Lab Matters Spring 2018 | Page 31

infectious diseases

by Ryan Jepson , M ( ASCP ), microbiology supervisor , State Hygienic Laboratory at the University of Iowa and Christin Hanigan , PhD , senior specialist , Advanced Molecular Detection

MicrobeNet is an online database that enables public health laboratories ( PHLs ) to more efficiently identify rare or complex pathogens by comparing their results against a large database derived from the US Centers for Disease Control and Prevention ’ s ( CDC ’ s ) collection of rare organisms . Its purpose is to curate and characterize rare and unusual pathogens by cataloging information such as sequence , morphological characterization , antibiotic resistance profiles and biochemical information .

MicrobeNet ’ s user friendly interface and reporting language have proven easy to incorporate into existing procedures and workflows . Because all data from sequencing is stored locally , it was easy to pull large numbers of representative bacterial and mycobacterial sequence data for MicrobeNet validation .

In fall 2017 , APHL surveyed PHLs on their use of MicrobeNet . Though some have not yet incorporated the reference database into their routine workflow , PHLs are overall optimistic about its potential .

MicrobeNet in Iowa : Saving Money , Improving Detection

The State Hygienic Laboratory at the University of Iowa ( SHL ) has used MicrobeNet for approximately two years . Over that time , it has saved about $ 10,000 previously spent on an annual subscription to a commercial sequencing database . Moreover , SHL finds that the database ’ s extensive library has more than replaced the commercial software , providing more user-friendly reports and incorporating biochemical with sequencing data .

To prepare to transition to MicrobeNet , SHL sent a laboratorian to 16S rRNA Sequence Based Bacterial Training at CDC . It subsequently created multiple MicrobeNet user accounts and validated the MicrobeNet database using data generated from previously sequenced bacteria . Within six months , SHL had switched to MicrobeNet .

A typical workflow relies on Gramstain and MALDI-TOF analysis for isolates submitted to the laboratory . Any isolates that cannot be identified using MALDI-TOF are batched for 16s rRNA sequencing . After the once-a-week run is completed , results of bacteria or mycobacteria are analyzed using

Clinical lab technical specialist Jennifer Elwood uses MicrobeNet for bacterial identification at the State Hygienic Laboratory at the University of Iowa . Photo : SHL

MicrobeNet . Since its inception , Iowa has used MicrobeNet to identify over 500 bacterial and mycobacteria isolates . The transition to MicrobeNet has been seamless .

MicrobeNet ’ s user friendly interface and reporting language have proven easy to incorporate into existing procedures and workflows . Because all data from sequencing is stored locally , it was easy to pull large numbers of representative bacterial and mycobacterial sequence data for MicrobeNet validation .

Technologists at SHL report an increase in the number of successfully identified atypical bacteria that previously were not identified using National Center for Biotechnology Information and commercial databases . Jennfier Elwood , SHL clinical lab technical specialist , noted an increase in the identification of acid fast bacillus and miscellaneous gramnegative rods , which has allowed SHL to identify greater than 95 % of clinical bacterial isolates submitted .

The MicrobeNet of the Future

SHL plans to validate MicrobeNet for sequencing identification of molds and MALDI-TOF protein spectra . MicrobeNet , in the view of SHL scientists , could be the ideal repository for all pathogen characterization and identification , including both environmental and clinical pathogens . SHL will be following its progress as MicrobeNet expands its vast database to provide more complete data , including MALDI-TOF spectra and whole genome sequences . n