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Using genomics to combat superbugs: Q/A with Dr. Rob Beiko

Recently, the Government of Canada announced funding for 37 Genome Canada projects including $1.4 million for Antimicrobial Resistance: Emergence, Transmission, and Ecology (ARETE), a project co-led by Dalhousie University’s Dr. Robert Beiko and Dr. Fiona Brinkman of Simon Fraser University.  ARETE aims to develop new surveillance tools to help identify and track the genes that contribute to antimicrobial resistance (AMR), a huge problem for the agri-food industry and the health of Canadians.

Backed by his lab team at Dalhousie University, Dr. Beiko has earned a place on the front line of bioinformatics research, probing the mysteries of AMR in bacteria. It’s an area of pressing worldwide concern for human health, agriculture and the food industry, as the effectiveness of antibiotics declines and antimicrobial resistance grows.

A biologist and expert in computational biology, he applies the power of algorithms, machine-learning and biological data visualization to microbial research. His focus has been on gaining a better understanding of the genes that make bacteria resistant to antibiotics and how they spread.

Genomics has a central role in this research field.  Unfortunately, current analysis tools lack the needed software to predict antimicrobial resistance profiles in the huge datasets generated from genetic profiling of microbial communities (metagenomics). Software is needed to separate the wheat from the chaff. Dr. Beiko, alongside Drs. Andrew McArthur of McMaster University and Fiona Brinkman of Simon Fraser University, has been working on a software solution, enabled by Genome Canada’s Bioinformatics and Computational Biology funding program, with support from Genome Atlantic.  

Through ARETE, Drs. Beiko, Brinkman and their fellow researchers will take a closer look at lateral gene transfer (LGT), the process by which bacteria share genes with each other. Disease-resistant bacteria can move between habitats, such as soil and animals, but science has yet to learn the most important points of transmission – this information is vital for monitoring and regulating the process.

Dr. Beiko has led or been involved in numerous large-scale research projects funded by Genome Canada, Genome Atlantic and other regional Genome Centres, the Natural Sciences and Engineering Council of Canada, and other major national and international granting agencies.

How close are you to developing software that will open up microbe research for better genomics analysis?

It’s an ongoing process. You can draw a clear line from the tools developed in the 1980s, which were developed before genome sequencing really took off, to the ones we use today. Each technological revolution brings new challenges, and we were asking very different questions in 2000 when the first microbial genomes came out than we are now. Where once we had maybe one or two genomes of important species, we’re now looking at tens of thousands of genomes of E. coli or Salmonella alone. These rich datasets offer great opportunities for us to map out the fine points of the emergence and evolution of pathogens, and AMR in particular. But as you can probably guess, dealing with 100,000 genomes at a time opens up some new and very exciting challenges from a bioinformatics standpoint.

ARETE is built on a foundation of existing tools, including large databases of AMR genes and mutations, methods to identify regions of microbial genomes that pose a high risk for carrying and transmitting AMR, and software that can identify the transmission of genes between potentially very distantly-related bacteria. A key challenge in ARETE is getting these tools working together properly and to scale up the absurd number of genomes that are coming down the pipe. Consequently, and coming back to the original question, many pieces of the puzzle are in place, which makes us very optimistic about delivering a unified toolkit over the three years of the project.

What practical advantages do you envision for microbe research from this kind of software?

A key aspect of the ARETE project is the close involvement of researchers in the Public Health Agency of Canada. DNA sequencing has become the gold standard for mapping epidemics, which has resulted in a huge effort to sequence the genome of every pathogen that comes across our desk. But what are the benefits of having all this information? There are lots of practical outcomes of this research, but the key driver of ARETE and the wider umbrella of genomic epidemiology projects is the ability to study the transmission pathways of both AMR genes and the bacteria that contain them. If you see the exact same gene in chicken X and patient Y, in farm soil, sewage, or what have you, that can give you a pretty clear view of what is being transferred, where it is happening, and by whom. This knowledge can then drive efforts to contain the spread of AMR.

What intrigues you most about lateral gene transfer – the process of gene sharing among bacteria?  Why?

The realization that LGT is a defining aspect of microbial evolution broke most people’s preconceived notions about how bacteria evolve. When we think about inheritance, we almost invariably picture an unbroken line of transmission from parent to offspring. In a lot of cases this is not true of microorganisms. Although researchers always knew that some transmission was happening, the central role of LGT could only be appreciated when people started to sequence genomes en masse. We now know that when one microorganism has a good idea, evolutionarily speaking, it might not be long before its neighbours pick it up. While the life-or-death (for the bacterium) situation of AMR is a particularly acute driver, we see strong evidence for a central role of LGT in the evolution of everything from adaptation to extreme temperatures (in some cases, above the boiling point of water) to the breakdown of new compounds that humans have introduced into the environment.

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