17 - Human Microbes for Life

Question 1

Holobiont

Answer 1

An assemblage of a host and the many other species living in or around it, which together form a discrete ecological unit

Question 2

Microbiota

Answer 2

The micro-organisms present in a specific site (e.g. gut microbiota)

Question 3

Microbiome

Answer 3

• Microbial community that occupies a well defined habitat
• Includes the collective genome contained within the microbiota
• Microbiota + ‘theatre of activity’

Question 4

Theatre of activity

Answer 4

• Microbial structural elements (e.g. proteins, lipids, nucleic acids)
• Internal/external structural elements (e.g. environmental conditions, microbial metabolites)

Question 5

Probiotic

Answer 5

Live microorganisms that, when administered in adequate amounts, confer health benefit on host

Question 6

Prebiotic

Answer 6

A substrate that is selectively utilised by host microorganisms conferring a health benefit

Question 7

Reconstituting germ-free mice with the microbial communities associated with a human disease state

Answer 7

Could transfer the phenotype to the animals

Question 8

Paradigm shifts of microbiome research

Answer 8

• 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)

Question 9

How do we measure the microbiota and its function

Answer 9

Through:
- DNA (gene amplicon and shotgun metagenomics)
- RNA (metatranscriptomics)
- Protein (metaproteomics)
- Metabolites (metabolomics)
- Culture

Question 10

Two key sequence-based methods for measuring the microbiota

Answer 10

• 16S rRNA gene sequencing
• Whole metagenome sequencing

Question 11

Whole metagenome shotgun sequencing

Answer 11

• Extract total nucleic acid and fragment into unordered sequence segments
• Massively parallel sequencing of fragments and assembly of sequence segments

Question 12

16S rRNA gene sequencing

Answer 12

• 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

Question 13

Structure of 16S rRNA gene

Answer 13

• 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

Question 14

Summary of the 16S rRNA gene amplicon sequencing method

Answer 14

• 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

Question 15

Early approaches for taxonomic assignment

Answer 15

• First cluster similar sequences into OTUs (operational taxonomic units)
• Then chose a ‘representative’ sequence for that OTU and assigned taxonomy to OTU

Question 16

Newer approaches for taxonomic assignment

Answer 16

• 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.

Question 17

ASV vs OTU

Answer 17

• 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

Question 18

Advantages of Amplicon (16S/18S)

Answer 18

• Quick analysis
• Low biomass requirement
• Applicable to samples contaminated by host DNA

Question 19

Disadvantages of Amplicon (16S/18S)

Answer 19

• PCR and primer biases
• Limited to genus level
• False positive in low biomass samples

Question 20

Advantages of metagenome

Answer 20

• Species or strain level
• Functional potential
• Uncultured microbial genome

Question 21

Disadvantages of metagenome

Answer 21

• Expensive
• Time consuming analysis
• Host derived contamination

Question 22

Approaches to the analysis of microbiome data

Answer 22

• Visualizing composition
• Diversity measures
• Differential abundance testing
• Prediction testing (machine learning)
• Network analysis

Question 23

Two methods of visualising composition using taxonomic composition

Answer 23

• Composition bar plots
• Violin plots

Question 24

Taxonomic composition

Answer 24

• 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.

Question 25

Biodiversity

Answer 25

• Variety within and among life forms in a sample, ecosystem, or landscape
• Measured using two components (richness and evennes)

Question 26

Richness

Answer 26

• Number of groups of genetically or functionally related individuals
• e.g. Number of bacterial genera or species in a sample (OTUs or ASVs)

Question 27

Evenness

Answer 27

• 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.

Question 28

Alpha diversity

Answer 28

• 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

Question 29

Beta diversity

Answer 29

• 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

Question 30

Visualising beta diversity

Answer 30

• Hierarchical clustering
• Principal component analysis (PCA)

Question 31

Differential abundance analysis

Answer 31

• 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