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Ecological structuring of yeasts associated with trees around Hamilton, Ontario, Canada

Harinad Maganti, David Bartfai, Jianping Xu
DOI: http://dx.doi.org/10.1111/j.1567-1364.2011.00756.x 9-19 First published online: 1 February 2012


This study seeks to determine the distribution and diversity of yeasts in and around the Hamilton area in Canada. In light of the increasing number of fungal infections along with rising morbidity and mortality rates, especially among the immunocompromised, understanding the diversity and distribution of yeasts in natural environments close to human habitations has become an increasingly relevant topic. In this study, we analyzed 1110 samples obtained from the hollows of trees, shrubs, and avian droppings at eight geographical sites in and around Hamilton, Ontario, Canada. A total of 88 positive yeast strains were isolated and identified belonging to 20 yeast species. Despite the relative proximity of the sampling sites, our DNA fingerprinting results showed that the yeast populations were highly heterogenous. Among the 14 tree species sampled, cedar, cottonwood, and basswood hollows had relatively high yeast colonization rates. Interestingly, Candida parapsilosis was isolated almost exclusively from pine trees only. Our results are consistent with microgeographic and ecological differentiation of yeast species in and around an urban environment.

  • yeast diversity
  • internal transcribed spacer
  • yeast-tree association
  • microgeographic structuring


Yeasts are known to inhabit a wide range of ecological niches. They are found in both terrestrial and aquatic environments which include those with extreme conditions such as deep-sea hydrothermal vents, polar soils, and extremely acidic continental waters (Gadanho and Sampaio, 2005; Gadanho et al., 2006; Connell et al., 2008). Some yeasts in the Ascomycota and Basidiomycotas phyla have been isolated from a wide variety of surfaces such as those of leaves, rotting wood, and soil, where recent evidence has shown that they play significant ecological functions (Lachance et al., 2001; Fraser et al., 2006; Boby et al., 2008; Cloete et al., 2009; Rodrigues et al., 2009). In addition, yeasts have been isolated from beetle guts and have been found to play an integral role in the beetle's ability to utilize wood as part of its diet (Tanahashi et al., 2010). This ability of yeasts to degrade and draw nutrients from certain complex organic molecules is speculated to play an important role in the distribution of these and other microscopic eukaryotes. For example, yeasts have been shown to possess different abilities to degrade and utilize nutrients such as lipids, hemicellulose, xylan, and ferulic, hydroxycinnamic, gallic, and tannic acids (Middlehoven, 1997; Bhadra et al., 2008). The variable degrading abilities of yeasts could contribute to differences in yeast species compositions found among microbial communities in soil and rotting wood environments (Middlehoven, 1997; Inacio et al., 2002; Sláviková et al., 2007).

Population studies of yeasts have shown a surprising amount of variation in yeast species composition among neighboring regions. In soil populations of yeasts, variations in pH, nitrogen concentration, and water saturation could impact the quantity and composition of yeast populations (Yarwood et al., 2009). While most yeasts are able to tolerate a wide range of environmental conditions, barriers to their spread over even relatively short distances do exist. For example, the Cryptococcus gattii outbreak on Vancouver Island, British Columbia, which began in 1999 has yet to establish a stable and comparable reservoir on the mainland or any other neighboring islands (Fraser et al., 2006; Byrnes & Heitman, 2009; MacDougall et al., 2011). Given the ability of C. gattii to spread via airborne or waterborne spores as well as many anthropomorphic routes, this failure to colonize nearby landmasses may be due to mechanisms other than that of its ability to disperse over natural barriers (Fraser et al., 2006; Kidd et al., 2007).

