More Related Content Similar to An Ecophylogenetic Approach to Determine the Evolutionary History of the Mammalian Gut Microbiome #ASMMicro2016 (20) 1. An Ecophylogenetic Approach to Determine the Evolutionary History of the Mammalian Gut Microbiome
Christopher A. Gaulke(1), Holly Arnold(1), Steven W. Kembel(2), James P. O’Dwyer(3), Thomas J. Sharpton (1,4)
(1) Department of Microbiology, Oregon State University, Corvallis, OR, USA (2) Département des Sciences Biologiques, Université du Québec à Montréal, Montreal, QC, Canada
(3) Department of Plant Biology, University of Illinois, Urbana, IL, USA (4) Department of Statistics, Oregon State University, Corvallis, OR, USA
Abstract
ClaaTU: An Ecophylogenetic Microbial
Community Analysis Framework
Identifying those gut microbes that co-diversify with mammals is important to our un-
derstanding of the mechanisms and health implications of host-microbiome interac-
tions. For example, microbiota that are conserved across mammalian species may ex-
press a trait that has been subject to selection throughout the evolution of these mam-
mals, possibly because it is critical to health. While advances in environmental DNA se-
quencing have transformed our understanding of how enteric microbes are distributed
across mammalian species, these data are frequently analyzed using phylogenetically
agnostic approaches. Such approaches can obscure the detection of diverged groups of
bacteria that have been conserved across mammalian species.To provide enhanced res-
olution into evolutionary associations between gut microbiota and mammals, we inno-
vated a high-throughput ecophylogenetic method, known as ClaatTU (Cladal Taxonom-
ic Units). ClaaTU analyzes phylogenies assembled from environmental DNA sequences
collected from a set of microbial communities and profiles the presence and abundance
of each monophyletic clade in each community. As a result, it enables the identification
of specific microbial clades that are distributed across host communities in a manner in-
dicative of being associated with mammalian evolution. To demonstrate this, we ap-
plied ClaaTU to a mammalian microbiome dataset and (1) identified clades of gut bacte-
ria that are unique to groups of mammals based on their taxonomy or dietary regime, (2)
found that there exists ecophylogenetic structure in the mammalian gut microbiome,
indicating that gut bacterial phylogenetic diversity associates with host phylogeny, and
(3) discovered specific clades that are present in a larger number of mammals than ex-
pected by chance, some of which may co-diversify with their hosts. Our findings indi-
cate that some mammalian gut microbiota may have been anciently acquired and sub-
sequently retained in extant lineages, indicating that they may play an important role in
mediating host-microbiome interactions and maintaining host health.
Case Study: Conserved Responses to
Dietary Variation Among Monophyletic
Clades of Gut Bacteria
Summary
Acknowledgements
Ecophylogenetic Structure in the Mammalian
Gut Microbiome
Monophyletic Clades of Gut Bacteria
Are Conserved across Mammalian
Sample 1 Sample 2 Sample 3
1
2
3
4
5
6
7
Sample 1
Sample 2
Sample 3
Sample 1
Sample 2
Sample 3
1 2 3 4 5 6 7
2
2
2
2
0
0
2
2
0
2
20
0
0
01
1
0
1
1
1
Figure 1: Analysis of the ecological distribu-
tion of monophyletic clades (ecophylogenet-
ics) can reveal groups of organisms that ex-
hibit evolutionarily conserved functions that
impact their ecology. 16S sequences derived
from three different various communities (”Sam-
ples”) can be related via a phylogeny (solid lines)
or clustered into OTUs (red circles). In this exam-
ple, no OTU is common to all communities (red
arrows), but a monophyletic clade is (shaded
area), indicating that the common ancestor may
have evolved and subsequently maintained a
function critical to occupying these communi-
ties. Note that interesting clades (e.g., core
clades) may also be discovered at the sub-OTU
Figure 2: The ClaaTU workflow. The Cladal Taxonomic Units (ClaaTU) workflow quantifies the abundance of specific
clades in a user provided phylogenetic tree. ClaaTU first assigns identifiers to all internal clades on a phylogenetic tree and
then conducts a root-to-tip traversal of the tree to quantify the abundance of each clade by summing the counts of the de-
scendants. The output of ClaaTU is a clade abundance matrix, which logs the abundance of each clade in each sample.
Much like an OTU abundance matrix, these data can be used to identify clades that associate with samples, indicating their
interaction. Notably, ClaaTU can use data files produced by third party microbiome analysis software (e.g., QIIME and
Mothur) and analyze phylogenies assembled from OTU clustered sequences.
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
PC1
group
●
●
●
●
●
●
●
●
●
●
Artiodactyla
Carnivora
Diprotodontia
Hyracoidea
Lagomorpha
Perissodactyla
Primates
Proboscidae
Rodentia
Xenarthra
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
PC1
Diet
●
●
●
Carnivore
Herbivore
Omnivore
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
● ●
●●
●
●
●
PC1
Diet
●
●
●
Carnivore
Herbivore
Omnivore
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●●
●
●
●
●
●
PC1
group
●
●
●
●
●
●
●
●
●
●
Artiodactyla
Carnivora
Diprotodontia
Hyracoidea
Lagomorpha
Perissodactyla
Primates
Proboscidae
Rodentia
Xenarthra
Order
●
●
●
●
●
●
●
●
●
●
Artiodactyla
Carnivora
Diprotodontia
Hyracoidea
Lagomorpha
Perissodactyla
Primates
Proboscidae
Rodentia
Xenarthra
BushDog
Black Bear
Polar Bear
Spectacled Bear
Hyena
Lion
Horse
Zebra
Black Rhino
Okapi
Giraffe
Urial
Big Horn
Gazelle
Springback
Pig
Capybara
Squirrel
Rabbit
Orangutan
Gorilla
Chimpanze
Colobus
Baboon
Saki
Callimicos
Red Tailed Lemur
Black Lemur
Armadillo
Hyrax
African Elephant
Kangaroo
H C O
0
50
100
150
Diet Specific Clades
#CladesperHost
Diet
Art Car Pri
0
20
40
60
80
Order Specific Clades
#CladesperHost
Order
Unweighted
Clade Bray-Curtis
Weighted
Clade Bray-Curtis
ClusteringByHostOrderClusteringByHostDiet
Host Phylogeny
Figure 5: Gut microbiomes from 32 mammals were pro-
cessed with ClaaTU. 16S rRNA sequences that were originally
published in [1] were processed with ClaaTU as in Fig. 3. (Left)
The phylogeny of the host taxa as provided by [2]. (Right) The
distribution of clades unique to members of each host Order
(only Artiodactyla, Carnivora, Primates shown due to limited
sampling in other Orders) or diet (Herbivore, Carnivore, Omni-
vore) were quantified. Unique clades were normalized by
number of hosts to correct for sampling disparities. This analysis
reveals that different groups of hosts have acquired specialized
clades of bacteria.
Figure 6: Highly abundant gut microbiome clades sepa-
rate hosts by dietary preference while lowly abundant
clades separate by host taxonomy. The clade abundance
matrix produced by ClaaTU from the analysis of the 32 mam-
mals was used to calculate the weighted and unweighted
Bray-Curtis dissimilarity (BCD). PCoA was used to visualize re-
sults. Ellipses represent 95% confidence intervals and are sup-
pored by PERMANOVA analysis (p < 0.05). Separation among
groups is highest for unweighted BCD when clustering by
Order, and for weighted BCD when clustering by diet.
