O R I G I NA L A RT I C L E
doi:10.1111/evo.12169
EVOLUTION OF HABITAT PREFERENCE AND
NUTRITION MODE IN A COSMOPOLITAN
FUNGAL GENUS WITH EVIDENCE OF
INTERKINGDOM HOST JUMPS AND MAJOR
SHIFTS IN ECOLOGY
Priscila Chaverri1,2 and Gary J. Samuels3
1
Department of Plant Science and Landscape Architecture, University of Maryland, 2112 Plant Science Building, College
Park, Maryland 20742
2
3
E-mail: [email protected]
United States Department of Agriculture, Agricultural Research Service, Systematic Mycology and Microbiology
Laboratory, 10300 Baltimore Avenue, Building 010A, Room 213, Beltsville, Maryland 20705
Received August 12, 2011
Accepted May 14, 2013
Host jumps by microbial symbionts are often associated with bursts of species diversification driven by the exploitation of new
adaptive zones. The objective of this study was to infer the evolution of habitat preference (decaying plants, soil, living fungi,
and living plants), and nutrition mode (saprotrophy and mycoparasitism) in the fungal genus Trichoderma to elucidate possible
interkingdom host jumps and shifts in ecology. Host and ecological role shifts were inferred by phylogenetic analyses and ancestral
character reconstructions. The results support several interkingdom host jumps and also show that the preference for a particular
habitat was gained or lost multiple times. Diversification analysis revealed that mycoparasitism is associated with accelerated
speciation rates, which then suggests that this trait may be linked to the high number of species in Trichoderma. In this study
it was also possible to infer the cryptic roles that endophytes or soil inhabitants play in their hosts by evaluating their closest
relatives and determining their most recent ancestors. Findings from this study may have implications for understanding certain
evolutionary processes such as species radiations in some hyperdiverse groups of fungi, and for more applied fields such as the
discovery and development of novel biological control strategies.
KEY WORDS:
Adaptive radiation, Ascomycota, horizontal gene transfer, Hypocrea, phylogenetics, speciation.
Host jumps or shifts by microbial symbionts are often associated
with bursts of species diversification driven by the exploitation of
new adaptive zones (Schluter 2000; Fordyce 2010). Most shifts
occur among closely related host taxa, for example, from one
plant/animal host species or genus to another, whereas interkingdom host jumps are less frequent. Interkingdom host jumps in the
kingdom Fungi have occurred within the Clavicipitaceae sensu
lato, shifting from insect associates to plant biotrophs or fungi-
C
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2013 The Author(s).
Evolution
coles and vice versa (Nikoh and Fukatsu 2000; Spatafora et al.
2007; Kepler et al. 2012). Others have reported an organism as
being associated to both living animals and dead plant material,
such as the human pathogenic fungus Coccidioides spp. However, more recent studies using genome analyses revealed that
Coccidioides spp. evolved to remain associated only with their
dead animal hosts in the soil, disproving previous reports about
their ability to be saprophytic (Sharpton et al. 2009).
P. C H AV E R R I A N D G . J. S A M U E L S
Species of the cosmopolitan fungal genus Trichoderma
(Ascomycota, Pezizomycotina, Sordariomycetes, Hypocreales,
Hypocreaceae; sexual stage Hypocrea) are principally known
as soil inhabitants but they are also found as plant decomposers (saprotrophs), and parasites of other fungi (mycoparasites = fungicoles; Chaverri and Samuels 2003; Samuels 2006;
Jaklitsch 2009). They are occasionally isolated as human
pathogens from immunocompromised patients (Walsh et al. 2004;
Kantarcioglu et al. 2009). Species of the genus often interface
with human activities and therefore have an important economic
impact. For example, T. reesei is a well-known producer of industrial cellulases (Schuster and Schmoll 2010); some species
are used in the biological control of fungal-induced plant disease (Harman and Kubicek 1998; Harman et al. 2004); whereas
other species remediate soils contaminated with hydrocarbons
(Argumedo-Delira et al. 2009). The fact that many Trichoderma
species have antifungal or plant-growth–stimulating activities has
led to their widespread investigation and application as biological control agents (Harman and Kubicek 1998; Harman et al.
2004).
Many studies report single species of Trichoderma as being both saprotrophic and mycoparasitic (Samuels et al. 1998;
Chaverri and Samuels 2003; Jaklitsch et al. 2008; Jaklitsch 2009).
However, this is unlikely because rarely an individual species can
obtain nutrients, through direct associations, from organisms of
completely unrelated kingdoms. The true ecological role, that is,
mycoparasitism or saprotrophy, of some Trichoderma species is
sometimes difficult to ascertain. Natural populations of Trichoderma are generally concealed within soils, wood, or living plants
(as endophytes; Chaverri and Samuels 2003; Evans et al. 2003;
Samuels 2006; Jaklitsch 2009; Fig. 1). In many cases, the Trichoderma fruiting structures are not obviously growing on other
fungi (Fig. 1). This makes it difficult to determine whether they
are parasitic on hyphae of another fungus or decomposing dead
plants. Trichoderma species rarely occur as primary or pioneer
colonizers of recently dead plant material and are most commonly found sporulating in old-secondary to old-growth forests
(Chaverri and Vı́lchez 2006). This suggests that Trichoderma
parasitize fungi that were the primary colonizers and decomposers of plants. The problem of determining the cryptic role of
Trichoderma becomes more complicated when studies may fail
to discriminate cryptic species, each with more restricted ecological roles. For example, one study concluded that the fungus
Tuberculina, known as a parasite of rust fungi, is a synonym of
Helicobasidium, which is found in spermatophytes (Lutz et al.
2004). In this study, the authors used the nuclear ribosomal DNA,
which in most cases is too conserved to reveal closely related
species. Cryptic speciation is common in Trichoderma (Chaverri
et al. 2003; Chaverri and Samuels 2003; Druzhinina et al.
2010).
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Fruiting structures of Trichoderma (Hypocrea). (A)
Hypocrea state of Trichoderma ceramicum. (B) Longitudinal section
Figure 1.
of the fruiting structure of T. ceramicum showing that it is growing on a pigmented fungus (arrow) possibly in the Ascomycota.
(C) Hypocrea state of Trichoderma chromospermum (black arrow)
clearly growing on another ascomycetous fungus (white arrow).
(D) Trichoderma sp. tuft (arrow) on well-rotten wood where it is
not clear of it is decaying wood or parasitizing dark hyphae of
other fungi.
Because Trichoderma species were only recently reported as
endophytes, it is not clear what their functions are in regards
to their hosts or the environment. In recent years, species of
Trichoderma have been shown to be among the most abundant
avirulent endosymbionts (endophytes) in stems (vascular cambium and phloem) of various woody plants (Evans et al. 2003;
Mahesh et al. 2005; Crozier et al. 2006; Gond et al. 2007; Verma
et al. 2007; Gazis and Chaverri 2010). The number and diversity of
these horizontally transmitted endophytic species of Trichoderma
has grown tremendously (e.g., Holmes et al. 2004; Samuels et al.
