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Next Generation Metagenomic Sequencing

Sophie Jabban
Onegevity Science Team

The human microbiome defines a complex ecosystem of microorganisms co-inhabiting the surfaces of our bodies. Recent developments in microbiology and human health have demonstrated that the microbiome plays an instrumental role in the wellness of its host, from maintaining vaginal pH to protecting infants from developing allergies. 

Most strikingly, many scientific discoveries place an even greater emphasis on the role of the gut microbiome—the network of flora that reside within your intestines—during digestion, body composition, and even mental health. As a result of recent findings, the demand for tools to accurately screen for the particular species that occupy your digestive tract has risen exponentially. 

Understanding the activity of your gut’s unique microbiome, and more importantly, knowing which organisms are contributing to its dysregulation, is critical to evaluating and treating gastrointestinal diseases such as IBS, IBD, and Crohn’s.1  

Scientific understanding of microbiome dysbiosis, i.e., the failed symbiosis between microbes and their host that ultimately yields intestinal health problems, is hardly contemporary news. For several years, engineers and entrepreneurs in the startup space have been working to put existing technologies to use to identify the species that populate their customers’ gut microbiome. While many of these companies already exist, the “16s amplicon sequencing” technology they use for identification differs considerably from Onegevity’s metagenomic, “whole-genome shotgun” (WGS) approach.  

In order to distinguish as many specific species that comprise an individual’s microbiome as possible, metagenomics sequencing is in order. From a fecal sample, scientists can extract the microorganisms that originated from your gut and ultimately isolate the microbes’ DNA itself.This “metagenomic” sample—the pooled DNA of all microorganisms living in the gut—can then be placed into a next-generation sequencer.2

The sequencer, through complex biochemistry, reads the sample’s genetic code comprised of A’s, C’s, T’s, and G’s, and outputs these raw reads onto a computer. Because all organisms have a slightly different genetic code, the reads can be mapped to the unique sequence of the corresponding organism computationally. Both the classic methods of other direct-to-consumer gut microbiome tests and Onegevity’s Gutbio test analyses require biochemical sequencing and computational analysis; however, the 16s approach is outdated and less accurate than WGS.2

A quick reminder: Biology 101

If you recall from your last biology course, whenever that may have been, all life diverged into three domains at one point in history: eukarya, bacteria, and archaea (with further subdivisions in each). As humans, we are a part of the domain eukarya; we have membrane-bound organelles, our DNA hides in the nucleus; we are complex, multicellular organisms. Bacteria, archaea, and most other microbes that inhabit our digestive tract are prokaryotic cells, and while they lack most organelles and have free-floating DNA, one critical particle we all share is the ribosome. And yet, these ribosomes differ in size. 

What is 16s sequencing?

It is by targeting the so-called “16s” subunit in prokaryotic cells, specifically the ribosomal gene that codes it, that we selectively decode the sequence of our microbial inhabitants while excluding all “15s” genes belonging to ourselves (eukaryotic cells). Exactly how this works is slightly more complex. 

Before decoding, the 16s rRNA (ribosomal RNA) gene must be flanked by primers that recognize highly conserved regions of the gene and then repetitively re-copied through a process called PCR (polymerase chain reaction).These primers are about 10 to 15 nucleotide long sequences that are complementary to the ends of the rRNA gene; they are exceptionally important in selectively attaching themselves to microbial genes, attaching themselves to 16s, and avoiding our eukaryotic 15s sequence.2

These selectively identified samples then undergo PCR, wherein they are repeatedly copied in order to increase the amount of DNA available for the sequencing machine to read. Once the amplified DNA is inserted into a next-generation sequencer, the raw reads must be compared to the specific 16s rRNA sequences of every known microbe provided by a database. Finally, matches between DNA samples and microorganisms are made.2

16s sequencing limitations

One major limitation of 16s amplicon sequencing is that it only accurately reflects organisms at the phyla or even genera level—the exact species is hardly ever determined, nevermind the strain (a couple of levels beyond species).2Accurate identification of species is much more difficult with this technology because scientists can only align one specific rRNA gene to a reference.2

Another result of the computational mapping associated with 16s technology is those specific genes are not directly observed-- but hypothesized-- based on the associated rRNA sequence; however, many bacteria undergo a process of horizontal gene transfer by which they can actually pass on a useful gene to a nearby species. Horizontal gene transfers are unrecognizable through the standard estimation procedures of 16s, and thus impactful genes that help harmful bacteria rest in your gut may be that much harder to identify.2

While 16s is still very useful in microbiome mapping, new technology is catching up in terms of economic feasibility and algorithmic ingenuity, and Onegevity has found a way to deliver it to users. 

This technology is called the whole-genome shotgun sequencing, and much like it sounds, the purpose of shotgun metagenomic sequencing is to comprehensively sample all genes in all organisms present in a complex sample.

This platform also uses next-generation sequencing technology; however, the sample preparation is quite different, and the computational analysis far more complex. To prepare samples for sequencing, scientists must shear, or cut, the massive metagenomic sample into 300 to 600 nucleotide fragments.These fragments are then placed into a “DNA library,” a process defined by a series of modifications that makes the DNA fragments compatible with NGS technology. The sequences are immobilized to a glass slide, attached to NGS recognizable adaptors (short DNA sequences), and multiplied.

Once the raw reads of the enormous metagenomic sample are output to the computer, the complex computational analysis begins. Reads get combined based on shared overlap into larger reads called contigs, and these contigs are aligned with one another into scaffolds.When these major assembly pieces are generated, they are sorted into a tentative organism “bin” based on common features shared between the scaffold and a known organism--and voila, the organisms that comprise your gut microbiome, are determined.4

As you can probably tell, Onegevity’s process of whole-genome shotgun metagenomics requires extensive and more complex data analysis techniques than 16s amplicon sequencing.WGS is also a more expensive process that requires far more input of DNA to identify microbiota accurately. 

Onegevity’s machine learning platform facilitates the complicated process of organism mapping, and the near-exponential decline in next-generation sequencing technology prices has finally made the prospect of whole metagenome sequencing possible. The WGS method gives Onegevity more power over competitors-- to identify organisms at the taxa level accurately, better classify and estimate what metabolites might be present in the gut, and ultimately provide users with an informative and affordable method to understand and optimize their gut health. 

  1. Kinross JM, Darzi AW, Nicholson JK. Gut microbiome-host interaction in health and disease. Genome Medicine. 2011;3(14)
  2. Ranjan R, Rani A, Metwally A, McGee HS, Perkins DL. Analysis of the microbiome: Advantages of whole genome shotgun versus 16S amplicon sequencing. Biochem BiophysRes Commun. 2016;469(4):967–977.
  3. Head SR, Komori HK, LaMere SA, et al. Library construction for next-generation sequencing: overviews and challenges. Biotechniques. 2014;56(2):61–passim.
  4. Venter CJ, Remington K, Heidelberg JF. Environmental genome shotgun sequencing of the Sargasso Sea. Science. 2004;304(5667):66-74