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1.  Antibiotic Restriction Might Facilitate the Emergence of Multi-drug Resistance 
PLoS Computational Biology  2015;11(6):e1004340.
High antibiotic resistance frequencies have become a major public health issue. The decrease in new antibiotics' production, combined with increasing frequencies of multi-drug resistant (MDR) bacteria, cause substantial limitations in treatment options for some bacterial infections. To diminish overall resistance, and especially the occurrence of bacteria that are resistant to all antibiotics, certain drugs are deliberately scarcely used—mainly when other options are exhausted. We use a mathematical model to explore the efficiency of such antibiotic restrictions. We assume two commonly used drugs and one restricted drug. The model is examined for the mixing strategy of antibiotic prescription, in which one of the drugs is randomly assigned to each incoming patient. Data obtained from Rabin medical center, Israel, is used to estimate realistic single and double antibiotic resistance frequencies in incoming patients. We find that broad usage of the hitherto restricted drug can reduce the number of incorrectly treated patients, and reduce the spread of bacteria resistant to both common antibiotics. Such double resistant infections are often eventually treated with the restricted drug, and therefore are prone to become resistant to all three antibiotics. Thus, counterintuitively, a broader usage of a formerly restricted drug can sometimes lead to a decrease in the emergence of bacteria resistant to all drugs. We recommend re-examining restriction of specific drugs, when multiple resistance to the relevant alternative drugs already exists.
Author Summary
Methods for minimizing antibiotic resistance are becoming more important as antibiotic resistance frequencies are rising, coupled with low discovery rates of new antibiotics. In this work we examined the practice of restricting specific drugs to be used only as 'last resort'. The goal of such restrictions is to maintain low resistance levels to certain drugs, and prevent the creation of bacteria resistant to all available treatment options. We used a mathematical model to study the impact of such restrictions, when some resistance to the unrestricted drugs is already present. We estimated the resistance frequencies of common bacteria from hospital data. We find that restricting drugs leads to increased rates of incorrect treatment, and might simultaneously lead to increased emergence of multidrug resistant bacteria. We conclude that restricting specific antibiotics should be done with caution. In some cases lifting restrictions might even delay MDR emergence.
PMCID: PMC4481510  PMID: 26110266
2.  Food Selectivity and Diet Switch Can Explain the Slow Feeding of Herbivorous Coral-Reef Fishes during the Morning 
PLoS ONE  2013;8(12):e82391.
Most herbivorous coral-reef fishes feed slower in the morning than in the afternoon. Given the typical scarcity of algae in coral reefs, this behavior seems maladaptive. Here we suggest that the fishes' slow feeding during the morning is an outcome of highly selective feeding on scarcely found green algae. The rarity of the food requires longer search time and extended swimming tracks, resulting in lower bite rates. According to our findings by noon the fish seem to stop their search and switch to indiscriminative consumption of benthic algae, resulting in apparent higher feeding rates. The abundance of the rare preferable algae gradually declines from morning to noon and seems to reach its lowest levels around the switch time. Using in situ experiments we found that the feeding pattern is flexible, with the fish exhibiting fast feeding rates when presented with ample supply of preferable algae, regardless of the time of day. Analyses of the fish's esophagus content corroborated our conclusion that their feeding was highly selective in the morning and non-selective in the afternoon. Modeling of the fishes' behavior predicted that the fish should perform a diel diet shift when the preferred food is relatively rare, a situation common in most coral reefs found in a warm, oligotrophic ocean.
PMCID: PMC3866113  PMID: 24358178
3.  Implications of stress-induced genetic variation for minimizing multidrug resistance in bacteria 
BMC Medicine  2012;10:89.
Antibiotic resistance in bacterial infections is a growing threat to public health. Recent evidence shows that when exposed to stressful conditions, some bacteria perform higher rates of horizontal gene transfer and mutation, and thus acquire antibiotic resistance more rapidly.
We incorporate this new notion into a mathematical model for the emergence of antibiotic multi-resistance in a hospital setting.
We show that when stress has a considerable effect on genetic variation, the emergence of antibiotic resistance is dramatically affected. A strategy in which patients receive a combination of antibiotics (combining) is expected to facilitate the emergence of multi-resistant bacteria when genetic variation is stress-induced. The preference between a strategy in which one of two effective drugs is assigned randomly to each patient (mixing), and a strategy where only one drug is administered for a specific period of time (cycling) is determined by the resistance acquisition mechanisms. We discuss several features of the mechanisms by which stress affects variation and predict the conditions for success of different antibiotic treatment strategies.
These findings should encourage research on the mechanisms of stress-induced genetic variation and establish the importance of incorporating data about these mechanisms when considering antibiotic treatment strategies.
PMCID: PMC3482572  PMID: 22889082
stress induced mutagenesis; HGT; antibiotic resistance; evolution; mathematical model
4.  Home and away- the evolutionary dynamics of homing endonucleases 
Homing endonucleases (HEases) are a large and diverse group of site-specific DNAases. They reside within self-splicing introns and inteins, and promote their horizontal dissemination. In recent years, HEases have been the focus of extensive research due to their promising potential use in gene targeting procedures for the treatment of genetic diseases and for the genetic engineering of crop, animal models and cell lines.
Using mathematical analysis and computational modeling, we present here a novel account for the evolution and population dynamics of HEase genes (HEGs). We describe HEGs as paradoxical selfish elements whose long-term persistence in a single population relies on low transmission rates and a positive correlation between transmission efficiency and toxicity.
Plausible conditions allow HEGs to sustain at high frequency through long evolutionary periods, with the endonuclease frequency being either at equilibrium or periodically oscillating. The predictions of our model may prove important not only for evolutionary theory but also for gene therapy and bio-engineering applications of HEases.
PMCID: PMC3229294  PMID: 22054298

Results 1-4 (4)