2006; Verma et al. 2007; Hanada et al. 2008; Chaverri et al. 2011)
since Evans et al. (2003) discovered members of the genus to
dominate the mycobiota of sapwood of healthy trees of the tropical tree Theobroma gileri. The ecological costs and benefits of
endophytes are not well understood, but several studies suggest
they may be latent pathogens (Petrini 1986; Carroll 1988; Clay
1993; Saikkonen et al. 1998; Rojas et al. 2010), saprotrophs (Hyde
et al. 2007; Promputtha et al. 2007, 2010), or mutualists that protect plants against diseases or herbivores (Carroll 1988; Arnold
et al. 2003; Evans et al. 2003; Schulz and Boyle 2005; Bailey
et al. 2008). The same uncertainty about the ecological role of endophytes also applies to Trichoderma species found in the soil. In
this environment it is unclear whether they are actively obtaining
nutrients from decomposing plant material or from other microorganisms that live in the soil, or if they exist primarily in their latent
T R I C H O D E R M A E VO L U T I O N
stages using adapted structures for survival (e.g., chlamydospores
or conidia).
The functions of organisms in an ecosystem are influenced
by adaptation to the environment and shared ancestry (Powell
et al. 2009; Parrent et al. 2010). Therefore, tracing the evolution
(e.g., through phylogenetic analyses) of certain niche traits in
Trichoderma may provide insight into the functional ecology of
these ubiquitous and cosmopolitan fungi (Saunders et al. 2010).
These particular traits would include nutrition mode, host or substrate preference, and specificity. For example, some Trichoderma
species that occur as endophytes or as soil inhabitants are also reported as mycoparasites or saprotrophs. This suggests that one
species is able to occupy multiple niches or live in different types
of substrata. The life cycles of fungi can include an endophytic
stage that may lead them to become saprotrophs at host senescence or pathogens when conditions are suitable (Petrini 1986;
Schulz and Boyle 2005; Promputtha et al. 2007; Parfitt et al.
2010). Several studies support the hypothesis that saprotrophic
fungi with an endophytic stage have an advantage over those
that are exclusively saprotrophs (Müller et al. 2001; Parfitt et al.
2010). This means that when the plant dies they represent the first
colonizers of the decaying plant material. Several other Trichoderma species are exclusively known as mycoparasites (Samuels
et al. 2000, 2002; Overton et al. 2006), sometimes with antifungal
properties (Harman and Kubicek 1998; Elad 2000; Harman et al.
2004). This suggests that many species in the genus, including the
endophytes and soil inhabitants, potentially protect the host plant
from infectious diseases.
The objective of this study was to reconstruct the phylogeny
of Trichoderma spp. and infer the evolution of their (1) habitat
preference (decaying plants, soil, fungi, and living plants); and
(2) nutrition mode (saprotrophy and mycoparasitism). These objectives were addressed through the phylogenetic analyses of five
genes for 143 taxa, ancestral character reconstructions, and diversification analyses. The results of this study may also provide clues about the ecological roles of endophytic and soil
Trichoderma species. The facts that these species are abundant
endophytes, especially in natural tropical forests where the impacts of plant diseases are much lower than in plantations (Evans
et al. 2003; Mahesh et al. 2005; Gond et al. 2007; Verma et al.
2007; Gazis and Chaverri 2010), and that many have antifungal or mycoparasitic characteristics, suggest that they might not
be neutral symbionts, but rather act as mutualists that provide
protection against pathogens. The results may also clarify the
cryptic function the apparently saprotrophic species play. In addition, this study can provide a framework for predicting biological control activity of individual species in those groups
and for understanding certain evolutionary processes such as
species radiations and adaptation in some hyperdiverse groups of
fungi.
Materials and Methods
TAXON SAMPLING
Data matrices for 143 Trichoderma taxa were assembled for five
unlinked loci: α-actin (act), calmodulin (cal), internal transcribed
spacers of the nuclear ribosomal DNA (ITS), RNA polymerase
II subunit 2 (rpb2), and translation elongation factor 1-α (tef1;
Table S1). Taxon sampling attempted to include most described
species of Trichoderma spanning all life styles and substrata (i.e.,
endophytes, mycoparasites, and plant saprotrophs and soil inhabitants). Approximately 200 species of Trichoderma have been
described (Index Fungorum, indexfungorum.org). Each taxon included in the analyses represents a species either previously defined by a combination of morphological and phylogenetic data or
only by Genealogical Concordance Phylogenetic Species Recognition (GCPSR; Taylor et al. 2000), a concept widely used in
fungi. In this study, GCPSR was used especially in the species
complexes Trichoderma harzianum, Trichoderma hamatum, Trichoderma ovalisporum, and Trichoderma spirale. However, data
for each of these species complexes are not presented here because their taxonomy is beyond the scope of this study and are
being treated in separate publications (Chaverri and Samuels,
in prep.). Because putative species within the above-mentioned
species complexes have not been officially named, in this article
they are labeled informally as, for example, T. cf. harzianum01,
T. cf. harzianum02, etc.
SOURCE OF FUNGAL STRAINS
Specimens and living cultures of various Trichoderma species
were obtained from decaying plant material such as wood, bark,
and twigs; from soil; from other fungi; and from live stem
tissues of the vascular cambium and phloem ( = sapwood). The
Trichoderma strains from decaying plant material and from other
fungi were obtained over several years from several sources
using techniques similar to those described in Chaverri and
Samuels (2003). Endophytic strains were obtained by isolating
them from living sapwood tissue using techniques described in
previous publications (Kowalski and Kehr 1996; Evans et al.
2003; Gazis and Chaverri 2010). Fungal cultures are stored
at University of Maryland and the Systematic Mycology and
Microbiology Laboratory (USDA-ARS-SMML) in 20% glycerol
cryovials at −80◦ C, or in public culture collections such as
the American Type Culture Collection (ATCC, Manassas,
VA); Agriculture and Agri-Food Canada National Mycological
Culture Collection (DAOM; Canada); and the Centraalbureau
voor Schimmelcultures (CBS; Utrecht, the Netherlands).
DNA EXTRACTION, POLYMERASE CHAIN REACTION,
AND SEQUENCING
Fungal strains were grown in 6-cm-diameter Petri dishes containing DifcoTM potato-dextrose-broth. Plates were incubated at
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P. C H AV E R R I A N D G . J. S A M U E L S
25◦ C for ca. 1 week. DNA was extracted from mycelial mats
harvested from the surface of the broth. The PowerPlantTM DNA
Isolation Kit (MO BIO Laboratories, Inc., Carlsbad, CA) was
used to extract DNA from the samples. DNA sequences of act
(ca. 700 bp); cal (ca. 500 bp); ITS, including 5.8S of the nuclear
ribosomal DNA (ca. 600 bp); rpb2 (ca. 900 bp); and tef1 (ca.
