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Using Transduction to reverse Antibiotic Resistance?

Using Transduction to reverse Antibiotic Resistance?


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Is it possible to use reverse transduction to reverse antibiotic resistance. Since antibitiotic resistance is causee by transduction of the F factor, is it possible to induce a F+ non antibiotic resistant bacteria into a region of F- resistant bacteria?


When Alexander Fleming discovered penicillin in 1928, it was one of the world’s first true antibiotics to ever be successful in eliminating infectious disease. Since then, antibiotics have been essential to preventing avoidable deaths.

But a troubling reality faces us all. Throughout all of Earth’s evolutionary history, multicellular organisms have continually changed and adapted. But unicellular bacteria evolve so quickly, that a majority are now resistant to a wide array of antibiotics. The problem of antibiotic resistance is so serious, that the United Nations placed it at crisis level along with HIV.

As a response, scientists have taken on the challenge to solving this global pandemic. One group of scientists from Oregon State University (OSU) recently discovered a weapon in fighting antibiotic-resistant bacteria. Their findings were recently published in the Journal of Antimicrobial Chemotherapy.

These scientists found their answer inside a peptide-conjugated phosphorodiamidate morpholino oligomer (PPMO) molecule. They believe that this molecule could combat an enzyme produced by bacteria called New Delhi metallo-beta-lactamase (NDM-1) which is responsible for coding resistance along with several other genes.

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Since the genes are shared across many different types of bacteria, only one PPMO molecule would be needed to fight the resistance. It would make contact with the antibiotic and restore its ability to fight bacteria that express NDM-1. In the study at OSU, the scientists used an antibiotic called meropenem, which is an ultra-broad-spectrum drug of the penicillin-type carbapenem class. Meropenem was effective in treating mice that were infected with E. Coli that was found to be NDM-1 positive. Testing for humans is slated to begin in about three years.


Putting bacterial antibiotic resistance into reverse

The use of antibiotics to treat bacterial infections causes a continual and vicious cycle in which antibiotic treatment leads to the emergence and spread of resistant strains, forcing the use of additional drugs leading to further multi-drug resistance.

But what if it doesn't have to be that way?

In a presentation at the American Society for Biochemistry and Molecular Biology's annual meeting, titled "Driving backwards the evolution of antibiotic resistance," Harvard researcher Roy Kishony discussed his recent work showing that some drug combinations can stop or even reverse the normal trend, favoring bacteria that do not develop resistance.

"Normally, when clinicians administer a multi-drug regimen, they do so because the drugs act synergistically and speed up bacterial killing," Kishony explains. However, Kishony's laboratory has focused on the opposite phenomenon: antibiotic interactions that have a suppressive effect, namely when the combined inhibitory effect of using the two drugs together is weaker than that of one of the drugs alone.

Kishony and his team identified the suppressive interaction in E. coli, discovering that a combination of tetracycline -- which prevents bacteria from making proteins -- and ciprofloxacin -- which prevents them from copying their DNA -- was not as good as slowing down bacterial growth as one of the antibiotics (ciprofloxacin) by itself.

Kishony notes that this suppressive interaction can halt bacterial evolution, because any bacteria that develop a resistance to tetracycline will lose its suppressive effect against ciprofloxacin and die off therefore, in a population the bacteria that remain non-resistant become the dominant strain.

While such a weakened antibiotic combination is not great from a clinical standpoint, the Kishony lab is using this discovery to set up a drug screening system that could identify novel drug combinations that could hinder the development of resistance but still act highly effectively. "Typical drug searches look for absolute killing effects, and choose the strongest candidates," he says. "Our approach is going to ask how these drugs affect the competition between resistant versus sensitive bacterial strains."

To develop such a screen, Kishony and his group first had to figure how this unusual interaction works.

"Fast growing bacteria like E. coli are optimized to balance their protein and DNA activity to grow and divide as quickly as the surrounding environment allows," Kishony explains. "However, when we exposed E. coli to the ciprofloxacin, we found that their optimization disappeared."

"We expected that since the bacteria would have more difficulty copying DNA, they would slow down their protein synthesis, too," Kishony continues. "But they didn't they kept churning out proteins, which only added to their stress." However, once they added the tetracycline and protein synthesis was also reduced in the E. coli, they actually grew better than before. They then confirmed the idea that production of ribosomes -- the cell components that make proteins -- is too high under DNA stress by engineering E. coli strains that have fewer ribosomes than regular bacteria. While these mutants grew a more slowly in normal conditions, they grew faster under ciprofloxacin inhibition of DNA synthesis.

Kishony notes that their preliminary work on the development of a screen for drugs that put resistance in a disadvantage looks promising, and hopes that it would lead to the identification of novel drugs that select against resistance.


