Salmonella. Image by Dr Mary Parker, the Quadram Institute
Cutting-edge technology has allowed scientists to watch bacteria developing antimicrobial resistance in real-time, according to new research published in Microbial Genomics.
Single-cell genomics and analysis, being pioneered at the Earlham Institute in Norwich, could help to chronicle the appearance of genetic mutations that allow bacteria to resist antibiotics, providing new and urgently-needed avenues to tackle the rise of superbugs.
Antibiotic resistance describes how bacteria have changed and evolved through random mutations in their DNA in response to antibiotics, which are usually prescribed to fight bacterial infections. However, due to their overuse throughout medicine and agriculture, antibiotics can now be found in most ecosystems. This misuse of antibiotics, coupled with other factors including poor sanitation, have played a part in the rise of so-called superbugs – infectious bacteria which are resistant to current antibiotics. With a lack of new antibiotics in development, scientists are looking to better understand the genetic origins of this resistance.
In this study, a collaboration between researchers based at the Quadram Institute and Earlham Institute, funded by a BBSRC Tools and Resources Development Fund (TRDF) award, researchers exposed strains of Salmonella to small concentrations of ciprofloxacin, a common antibiotic used to treat bacterial infections.
By taking regular samples and sequencing single cells in the population, they were able to track mutations as they appeared and record any that helped the bacteria evade the treatment. The team were able to identify specific mutations in single cells known to be responsible for resistance. They were also able to determine variation in the population; whether all resistant bacteria had one common ancestor, or if multiple bacteria had mutated independently.
“The evolution of bacteria is like a card game; the environment plays a card and the bacteria has to beat the dealer,” said study author Dr Matt Bawn, Postdoctoral Scientist at the Earlham Institute and Quadram Institute. “If there are more sub-populations, then the bacteria have more cards to play and can increase their chance of success.”
If scientists can ‘cheat’ by seeing the bacteria’s hand, they can analyse the population diversity and understand precisely how adaptable and likely its survival will be – informing more personalised treatments for common bacterial infections.
Previous in vitro evolutionary studies have used a technique called ‘bulk sequencing’ to analyse the genetic variation occurring in evolving populations, where all individual genomes within a population are sequenced together. Although this enables scientists to see the differences between populations at different time points, it doesn’t link those differences to individual cells or allow for the identification of sub-populations that share similar genetic traits, such as a specific mutation that confers antibiotic resistance.
Single-cell sequencing is a rapidly emerging technology that allows individual cells and sub-populations to be identified. More commonly applied to study human cells, for example in cancer or developmental biology, the technology can also provide a much higher resolution view of bacterial genomes, helping to reveal genetic changes that might otherwise have been missed.
Dr Johana Hernandez, joint first author and former EI postdoc, currently Leader of Genomic Surveillance at Secretaria Distrital de Salud, Colombia, said: “Applying single-cell technology to bacteria is still relatively new – for this study we had to develop approaches to isolate individual cells and subsequently read out the minute amount of DNA present in them. “We were really amazed by the amount of data we could generate from each cell; sometimes we could read almost all of a single cell’s genome – and we could use that data to accurately detect mutations that distinguish one cell from another.”
“This makes it a perfect tool to explore bacterial evolution and the emergence of AMR”
Professor Mark Webber, study author at the Quadram Institute and University of East Anglia, said: “We know mutation is fundamental to the development of antibiotic resistance, this study has allowed us to study this process in unprecedented detail and understand better the routes by which bacteria can become resistant to drugs. This is important in allowing us to develop ways to use current drugs better and prevent resistance emerging in future.”
Dr Iain Macaulay, Group Leader in Technical Development at the Earlham Institute, said: “Single-cell techniques bring the kind of resolution that is absolutely fundamental to identifying genetic diversity. This allows us to start spotting those cells or sub-populations that have acquired a change in their DNA with the potential to make the bacteria more resilient. “In a way it lets us build a ‘family tree’ of the bacteria as they evolve and see the branches of that tree where resistance emerges.”
This work suggests microbes are evolving resistance at a greater rate than we are discovering and developing new antibiotics. There is hope for new alternatives but the researchers are cautious.
“Considering how easily bacterial populations adapt to our current antibiotics,” says Dr Bawn, “there’s no guarantee that future solutions will be viable for long. “This single-cell approach has the potential to future-proof emerging antibacterial treatments, such as phage therapy, by looking at how they affect bacterial evolution at a greater resolution than ever before.”
In the future, the researchers hope to scale up their single-cell approach and establish whether it could provide a route to developing treatments that reduce bacterial virulence by limiting its population diversity. Single-cell genomics reveals population structures from in vitro evolutionary studies of Salmonella is published in Microbial Genetics.
Reference: Single-cell genomics reveals population structures from in vitro evolutionary studies of Salmonella. Matt Bawn, Johana Hernandez, Eleftheria Trampari, Gaetan Thilliez, Christopher Quince, Mark A. Webber, Robert A. Kingsley, Neil Hall, Iain C. Macaulay. Microbial Genomics DOI: 10.1099/mgen.0.000871