Profiling microbial communities

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Profiling microbial communities with
T-RFLP (terminal restriction fragment length
polymorphism) Anne Fahy
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why microbial ecology?
Microbial organisms occupy a peculiar place in
the human view of life. Microbes receive little
attention in our general texts of biology. They
are largely ignored by most professional
biologists and are virtually unknown to the
public except in the context of disease and rot.
Yet, the workings of the biosphere depend
absolutely on the activities of the microbial
world. (Pace, 1997)

• huge metabolic diversity
• higher organisms dependent on microbial
  activities
• applications bioremediation and natural
  attenuation of pollutants in the environment

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why culture-independent?

• between 0.001 and 1 microorganisms are
  culturable (Amann 1995)
• microbial communities are complex
• huge diversity
• close interactions between organisms
• highly dynamic

phylogenetic tree based on 16S rRNA major phyla
of the domain Bacteria (Rappé Giovannoni,
2003) black 12 original phyla described by
Woese, 1987 white 14 phyla with isolated
representatives grey 26 candidate phyla with
no known isolates
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why 16S rRNA as a phylogenetic marker ?

• protein translation universal
• no horizontal transfer (caveat Wang
  Zhang, 2000)
• convenient length 1500 bp
• highly conserved regions as well as
  species-specific regions
• large databases (EMBL, NCBI, DDJB)

secondary structure of the Escherichia coli 16S
rRNA molecule (Van de Peer, et al. 1996).
colours ?? variability between organisms pink
highly conserved red least conserved grey
unaligned
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other phylogenetic markers

• proteins difficult to identify homologous
  proteins (Demoulin, 1979)
• historically also 5S, 23S rRNA
• ribosomal intergenic spacer 16S 23s
• 18S for Eukaryotes

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T-RFLP (Terminal Restriction Fragment Length
Polymorphism)
1 extraction of community DNA or RNA from
environmental sample (need RT-PCR step with RNA)
3 digestion of amplicons with restriction enzyme
2 PCR amplification of 16S rRNA gene with
fluorescent primers
4 detection and sizing of labelled terminal
fragments by capillary or gel electrophoresis
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raw data
T-RFLP (2)
Red internal size standard Blue forward
primer Green reverse primer
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T-RFLP (3)
Analysis of raw data with Genescan virtual
filter adjust overlap of fluorescence sizing
standard curve integration of peaks
size calling curve
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T-RFLP (4)
Electropherogram a visual profile of the
community. In principle, the height and area of
the peaks are representative of the abundance of
the groups of organisms. Several groups of
organisms may share the same T-RF.
Table digital data can be further processed and
used, for example, to generate dendrograms
illustrating the relationship between bacterial
communities.
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T-RFLP resolution

• several groups of organisms may share the same
  T-RF
• T-RFs need to be within range of size standard

resolution of T-RFLP depends on the choice of
restriction enzyme / primer combination

• Ribosome Database Project
• TAP-TRFLP application
• enter choice of enzyme/primer
• in silico digestion of 16S rRNA on the database
• http//rdp8.cme.msu.edu/html/TAP-trflp.htmlprogr
  am

several digests combine data ? increase
resolution
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T-RFLP good technique

• reproducible technique
• relatively fast ? monitor community dynamics
• culture-independent
• digital data for further analyses
• link data to clone libraries

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but.. . need to look at data to avoid pitfalls
and know the limitations

• sources of biases (von Wintzingerode et al.,
  1997)
• experimental design
• sampling
• storage of sample
• DNA extraction
• PCR amplification (loads of literature!)

keep experimental procedures constant ? PCR-based
techniques provide information that is not
obtainable through other methods
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limitations inherent to T-RFLP

• glitches in the electrophoresis ? rerun sample
• incomplete digestion (partially single-stranded
  amplicons Egert Friedrich, 2003) ? be aware

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limitations inherent to T-RFLP (2)
renaturation of sample salts in buffer amount
of DNA in sample delay between denaturation and
electrophoresis ? rerun sample
renaturation of internal size standard
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limitations inherent to T-RFLP (3)
overloading of the capillary ? rerun sample
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limitations inherent to T-RFLP (4) sizing
problems
discrepancy between expected T-RF (from in
silico digestion of known sequence) apparent
T-RF (from electrophoresis) ? caution when
interpreting T-RFLP profiles
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limitations inherent to T-RFLP (5) sizing
problems
causes - apparent size varies with the type of
genetic analyser a 142 nt fragment will measure
143.4 and 140.6 nt respectively on a gel or
capillary genetic analyser (GeneScan Reference
Guide) - resolution decreases as fragment
length increases - ROX label of internal standard
migrates more slowly than the FAM label of the
forward primer (Boorman et al., 2002) - apparent
size of fragment depends on its secondary
structure
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limitations inherent to T-RFLP (6) sizing
problems
- difference proportional to fragment length -
can vary from -2 to -4 nt for very similar length
of fragment - outside range of size standard
cant size accurately - abnormal migration
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limitations inherent to T-RFLP (7) sizing
problems
very abnormal migration from a specific clone
T-RF

• possible hairpin from secondary structure
• - no such discrepancy from other clones with same
  sequence immediately preceding the restriction
  site

in press Nogales et al. (a study of mobility
anomalies of 16S rRNA gene fragments)
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limitations inherent to T-RFLP (8) Conclusions
T-RFLP very reproducible (electropherograms need
to be perfect) comparison of data limited to
studies using same type of genetic analyser
cannot predict phylogenetic affiliations from
the length of the T-RFs within its
limitations, T-RFLP is a good culture-independent
technique for profiling microbial communities!
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many community profiling techniques
Techniques based on PCR of rDNA Cloning and
sequencing of 16S rDNA DGGE (denaturing
gradient gel electrophoresis) SSCP (single
strand conformation polymorphism) RFLP
(restriction fragment length polymorphism) LH-PCR
(length heterogeneity analysis by PCR) ARISA
(automated ribosomal intergenic spacer
analysis) DGGE and T-RFLP also used for diversity
of catabolic genes Other approaches to
community profiling Hybridisation, FISH, PLFA,
BIOLOG Linking metabolic function to
phylogeny SIP (stable isotope probing)