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102 Early days of MLST

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Treść dostarczona przez Micro Binfie Podcast and Microbial Bioinformatics. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Micro Binfie Podcast and Microbial Bioinformatics lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.
Ed Feil is a professor of bacterial evolution at the University of Bath, and Natacha Couto, a data scientist at the Center of Genomic Pathogen Surveillance at the University of Oxford. We delve into the concept of multi-locus sequence typing (MLST) in bacterial population genetics. They highlight how the MLST method allows for defining strains based on partial sequences that range up to 500 base pairs. The method measures differences between loci for each strain, offering an allele number while assigning similar numbers to identical sequences. The cumulative sequence number represents the unique identification, which is subsequently referred to as the sequence type (SST). MLST has revolutionized the field by facilitating digital storage and comparison of epidemiological databases, proving particularly useful in investigating transmission events and dissemination of certain strains. Although there are other methods such as Pulse Field Gen Electrophoresis (PFGE) that offer higher resolution when looking for similarities between different strains, MLST remains a versatile and widely used method. They also talk about the shortcomings of MLST and the need for continued improvements in population genetics research. They mention the development of the Eburst program, which uses a circular model, rather than the traditional dendrogram tree structure, to better visualize MLST data and understand the clonal expansion of populations. They also discuss how the original MLST schemes may not have included the best genes for all bacterial species as the genes were chosen before genome sequencing became widely available. Ed and Natacha further elaborate on the concept of clonality among bacterial species. Ed suggests that bacterial population structures have no consistent pattern, with some organisms being well-behaved, while others have a lot of allele shuffling. However, clones have existed since day one, and their presence is still seen today. Natacha adds that although MLST has flaws, it leaves behind the nomenclature for the lineages or clones, which is a lasting legacy. Nabil-Fareed notes that while most reference labs have moved on to genomics, some people still use MLST. He adds that the pipeline is the same for any organism, and the process is efficient in the end. The discussion concludes with the hosts thanking the guests and promising more exciting topics in their next episode. Overall, the hosts highlight the significance of understanding the limitations of MLST and the scope for further research in bacterial population genetics.
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Manage episode 357586619 series 3381906
Treść dostarczona przez Micro Binfie Podcast and Microbial Bioinformatics. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Micro Binfie Podcast and Microbial Bioinformatics lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.
Ed Feil is a professor of bacterial evolution at the University of Bath, and Natacha Couto, a data scientist at the Center of Genomic Pathogen Surveillance at the University of Oxford. We delve into the concept of multi-locus sequence typing (MLST) in bacterial population genetics. They highlight how the MLST method allows for defining strains based on partial sequences that range up to 500 base pairs. The method measures differences between loci for each strain, offering an allele number while assigning similar numbers to identical sequences. The cumulative sequence number represents the unique identification, which is subsequently referred to as the sequence type (SST). MLST has revolutionized the field by facilitating digital storage and comparison of epidemiological databases, proving particularly useful in investigating transmission events and dissemination of certain strains. Although there are other methods such as Pulse Field Gen Electrophoresis (PFGE) that offer higher resolution when looking for similarities between different strains, MLST remains a versatile and widely used method. They also talk about the shortcomings of MLST and the need for continued improvements in population genetics research. They mention the development of the Eburst program, which uses a circular model, rather than the traditional dendrogram tree structure, to better visualize MLST data and understand the clonal expansion of populations. They also discuss how the original MLST schemes may not have included the best genes for all bacterial species as the genes were chosen before genome sequencing became widely available. Ed and Natacha further elaborate on the concept of clonality among bacterial species. Ed suggests that bacterial population structures have no consistent pattern, with some organisms being well-behaved, while others have a lot of allele shuffling. However, clones have existed since day one, and their presence is still seen today. Natacha adds that although MLST has flaws, it leaves behind the nomenclature for the lineages or clones, which is a lasting legacy. Nabil-Fareed notes that while most reference labs have moved on to genomics, some people still use MLST. He adds that the pipeline is the same for any organism, and the process is efficient in the end. The discussion concludes with the hosts thanking the guests and promising more exciting topics in their next episode. Overall, the hosts highlight the significance of understanding the limitations of MLST and the scope for further research in bacterial population genetics.
  continue reading

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