Z0220
Z0221
Z0222
Z0223
Z0224
Z0225
Z0226
Z0227
Z0229
Z0230
Z0231
Z0232
Z0233
Z0234
Z0235
Z0236
Z0237
Z0239
Z0240
Z0241
Z0242
Z0243
Z0244
Z0246
Z0247
Z0248
Z0249
Z0251
Z0252
Z0253
Z0254
Z0255
Z0256
Z0257
Z0258
Z0259
Z0260
Z0262
Z0263
Z0264
7 6 5 4 3 2 1 0
Color Key
log10 relative abundance
OTUPhylogenyAndAbundances
Clade Abundances
Standard
Lab Diet
Defined
High Zn
Defined
Low Zinc
Clade 1888 - A Subclade
within GammaproteobacteriaDefined Diet
Zinc Sufficient
MiSeq
QIIME OTU
Clustering
ClaaTU
Standard
Lab Diet
Defined Diet
Zinc Deficient
Figure 3: A Zebrafish Dietary Exposure
Study Design. Forty-five 5D line zebrafish
were fed one of three diets (3 tanks/diet): a
standard lab diet (Gemma Micro 300, a 130
mg/kg zinc), a defined diet with sufficient
levels of zinc (33 mg/kg), and a defined diet
with deficient levels of zinc (12.46 mg/kg).
Stool was collected through temporary isola-
tion of fish. Gut microbiomes were interro-
gated using V4 16S rRNA MiSeq sequencing,
QIIME (97% identity OTUs), and ClaaTU with
FastTree.
Figure 4: An example of a monophyletic clade that strati-
fies high and low zinc diets. A specific clade (1888, ingroup
above blue line) significantly differs in abundance between
the high (orange and blue) and low (green) zinc diets (krus-
kal-wallis p < 0.05). Notably, no single OTU reveals a signifi-
cant difference in association with zinc status.
Individuals
Significantly Conserved Clades
#Clades
0
2
4
6
8
10
12
Class
Order
Family
Genus
Species
Ruminococcacea
Lachnospiraceae
Clostridiales
Bacteroidales
Turicibacter
Alphaproteobacteria
Christensenellaceae
Eubacterium
biformeBlautia
DoreaPrevotella
Prevotellacopri
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●●
●
●●
●
●
● ● ● ●●
●
●
●
●●
●
● ● ●
●
●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●●
●
●●
●
● ●
●
●
● ● ● ● ●●●●●●
●
●
●●●
●●●●
●●
●
●
●
●
●
●
●
●●
●
●
●
●●●
●●
●
● ●●
●
●
●
●●
●
● ●●
●●
●
●
●● ●●●
●
●
●●
●
●
●
●
●
● ●
●
●●●
●
●●
●
●
●
●
●
●
●
●
●
● ● ●●●
●
●
●
●
●
●
●●●
●
● ●●
●
●●
●
●
●●● ●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
●
●●●●
●●
●● ●
●
● ●
●●●
●
●
●
●
●
● ●
●
●●
●
●
●
●
●●●
●
●
●
●
●
● ●
● ●
●●
●
●
●
●
●
●
●
●
● ●
●
●●
●
●
●
●
●
●●
● ●
●
●
●●
●
●
●●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●●
● ●
●
● ●
●
● ●
●
●
● ●
●
●
●
● ● ●
●
●
● ●
●
●
●
●●●
●
●
●
●
●● ●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●●●
●
●
● ●
●●
●
●
●
● ●
●●●
●●●
●
●
●
●
●●
● ●
●
●
●
●
●
●
●
● ●
●
●
● ●●
●
●●●
●
●
●
●●
●
●
●
●
●●● ●
●● ●
●
●
●
●
●
●
●
●●●
●
●
● ●
●
●
●
●● ●
●●
●
●
● ●
●● ●●
●
●●
●
● ●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
● ●●●●
●
●●
●
● ●
●●●●
●
●
●●
●●
●●●
●
●
●
●
●
●●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●●●
●●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●●● ●
●
●
● ●
●
●
● ●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●
● ●● ●
●
●
●
●● ● ●
●●
●● ●
●
●●●●
●
●
●
● ●●
●
●●●
●
● ●
●
●●● ●●●●●●●●●●●
●
●●
●
●
●●
●
●● ●
●
●●
●
●
●
●●
●
●
● ●
●
● ● ●
●
●
●
●
● ●●
●
●
●●●
●
●
●●
●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●
●● ●
● ●
●
●
●
●
●● ●
● ● ●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●● ●
●●
●●●
●
●
●
● ●
●
●
●
● ● ● ●
● ●
●●
●
●
●●
● ●
●●
●
●●●●
●●
●● ●
●
●
●●●● ●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●●
●
●
●
●
●
●
●
●
●●
● ● ● ● ●
●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●
● ●
●
●●
●
●
●
●
●
● ● ●
●
● ●
●
●
●
●
●
●●
●
●
●● ●
● ●●
●
●
●
●
● ●
●
●●
●●●
●
● ●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
● ●●● ●● ● ●●
●
●● ●●●
●
●
●●●
●
● ●●
● ●
●
●
●
● ● ●●
●
●
●
●
●●
●
●
●
● ●
●
● ● ●
●
●
●
●
●●
● ●
● ●●
●●
● ●
●●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ● ●
●
●
●
●
●
●
●
●
●●
●
●
●
●
● ●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●
●
●●
●
●
●
●●●
●
●
● ● ●
●
●
●
●
●
●●
●
●
●
● ●
●
● ●
●
●
●
●●
●
●
●●
●
●
●●● ●
●
●●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●
●
● ●● ●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
● ●
●
●●●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
● ●
●
●
●
●
●●
●
● ●●●
●
●
●●
●
●
●
●
●
●
●●
●
●●● ●
●●
●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●●●●
●●●
●
●
●● ●●●●●● ●
●
●●●●
●
●
●●
●
●
●
●
● ● ●
● ●●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ● ● ● ●● ● ●
● ●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
● ●●●
●● ●
●
●
●
●
●● ●
● ● ●● ●
●
●●
●
●●●
●
●
●
●
●●
●
●●
●
●
●
●
●
● ●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
● ●
● ●
●
●
●
●
●
●
●
●
●
●
● ●
●
● ●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
● ● ●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●●
● ● ●
●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
● ●●
●
●●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●●
●
●
●
●●
●
● ●●
●
●
●
●
●
● ●
●
● ● ● ● ●●
●
●
●
●●●
●
●
●
●
● ●
●
●
●●●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
● ●
● ●
●
●●
●●
●
●●
● ●
●
●
●
● ●
●
●
●
●
●
●
●●
●
●
●●
●
●
● ●
●
●
●
●
● ●
●
●
●●
●
●
●
●● ●
●
●
●
● ●
●
●
●
●●
● ●
● ●●
●
● ●
●
●
● ●
●●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
● ●
●
●
●●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●
●●
● ●●●●●
●●
●●●
●
●●●
●
●
●
●
●
●
●●
●
●
●
● ●
●
● ●
●
●
●● ●●
●
●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
● ● ●
●
●
●
● ●
●● ●
●
●●
●
●
●●●●●
●
●
●
●
● ●●●
●
●
●
●
●
●●●
●
●● ●●●●●
● ●●
●
●
●
●●
●
●
●●●● ●
●●
●●●
● ●●
●
● ●●
●
● ●●●●●●
●
●
●
●
●
●
● ●
●
●●●
●
●
●●
●
●
●●
●
●
● ●●●●
●●●● ●●●
●
●
●
●
●
● ●
●●
●●
●
●
●●
●
●●
●
●
●
●
● ●
●
●●
●
●
●
●●●●
●
●●
●
●
●●
●●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
● ●
●●
●
●
●
●●
●
●
●
● ●
● ●
●
●
●
● ● ●
●
●●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●●
●
● ●
●●●
●
●
●
●
●
●●●●
●
●
●
●
●
●
●
●
●
● ●
● ●
●
●
●
●
●
● ●●
● ●
●
●
●
●●
●
●
●● ●
●
●
●
●
●
●●
●
●
●
● ●
● ●
●
● ●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●●
●●●●●●
●
●
●
●
●●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
● ●
●
●
● ●
●
●
●
●
●●
●
●
●
●
●●
●
●●
● ●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●●
●
● ●
●●
●●
●
●
●
●●
●
●
●
●
●●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
● ●
●
●
●
●
●
●
●
● ●
●
● ●
●●●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●● ●
●
●
●
●●
●
●
●
● ●
●
●
●
●
●
●
●
● ●
●●
● ●
●
●
●
●●
●
●
●
●●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
● ●●
●
●
●
●
●
●
●●
●●●
●
●
●
●
● ●
●
●●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●●
