Fenfluramine was marketed by American Home Products (later known as Wyeth) as Pondimin, but was shown to cause potentially fatal pulmonary hypertension and heart valve problems, which eventually led to its withdrawal and legal damages of over $13 billion. Fen-phen was pulled in 1997.
Drug recalls Vioxx is a nonsteroidal anti-inflammatory drug that has now been withdrawn over safety concerns. It had gained widespread acceptance among physicians treating patients with arthritis and other conditions causing chronic or acute pain. Worldwide, over 80 million people were prescribed Vioxx at some time. On September 30, 2004, Merck withdrew Vioxx from the market because of concerns about increased risk of heart attack and stroke associated with long-term, high-dosage use. Merck withdrew the drug after disclosures that it withheld information about Vioxx’s risks from doctors and patients for over five years, resulting in between 88,000 and 140,000 cases of serious heart disease. It was one of the most widely used drugs ever to be withdrawn from the market. In the year before withdrawal, Merck had sales revenue of US$2.5 billion.
Susceptibility testing guides antibiotic choice
Demographics also guide antibiotic choice Prevalence of drug resistance within MRSA patients in Chicago
Pharmacokinetics Minimum inhibitory concentration Minimum toxic concentration MIC
Serum protein binding A drug's efficiency may be affected by the degree to which it binds to the proteins within blood plasma. The less bound a drug is, the more efficiently it can traverse cell membranes or diffuse. Common blood proteins that drugs bind to are human serum albumin, lipoprotein, glycoprotein, and globulins. Notably, it is the unbound fraction which exhibits pharmacologic effects. It is also the fraction that may be metabolized and/or excreted. For example, the "fraction bound" of the anticoagulant warfarin is 97%. This means that of the amount of warfarin in the blood, 97% is bound to plasma proteins. The remaining 3% (the fraction unbound) is the fraction that is actually active and may be excreted. Protein binding can influence the drug's biological half-life in the body. The bound portion may act as a reservoir or depot from which the drug is slowly released as the unbound form. Since the unbound form is being metabolized and/or excreted from the body, the bound fraction will be released in order to maintain a bound/unbound equilibrium. Albumin
Pharmacokinetics and pharmacodynamics
Dosing MIC MTD
Population variance 99 th percentile
Dosing and safety considerations must reflect population variance
Drug metabolism The enzyme cytochrome p450 finds unusual molecules and add oxygen atoms to them. In most cases, this has the effect of making the molecule more soluble in water, and thus, easier to flush out of the body. The added oxygen also provides a ready handle for other detoxifying enzymes to take hold and further modify, and destroy, these toxic molecules. This task of adding oxygen is chemically tricky, and cytochrome p450 enzymes use a powerful molecular tool to perform the reaction: an iron atom in a heme group (similar to the heme in myoglobin and hemoglobin that binds oxygen). Cytochrome p450 is shown here bound to the antibiotic erythromycin (blue). Note however that the enzyme acts on many different types of drugs and other organic small molecules. In fact, it is believed that cytochrome p450’s account for 75% of the total number of metabolic reactions.
Chapter 5: Emergence of resistance
Resistance happens Resistance is inevitable. But we clearly have some control on the timeline of when it occurs.
Resistance can happen on an individual basis JH Diagnosed with a S. aureus infection that was resistant to erythomycin, clindamycin, rifampicin and the fluoroquinolones. Judged susceptible to vancoymcin and the -lactam oxacillin (even though 0.01% of the bacteria was resistant). JH was treated with both. His symptoms persisted and 2 months later he was tested again for resistance. MIC oxa = 0.75 g/ml 25 g/ml (resistant) MIC van = 1 g/ml 4 g/ml (intermediate) He was tested again twice over the course of 3 weeks MIC van = 1 g/ml 4 g/ml 6 g/ml 8 g/ml One week later JH died.
The molecular basis of mutation The error in adding nucleotides to a growing nucleic acid chain by DNA polymerase is about 1/10 5 (proof reading and error fixing mechanisms reduce the effective mutation rate to 1/10 7 to 1/10 9 in bacteria). Most mutation are deleterious, but a few are beneficial.
The DNA repair machinery is extensive DNA Ligase Base excision repair enzyme Scanning and fixing
Sequential vs. a single leap Usually based on independent mutations to multiple genes.
The mutant selection window hypothesis The mutant selection window hypothesis postulates that an antibiotic concentration range exists in which selective amplification of single-step, drug-resistant mutants occurs. This hypothesis suggests a dosing strategy that is keyed to the upper boundary of the selection window: the mutant prevention concentration (MPC). Correlations exist between the mutant prevention concentration--a static parameter that is measured with agar plates--and fluctuating drug concentrations that restrict mutant amplification. The selection window increases when drug resistance is acquired stepwise, making the suppression of each successive mutant increasingly more difficult. MPC is defined as the MIC value for the single mutant that is least susceptible.