The failure to migrate and colonize new niches has been observed within established populations of microorganisms, especially those competing for similar nutrients. In these cases, established populations may be better adapted to the particular niche or climate than new migrants and can outcompete and prevent the spread of new populations to those niches (Lachance et al., 2003). For example, population dynamics studies of Aureobasidium pullulans have shown that resident populations of this yeast are highly resistant to immigrant invasions, even if they are from the same yeast species (Woody et al., 2007). In most geographic areas, not only fungal (including yeast) populations often contained a high degree of intraspecific diversity, but also these communities are rarely homogeneous and frequently contain very different species compositions (Nakase, 2000; Inacio et al., 2002). Even for strains belonging to the same species from a single ecological niche, a measurable genetic variability could still be found, often with their degrees of genetic relationship correlated with geographic distances (Johnson et al., 2004; Koufopanou et al., 2006). However, most recent studies have focused on natural environments far from human habitations. In this study, we attempted to survey the diversity of fast growing nonfermentative yeasts in and around an urban area in Hamilton, Ontario, Canada. To avoid confounding factors in our analyses, our focus will be on tree hollows. Tree hollows have been found to be a significant reservoir for the human fungal pathogens Cryptococcus neoformans and C. gattii (Randhawa et al. 2010). We were specifically interested in not only the yeast species distribution patterns but also the potential genetic variability within individual species to determine whether frequent anthropogenic activities could obscure the potential genetic differentiations among the different sites in the urban environment. Yeasts were isolated from eight sites within and around Hamilton, and their species designation was identified based on sequences at the internal transcribed spacer (ITS) region. In addition, DNA fingerprinting was used to determine their genotypes. Yeast species diversity, distribution, and their genetic variation were analyzed and compared between the geographic sites and host trees.

Materials and methods

Sample collection

Yeast samples were collected between 26 May 2008 and 28 September 2008 from eight sites within and around Hamilton: Site A (43.24028, −79.8873), Site B (43.2565, −79.86715), Site C (43.27793, −79.97966), Site D (43.24747, −79.7489), Site E (43.26191, −79.9193), Site F (43.26286, −79.92069), Site G (43.26910, −79.9031), and Site H (43.22990, −79.9760) (Fig. 1). These eight sites were all within a 30 km region, and the majority were within 10 km radius from site E. While sites A, B, D, E, and G were all within urban environments, sites C, F, and H were in conservation areas bordering the city.

Figure 1

Locations where samples for this study were obtained in Hamilton, Ontario, Canada. The sites A–H sampled between 26 May 2008 and 28 September 2008 are indicated in the map. © 2011 Google.

Samples were located within roughly 500 m of the center of each of the sampling locations. As previous studies have shown yeast species including Cryptococcus to be prevalent in avian droppings and decaying tree hollows (Hiremath et al., 2008; Randhawa et al., 2008), our focus here is on tree hollows. Within each area, all tree hollows were sampled, with each tree hollow sampled three times. Selected avian droppings were also swabbed. A total of 370 different surfaces were swabbed (tree hollows and avian droppings together), representing 1110 samples in all. For each sample, a sterile cotton swab was first soaked in sterile 0.5% saline solution immediately before the swab was applied to each sample surface. Each swab was placed in a 2000-μL tube containing 500 μL of the same saline solution. The swabbing technique used in this study was previously shown to be effective in isolating fast growing nonfermentative yeast species like Cryptococcus species (Hiremath et al., 2008; Randhawa et al., 2008). It was also effective in minimizing mold contamination. Whenever possible and necessary, a section of a branch with multiple leaves was also obtained and labeled to allow for the host tree species identification soon after returning to the laboratory.

Sample processing

Immediately after returning to the laboratory (usually within a few hours of swabbing), the samples were enriched with 500 μL of yeast extract–peptone-dextrose (YEPD) liquid agar supplemented with 50 mg mL−1 of the antibiotic chloramphenicol. Enriched samples were incubated at 30 °C for 48 h. Samples were then vortexed and plated onto solid YEPD medium and incubated at 30 °C for 48 h. Any colonies displaying yeast-like morphology were isolated and re-streaked onto YEPD agar and incubated at 30 °C for 48 h. Single colonies were then suspended in 500 μL of 20% Glycerol and frozen at −80 °C. Frozen samples were revived by plating 10 μL on YEPD agar and incubated for 48 h at 30 °C for DNA extraction and genotyping. We would like to note that this protocol selects for fast growing nonfermentative yeasts, and this group of yeasts is the focus of this study.

PCR amplification

DNA was extracted using the protocol described in Xu et al. (2000) for 88 purified yeast-like isolates. The ITS gene fragment of each isolate was amplified using primers ITS1 (5′ TCCGTAGGTGAACCTGCGG 3′) and ITS4 (5′ TCCTCCGCTTATTGATATGC 3′) and the following PCR cycle protocol; DNA was denatured at 95 °C for 4 min followed by 40 cycles at 95 °C for 30 s, 50 °C for 30 s, 72 °C for 1 min, and a final cycle at 72 °C for 6.5 min.