Special Issue Editors

We are 30 years away from the dire prediction that antimicrobial resistance (AMR) will claim 10 million lives a year and cost the world 100 trillion USD. Over the last decade, industry and academia have collaborated and mobilised forces in preparation to avert this public health crisis however, these efforts are yet to have an effect on the global AMR trends. Currently, infections caused by &lsquosuperbugs&rsquo claim the lives of an estimated 700,000 worldwide. A large majority of these infections in caused by strains of Mycobacterium tuberculosis and the ESKAPE group of infectious bacterial pathogens comprising of Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and the Enterobacter species. Transmission of resistance and increasing resistance profiles of these organisms make their control and treatment extremely challenging in the current environment of limited drug options that are still effective against them.

With calls urging our attention towards tackling the post-antibiotic era, research and development has to stay ahead and at times pre-empt the evolution of these pathogens. It is time to diversify our approach by attacking the instrinsic mechanisms of drug resistance such as efflux pumps, formation of biofilms and the activity of drug modifying enzymes to name a few. Therefore, instead of the conventional route of targeting novel pathways wherein resistance is quick to develop, these approaches will serve to reverse resistance and potentiate currently available therapy.

In this Special Issue, we aim to highlight the importance of interdisciplinary approaches in accelerating new drug development and repurposing existing drugs.

We invite authors to send in their manuscripts in the areas of interest as highlighted below:

  • Importance of rational drug design vis-a-vis whole-cell evaluation of chemical libraries
  • Reversing resistance by affecting intrinsic mechanisms of resistance
    • &beta-lactamase inhibition
    • Efflux pump inhibition
    • Disruption of biofilm
    • Membrane permeabilisers
    • Development of drug carriers that increase uptake of antibiotics
    • Phage therapy
    • Therapeutic vaccine development

    Manuscripts that further our understanding of antimicrobial resistance, means to reverse them, and novel approaches not in this list specifically, yet still falling within the scope of the Special Issue are also welcome.

    Prof. Sanjib Bhakta
    Dr. Arundhati Maitra
    Guest Editors

    Manuscript Submission Information

    Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

    Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Antibiotics is an international peer-reviewed open access monthly journal published by MDPI.

    Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


    Scientists combine evolutionary biology and mathematics to reverse antibiotic resistance

    For more than a decade, biologist Mariam Barlow has been working on the theory that administering antibiotics on a rotating basis could be a solution to antibiotic resistance. After years of research, Barlow had lots of data, but she needed a more precise way to make sense of it all — something that was so specific it could easily be used to treat patients. So, she joined forces with a team of mathematicians. And the amazing results could help solve an enormous, worldwide problem.

    In a nutshell, the team of biologists and mathematicians developed a software program that generates a road map to reverse the evolution of antibiotic resistance in bacteria. In a study published earlier this month in the journal PLOS ONE, they unveiled a mathematical model that pinpoints optimal antibiotic cycling patterns with the highest probability of turning back the evolutionary clock of antibiotic resistance. Barlow, an evolutionary biologist and associate professor at the University of California-Merced School of Natural Sciences, told me that she and fellow researchers found cycles of antibiotics that could reverse resistance and drive bacteria back to a state observed in the 1960s — a state the researchers call the “wild type state.” So it’s not surprising that the software that makes it all possible was aptly named “Time Machine.”

    “It makes sense that we would look for answers (to antibiotic resistance) in evolutionary biology,” Barlow told me. “Bacteria are so good at evolving — and they’ll probably find new ways we don’t even know about yet — but based on what we’ve seen, this is something we can deal with. Antibiotic resistance is something we can handle.”

    The research comes at a time of widespread concern that without a coordinated, well-funded response to growing antibiotic resistance, medicine could lose some of its most effective, life-saving tools. Every year, according to the Centers for Disease Control and Prevention, about 2 million people become infected with antibiotic-resistant bacteria and at least 23,000 people die as a result of such infection. For example, last year, CDC described the development of antibiotic-resistant gonorrhea as an “urgent public health threat,” warning that we may run out of options for treating the sexually transmitted disease. Also at the federal level, the White House recently released its first “National Action Plan for Combating Antibiotic-Resistant Bacteria” and in his fiscal year 2016 budget proposal, President Obama recommended doubling federal funds to find solutions to antibiotic resistance to $1.2 billion (of course, that recommendation has to get through Congress). Everyone agrees that antibiotic resistance is a huge problem with fatal consequences.

    Thankfully, Barlow and her colleagues may have found an answer that not only tackles resistance, but helps preserve the effectiveness of existing antibiotics. And here’s how they did it. Researchers created bacteria in the lab, exposed it to 15 different antibiotics and measured their growth rates. Using those measurements, the team of biologists and mathematicians computed the probability of mutations required to return the bacteria back to its harmless state. They tested up to six antibiotics in rotation at a time and computed thousands of measurements to find the most likely cycling strategies for reversing the development of antibiotic resistance.

    Researchers eventually concluded that the Time Machine software and its mathematical foundations proved to be a promising way to quickly and more precisely generate an optimal antibiotic cycling plan most likely to reverse resistance. Simply put, the software is a matchmaker — it computes which antibiotic goes with which mutation at which point in time to best manage the evolution of resistance and ultimately, cure the patient.

