Monday, 15 August 2016 11:32

Microbial Identification and Tracking: the Next Generation

Written by 
Published in mBiosphere

Screen Shot 2016-08-15 at 12.02.47 PM

How do you identify an unknown microbe? If you’ve taken an introductory microbiology lab course in the past twenty years, chances are you were assigned an unknown bacterium that you had to identify through differential media and biochemical assays. Newer techniques like qPCR are being standardized to identify human-associated fecal bacteria for water safety surveillance. But in the wake of the next-generation sequencing revolution, there is no substitute for whole-genome sequencing as a method to pinpoint the exact strain of an unknown microbial species. As NGS technology has advanced, sequencing costs have decreased and applications of the technology have broadened.

Clinical applications are no exception, and a series of review articles in the Journal of Clinical Microbiology highlights how public health will benefit from these new applications. The articles are introduced in a Commentary by Marc Allard, who summarizes the four reviews and remarks on WGS potential. A few themes repeat throughout the reports, despite their unique applications:

Sequence Typing versus Whole-Genome Sequencing

Martin Maiden and Odile Harrison highlight the use of next-generation sequencing for Neisseria WGS analyses. Databases that store entire genomic sequences make it easy to identify loci for use in whole-genome MLST (wg-MLST). Genetic sequences such as the bacterial ribosome protein subunits (rps genes) can be used for more detailed microbial taxonomy, in which an unknown sequence is compared to a database of known sequences from more than 130,000 sequenced bacterial genomes.

Because the same genes and gene fragments have been used to study N. meningitides as N. gonorrhoeae populations, evolutionary comparisons can be made between these two species. As new Neisseria isolate genomes are generated and deposited, scientists’ knowledge of the evolution of this genus grows. This same application will be useful for understanding many clinically relevant species’ evolution as data scientists analyze an increasing number of sequenced genomes.

Our understanding of bacterial and archaeal evolution may shift entirely if we start using whole-genome sequences in place of 16S rRNA gene sequences to study relatedness between isolates, as George Garrity writes. WGS won’t completely displace 16S gene sequencing taxonomy immediately, since species, subspecies, and strain-level relationships aren’t clearly defined for many organisms. WGS will however increase our growing understanding of these definitions and help define clearer algorithms to automate sequence relationship analysis.

Assessing Phenotype from Genotype

No matter the sequencing methodology or extent, nucleotide sequence alone will not supplant the need for experimental data to associate ecological and phenotypic data to the accumulated genetic information, Garrity writes. This holds true regardless of sequencing purpose: factors such as expression level, mRNA or protein turnover, and cofactor presence are necessary to know how a given DNA sequence affects the biology of an organism.

That doesn’t mean we can’t identify virulence- or resistance-related traits from WGS data. In some cases, the presence of a gene transferred as a mobile genetic element clearly differentiates the course of disease, as is the case with Escherichia coli ST131. Sequence analysis alone can differentiate this extremely pathogenic strain based on virulence factor and other genetic information. Detections of virulence determinants can help identify potential outbreaks before they become widespread, as Allard et al write in a review on food pathogen surveillance.

Similarly, WGS can be a first line of antibiotic susceptibility. Antibiotic resistance profiles will still be necessary for individual isolates, as efflux pump expression can increase to mediate drug removal from intracellular targets. However, a patient with a Gram-negative isolate identified using WGS with genomic sequence containing blandm-1, blaVIM, or other beta-lactamase genes is not a good candidate for carbapenem therapy, narrowing the field of potential therapeutics before the antibiogram is analyzed.

Databases Facilitate Analysis

In their review, Maiden and Harrison make use of the Bacterial Isolate Genome Sequence database (BIGSdb), which is a database storage location for bacterial isolates. This database links the bacterial phenotype, origin, and sequences that facilitates wgMSLT. Another important database, GenomeTrakr is considered in a review on food pathogen tracking by a Food and Drug Administration scientific team.

GenomeTrakr seeks to create a centralized, globally accessible database for pathogen genome collection. The GenomeTrakr network has currently sequenced over 50,000 genomes deposited, and is sequencing over 1,000 isolates monthly. The larger the collection, the easier it will be to find a match when an outbreak occurs, and the number of state health departments and international collaborators is quickly growing.

Databases of microbial genomes will further aid in pinpointing the source of an outbreak for forensic purposes, as summarized by Sarah Schmedes, Antti Sajantila, and Bruce Budowle. Use of NGS or WGS in court testimony requires standardization of the protocol and accepted analyses in the broader scientific community, however.

Another of the infrastructural areas that NGS users hope to improve as the technology advances is maintenance and interactivity of these large datasets. Abundant data can be mined for additional information, such as virulence- or resistance-related genes, but this requires a uniform database into which researchers are depositing their sequences. This available information can then be analyzed in aggregate to investigate clustering or outbreak-related sequences.

Next-generation sequencing coalition

ASMNGS_FB

The four minireviews make it clear that NGS technical applications within microbiology are quickly multiplying. To address the future of NGS, ASM has established a new, multistakeholder mechanism to move the science of NGS forward. The NGS Coalition will bring together 23 experts representing government agencies, private industry, and academia and will be convened by the American Academy of Microbiology and ASM Strategic Alliances.The meeting will take place on September 9-10th, with discussion of identifying needs and opportunities associated with NGS across various scientific disciplines, including the clinical, biomedical, forensic, environmental, and agricultural sciences.

Before the Coalition meeting, we would like your input! If you’ve worked with NGS at any point in your career, you may have encountered obstacles (data analysis, storage, lack of training) you wish you could fix. ASM is currently hosting a Twitter poll to collect input on some of these points that should be addressed. If you are a Twitter user, please go to @ASMicrobiology and address the polls listed there. If you aren’t on Twitter, you can find the same questions in this online survey. And if you wish to engage in a broader question set, please contact academy[at]asmusa.org to receive an email correspondence.

Photo credits: Mixed microbial population

Julie Wolf

ASM Communications Social Media Specialist Julie Wolf spent her research career focused on medical mycology and infectious disease. Broadly interested in microbiology and scientific communication, she has taught at Long Island University and the community biolab Genspace and has written for the Scientista Foundation and Scholastic’s Science World magazine. Follow her on Twitter for more ASM and Microbiology highlights at @JulieMarieWolf.

TPL_asm2013_ADDITIONAL_INFORMATION

TPL_asm2013_SEARCH

454:microbial-identification-and-tracking-the-next-generation