DNA sequencing

Amplified ITS DNA fragments were then cleaned before sequencing by adding an equal volume of MicroClean© to 10–15 μL of PCR product, vortexed, and incubated at 20 °C for 5 min. Samples were then centrifuged at 5678 g for 5 min, and visible supernatant was added to 15 μL of double distilled H2O and incubated at 20 °C for 5 min. Samples were then centrifuged a second time at 13 000 r.p.m. for 5 min, and the supernatant was transferred to a new container. Presence of purified DNA product was tested via electrophoresis on 1.0% agarose gel with 1× Tris–borate–EDTA buffer [TBE (pH 8)] stained with ~1 μL of ethidium bromide for 1 h at 100 V. The gels were then photographed under ultraviolet light (Chemi-imager; Alpha InnovTech). Sequencing was carried out by the MOBIX laboratory of McMaster University and by the Life Sciences Core Laboratory Centre of Cornell University.

Species identification

The ITS sequences were compared to archived ITS sequences on the NCBI database using the blast algorithm to determine the yeast species. Species were identified based upon the best fit with a nucleotide identity of at least 97%. Species that were found to be present in more than one geographical site were subjected to PCR fingerprinting, to observe their genetic similarity and diversity.

ITS phylogeny construction

All the ITS sequences of the yeast strains were aligned by ClustalW, along with reference sequences for the individual species previously deposited in GenBank. The aligned sequences were used to construct a maximum-parsimony tree (Swofford, 2003). The bootstrap supports for individual branches were generated with 1000 replicate randomized data set.

PCR fingerprinting

All yeast isolates were genotyped by PCR fingerprinting using three arbitrary primers (GACA)4, OPA3, and M13, each separately (Rentz et al., 1998; Gudlaugsson et al., 2003; Hajjeh et al., 2004; Maganti et al., 2011). Each standard PCR tube contained 8 μL of Ready-to-Go-PCR mix (Amersham Biosciences), 4 μL of working concentration of DNA, and 4 μL of 0.10 μM of desired primer. The amplifications were subjected to gel electrophoresis on 1.0% agarose gels with 1× TBE buffer for 3 h at 100 V. The agarose gels were stained with ethidium bromide prior to loading the samples. On completion of gel electrophoresis, the gels were photographed digitally under ultraviolet light (Chemi-imager; Alpha Innovtech). Representative strains from each of the analyzed species were tested multiple times for PCR fingerprinting and gel electrophoresis to check for reproducibility of the PCR-fingerprinting patterns.

PCR fingerprinting data analysis

The DNA bands on the PCR fingerprinting gels were scored manually as done elsewhere. A position tolerance setting of 2% was used (Soll, 2000; Ásmundsdόttir et al., 2008). Strains with identical genotypes were expected to show identical fingerprint patterns for all the three primers used. To ensure consistency and minimize errors, all the fingerprinting results were scored twice by two individuals (HM and DB), and this was done for each of the three primers.

Phylogram construction and discriminatory index

The scored fingerprinting results of the amplified DNA were used to construct phylograms to determine the relationships between the strains using the phylogenetic program paup (Swofford, 2003). This was done independently for each of the three primers as well as for the combined data set. The discriminatory index for each of the three primers was calculated using the Simpsons diversity index as done elsewhere (Xu et al., 2000; Gudlaugsson et al., 2003).

Species richness comparison

The species richness for each site was determined as a ratio of the number of unique yeast species found at each site divided by the total number of yeast isolates found in the area.

Host tree preference analysis

The percentage of positive yeast samples obtained from a tree species was calculated by dividing the total number of positive yeast isolates obtained from that tree by the total number of swabs taken from it. This was termed as ‘tree positive percentage’ (TPP) and was done for each of the individual tree hosts. The mean and standard deviation for all these values were calculated. We refer to the overall mean as the ‘mean positive percentage’ (MPP) and the standard deviation as SD.

The significance of any observed yeast–tree preference was evaluated through Z score analysis. The null hypothesis of the test is that the percentage of positive yeast samples obtained from all the trees is similar to each other and close to the mean. A Z value of > 1.64 (Q > 0.95) indicates that the specific tree has a significantly higher yeast colonization rate than the mean. The Z score was calculated by subtracting MPP from TPP and then dividing this number with SD.

