Metagenomic Next Generation Sequencing: How Does It Work???

Next generation sequencing (NGS) methods started to appear in the literature in the mid-2000s and had a transformative effect on our understanding of microbial genomics and infectious diseases. There is nonetheless considerable controversy on how, when, and where next generation sequencing will play a role in the clinical diagnostic laboratory.

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Metagenomic Sequencing

What is Metagenomic Next Generation Sequencing?

Next generation sequencing is any of several high-throughput sequencing methods whereby billions of nucleic acid fragments can be simultaneously and independently sequenced. Contrast this technique to classical methods such as Sanger sequencing (also known as dideoxynucleotide chain termination sequencing), which processes one nucleotide sequence per reaction.

To characterize a bacterial genome using NGS, for example, the genome is split into multiple fragments that produce sequences or reads ranging from hundreds to tens of thousands of bases in length.  The sequences are assembled into a single genome using computational approaches. Several overlapping sequence reads are pieced together to produce a single longer sequence called a contig. There are often gaps between contigs and although high-fidelity longer sequence reads would be the ideal method of sequencing, platforms that produce shorter reads are generally less costly and the overlap in sequences makes them more accurate.

Metagenomic NGS (mNGS) is simply running all nucleic acids in a sample, which may contain mixed populations of microorganisms, and assigning these to their reference genomes to understand which microbes are present and in what proportions. The ability to sequence and identify nucleic acids from multiple different taxa for metagenomic analysis makes this a powerful new platform that can simultaneously identify genetic material from entirely different kingdoms of organisms.

Metagenomic Next Generation Sequencing?

The largest strength of mNGS is that it is an unbiased hypothesis-free diagnostic method, unlike targeted polymerase chain reaction (PCR) methods that rely on primers for identification of specific targets to be amplified and detected. Even universal or broad-range PCR methods are not sufficiently broad to be considered metagenomic, as they use specific primers of conserved 16S ribosomal RNA (rRNA) gene and internal transcribed spacer (ITS) sequences to amplify distinctive nucleic acid sequences that can be bioinformatically classified into bacteria/archaea, or fungi respectively.

What are the Challenges of Metagenomic Next Generation Sequencing?

Despite the potential of mNGS, there are many barriers to clear before the technology can become part of the mainstream laboratory, as well as gaps in our understanding about its diagnostic utility. Major reservations include the interpretation of findings (distinguishing contamination and colonization from true pathogens), selection and validation of databases used for analyses, and prediction (or lack thereof) of antimicrobial susceptibilities.

The specificity of mNGS remains the proverbial elephant in the room. Contamination of samples during specimen collection is a large concern given the increased analytical sensitivity of mNGS in comparison to standard culture methods, and there needs to be a validated quality-control process in place for steps from assessing reagent purity to measuring adequate genome coverage controls. Furthermore, with some Illumina platforms, the wrong barcode indices can be designated, leading to false positives on sequencing data.

Bioinformatic quality controls are needed to ensure that high quality and validated genomes are available with minimal database errors and there would ideally be bioinformatic personnel available to interpret sequencing results for each test, which is not available at most clinical microbiological laboratories. The Federal Drug Administration (FDA) has collaborated with other federal agencies to curate a database entitled FDA-ARGOS (FDA-database for regulatory-grade microbial sequences), which has been useful to ensure that current mNGS results are reliable and accurate, but these resources need to be updated and maintained.

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