●●●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●●
●
●●
●
●
●
●
●●●●
●
●●
●
●
●
●●
●
●●
●
●
●
●
●●
●
●
●
●●
●
● ●
●
●
●
●
●
●
●
●
●●
●
●● ●
●●
●●
●
●
●
●
●
●●
●
●
●
●
●
●
● ●
●
●
● ●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
● ● ●
●
●
●
●
●
●
● ●
● ●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
● ● ● ●
●
●
● ●
●
●
●
●
●
●●
●
●●
●
●
●
●●
●
●
●●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
● ●
●●
●
●
●
●
●● ●
●
●● ●●
●
●
●
●
●
●
●
●
●
●
● ●
●
● ●●
●
●● ●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●●
●
●
●
● ●
●● ●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
● ●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ● ● ●●
●
●
● ●● ●
●
●
●
●●
●
●
●
●●
●
●
●
●●●
●
●
●●●
●●
●●
●●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●●●●●
●●●
●
●
●
●
●
●
●●●
●●
●●
●
●
●
●
●●●●
●●
●
●
●
●
●
●●●
●●
●
●
●●
●
●
●
●●
●● ●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
● ●
●
●●
●
●
● ●
●
●
●
●
●
●
●●
●
●
●
●
●
● ●●●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●● ●●●● ●●
●
●
●
●
●
●
●
●●●
●
●
● ●
●●
●
● ●
●●
●
●
●
●
●
●
●
●
●
● ●
●●●
●
●● ●●●●●
●
●
●
●
●
●
●
● ●
●●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
● ●
●●
●
●
●
● ●
●
●
● ●●●
●
●
●●
●
●
●
●
●●●
● ●
●
●
●
●
●
●
●●●
●
●
●●
●
●● ●
●
●
●
●
●●●●●
●
●
●●
●
●
●
●
●●●
●
●
●
●
●
●●
●●
●●
●
●
●●
●
●
●
●
●●
●
●●●●
●●
●
●
●
●●
●
●
●●●
●
●
●●
●●
●
●●
●
●
●
●●
●
●
●
●
●
●●
●●●●
●
●
●
●
●
●●●
●● ●●●●
●
●
●
●●
●
●
●
●
●
●
● ●● ● ●
●
● ●
●
●
●
●
●●
●
●
●●
●●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
● ●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●●●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
● ●●●●
●
●
●
●
●
●
●
●
●●
●
●
●
●●
●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●● ●
●●
●●
●
●
●●
●
●
●
●
●
●●●
● ● ●
●
●
●
●
●●
●
●
●
●
●●●
●● ●
●
●
●●
●
●
●
●
●
●
●
●
● ● ●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
● ●
●
●●
●
●
●
●
●
●
●
●
●
●●
●
●●
●
●●
● ●
●●
●
●
●
●
●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
● ● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●●
●
● ● ●
●
●
●
●
● ●
●
●
●
●
●
●
●
● ●
●
●●
●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
● ● ●●
●
● ●
●
●
●
●
●● ●
●
●
●
●
●
●
●
●
●●
●
●
●
●●
●
● ●
●●●
●
●
●
●
● ●
●
●
●●
●
●
●
●●●●
●
●
●●
●●
●●
●●
●●●
●
●
●●
●
●
●
●
●
●
●
● ●
● ●
● ●
●
●
●●●● ●●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●● ●●
● ●●
●
●
●
●
●●
●
●
●
●
●●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
● ●
●
●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●● ●
●
●
●
●
●●
●
● ●
●
●●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●●
●
●●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●●●●
● ●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●●●
●●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●●●●●
●
●
●●
●
●●
●●
●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
● ●
● ●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●●
● ●
●●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●●
●●●
●
●
● ●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●●●●
●
●
●
●
●
● ●
●●
● ●
●
●●
● ●●●
●
●●
●
●
●
●●
●●
● ●●
●●
●
●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●● ●
●
●
● ●
●
●
●●
●
●
●
●
●
●
●
●
●●●
●●
●
●
●
●
●●
●
●
●
● ●
●
●
●
●
●
●●
●
●●●
●
●
●
●
●● ●
●
●
● ●
●
●
●●
●
●●●
●●
●
●
●
●
●
● ●●● ●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●●
●
●
●
●
● ●●
●
●
● ●
●
●● ●
●
●● ●
●
●●●
●
●●● ●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
● ● ●● ●● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●●
●
●●
●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●
●●
●
●
●● ●● ●
●
●
●
●●
●●
●
● ● ●
●
●
●
●
●
●
●
●
●●
●●
●
●
● ●●●●
●
●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●●●
●●
●●●●●
●
●
●
●
●
●
●
●
●
●
●
●● ●
●●
●
●
●
●
●
●
●
●
●
●●●●
●●
●
●
●●● ●●
●●
●
●
●
●
●
●
●●
●
●
●●
●
●
●
●●
●●
●
●
●
● ●
●
●
●●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●●●●
●●
●
●
●
●
●●
●
●●
●●
●●
●
●
●
● ●●
●
●
●
●
●
●
●
●
●●
●
●
●
●● ●
●
●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●●
●
●
●
●●
●
●●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●●●●●
●
●
●
●
●●
●●
●●
●
●
●●
●●●
●
●
●
● ●
●
●
●
●●
●●
●
●
●
●
●
●●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●●
●●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
● ●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
●●
●
●●
●
●●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
● ●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
● ●●●
●●
●●
●
●
●
●
●
●
● ●
●
●
● ●
●
●
●
●
●
●●
●
●
●●
●
● ●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
● ●
●
●
●
●●● ●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●● ●●
●
●
●
●
●
● ●
●
●
●
●● ●
●
●
●
●
●
●
●
●
● ●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●●●
●●●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●●●
●
●
●
● ●
●●
●●
● ●
●
●
●
●
●
●
●●
●
●●
●
●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
● ●
●
●
●
●
●
● ●
● ●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●
●●
●
●
●
●
●
●
●
●
● ●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●●
●
● ●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●●
●●
●
● ●
●
●
●
● ●
●
●
●
●
● ●
●
●● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●●●
●
●
●
● ●
●
●
●
●
●
●
●
●●
●
●
●
●●
●● ●
●●
●●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●
●
●
● ●
●
●●
●
●
●●●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●●
● ●
●●●●
●
●
●
●
●
●
● ●
●
●●
●
●
●
●
●
● ●
●
●
●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
● ●
●
●
●
● ●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●●
● ●
●
●
●
●
●
●
●
● ●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
● ●
●
●●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●● ●
●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
● ●
●●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
● ●●●
●
●
●
●
●
●●
● ●
●
●
●
●
●
●
●●●
●●
●
●
●●●
●
●
●
●
●
●●
●
●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●●
●
●●
●●●
●
●
●
●●
●●
●●
●
●●
●
●
●●
●
●●●
●●
●
●
●
●
●
●●
●●●
●●
●
●
●
●●
●
●●
●●
●
●
●
●
●
●
●
●
●●●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
●●●●●
●
●
●●
●●
●
●
●
● ●
●
●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●●●●●
●●
● ● ●●
●
●●
●
●
●
●
●●●
●
●
●
●
●
●
●
●●
●
●●
●●
●
●
●
●
●
● ●
●
●
●
●
●
●●
●
●
●●
● ●
●
●●
●●
●
●●●●●● ●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
● ●●
●●
●
●
●
●
●
●
●
●
●
●
●
●●●●●
●
●
●
● ●
●
● ●
●
●
●
