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