Transcript 4_OTUS_OPUS_SPECIES

Species  OTUs  OPUs
 Species
 OTUs
 OPUs
SPECIES  CONCEPT versus DEFINITION
The CONCEPT is the IDEA, what embraces a unit
(generally immutable)
The DEFINITION is the WAY to embrace a unit
(changes with technical developments)
(depends on the observable characters)
Taxa circumscription
depends on the
observable characters
Most plants & animals
Rest of eukaryotes
Prokaryotes
Sexual isolation (biological SC)
Morphology (taxonomic SC)
Genealogy / Genetics / Phenotype
Rosselló-Mora & Amann 2001, FEMS Rev. 25:39-67
CONCEPT vs DEFINITION
The CONCEPT is the IDEA, what embraces a unit (generally immutable)
 monophyletic group of isolates
 genomically coherent
 sharing high similarity in many independent phenotypic features
The DEFINITION is the WAY to embrace a unit (changes with technical developments)
 monophyly  gene sequence analysis (i.e. 16S rRNA)
 genomic coherence  DDH
 phenotype (biochemical tests, chemotaxonomy…)
How do we define / circumscribe species for prokaryotes
phylogenetic coherence
genomic coherence
phenotypic coherence
50%
60%
70%
70-50%
70%
80%
100%
RNAr 16S
Functional genes (MLSA)
Genomic analyses
Reasociación DNA-DNA
G+C, AFLP, MLSA
Genomic comparisons
(ANI; AAI)
metabolism
chemotaxonomy
spectrometry
(Maldi-Tof; ICR-FT/MS)
 16S rRNA gene sequence (gold sdt)
 DDH (gold standard)
 identificative phenotypic property
 97% - 98.7% identity threshold
 70% similarity threshold
 chemotaxonomic markers
 all organisms must be monophyletic
 96% ANI
 metabolic homogeneity
Tindall et al., 2010 IJSEM 60:249-266
The problems of having to isolate organisms for taxonomic studies:
 it is impossible to “formally” classify uncultured organisms yet
 just the Candidatus status is recognized
 difficulties to homogenize names for the scientific community
The benefits of having to isolate organisms for taxonomic studies:
 validation of a name requires DEPOSIT of a type strain in TWO
international collections
 type material should be AVAILABLE to all the scientific community
 type strains are the REFERENCE for any taxonomic work
Species  microbial molecular ecology
MOLECULAR TECHNIQUES
 generally identification of units (species) by means of 16S rRNA genes
 generally inform about the highly abundant organisms
 it is not clear where to set a threshold of what is a species
Red => knowable diversity / black => seed bank, unknown, difficult to know
Pedrós-Alió, 2006 TRENDS Microbiol 14:257-263
≠ disciplines use ≠ size of their basic units
≠ observational methods
 Taxonomists  phylogenetic / genomic / phenotypic coherence
 Ecologists 97% identity OTUs  too wide for taxonomists
 Evolutionary microbiologists  much more strict  too narrow for taxonomists
Compile microdiversity
Ecotype; early stage of
speciation
A stable framework needs PRAGMATISM
into OTUs at 97% identity
Rosselló-Móra, 2011 Environ Microbiol 14:318-334
OTUs OPERATIONAL TAXONOMIC UNITS
 Clustering by sequence identity threshold
Clustering at XX% identity
Quiime …
Metagenome
5’
V1 & V2
OTU 1
V5 & V6
OTU 2
OTU 3
OTU 4
Singletons
doubletons
3’
 Different groups use different variable zones
 metagenomes of different zones are not comparable
 perhaps identical sequences of different stretches may match different OTUs (green highlighted)
 High identity does not mean common ancestry
OTUs OPERATIONAL TAXONOMIC UNITS
 97% sequence identity threshold
100%
100%
reconditioning
99%
98%
97%
Clone libraries
 great phylotype diversity
 PCR errors (reconditioning)
 microdiversity (several operons?)
 grouping through % identity
 OTU (Operational Taxonomic Unit)
 97% one species?
Acinas et al., 2004 Nature 430:551-554
RECOMMENDATIONS FOR THE USE OF OTUS
 Use 99% or 98.7% identity (IS AT THE RESOLUTION OF A TAXONOMIC SPECIES)
 Ecologists 97% identity OTUs  too wide for taxonomists
 Evolutionary microbiologists  much more strict  too narrow for taxonomists
450000
SILVA REF 112
DATABASE
400000
SEQUENCING
ERRORS
350000
300000
250000
200000
150000
99,50%
100000
99,00%
98,70%
50000
0
0
300000
600000
900000
1200000
Yarza et al., Nature Revs. 2014. 12: 635-645
OPUs OPERATIONAL PHYLOGENETIC UNITS
 Grouping after phylogenetic inference (using parsimony tool of ARB)
Clustering at XX% identity
Quiime …
Metagenome
OTU 1
OTU 2
OTU 3
(representatives)
OTU 4
Singletons
doubletons
 Selected sequences are inserted in a tree
preexisting using parsimony inference
 different sizes, zones, may affiliate together
 if no use of ARB, one can select the best
sequences from the databases matching OTUs
and reconstruct properly
 One OPU will contain different OTUs of
different length, zone, sample, etc…
OPUs  subjective  best solution to measure diversity
OPU  Operational Phylogenetic Unit
 similar to “Operational Phylogenetic-based Microbial Populations” (Pernthaler & Amann)
 somehow subjective, but may reflect better ecologically relevant populations
Rosselló-Móra & López-López, 2008. In: Accessing Uncultivated Microorganisms ASM Press
López-López et al., 2010 Environ Microbiol Reports 2:258-271
Pernthaler & Amann. 2005. Microbiol Mol Biol Rev 69:440-461
OPUs  reduce diversity but may reflect metabolic groups
OPUs
 Reduce diversity measures
 somehow more tedious and subjective (not always negative)
 avoid the use of artificial thresholds
Species  OTUs  OPUs
 Species are taxonomic units based on well characterized isolates
 Molecular microbial ecology  sequences  97% identity = OTU (artificial threshold)
 I recommend you to use a cutoff value of 99% for OTU clustering
 OPUs avoid rigid thresholds & may reflect better metabolic and/or ecological types