Difference between deciduous and coniferous trees

The statistical significance of yeast preference to grow on deciduous trees over coniferous trees or vice versa was examined using the Fisher's exact test. The null hypothesis of the test was that the yeasts show no preference between deciduous trees and coniferous trees.

Difference between urban environment and conservation areas

The statistical significance of the difference in yeast prevalence between urban environments and conservation areas was examined using the Fisher's exact test. The null hypothesis of this test was that there was no difference in yeast prevalence between urban and natural environments.


Yeast species diversity at different geographical sites

A total of 370 tree hollows were sampled, of which 88 were positive for yeast. Of the 88 positive yeast samples, 13 were from the Site A, five were from Site B, 13 were from Site C, 21 were from Site D, 19 were from Site E, nine were from Site F, seven were from Site G, and one were from Site H (Table 1). Based on the ITS sequences, the 88 yeast samples belonged to 20 yeast species (Fig. 2). Sixteen of the 20 yeast species (Candida parapsilosis; Candida psychrophila; Candida lignohabitans; Lachancea kluyveri; Hanseniaspora opuntiae; Septoria citricola; Debaryomyces pseudopolymorphus; Saccharomyces paradoxus; Kazachstania aerobia; Kluyveromyces lactis; Saccharomyces martiniae; Torulaspora delbrueckii; Debaryomyces hansenii; Pichia guilliermondii; Pichia hampshirensis; Candida tropicalis) were ascomycetes, three were Basidiomycetes (Rhodosporidium toruloides; Rhodotorula mucilaginosa; and Fibulobasidium inconspicuum), while one was an Oomycete (Phytophthora parasitica). No yeast belonging to the genus Cryptococcus was found. The accession numbers of all the ITS sequences belonging to the 88 yeast samples were from JF916480 to JF916567.

Figure 2

A maximum parsimony tree based on ITS sequences of all the 88 environmental yeast strains sampled. Each strain in the phylogram was named in the following manner: Strain identification number _ Species abbreviation _ tree species isolated from _ geographical site isolated from. *Denotes reference sequences for each respective yeast species. The names of the tree species have been abbreviated in the following manner: Ash (As), Basswood (Bw), Birch (Bi), Cedar (Cd), Cherry (Ch), Chestnut (Cn), Cottonwood (Ct), Hawthorn (Ht), Maple (Mp), Oak (Ok), Pine (Pi), Sycamore (Sy), Raspberry (Rb) and Beech (Be). Detritus and bird droppings have been abbreviated as Di and Bd. We would like to mention that the objective of this figure is to show that all our isolates can be unambiguously placed into identified existing yeast species. We emphasize that the figure does not represent the true phylogeny of these yeasts. Multiple genes such as those by James et al. (2006) and more are needed to correctly resolve the relationships between these fungi.

View this table:

Summary information relating to the total number samples collected at each sampling site and percentage of them that turned out to be yeast

LocationTotal samples (370 tree hollows × 3)Samples with yeastPercent samples containing yeasts
Site A1201310.83
Site B12054.17
Site C1201310.83
Site D902123.33
Site E1201915.83
Site F36092.50
Site G10576.67
Site H7511.33
Mean ± SD138.75 ± 90.9811 ± 6.857.93 ± 7.44

Six of the 20 yeast species (C. parapsilosis, K. aerobia, K. lactis, T. delbrueckii, D. hansenii, and S. paradoxus) containing 62 strains were identified to be present at more than one site. The remaining 14 yeast species were each found at only one of the sampled sites (Fig. 2; Table 2).

View this table:

Summary information of yeast species and tree species identified at each sampling site and the number of yeast isolates for each species at each site

Site nameYeast species identified [no. of isolates]Tree species identified
Site AS. paradoxus [13]Cedar, Basswood, Oak, Maple, Cottonwood
Site BR. mucilaginosa [5],Cherry
Site CD. hansenii [1], P. guilliermondii [4], S. martiniae [1], T. delbrueckii [1] C. psychrophila [1], H. opuntiae [1], F. inconspicuum [1], R. toruloides [1], S. citricola [2]Hawthorn, Walnut, Beech, Ash, Basswood, Birch, Sycamore, Cotton wood
Site DK. lactis [2], T. delbrueckii [1], C. parapsilosis [7], K. aerobia [3], D. pseudopolymorphus [1], D. hansenii [5], P.parasitica [1], S. paradoxus [1]Pine, Cottonwood, Basswood, Ash, Maple, Raspberry
Site ED. hansenii [1], K. lactis [5], T. delbrueckii [3], K. aerobia [6], R. mucilaginosa [1], L. kluyveri [2], S. paradoxus [1]Ash, Sycamore, Cottonwood, Chestnut, Beech
Site FP.hampshirensis [3], C.tropicalis [1], K.lactis [3], S.paradoxus [2]Cottonwood, Cedar, Basswood, Sycamore, Maple
Site GC.parapsilosis [2], T. delbrueckii [5],Pine, Beech, Cottonwood, Chestnut
Site HC. lignohabitans [1]Cottonwood