    And Barlow reminded me that this type of precision is not necessarily the norm in medicine. Even though incorrect antibiotic prescribing is a main driver of antibiotic resistance, the current dearth in rapid antibiotic-resistant diagnostics means physicians are often left with little choice but to start treating an ill patient before seeing any lab results. However, antibiotic cycling can help guide that process to make a better, more ordered treatment plan — “it’s an approach that can be accessible to any hospital and can help empiric therapy be more reliable,” Barlow said.

    In the PLOS ONE study, authors Barlow, Kristina Crona, Portia Mira, Devin Greene, Juan Meza and Bernd Sturmfels write:

    Efforts to remove resistance genes from clinical environments by either discontinuing or reducing the use of specific antibiotics for some period of time, either through general reduction of antibiotic consumption or periodic rotations of antibiotics (cycling) have not worked in any reliable or reproducible manner indeed it would have been surprising if they had worked.

    Since antibiotic resistance is unavoidable, it only makes sense to accept its inevitability and develop methods for mitigating the consequences. One reasonable approach is to rotate the use of antibiotics. This has been implemented in many ways and there are recent studies to model the optimal duration, mixing versus cycling, and how relaxed antibiotic cycles may be and still function as planned. However, none of those models have focused on developing a method for designing an optimal succession of antibiotics.

    Which is exactly what the Time Machine software attempts to do. As the study mentioned, antibiotic cycling has been studied before, but it was the marriage of evolutionary biology and mathematics that made the difference, Barlow said.

    “We took the theory of adaptive landscapes and used it as a foundation for organizing our data and with that style of organized data, a team of mathematicians was able to develop a model,” Barlow said. “It’s just one of those wonderful things that just falls into place.”

    Study co-author Kristina Crona, an assistant professor in the Department of Mathematics and Statistics at American University, noted that the antibiotic cycling problem perfectly illustrates the role of mathematics in biology. Unfortunately, she told me, the two fields don’t have a strong tradition of working together.

    “How can we use antibiotics as well as possible? What sequence of drugs would be best? How do we find the best treatment plan?” Crona asked. “These are all very quantitative problems. If we can move medicine and biology closer to mathematics, I think it would produce all kinds of advantages.”

    Of course, the ultimate goal is to create a cycling protocol that physicians and health care providers can easily use in a clinical setting, Barlow said. To begin that translation process, Barlow and colleagues are collaborating with a hospital in Merced to collect resistant isolates and analyze the relationship between the development of antibiotic resistance and the antibiotics being prescribed by staff.

    “I’ve gotten so many great responses (to the study), it’s almost overwhelming,” Barlow told me. “This idea that we’ve been working on for so long — to see it progress to a level that people can understand and get excited about is so rewarding.”

    To read a full copy of the study, visit PLOS ONE. To learn more about antibiotic resistance, visitKeep Antibiotics Working.

    Kim Krisberg is a freelance public health writer living in Austin, Texas, and has been writing about public health for more than a decade.


    TCM Suppresses Antibiotic-Resistant Bacteria

    There is a resourceful of medicinal plants in the global scale, in which 400 species of TCM herbs are included. The application of those TCM herbs on the prevention and treatment of diseases, including infection and cancer, has been practiced for several thousand years. There are increasing evidences that TCM herbs, including monomers of TCM (Table 1) and extracts of TCM (Table 2), exhibit obvious antibacterial ability and enhance the activity of antibiotics (Ma et al., 2010), and some of them diminish antibiotic resistance (Wu et al., 2008). TCM treatment on infection diseases have many advantages, such as abundant resources, moderate price, multi-component, multi-target, and medical synergism. Therefore, TCM treatment may be one of the effective methods to solve the problem of antibiotic resistance.

    Table 1. Active ingredients of TCM herbs.

    Table 2. Antibacterial activity of TCM extracts.

    Inhibition Activity of Monomer of TCM Herbs on Antibiotic-Resistant Bacteria Activity

    The single components of some TCM herbs exert antibacterial activity. Alves et al. demonstrated the antimicrobial activity of the major oil compound (linalool) of Coriandrum sativum against Acinetobacter baumannii (A. baumannii), and evaluated its roles on planktonic cells and biofilms of A. baumannii on different surfaces, as well as its effect on adhesion and QS. Linalool inhibited biofilm formation, dispersed established biofilms of A. baumannii, changed the adhesion of A. baumannii to surfaces and interfered with the QS system (Alves et al., 2016). In addition, the multiple elements of the same TCM herbs display similar antibacterial activity. (E)-anethole, anisyl acetone, anisyl alcohol and anisyl aldehyde, identified from the extracts of Illicium verum, exhibit the synergistic antibacterial activity against 67 clinical antibiotic-resistant isolates, including 27 A. baumannii, 20 Pseudomonas aeruginosa (P. aeruginosa), and 20 MAS, indicating that those three compounds might be the active ingredients of Illicium verum with antibacterial activity (Jyh-Ferng et al., 2010 Table 1).