The mutant selection window hypothesis
Stress induced mutation rate increases Recent research has shown that the SOS pathway may be essential in the acquisition of bacterial mutations which lead to resistance to some antibiotic drugs. The increased rate of mutation during the SOS response is caused by three low-fidelity DNA polymerases: Pol II, Pol IV and Pol V. Researchers are now targeting these proteins with the aim of creating drugs that prevent SOS repair. By doing so, the time needed for pathogenic bacteria to evolve antibiotic resistance could be extended, and thus improve the long term viability of some antibiotic drugs.
Viral replication is low fidelity mutations! Viruses makes lots of new viruses, and they tend to lack proofreading functionalities. As such, they are error prone, creating large viral genetic diversity. In fact, so many errors occur that viral infections often have many sub-types. Drug resistance in HIV, for example, occurs frequently due to this, which necessitating multi-drug cocktails to combat it.
Resistance mutations do have a cost
The likelihood of fixing the mutation depends upon both the cost and the gain Schulz zur Wiesch P et al. Antimicrob. Agents Chemother.2010;54:
High-level FQ resistance in salmonellae have prohibitive fitness costs
Nature Reviews | Microbiology (2010). 8:265 Assays There are several assays to estimate fitness of strains. However it is debatable as to which assay best simulates in vivo conditions. In competition experiments, it is usually assumed that the competing strains do not affect each other and that they compete only by their intrinsic growth rate and efficiency in utilizing available nutrients. Thus we have chosen growth rate as a measure of relative fitness for competing strains in vitro. PLOS ONE, 2012, 7(3): e33507.
Nature Reviews | Microbiology (2010). 8:265 Compensating mutations in orange reestablish fitness. Two alternate paths to resistance, one that affects fitness and one that does not. Compensatory mutations and alternate paths Streptomycin in S. entericaFluoroquinolone in E. coli More common scenario Less common scenario
Nature Reviews | Microbiology (2010). 8:265 The effects of resistance mutations on fitness
Nature Reviews | Microbiology (2010). 8:265 The effect of compensatory mutations
Nature Reviews | Microbiology (2010). 8:265 5 Lessons 1.Epistasis can affect fitness costs. (Epistasis is when the effect of one gene depends on the presence of one or more 'modifier genes'.) AmpC/Amp is a classic example of this. 2.Environmental conditions affect fitness costs. There can be big differences between lab and in vivo results. 3.Some mutations are cost free. 4.The cost of the mutation can be regulated by altering the resistance mechanism. 5.Cost competition and resistance can be linked. That is, it has been demonstrated that mutations can simultaneously confer advantages to both.
Can we reverse evolution? Percentage (%) Antibiotic Resistance ? Fitness is typically determined by simple bacterial counts. In the lab we can routinely generate highly resistant populations, but this usually comes with a high fitness cost, and so rapidly reverts to an antibiotic sensitive form when we remove the antibiotic. However, in strains associated with clinical epidemics, we see resistant strains with little or no fitness cost. In some cases, fitness gains might actually occur, even in the absence of the antibiotic. This was found to be the case with with a mutation conferring resistance to ciprofloxacin (a fluoroquinolone) in the pathogen C. jejuni Both = without antibiotics
Antibiotic cycling “These findings suggest that the fitness costs of resistance will allow susceptible bacteria to outcompete resistant bacteria if the selective pressure from antibiotics is reduced. Unfortunately, the available data suggest that the rate of reversibility will be slow at the community level.” Nature Reviews-Microbiology, 2010, 8:260.
Nature Reviews | Microbiology (2010). 8:265 Main conclusions 1.The main finding is that reversibility in clinical settings is expected to be slow or non- existent. The main reasons for this are that the intrinsic dynamics of reversal are expected to be slow (even if a fitness cost is present), compensatory evolution and cost-free resistances can reduce the cost and thereby reduce the driving force for reversibility, and co-selection between the resistance mechanism and other selected markers can slow down any potential reversibility that may be driven by fitness costs. 2.A second key conclusion is that we could use this knowledge to reduce the likelihood of resistance development, for example, by choosing antibiotic targets for which the resistance mechanism confers a high fitness cost and for which the rate and extent of compensation is low. Similarly, it could be possible to exploit the detailed knowledge of the physiological basis of fitness costs for the choice and design of novel therapies that target the physiological ‘Achilles heel’ that is associated with a particular resistance mechanism. 3.Finally, a better understanding of fitness costs and compensatory evolution and of their impact on the emergence and spread of resistant bacteria should allow us to make better quantitative predictions about the rate and trajectory of the evolution of resistance towards new and old drugs and, by inference, should also give us possibilities to prevent this evolution.
A new reason to hope?
Molecular mechanisms of resistance 1.Changes in the cell wall or membrane. 2.Efflux pumps (see pic). Can be plasmid encoded. 3.Enzymes that destroy the antibiotic (i.e., -lactamase). Can be plasmid encoded. 4.Alteration to the antibiotic receptor (see pic). 2. Efflux pumps 4. Molecular receptors 3. -lactamase