Bioinformatics – understanding biological data

At the most basic level, we need to establish which microbes are present in a given sample, which features they have, and establish whether or not these features have an effect on your patient, or study hypothesis.

To do this, we measure sequences of microbes. We know that these microbes have a number of recognisable features, or traits. What we then want to establish, is whether or not these features are important or not, given the question or hypothesis we have been asked to investigate.


There are three levels of analysis, and we look at the sample from various perspectives.

  1. Ecology: first we look at the composition of the sample microbe community and establish how diverse it is.
  2. Species: then we go more into the species of the various bacteria, and look at those specifically — which species are present and which are not. We then look at their corresponding traits.
  3. Correlation: this phase relates to your study setup and data needs and is a tailor-made process.


Leading edge science

At MiCA we have a wet lab where samples are checked, logged and processed. The dna is extracted and converted into computational data.

The first phase of analysis is to “de-noise” the raw sequence data. This means reducing a very large amount of information into a small, useful data set.

The methods used for this process are very new and part of a developing field. Currently Microbiota Center Amsterdam uses a method developed in 2017. This is constantly being improved and developed. MiCA is more advanced in this field than most commercial “sample shops”.


From OTUs to ASVs

Once the sample has been de-noised, we can establish the molecular operational taxonomy units (OTUs). These are the abundance profiles of all bacteria, so we know what is there, and how abundant they are and how they are related. This is the basic level of sample output data.

Within the testing community at MiCA, the OTU method is gradually being phased out and replaced by new, more accurate, ASV method. New methods control errors enough so that amplicon sequence varients (ASVs) can be accurately resolved down to the level of single-nucleotide differences within a sequenced gene region. ASVs provide a finer resolution and may, in time, supercede the use of OTUs in this process.


Deeper Analysis

From this point on we begin the deeper analysis, and start answering specific questions regarding the sample. This goes from basic analysis (such as alpha diversity and beta diversity) at this stage we can also look into differential requirements to establish, for example, if specific microbes (marker bacteria) correlate with the sample data.


More advanced

If required, we can look even deeper to see if there is any other metadata to which this data could be correlated such as patient data, blood samples, diet and BMI. These are not standard procedures, and involves more collaboration with our clients and their hypotheses. This is a very interactive part of the process and results in tailor-made output, resulting from several conversations.


Today and Tomorrow

Looking into the future, as Microbiota Center Amsterdam collects more and more data, we will be able to relate your data set to a wider context, and relate the data and metadata of your samples to other studies in this and similar areas.


Read more about sample analysis