Progress in Microbes and Molecular Biology 1 Original Research Article Microbial community diversity in the soil of Barrientos Island estimated by RAPD and Biolog Ecoplate methods Learn-Han Lee1, Vengadesh Letchumanan1, Nurul-Syakima Ab Mutalib2, Yoke Kqueen Cheah3* 1Novel Bacteria and Drug Discovery (NBDD) Research Group, Microbiome and Bioresource Research Strength (MBRS), Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, 47500, Selangor Darul Ehsan, Ma- laysia 2UKM Medical Molecular Biology Institute (UMBI), UKM Medical Centre, University Kebangsaan Malaysia, Kuala Lum- pur, Malaysia 3Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang 43300, Malaysia Abstract: The diversity of soil microbial communities at Barrientos Island with different soil characteristics were evalu- ated using PCR-based method random amplified polymorphic DNA (RAPD) and community level physiological profiles (CLPP) of Biolog Ecoplate. The soils were selected from 17 different locations around Barrientos Island inhabited by differ- ent breeders. Shannon-Weaver index and multivariate analysis were performed to characterize variations of soil microbial communities. Both RAPD and CLPP methods exhibited that most soils with different type of rookery and characteristics could possibly affect the DNA sequence diversity and soil microbial diversity. The abandoned type of rookery had the high- est Shannon-Weaver index as exhibited by soil sample 445 (3.4 for RAPD) and 450 (3.09 for CLPP). Higher coefficients of DNA sequence similarity were found in soil samples colonized by similar breeders, like soil 442 and 446 (both were active Chinstrap rookery) shared highest similarity in DNA sequences (73.53). The cluster analysis of RAPD profiles by UPGMA and principle component analysis (PCA) of Biolog Ecoplate exhibited similar influence of type of rookery and soil condition towards soil microbial community diversity. The results may suggest that the change in microbial community DNA composi- tion is accompanied with the change in microbial functional properties. Keywords: Microbial; diversity; random amplified polymorphic DNA (RAPD); Biolog; soil; Barrientos Island Received: 9th November 2019 Accepted: 10th December 2019 Published Online: 18th January 2020 Citation: Lee L-H, Letchumanan V, Ab Mutalib N-S, Cheah Y-K. Microbial Community Diversity in the Soil of Barri- entos Island Estimated by RAPD and Biolog Ecoplate Methods. Prog Microbes Mol Biol 2020; 2(1): a0000046. https:// doi.org/10.36877/ pmmb.a0000046 Introduction The soil microbial community is the most important composition of the soil ecosystem[1]. They are involved in many ecosystem processes such as nutrient transfor- mation, litter decomposition, plant health maintenance and soil organic matter formation[2]. Soil microbiological parameters, such as microbial biomass carbon and basal respiration have been suggested and used as possible indi- cators of soil quality[3–5]. Recently, soil microbial community structure is frequently used as indicators for soil quality and fertility[1]. Howev- er, the use of cultivation-based method to study soil mi- crobial community are proven to be challenging as only a small fraction of microorganisms (less than 10%) are culturable[6,7]. The limitation of culturable methods re- sulted in difficulty to understand the shift in the complex microbial community of soils[8]. These limitations could be overcome by using Biolog system and various mo- lecular methods such as RAPD, PCR-DGGE, RFLP and others[1,9–14]. The advancement of molecular methods has enabled various advancement and discovery in the study of microbial genomics[15–28]. The RAPD analysis uses arbitrary short primers that am- plify the intervening portion of the genome, and creat- ing variably sized amplicons[29] that could be applied to study soil microbial community structure[9] and bacteria genome[30,31]. RAPD has become a popular DNA-based method as it is rapid, simple and able to provide mean- ingful information about soil microbial community than isolate-based methods[32]. The Biolog system is used to assess community level physiological profiles (CLPP) of a soil sample. It is a means of investigating the func- tional diversity of soils as they could reflect how the soil microbial communities could utilize a range of carbon substrates[33]. In this study, RAPD and Biolog Ecoplate Copyright 2020 by Lee L-H et al. and HH Publisher. This work under licensed under the Creative Commons Attribution-NonCommer- cial 4.0 International Lisence (CC-BY-NC 4.0) *Correspondence: Yoke Kqueen Cheah, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang 43300, Malaysia. Email: ykcheah@upm.edu.my 2 methods were used to investigate the influence of soil characteristics like type of rookery on soil microbial community diversity. Material and Methods Environmental Sampling In 2007, during the XI Ecuadorian Antarctic Expedition to the Research Station “Pedro Vicente Maldonado”, Greenwich Island, South Shetland Islands, sampling for analysis of microbial communities from the soil was carried out at Barrientos Island (coordinates: S 62° 24’ 18.7” to S 62° 24’ 32.4” and W 59° 44’ 13.2” to W 59° 45’ 39.3”). Top soil samples