    For different TCM herbs in the same family, there may be identical antibacterial active ingredients. Sarkisian et al. isolated five secondary metabolites from the same family species Hypericum densiflorum, Hypericum ellipticum, Hypericum prolificum, and Hypericum punctatum, which all inhibited bacterial growth and biofilm production. The five compounds, including 3-geranyl-1-(2-methylpropanoyl) phloroglucinol, 3-geranyl-1-(2-methylbutanoyl) phloroglucinol, 2-geranyloxy-1-(2-methylpropanoyl) phloroglucinol, 2-geranyloxy-1-(2-methylbutanoyl) phloroglucinol, and 2-geranyloxy-4,6-dihydroxybenzophenone, displayed the inhibitory activity against the G- bacteria and biofilm formation at low concentrations (Sarkisian et al., 2012 Table 1).

    Some Chinese herbal ingredients may be used as sensitizers to improve the sensitivity of antibiotic-resistant bacteria to medical antibiotics. Piperine isolated from black pepper was shown to enhance antimicrobial activity of mupirocin against S. aureus strains including MASA through the inhibition of efflux of ethidium bromide (Mirza et al., 2011). In addition, Schmidt et al. (2016) revealed therapeutic potential of glycyrrhizic acid in co-application with gentamicin for defined local bacterial infections caused by vancomycin-resistant Enterococcus strains, indicating that glycyrrhizic acid improve the antimicrobial activity of gentamicin to antibiotic-resistant bacteria (Table 1).

    Inhibition Roles of Extracts of TCM Herbs on Drug-Resistant Bacteria Activity

    Researchers isolate active extracts of antibiotic-resistant bacteria from TCM herbs through applying different solvents, such as essential oil, water extract, and ethanol extract. Coutinho et al. (2010) demonstrated that the ethanol extract of Momordica charantia L. (Cucurbitaceae) displayed the antibiotic activity against Methicillin-resistant Staphylococcus aureus (MRSA) strain, indicating the potentiating effect of the ethanol extract on aminoglycosides. Even though there are different extracts from same TCM hebs, they exert similar activity. The methanol extract, ethanol extracts and butanol extract fractions from Withania somnifera (L) Dunal was found to be effective against the multi-drug resistant (MDR) S. aureus strains (Datta et al., 2011). However, for some of TCM herbs, different extracts of same TCM herbs may exhibit the distinct antimicrobial activity for different antibiotic-resistant bacteria. The ethanol extract of Hypericum perforatum L. exert strong antimicrobial activity against S. mutans, S. sobrinus, Lactobacillus plantarum (L. plantarum), and Enterococcus faecalis (E. faecalis). Its water extracts display strong antibacterial activity against S. sobrinus and L. plantarum and exerted moderate activity against S. mutans and E. faecalis. Both ethyl acetate and n-butanol extracts from Hypericum perforatum L. exhibit antimicrobial activity against L. plantaru (Süntar et al., 2015 Table 2).

    The chemical components of TCM extracts are complicated. Even though some TCM herbs can prevent antibiotic-resistant bacteria, their bacteriostatic concentrations are relatively high, resulting in the decrease of clinical practicability. Therefore, many researchers identified the active components of TCM extracts to promote the application of TCM on antibiotic-resistant bacteria using advanced techniques. Luo et al. (2014) utilize chemical fingerprinting to find that the functional components of Rhizoma coptidis (Coptis chinensis Franch. Huanglian in Chinese) are alkaloids, which display the ability against the drug resistance induced by NorA gene. Ethyl acetate extracts deriving from the leaves of Dracontomelon Dao (Blanco) Merr. & Rolfe exhibit obvious antibacterial activity on ampicillin-resistant E. coli. Furthermore, Xu et al. (2019) revealed that flavonoids and phenolic acids isolated from the ethyl acetate extracts were active ingredients using liquid chromatography–mass spectrometry (Table 2).


    Using Transduction to reverse Antibiotic Resistance? - Biology

    During the holiday season, Kim, Liz and I are taking a short break from blogging. We are posting some of our favorite posts from the past year. Here’s one of them, originally posted on May 27, 2015:

    For more than a decade, biologist Mariam Barlow has been working on the theory that administering antibiotics on a rotating basis could be a solution to antibiotic resistance. After years of research, Barlow had lots of data, but she needed a more precise way to make sense of it all — something that was so specific it could easily be used to treat patients. So, she joined forces with a team of mathematicians. And the amazing results could help solve an enormous, worldwide problem.

    In a nutshell, the team of biologists and mathematicians developed a software program that generates a road map to reverse the evolution of antibiotic resistance in bacteria. In a study published earlier this month in the journal PLOS ONE, they unveiled a mathematical model that pinpoints optimal antibiotic cycling patterns with the highest probability of turning back the evolutionary clock of antibiotic resistance. Barlow, an evolutionary biologist and associate professor at the University of California-Merced School of Natural Sciences, told me that she and fellow researchers found cycles of antibiotics that could reverse resistance and drive bacteria back to a state observed in the 1960s — a state the researchers call the “wild type state.” So it’s not surprising that the software that makes it all possible was aptly named “Time Machine.”

