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Monitoring the Spread of Antibiotic Resistance Using Computational Methods

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  • Monitoring the Spread of Antibiotic Resistance Using Computational Methods

    Antimicrobial resistance is a global public health threat that results in at least 1.27 million deaths every year1. Newly published research in Antibiotics focuses on a method that can be used for monitoring the spread of antimicrobial resistance genes in bacterial populations. The team of researchers conducting the study developed computational methods that utilized publicly available bacterial sequence data like those uploaded in the NCBI GenBank database.

    “Our idea is that this could be used as a monitoring system,” said Ivan Erill, professor at UMBC and the study’s corresponding author. “It’s great for studies trying to find insight into what’s happening in bacterial genomes.”

    Erill, along with Miquel Sánchez-Osuna and Jordi Barbé from Universitat Autònoma de Barcelona, wrote code to analyze sequence data from all known bacterial plasmids that can produce results in roughly an hour. By using this computational method, the researchers understood they could provide analysis faster and at a lower cost than if they had coordinated a worldwide search with different clinicians. During their analysis, they discovered that certain resistance genes are spreading more than others and developed insights into the origin of these genes.

    “There’s going to be more and more data that you can mine this way,” explained Erill. “I love it because it’s simple; it’s fast, and you can deploy it in a flash.” He also mentioned how sequencing data for this type of publicly available genetic information tends to double roughly every two years, strengthening this type of work.

    Detection Strategy
    The design of their method relies on understanding the ratio of DNA bases in different bacteria. The distribution of bases varies across species; while some bases are roughly even for AT and GC pairs, many other species have much higher or lower percentages of GC pairs. Erill and his fellow scientists exploited this base variability in previous work to study resistance to sulfonamides, another type of antimicrobial agent.

    Resistance genes are commonly spread across species through the transfer of plasmids, which typically maintain the same percentage of GC content as their original host. When the percent of GC content in a resistance gene and the bacterium’s genome doesn’t match, this shows a resistance gene that was acquired from another species. Detecting these differences in the GC content is the focal point of this technique and is much faster than traditional methods of tracking the spread of resistance genes.

    Over time a resistance gene will start to match the GC content of its current bacterial host, but this process can take upwards of millions of years to reflect those changes. “For what we’re looking at, which is gene movement in the last 60 to 100 years,” said Erill, “it’s basically a snapshot.”

    The results of the investigation confirmed the idea that resistance genes are more likely to be passed on if they are found on a conjugative plasmid. This type of plasmid is easily transferred across different types of bacteria. In addition, the researchers discovered that the resistance genes responsible for targeting very specific antibiotics appear to spread the most. Since the evolution of these genes often requires large numbers of mutations, it is unlikely that the genes developed naturally. However, they tend to spread rapidly when present in a bacterial population during the introduction of a matching antibiotic.

    “As soon as there is selective pressure from that antibiotic, there is selective pressure to move this thing around, because it is a bacterium’s silver bullet against that antibiotic,” said Erill. Conversely, more broad resistance, which typically needs minimal mutations in present genes, is often less likely to spread so quickly. “There isn’t a lot of selective pressure to pass it along because by the time it comes, the bacterium has likely already discovered it,” he explained.

    The results also showed that resistance genes to antibiotics common in livestock and outside hospital use were likely to spread throughout bacteria across the world, while resistance genes to limited-use antibiotics rarely spread. “That tells you that if you use things cautiously, then there is not so much selective pressure,” added Erill.

    Another important discovery from this work showed that a majority of the resistance genes were from a single source before spreading instead of many independent (convergent) evolution events. Erill believed that “Resistance is in the environment,” and said that it requires a vehicle to become part of the mainstream.

    Furthermore, Erill contends that keeping antibiotic use restricted to hospitals will reduce the spread of resistance because “[we] would presume that you have naturally resistant bacteria living in the hospital already, ready to pass on their genes.” And despite having infectious bacteria in hospitals, “most of the microbial diversity is in the soil and the water,” he said. Therefore, resistance won’t be spread if antibiotics don’t come in contact with the cells containing resistance genes.

    Erill believes this study is “a methods paper more than a results paper.” But he also said, “we believe it’s an important contribution.” This method allows other researchers to monitor the spread of resistance over time and may encourage others to limit the use of antibiotics outside of hospitals.

    Finally, Erill hopes that other groups utilize this technique for their investigations, and said, “You can use it with a very fine comb to poke at whatever you are interested in.”

    References
    1. Centers for Disease Control and Prevention, National Center for Emerging and Zoonotic Infectious Diseases (NCEZID), Division of Healthcare Quality Promotion (DHQP)

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