A WGS-based genomics platform for early identification of MRSA transmission in ICU Settings

Methicillin resistant Staphylococcus aureusMRSAposes a significant public threat in hospitalsimpacting patient lives and creating a financial burdenIn recent yearsboth community associatedCAand healthcareassociatedHAMRSA strain types have been seen in various U Shospitalsoften co existing in the same ward or ICU locationcomplicating the efforts of infection prevention and controlWhile Whole Genome SequencingWGShas started to show significant promise for identifying emerging strain clustersSaureus poses unique challenges for genomic epidemiologyDue to the hyper mutation rates of some Saureus cladessamples within an outbreak cluster can differ by as many asSNPsa far higher threshold than other bacterial pathogensAdditionallyisolates from the same colony often display high genomic diversityespecially when the samples are taken from nasal swabsThis genomic diversity within a single colony further complicates the difficulty of identifying emerging clusters as part of routine infection prevention and transmission epidemiologyIn this proposalwe look to develop an automated cloud based bioinformatics platform that is designed to address these unique challenges in analyzing WGS data from MRSA isolatesOur platform will avoid traditional core alignment methodologies to separate genomic clusters and instead use a different methodology to group isolates that share recent phylogenyIn a preliminary evaluationwe performed a manual analysis of this new approach by using raw sequence data from a recent MRSA study at an ICU settingBesides correctly separating strain clusters from the surrounding isolatesour platform was able to additionally isolate critical biomarkers that core alignment methodologies are not designed forOur cloud based MRSA genomics framework will be implemented in Amazon Web ServicesAWScloudFollowing implementationevaluation will be carried out using both public NCBI data and MRSA sequence data from a single hospitalOur Phasebenchmark will be to complete all WGS analyses forisolates within one hourOur Phaseaims areDevelop a WGS based screening module that accurately identifies MRSA clonal complexesDevelop a WGS based clonal module that further separates clonal MRSA isolates into distinct lineages and underlying clustersEvaluate both screening and clonal modules by sequencingbanked samples of CA MRSA and HA MRSA isolates from a single U Shospital Methicillin resistant Staphylococcus aureusMRSAinfections cause high mortality in ICU settingsWhile Whole Genome SequencingWGSoffers significant promise for tracking endemic hospital lineagesMRSA poses unique challenges for genomic epidemiology due to sample diversity from nasal swabs and high mutation rates of some cladesIn this proposala different approach is outlined that addresses these unique challengesOur cloud based platform can be deployed by any large hospital to routinely track circulating MRSA lineages and implement targeted containment strategieslowering the burden of MRSA