●
●
●
●
● ●●
●
●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●● ●
● ●
●
●
●
●
●
●●
●
●
●
● ●
● ●
●
●●
●
●
●
●
●
●
● ●
●
●
●
●●
● ●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
● ●
●
●
●
●
●
●●
●
●
● ●
●
●
●● ●
●
●
●
●
●
● ●
●
●
●
●● ●●
●
●●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●● ●
●
●
●●●
●
●
●●
●
●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●●
●
●
●
●
●●●
●
●
●●
●
●
●
●
●●
●
●●
●●
●●
●
●●
● ●
●
●
●●
●
●
●
●●●
●
●
●
●
●
●●●
●
●
●
●●
●
●
●
●
●●
●
●
●
●●
●
●
●
●
●●
●
●●
●
●●
●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●
●
●
●
●●
●
●●
●
●●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●●●
●
●●
●
●
●
●
●
●
●
●
● ●●
●
●
●
●
●
●
●
●●●●
● ●
●●●
●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●●
●
●
●●
●
●
●●●
●
●
●
●●
●●
●
●
●
●●●
●
●
●
●
●●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●●
●●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●●
●●
●
●●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●●
●
●●
●
●
●
●
●
●● ●●
●
●●
●●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●●
●
●
● ●●●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●●
●● ●
●
●
●
●
●
●
●
●
●●
●
●
●●
●●
● ●● ●●
●
●●●
●
●●●
●
●●
●
●
●●
●
●
●
●
●
●
● ●
●
●●
●
●
●
●●●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●
●
●
●
● ●
●●
●
●
●
●
●
●
●● ● ●
●
● ●●●
●
●
●●
● ●●
●●●●
●
●
●
● ●
●
●●●●● ● ●
●
●
●
●
●
●●
●
●
●●● ●
● ●●
●●●●
●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●
●●
●● ●
●
●●● ●●
●
●●●●●●●●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●
●
●
● ●
●
●●
●●●●●●●
●
● ●● ●●●● ●
● ●
●
●●
●●
● ●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
● ● ●
●
●
●
●●
●●
●●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
● ●●
●
●● ● ● ●
●●
●
●
●●●
●
● ●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●●
●
●
●●
●
●
●
●
●
●
●●
● ●● ●●●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●
●
●●
●
●
●
●
●
●
●
●
●●●
●
●●●
●●
●
●
●●●
●
●
●
● ●
●
●●
●
●
●● ●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●●
●●
●
●
●●
●
●
●
●●
●
●●
●
●
●
●
●
●
●
●
●
●
●●●
●
●●
●
●
●●
●
●
●
●●
●
●●
●●●●
●
●●
●●
●
●
●
●
●●
●
●●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●●
●
●
●●
●●
●
●
●
●●
●●●●●●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●●
●
●
●
●
●
●
●
● ●●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●●●
●●
●
●●
●
●
●
●
●
●●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●●
●
●●●
●
●
●●
●
●
●
●
●
●
●●
●●●
●
●
●
●
●
●
●
●
●
●●
●
●
●●
●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●●●
●
●
●
●
●
●
●
●
● ●
●
●
●● ● ●
●
●●●
●
●
●●
●
●
●
●●●
●●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●●
●●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●
●●●●
●
●
●
●
●
●
●●
●
●
●
● ●●
●
●
● ●
●
●
●
●● ●●●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●● ●
●
●
●●
●
● ●
● ●
●●
●
●
●
●
●
●
●●
●●●
●
●
●
●
● ●
● ●
●●●
● ● ●
●
●
●●
●● ●
●
●
●
●
●
●
●
●
●● ●
●
●●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●●●
●
●
●
●
●
●
●●
●
●
●
●
●
●●●
●
●
●
●●
●
●
●
●
●
●
●
●
●● ●
● ●●
●
●
●
● ●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●●● ●
●
●
● ●
● ● ●●●●
●
●●
●
●
●
●
●
●
● ●
●● ●●
●
●
●●
●
● ● ●●●●●
●
●●●
●
●
●● ● ● ●
●
● ●
●
● ●
●
●●
●
●● ●
●
●
●● ●●
●
●
●
●
●
●
●
●
●
●
●
●● ●●
●
● ●
●
●
●
●●
●
● ● ●●
●
●
●
●●
●●● ●● ● ●●
●
● ●● ●
●
● ● ● ●●● ●● ●●
●●
●● ●●
●●
●
●
● ● ● ●
●
●● ● ●●● ●●●●● ●
●
●
●●●
● ●● ●
●
●●
●
●
●
●
●
●
0.00
0.25
0.50
0.75
1.00
0.0 0.5 1.0 1.5
Distance
CladeConservationRate
0.25
0.50
0.75
1.00
q
Figure 6: Several clades of mammalian gut
bacteria are more conserved across host
samples than expected by chance. A phyloge-
netic permutational analysis was used to quanti-
fy whether the frequency with which a clade
was observed across Mammalian hosts (i.e.,
clade conservation rate) was greater than ex-
pected by chance. (Top) The clade conservation
rate is moderately inversely proportional to the
distance of the clade from the root of the 16S
phylogeny. Each point represents a clade and is
colored by its q-value corrected permutational
test p-value.The line of best fit is shown in black.
Many significantly conserved clades are ob-
served near the middle of the 16S phylogeny in-
dicating that they represent broad groups of
bacteria. Others appear closer to the tips, indi-
cating that they contain more specialized
groups of bacteria. (Bottom) The taxonomy of
each significantly conserved clade was charac-
terized based on the consensus of the taxonom-
ic annotations of all descendents. The Green-
Genes taxonomy was used as a reference in this
analysis. Bars correspond to taxonomic groups
that contain significantly conserved clades and
are colored by their taxonomic level. Notably,
the species Prevotella copri is significantly con-
served among the Primates.
Figure 7: Possible patterns of co-diversification be-
tween conserved gut microbiome clades and mam-
mals may exist. (Top) A co-phylogeny of gut microbi-
ome OTUs (left) and host mammals (right). Edges indi-
cate an OTU was found in a host. Only edges from OTUs
that are member of significantly conserved clades are
visualized (q < 0.2). (Bottom) An example of one clade,
which contains Ruminococcus
avefaciens, which is enriched among
the herbivores and known to be im-
portant to degrading plant cell walls.
[3]. Future work will quantify correla-
tions between host and clade phylog-
1. ClaaTU reveals how monophyletic clades of bacteria are distributed
across samples (https://github.com/chrisgaulke/Claatu).
2. This can clarify how bacteria respond to environmental variation
3. Applying this approach to the mammalian microbiome reveals highly
conserved clades of bacteria and potential patterns of co-diversification
and finds
We are grateful to E. Ho, R. Tanguay, C. Wong, L. Beaver, C. Barton, N. Kirchoff and C.
Armour for their assistance with varisous aspects of this project. This work is generously
supported by the National Science Foundataion (DEB 1557192).
References
[1] Muegge BD, et al. Diet drives convergence in gut microbiome functions across mam-
malian phylogeny and within humans. Science. 332(6032). 2011.
[2] Hedges SB, et al. Tree of Life Reveals Clock-Like Speciation and Diversification. Mol
Biol Evol. 32. 2015.
[3] Rincon MT, et al. A novel cell surface-anchored cellulose-binding protein encoded by
the sca gene cluster of ruminococcus avefaciens. Journal of bacteriology. 189 (13) 2007.
