How we study the Microbiome Pt 2
This is the study of biological molecules.
Omic techniques allow us to look at:
Who is in an environment?
What are they doing?
1. Genomics: the study of DNA
This identifies microbes and their genes. For instance, in the colon we will see:
- Human cells
- Food particles
- Viruses: these infect human cells (such as the Ebola virus) or infect bacteria (bacteriophage)
Bacterial cells contain a variety of molecules. We can DNA sequence, identify the bacteria and look at the genes.
- Can target all DNA molecules (shotgun approach) to find out which genes are functional on the gut community
- Can target specific gene i.e. 16S rRNA to see what type
- Can isolate bacterial cells and study genome
Sequencing DNA tells us:
Who is present
What type of genes they have
2. Transcriptomics: the study of RNA
This identifies which genes are being used.
DNA is similar to RNA except for one nucleotide. RNA has Uracil instead of Thymine therefore it is more flexible. DNA is like the desktop holding all files, whereas RNA is like the USB transporting files.
Only some of the DNA is copied in to the messenger RNA.
3. Proteomics identifies which proteins are being made.
Proteins are the workhorses of the cell. They are large molecules that perform many functions, moving other molecules, signalling other cells and initiating chemical reactions.
By identifying proteins of bacteria, we can see what they are doing in the gut. The human gut microbiome has a core of about 1000 proteins i.e. Glutamate Dehydrogenase which affects the metabolism.
Proteomics allows us to go beyond composition and to function. It looks at the impact that microbes have on the body i.e. Chron’s disease – lack of Faecalibacterium which produce short chain fatty acids that are beneficial for the colon.
4. Metabolomics identifies the metabolites/end products in cells. These include things such as hormones, signalling molecules and lipids. An understanding of the molecules produced by microbes is critical. For instance, microbes:
- Process our foods
- Give us vitamins
- Impact neuro-behaviour
By mapping the microbial community we can match it to molecules produced in regions of the body. Therefore we can tell if microbes are responsible for the presence of molecules i.e. in the case of cystic fibrosis (diminished lung function). This 3-d mapping of molecules and microbes allows us to see biochemical pathways and special pathways. We still do not fully understand the biochemical pathways. We call the transcription of a community of organisms Metatranscriptomics.
One of the main challenges is that we have so much data that needs to be knitted together
How do we identify a microbe?
Microbes that we look at and grow may seem the same but are very different i.e. two types of E-Coli may only share 40% of genes. As a comparison, we share 98% of our genes with chimpanzees and 90% with mice.
Taxonomy is the study of where organisms appear on the tree of life/evolutionary history.
The 16S rRNA gene is so essential to the cell and therefore is an excellent marker for taxonomy. Or we can identify microbes by looking at their function.
Taxonomy is like an address: when we analyse a faecal sample we obtain short DNA sequences that act like postcodes, so that we can place them on the tree of life.
Taxonomy has many levels like an address which go from broad to specific:
Some of the above may have the same name.
There are basically 3 domains of life to classify: Bacteria, Archaea, and Eukaryotes
When we describe bacterial communities we often group them by Phylum wide for instance fish and dogs. This gives us an initial overview. We usually name bacteria according to their Genus or Species. We often group organisms into their Operational Taxonomic Unit (OUT). We do this as sometimes it is difficult to know when bacteria should be considered different genus, species or family. We use DNA sequence similarity to help us standardise our groupings.
OTUs are defined by looking at how similar 16S sequences are to each other because 16S is so highly conserved. Two organisms that are closely related will have highly similar 16S sequences.
We can look at common ancestors and then group them together. We look for a percentage match in the DNA of around 97% similarity.
All of this sequenced data is then placed on the tree of life.
This is the genetic analysis of the individual level of variation across the genome, using genetic information from entire populations of microbes to learn about individual microbes.
Differential Coverage Binning looks at sets of related metagenomes (timed/spacial) which have the same populations but differ in relative abundance. This is used as a signature to obtain a coverage pattern.
We can make genome trees which are more robust than 16S trees.
In 2-3 years from now the dominant form will be population genomes. Every study of every habitat gives us these so we can classify lifeforms
We can now do an ecological analysis much more robustly.
Population genomics can pull out major players in an ecosystem and find out which organisms perform which functions
Phylogeny is the natural grouping of organisms and we want to organise microbes along these lines. There are numerous instance where taxonomy does not match phylogeny.
Because so much diversity is not represented by cultured organisms we need to classify these parts of the tree.
Alpha-diversity: how many organisms in a sample and how abundant they are. This includes:
Richness: how many different organisms there are.
Evenness: how similar abundances of different organisms are. Shannon and Simpson Indices takes this into account.
Faith’s Phylogenetic Distance: a community is more diverse if the organisms are less closely related i.e. same richness and evenness into account.
Biodiversity: diverse species means more functions and more adaptability.
Sampling more leads to better results but only up to a point, therefore it is a waste of time to over-sample.
If it is a simple community then there is no need to sample a lot, but if it is a complex community we need to sample frequently (why high-input sequencing is so important).
Two different studies may be samples differently according to the person doing the studying, so we have to make sure that the sample/effort is the same.
Beta-diversity: how different microbes are across body sites/people. Measurement of similarity/dissimilarity between different samples. Amount of change between two different environments.
The higher the beta-diversity the less similar the communities are.
Beta-diversity is low in the mouth and high in the gut
Qualitative: how many kinds of organisms are shared. The more organisms are shared, the lower the beta-diversity.
We also need to consider how many of each organism is in each community. We also need to look at how closely related they are. This is important as species more closely related have more similar roles.