Fingerprinting results

Our combined PCR fingerprinting results identified that the nine strains of C. parapsilosis belonged to eight distinct genotypes. Seven of these genotypes representing one strain each were present at site D. The remaining genotype contained two strains, both from the same pine tree at site G. None of the eight genotypes overlapped between the two sites.

The nine strains of K. aerobia belonged to eight unique genotypes. Of the eight genotypes, two were found at site D with one genotype representing two strains from hollows of two different ash trees. The remaining six genotypes were found at site E with each representing only one strain. None of the eight genotypes overlapped between the two different sites.

The 10 strains of K. lactis belonged to nine genotypes. Two of the nine genotypes were present at Site D, while four and three genotypes were found at site E and site F, respectively. The two strains sharing the same genotype were found at site E with one from ash and the other from chestnut. All other genotypes represented only one strain each. None of the nine genotypes overlapped across the three different sites.

The 10 strains of T. delbrueckii each had a different genotype. Of the 10 strains, one was found at site D, five at site G, three at site E, and one at site C. There was no sharing of genotypes within or between the four different sites.

The 17 strains of S. paradoxus were identified to belong to 17 genotypes. Of the 17 strains, one was found at site D, two at site F, 13 at site A, and one at site E. There was no sharing of genotypes within or between the four different sites.

The seven strains of D. hansenii belonged to seven genotypes. Of the seven strains, one was found at site E and site C each, while five were found at site D. There was no sharing of genotypes within or between the three different sites.

Discriminatory power of the PCR fingerprinting markers

The discriminatory powers of the three PCR fingerprinting primers were similar. For C. parapsilosis, the M13 PCR fingerprinting primer had the highest power of 0.87 followed by OPA3 and (GACA)4 with values of 0.86 and 0.85. The combined discriminatory power for the markers was identified to be 0.97. Among K. aerobia strains, the OPA3 primer had the highest discriminatory power of 0.87, followed by (GACA)4 and M13 with powers of 0.86 and 0.85. The combined discriminatory power for the three markers was 0.97. As for K. lactis strains, M13 had the highest discriminatory power of 0.90 followed by OPA3 and (GACA)4 with values of 0.86 and 0.85. Their combined discriminatory power for the three markers was 0.98.

Among the T. delbrueckii strains, the marker OPA3 had the highest discriminatory power of 0.91 followed by (GACA)4 and M13 with powers of 0.90 and 0.89. The combined discriminatory power for the three markers was identified to be 1.0. Among S. paradoxus strains, the marker M13 had the highest discriminatory power of 1.0 followed by (GACA)4 and OPA3 with powers of 0.95 and 0.91. The combined discriminatory power for the three markers was identified to be 1.0. Amid the D. hansenii strains, the marker (GACA)4 had the highest discriminatory power of 0.87 followed by M13 and OPA3 with powers of 0.86 and 0.85. The combined discriminatory power for the three markers was identified to be 1.0.

Yeast species richness based on geographic sites

Site C was identified to be the most species rich site, containing strains belonging to nine species. This was followed by site D (eight species), site E (seven species), site F (four species), site G (two species), and lastly sites A, B, and H with each containing strains belonging to only one species each (Table 2).

Host tree–yeast species correlation

Host tree species also appeared to have an impact on the number and type of yeast isolates collected from each site. A significantly high percentage of samples swabbed from cedar, basswood, and cottonwood contained yeasts (Table 3). Overall, the probability of finding yeasts on conifers was significantly higher than that of yeasts on deciduous trees (Table 4). Interestingly, all the C. parapsilosis isolated strains were found to be present on pine trees only. Most of the yeasts in our study belonged to Ascomycetes. In contrast, surveys conducted before showed basidiomycete yeast to be more prevalent in tree hollows with some on detritus (e.g., Randhawa et al., 2008).