![An Ecophylogenetic Approach to Determine the Evolutionary History of the Mammalian Gut Microbiome
Christopher A. Gaulke(1), Holly Arnold(1), Steven W. Kembel(2), James P. O’Dwyer(3), Thomas J. Sharpton (1,4)
(1) Department of Microbiology, Oregon State University, Corvallis, OR, USA (2) Département des Sciences Biologiques, Université du Québec à Montréal, Montreal, QC, Canada
(3) Department of Plant Biology, University of Illinois, Urbana, IL, USA (4) Department of Statistics, Oregon State University, Corvallis, OR, USA
Abstract
ClaaTU: An Ecophylogenetic Microbial
Community Analysis Framework
Identifying those gut microbes that co-diversify with mammals is important to our un-
derstanding of the mechanisms and health implications of host-microbiome interac-
tions. For example, microbiota that are conserved across mammalian species may ex-
press a trait that has been subject to selection throughout the evolution of these mam-
mals, possibly because it is critical to health. While advances in environmental DNA se-
quencing have transformed our understanding of how enteric microbes are distributed
across mammalian species, these data are frequently analyzed using phylogenetically
agnostic approaches. Such approaches can obscure the detection of diverged groups of
bacteria that have been conserved across mammalian species.To provide enhanced res-
olution into evolutionary associations between gut microbiota and mammals, we inno-
vated a high-throughput ecophylogenetic method, known as ClaatTU (Cladal Taxonom-
ic Units). ClaaTU analyzes phylogenies assembled from environmental DNA sequences
collected from a set of microbial communities and profiles the presence and abundance
of each monophyletic clade in each community. As a result, it enables the identification
of specific microbial clades that are distributed across host communities in a manner in-
dicative of being associated with mammalian evolution. To demonstrate this, we ap-
plied ClaaTU to a mammalian microbiome dataset and (1) identified clades of gut bacte-
ria that are unique to groups of mammals based on their taxonomy or dietary regime, (2)
found that there exists ecophylogenetic structure in the mammalian gut microbiome,
indicating that gut bacterial phylogenetic diversity associates with host phylogeny, and
(3) discovered specific clades that are present in a larger number of mammals than ex-
pected by chance, some of which may co-diversify with their hosts. Our findings indi-
cate that some mammalian gut microbiota may have been anciently acquired and sub-
sequently retained in extant lineages, indicating that they may play an important role in
mediating host-microbiome interactions and maintaining host health.
Case Study: Conserved Responses to
Dietary Variation Among Monophyletic
Clades of Gut Bacteria
Summary
Acknowledgements
Ecophylogenetic Structure in the Mammalian
Gut Microbiome
Monophyletic Clades of Gut Bacteria
Are Conserved across Mammalian
Sample 1 Sample 2 Sample 3
1
2
3
4
5
6
7
Sample 1
Sample 2
Sample 3
Sample 1
Sample 2
Sample 3
1 2 3 4 5 6 7
2
2
2
2
0
0
2
2
0
2
20
0
0
01
1
0
1
1
1
Figure 1: Analysis of the ecological distribu-
tion of monophyletic clades (ecophylogenet-
ics) can reveal groups of organisms that ex-
hibit evolutionarily conserved functions that
impact their ecology. 16S sequences derived
from three different various communities (”Sam-
ples”) can be related via a phylogeny (solid lines)
or clustered into OTUs (red circles). In this exam-
ple, no OTU is common to all communities (red
arrows), but a monophyletic clade is (shaded
area), indicating that the common ancestor may
have evolved and subsequently maintained a
function critical to occupying these communi-
ties. Note that interesting clades (e.g., core
clades) may also be discovered at the sub-OTU
Figure 2: The ClaaTU workflow. The Cladal Taxonomic Units (ClaaTU) workflow quantifies the abundance of specific
clades in a user provided phylogenetic tree. ClaaTU first assigns identifiers to all internal clades on a phylogenetic tree and
then conducts a root-to-tip traversal of the tree to quantify the abundance of each clade by summing the counts of the de-
scendants. The output of ClaaTU is a clade abundance matrix, which logs the abundance of each clade in each sample.
Much like an OTU abundance matrix, these data can be used to identify clades that associate with samples, indicating their
interaction. Notably, ClaaTU can use data files produced by third party microbiome analysis software (e.g., QIIME and
Mothur) and analyze phylogenies assembled from OTU clustered sequences.
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
PC1
group
●
●
●
●
●
●
●
●
●
●
Artiodactyla
Carnivora
Diprotodontia
Hyracoidea
Lagomorpha
Perissodactyla
Primates
Proboscidae
Rodentia
Xenarthra
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
PC1
Diet
●
●
●
Carnivore
Herbivore
Omnivore
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
● ●
●●
●
●
●
PC1
Diet
●
●
●
Carnivore
Herbivore
Omnivore
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●●
●
●
●
●
●
PC1
group
●
●
●
●
●
●
●
●
●
●
Artiodactyla
Carnivora
Diprotodontia
Hyracoidea
Lagomorpha
Perissodactyla
Primates
Proboscidae
Rodentia
Xenarthra
Order
●
●
●
●
●
●
●
●
●
●
Artiodactyla
Carnivora
Diprotodontia
Hyracoidea
Lagomorpha
Perissodactyla
Primates
Proboscidae
Rodentia
Xenarthra
BushDog
Black Bear
Polar Bear
Spectacled Bear
Hyena
Lion
Horse
Zebra
Black Rhino
Okapi
Giraffe
Urial
Big Horn
Gazelle
Springback
Pig
Capybara
Squirrel
Rabbit
Orangutan
Gorilla
Chimpanze
Colobus
Baboon
Saki
Callimicos
Red Tailed Lemur
Black Lemur
Armadillo
Hyrax
African Elephant
Kangaroo
H C O
0
50
100
150
Diet Specific Clades
#CladesperHost
Diet
Art Car Pri
0
20
40
60
80
Order Specific Clades
#CladesperHost
Order
Unweighted
Clade Bray-Curtis
Weighted
Clade Bray-Curtis
ClusteringByHostOrderClusteringByHostDiet
Host Phylogeny
Figure 5: Gut microbiomes from 32 mammals were pro-
cessed with ClaaTU. 16S rRNA sequences that were originally
published in [1] were processed with ClaaTU as in Fig. 3. (Left)
The phylogeny of the host taxa as provided by [2]. (Right) The
distribution of clades unique to members of each host Order
(only Artiodactyla, Carnivora, Primates shown due to limited
sampling in other Orders) or diet (Herbivore, Carnivore, Omni-
vore) were quantified. Unique clades were normalized by
number of hosts to correct for sampling disparities. This analysis
reveals that different groups of hosts have acquired specialized
clades of bacteria.
Figure 6: Highly abundant gut microbiome clades sepa-
rate hosts by dietary preference while lowly abundant
clades separate by host taxonomy. The clade abundance
matrix produced by ClaaTU from the analysis of the 32 mam-
mals was used to calculate the weighted and unweighted
Bray-Curtis dissimilarity (BCD). PCoA was used to visualize re-
sults. Ellipses represent 95% confidence intervals and are sup-
pored by PERMANOVA analysis (p < 0.05). Separation among
groups is highest for unweighted BCD when clustering by
Order, and for weighted BCD when clustering by diet.
Z0220
Z0221
Z0222
Z0223
Z0224
Z0225
Z0226
Z0227
Z0229
Z0230
Z0231
Z0232
Z0233
Z0234
Z0235
Z0236
Z0237
Z0239
Z0240
Z0241
Z0242
Z0243
Z0244
Z0246
Z0247
Z0248
Z0249
Z0251
Z0252
Z0253
Z0254
Z0255
Z0256
Z0257
Z0258
Z0259
Z0260
Z0262
Z0263
Z0264
7 6 5 4 3 2 1 0
Color Key
log10 relative abundance
OTUPhylogenyAndAbundances
Clade Abundances
Standard
Lab Diet
Defined
High Zn
Defined
Low Zinc
Clade 1888 - A Subclade
within GammaproteobacteriaDefined Diet
Zinc Sufficient
MiSeq
QIIME OTU
Clustering
ClaaTU
Standard
Lab Diet
Defined Diet
Zinc Deficient
Figure 3: A Zebrafish Dietary Exposure
Study Design. Forty-five 5D line zebrafish
were fed one of three diets (3 tanks/diet): a
standard lab diet (Gemma Micro 300, a 130
mg/kg zinc), a defined diet with sufficient
levels of zinc (33 mg/kg), and a defined diet
with deficient levels of zinc (12.46 mg/kg).