600 bp) were used in the phylogenetic analyses. The primers used
were: for act, TRI-ACT1, TRI-ACT2, act500, act511 (Carbone
and Kohn 1999; Samuels and Ismaiel 2009); for cal, cal-228, cal737 (Carbone and Kohn 1999); for ITS, ITS5, and ITS4 (White
et al. 1990); for rpb2, rpb2–5f1 and frpb2–7cr (Liu et al. 1999);
and for tef1, ef-728M, ef2, ef700f, tef1r (Carbone and Kohn 1999;
Rehner 2001). Each 25 μL polymerase chain reaction (PCR) reR Green Master Mix (Promega
action consisted of 12.5 μL GoTaq
Corporation, Madison, WI), 1.25 μL forward primer, 1.25 μL of
reverse primer, 1 μL of the DNA template, 1 μL of dimethyl
sulfoxide, and 8 μL of sterile RNAase-free water. Polymerase
chain reaction reactions were run in an Eppendorf Mastercycler
ep using standard protocols previously described (Chaverri et al.
2003; Chaverri and Samuels 2003; Samuels and Ismaiel 2009).
Polymerase chain reaction products were digested with ExoSAPR (USB Corporation, Cleveland, OH) and sequenced at the
IT
DNA Sequencing Facility (Center for Agricultural Biotechnology,
University of Maryland, College Park, MD) and at the Systematic Mycology and Microbiology Laboratory (USDA, Beltsville,
MD). Sequences were assembled and edited with Sequencher 4.9
(Gene Codes, Madison, WI). Sequences produced for this study
and additional sequences were deposited and obtained from GenBank (Table S1).
PHYLOGENETIC ANALYSES
Basic analyses
The included sequences were aligned with Simultaneous Alignment and Tree Estimation (SATé; Liu et al. 2009) using MAFFT
(Katoh et al. 2005) as the external sequence alignment tool and
RAxML (Stamatakis 2006) as the tree estimator. Simultaneous
Alignment and Tree Estimation is an automated method that
quickly and accurately estimates both DNA alignments and trees
with the maximum likelihood (ML) criterion. Where needed,
the alignment was improved by hand with Seaview version 2.4
(Galtier et al. 1996) and MESQUITE version 2.75 (Maddison
and Maddison 2011). Ambiguously aligned, low-complexity and
poly-A/T regions were manually excluded from all analyses
(30 bp in ITS, 22 bp in cal, and 569 bp in tef1 were excluded
from alignments; tef1 alignments included many indels due to
high variation in the introns). Alignments have been deposited in
TreeBase under submission number S13888.
Maximum likelihood and Bayesian inference (BI) analyses
were performed with all sequences, first with each gene/locus
separately, and then with the concatenated data sets. For both
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EVOLUTION 2013
analyses, data were partitioned by gene and by codon position.
JMODELTEST (Posada 2008) was used to select the models of
nucleotide substitution for the ML and BI analyses. Once the likelihood scores were calculated, the models were selected according
to the Akaike Information Criterion (AIC). Following jMODELTEST model selection, the parameters indicated in Table S2 were
used for the ML and BI analyses.
GARLI-PART version 0.96 (Zwickl 2006) was used for
the ML and bootstrap (BP) analyses through the Grid computing (Cummings and Huskamp 2005) and The Lattice Project
(Bazinet and Cummings 2008), which includes several clusters
and desktops in one encompassing system (Myers et al. 2008).
GARLI-PART allows for ML analysis with partitioned data as
mentioned earlier. In GARLI-PART, the starting tree was obtained by stepwise addition and the number of runs or search
replicates was set to 50. Bootstrap analyses were replicated 2000
times. Bayesian inference analysis was performed with MrBayes
version 3.1.2 (Huelsenbeck et al. 2001; Ronquist 2004) also with
the partitioned data. Two independent analyses of two parallel
runs and four chains were carried out for 25,000,000 generations.
Analyses were initiated from a random tree and trees were sampled every 1000th generation. Convergence of the log likelihoods
was analyzed with TRACER version 1.5 (Rambaut and Drummond 2009). The first 20% of the resulting trees were eliminated
(= “burn in”). Both runs were pooled and a consensus tree (“sumt”
option) and posterior probabilities (PP) were calculated in MrBayes. Hypomyces aurantius and Sphaerostilbella aureonitens
were used as outgroup because they are sister taxa to Trichoderma
(Sung et al. 2007).
PHYCAS version 1.1.2 (www.phycas.org) was used as
another tree searching method and also to resolve possible
polytomies (“Star Tree Paradox” problem; Lewis et al. 2005).
PHYCAS uses reversible-jump MCMC (RJ-MCMC) to allow
unresolved (trees with polytomies or very short and poorly supported branches) and fully resolved tree topologies to be sampled
during a BI analysis. Unresolved trees generally occur when the
time between speciation events is so short or the substitution rate
so low that no substitutions occurred along a particular internal
edge in the true tree. For this analysis, the RJ-MCMC run was set
to disallow for polytomies. The number of cycles in PHYCAS was
set to 100,000, sampling every 100 cycles, and with a starting tree
obtained randomly. TRACER was also used to analyze convergence of log likelihoods. A 20% burn-in was used. A consensus
tree and posterior probabilities were automatically calculated in
PHYCAS. Only S. aureonitens was used as outgroup as allowed
by PHYCAS.
Data compatibility
A reciprocal 70% ML BP threshold (de Queiroz 1993; MasonGamer and Kellogg 1996; Reeb et al. 2004) was used to determine
T R I C H O D E R M A E VO L U T I O N
if partitions could be combined into a single phylogeny. Two thousand BP replicates were generated with GARLI during an ML tree
search. A conflict was assumed to be significant if two different
relationships for the same taxa—one being monophyletic and the
other nonmonophyletic, both with BP ≥ 70%—were observed
on each of the act, cal, ITS, rpb2, and tef1 majority-rule consensus trees. In the absence of conflict between highly supported
clades among individual gene genealogies, the loci sequenced
were assumed to share similar phylogenetic histories, and thus
were combinable. The concatenated data were used for building
phylogenetic trees.