    “It makes sense that we would look for answers (to antibiotic resistance) in evolutionary biology,” Barlow told me. “Bacteria are so good at evolving — and they’ll probably find new ways we don’t even know about yet — but based on what we’ve seen, this is something we can deal with. Antibiotic resistance is something we can handle.”

    The research comes at a time of widespread concern that without a coordinated, well-funded response to growing antibiotic resistance, medicine could lose some of its most effective, life-saving tools. Every year, according to the Centers for Disease Control and Prevention, about 2 million people become infected with antibiotic-resistant bacteria and at least 23,000 people die as a result of such infection. For example, last year, CDC described the development of antibiotic-resistant gonorrhea as an “urgent public health threat,” warning that we may run out of options for treating the sexually transmitted disease. Also at the federal level, the White House recently released its first “National Action Plan for Combating Antibiotic-Resistant Bacteria” and in his fiscal year 2016 budget proposal, President Obama recommended doubling federal funds to find solutions to antibiotic resistance to $1.2 billion (of course, that recommendation has to get through Congress). Everyone agrees that antibiotic resistance is a huge problem with fatal consequences.

    Thankfully, Barlow and her colleagues may have found an answer that not only tackles resistance, but helps preserve the effectiveness of existing antibiotics. And here’s how they did it. Researchers created bacteria in the lab, exposed it to 15 different antibiotics and measured their growth rates. Using those measurements, the team of biologists and mathematicians computed the probability of mutations required to return the bacteria back to its harmless state. They tested up to six antibiotics in rotation at a time and computed thousands of measurements to find the most likely cycling strategies for reversing the development of antibiotic resistance.

    Researchers eventually concluded that the Time Machine software and its mathematical foundations proved to be a promising way to quickly and more precisely generate an optimal antibiotic cycling plan most likely to reverse resistance. Simply put, the software is a matchmaker — it computes which antibiotic goes with which mutation at which point in time to best manage the evolution of resistance and ultimately, cure the patient.

    And Barlow reminded me that this type of precision is not necessarily the norm in medicine. Even though incorrect antibiotic prescribing is a main driver of antibiotic resistance, the current dearth in rapid antibiotic-resistant diagnostics means physicians are often left with little choice but to start treating an ill patient before seeing any lab results. However, antibiotic cycling can help guide that process to make a better, more ordered treatment plan — “it’s an approach that can be accessible to any hospital and can help empiric therapy be more reliable,” Barlow said.

    In the PLOS ONE study, authors Barlow, Kristina Crona, Portia Mira, Devin Greene, Juan Meza and Bernd Sturmfels write:

    Efforts to remove resistance genes from clinical environments by either discontinuing or reducing the use of specific antibiotics for some period of time, either through general reduction of antibiotic consumption or periodic rotations of antibiotics (cycling) have not worked in any reliable or reproducible manner indeed it would have been surprising if they had worked.

    Since antibiotic resistance is unavoidable, it only makes sense to accept its inevitability and develop methods for mitigating the consequences. One reasonable approach is to rotate the use of antibiotics. This has been implemented in many ways and there are recent studies to model the optimal duration, mixing versus cycling, and how relaxed antibiotic cycles may be and still function as planned. However, none of those models have focused on developing a method for designing an optimal succession of antibiotics.

    Which is exactly what the Time Machine software attempts to do. As the study mentioned, antibiotic cycling has been studied before, but it was the marriage of evolutionary biology and mathematics that made the difference, Barlow said.

    “We took the theory of adaptive landscapes and used it as a foundation for organizing our data and with that style of organized data, a team of mathematicians was able to develop a model,” Barlow said. “It’s just one of those wonderful things that just falls into place.”

    Study co-author Kristina Crona, an assistant professor in the Department of Mathematics and Statistics at American University, noted that the antibiotic cycling problem perfectly illustrates the role of mathematics in biology. Unfortunately, she told me, the two fields don’t have a strong tradition of working together.

    “How can we use antibiotics as well as possible? What sequence of drugs would be best? How do we find the best treatment plan?” Crona asked. “These are all very quantitative problems. If we can move medicine and biology closer to mathematics, I think it would produce all kinds of advantages.”

    Of course, the ultimate goal is to create a cycling protocol that physicians and health care providers can easily use in a clinical setting, Barlow said. To begin that translation process, Barlow and colleagues are collaborating with a hospital in Merced to collect resistant isolates and analyze the relationship between the development of antibiotic resistance and the antibiotics being prescribed by staff.

    “I’ve gotten so many great responses (to the study), it’s almost overwhelming,” Barlow told me. “This idea that we’ve been working on for so long — to see it progress to a level that people can understand and get excited about is so rewarding.”

    To read a full copy of the study, visit PLOS ONE. To learn more about antibiotic resistance, visitKeep Antibiotics Working.