Stool was collected through temporary isola-
tion of fish. Gut microbiomes were interro-
gated using V4 16S rRNA MiSeq sequencing,
QIIME (97% identity OTUs), and ClaaTU with
FastTree.
Figure 4: An example of a monophyletic clade that strati-
fies high and low zinc diets. A specific clade (1888, ingroup
above blue line) significantly differs in abundance between
the high (orange and blue) and low (green) zinc diets (krus-
kal-wallis p < 0.05). Notably, no single OTU reveals a signifi-
cant difference in association with zinc status.
Individuals
Significantly Conserved Clades
#Clades
0
2
4
6
8
10
12
Class
Order
Family
Genus
Species
Ruminococcacea
Lachnospiraceae
Clostridiales
Bacteroidales
Turicibacter
Alphaproteobacteria
Christensenellaceae
Eubacterium
biformeBlautia
DoreaPrevotella
Prevotellacopri
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●●
●
●●
●
●
● ● ● ●●
●
●
●
●●
●
● ● ●
●
●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●●
●
●●
●
● ●
●
●
● ● ● ● ●●●●●●
●
●
●●●
●●●●
●●
●
●
●
●
●
●
●
●●
●
●
●
●●●
●●
●
● ●●
●
●
●
●●
●
● ●●
●●
●
●
●● ●●●
●
●
●●
●
●
●
●
●
● ●
●
●●●
●
●●
●
●
●
●
●
●
●
●
●
● ● ●●●
●
●
●
●
●
●
●●●
●
● ●●
●
●●
●
●
●●● ●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
●
●●●●
●●
●● ●
●
● ●
●●●
●
●
●
●
●
● ●
●
●●
●
●
●
●
●●●
●
●
●
●
●
● ●
● ●
●●
●
●
●
●
●
●
●
●
● ●
●
●●
●
●
●
●
●
●●
● ●
●
●
●●
●
●
●●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●●
● ●
●
● ●
●
● ●
●
●
● ●
●
●
●
● ● ●
●
●
● ●
●
●
●
●●●
●
●
●
●
●● ●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●●●
●
●
● ●
●●
●
●
●
● ●
●●●
●●●
●
●
●
●
●●
● ●
●
●
●
●
●
●
●
● ●
●
●
● ●●
●
●●●
●
●
●
●●
●
●
●
●
●●● ●
●● ●
●
●
●
●
●
●
●
●●●
●
●
● ●
●
●
●
●● ●
●●
●
●
● ●
●● ●●
●
●●
●
● ●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
● ●●●●
●
●●
●
● ●
●●●●
●
●
●●
●●
●●●
●
●
●
●
●
●●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●●●
●●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●●● ●
●
●
● ●
●
●
● ●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●
● ●● ●
●
●
●
●● ● ●
●●
●● ●
●
●●●●
●
●
●
● ●●
●
●●●
●
● ●
●
●●● ●●●●●●●●●●●
●
●●
●
●
●●
●
●● ●
●
●●
●
●
●
●●
●
●
● ●
●
● ● ●
●
●
●
●
● ●●
●
●
●●●
●
●
●●
●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●
●● ●
● ●
●
●
●
●
●● ●
● ● ●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●● ●
●●
●●●
●
●
●
● ●
●
●
●
● ● ● ●
● ●
●●
●
●
●●
● ●
●●
●
●●●●
●●
●● ●
●
●
●●●● ●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●●
●
●
●
●
●
●
●
●
●●
● ● ● ● ●
●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●
● ●
●
●●
●
●
●
●
●
● ● ●
●
● ●
●
●
●
●
●
●●
●
●
●● ●
● ●●
●
●
●
●
● ●
●
●●
●●●
●
● ●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
● ●●● ●● ● ●●
●
●● ●●●
●
●
●●●
●
● ●●
● ●
●
●
●
● ● ●●
●
●
●
●
●●
●
●
●
● ●
●
● ● ●
●
●
●
●
●●
● ●
● ●●
●●
● ●
●●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ● ●
●
●
●
●
●
●
●
●
●●
●
●
●
●
● ●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●
●
●●
●
●
●
●●●
●
●
● ● ●
●
●
●
●
●
●●
●
●
●
● ●
●
● ●
●
●
●
●●
●
●
●●
●
●
●●● ●
●
●●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●
●
● ●● ●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
● ●
●
●●●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
● ●
●
●
●
●
●●
●
● ●●●
●
●
●●
●
●
●
●
●
●
●●
●
●●● ●
●●
●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●●●●
●●●
●
●
●● ●●●●●● ●
●
●●●●
●
●
●●
●
●
●
●
● ● ●
● ●●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ● ● ● ●● ● ●
● ●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
● ●●●
●● ●
●
●
●
●
●● ●
● ● ●● ●
●
●●
●
●●●
●
●
●
●
●●
●
●●
●
●
●
●
●
● ●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
● ●
● ●
●
●
●
●
●
●
●
●
●
●
● ●
●
● ●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
● ● ●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●●
● ● ●
●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
● ●●
●
●●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●●
●
●
●
●●
●
● ●●
●
●
●
●
●
● ●
●
● ● ● ● ●●
●
●
●
●●●
●
●
●
●
● ●
●
●
●●●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
● ●
● ●
●
●●
●●
●
●●
● ●
●
●
●
● ●
●
●
●
●
●
●
●●
●
●
●●
●
●
● ●
●
●
●
●
● ●
●
●
●●
●
●
●
●● ●
●
●
●
● ●
●
●
●
●●
● ●
● ●●
●
● ●
●
●
● ●
●●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
● ●
●
●
●●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●
●●
● ●●●●●
●●
●●●
●
●●●
●
●
●
●
●
●
●●
●
●
●
● ●
●
● ●
●
●
●● ●●
●
●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
● ● ●
●
●
●
● ●
●● ●
●
●●
●
●
●●●●●
●
●
●
●
● ●●●
●
●
●
●
●
●●●
●
●● ●●●●●
● ●●
●
●
●
●●
●
●
●●●● ●
●●
●●●
● ●●
●
● ●●
●
● ●●●●●●
●
●
●
●
●
●
● ●
●
●●●
●
●
●●
●
●
●●
●
●
● ●●●●
●●●● ●●●
●
●
●
●
●
● ●
●●
●●
●
●
●●
●
●●
●
●
●
●
● ●
●
●●
●
●
●
●●●●
●
●●
●
●
●●
●●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
● ●
●●
●
●
●
●●
●
●
●
● ●
● ●
●
●
●
● ● ●
●
●●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●●
●
● ●
●●●
●
●
●
●
●
●●●●
●
●
●
●
●
●
●
●
●
● ●
● ●
●
●
●
●
●
● ●●
● ●
●
●
●
●●
●
●
●● ●
●
●
●
●
●
●●
●
●
●
● ●
● ●
●
● ●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●●
●●●●●●
●
●
●
●
●●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
● ●
●
●
● ●
●
●
●
●
●●
●
●
●
●
●●
●
●●
● ●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●●
●
● ●
●●
●●
●
●
●
●●
●
●
●
●
●●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
● ●
●
●
●
●
●
●
●
● ●
●
● ●
●●●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●● ●
●
●
●
●●
●
●
●
● ●
●
●
●
●
●
●
●
● ●
●●
● ●
●
●
●
●●
●
●
●
●●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
● ●●
●
●
●
●
●
●
●●
●●●
●
●
●
●
● ●
●
●●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●●
●●●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●●
●
●●
●
●
●
●
●●●●
●
●●
●
●
●
●●
●
●●
●
●
●
●
●●
●
●
●
●●
●
● ●
●
●
●
●
●
●
●
●
●●
●
●● ●
●●
●●
●
●
●
●
●
●●
●
●
●
●
●
●
● ●
●
●
● ●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
● ● ●
●
●
●
●
●
●
● ●
● ●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
● ● ● ●
●
●
● ●
●
●
●
●
●
●●
●
●●
●
●
●
●●
●
●
●●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
● ●
●●
●
●
●
●
●● ●
●
●● ●●
●
●
●
●
●
●
●
●
●
●
● ●
●
● ●●
●
●● ●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●●
●
●
●
● ●
●● ●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
● ●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ● ● ●●
