- Research article
- Open Access
Composition of soil microbiome along elevation gradients in southwestern highlands of Saudi Arabia
© Yasir et al.; licensee BioMed Central. 2015
Received: 17 November 2014
Accepted: 24 February 2015
Published: 14 March 2015
Saudi Arabia is mostly barren except the southwestern highlands that are susceptible to environmental changes, a hotspot for biodiversity, but poorly studied for microbial diversity and composition. In this study, 454-pyrosequencing of 16S rRNA gene hypervariable region V6 was used to analyze soil bacterial community along elevation gradients of the southwestern highlands.
In general, lower percentage of total soil organic matter (SOM) and nitrogen were detected in the analyzed soil samples. Total 33 different phyla were identified across the samples, including dominant phyla Proteobacteria, Actinobacteria and Acidobacteria. Representative OTUs were grouped into 329 and 508 different taxa at family and genus level taxonomic classification, respectively. The identified OTUs unique to each sample were very low irrespective of the altitude. Jackknifed principal coordinates analysis (PCoA) revealed, overall differences in the bacterial community were more related to the quantity of specific OTUs than to their diversity among the studied samples.
Bacterial diversity and soil physicochemical properties did not show consistent changes along the elevation gradients. The large number of OTUs shared between the studied samples suggest the presence of a core soil bacterial community in the southwestern highlands of Saudi Arabia.
The microbial community of soil is extremely diverse and integral part of ecosystems that play a major role in the climate change trough contribution in soil organic matter decomposition . Prime reservoir of global terrestrial carbon resides in soil , and fractional scale changes in cycling of total soil carbon could have considerable impacts on the density of atmospheric carbon dioxide. Therefore, a change in soil carbon is a critical regulator of future climate in response to environmental changes . Climate change is a complex phenomenon regulated by numerous factors, including complex interactions and feedbacks between climate, plants, animals and soil microbes [2,3].
Overall, global warming effects are more prime on microbial community and consequent decomposition processes in alpine, arctic and highland regions . However, altitudinal patterns of microbial community have not been well studied and remain poorly understood compared to macroorganisms diversity that have been studied for centuries . Bacterial diversity and abundance probably is reduced with altitude and influenced by ecological and geological factors such as vegetation, temperature and pH level etc. that establish complex interaction [4,5]. Several studies did not observe similar types of consistent changes in microbial community along elevation gradients [6,7]. Species of Azotobacter chroococcum and Azospirillum brasilense were reported as dominant nitrogen fixing bacteria at high altitude . Seasonal variations have influenced on bacterial community diversity and abundance within taxa in Colorado Mountains. The Acidobacterium division was most abundant in spring. Winter community had the highest proportion of Actinobacteria and members of the Cytophaga/Flexibacter/Bacteroides division. However, some of the species resist temperature fluctuations, e.g. the α– Proteobacteria . Further studies that parallelly investigate empirical patterns of plants, animals and microorganisms will provide a better sketch of diversity patterns in major environmental gradients of Earth, and will predict system wide ecological responses to climatic changes .
Saudi Arabia represents almost 80% of the Arabian Peninsula , and at least one–third of its land is desert . Saudi Arabia is generally known for high temperature and low rainfall with exception of the southwestern highlands that are covered by diverse forests . According to the report of Darfaoui and Assiri , Saudi Arabia is more vulnerable to climate change, and forecasted temperature increase in this region is higher compared to an average increase in the global temperature along with high moisture in the western highlands of the country. So far no study has been conducted to document the soil microbial community in this geographically distinct region with unique environmental conditions. In this study, soil samples were collected from the southwestern highlands of Saudi Arabia at different elevational gradients to document bacterial community composition using high throughput next generation sequencing targeting hypervariable V6 region of 16S rRNA gene. In future prospective, the study would help us to understand the impact of climate change in this region on microbial community composition and their possible consequences on flora and fauna.