    Kim Krisberg is a freelance public health writer living in Austin, Texas, and has been writing about public health for more than a decade.


    Down with the (antibiotic) resistance!

    Phages force problem bacteria to expose themselves to antibiotics.

    How do you stop a superbug from fighting an antibiotic? Try giving it another enemy.

    Acinetobacter baumannii is a bacterium fairly commonly found in hospitals that can cause infections in the lungs, blood and urinary tract. This fast-mutating bug easily overcomes antibiotics, so it’s difficult to manage.

    Now, a team from Australia’s Monash University, led by Fernando Gordilla Altamirano, has found a way to reverse antibiotic resistance in A. baumannii by using phages to trick the bacteria into letting down their guard.

    Key research points

    • Antibiotic resistance can be reversed using phages
    • Phages use bacterium A. baumannii’s protective layer as an entry target
    • A. baumannii mutates to defend against phage attack
    • Mutations lead to loss of protective layer and allow antibiotic entry

    Phages are viruses that target bacteria specifically by injecting viral components into the bacterium to kill it. They’re well-established as useful tools for overcoming antibiotic resistance, but it hasn’t always been clear exactly why.

    In a paper published in Nature Microbiology, the authors describe the mechanism by which phages achieve this. The phages attack A. baumannii, forcing it to mutate out of defence, thereby changing its protective layer enough to reverse resistance to the antibiotics.

    A. baumannii produces a capsule, a viscous and sticky outer layer that protects it and stops the entry of antibiotics,” says Gordillo Altamirano.

    The phages target the capsule layer by using it as their entry point. This forces the bacterium to stop making the layer, leaving it naked and exposed to antibiotics.

    “In an effort to escape from the phages, A. baumannii stops producing its capsule, and that’s when we can hit it with the antibiotics it used to resist,” says Gordillo Altamirano.

    This takes advantage of the fast-mutating nature of bacteria and turns A. baumannii’s strength into a weakness.

    “We have a large panel of phages that are able to kill antibiotic-resistant A. baumannii,” says co-author Jeremy Barr. “But this superbug is smart, and in the same way it becomes resistant to antibiotics, it also quickly becomes resistant to our phages.”

    The study focused on two specific phages called ΦFG02 and ΦCO01, which were able to help resensitise at least seven different antibiotics. They used mice models for the research, which provides exciting potential for the future.

    “The phages had excellent effects in experiments using mice, so we’re excited to keep working on this approach,” says Gordillo Altamirano.

    “We’re showing that phages and antibiotics can work great as a team.”

    After all, the enemy of my enemy is my friend.

    Spotlight: Antimicrobial resistance

      (AMR) is a big health concern
  • It occurs when germs mutate to resist medicines and antibiotics
  • This can lead to infections which extend hospital stays
  • Only use antibiotics at the direction of your health care provider
  • Deborah Devis

    Dr Deborah Devis is a science journalist at The Royal Institution of Australia.

    Read science facts, not fiction.

    There’s never been a more important time to explain the facts, cherish evidence-based knowledge and to showcase the latest scientific, technological and engineering breakthroughs. Cosmos is published by The Royal Institution of Australia, a charity dedicated to connecting people with the world of science. Financial contributions, however big or small, help us provide access to trusted science information at a time when the world needs it most. Please support us by making a donation or purchasing a subscription today.

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    Putting bacterial antibiotic resistance into reverse

    The use of antibiotics to treat bacterial infections causes a continual and vicious cycle in which antibiotic treatment leads to the emergence and spread of resistant strains, forcing the use of additional drugs leading to further multi-drug resistance.

    But what if it doesn't have to be that way?

    In a presentation at the American Society for Biochemistry and Molecular Biology's annual meeting, titled "Driving backwards the evolution of antibiotic resistance," Harvard researcher Roy Kishony will discuss his recent work showing that some drug combinations can stop or even reverse the normal trend, favoring bacteria that do not develop resistance. The talk will be in Anaheim Convention Center Room 304D, on Sunday April 25 at 3:30 pm PST.

    "Normally, when clinicians administer a multi-drug regimen, they do so because the drugs act synergistically and speed up bacterial killing," Kishony explains. However, Kishony's laboratory has focused on the opposite phenomenon: antibiotic interactions that have a suppressive effect, namely when the combined inhibitory effect of using the two drugs together is weaker than that of one of the drugs alone.

    Kishony and his team identified the suppressive interaction in E. coli, discovering that a combination of tetracycline - which prevents bacteria from making proteins - and ciprofloxacin - which prevents them from copying their DNA - was not as good as slowing down bacterial growth as one of the antibiotics (ciprofloxacin) by itself.

    Kishony notes that this suppressive interaction can halt bacterial evolution, because any bacteria that develop a resistance to tetracycline will lose its suppressive effect against ciprofloxacin and die off therefore, in a population the bacteria that remain non-resistant become the dominant strain.