●
●
● ●● ●
●
●
●
●●
●
●
●
●●
●
●
●
●●●
●
●
●●●
●●
●●
●●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●●●●●
●●●
●
●
●
●
●
●
●●●
●●
●●
●
●
●
●
●●●●
●●
●
●
●
●
●
●●●
●●
●
●
●●
●
●
●
●●
●● ●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
● ●
●
●●
●
●
● ●
●
●
●
●
●
●
●●
●
●
●
●
●
● ●●●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●● ●●●● ●●
●
●
●
●
●
●
●
●●●
●
●
● ●
●●
●
● ●
●●
●
●
●
●
●
●
●
●
●
● ●
●●●
●
●● ●●●●●
●
●
●
●
●
●
●
● ●
●●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
● ●
●●
●
●
●
● ●
●
●
● ●●●
●
●
●●
●
●
●
●
●●●
● ●
●
●
●
●
●
●
●●●
●
●
●●
●
●● ●
●
●
●
●
●●●●●
●
●
●●
●
●
●
●
●●●
●
●
●
●
●
●●
●●
●●
●
●
●●
●
●
●
●
●●
●
●●●●
●●
●
●
●
●●
●
●
●●●
●
●
●●
●●
●
●●
●
●
●
●●
●
●
●
●
●
●●
●●●●
●
●
●
●
●
●●●
●● ●●●●
●
●
●
●●
●
●
●
●
●
●
● ●● ● ●
●
● ●
●
●
●
●
●●
●
●
●●
●●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
● ●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●●●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
● ●●●●
●
●
●
●
●
●
●
●
●●
●
●
●
●●
●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●● ●
●●
●●
●
●
●●
●
●
●
●
●
●●●
● ● ●
●
●
●
●
●●
●
●
●
●
●●●
●● ●
●
●
●●
●
●
●
●
●
●
●
●
● ● ●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
● ●
●
●●
●
●
●
●
●
●
●
●
●
●●
●
●●
●
●●
● ●
●●
●
●
●
●
●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
● ● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●●
●
● ● ●
●
●
●
●
● ●
●
●
●
●
●
●
●
● ●
●
●●
●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
● ● ●●
●
● ●
●
●
●
●
●● ●
●
●
●
●
●
●
●
●
●●
●
●
●
●●
●
● ●
●●●
●
●
●
●
● ●
●
●
●●
●
●
●
●●●●
●
●
●●
●●
●●
●●
●●●
●
●
●●
●
●
●
●
●
●
●
● ●
● ●
● ●
●
●
●●●● ●●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●● ●●
● ●●
●
●
●
●
●●
●
●
●
●
●●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
● ●
●
●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●● ●
●
●
●
●
●●
●
● ●
●
●●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●●
●
●●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●●●●
● ●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●●●
●●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●●●●●
●
●
●●
●
●●
●●
●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
● ●
● ●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●●
● ●
●●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●●
●●●
●
●
● ●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●●●●
●
●
●
●
●
● ●
●●
● ●
●
●●
● ●●●
●
●●
●
●
●
●●
●●
● ●●
●●
●
●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●● ●
●
●
● ●
●
●
●●
●
●
●
●
●
●
●
●
●●●
●●
●
●
●
●
●●
●
●
●
● ●
●
●
●
●
●
●●
●
●●●
●
●
●
●
●● ●
●
●
● ●
●
●
●●
●
●●●
●●
●
●
●
●
●
● ●●● ●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●●
●
●
●
●
● ●●
●
●
● ●
●
●● ●
●
●● ●
●
●●●
●
●●● ●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
● ● ●● ●● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●●
●
●●
●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●
●●
●
●
●● ●● ●
●
●
●
●●
●●
●
● ● ●
●
●
●
●
●
●
●
●
●●
●●
●
●
● ●●●●
●
●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●●●
●●
●●●●●
●
●
●
●
●
●
●
●
●
●
●
●● ●
●●
●
●
●
●
●
●
●
●
●
●●●●
●●
●
●
●●● ●●
●●
●
●
●
●
●
●
●●
●
●
●●
●
●
●
●●
●●
●
●
●
● ●
●
●
●●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●●●●
●●
●
●
●
●
●●
●
●●
●●
●●
●
●
●
● ●●
●
●
●
●
●
●
●
●
●●
●
●
●
●● ●
●
●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●●
●
●
●
●●
●
●●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●●●●●
●
●
●
●
●●
●●
●●
●
●
●●
●●●
●
●
●
● ●
●
●
●
●●
●●
●
●
●
●
●
●●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●●
●●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
● ●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
●●
●
●●
●
●●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
● ●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
● ●●●
●●
●●
●
●
●
●
●
●
● ●
●
●
● ●
●
●
●
●
●
●●
●
●
●●
●
● ●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
● ●
●
●
●
●●● ●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●● ●●
●
●
●
●
●
● ●
●
●
●
●● ●
●
●
●
●
●
●
●
●
● ●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●●●
●●●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●●●
●
●
●
● ●
●●
●●
● ●
●
●
●
●
●
●
●●
●
●●
●
●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
● ●
●
●
●
●
●
● ●
● ●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●
●●
●
●
●
●
●
●
●
●
● ●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●●
●
● ●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●●
●●
●
● ●
●
●
●
● ●
●
●
●
●
● ●
●
●● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●●●
●
●
●
● ●
●
●
●
●
●
●
●
●●
●
●
●
●●
●● ●
●●
●●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●
●
●
● ●
●
●●
●
●
●●●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●●
● ●
●●●●
●
●
●
●
●
●
● ●
●
●●
●
●
●
●
●
● ●
●
●
●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
● ●
●
●
●
● ●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●●
● ●
●
●
●
●
●
●
●
● ●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
● ●
●
●●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●● ●
●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
● ●
●●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
● ●●●
●
●
●
●
●
●●
● ●
●
●
●
●
●
●
●●●
●●
●
●
●●●
●
●
●
●
●
●●
●
●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●●
●
●●
●●●
●
●
●
●●
●●
●●
●
●●
●
●
●●
●
●●●
●●
●
●
●
●
●
●●
●●●
●●
●
●
●
●●
●
●●
●●
●
●
●
●
●
●
●
●
●●●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
●●●●●
●
●
●●
●●
●
●
●
● ●
●
●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
● ●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●●●●●
●●
● ● ●●
●
●●
●
●
●
●
●●●
●
●
●
●
●
●
●
●●
●
●●
●●
●
●
●
●
●
● ●
●
●
●
●
●
●●
●
●
●●
● ●
●
●●
●●
●
●●●●●● ●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
● ●●
●●
●
●
●
●
●
●
●
●
●
●
●
●●●●●
●
●
●
● ●
●
● ●
●
●
●
●
●
●
●
● ●●
●
●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●●
●
●
●
●● ●
● ●
●
●
●
●
●
●●
●
●
●
● ●
● ●
●
●●
●
●
●
●
●
●
● ●
●
●
●
●●
● ●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
● ●
●
●
●
●
●
●●
●
●
● ●
●
●
●● ●
●
●
●
●
●
● ●
●
●
●
●● ●●
●
●●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●● ●
●
●
●●●
●
●
●●
●
●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●●
●
●
●
●
●●●
●