ANALYSES OF CHARACTER EVOLUTION (CHARACTER
STATE CODING AND ANALYSES)
Likelihood and Parsimony ancestral character reconstructions
(ACRs) were conducted for two traits to trace (1) the evolution
of habitat preference (trait 1) and (2) the evolution of nutrition
mode (saprotrophy vs. mycoparasitism) (trait 2). Habitat preference (trait 1) specifically refers to where the fungus was found
which could then reflect a preference toward a certain lifestyle or
substrate. This trait does not directly reveal from which organism
the fungus is obtaining nutrients (e.g., a decaying plant or a fungus). For trait 1, character states were coded as binary characters
for the ACR likelihood analyses (Table S3). Some species may
have more than one character state because they have been found
on various habitats. The character states were coded as follows:
on decaying plant material = 0: absent, 1: present; in soil = 0:
absent, 1: present; on other fungi = 0: absent, 1: present; in living plant tissues (as endophytes) = 0: absent, 1: present. For the
Parsimony ACR, characters were coded as multistate as follows:
on decaying plant material = 1, in soil = 2, on other fungi = 3,
in living plant tissues = 4.
Trait 2 (nutrition mode) refers to the organism from which
the fungus is obtaining nutrients (e.g., a decaying plant or a fungus), and should not be misinterpreted as only symbiosis with
plants and fungi. The species may be obtaining nutrients from
a dead plant (saprotrophy) or parasitizing another fungus (mycoparasitism). Ancestral character reconstructions of this trait might
clarify the evolution of saprotrophy and mycoparasitism in Trichoderma. Character states for trait 2 were coded as saprotrophy =
0, mycoparasitism (living fungus host, fungicole) = 1, or undetermined = ? (Table S3). The “undetermined” classification refers
to those taxa where it is not possible to precisely define the host,
as in the case of species that fruit or sporulate on decaying plant
material may actually be mycoparasitic. The codification done by
this and previous studies (Chaverri and Samuels 2003; Jaklitsch
2009) is based on macroscopic observations of fruiting bodies
growing near other fungi, on microscopic observations of longitudinal sections of the fungus and its substrate, or on assumptions
based on the close phylogenetic relationship with other mycopar-
asitic species. Similarly, some species found in the soil might not
be saprotrophs, but may be necrotrophic or parasitic on other soil
microorganisms (Lumsden and Locke 1989; Sharon et al. 2001;
Prasad et al. 2002; Berg et al. 2005; Samuels 2006). In this study,
if a taxon is reliably known to occur on other fungi, then it was
coded as “1.” If the taxon is on other substrata, it was either coded
as (a) “?” (undetermined), if it is in a clade or closely related to
other taxa that are clearly mycoparasitic; or as (b) “0” (saprotroph) if it belongs to a major clade of only taxa on decaying plant
material; the hypothesis being that closely or phylogenetically
related taxa will have the same function or trait due to shared ancestry (Powell et al. 2009; Parrent et al. 2010). Once a priori ACR
analyses were performed for trait 2, the results were then used to
assign character states to the undetermined state (“?”). Then, once
again, ACR analyses were conducted on trait 2 (nutrition mode
“a posteriori”). Table S3 indicates all the characters and states for
both traits.
Ancestral character reconstructions were integrated over
1000 post-burnin trees with the best log-likelihoods obtained
from the BI analyses. Two methods for ACR were used and compared: (1) an ML approach (Schluter et al. 1997; Pagel 1999);
and (2) a Parsimony method (Fitch 1971), both implemented in
MESQUITE. In MESQUITE, the option, “trace character over
trees” under “analysis” was selected to reconstruct ancestral character states assuming an Mk1 class model and unordered characters. Parsimony reconstructions were optimized using “most parsimonious reconstructions” (MPRs) option in MESQUITE. The
“Summarize State Changes Over Trees” option in MESQUITE
was used to summarize ancestral state changes over a series of
trees, that is, 1000 trees. For the ML method, a threshold (T) of
two or more log-likelihood units was set to decide whether an ancestral state is supported over another; states with log-likelihoods
higher (worse) than the best by T or more are not included in the
estimate (Pagel 1999).
SPECIATION RATE ANALYSES
It has been proposed that ecologically driven diversification may
result in changes in average diversification rate coincident with
shifts in morphology, life history, or ecology (Alfaro et al. 2009;
Wiegmann et al. 2011). In this study, the effect of shifts between
being a mycoparasite to/from a saprotroph and diversification rate
was tested. First, the association between the mycoparasitism trait
(Trait 2 a posteriori) and speciation rate using binary-state speciation and extinction analysis (BiSSE; Maddison et al. 2007) was
tested. The analysis was implemented in MESQUITE using the
BiSSE Ln Likelihood Difference calculation with a likelihood
ratio test (LRT). This method describes diversification across a
phylogeny in terms of six parameters: speciation rate (λ1 and λ0 ),
extinction rate (μ1 and μ0 ), and transition rate between states
(from 1 to 0, q10 ; from 0 to 1, q01 ). Here, the binary states are
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T R I C H O D E R M A E VO L U T I O N
“mycoparasitism” (state 1) and “not mycoparasitism” ( = saprotrophy) (state 0). In this analysis, the likelihood difference was
used to answer whether speciation rate in mycoparasitic taxa was
equal to the saprotrophic ones (H0 : λ1 = λ0 ). The BiSSE parameters in the constrained case (λ1 = λ0 ) were calculated. One
thousand trees and characters were simulated. An LRT of the difference between the unconstrained six-parameter model (H1 : λ1
= λ0 ) and a constrained five-parameter model (H0 : λ1 = λ0 ) was
done. The focus was on speciation rate rather than net diversification rate (speciation rate–extinction rate: r = λ − μ) because the
interest is specifically in the effect of mycoparasitism on speciation rates and because of several limitations in estimating extinction rate in extant phylogenies (Ricklefs 2007; Rabosky 2010).
The transition rates focusing on the ratio of the transition rate away
from the mycoparasitism state to the transition rate toward the
mycoparasitism state (q10 /q01 ) were also calculated. For this, the
BiSSE parameters were calculated over 1000 trees obtained from
the BI analysis. The resulting value is indicated as the mean ± SD.
SELECTION ANALYSES
A test for detecting episodic diversifying selection was done to infer possible adaptive evolution. Adaptive evolution frequently occurs in episodic bursts limited to a few sites in a gene and to a small
number of lineages in a phylogenetic tree (Messier and Stewart
1997). A branch-site model (“Branch-Site REL,” Kosakovsky
Pond et al. 2011) implemented in the software HyPhy version
2.1.2 (Pond et al. 2005) was used to detect episodic selection. With
this method one can infer at what point in the evolutionary history
of sequences did selection occur. This branch-site model extends
Felsenstein’s pruning algorithm to allow efficient likelihood computations for models in which variation over branches and sites
is described in the random effects likelihood (REL). Branch-site
REL performs likelihood ratio tests to identify the lineages in a
phylogeny where a proportion of sites evolves with dN/dS > 1.