Location of the study sites and physicochemical characteristics of soil samples
Organic matter %
8.3 ± 0.2
0.85 ± 0.03
0.04 ± 0.004
26.4 ± 0.3
8.1 ± 0.15
0.71 ± 0.02
0.08 ± 0.001
5.5 ± 0.5
7.7 ± 0.11
1.75 ± 0.01
0.09 ± 0.003
14.4 ± 0.1
8 ± .026
1.75 ± 0.03
0.09 ± 0.001
19.7 ± 0.1
7.8 ± 0.35
1.61 ± 0.01
0.08 ± 0.005
52.1 ± 1.9
7.8 ± 0.05
1.75 ± 0.02
0.09 ± 0.002
48.2 ± 2.0
7.9 ± 0.25
0.7 ± 0.1
0.04 ± 0.001
45.5 ± 0.4
7.8 ± 0.17
1.54 ± 0.04
0.07 ± 0.006
28.2 ± 0.3
7.8 ± 0.1
0.21 ± 0.06
0.02 ± 0.008
28.2 ± 0.1
7.9 ± 0.15
1.75 ± 0.04
0.09 ± 0.001
34.9 ± 0.4
Bacterial community composition
In this study, we obtained a total of 62081 raw sequence reads from 10 samples utilizing Roche 454-FLX titanium instruments. After sequence processing, 58617 number of high quality sequence reads (>200 bp) were obtained and assigned to bacteria domain. The average reads number were 5861 ± 1708 sequences per sample.
Taxonomic analysis revealed 103 OTUs including a group of 19 (18.4%) unclassified OTUs at class level. Members from Actinobacteria (class) dominated the Actinobacteria phylum, occupying 17.4% of the total sequence reads, but were showing high variability ranging from 3.9–40.2 % within the samples. Class α– Proteobacteria occupied 12.5% of the total sequence reads and was dominating phylum Proteobacteria ranging from 4.3–21.9% within the samples compared to other Proteobacteria classes, β–Proteobacteria (4.5 ± 2.4%), γ–Proteobacteria (3.7 ± 2.1%) and δ–Proteobacteria (3.3 ± 1.2 %). Members of the class Acidobacteria –6 (4.0 ± 2.9 %) and Thermoleophilia (Actinobacteria, 3.5 ± 2.8%) were commonly detected within the samples. Statistically, only the distribution of rarely detected classes, Solibacteres (Acidobabcteria), Actinobacteria MB*2A–108 and unclassified class of Verrucomicrobia present in <1% concentration of the total sequence reads were significantly different (p < 0.05) between the groups of samples collected at elevation of 2000 meter below and above.
Overall, 508 OTUs were found at genus level taxonomic classification in the total sequence reads. Among those, only 164 OTUs were assigned to defined genera. The 54 OTUs were commonly detected within the analyzed samples and were representing 66.3% of the total sequence reads. Only few OTUs were present specifically per studied samples ranged from 6–26. Maximum number of unique 26 OTUs at genus level were identified in the sample Swh6 (Figure 2B). On average, 227.6 ± 41.1 OTUs at genus level were identified per sample, and highest diversity was observed in the sample Swh10 containing 296 taxa followed by Swh5 (268) and Swh2 (265). The genera from following groups Actinomycetales, Chloracidobacteria, Geodermatophilaceae, Acidobacteria –6, Rhizobiales, Betaproteobacteria, Micromonosporaceae, Solirubrobacterales, Alphaproteobacteria and Pseudonocardia were dominantly detected at level of >1% concentration in each sample.
Pyrosequencing data statistical analyses
Natural ecosystem in the western highlands of Saudi Arabia is susceptible to climate change as result of global warming, overgrazing and expansion of uncontrolled urbanization that is leading to changes in species composition, richness and a decrease in biodiversity [10,13]. Presently, western highlands of Saudi Arabia are experiencing a drastic shift from ruler to urban environment and population influx. Urbanization has detrimental effects on soil ecosystems and microbial community . According to GCM models, expected average warming in Saudi Arabia for the year 2041 will be higher than the global average . Therefore, it is critical to document the ecosystem, particularly the poorly studied microbial community over different parts of the country and to plan for the sustaining of local ecosystems in the western highlands.
