1. Quantitative Phylogenetic Assessment of Microbial Communities in Diverse Environments
Xinjun Zhang

2. Microorganism Make up more than 1/3 biomass on earth
Play roles in cycling of nutrients, interact with animals and plants, and influence climate
But our knowledge about them remains limited and fragmentary – most of them can’t be cultivated in lab

3. How to characterize these organisms
First step: provide a taxonomic consensus
Cloning and sequencing 16S or 18S rRNA
(+)successful in revealing microbial diversity
(-) amplification bias in PCR process, chimeric error
Directly shotgun sequencing of community DNA
(+)No PCR step, unusual organism could also be captured
(-)not entirely free from quantitative distortions due to sample preparation, but could later be adjusted by DNA extraction protocol

4. Analysis procedure Marker gene: nearly one copy per genome
BLAST, > 60
Marker gene: nearly one copy per genome
COG: Cluster of orthologous group, maintained at the STRING website
Multiple alignment using HMMALIGN;
concatenate and remove gaps using GBLOCKS
TREE-PUZZLE to decide the most probable branching position (Why not BLAST?)
Finally, all query sequences get placed

5. Representation of sequenced genomes

6. living environments of proteobacteria
Proteobacteria to be the most dominant phylum of microbial life in bothmarine and soil environments. And marked differences within the Proteobacteria were apparent:

7. few endospore-forming organisms in the community sequences
Both Bacilli and Clostridia were quite rare; their largest combined abundance was a mere 1% (in soil).
Actinobacteria (many of which have a spore stage) ranged from being virtually absent in the acidic mine drainage biofilm to only 6.2% in the soil sample.
->It is conceivable that spores are underrepresented in the data. (they may withstand the DNA extraction protocols)
Quantitative analyses of relatively rare phylas

8. Quantitative analysis of undersampling errors – Jackknife testing

9. Quantitative analysis of undersampling errors – boostrap testing

10. Depth of environment sequencing placement
Almost all placements of environmental sequences occurred at relatively deep, internal nodes in the reference tree;
only a few could be placed toward the tips as close relatives of the cultured and sequenced genomes.
Most of these deep placements in fact originated from lineages not yet represented among sequenced genomes, meaning no close enough relatives in the tree

11. Branch length and evolution rate
The maximum likelihood branch length, provide detailed information about evolution rates.

12. Habitat stabilityof microbial organisms
At short to intermediate evolutionary time scales, we observed a noticeable stability of habitats: Many of the closer relatives in the tree showed the same environmental preference,indicating that microbial lineages do not very often change (or specialize) their lifestyles and habitats
At longer time scales, we did observe notable changes of preferred habitats: Proteobacteria and Cyanobacteria

13. Diverse habitats occupancy of proteobacteria

14. Habitats occupancy of cyanobacteria

15. Hypothesis: Microbial taxa have preferred environments
microorganisms are frequently dispersed globally, and that they are only subsequently selected by the environments based on their functional capacities
Nonspecialist intruders could acquire the necessary functionality through horizontal gene transfer and thus survive.

16. Quantitative support for this hypothesis
Analysis of habitat information available for cultivated strains in culture collections, as well as the large body of publicly available rRNA sequence data.
In the case of cultivated strains, taxonomic assignments can be parsed for the last taxonomic rank still shared
In the case of rRNA sequence data, branch length information can be analyzed using a global phylogeny of small subunit RNA sequences

17. Quantitative support for this hypothesis (cont)
for any two microbial isolates, the similarity of their annotated habitat (as measured by automated keyword comparisons), is strongly correlated to their evolutionary relatedness
Even strains related only at the level of taxonomic order are still significantly more frequently found in the same environment than a random pair of isolates

18. Conclusion
This alternative approach of taxonomic profiling of complex communities has sufficient resolution to uncover differences in evolutionary rates of entire communities, as well as long-lasting habitat preferences for bacterial clades.

19. Thanks!