Microbial communities profoundly impact host biology by influencing immune development, metabolic processes, and therapeutic outcomes. However, accurately profiling these communities at sufficient resolution to capture subtle, biologically meaningful differences remains challenging. Variability in microbiome composition—even among genetically identical laboratory animals under controlled conditions—can confound experimental results and hinder reproducibility. Addressing this challenge requires methods capable of experimentally standardizing microbiomes and computationally profiling them with strain-level resolution. First, I will present a bioinformatics workflow capable of handling large-scale microbiome datasets with high resolution. This workflow was used to demonstrate that a single antibiotic-free cecal microbiome transplantation (CMT) effectively standardizes gut microbiomes across genetically diverse mouse populations, reducing unwanted variability without promoting antibiotic-resistant pathogens. I will then introduce AmpliconHunter, a tool developed to facilitate precise identification and tracking of these microbiomes. AmpliconHunter is a highly scalable computational tool for accurate PCR amplicon sequence prediction using degenerate primers. Its performance enables efficient strain-level profiling and evaluation of primer pairs with similar accuracy and significantly improved speed when compared to existing methods. I will also detail my work creating AmpliconHunter2: a SIMD-accelerated update to the original that completes analysis for V1V9 primers on the ~2.4M genomes from the AllTheBacteria project in 38.73 minutes, compared to 419.45 minutes for AmpliconHunter (~10.8x speedup). Finally, I will introduce another tool: Microbiome HiFi Amplicon Sequence Simulator (MHASS) creates realistic synthetic PacBio HiFi amplicon sequencing datasets for microbiome studies, by integrating genome-aware abundance modeling, realistic dual-barcoding strategies, and empirically derived pass-number distributions from actual sequencing runs. MHASS generates datasets tailored for rigorous benchmarking and validation of long-read microbiome analysis workflows, including ASV clustering and taxonomic assignment. Together, these innovations will provide practical, robust and scalable methods to address microbiome variability, improving reproducibility and translational potential in microbiome-focused biomedical research. All tools are made available on GitHub under an MIT license. AmpliconHunter and AmpliconHunter2 are also made available as freely accessible web servers at https://ah1.engr.uconn.edu and https://ah2.engr.uconn.edu/.

Abstract: Microbial communities profoundly impact host biology by influencing immune development, metabolic processes, and therapeutic outcomes. However, accurately profiling these communities at sufficient resolution to capture subtle, biologically meaningful differences remains challenging. Variability in microbiome composition—even among genetically identical laboratory animals under controlled conditions—can confound experimental results and hinder reproducibility. Addressing this challenge requires methods capable of experimentally standardizing microbiomes and computationally profiling them with strain-level resolution. First, I will present a bioinformatics workflow capable of handling large-scale microbiome datasets with high resolution. This workflow was used to demonstrate that a single antibiotic-free cecal microbiome transplantation (CMT) effectively standardizes gut microbiomes across genetically diverse mouse populations, reducing unwanted variability without promoting antibiotic-resistant pathogens. I will then introduce AmpliconHunter, a tool developed to facilitate precise identification and tracking of these microbiomes. AmpliconHunter is a highly scalable computational tool for accurate PCR amplicon sequence prediction using degenerate primers. Its performance enables efficient strain-level profiling and evaluation of primer pairs with similar accuracy and significantly improved speed when compared to existing methods. I will also detail my work creating AmpliconHunter2: a SIMD-accelerated update to the original that completes analysis for V1V9 primers on the ~2.4M genomes from the AllTheBacteria project in 38.73 minutes, compared to 419.45 minutes for AmpliconHunter (~10.8x speedup). Finally, I will introduce another tool: Microbiome HiFi Amplicon Sequence Simulator (MHASS) creates realistic synthetic PacBio HiFi amplicon sequencing datasets for microbiome studies, by integrating genome-aware abundance modeling, realistic dual-barcoding strategies, and empirically derived pass-number distributions from actual sequencing runs. MHASS generates datasets tailored for rigorous benchmarking and validation of long-read microbiome analysis workflows, including ASV clustering and taxonomic assignment. Together, these innovations will provide practical, robust and scalable methods to address microbiome variability, improving reproducibility and translational potential in microbiome-focused biomedical research. All tools are made available on GitHub under an MIT license. AmpliconHunter and AmpliconHunter2 are also made available as freely accessible web servers at ah1.engr.uconn.edu (https://nam10.safelinks.protection.outlook.com/?url=http%3A%2F%2Fah2.engr.uconn.edu%2F&data=05%7C02%7Cscott.cathcart%40uconn.edu%7Ced715e9889ed453f1e3508de1702a046%7C17f1a87e2a254eaab9df9d439034b080%7C0%7C0%7C638973497307282439%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=t8y8O3Bp7PLzt%2B2n%2FbU%2BphngUK7fDCsi0bfQ62np2F0%3D&reserved=0) and ah2.engr.uconn.edu (https://nam10.safelinks.protection.outlook.com/?url=http%3A%2F%2Fah2.engr.uconn.edu%2F&data=05%7C02%7Cscott.cathcart%40uconn.edu%7Ced715e9889ed453f1e3508de1702a046%7C17f1a87e2a254eaab9df9d439034b080%7C0%7C0%7C638973497307308204%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=Ndsyhc4WFLKZw0r3MmHs7ZFwzlmHjWTxofTSdKGlRC4%3D&reserved=0).

For the full class schedule, descriptions, and to register, please visit the UConn Recreation website (https://recreation.uconn.edu/group-fitness-schedule/).

Students who may benefit from attending a Let's Talk: Mental Health Office Hours session include:Students who want help connecting to resources but are unsure where to begin Students who are looking for advice on a non-clinical issue Students who are unsure about therapy and are curious about what it is like to talk to a therapist Students who may have concerns about the mental health of a friend and seek advice on how to support their friend If a student is not an imminent risk, and is refusing your support in contacting our office, you may also consider contacting the UConn Student CARE Team (https://studentcareteam.uconn.edu/). This session is held by Sarah Hallwood, LCSW, LICSW (https://studenthealth.uconn.edu/person/sarah-hallwood/)