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Alyssa Pivirotto ACCESS CSSN, Campus Champions
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Daniel Morales Campus Champions
Deborah Penchoff Campus Champions
Diana Toups Dugas RMACC, SWEETER, Campus Champions
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Jeffrey Weekley Campus Champions
Jason Wells ACCESS CSSN, Campus Champions
Amy Koshoffer Campus Champions
shuai liu ACCESS CSSN
Nicholas Danes Campus Champions, MINES
Nicholas Panchy Campus Champions
Rob Harbert Northeast
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Thomas Pranzatelli
Wesley Brashear ACCESS CSSN, Campus Champions
William Lai ACCESS CSSN
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Aidan McCrillis
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Projects
Project Title Project Institution Project Owner Tags Status
High throughput Python pipeline to identify Horizontal Gene Transfer Cabrini University Vinayak Mathur bioinformatics, biology, data-wrangling, genomics, github, python, workflow Halted
Metagenomic analysis to identify gene clusters associated with IgA production SUNY Upstate Medical University Joel Wilmore bioinformatics, biology, genomics, python, r, research-facilitation Finishing Up
Simulating 21st century boreal forests and fire with a state-of-the-art process-based model Cary Institute Winslow Hansen biology, cluster-support, dependencies, deployment, netcdf, performance-tuning, r Finishing Up
Assembly and Taxonomic Profiling of Metagenomic Sequences using Deep Learning University of Rhode Island Gaurav Khanna ai, bioinformatics, biology, deep-learning, gpu, hardware, machine-learning, neural-networks, python Complete
Host-symbiont population genomics - analyzing the intraspecific variability of methanogenic archaeal endosymbionts of genus Methanocorpusculum hosted by a marine anaerobic ciliate Metopus sp. (Metopida) University of Rhode Island -- Bay Campus Gaurav Khanna bioinformatics, biology, genomics Complete
Develop a data portal for the organization of molecular and imaging data University of Rhode Island -- Bay Campus Gaurav Khanna archiving, aws, bioinformatics, biology, Cloud, Data Storage, docker, genomics Complete
Detecting Covid-19 Misinformation on Social Media Bryant University Gaurav Khanna ai, bash, batch-jobs, big-data, biology, cuda Complete
Computational pipelines for the analysis of plastic-degrading genes University of Rhode Island Gaurav Khanna bioinformatics, biology, workflow, workforce-development Complete
Development of personalized healthy food incentives to improve diet and cardiovascular risk University of Rhode Island Gaurav Khanna biology Complete
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Prediction of Polymerization of the Yersinia Pestis Type III Secretion System
Nova Southeastern University

Yersinia pestis, the bacterium that causes the bubonic plague, uses a type III secretion system (T3SS) to inject toxins into host cells. The structure of the Y. pestis T3SS needle has not been modeled using AI or cryo-EM. T3SS in homologous bacteria have been solved using cryo-EM. Previously, we created possible hexamers of the Y. pestis T3SS needle protein, YscF, using CollabFold and AlphaFold2 Colab on Google Colab in an effort to understand more about the needle structure and calcium regulation of secretion. Hexamers and mutated hexamers were designed using data from a wet lab experiment by Torruellas et. al (2005). T3SS structures in homologous organisms show a 22 or 23mer structure where the rings of hexamers interlocked in layers. When folding was attempted with more than six monomers, we observed larger single rings of monomers. This revealed the inaccuracies of these online systems. To create a more accurate complete needle structure, a different computer software capable of creating a helical polymerized needle is required. The number of atoms in the predicted final needle is very high and more than our computational infrastructure can handle. For that reason, we need the computational resources of a supercomputer. We have hypothesized two ways to direct the folding that have the potential to result in a more accurate needle structure. The first option involves fusing the current hexamer structure into one protein chain, so that the software recognizes the hexamer as one protein. This will make it easier to connect multiple hexamers together. Alternatively, or additionally the cryo-EM structures of the T3SS of Shigella flexneri and Salmonella enterica Typhimurium can be used as models to guide the construction of the Y. pestis T3SS needle. The full AlphaFold library or a program like RoseTTAFold could help us predict protein-protein interactions more accurately for large structures. Based on our needs we have identified the TAMU ACES, Rockfish and Stampede-2 as promising resources for this project. The generated model of the Y. pestis T3SS YscF needle will provide insight into a possible structure of the needle. 

Status: Complete

People with Expertise

Frédéric Chevalier

Texas Biomedical Research Institute

Programs

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researcher/educator, domain champion

Expertise

Chris Hemme

University of Rhode Island

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Alyssa Pivirotto

Bryn Mawr College

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ACCESS CSSN, Campus Champions

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research computing facilitator, cssn

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Kaitlyn Varela

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ACCESS CSSN

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Ana Ayala Pazzi

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ACCESS CSSN

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Alexandra Lamtyugina

University of Chicago

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ACCESS CSSN

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