- Grad student competition tests the ability to succinctly convey research
- One finalist offers a better way to analyze the microbiome
- Open source metatranscriptome program offers hi-res species-specific analysis
The University of California Grad Slam is an annual contest in which master’s and Ph.D. students sum up their research for a general audience.
Sam Westreich, one of ten finalists to compete on May 4, shares his three-minute explanation of the microbiome and metatranscriptomics.
We have more than five trillion stowaways hiding inside our bodies.
This is the gut microbiome, the collection of more than a thousand species of bacteria living inside the human intestinal tract.
In the last couple of decades scientists have come to understand that a balanced and stable gut microbiome does more than just contribute to intestinal regularity. It also plays a vital role in nutrient absorption and keeps our immune system in fit and fighting shape.
Disruption of this complex environment is correlated with obesity, with the development of allergies in young children, and even with life-threatening auto-immune diseases. Worst of all, as many as one in three adults will suffer from a gut microbiome-linked disruption at some point during their lives.
To study this important environment, most researchers today rely on an older approach, called 16S rRNA sequencing – which we can imagine as ‘barcoding.’ This approach looks at the sequence of a single ‘barcode' gene in bacteria to give us a broad overview of which groups are present in an environment.
16S, however, is low resolution. In an environment where species-specific differences can cause huge impacts, 16S is often unable to identify organisms below the family level.
Relying on 16S to look at the gut microbiome is like trying to navigate the streets of an unfamiliar city – with only a single, blurry, satellite photograph as a guide.
Today, researchers are working on creating a better method – called metatranscriptomics.
Metatranscriptomics is the epitome of big data – this is the sequencing of not just that single barcode gene, but of all the active genetic material, or RNA, from all the microbes within the gut.
The resulting dataset is immense, far more than one person could ever analyze, so researchers use a series of programs on supercomputers, called a bioinformatics pipeline, to extract insights from the noise.
Metatranscriptomics is much more computationally intensive than 16S, and its costs are higher. But metatranscriptomics can identify the microbes within the gut to the species, or even the strain, level with much better resolution than with 16S.
And if that weren't already enough, metatranscriptomics doesn’t just reveal which microbes are present — it's the only method that identifies the functions currently being performed by those bacteria.
Metatranscriptomics is like driving through the streets of a new city, but with both crystal-clear maps and turn-by-turn GPS directions.
To handle complex metatranscriptome data, beginning to end, there’s SAMSA, a bioinformatics pipeline designed for researchers who may lack programming experience.
SAMSA has been used to identify causes of chronic diarrhea in Rhesus macaque monkeys, a microbiome-linked bowel disease that may have important implications for human irritable bowel syndrome (IBS).
SAMSA has also helped scientists understand the effects of prebiotic supplementation on the human gut, determining the true impact of some of the supplements for sale in grocery store aisles.
All SAMSA code is open source, and the databases and tools used by the pipeline are freely accessible. Other researchers who use this SAMSA pipeline can see exactly what code is implemented and can customize and alter the flow of data as they choose.
Metatranscriptomics is still a new and developing field, and approaches and techniques are still being developed and refined to handle the massive amounts of necessary data.
But by creating open-source pipelines like SAMSA, other researchers will move away from older 16S-based approaches and use metatranscriptomics to gain a deeper, more complete understanding of how the trillions of stowaways affect our human journey.