In this case, the instances of episodic (dN/dS varies across the
tree) diversifying selection at a proportion of sites (dN/dS varies
across sites). For these analyses, the nucleotide sequences (with
introns excluded) of the protein-coding genes act, cal, rpb2, and
tef1 were used. Each gene was analyzed separately. A maximum
parsimony phylogenetic tree for each gene was constructed with
PAUP version 4.0a126 using a heuristic search, with a starting tree
obtained via stepwise addition, 1000 random addition sequences,
and TBR branch-swapping algorithm.
Results
PHYLOGENETIC ANALYSES AND DATA
COMPATIBILITY
The reciprocal 70% ML BP threshold test for determining data
compatibility revealed no significant topological incongruence.
Therefore, the matrices were combined and phylogenetic analyses
were run with the concatenated data. Maximum likelihood and BI
analyses produced phylogenies with similar topologies (Fig. S1).
Differences were seen in the BP and posterior probability (BI
PP) values. Most nodes are supported by at least one analysis, in
most cases, in PHYCAS. The analysis in PHYCAS significantly
increased support for some nodes that were not supported by ML
BP and/or BI PP (Fig. S1).
EVOLUTION OF HABITAT PREFERENCE
Ancestral character reconstructions show that a preference for a
particular habitat was gained or lost multiple times in the evolution of the genus (Tables S4 and S6). The majority of the shifts
occurred from decaying plant material to soil (6–22 changes) or
from decaying plant substrate to fungi (7–28 changes), followed
by from soil to endophyte (2–15 changes) and from fungi to decaying plant material (0–9 changes; Table S5). The least number
of changes occurred from endophyte to fungi (0–2 changes) and
from endophyte to decaying plant material (0–4 changes; Table
S5). In Figure 2, 76 species are labeled as collected on decaying
plant material, 46 spp. on other fungi (fungicoles, mycoparasites),
43 spp. in soil, and 20 spp. that are endophytic (in living plant
tissues). Species that live in decaying plant material and in soil do
←−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−
Evolution of nutrition mode (plant = saprophytism or fungus = mycoparasitism) and habitat preference (decaying plant
material, soil, fungi, living plant) in Trichoderma. Results of ancestral character reconstructions are illustrated on a consensus phylogeny
of the Bayesian inference (BI) analysis (see supplementary material for details of results of each analysis). Color of branches represents the
Figure 2.
nutrition mode (plant saprotrophy or mycoparasitism) of the ancestor at that node. A black branch means an equivocal reconstruction or
an absent node. Circles with node numbers are colored according to the hypothesized habitat preference of the ancestor at that particular
node; for example, preference to live in soil, on decaying wood, on other fungi, or in living plant tissues as endophytes. Empty/white
circles represent equivocal reconstructions. If no circles are present is because that particular node was not supported by posterior
probabilities or BP. Column on the right of the taxon names indicates the substrate/habitat where these species have actually been
found. Assignment of character states is based on the consensus of both analyses: parsimony and likelihood. Negative log likelihoods (as
numbers on branches) and average probabilities (as pie charts) across 1000 trees are included for selected nodes where a major transition
may have occurred. Node 243 does not have a pie chart because the probability is 1 for the mycoparasitism character state. Genomes
sequenced in Kubicek et al. (2011) are highlighted in gray. Species or nodes with preliminary evidence of episodic diversifying selection
are highlighted in yellow or with a yellow arrow, respectively.
EVOLUTION 2013
7
P. C H AV E R R I A N D G . J. S A M U E L S
not form a monophyletic group, and they are scattered throughout
the phylogeny. By contrast, mycoparasitic species are concentrated in particular groups, for example nodes/clades 17, 42, 68,
149, 196, and 243, among other smaller ones. The most ancestral
species, including the outgroup taxa (Hypomyces and Sphaerostilbella) are mycoparasites. Species that become endophytic are
less common and can be mostly found in nodes/clades 48, 89, 175,
and 197. In ACR analyses, out of the total number of nodes in
Figure 2, the majority (58) of the character states of the ancestors
were resolved as on decaying plant material, followed by on other
fungi (34), in soil (19), and endophytic (5). Results of parsimony
and likelihood ACR analyses for trait 1 are presented in Tables
S4 and S6, respectively.
EVOLUTION OF NUTRITION MODE (SAPROTROPHY
OR MYCOPARASITISM)
A priori and a posteriori ACR analyses of trait 2 resolved most
nodes. A priori analyses of trait 2, including character states that
were undetermined, resulted in the majority of the ancestral nodes
with a resolved character state, with 0–5 changes from mycoparasitism to saprotrophy; and 0–5 changes from saprotrophy to mycoparasitism (Tables S7–S10). With these results, character states
were assigned to those taxa that had undetermined character states
(“?”) and ACR analyses were re-run (a posteriori). The a posteriori ACR analyses of trait 2 resolved most nodes to a particular
major nutrition mode and thus ecological role (Tables S11 and
S13), with 1–4 (avg. = 2) changes in MPR and 0–3 (avg. = 0.66)
changes in likelihood, from saprotrophy to mycoparasitism; and
1–4 (avg. = 2) changes in MPR and 0–3 (avg. 1.67) changes in
likelihood, from mycoparasitism to saprotrophy (Tables S12 and
S14). The results of ACR analyses show that the basal species
of Trichoderma, including the outgroup taxa, are associated with
or parasitize other fungi (Fig. 2). Although Hypomyces delicatula, Hypomyces subalpina, and Hypomyces parmastoi have not
been observed to parasitize other fungi (they occur on decaying
plant material), based on the ACR results, it can be hypothesized
that they are actually parasitizing hyphae of other fungi that are
growing within the decomposing tissues of the plant. Ancestral
character reconstruction analyses also show that association with
plants (i.e., saprotrophy or plant necrotrophy, because no Trichoderma species have been reported as plant pathogens) evolved at
least twice (nodes 130 and 157), and then reversed to mycoparasitism possibly twice (nodes 197 and 243; Fig. 2, Tables S12 and
S14). These results support at least four interkingdom host jumps
or major shifts in nutrition mode and ecological role.
DIVERSIFICATION AND SELECTION ANALYSES
Ancestral character reconstructions show that multiple shifts from
saprotrophy (state 0 = decaying plant host) to/from mycoparasitism (state 1 = fungal host) occurred. Whether these shifts and
8
EVOLUTION 2013
nutrition mode (Trait 2 a posteriori) had an effect on speciation
rates was tested. Results from BiSSE Ln Likelihood Difference
analysis show that mycoparasitism is associated with higher speciation rate (λ0 = 18.47; λ1 = 26.78; μ0 = 4.61 × 10−5 ; μ1 =
7.34; q01 = 2.05; q10 = 0.26; LRT P < 0.0001; Fig. S2). The
ratio of transition rate away from mycoparasitism to the transition
rate toward mycoparasitism (q10 /q01 ) was 0.30 ± 0.08, indicating that rapid speciation rates were favored by the transitions to
mycoparasitism.
