17 - Human Microbes for Life Flashcards
Holobiont
An assemblage of a host and the many other species living in or around it, which together form a discrete ecological unit
Microbiota
The micro-organisms present in a specific site (e.g. gut microbiota)
Microbiome
- Microbial community that occupies a well defined habitat
- Includes the collective genome contained within the microbiota
- Microbiota + ‘theatre of activity’
Theatre of activity
- Microbial structural elements (e.g. proteins, lipids, nucleic acids)
- Internal/external structural elements (e.g. environmental conditions, microbial metabolites)
Probiotic
Live microorganisms that, when administered in adequate amounts, confer health benefit on host
Prebiotic
A substrate that is selectively utilised by host microorganisms conferring a health benefit
Reconstituting germ-free mice with the microbial communities associated with a human disease state
Could transfer the phenotype to the animals
Paradigm shifts of microbiome research
- Disease caused by unsocial organisms acting alone
- Instead, microbes interact to build up stable network structures which interact with the host and environment (extension of one health concept)
How do we measure the microbiota and its function
Through:
- DNA (gene amplicon and shotgun metagenomics)
- RNA (metatranscriptomics)
- Protein (metaproteomics)
- Metabolites (metabolomics)
- Culture
Two key sequence-based methods for measuring the microbiota
- 16S rRNA gene sequencing
- Whole metagenome sequencing
Whole metagenome shotgun sequencing
- Extract total nucleic acid and fragment into unordered sequence segments
- Massively parallel sequencing of fragments and assembly of sequence segments
16S rRNA gene sequencing
- PCR primers directed against conserved regions of the 16S gene are used to amplify variable regions
- NGS parallel sequencing of all of these variable regions gives us a readout of all the different sequence variants, and their relative abundance
Structure of 16S rRNA gene
- Different bacterial taxa have different sequences in variable regions
- Variable regions are sequenced and taxonomy assigned based on sequences
- Shorter sequences are less discriminatory (genus only) than full length sequencing (species level assignment
Summary of the 16S rRNA gene amplicon sequencing method
- Collection of skin microbes
- DNA isolation from sample
- PCR amplification of bacterial 16S rRNA gene
- High throughput sequencing of amplified 16S rRNA genes
- Data processing, quality control and analysis using bioinformatic tools
- Provides relative abundance not absolute due to amplification
Early approaches for taxonomic assignment
- First cluster similar sequences into OTUs (operational taxonomic units)
- Then chose a ‘representative’ sequence for that OTU and assigned taxonomy to OTU
Newer approaches for taxonomic assignment
- Omit the clustering step and call each sequence variant an “ASV” (amplicon sequence variant)
- Each ASV is assigned a taxonomic classification
- Because there is no clustering with the ASV approach we end up with many more ASVs than OTUs.
ASV vs OTU
- With the OTU approach, only the representative sequences for each cluster are distinguished and given a name
- With the ASV approach, each of these sequence variants would be distinguished and given a name
Advantages of Amplicon (16S/18S)
- Quick analysis
- Low biomass requirement
- Applicable to samples contaminated by host DNA
Disadvantages of Amplicon (16S/18S)
- PCR and primer biases
- Limited to genus level
- False positive in low biomass samples
Advantages of metagenome
- Species or strain level
- Functional potential
- Uncultured microbial genome
Disadvantages of metagenome
- Expensive
- Time consuming analysis
- Host derived contamination
Approaches to the analysis of microbiome data
- Visualizing composition
- Diversity measures
- Differential abundance testing
- Prediction testing (machine learning)
- Network analysis
Two methods of visualising composition using taxonomic composition
- Composition bar plots
- Violin plots
Taxonomic composition
- Describes the microbiota that are present in a microbial community, often visualized using a stacked bar plot
- Microbiota is often shown at the phylum or genus level in the plot.
Biodiversity
- Variety within and among life forms in a sample, ecosystem, or landscape
- Measured using two components (richness and evennes)
Richness
- Number of groups of genetically or functionally related individuals
- e.g. Number of bacterial genera or species in a sample (OTUs or ASVs)
Evenness
- Proportions of each of the different species or strains present within a sample
- If species are present in similar proportions, the sample has high evenness.
- If a few species dominate the sample, it has low evenness.
Alpha diversity
- Measure of the mean diversity within a sample (e.g. Shannon or Simpson index)
- Sample with high alpha diversity will have high richness and evenness
Beta diversity
- Measure of diversity between samples (e.g. Bray Curtis, Unifrac distance measures)
- If samples share many of the same species and those species are present in similar proportions across the samples, beta diversity will be low
Visualising beta diversity
- Hierarchical clustering
- Principal component analysis (PCA)
Differential abundance analysis
- Used to identify taxa (such as species or genus) with significantly different abundances between groups
- e.g. T test, U test
- Prone to false positives
