L2: The Study of Microbiomes: omic and other techniques Flashcards
what are the levels of microbiome study?
- who are they
- what do they do
- how do they do
levels of microbiome study: who are they - how is this answered
through taxonomic profiling
levels of microbiome study: what do they do- how is this answered
through microbiome functional profiling
levels of microbiome study: how do they- how is this answered
through mechanism study
how can we study microbiomes
- bacterial isolation
- 16S rRNA sequencing
- metagenomic sequencing
studying microbiomes - bacterial isolation
- isolate → whole-genome sequencing
- helps understand what microbes are there
- only helps with taxonomic profiling (level one of microbiome study)
studying microbiomes: bacterial isolation - explain the process
- extract DNA
- amplify gene marker
- sequence DNA
studying microbiomes: bacterial isolation - disadvantage
- dark matter cannot be isolated
- for these microorganisms, need to use metagenomic or 16S rRNA gene sequencing
studying microbiomes: bacterial isolation disadvantage - dark matter
- used to describe the majority of microbial organisms that microbiologists cannot culture in a lab
- makes up most microbes (only 1% can be cultured and isolated)
studying microbiomes: 16S rRNA sequencing - general process
microbiome → phylogenetic marker gene sequencing (amplicon) → taxonomic profile → predicted functional profile
studying microbiomes: 16S rRNA sequencing - why use 16S rRNA
- it is part of prokaryotic small ribosomal subunit
- has 9 conserved and hypervariable regions
- low mutation and horizontal gene transfer rates
16S rRNA sequencing: why use 16S rRNA - what is the conserved regions used for
used to design primers which amplify genes
16S rRNA sequencing: 16S rRNA conserved regions - what must you do when designing primers and why
- choose primers that overlap the paired hypervariable regions
- full length variables are not used unless you only use one organism bc otherwise it will increase sequencing errors
16S rRNA sequencing: why use 16S rRNA - explain the hypervariable regions
allows us to see which genes are different
16S rRNA sequencing: why use 16S rRNA - what do conserved and hypervariable regions look like on a sequencing graph
- conserved: low lines
- hypervariable: high lines
studying microbiomes: 16S rRNA sequencing - explain the overall 16S rRNA analysis
environmental samples → bacteria + PCR amplification → 16S rRNA sequencing → sequencing comparison → community composition + phylogeny → diversity + statistical analysis
16S rRNA sequencing: overall 16S rRNA analysis - which parts are considered quantitative analysis on taxonomic groups
community composition + phylogeny → diversity + statistical analysis
16S rRNA sequencing:16S rRNA analysis - what are ASVs
- Amplicon Sequence Variants
- it is all the different DNA sequences within the sample
- put the bacteria in a phylogeny and every node is a ASVs
16S rRNA sequencing:16S rRNA analysis - what are OTUs
- Operational Taxonomic Unit
- clustering sequences in a 97% similarity threshold
- the old way
16S rRNA sequencing:16S rRNA analysis - what is a problem associated with OTUs
- some groups don’t represent the threshold
- certain genotypes that are different would represent the threshold
16S rRNA sequencing - 16S rRNA analysis limitations
- restricted to prokaryotes since you will need to change the primers for eukaryotes
- limited resolution and low sensitivity in some bacterial groups
- PCR errors
- results depend on the variable sequence considered
16S rRNA sequencing: 16S rRNA analysis limitations - why may you have limited resolution and low sensitivity
- some bacteria can only be sequenced to the genome level
- cannot distinguish on the species level
16S rRNA sequencing: 16S rRNA analysis limitations - why are the results dependent on the variable sequence
mutation rates across variable regions are different for each organism
16S rRNA sequencing - is amplicon sequencing the best for showing true diversity
- no
- when comparing taxonomic results with metagenomic results, the metagenome always shows more diversity
- this is bc not all groups can be shown through PCR
16S rRNA sequencing - most common plots derived from 16S rRNA
- bar plots
- orgination (beta-diversity)
- boxplots (alpha-diversity)
16S rRNA sequencing: most common plots - bar plots
- shows dominant sample
- color = bacterial groups
- bars = different organisms
16S rRNA sequencing: most common plots - bar plots disadvantage
when plotting a lot of organisms, it can look messy + you cannot see a consensus main groups
16S rRNA sequencing: most common plots - orgination (beta-diversity)
- compares different samples based on microbiomes
- every dot = different sample/individual
- the closer the dots are, the more similar the microbiomes are
16S rRNA sequencing: orgination (beta-diversity) - explain the axis
- amount of variation explained
- percent shows the similarity
- subtracting percent from 100, get the percent differences
16S rRNA sequencing: most common plots - boxplot (alpha-diversity)
counting how many species (diversity) seen in each sample
studying microbiomes - metagenomics
- microbiome → shotgun sequencing → taxonomic + functional profile
- sequences entire DNA samples without PCR
studying microbiomes: metagenomics - explain the actual process
DNA extraction → fragmentation → DNA sequencing → read classification → taxonomic profiling OR virulence factor analysis OR functional profiling
metagenomics: the actual process - why is it fragmentated
DNA sampling works better with fragments and not whole DNA samples
metagenomics: explain the actual process - how is DNA sequencing done
via curated genomes from database
metagenomics: the actual process - what is considered quantitative metagenomics
- taxonomic profiling
- virulence factor analysis
- functional profiling via annotating the config to its function
metagenomics: quantitative metagenomics - why is the ‘read classification’ step necessary before using quantitative metagenomics
- in order to use quantitative metagenomics, you need to assemble DNA into larger configurations (config) via that step
- so you have to generate a config
metagenomics - explain metagenomic binning
its a process used to classify DNA sequences obtained from metagenomic sequencing into discrete groups (bins) based on similarity
metagenomic binning - explain the process
DNA extraction → fragmentation → DNA sequencing → assembly → gene finding + annotation → phylogenetic binning (separates genomes) → metabolic reconstruction
limitation of metagenomics
- takes a lot of time, not feasible for large-scale studies + its expensive
- assembling reads is impossible for medium or high diversity communities
- may show host DNA in symbiotic systems (i.e., contamination)
limitation of metagenomics - what solution is there for symbiotic systems
- functional inference from 16S data
- not an ideal solution however
what are microbial “omics”
- carious disciplines in biology
- ex: metagenomics, metatranscriptomics, metaproteomic, metabolomics
microbial “omics” - metagenomics
- DNA level
- asks:
1. which microbes are present
2. what is their relative abundance
3. what microbial genes are present
microbial “omics” - metatranscriptomics
- mRNA level
- asks:
1. which microbial mRNA are present
2. what are their potential abundance
3. what is their relative abundance
4. what microbes produced them
microbial “omics” - metaproteomics
- protein level
- asks:
1. which microbial proteins are present
2. how much of the proteins are present
3. what are their known functions
4. which microbes express them
microbial “omics” - metabolomics
- metabolites level
- asks:
1. which microbial metabolites are present
2. how much of the metabolites are present
3. what are their known functions
4/ which microbes produce them
explain the Fluorescence in situ hybridization (FISH) protocol
- permeabilization/fixation
- hybridization
- washing
- visualization
Fluorescence in situ hybridization (FISH) protocol - permeabilization/fixation
lets molecules have access to cells without ruining the cell
Fluorescence in situ hybridization (FISH) protocol - hybridization
target a particular molecule/bacteria
Fluorescence in situ hybridization (FISH) protocol - visualization
see green molecules through fluorescent microscope
explain the nanoSIMS protocol
- incubate samples and provide a nutrient and label it with an isotope
- can now track it
- more coloration = more nutrient present