Based on the above results, it can be inferred that rapid speciation in Trichoderma is occurring as a result of adaptive evolution,
that is, species of Trichoderma possibly becoming better suited to
its shifting host or substrate. To support the hypothesis of adaptive evolution, the occurrence of episodic bursts of diversifying
selection were assessed. Preliminary evidence of episodic diversifying selection was found in rpb2 and tef1 in two and four
lineages/nodes, respectively (Tables S15 and S16). Cal and tef1
showed a large proportion of nodes/lineages with most of their
sites undergoing strong diversifying (positive) selection (cal: 0.45,
tef1: 0.57; Fig. S3). In cal, a similar proportion of nodes/lineages
suggest purifying (negative) selection (0.56, Fig. S3). In contrast,
rpb2 and act showed a large proportion of nodes/lineages experiencing purifying selection (rpb2: 0.98, act: 0.88; Fig. S3). The
mean ω across all sites, nodes/lineages, and genes is 2.69, indicating weak diversifying selection. Even though there is some
evidence that fungal antibiosis has an effect on elongation factors
(Dominguez et al. 1998), the genes used for this analysis are regarded as “house-keeping” genes. Additional genes that encode
enzymes involved in interactions with the host or substrate (e.g.,
cellulases, chitinases, or proteases) could then be used to confirm
the results obtained here.
Discussion
EVOLUTION OF NUTRITION MODE, MAJOR HOST
AFFILIATION, AND ECOLOGICAL ROLE (PLANT
SAPROTROPHY VS. MYCOPARASITISM)
Ancestral character reconstructions support at least four interkingdom host jumps in Trichoderma, two from fungus to plant
and two from plant to fungus. This also means that at least four
major shifts in nutrition mode and ecological role occurred, two
from mycoparasitism to saprotrophy and two from saprotrophy
to mycoparasitism. To date, no other studies reported a fungus
being both mycoparasitic and saprotrophic. Therefore, it is likely
that there were several host jumps in this genus. This is the first
report of such phenomenon within the same genus. Interkingdom
host jumps have been reported in closely related fungal genera
or families (e.g., Clavicipitaceae sensu lato; Nikoh and Fukatsu
2000; Spatafora et al. 2007). A recent study of three Trichoderma genomes (Trichoderma atroviride, Trichoderma reesei, and
T R I C H O D E R M A E VO L U T I O N
Trichoderma virens) found that mycoparasitism-specific genes
were prevalent in T. atroviride and T. virens (nodes 200 and 124,
respectively, in Fig. 2), and lost in T. reesei (node 138 in Fig. 2;
Kubicek et al. 2011), supporting the host shifts hypothesized in
this study. In Kubicek et al. (2011), some of the genes that are
expanded in mycoparasitic species, such as T. virens and T. atroviride, are proteases. These proteases are involved in degradation
of proteins, a major trait of mycoparasites (Seidl et al. 2009).
They also found an increase in chitinolytic enzymes and some
β-glucanase containing glycoside hydrolase families, which are
involved in destruction of the fungal cell walls.
High speciation rates and episodic diversifying selection is
some of the evidence presented here that suggests species radiations in Trichoderma. The higher speciation rates that resulted
from transitions from saprotrophy (plant host/substrate) to mycoparasitism (fungal host/substrate) concur with previous studies
that host shifts are often associated with bursts of species diversification (Schluter 2000; Fordyce 2010). In this case, diversification
was possibly driven by the exploitation of new adaptive zones. The
new adaptive zones may be the fungi, which have higher diversity when compared to plants. There have been some estimates
that fungi outnumber plants 6 to 1 (Hawksworth 1991). However, more recent studies propose that this ratio is much higher
(Blackwell 2011). Thus, Trichoderma has had many more hosts
to exploit. In addition, Trichoderma can parasitize both members
of the Ascomycota and Basidiomycota, a trait that is rare or absent
in its ancestors. Ascomycota is considered the phylum with the
most species (Blackwell 2011). The closest relatives and ancestors of Trichoderma are mostly parasites of Basidiomycota and
with much less species than the estimated 200+ spp. in Trichoderma, for example, Hypomyces: ca. 100 spp.; Sphaerostilbella:
7 spp.; and Arachnocrea: 1 spp. (Rossman et al. 1999 and Index
Fungorum).
Rapid speciation or radiation is also evidenced by the low
support for some parts of the backbone of the Trichoderma phylogeny produced in the present and previous studies (Kindermann
et al. 1998; Kullnig-Gradinger et al. 2002; Chaverri and Samuels
2003; Jaklitsch 2009). If host shifts facilitate rapid diversification,
there is the expectation that branches on the tree following a host
shift will be relatively short (Schluter 2000). However, alternative
hypotheses should also be considered, such as incomplete lineage
sorting (Kubicek et al. 1996; Lübeck et al. 2000; Leschen and
Buckley 2007; Kubicek et al. 2011), introgression/hybridization
(Mäntylä et al. 1998; Schluter 2000; Polizzi et al. 2011), incomplete reproductive isolation (Mäntylä et al. 1998; Lübeck et al.
2000; Fordyce 2010), and incomplete taxon sampling or choice
of genetic markers (Sharpton et al. 2009).
It is not clear how interkingdom host jumps occurred. A few
studies with animal pathogens (human/primates-viruses) suggest
that rapid evolution within pathogen lineages allow for host jumps
across large evolutionary distances (Davies and Pedersen 2008).
The potential contact between the pathogen and a novel host is
likely to be greatest where infected and noninfected species occur
in sympatry, thus increasing the chance for a host jump (Fenton
and Pedersen 2005). The consequences of such pathogen host
jumps can vary. The infection of the new host may be ephemeral
(Daszak et al. 2000) or may be maintained independently in both
host species resulting in a net host range expansion and potentially leading to the manifestation of the disease in the new host
species (Fenton and Pedersen 2005). In concordance with the
above phenomenon, it is possible that host jumps from fungus to
decaying plant occurred because ancestral mycoparasitic species
of Trichoderma were parasitizing hyphae immersed in the decaying plant substrates. However, it seems that such shifts to
saprotrophy are transient in some groups of Trichoderma since
at least two reversals from saprotrophy to mycoparasitism occurred (nodes/clades 197 and 243; Fig. 2). This phenomenon can
further be explained by the “host habitat hypothesis” first defined by Nikoh and Fukatsu (2000). It is also based on the idea
that the sympatric co-habitation will increase chances for host
jumps. This hypothesis explains two interkingdom host jumps in
fungi: (1) parasitic species in Elaphocordyceps jumping between
cicada nymphs and false truffles (both chitin based) due to their
co-occurrence near plant roots (Nikoh and Fukatsu 2000); and
(2) the multiple shifts from animal (insects) to plant hosts in the
Clavicipitaceae due to the closeness between sap-feeding insects
(e.g., scale-insects) and their plant hosts (Kepler et al. 2012).