We investigated the soil bacterial community composition and soil residues along an altitude in the southwestern highlands of Saudi Arabia, where the ecosystem is expected to be more fragile with respect to climate change [3,15]. We found that neither bacterial diversity nor soil physicochemical properties showed consistent changes with altitude. There were no significant differences observed in pH level at different altitudes. Similarly, Tukey HSD analysis indicated that the concentration of SOM and total nitrogen were not significantly different within the samples Swh3, Swh4 and Swh10 collected at different altitudes. Previously, it was reported that microbial flora does not affect by altitude. Physicochemical factors such as SOM, total nitrogen, electrical conductivity and pH changed with altitude . The relation between SOM and altitude increased linearly in grassland soil . Generally, effect of altitude on soil chemistry is dependent on vegetation, climate and environmental ecology of the investigated study site [3,7]. Overall, the concentration of SOM was less than 2% within each analyzed soil samples that limited to desert area and representing low–lying of SOM contents in the southwestern highlands of Saudi Arabia.
In order to understand bacterial diversity and community’s composition at southwestern highlands, we analyzed the output of 16S rRNA gene sequence reads qualitatively and quantitatively. The identified OTUs unique to each sample were very low irrespective of the altitudinal level. The highest number of twenty six unique OTUs at genus level were identified in the sample Swh6 collected at 2100 meter height followed by 22 unique OTUs identified in the Swh10 collected at 1871 meter height. Maximum diversity was detected in the samples Swh10, Swh5 and Swh2, respectively collected at different altitudinal level. Consistent with several previous studies, soil from the southwestern highlands at different altitudes were dominated by the conserved set of phyla Proteobacteria, Actinobacteria and Acidobacteria that were commonly detected in different types of soil such as agriculture, forest and Arctic [18-20]. It suggests the presence of a well adapted soil core bacterial community that is resistant to environmental disturbance factors and commonly present in different types of soil. However, the overall similarities and dissimilarities are associated with the soil type acting as a dominant factor driving bacterial community composition . For example, phyla Firmicutes and Bacteroidetes were detected at higher concentrations in sample Swh6 compared to the other samples. This difference may be attributed to the sedimentary nature of soil collected around a lake and vegetation of the sampling site. Similar structure in microbial community was detected along different alpine vegetative zones and altitudinal gradients from 900–1900 meters in the Austrian Limestone Alps , and in the soil from the Bornean tropical forest at altitudinal gradients (700–2700 meters) . Margesin et al.  reported a decrease in microbial activity and shift in microbial community composition with altitude in the Grossglockner mountain area of the Austrian Central Alps. Probably, the apparent inconsistency between the studies may be due to difference in the study sties, climate, elevation increments and vegetation or methodology used for assessment of microbial community composition. Several researchers identified significant influence of vegetation and plant species over microbial flora  and soil chemistry . In this study, we did not focus on the association of plant species specific interaction with microbial community at the sampling sites that were mainly covered by the scattered density of Juniperus procera followed by Acacia spp. Olea europaea and shrubs. Ushio et al.  revealed the indirect role of plant species in regulation of soil microbial community composition mainly through their effects on soil physicochemical properties such as pH, total carbon and nitrogen etc. The interaction between plants, soil chemistry, microorganism and other ecological factors is quite complex phenomena that drives the ecosystem functions and any alteration in these factors might affect the microbial community composition and the ecological processes [3,22,27].
Interestingly, the majority of sequence reads from all the analyzed samples were not classified to any defined taxonomy units at and below family level. It is consistent with the previous studies investigated untouched environments such as Antarctica, and found a unique type of flora that showed lower similarities with 16S rRNA gene sequences retrieved from other environmental samples . It should be noted, there are few limitations exist in our study that include selection of few sampling sites as a proxy to assess the western highland of Saudi Arabia, although the studied sites have a representative landscape of southwestern highlands. Our results based on single time point sampling and seasonal dynamics might affect the microbial community’s diversity and composition. In fact, some previous studies have noticed that long–term patterns of subsurface microbial community are likely to remain generally intact .