    While such a weakened antibiotic combination is not great from a clinical standpoint, the Kishony lab is using this discovery to set up a drug screening system that could identify novel drug combinations that could hinder the development of resistance but still act highly effectively.

    "Typical drug searches look for absolute killing effects, and choose the strongest candidates," he says. "Our approach is going to ask how these drugs affect the competition between resistant versus sensitive bacterial strains."

    To develop such a screen, Kishony and his group first had to figure how this unusual interaction works.

    "Fast growing bacteria like E. coli are optimized to balance their protein and DNA activity to grow and divide as quickly as the surrounding environment allows," Kishony explains. "However, when we exposed E. coli to the ciprofloxacin, we found that their optimization disappeared."

    "We expected that since the bacteria would have more difficulty copying DNA, they would slow down their protein synthesis, too," Kishony continues. "But they didn't they kept churning out proteins, which only added to their stress." However, once they added the tetracycline and protein synthesis was also reduced in the E. coli, they actually grew better than before. They then confirmed the idea that production of ribosomes - the cell components that make proteins - is too high under DNA stress by engineering E. coli strains that have fewer ribosomes than regular bacteria. While these mutants grew a more slowly in normal conditions, they grew faster under ciprofloxacin inhibition of DNA synthesis.

    Kishony notes that their preliminary work on the development of a screen for drugs that put resistance in a disadvantage looks promising, and hopes that it would lead to the identification of novel drugs that select against resistance.


    Transduction, Plasmids, and the Foundation of Biotechnology

    Between 1947 and the mid-1950s, Joshua Lederberg and his collaborators in the Department of Genetics at the University of Wisconsin described a steady stream of important experimental techniques and results which transformed the science of bacterial genetics and helped define the classical era of molecular biology. Their most important discoveries were that of transduction--the transfer of genetic fragments from one cell to another by a virus--and of extra-chromosomal genetic particles called plasmids. Lederberg has invoked the excitement and enduring mysteries of the field at the time: "We were exploring a completely new territory that we only dimly understood. We weren't looking for transduction--we bumped into it. We weren't looking for plasmids--we bumped into them. Every time we turned around we found something unexpected." Yet, these serendipitous discoveries confirmed that bacterial cells differ in fundamental ways from cells in higher organisms, and laid the foundation for genetic engineering and modern biotechnology.

    After Lederberg took up his first faculty position at the University of Wisconsin in 1947, he and the other members of his small laboratory, in particular his wife, microbiologist Esther Zimmer, and graduate students Norton Zinder and Larry Morse, expanded the systematic search for genetic recombination in bacteria by looking for it in Salmonella, a cousin of Escherichia coli which was of considerable medical interest because of its virulence. By the early 1950s they had pioneered methods for using penicillin and streptomycin to select for antibiotic resistance as an additional genetic marker in nutritional mutants. Streptomycin-resistance proved especially important because Lederberg was able to use it to quickly identify strains that were fertile and able to mate, until then a laborious procedure. Another important genetic marker isolated by Lederberg was that for Beta-galactosidase, a group of enzymes that enable bacteria to ferment the sugar lactose. This work presaged Jacque Monod's use of Beta-galactosidase some years later in formulating his theories on the mechanism of genetic expression and control in E. coli.

    During the same period in the early 1950s, Lederberg and Zimmer developed a procedure, replica plating, which made possible the selection of mutants that were resistant to antibiotics or to bacterial viruses (called bacteriophages, or phages for short) without exposing them to the selective agent, the drug or the phage. They transferred impressions of a large number of bacterial colonies from a master plate, a circular glass dish where they had been cultured on growth media, to other, sterile plates (sterile meaning they contained not bacterial colonies of their own). For this they at first used blotting paper (numerous pieces of which can be found taped into his laboratory notebooks), then a beaker full of toothpicks, and finally velveteen cloth, which was pressed onto the colonies on the master plate, picking up members of colonies in their original spatial layout, which was then pressed onto the secondary plates, producing a copy, or replica, of the lawn of bacterial colonies on the master plate. The selective agent was spread on the secondary plates, which meant that only resistant colonies were able to grow on them. Their locations on the master plate could be inferred from their congruent location on the secondary plate. More colonies could be transferred from their locations of origin on the master plate, and the process repeated, until all resistant colonies on the master plate had been isolated.

    Replica plating confirmed that drug or phage resistance in bacteria was the result of a genetic mutation, and not a physiological adaptation to the presence of the selective agent. It discredited Lamarckian interpretations, still held by some scientists including Nobel laureate Sir Cyril Hinshelwood, that characteristics in bacteria such as drug resistance were acquired under adverse environmental influences, for instance the presence of antibiotics, and were then imprinted into the bacterial genome. As a laboratory technique, replica plating became widely used for genetic studies of large populations of bacteria.

