Title: Computational Problems in Metagenomic Amplification
Speaker: Christina Boucher - University of Florida
Metagenomic data can be used to profile high-importance functions within microbiomes. However, current metagenomic workflows produce data that suffer from low sensitivity and an inability to accurately reconstruct partial or full genomes. These limitations preclude colocalization analysis, i.e., the ability to characterize the genomic context of genes and functions within a metagenomic sample. Genomic context is especially crucial for functions associated with horizontal gene transfer (HGT) via mobile genetic elements (MGEs), for example antimicrobial resistance genes (ARGs). In this talk, I will present a method for comprehensive and accurate reconstruction of antimicrobial resistance genes (ARGs) and MGEs from metagenomic DNA, termed target-enriched long-read sequencing (TELSeq). TELSeq uses bait enrichment, which is a new sequencing protocol that is becoming increasingly ubiquitous as it has been shown to successfully amplify regions of interest (such as MGEs and ARGs) in metagenomic samples.
Hence, I will discuss the computational challenge of designing baits, and present our solution to this challenge, which we refer to as Syotti. We show that Syotti requires only 25 minutes to design baits for a dataset comprised of 3 billion nucleotides from 1000 related bacterial substrains, whereas competing methods fail to process even a subset of 8% of the data in 24 hours. Next, I demonstrate the use of bait enrichment in TELSeq. Using replicates of diverse sample types, I will present the performance of TELSeq to that of non-enriched PacBio and short-read Illumina sequencing. TELSeq achieved much higher sensitivity than the other methods, revealing an extensive resistome profile comprising many low-abundance ARGs, including some with public health importance. Using the long reads generated by TELSeq was able to identify numerous MGEs flanking the low-abundance ARGs, indicating that these ARGs could be transferred across bacterial taxa via HGT.
Dr. Boucher is an Associate Professor in the Department of Computer and Information Science and Engineering at the University of Florida. She has over 85 publications in bioinformatics, with over two dozen of them in succinct data structures and/or alignment. Considering this, she was a keynote speaker for IABD 2019, FAB 2018, RECOMB-SEQ 2016 and the ECCB 2016 Workshop on Pan-Genomics. She is a recipient of an ESA 2016 Best Paper Award. She oversees the development and maintenance of several software methods, including MEGARes and AMRPlusPlus, METAMarc, Kohdista, Vari, VariMerge — and most recently, Moni. In addition, she has built a team of collaborators in various biomedical sciences including microbiology, veterinarian medicine, epidemiology, public health, and clinical sciences.
In addition, she actively works on increasing the diversity in bioinformatics education. Her efforts include being a member of the University of Florida’s Implicit Bias committee, being a panellist for the NSF-funded ACM BCB 2015 Women in Bioinformatics meeting, serving as a faculty advisor for an ACM-W chapter, and being an active member of the Diversity Committee for over three years. She also received a fellowship from The Institute for Learning and Teaching (TILT) for her course redevelopment and served on the advisory committee for an NSF Research Traineeships Program.
She has been the PC chair for several conferences, including SPIRE 2020, RECOMB-SEQ 2019, and ACM-BCB 2018. Most recently, she was nominated to serve on the NIH BDMA Study Section as a Standing Member, and a Board Member of SIG BIO.
Contact Person: Zsuzsanna Lipták
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