Analysis indicated that bacterial community within soil samples collected from southwestern highlands of Saudi Arabia were similar but not identical, and did not show a consistent shift with altitudinal level. Overall, 12 phyla were commonly found across the samples and a group of core dominant phyla Proteobacteria, Actinobacteria and Acidobacteria reported previously from other different types of soil. Members from the phyla Chloroflexi, Bacteroidetes, Firmicutes, Planctomycetes and Gemmatimonadetes were present in lower abundance. PCoA analysis revealed, overall differences between the samples were more related to the abundance of specific OTUs than to their presence or absence. There is need of further studies to investigate the microbial community in conjunction with other ecological parameters in the western highlands of Saudi Arabia. Because it may encounter catastrophic shifts due to urbanization and climate change.
Study area and samples collection
At each sampling spot, quadrates of 3.5 × 3.5 meters were selected. Surface soil of 3 cm was removed. Multiple samples were collected from the four corners and middle of each quadrate at depth of 10 cm with a sterilized spatula, and the samples were sieved through 2 mm mesh. Samples from each spot were mixed in a sterilized bag and frozen at –80°C for DNA extraction. All the samples were collected on the same day in May 2012.
The pH of each sample was measured using Meridian benchtop meters (Denver, Germany) in a saturated colloid solution of soil in deionized water. Total soil organic matter (SOM) was determined using the partial oxidation method. Total phosphorus was measured colorimetrically and total nitrogen (TN) was analyzed by the micro Kjeldahl method . Each sample was analyzed in triplicate.
DNA extraction and pyrosequencing
Samples were homogenized and metagenomic DNA isolation was performed using PowerSoil® DNA extraction kit (MoBio Laboratories, Carlsbad), as recommended by the manufacturer. To get maximum coverage, DNA extraction from each sample was performed in triplicates, pooled and quantified using Qubit fluorometer (Invitrogen, USA). PCR amplification of 16 S rRNA gene was performed from extracted DNA of each sample by using bar–coded 926 F AAACTYAAAKGAATTGACGG and 1394R ACGGGCGGTGTGTRC universal primers containing the A and B sequencing adaptors targeting hypervariable V6–V8 region of 16S rRNA gene following the procedure of Dowd et al. . Amplicon products of PCR from all samples were quantified using high sensitivity Qubit technology and purified using Agencourt Ampure beads (Agencourt, USA). Sequencing was performed on 454 FLX–titanium amplicon pyrosequencing technology (Roche, Basel Switzerland) following the manufacturer’s protocol.
The raw sequence data was processed using a proprietary analysis pipeline (MR DNA, TX USA). The sequence reads containing N, sequences with homopolymer runs exceeding 6 bp, chimera and sequence reads < 200 bp were removed. Sequences were depleted from barcodes and primers. The high quality sequence reads were clustered into operational taxonomic units (OTUs) using threshold of 97% sequence similarity. The OTUs were taxonomically classified using BLASTn against a curated GreenGenes database, and RDP classifier and RDP training set .
Richness and biodiversity index of the OTUs were calculated with implementation of Chao1 and non–parametric Shannon formula using QIIME v1.8 software package . The UniFrac unweighted pair group method with arithmetic mean phylogeny–based distance metric analysis was used to investigate differences in microbial community among soil samples collected at different altitudes from the southwestern highlands of Saudi Arabia . The resulting matrices were also processed for PCoA that showed fraction of total variance at each axis. One–way anova and Tukey HSD (Honestly Significant Difference) tests were used to statistically compare physicochemical parameters, and no–parametric Kruskal–Wallis along with Mann–Whitney analysis were performed to identify significantly different bacterial taxa between the samples collected below and above 2000 meters. Statistical analyses were performed using SPSS version 20.
