Conference Contributions
Optimizing targeted interventions: Identifying Imported SARS-CoV-2 Lineages and Reconstructing Local Dispersal in Large Phylogenetic Datasets (Poster presented at EEID)
A Comparative Machine Learning Analysis of SARS-CoV-2 Wastewater Surveillance Methods for COVID-19 Case Prediction (Poster presented at ASM Microbe)
This work aimed to explore the predictive capabilities of SARS-CoV-2 wastewater surveillance data produced by varying methodologies to better prioritize wastewater monitoring and predictive efforts. More specifically, both quantifiable (qPCR) and non-quantifiable (presence-absence) SARS-CoV-2 wastewater data were used to train Random Forest models to predict county-level COVID-19 case counts. We also tested the influence of replicate depth (n of extraction replicates) on model performance. Finally, we determined the model with the best accuracy and fit and examined the importance of each feature (wastewater catchment, gene target). These insights could allow for more simplified, rapid approaches for wastewater pathogen detection and case incidence prediction.
Phylodynamics of the H5Nx Clade 2.3.4.4b Avian Influenza Outbreak in Europe and Phylogeographic Diffusion and Host Dynamics of HPAI H5Nx Virus Clade 2.3.4.4b in Europe (Posters presented at EEID & CEIRR)
Integrating Molecular Dynamics and Phylodynamics to Unravel Sialic Acid and HA Interactions Patterns in Avian H5 2.3.4.4b Influenza (Poster presented at CEIRR)
A Preliminary Study on Wastewater-Based Genomic Surveillance for the Early Detection of SARS-CoV-2 and its Distinct Transmission Patterns Across the State of Georgia (GPHL poster)
Harrison Yu, Steven Woods, Carter O’Ryan, Lauren Briggman, Jason Harrison, Amanda Feldpausch, Cristina Meza, Hannah-Leigh Crawford, Tonia Parrott, Arunachalam Ramaiah, Nandhakumar Balakrishnan
Wastewater surveillance offers a non-invasive method to track community-level trends of circulating pathogens, complementing traditional clinical testing. The Georgia Public Health Laboratory, in collaboration with Georgia National Wastewater Surveillance System (NWSS) program, has sequenced SARS-CoV-2 from over 700 wastewater samples collected across 17 treatment facilities in Georgia from January 2023 to July 2024. A Nextflow-based bioinformatics pipeline was developed and used to call variants and obtain lineage abundances. This study identified wastewater-based genomic surveillance of SARS-CoV-2 can provide early detection and reveal transmission patterns, such as the introduction of cases from other states into Georgia.
Validation and Comparison of Bioinformatic Workflows for Routine Genomic Surveillance of Group A Streptococcus in a Public Health Laboratory (GPHL poster)
Tatyana Kiryutina, Arunachalam Ramaiah, Mahalet Bekele, Indira Sawh, Steven Woods, Tonia Parrott, Nandhakumar Balakrishnan
Group A Streptococcal (GAS) infections are caused by Streptococcus pyogenes and are considered a serious public health threat. While Whole-Genome Sequencing (WGS) has been performed in public health laboratories for diagnosis and routine genomic surveillance, there is limited data on bioinformatics pipelines validation for GAS. GPHL aimed to compare three bioinformatics pipelines: FLAQ (Southeast Bioinformatics Regional Resources), PHoeNIx (CDC), and Bactopia (Emory, PGCOE partner), for GAS Multi-locus Sequence Typing (MLST), and genomic characterization to determine their suitability for high-quality results. While a few in-house custom scripts were used to obtain outputs in the desired format, PHoeNIx was facile, automatic, comprehensive, and performed precise quality checks compared to FLAQ and Bactopia. Considering the limitations and advantages of these pipelines, we are evaluating these pipelines on other bacterial species to identify the most suitable bioinformatics pipeline for routine use in public health laboratories for genomic surveillance.
Genomic Analysis of the New Delhi metallo-β-lactamase (blaNDM) Producing Carbapenem-Resistant Enterobacterales Informs the Clonal Transmission of Emerging Lineages in Georgia
Arunachalam Ramaiah, Tatyana Kiryutina, Gebre Tiga, Kaelyn Dugger, Addisalem H Bedada, Steven Woods, Eleen Daley, Tonia Parrott, Nandhakumar Balakrishnan
New Delhi metallo-β-lactamase (blaNDM)-producing carbapenem resistance Enterobacterales (CRE) are more commonly associated with travel, however there is increasing incidence of NDM across healthcare settings in State of Georgia. As part of the Antimicrobial Resistance Laboratory Network (ARLN), antimicrobial surveillance and outbreak investigations are being performed in Georgia to detect the emergence and spread of organisms harboring plasmid and chromosomal genes conferring carbapenem resistance mechanisms. Due to the increase in epidemiologically linked NDM-producing CRE in Georgia, we characterized the genomic diversity of CRE isolates containing the blaNDM gene by whole genome sequencing (WGS). Based on blaNDM genomic characterization, 3 variants were documented including blaNDM-1, blaNDM-5, and blaNDM-7. Most within-species clusters of closely related genomes are predominated by one MLST sequence type. These clusters could be of potential interest for assisting outbreak investigation and understanding clonal dissemination within the facilities.
First report on the emergence of carbapenem resistant Pseudocitrobacter frankii sp. nov., harboring blaNDM-7 in Georgia
Arunachalam Ramaiah, Tatyana Kiryutina, Indira Swah, Gebre Tiga, Addisalem H Bedada, Maranibia Oelemann, Steven Woods, Michael Anderson, JoAnna Wagner, Tonia Parrott, Nandhakumar Balakrishnan
NDM-producing Carbapenem-resistant Enterobacterales (CRE) are more commonly associated with travel, however there is increasing incidence of NDM across healthcare settings in the State of Georgia. In this study, gram-negative, motile, oxidase-negative, catalase-positive, blaNDM-7-positive bacterial strain 2023LY77 was isolated from urine culture of 84-year-old male patient. The strain was characterized by phenotypic, genotypic and WGS methods. MALDI-TOF results included a wide variety of species, within Enterobacterales family. The 16S rRNA and WGS based ANI, in silico-DNA-DNA hybridization (isDDH), phylogenetic and pairwise comparison of this genome with closest type-strain genomes showed that this strain was distinct from other species within the genus Pseudocitrobacter. Based on the distinct differences from their closest species within the genus Pseudocitrobacter, we propose a new name for strain 2023LY77 as “Pseudocitrobacter frankii sp. nov.”