Wastewater monitoring for SARS-CoV-2 variants of concern in Houston

Background

The prevalence of SARS-CoV-2 RNA in stool [1, 2, 3] has opened the door to several SARS-CoV-2 wastewater surveillance efforts across the globe. In the rush to surveil the presence of SARS-CoV-2 in wastewater, PCR-based diagnostics designed for pristine clinical samples (from nasopharyngeal swabs and saliva samples) were deployed for wastewater monitoring. However, SARS-COV-2 RNA in wastewater can be degraded and partial, and is commonly found in trace amounts. In addition, sensitive and accurate detection and functional characterization of microbial pathogens in water samples presents many challenges. Furthermore, prior efforts have highlighted the need to monitor a collection of indicator organisms in wastewater to have improved predictive power for detecting the presence of specific pathogens. In collaboration with the Stadler lab, the goal of this project is two-fold: 1) design improved computational approaches for targeted detection of SARS-CoV-2 Variants of Concern (VOC) in wastewater, and 2) compare and contrast targeted diagnostics to untargeted metagenomic sequencing approaches for tracking outbreaks of emerging pathogens.

Collaborators

  • Dr. Lauren Stadler (Rice University)
  • Esther G. Lou (Rice University)
  • Dr. Kathy Ensor (Rice University)
  • Dr. Loren Hopkins (HHD)
  • Rebecca Schneider (HHD)
  • Ryker Penn (HHD)
  • Pamela Brown (HHD)
Nicolae Sapoval
Nicolae Sapoval
PhD student

Nick (4th year PhD student) obtained a B.S. degree in Computer Science and a B.S. with Honors in Mathematics from the University of Chicago. At the University of Chicago Nick worked in wireless networks research and later in computational biophysics focusing on conformational transition modeling for insulin degrading enzyme. His current interests are in the areas of computational biology with a focus on genomic data.

Yunxi Liu
Yunxi Liu
PhD student

Louis (4th year PhD student) obtained a B.S. degree in Computer Science from the University of Houston and a B.S. degree in Pharmacology from China Pharmaceutical University. During his undergraduate in UH, he did research in the Pattern Analysis Laboratory on image feature extraction. His current research interests include computational biology, metagenomics, and data science.

Dr. Michael Nute
Dr. Michael Nute
Postdoctoral Scientist from August 2020 through September 2022

Mike (Postdoctoral Scientist) received his Ph.D. in Statistics in 2019 from the University of Illinois at Urbana-Champaign where he was advised by Dr. Tandy Warnow in the Department of Computer Science and worked on algorithms related to multiple sequence alignment and phylogenetic tree estimation, in particular applying these methods to studying microbial communities. He was co-advised by Dr. Rebecca Stumpf in the Department of Anthropology where he and other lab members developed novel methods to compare the microbiomes of human and non-human primates. His research interest is in discovering a new applications for our understanding of microbial communities.

Michael Wang
Michael Wang
PhD student

Michael (4th year PhD student) obtained a B.E. degree in Biomedical Engineering from Tsinghua University in 2019. During his undergraduate, he did research in developing multiplexed droplet digital PCR (ddPCR). His primary research interest is primer and probe design for highly multiplexed NGS panels.

Todd J. Treangen
Todd J. Treangen
Assistant Professor of Computer Science

My research interests include algorithms and data structures for efficient analysis of microbial genomes and metagenomes

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