Availability of supporting data
Sequence data of this study is available in the NCBI Sequence Read Archive under accession no. SRX759755.
This project was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, under grant no. (442/141/1433). The authors, therefore, acknowledge with thanks DSR technical and financial support.
- Davidson EA, Janssens IA. Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature. 2006;440(7081):165–73.View ArticlePubMedGoogle Scholar
- Heimann M, Reichstein M. Terrestrial ecosystem carbon dynamics and climate feedbacks. Nature. 2008;451(7176):289–92.View ArticlePubMedGoogle Scholar
- Bardgett RD, Freeman C, Ostle NJ. Microbial contributions to climate change through carbon cycle feedbacks. ISME J. 2008;2(8):805–14.View ArticlePubMedGoogle Scholar
- Bryant JA, Lamanna C, Morlon H, Kerkhoff AJ, Enquist BJ, Green JL. Colloquium paper: microbes on mountainsides: contrasting elevational patterns of bacterial and plant diversity. Proc Natl Acad Sci U S A. 2008;105 Suppl 1:11505–11.View ArticlePubMed CentralPubMedGoogle Scholar
- Young IM, Crawford JW. Interactions and self-organization in the soil-microbe complex. Science. 2004;304(5677):1634–7.View ArticlePubMedGoogle Scholar
- Djukic I, Zehetner F, Mentler A, Gerzabek MH. Microbial community composition and activity in different Alpine vegetation zones. Soil Biol Biochem. 2009;42(2):155–61.View ArticleGoogle Scholar
- Zhang B, Liang C, He H, Zhang X. Variations in soil microbial communities and residues along an altitude gradient on the northern slope of changbai mountain, china. PLoS One. 2013;8(6):e66184.View ArticlePubMed CentralPubMedGoogle Scholar
- Carpa R, Butiuc-Keul A, Dobrotă C, Muntean V. Molecular identification of diazotroph microbial consortia in mountain soil. Cent Eur J Biol. 2010;5(5):664–73.View ArticleGoogle Scholar
- Lipson DA, Schmidt SK. Seasonal changes in an alpine soil bacterial community in the colorado rocky mountains. Appl Environ Microbiol. 2004;70(5):2867–79.View ArticlePubMed CentralPubMedGoogle Scholar
- Almazroui M, Nazrul Islam M, Athar H, Jones PD, Rahman MA. Recent climate change in the Arabian Peninsula: annual rainfall and temperature analysis of Saudi Arabia for 1978–2009. Int J Climatol. 2012;32(6):953–66.View ArticleGoogle Scholar
- McCoy JF. Geo-Data: the World Geographical Encyclopedia. 3rd ed. 2003.Google Scholar
- El-Juhany LI, Aref IM. The present status of the natural forests in the southwestern saudi Arabia: 3- Asir and east Jazan forests. World Appl Scie J. 2013;21(5):710–26.Google Scholar
- Darfaoui EM, Assiri AA. Response to climate change in the Kingdom of Saudi Arabia. In: Director General of the Department of Natural Resources, MOA. KSA. 2010. p. 1–17.Google Scholar
- Xu HJ, Li S, Su JQ, Nie S, Gibson V, Li H, et al. Does urbanization shape bacterial community composition in urban park soils? A case study in 16 representative Chinese cities based on the pyrosequencing method. FEMS Microbiol Ecol. 2014;87(1):182–92.View ArticlePubMedGoogle Scholar
- Hansen J, Ruedy R, Glascoe J, Sato M. Correction to “GISS analysis of surface temperature change” by J Hansen et al. J Geophys Res Atmos. 2000;105(D10):12517.View ArticleGoogle Scholar
- Smith JL, Halvorson JJ, Bolton Jr H. Soil properties and microbial activity across a 500 m elevation gradient in a semi-arid environment. Soil Biol Biochem. 2002;34(11):1749–57.View ArticleGoogle Scholar
- Leifeld J, Bassin S, Fuhrer J. Carbon stocks in Swiss agricultural soils predicted by land-use, soil characteristics, and altitude. Agr Ecosyst Environ. 2005;105(1–2):255–66.View ArticleGoogle Scholar