Preliminary evidence suggests that ecological evolution in
Trichoderma resulted from a combination of mutations, duplications, and losses of genes that have been vertically inherited from
the common ancestor of Ascomycota and Basidiomycota, as well
as at least one event of horizontal gene transfer (HGT) from Basidiomycota to Trichoderma (Covert et al. 1992; Slot and Hibbett
2007; Floudas et al. 2012). Through phylogenetic analyses, Slot
and Hibbett (2007) found that the nitrate assimilation gene cluster
(fHANT-AC) was transferred horizontally from the Basidiomycota to Trichoderma reesei. In that study, they suggested that the
gain of nitrate assimilating ability contributed to the success and
improved fitness of T. reesei in a new niche. In this case, the
new niche or ecological role may have been plant saprotrophy.
However, HGT might not always be the case. A recent study of
31 fungal genomes found that 20 gene families encoding carbohydrate active enzymes and oxidoreductases implicated in wood
decay are shared between T. reesei and diverse Agaricomycetes
(Floudas et al. 2012); no evidence of HGT was detected in that
study. Similarities of cellulolytic cellobiohydrolase I (cbh1) genes
of T. reesei and the wood-decaying basidiomycete Phanerochaete
chrysosporium have also been noted (Covert et al. 1992). Cbh1 is
involved in cellulolytic activity, thus, wood decay ability. Further
studies are needed to determine if genes such as cbh1, may have
EVOLUTION 2013
9
P. C H AV E R R I A N D G . J. S A M U E L S
also been horizontally transferred from basidiomycetes. Horizontal gene transfer may have occurred because the most ancestral
species of Trichoderma were mycoparasitic on basidiomycetous
hosts (e.g., H. alcalifuscescens, H. americana and related species,
H. cinereoflava, H. fomiticola, and H. moravica, among others).
Ecological proximity and hyphal anastomosis are some of the
mechanisms linked to horizontal gene transfer (see review in
Fitzpatrick 2012).
In addition to hosts occurring in sympatry, other factors may
have facilitated host shifts and thus ecological speciation in Trichoderma. Many fungi, and in this case Trichoderma, possess
several unique and remarkable attributes that give them the ability
to locally adapt to their hosts. Some of those attributes are: frequent asexual reproduction with rare events of sexual reproduction
(Druzhinina et al. 2010); production of a large amount of spores,
which increases adaptive variation input by mutation (Gao and
Liu 2010); and mating within the host, which creates pleiotropic
interactions between host specificity and assortative mating
(Giraud et al. 2010). In the fungal pathogen Colletotrichum
kahawae, immigrant inviability and a predominantly asexual
lifestyle may have been influential in driving speciation by creating pleiotropic interactions between local adaptation and reproductive patterns (Silva et al. 2012).
EVOLUTION OF HABITAT PREFERENCE
Various publications have hypothesized that Trichoderma is undergoing rapid speciation (Kullnig-Gradinger et al. 2002; Chaverri
and Samuels 2003; Kubicek et al. 2008; Druzhinina et al. 2010).
Trichoderma is a species-rich genus, containing 200 or more
species. This rapid gain of species may have been due to adaptive
radiation because Trichoderma species are able to live in all latitudes and longitudes, and temperatures, but especially because
they inhabit many types of substrata or ecological niches. Results
from this study support the hypothesis that Trichoderma species
can be mycoparasitic on many diverse species of fungi (e.g., Basidiomycota and Ascomycota), saprotrophic, and can live asymptomatically in the tissues of living plants (endophytic). In contrast,
the closest relatives of Trichoderma are strictly fungicolous (e.g.,
Arachnocrea, Hypomyces, and Sphaerostilbella), specifically on
basidiocarps of Agaricomycetes (Basidiomycota; Rogerson 1970;
Rossman et al. 1999); as mentioned before, these close relatives
have a much lower number of species.
In general, it can be inferred that the different habitat preferences have been gained and/or lost multiple times in Trichoderma
evolution. These habitat preference shifts are evidently an active
process in Trichoderma. It has previously been suggested that although symbiotic lineages (i.e., endophytes) frequently give rise
to saprotrophs, reversions to symbiosis are rare (Arnold et al.
2009). This is not the case here. In Trichoderma, multiple rever-
10
EVOLUTION 2013
sions from saprotrophy/mycoparasitism to endophytism exist, and
species that may become endophytic are in more derived groups.
It is still unknown why so many species (ca. 18 spp. in Fig. 2)
of Trichoderma are exclusively isolated from soil. It is possible
that these species are adapted to hyperparasitize or obtain nutrients from other soil organisms such as Phytophthora, Pythium,
Rhizoctonia, and nematodes, among others (Hallmann and Sikora
1996; Harris and Lumsden 1997; Gracia-Garza et al. 2003; John
et al. 2010). Other soil-borne Trichoderma species can also occur
on decaying plant material (saprotroph) or on other fungi, which
can be used to infer the function of these soil species.
EVOLUTION AND ECOLOGICAL ROLE
OF ENDOPHYTIC TRICHODERMA
Recent studies have shown that endophytic Trichoderma spp. in
wild trees might be more common than previously thought. Results from this study show that endophytic species are present in
more derived clades. This presents some evidence to support a
hypothesis that these endophytic species evolved from ex planta
species that settled in a new adaptive zone: the endophytic niche.
The role these endophytic Trichoderma spp. play in the environment or in their plant hosts is only just beginning to be unraveled.
Some experimental studies show that endophytic Trichoderma
spp. protect the host against infection by fungal pathogens (Evans
et al. 2003; Bailey et al. 2008; Mejia et al. 2008), promote plant
growth (De Souza et al. 2008), and reduce drought stress (Bae
et al. 2009). Based on the results from this study, it is possible to
infer and predict that some endophytic Trichoderma species may
be saprotrophic or mutualistic. That is, some species may be (1)
latent saprotrophs, for example, T. protrudens and T. brevicompactum, “awaiting” for plant host death to start the decomposition
process (Müller et al. 2001; Hyde et al. 2007; Promputtha et al.
2007; Parfitt et al. 2010); (2) mutualists, protecting the host plant
from diseases; or (3) latent mycoparasites, “awaiting” for plant
death and infection by primary or pioneer decomposers which
can then be parasitized by Trichoderma (Chaverri and Vı́lchez
2006; e.g., Trichoderma amazonicum; T. cf. harzianum 01, sp.04,
sp.06, sp.07, sp.10; T. cf. spirale02; and Trichoderma evansii;
among others).
IS IT POSSIBLE TO PREDICT THE ECOLOGY OF A
SPECIES AND ITS PRACTICAL APPLICATIONS BY
USING ITS EVOLUTIONARY HISTORY?
