1. Species  OTUs  OPUs  Species  OTUs  OPUs

2. Rosselló-Mora & Amann 2001, FEMS Rev. 25:39-67 Taxa circumscription depends on the observable characters Most plants & animals Rest of eukaryotes Prokaryotes Sexual isolation (biological SC) Morphology (taxonomic SC) Genealogy / Genetics / Phenotype The CONCEPT is the IDEA, what embraces a unit (generally immutable) (generally immutable) The DEFINITION is the WAY to embrace a unit (changes with technical developments) (depends on the observable characters) SPECIES  CONCEPT versus DEFINITION

3. 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…) CONCEPT vs DEFINITION

4. phylogenetic coherence RNAr 16S Functional genes (MLSA) Genomic analyses 70-50% 70% genomic coherence Reasociación DNA-DNA G+C, AFLP, MLSA Genomic comparisons (ANI; AAI) 100% 60% 70% 80% 50% phenotypic coherence metabolism chemotaxonomy spectrometry (Maldi-Tof; ICR-FT/MS)  16S rRNA gene sequence (gold sdt)  97% - 98.7% identity threshold  all organisms must be monophyletic  DDH (gold standard)  70% similarity threshold  96% ANI  identificative phenotypic property  chemotaxonomic markers  metabolic homogeneity Tindall et al., 2010 IJSEM 60:249-266 How do we define / circumscribe species for prokaryotes

5.  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 The benefits of having to isolate organisms for taxonomic studies: 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

6. Pedrós-Alió, 2006 TRENDS Microbiol 14:257-263 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 Species  microbial molecular ecology

7. ≠ disciplines use ≠ size of their basic units ≠ observational methods Rosselló-Móra, 2011 Environ Microbiol 14:318-334  Taxonomists  phylogenetic / genomic / phenotypic coherence  Ecologists 97% identity OTUs  too wide for taxonomists  Evolutionary microbiologists  much more strict  too narrow for taxonomists Compile microdiversity into OTUs at 97% identity Ecotype; early stage of speciation A stable framework needs PRAGMATISM

8. OTUs OPERATIONAL TAXONOMIC UNITS  Clustering by sequence identity threshold Clustering at XX% identity Quiime … Metagenome OTU 1 OTU 2 OTU 3 OTU 4 Singletonsdoubletons 5’5’5’5’ 3’3’3’3’ V1 & V2 V5 & V6  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

9. 100% 100%reconditioning 99% 98% 97% Acinas et al., 2004 Nature 430:551-554 Clone libraries  great phylotype diversity  PCR errors (reconditioning)  microdiversity (several operons?)  grouping through % identity  OTU (Operational Taxonomic Unit)  97% one species? OTUs OPERATIONAL TAXONOMIC UNITS  97% sequence identity threshold

10. 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 Yarza et al., Nature Revs. 2014. 12: 635-645 SEQUENCING ERRORS SILVA REF 112 DATABASE

11. 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 OTU 4 Singletonsdoubletons (representatives)  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…

12. OPUs  subjective  best solution to measure diversity 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 OPU  Operational Phylogenetic Unit  similar to “Operational Phylogenetic-based Microbial Populations” (Pernthaler & Amann)  somehow subjective, but may reflect better ecologically relevant populations

13. 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

14. 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