From the human genome to the human microbiome: Toward clinical applications

In 1991 the Human Genome Project—a collaborative effort to map the whole human genome—was established. A 5-year plan was put in place addressing the initial framework for the efforts including reliable testing methods, validated protocols, and milestones along the way. This marked a different path from previous studies of genetics—that is, the study of genes, or rather the identification of a particular gene that may be instrumental in a phenotypic outcome. Much of the work in this field had previously been exploratory in nature, with a growing body of evidence linking certain genetic variations or single nucleotide polymorphisms (SNPs) to disease states.

In mid-2000 it was announced that the Human Genome Project had published their results of the almost completely sequenced human genome. While the results were interesting, the data were a far cry from being applicable. What it did do was spur further interest in developing better technologies that would allow cheaper and faster sequencing to add onto these initial findings.

In the years spanning 2004 to 2014 a multitude of companies were competing to churn out faster and better technologies such as the Roche 454 and the Illumina sequencing systems. The technologies were proving to be advantageous in many ways; for example, iterations of these technologies were serving to advance the microbiological sciences.

Awareness of the Microbiome

While the whole genome studies were mushrooming during this decade, the study of microbes was still largely based on culture dependent techniques and there was very little information or interest in communities of microbes residing in the body. Basic microbiology was built on the identification of single pathogenic microbes that were instrumental in disease states, while the non-pathogenic microbes were believed to lie dormant. However, certain areas of research focused on how microbes might influence host, or vice versa.

It was becoming widely accepted that microbes in the gut had a part to play in localized gut related diseases such as Crohn’s but it was less understood how the commensal bacteria shifted in abundance, and what caused these ideal growth conditions. This curiosity began to blossom, largely due to the advances in technology brought about by the human genome project, that would allow these growing questions (and concerns) to be addressed affordably and quickly. In 2007 the Human Microbiome Project was born.

“The recent emergence of faster and cost-effective sequencing technologies promises to provide an unprecedented amount of information about these microbial communities, which will bolster the development and refinement of analytical tools and strategies.”

– NIAID Director, Anthony S. Fauci

Microbial Snapshots

Once it was established that the microbiome was of interest, and of importance to the host, researchers developed new methods for studying it by taking advantage of the high throughput sequencing technologies that came to market during the genomics boom. First amplicon sequencing methods and later shotgun metagenome methods were the gold standard in microbiome research. But scientists began to acknowledge several factors as information about different ecosystems was being compared; first, that microbiomes were specific to their locations and diverse in nature, making them quite different from one body site to another. This was a paradigm shift as many had not considered this level of diversity in commensal and pathogenic bacteria, but also as compared to receiving the same genetic information from every host cell regardless of its location in the body. Secondly, the microbiomes are ever shifting and, upon collection, must be stabilized in such a way that the ‘snapshot’ is maintained at time zero. This means that factors such as temperature and moisture could quickly change a microbial profile if the sample is not treated with care. This opened the doors to a wide variety of collection devices and stabilization buffers with specific media to help maintain these profiles while being interoperable to laboratory procedures.

Clinical Applications

We already see clinical and diagnostic applications for microbiome findings. Although we are still working towards scientifically validating these applications we seem to be on a similar trajectory as we saw with genomics research in terms of diagnostic applications, publications, and consumer-friendly offerings. Interestingly, a singular ‘omics’ (i.e. proteomics, metabolomics, genomics, microbiomics) is informative on its own, but combining multiple features to define functionality of systems in the body will prove to be more fruitful in the long run. Understanding the complex nature of these systems and how they interact will enable us to see how changes or shifts in one system can have effects in other systems. This multi-omics approach is the basis for personalized medicine and furthermore can apply in other domains such as plants, animals, and environmental ecosystems.

At Microbiome Insights we are working with researchers to elucidate synergistic effect of multiple 'omics' at work. With this approach we are focused on the skin microbiome, the gut-brain axis, pharmacology, and other areas of science that bring together the genome and microbiome for a better understanding of human health.

 

About Microbiome Insights

Microbiome Insights, Inc. is a global leader providing end-to-end microbiome sequencing and comprehensive bioinformatic analysis. The company is headquartered in Vancouver, Canada where samples from around the world are processed in its College of American Pathologist (CAP) accredited laboratory. Working with clients from pharma, biotech, nutrition, cosmetic and agriculture companies as well as with world leading academic and government research institutions, Microbiome Insights has supported over 925 microbiome studies from basic research to commercial R&D and clinical trials. The company's team of expert bioinformaticians and data scientists deliver industry leading insights including biomarker discovery, machine-learning based modelling and customized bioinformatics analysis.