Increasing availability of phylogenetic data and bioinformatics
tools have facilitated a rapid expansion of studies that apply phylogenetics and evolutionary biology to ecology (Cavender-Bares
et al. 2009; Parrent et al. 2010) and agriculture (Saunders et al.
2010). Researchers are using phylogenetic tools to generate hypotheses about relationships between taxa and their ecological
functions. Because recently diverged taxa tend to be ecologically
T R I C H O D E R M A E VO L U T I O N
similar (Darwin 1859; Lord et al. 1995; Kraft et al. 2007), a direct
link may exist between the evolutionary relationship of organisms in a community, the traits they possess, and the ecological
processes that determine their distribution and abundance.
In this study we inferred the role Trichoderma endophytes
play in their hosts by taking into account the ecology of their
closest relatives and most recent ancestors. For example, many
endophytic species of Trichoderma may be fungicolous and thus
may protect the host plant from disease. The mechanisms by
which endophytic Trichoderma spp. protect plants remain unclear. Antifungal mechanisms in Trichoderma may be manifested
through antibiosis, by producing antifungal compounds (Howell
and Stipanovic 1991; Harman et al. 2004; Bailey et al. 2008), mycoparasitism (Elad 2000; Mishra et al. 2000; Bailey et al. 2008;
John et al. 2010), nutrient competition (Simon and Sivasithamparam 1989), and/or by triggering localized or plant-wide defense
mechanisms (or induced resistance; Harman et al. 2004; Bailey
et al. 2008). Some studies showed that exclusively endophytic
Trichoderma species might more efficiently trigger either localized or plant-wide defense mechanisms (or induced resistance)
than those that are not endophytic (Harman et al. 2004; Bailey
et al. 2008). Findings from the current and other supporting studies may have implications for the discovery and development of
novel biological control strategies against plant diseases. Species
phylogenetically associated with mycoparasitic taxa or that belong in the major mycoparasitic groups (e.g., clades/nodes 17,
42, 68, 149, 196, and 243 in Fig. 2) uncovered in this study may
have greater biocontrol potential than those that are related to
saprotrophs.
In the same manner, it might be possible to infer the nutritional mode of cryptic mycoparasites living in the soil or in decaying plant material. For example, H. eucorticiodes is reported
as a saprophyte on wood (Jaklitsch 2009). However, results from
this study show that this species clusters with a clade of mycoparasites descended from a mycoparasitic ancestor. It is likely that
Hypocrea eucorticioides shares this trait and parasitizes hyphae
of other fungi growing vegetatively in the decaying plant material.
This phenomenon has been observed previously for other species
(Chaverri and Samuels 2003). Two other examples, Trichoderma
tomentosum and Trichoderma velutinum are closely related to mycoparasites and have mycoparasitic ancestors; therefore, they may
be parasitizing other soil fungi. Trichoderma ghanense, whose
closest relatives are saprophytes on wood, may also be a saprotroph decomposing plant material in the soil. Its soil stage could
also act as inoculum that will eventually be dispersed to a rotting
piece of wood. Close relatives of T. ghanense, most notably T.
reesei, are well known for their ability to produce cellulases and
other wood degrading enzymes (Kubicek et al. 1996; Mäntylä
et al. 1998).
Although evolutionary studies such as the one presented here
may provide better insights into the ecology and practical applications of this ubiquitous fungal genus, empirical and experimental
studies still need to be undertaken to precisely determine the roles
Trichoderma species play in the environment. We propose that
this analysis be used as a guide to continued discovery of biological and ecological potential in Trichoderma and possibly other
economically important genera of fungi.
ACKNOWLEDGMENTS
The authors thank F. Lutzoni (Duke University); S. Rehner (Agricultural Research Service, United States Department of Agriculture [ARSUSDA]); graduate students (C. Salgado, C. Herrera, D. Skaltsas, S.
Linares) and post-doc (Y. Hirooka) in the “journal club” at UMD (“Advances in Research” PLSC 789A) and anonymous reviewers for their
very helpful comments on this article. The authors also thank O. Liparini
Pereira (Univ. Federal de Viçosa, Brazil) for providing the image Figure
1D. The authors greatly appreciate their collaborators around the world
for providing specimens and cultures of Trichoderma. The authors acknowledge A. Ismaiel (ARS-USDA) for his help in DNA sequencing.
This project was funded in part by National Science Foundation grants
DEB-9712308 to GJS and ELS, DEB-925672 to PC, and DEB-1019972
to PC.
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Associate Editor: S. Remold
Supporting Information
Additional Supporting Information may be found in the online version of this article at the publisher’s website:
Figure S1. Bayesian inference (BI) phylogram from act, cal ITS nrDNA, rpb2, and tef1 sequence data.
Figure S2. Distribution of P-values for likelihood ratio test (LRT) of BiSSE Ln Likelihood Difference (λ0 = λ1 )
Figure S3. Summarized results of Branch-Site REL diversifying selection analysis.
Table S1. Taxa and strains used in the analyses with their corresponding GenBank accession numbers.
Table S2. Results of model estimation under Akaike Information Criterion (AIC; jMODELTEST) for each of the partitions.
Table S3. Taxa and character state coding.
Table S4. Results of parsimony ancestral character reconstruction for trait 1 (habitat preference), optimized using most parsimonious reconstruction (MPR).
Table S5. Summary of changes over trees in character (trait 1, habitat preference), for parsimony ancestral character reconstruction
(ACR).
Table S6. Results of maximum likelihood ancestral character reconstruction for trait 1 (habitat preference).
Table S7. Results of parsimony ancestral character reconstruction for trait 2 (nutrition mode), a priori, optimized using most
parsimonious reconstruction (MPR).
Table S8. Summary of changes over trees in character (trait 2, nutrition mode), a priori, for parsimony ancestral character
reconstruction (ACR).
Table S9. Results of maximum likelihood ancestral character reconstruction for trait 2 (nutrition mode), a priori.
Table S10. Summarizing changes over trees in character (trait 2, nutrition mode), for likelihood ancestral character reconstruction
(ACR), a priori.
Table S11. Results of Parsimony ancestral character reconstruction for trait 2 (nutrition mode), a posteriori, optimized using most
parsimonious reconstruction (MPR).
Table S12. Summarizing changes over trees in character (trait 2, nutrition mode), a posteriori, for parsimony.
Table S13. Results of maximum likelihood ancestral character reconstruction for trait 2 (nutrition mode), a posteriori.
Table S14. Summarizing changes over trees in character (trait 2, nutrition mode), for likelihood ancestral character reconstruction
(ACR), a posteriori.
Table S15. Results of Branch-Site REL analysis on the rpb2 data set.
Table S16. Results of Branch-Site REL analysis on the tef1 data set.
EVOLUTION 2013
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