View this table:

Summary of positive yeast samples and the total number of samples taken from each tree as well as the Z score correlation between them

Sample SourceNo. of samples with yeastNo. of trees sampledTotal no. of samplesTPPZ ScoreQ > 0.95
Avian droppings3431292.32−0.99
  • +++, significantly higher than the mean (Q > 0.95, i.e., reject null hypothesis); −, not significantly higher than the mean (Q < 0.95, i.e., accept null hypothesis); TPP = Tree Positive Percentage; MPP = Mean Positive Percentage; SD = Standard deviation.

View this table:

Fisher's exact test analysis showing tree type preference

Samples without yeast676112788
Samples with yeasts622082


In this study, we isolated and identified 20 yeast species from 370 tree hollows across the eight sampling sites. Six of these 20 yeast species were distributed at more than one site (Fig. 2; Table 2). The genotype analysis based on PCR fingerprinting showed that no genotype was shared between any of the sites. This pattern was similar regardless whether the sampled sites were natural or urban environments. Our results are consistent with microgeographic and ecological structuring among the yeasts in and around an urban center. The high amount of heterogeneity found prevalent among the yeast populations in Hamilton was unexpected because of the relative proximity of the sampled areas (Fig. 1) and the availability of vectors (e.g., birds, rodents, and humans) to shuttle these yeasts between the areas. In addition, sites C, G, F, and D were all connected by waterways. While the detailed mechanisms are unknown, differences in population history could have contributed to the observed spatial heterogeneity. For example, established yeast populations have been previously identified to monopolize the nutrients of a particular site, thus blocking the founding of new yeast populations (Vishniac & Helen, 2006). However, compared to the large number of yeast species (> 2000) identified so far, the relative size of our yeast populations at the eight sampled sites was small. It is possible that some level of genetic overlap might be observed if more sites with more yeasts were sampled.

In terms of species richness, the eight sites showed some difference. However, there was no observed correlation between yeast species richness and tree species richness. With the exception of site C which was observed to be the most species rich site for both yeasts and trees, the order of yeast species richness and tree species richness varied among the different sites (Table 2). Similar findings have been reported by other studies conducted elsewhere (Middlehoven, 1997; Inacio et al., 2002; Sláviková et al., 2007). However, the amount of decomposing matter present on the grounds at the sampled sites might be related to the rate of yeast isolation at the given site. Although we did not quantify the decomposing organic matter, sites D and E contained visibly the largest amount of decomposing material and these two sites also contained the highest percentage of yeast isolation rate. In contrast, site H contained very little detritus, and it had the lowest yeast isolation rate. Because previous studies have shown that increased detritus leads to increased carbon availability in the soil which in the past has shown to lead to increased yeast and bacterial populations in soil (Gonzalez et al., 1989; Wardle, 1992; Wardle et al., 2004; H¨ogberg & Read, 2006; Yarwood et al., 2009), we speculate that these yeast species might have been carried from the soil onto the trees by animals and human activities. The hypothesis that anthropogenic factors might have impacted yeast distribution is supported by the higher yeast recovery from the urban sites than those from the natural environments (P = 0.01, Table 5). In addition, the species distributions were different between the urban environments and conservation areas. Of the 20 yeast species isolated here, six (K. aerobia; C. parapsilosis; R. mucilaginosa; D. pseudopolymorphus; P. parasitica; and L. kluyveri) were unique to the urban environment, while 10 were found only in the natural conservation areas (S. martiniae; P. guilliermondii; P. hampshirensis; C. tropicalis; C. psychrophila; C. lignohabitans; R. toruloides; S. citricola; F. inconspicuum; and H. opuntiae). The remaining four (S. paradoxus; K. lactis; T. delbrueckii; and D. hansenii) were found at both the urban and conservation sites.

View this table:

Fisher's exact test analysis showing a greater yeast prevalence in urban environments than conservation areas

Urban environmentConservation areasTotal
Samples without yeast4905321022
Samples with yeasts652388

Contrary to previous studies and to our expectation, our ITS–blast result showed that we isolated C. psychrophila, a psychrophilic yeast, through our standard enrichment protocol where we incubated all the yeasts at 30 °C for 2 days. This is interesting considering one of the defining features of psychrophilic yeast is that they cannot grow well beyond an upper limit temperature of 20 °C (Watson et al., 1978). However, this finding might be an artifact related to misidentification in the GenBank and/or the lack of ITS sequence variation among closely related species (Nilsson et al., 2008). An alternative hypothesis is that this presumed psychrophilic yeast actually contains subpopulations capable of growing at elevated temperatures. Further sequencing is needed to clarify this issue.