●
●●
●
●
●
●
●●
●
●●
●●
●●
●
●●
● ●
●
●
●●
●
●
●
●●●
●
●
●
●
●
●●●
●
●
●
●●
●
●
●
●
●●
●
●
●
●●
●
●
●
●
●●
●
●●
●
●●
●
●
●
●
●
● ●
●
●
●
●
●
●
●●
●
●
●
●
●●
●
●●
●
●●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●●●
●
●●
●
●
●
●
●
●
●
●
● ●●
●
●
●
●
●
●
●
●●●●
● ●
●●●
●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●●
●
●
●●
●
●
●●●
●
●
●
●●
●●
●
●
●
●●●
●
●
●
●
●●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●●
●●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●●
●●
●
●●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●●
●
●●
●
●
●
●
●
●● ●●
●
●●
●●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●●
●
●
● ●●●
●
●●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●●
●● ●
●
●
●
●
●
●
●
●
●●
●
●
●●
●●
● ●● ●●
●
●●●
●
●●●
●
●●
●
●
●●
●
●
●
●
●
●
● ●
●
●●
●
●
●
●●●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●
●
●
●
●
● ●
●●
●
●
●
●
●
●
●● ● ●
●
● ●●●
●
●
●●
● ●●
●●●●
●
●
●
● ●
●
●●●●● ● ●
●
●
●
●
●
●●
●
●
●●● ●
● ●●
●●●●
●
●
● ●●
●
●
●
●
●
●
●
●
●
●
●
●●
●● ●
●
●●● ●●
●
●●●●●●●●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●●
●
●
●
● ●
●
●●
●●●●●●●
●
● ●● ●●●● ●
● ●
●
●●
●●
● ●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
● ● ●
●
●
●
●●
●●
●●
●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
● ●●
●
●● ● ● ●
●●
●
●
●●●
●
● ●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●●
●
●
●●
●
●
●
●
●
●
●●
● ●● ●●●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●
●
●●
●
●
●
●
●
●
●
●
●●●
●
●●●
●●
●
●
●●●
●
●
●
● ●
●
●●
●
●
●● ●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●●●
●●
●
●
●●
●
●
●
●●
●
●●
●
●
●
●
●
●
●
●
●
●
●●●
●
●●
●
●
●●
●
●
●
●●
●
●●
●●●●
●
●●
●●
●
●
●
●
●●
●
●●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●●
●
●
●●
●●
●
●
●
●●
●●●●●●
●
●
●
●
●
●
●●
●
●
●
●
●
●●
●
●
●●
●
●
●
●
●
●
●
● ●●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●●●
●●
●●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●●●
●●
●
●●
●
●
●
●
●
●●
●
●
●●
●
●
●
●●
●
●
●
●
●
●
●●
●
●●●
●
●
●●
●
●
●
●
●
●
●●
●●●
●
●
●
●
●
●
●
●
●
●●
●
●
●●
●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●●●
●
●
●
●
●
●
●
●
● ●
●
●
●● ● ●
●
●●●
●
●
●●
●
●
●
●●●
●●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●
●
●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●●
●●
●
●
●
●
●
●●
●
●
●
●
●
●
●
●●
●
●●●●
●
●
●
●
●
●
●●
●
●
●
● ●●
●
●
● ●
●
●
●
●● ●●●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●
●
●
●
●
●● ●
●
●
●●
●
● ●
● ●
●●
●
●
●
●
●
●
●●
●●●
●
●
●
●
● ●
● ●
●●●
● ● ●
●
●
●●
●● ●
●
●
●
●
●
●
●
●
●● ●
●
●●
●
● ●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
● ●
●
●
●●●
●
●
●
●
●
●
●●
●
●
●
●
●
●●●
●
●
●
●●
●
●
●
●
●
●
●
●
●● ●
● ●●
●
●
●
● ●
●
●
●
● ●
●
●
●
●
●
●
●
●
●
●
●●● ●
●
●
● ●
● ● ●●●●
●
●●
●
●
●
●
●
●
● ●
●● ●●
●
●
●●
●
● ● ●●●●●
●
●●●
●
●
●● ● ● ●
●
● ●
●
● ●
●
●●
●
●● ●
●
●
●● ●●
●
●
●
●
●
●
●
●
●
●
●
●● ●●
●
● ●
●
●
●
●●
●
● ● ●●
●
●
●
●●
●●● ●● ● ●●
●
● ●● ●
●
● ● ● ●●● ●● ●●
●●
●● ●●
●●
●
●
● ● ● ●
●
●● ● ●●● ●●●●● ●
●
●
●●●
● ●● ●
●
●●
●
●
●
●
●
●
0.00
0.25
0.50
0.75
1.00
0.0 0.5 1.0 1.5
Distance
CladeConservationRate
0.25
0.50
0.75
1.00
q
Figure 6: Several clades of mammalian gut
bacteria are more conserved across host
samples than expected by chance. A phyloge-
netic permutational analysis was used to quanti-
fy whether the frequency with which a clade
was observed across Mammalian hosts (i.e.,
clade conservation rate) was greater than ex-
pected by chance. (Top) The clade conservation
rate is moderately inversely proportional to the
distance of the clade from the root of the 16S
phylogeny. Each point represents a clade and is
colored by its q-value corrected permutational
test p-value.The line of best fit is shown in black.
Many significantly conserved clades are ob-
served near the middle of the 16S phylogeny in-
dicating that they represent broad groups of
bacteria. Others appear closer to the tips, indi-
cating that they contain more specialized
groups of bacteria. (Bottom) The taxonomy of
each significantly conserved clade was charac-
terized based on the consensus of the taxonom-
ic annotations of all descendents. The Green-
Genes taxonomy was used as a reference in this
analysis. Bars correspond to taxonomic groups
that contain significantly conserved clades and
are colored by their taxonomic level. Notably,
the species Prevotella copri is significantly con-
served among the Primates.
Figure 7: Possible patterns of co-diversification be-
tween conserved gut microbiome clades and mam-
mals may exist. (Top) A co-phylogeny of gut microbi-
ome OTUs (left) and host mammals (right). Edges indi-
cate an OTU was found in a host. Only edges from OTUs
that are member of significantly conserved clades are
visualized (q < 0.2). (Bottom) An example of one clade,
which contains Ruminococcus
avefaciens, which is enriched among
the herbivores and known to be im-
portant to degrading plant cell walls.
[3]. Future work will quantify correla-
tions between host and clade phylog-
1. ClaaTU reveals how monophyletic clades of bacteria are distributed
across samples (https://github.com/chrisgaulke/Claatu).
2. This can clarify how bacteria respond to environmental variation
3. Applying this approach to the mammalian microbiome reveals highly
conserved clades of bacteria and potential patterns of co-diversification
and finds
We are grateful to E. Ho, R. Tanguay, C. Wong, L. Beaver, C. Barton, N. Kirchoff and C.
Armour for their assistance with varisous aspects of this project. This work is generously
supported by the National Science Foundataion (DEB 1557192).
References
[1] Muegge BD, et al. Diet drives convergence in gut microbiome functions across mam-
malian phylogeny and within humans. Science. 332(6032). 2011.
[2] Hedges SB, et al. Tree of Life Reveals Clock-Like Speciation and Diversification. Mol
Biol Evol. 32. 2015.
[3] Rincon MT, et al. A novel cell surface-anchored cellulose-binding protein encoded by
the sca gene cluster of ruminococcus avefaciens. Journal of bacteriology. 189 (13) 2007.](https://image.slidesharecdn.com/asm2016sharptonposter-160619105808/85/An-Ecophylogenetic-Approach-to-Determine-the-Evolutionary-History-of-the-Mammalian-Gut-Microbiome-ASMMicro2016-1-320.jpg)