of upper 20 cm layer (after removing the top 2–3 cm) were collected from 17 differ- ent sites within Barrientos Island. These sites have vari- ous interesting fauna and flora activities (Table 1). Soils were sampled into sterile plastic bags using an aseptic metal trowel, and kept in the dark for transport to Malay- sia. Soils were subsequently stored at -20°C, with an ali- quot stored at -80°C for molecular analysis like RAPD. While a portion of each soil sample was stored in 4°C and analyzed by Biolog Ecoplate assay. Table 1: Soil samples characteristics. Soil refer- ence Type of rookery / nest Soil condition 442 Active Chinstrap penguin Guano 443 Abandoned Gentoo penguin Guano 444 Abandoned Gentoo penguin No guano 445 Abandoned Gentoo penguin No guano 446 Active Chinstrap penguin Guano 447 Active Chinstrap penguin No guano 448 Active penguin No guano 449 Active Chinstrap penguin Guano 450 Abandoned Penguin Guano 451 Active Gentoo penguin (resting-deleted) area Guano 452 Abandoned Penguin Guano 453 Penguin resting area Guano 455 Active Gentoo penguin Guano 456 Abandoned Penguin No guano 457 Active Gentoo penguin No guano 458 Seal colony Guano 460 Giant Petrel nest No guano Soil DNA Extraction and Purification To minimize possible contaminants, all post-sampling manipulations were performed in a UV-sterilized lami- nar box hood, using sterile glass vials. Total soil DNA was extracted and purified from 1g dry weight of soil us- ing GF-1 Soil Sample Extraction kit (Vivantis, Selangor, Malaysia). The kit uses a specially-treated silica-based material fixed into a column to efficiently bind DNA in the presence of high salt. This kit applies the principle of a mini-column spin technology and the use of optimized buffers to ensure that only DNA is isolated while cellu- lar protein, humic acid and other low molecular weight impurities are removed during the subsequent washing stages. (Cat. No: GF-SD-025). DNA yield and quality were assessed by 0.8% (w/v) agarose gel electrophoresis following by DNA quantification using a Biophotometer (Eppendorf, Hamburg, Germany) and ratio A260/A280 was measured. Pure DNA has an A260/A280 ratio of 1.7–1.9. PCR Amplifications and Fragment Visualization RAPD arbitrary primer OPO 05 (5’-CCCAGTCACT-3’), OPO 06 (5’-CCACGGGAAG-3’) and OPO 18 (5’-CTC- GCTATCC-3’) was used for amplification of soil DNA by PCR using the Eppendorf Mastercycler (Eppendorf, Hamburg, Germany). The PCR reaction mixture consist- ed of ~10 ng of soil bacteria DNA, 2.0 ml of 10X opti- mized PCR buffer with 20 mM MgCl2, 2.0 ml of 10 mM dNTPs, 1 unit of Taq polymerase (Intron Biotechnology, South Korea) and 0.5 ml of 100 nM primer and sterile ultrapure water was added to final volume of 20 ml. The cycling parameters were 4 min at 94°C for pre-denatur- ation, 45 cycles each of 1 min at 94°C for denaturation, 1 min at 36°C for annealing, 1 min at 72°C for extension and 7 min at 72°C for final extension. The PCR amplifica- tion products were resolved by electrophoresis in 1.5% agarose gel (Promega, Madison, WI.), which was stained with ethidium bromide (0.5 mg ml–1) and viewed under a gel documentation system (Alpha Imager, Alpha Inno- tech, California). Data Analysis of RAPD Fingerprints Three arbitrary primers were used to amplify microbial community DNA from 17 soil samples. Since primer sequences were random and non-selective to soil DNA samples, amplification for one primer was equal to one random sampling from the whole microbial DNA se- quences[32]. The number of RAPD fragments was consid- ered to represent the RAPD fragment richness (S) of the whole DNA sequences. The calculations above rely on an assumption that each RAPD fragment contributes equally to the microbial diversity[32]. Since RAPD fragments amplified in all 17 soil samples contributed to the diversity of DNA sequences differ- ently as compared to those fragments amplified in only one, two, and three samples, it was necessary to make a modification for another diversity calculation. A fragment amplified in all 17 soil samples had the smallest contri- bution to the diversity because of no polymorphism, and therefore scored 0 for the diversity. A fragment ampli- fied in only one sample had the biggest contribution and scored 1. The other fragments, amplified in two or three samples, counted 2/3 or 1/3, respectively. This modifica- tion (modified richness, i.e., modified S), in fact, enlarged the contribution of the characteristic sequence to the DNA sequence diversity. The richness and modified richness of soil microbial community DNA sequences reflect to cer- Microbial Community Diversity... 