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, 8 (5), e62901

Control of Temperature on Microbial Community Structure in Hot Springs of the Tibetan Plateau


Control of Temperature on Microbial Community Structure in Hot Springs of the Tibetan Plateau

Shang Wang et al. PLoS One.


The Tibetan Plateau in Northwest China hosts a number of hot springs that represent a biodiversity hotspot for thermophiles, yet their diversity and relationship to environmental conditions are poorly explored in these habitats. In this study we investigated microbial diversity and community composition in 13 Tibetan hot springs with a wide range of temperatures (22.1-75°C) and other geochemical conditions by using the 16S rRNA gene pyrosequencing approach. Bacteria (10(8)-10(11) copy/g; 42 bacterial phyla) in Tibetan hot springs were more abundant and far more diverse than Archaea (10(7)-10(10) copy/g; 5 archaeal phyla). The dominant bacterial phyla systematically varied with temperature. Moderate temperatures (75-66°C) favored Aquificae, GAL35, and novel Bacteria, whereas low temperatures (60-22.1°C) selected for Deinococcus-Thermus, Cyanobacteria, and Chloroflexi. The relative abundance of Aquificae was correlated positively with temperature, but the abundances of Deinococcus-Thermus, Cyanobacteria, and Chloroflexi were negatively correlated with temperature. Cyanobacteria and Chloroflexi were abundant in Tibetan hot springs and their abundances were positively correlated at low temperatures (55-43°C) but negatively correlated at moderate temperatures (75-55°C). These correlation patterns suggest a complex physiological relationship between these two phyla. Most archaeal sequences were related to Crenarchaeota with only a few related to Euryarchaeota and Thaumarchaeota. Despite the fact that microbial composition in Tibetan hot springs was strongly shaped by temperature, microbial diversity (richness, evenness and Shannon diversity) was not significantly correlated with temperature change. The results of this study expand our current understanding of microbial ecology in Tibetan hot springs and provide a basis for a global comparison.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.


Figure 1
Figure 1. Geographic map showing sampling locations.
The red dots along the highway represent the sampling areas in Naqu County of Tibet, NW China.
Figure 2
Figure 2. Microbial distribution pattern based on the complete pyrosequencing dataset at the 97% OTU level.
A. Microbial cluster tree using jackknifed unweighted pair group method with arithmetic averages (UPGMA); B. Non-metric multidimensional scaling (NMDS) ordination for the community structure for all the samples. Ordination is based upon the Bray-Curtis similarity of the square-root-transformed abundances. The lower the 2D stress is, the better the ordination is; C. PCoA scatter plot that begins with a table of distances between the samples. The first two factors P1 and P2 can explain 26.7% and 23.7% variations, respectively. All three plots show the same pattern: the soil cluster, the low-temperature cluster, and the moderate-temperature cluster. The samples are primarily grouped by the sample type (hot spring sediments vs. adjacent soil); among the hot spring sediments, there are two groups separated by temperature (low vs. moderate temperature). Sample codes consist of sample ID and temperature for that spring. For example, GL13.4_66 represents the 4th site along an outflow channel of the 13th hot spring in the Gulu area with a temperature of 66°C. Different symbols are used to differentiate the different clusters.
Figure 3
Figure 3. Comparison of microbial composition at the phylum-level OTUs among the three groups.
The identified three groups are the soil cluster, the low-temperature cluster, and the moderate-temperature cluster. A. Cluster analysis using the complete dataset at the phylum-level OTUs; B. The pie charts show the relative proportions of microbial phyla in each group. Those phyla with <1% abundance (e.g. Deferribacteres, candidate phyla OP3, 8 and 9, SC4 and BRC1) are not shown and unknown bacteria are termed as “bac_other”. Dominant phyla marked on the pie charts are confirmed by the SIMPER analysis.
Figure 4
Figure 4. Comparison of alpha diversity.
Calculation of microbial Richness, Equitability, and Shannon diversity among the pooled samples for the low temperature cluster (60–22.1°C), the moderate temperature cluster (75–66°C), and the soil cluster at four OTU levels: 97%, 95%, 90%, and 80%. Error bars indicate standard error of the mean. Pairwise t tests were performed for each pair of comparisons, moderate vs. low temperature, moderate temperature vs. soil, and low temperature vs. soil at each OTU level. Symbols ***indicates p<0.001; **p<0.01; *p<0.05;. p<0.1; ∼ non-significant. A Bonferrroni correction was made for the number of comparisons.
Figure 5
Figure 5. Correlations between the relative abundances of dominant microbial groups and temperature.
The relative abundance of Aquificae (A) shows a positive correlation with temperature, whereas the relative abundances of the phyla Deinococcus-Thermus (B), Cyanobacteria (C) and Chloroflexi (D) as well as the class Chloroflexi (E) show negative correlations with temperature. The relative abundance of Cyanobacteria and temperature was not significantly correlated (R2 = 0.23; p<0.5) (Figure 5C); when the two outliers (springs NM6 and NM7, where Cyanobacteria were minor) were omitted, the linear correlation was dramatically improved (R2 = 0.90; p<0.005) (figure not shown). When qPCR data were used for Cyanobacteria (C) and class-level Chloroflexi (E), similar correlations resulted (data not shown for clarity).
Figure 6
Figure 6. Distribution of major Cyanobacteria and Chloroflexi genera across a wide temperature range.
The solid lines represent Cyanobacteria and the dash lines for Chloroflexi. A. The relative abundance of total Cyanobacteria and Filamentous Anoxygenic Phototrophic Chloroflexi (FAPs) as determined by qPCR and 454 pyrosequencing across a wide temperature range. Both methods showed a similar trend: in the range of 75–55°C, the abundance of Cyanobacteria was positively correlated with that of FAPs; in the range of 55–43°C, the abundance of Cyanobacteria was negatively correlated with that of FAPs. The difference in the relative abundance of Chloroflexi between the qPCR and the 454 results for Spring NM6 (Figure 6) was likely caused by different primers used: the 454 primer for Chloroflexi included Oscillochloris, but the qPCR primer did not include this genus. B. The relative abundance of three genera within FAPs and major genera within Cyanobacteria as a function of temperature. Each genus has its optimal temperature. The sum of these genera within FAPs and Cyanobacteria contributed to the positive or negative correlations between these two phyla at different temperature ranges. For Cyanobacteria, those organisms with the relative abundance of >5% were included, so Planktothricoides in Figure S5C were not included in Figure 6.

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Grant support

This work was supported by the National Natural Science Foundation grants of China (41030211, 41002123 and 40972211), the Key Project of International Cooperation of China Ministry of Science & Technology (MOST) (No. 2013DFA31980), the Scientific Research Funds for the 1000 “Talents” Program Plan from China University of Geosciences-Beijing (H.D.) and Tongji University (C.Z.), and National Science Foundation grants (OISE-0968421, DBI REU 1005223, and ETBC-1024614), and the Program for New Century Excellent Talents in University (NCET-12-0954). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.