There are many different ways to approach the study of the microbiota: from descriptional studies to functional studies, from examining whole microbial communities to examining a handful of bacterial species. Each of these approaches requires different forms of data and different computational methods to analyse this data. Therefore, before starting any microbiota study we must ask the following questions:
-	What form of data is most appropriate?
-	What questions can we ask of this data, and what computational methods are needed to answer these questions?
-	What are the challenges/biases associated with this form of data and these computational methods?

Marker gene sequencing, such as sequencing the 16S rRNA gene, is still the most widely used form of data in microbiota studies. This form of data is valuable as it provides us with a relatively inexpensive way of analysing the taxonomic composition of microbial communities. However, it is only able to provide limited functional information. A greater understanding of microbiota function can be acquired using shotgun metagenomic data, by analysing the genes present and by the construction of metagenome assembled genomes. However, this form of data only allows us to see the functional potential of the microbiota, as we are unable to assess if these gene are being transcribed in vivo. To assess in vivo function, we can produce various other “omic” datasets, including transcriptomics, proteomics and metabolomics.  

Once we have produced a high-quality dataset, we can use it to answer a diverse array of questions. A seemingly simple question such as “Does my treatment affect the composition of the microbiota?” can be approached in many different ways, most commonly by performing alpha and beta diversity analyses. Once we understand which components of the microbiota are associated with a particular group, we can then use methods such as machine learning to predict which group samples belong to. We can also perform network analyses to understand how different components of the microbiota are related to one another, and even discover clustering of samples via unknown factors.

However it is important to emphasise that with all of these analyses come various challenges. If the data quality is poor, or there is a lack of metadata, then no computational methods will be able to completely solve this. Microbiota data is also frequently very complex and we must think very carefully about the computational and statistical methods we use to analyse it. In conclusion, we have many options when it comes to using computational methods to analyse the microbiota. However, we need to be very careful about which methods we choose, to ensure that they are appropriate to the data we have produced and the biological questions we want to answer.

Plenary one: Computational methods to study microbial populations

The gastrointestinal tract is amongst the most densely populated ecosystems on earth, home to an abundant and diverse collection of microbial species, not just bacteria but also Archaea, viruses, fungi etc. Significant interest in this area has been sparked in recent years by an appreciation of the importance of the gut microbiota in the health of the host, and this has led to the microbiome of humans and animals being investigated in depth. Studies have drawn links between host nutrition, the gut microbiota and metabolic and immune functions, which in consequence affect physiology.



The first investigations of the structure of the microbiota were culture-based, however the introduction of sequencing technologies such as Sanger sequencing and subsequent development of 454 sequencing and metagenomics approaches have become the mainstay of microbiota studies. The creation of reference databases and analysis software has provided invaluable tools for assigning taxonomy to generated data. Great progress in characterising the structure of the microbiome recently has paved the way for ongoing and future studies on the functional interactions between the microbiota and the host. Studies on the function of the microbiota are critical in understanding the role of the microbiota in human homeostasis and disease pathogenesis.



The conference will be presenting the latest advancements in gut microbiome and health research. It will bring together experts who are driving technological advancements and striving to understand how nutrition impacts gut microbiome and the interactions between gut microbiome and health.



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Recordings of the conference will be available until 13 April 2021.