    Most notably, Lederberg and Zinder in 1951 uncovered a third mechanism of genetic transfer in bacteria, in addition to the mechanisms of transformation, discovered by Oswald Avery, and of mating, discovered by Lederberg himself. Lederberg named it transduction, from the Latin transducere, to lead across. Lederberg and Zinder had observed conjugation in several nutritional and drug-resistant mutants of Salmonella. Now they wanted to undertake a reverse test to ascertain that their results indeed reflected genetic recombination. They used a glass tube, bent into a U-shape and fitted with an extremely fine glass filter at the crook, and filled it with broth containing none of the nutrients their Salmonella mutants needed to grow. They then added one mutant parent strain to each arm, and pumped the broth back and forth through the filter. They expected to find no recombinants, because as Bernard Davis had recently shown the year before by using the same U-shaped device, the bacterial cells in Lederberg's original crossing experiments had to be in direct contact with one another for conjugation to take place.

    To their surprise, several bacteria nonetheless appeared and multiplied, an indication that recombination had occurred and had enabled each mutant strain to compensate for the nutritional deficiencies of the other. Obviously, a biological agent small enough to pass through the filter was at work. When they purified the agent, they found that it did not consist of pure deoxyribonucleic acid (DNA), Avery's transforming principle, or ribonucleic acid (RNA), because it was unaffected by enzymes that cleave these two nucleic acids. Instead, it proved to be a bacteriophage. The Salmonella Lederberg and Zinder had used turned out to be lysogenic: it had been infected many generations ago by a phage, whose viral DNA had been integrated into the chromosome of its bacterial host and had replicated along with the host chromosome. During the experiment the viral DNA had induced the synthesis of new phage within some of the Salmonella hosts, followed by the bursting, or lysis, of the host cell and the release of phage into the broth. Prior to lysis, the phage particles had picked up random snippets of host DNA, which they now carried across the filter (the phage were small enough to pass through) to the other arm of the test tube, there to infect other Salmonella bacteria and insert the fragments of bacterial DNA, along with their own viral genes, into the chromosomes of their new hosts. The phage had acted as a vector for bacterial genes. In this manner, Lederberg and Zinder concluded, the newly-infected mutant bacteria had acquired the genes that made up for their mutual genetic (nutritional) defects.

    The discovery of transduction was of fundamental scientific significance. It foretold William Hayes' discovery in 1952 that recombination in prokaryotes, cells without a clearly defined nucleus and with only a short segment of double-stranded DNA as their genetic material (such as bacteria), was a fragmentary process, meaning that these cells did not merge their complete genomes but only fragments thereof. This was in contrast to eukaryotes, the more complex cells of higher organisms, which have a nucleus encapsulated by a membrane as well as chromosomes on which DNA is associated with various proteins in an intricate conformation. Eukaryotic cells reproduce by endowing their two daughter cells with full complements of the chromosomes of their parents. The differentiation between prokaryotes and eukaryotes, to which Lederberg's transduction experiment contributed in crucial ways, became one of the founding concepts of molecular biology.

    Transduction was of equal consequence in medicine and biotechnology. It broadened conceptions about the composition, action, and biological significance of viruses. As an experimental technique, it helped researchers map bacterial chromosomes in fine detail. It explained how bacteria acquired genes that made them resistant to drugs much more quickly than the natural rate of genetic mutation and natural selection would allow: they simply picked up such genes from another strain by way of a viral medium.

    Transduction also played an essential role in the development of genetic engineering. Although the term was unknown at the time, the fact that the Genetics Department in which Lederberg held tenure was part of the University of Wisconsin's College of Agriculture made him well aware of the many practical applications of genetic research. That transduction could be similarly used to manipulate genes did not escape him. During the 1970s scientists learned to direct bacterial viruses to pick up pieces of DNA with a known sequence of nucleotides (and thus with a known function) and insert them into a bacterial chromosome, where they functioned in the same manner as the host's genes. During the 1990s, the use of viral vectors to deliver healthy genes to cells lacking such genes became the basis of gene therapy. Lederberg himself advanced the development of the biotechnology industry in the United States from its beginning by serving as a consultant to the Syntex Corporation and the Cetus Corporations, commercial pioneers in the field, between 1961 and 1978.

    A second important factor in the growth of biotechnology was Lederberg's discovery that bacteria contain ring-shaped, extrachromosomal pieces of DNA, which he named plasmids. Plasmids replicate independently of the chromosomes and transmit genes that specify functions not essential for cell growth. One such function is conjugation, which takes place only in bacterial strains carrying the so-called F plasmid. (The strain Lederberg first used in his mating experiments in 1945 lacked this plasmid.) Another is the production of enzymes, a property that would make plasmids an important tool for genetic engineering. During the 1970s, scientists succeeded in cleaving plasmids at specific locations with the help of so-called restriction enzymes, and in splicing into them foreign pieces of DNA, such as the gene for human insulin. Once closed up and reinserted into the bacterium, the altered plasmid directed the bacterium and its progeny (which inherited the engineered plasmid) to produce insulin for medical treatment, the first such drug created through genetic engineering.


    Watch the video: ΣΩΣΤΗ ΧΡΗΣΗ ΑΝΤΙΒΙΟΤΙΚΩΝ (September 2022).


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