- Chu H, Fierer N, Lauber CL, Caporaso JG, Knight R, Grogan P. Soil bacterial diversity in the Arctic is not fundamentally different from that found in other biomes. Environ Microbiol. 2010;12(11):2998–3006.View ArticlePubMedGoogle Scholar
- Janssen PH. Identifying the dominant soil bacterial taxa in libraries of 16S rRNA and 16S rRNA genes. Appl Environ Microbiol. 2006;72(3):1719–28.View ArticlePubMed CentralPubMedGoogle Scholar
- Fierer N, Strickland MS, Liptzin D, Bradford MA, Cleveland CC. Global patterns in belowground communities. Ecol Lett. 2009;12(11):1238–49.View ArticlePubMedGoogle Scholar
- Girvan MS, Bullimore J, Pretty JN, Osborn AM, Ball AS. Soil type is the primary determinant of the composition of the total and active bacterial communities in arable soils. Appl Environ Microbiol. 2003;69(3):1800–9.View ArticlePubMed CentralPubMedGoogle Scholar
- Wagai R, Kitayama K, Satomura T, Fujinuma R, Balser T. Interactive influences of climate and parent material on soil microbial community structure in Bornean tropical forest ecosystems. Ecol Res. 2011;26(3):627–36.View ArticleGoogle Scholar
- Margesin R, Jud M, Tscherko D, Schinner F. Microbial communities and activities in alpine and subalpine soils. FEMS Microbiol Ecol. 2009;67(2):208–18.View ArticlePubMedGoogle Scholar
- Bach LH, Grytnes J-A, Halvorsen R, Ohlson M. Tree influence on soil microbial community structure. Soil Biol Biochem. 2010;42(11):1934–43.View ArticleGoogle Scholar
- Liang C, Fujinuma R, Wei L, Balser TC. Tree species-specific effects on soil microbial residues in an upper Michigan old-growth forest system. Forestry. 2007;80(1):65–72.View ArticleGoogle Scholar
- Ushio M, Wagai R, Balser TC, Kitayama K. Variations in the soil microbial community composition of a tropical montane forest ecosystem: Does tree species matter? Soil Biol Biochem. 2008;40(10):2699–702.View ArticleGoogle Scholar
- Singh BK, Millard P, Whiteley AS, Murrell JC. Unravelling rhizosphere-microbial interactions: opportunities and limitations. Trends Microbiol. 2004;12(8):386–93.View ArticlePubMedGoogle Scholar
- Williams MA, Jangid K, Shanmugam SG, Whitman WB. Bacterial communities in soil mimic patterns of vegetative succession and ecosystem climax but are resilient to change between seasons. Soil Biol Biochem. 2013;57:749–57.View ArticleGoogle Scholar
- Hegazy AK, El-Demerdash MA, Hosni HA. Vegetation, species diversity and floristic relations along an altitudinal gradient in south-west Saudi Arabia. J Arid Environ. 1998;38(1):3–13.View ArticleGoogle Scholar
- Bremner JM, Mulvaney RG. Methods of soil analysis. 2nd ed. Madison: American Society of Agronomy; 1982.Google Scholar
- Dowd SE, Sun Y, Wolcott RD, Domingo A, Carroll JA. Bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP) for microbiome studies: bacterial diversity in the ileum of newly weaned Salmonella-infected pigs. Foodborne Pathog Dis. 2008;5(4):459–72.View ArticlePubMedGoogle Scholar
- DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol. 2006;72(7):5069–72.View ArticlePubMed CentralPubMedGoogle Scholar
- Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7(5):335–6.View ArticlePubMed CentralPubMedGoogle Scholar
- Lozupone CA, Hamady M, Kelley ST, Knight R. Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities. Appl Environ Microbiol. 2007;73(5):1576–85.View ArticlePubMed CentralPubMedGoogle Scholar
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