The degradative abilities of yeasts likely also play a role in their distribution on trees (Middlehoven, 1997; Inacio et al., 2002; Sláviková et al., 2007). In this study, we observed that coniferous trees seemed more likely to harbor yeasts than deciduous trees (P = 0.02). A significantly high percentage of samples (compared to the mean) isolated from the detritus of cottonwood, cedar, and basswood had yeast (Table 3). Of these trees, cedar is a softwood coniferous tree, while basswood and cottonwood are deciduous hardwood trees. Although previous studies conducted in urban environments using identical sampling protocols in India have indicated long-term colonization of Polyalthia longifolia, Mimusops elengi, and Manilkara hexandra trees by certain yeast species such as C. gattii and/or C. neoformans, there was no reported bias between deciduous and coniferous trees (Sláviková et al., 2007; Randhawa et al., 2008) (Table 4). Apart from the degradative abilities of yeast, another property that might have played a role in the distribution of yeast included the pH of the tree barks which might also vary among different tree species.

Aside from the nature of trees (i.e., deciduous or coniferous), the innate resistance of fungi to antifungal chemicals present in the trees could also play an important role in determining what yeast species inhabits which tree. In this study, all the C. parapsilosis strains were observed to colonize pine trees only. C. parapsilosis has been previously observed to grow on the barks of injured pine trees (El-Tabey Awad Shihata and Mrak, 1952). However, that association is not known to be exclusive. Our results here may be related to the fact that pine wood and pine needles contain beta-pinene, which is known to possess antifungal properties that few yeasts in Candida were resistant to (Uribe et al., 1985; Krauze-Baranowska et al., 2002; Pozzatti et al., 2010). This innate resistance of C. parapsilosis to this compound could potentially provide an advantage for C. parapsilosis over other yeasts to colonize the pine trees.

Environmental pollutants such as poly aromatic hydrocarbons (PAHs) may also shape microbial flora in natural environments. In this study, site D is located downwind of two steel mills and a highway and high levels of PAHs have been detected in this area. The two species C. parapsilosis and D. hansenii are capable of metabolizing PAHs (MacGillivray & Shiaris, 1993; Sofowote et al., 2008), and they were found on the trees close to the steel mills and the highway. A similar trend was also observed in sites C, F, and G, all of which are connected to site D by a waterway. In these sites, we observed the dominance of species belonging to Candida, Pichia, and Rhodotorula on trees close to the water sources and likely contained high levels of PAHs. Species in these genera are capable of metabolizing PAHs (MacGillivray & Shiaris, 1993). A detailed test of the levels of PAH at these environments would be needed to demonstrate whether PAH contamination selects for certain yeast species in the natural environment. Alternatively, aromatic compounds can also be generated when plant lignins are metabolized. Basidiomycetes are known to have significant capacity to metabolize lignin to obtain energy.

Several of the species identified here, especially those in genera Candida, Pichia, and Rhodotorula are capable of causing human and animal infections (Chakrabarti et al., 2001; Xu & Mitchell, 2003; Maganti et al., 2011). However, the potential impact of tree hollow yeast populations on human healthy remains unknown. It would be highly desirable to compare the yeast populations from the environments with those from clinics to determine the potential overlaps in genotypes.

In summary, we isolated 88 yeast strains and identified that they belonged to 20 yeast species. Six of the 20 species were present at more than one site. The fingerprinting results showed that despite the close proximity of the sampling sites and the presence of dispersal vectors, the populations of yeasts belonging to the same species were highly heterogeneous. Our results suggested little evidence for clonal dispersal among the strains in the urban environments. While the probability of finding yeasts on cedar, basswood, and cottonwood was noticeably high, C. parapsilosis was observed only on pine trees in our samples. Our results suggest that the substrate-utilization abilities of yeasts likely played a significant role in their distribution in the environment in and around Hamilton.


This study was supported by a grant from the Natural Science and Engineering Research Council (NSERC) of Canada.


  • Editor: Jens Nielsen


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