3 tain extent the diversity of soil microbial community DNA sequences, but do not indicate the relative abundance of soil microbial community DNA sequences. Shannon-Weaver index is developed to measure the species diversity of the community by integrating species richness and abundance. Her, we used Shannon-Weaver index as a measure of soil microbial community DNA sequence diversity by molecu- lar marker. Diversity of soil microbial community DNA sequences was estimated using the equation below: S S Dsh = -∑ PilnPi = - ∑ (Ni / N)ln(Ni / N) I=1 I=1 where Dsh is Shannon-Weaver index, Pi is the percent of the ith RAPD fragment gray degree to each DNA sample, Ni is the net gray degree quantity (subtracted by the back- ground gray degree of a gel) of the ith RAPD fragment in each DNA sample, N is the total net gray degree quantity of all RAPD fragments examined in each DNA sample, and S is the number of RAPD fragments in each DNA sample. The range of Dsh is between 0 and ln(S). By merging the data of RAPD fragment net gray degrees from each primer into a single dataset, a cumulative diversity of Shannon- Weaver index was calculated for each sample using the same equation above. RAPD-based Cluster Analysis By using BioNumerics version 6.0 gel analysis software (Applied Maths, Kortrijk, Belgium), the position of the markers in RAPD gels were normalized from lane-to- lane and gel-to-gel variation. This normalization enables comparison of banding patterns originating from differ- ent RAPD gels, provided there was a high degree of gel reproducibility based on migration of standards. Then a binary matrix was constructed for each microbial commu- nity based on the presence and absence of bands. Jaccard’s coefficient (a similarity measurement) was used to calcu- late the matrix and the data were subjected to clustering based on the unweighted pair group method using arithme- tic averages (UPGMA) to identify samples that generated patterns similar to each other [34]. Results were displayed in dendrogram form to illustrate the relationship between microbial communities from different soil. Biolog EcoPlate Inoculation and Incubation One hundred and fifty ml of sediment slurry from each sample was placed in sterile 400 ml beakers. Physiologi- cal saline solution was added to bring the volume to 200 ml. The resultant slurry was sonicated in a water bath for 5 min before 15 ml of the supernatant was extracted and centrifuged at 500 g for 3 min. A 150 ml aliquot of the centrifuged supernatant was then used to inoculate a microtitre Biolog EcoPlate. Biolog EcoPlates have 96 wells that contain 31 unique carbon compounds, in ad- dition a control of distilled water repeated in triplicate. When bacteria use one of these carbon sources, tetrazo- lium dye is reduced by bacterial respiration and accu- mulates as insoluble formazin. These results in the well turning from clear to darker shades of purple depending on the amount of formazin produced[35]. Each plate was cultivated at 25°C for 168 h, and the optical density at both 590 nm (color development plus turbidity) and 750 nm (turbidity only) was read every 24 h[36]. Biolog Data Analysis The final values used to represent the activity in each well were the 590 nm values minus the 750 nm values after being corrected for readings in the control well at these wavelengths. Well optical density values that were negative or under 0.06 were set to zero[36]. Average well color development (AWCD) was calculated as described by Garland and colleagues, i.e. AWCD (590–750 nm) = Σ(C590–750)/31, where 31 represents the number of car- bon sources used in Biolog EcoPlate. The final values of each well at 168 h were used to calculate the Shan- non’s diversity index (H), where H = − Σ(PilnPi), Pi is the proportional optical density value of each well, and Pi=C590–750/Σ (C590–750). Normalized data were analyzed by principal component analysis. Results RAPD Analysis In the present study, 3 arbitrary primers were used to amplify soil microbial DNA. The RAPD pattern gen- erated by arbitrary primers OPO 05, 06 and 18 for 17 soil samples were shown in Figure 1 as gel photo. Three primers generated a total of 416 RAPD fragments with OPO 05, OPO 06 and OPO 18 generated 130, 142 and 144 fragments, respectively. The number of fragments scored per primer ranged from 1 to 11, 5 to 11 and 3 to 12 for primer OPO 05, 06 and 18, respectively. Eight of the total fragments (1.9%) were polymorphic. The ra- tio of polymorphic fragments in each primer was 3.1% (OPO 05), 1.4% (OPO 06) and 1.4% (OPO 18), respec- tively (Table 2). Lee L-H et al. Table 2: Three primer amplified outputs to microbial community DNA from 17 soil samples. Primers Amplified Fragment Non-polymorphic Amplified fragments Polymorphic fragments Ratio of polymorphic frag- ments to total fragments OPO5 130 126 4 3.1% OPO6 142 140 2 1.4% OPO18 144 142 2 1.4% Total 416 408 8 1.9% 4 Microbial Community Diversity... Figure 1: RAPD fingerprint for 17 soil samples for OPO 05 (A), OPO 08 (B) and OPO 18 (C). Lane “M” contain DNA molecular weight markers. The numbers indicate the soil sample number as in Table 1. 5 RAPD analysis — Diversity of Soil Microbial Com- munities DNA sequence RAPD fragment richness (S) in DNA for 17 soils mi- crobial communities in Barrientos Island are shown in Table 3. Average RAPD fragments richness for sample 445 and 446 were both 10.7, respectively, which were the highest richness among all soils from Barrientos Is- land. Soil sample 443, 456 and 444 were the subsequent samples with high average richness value of 10, 9.3 and 9, respectively. Whereas soil 457 contain the lowest rich- ness, with average only 4 RAPD fragments per primer. Three soils comprised of relatively low richness, which is 457, 458 and 455 with 4, 4.3 and 5.3 RAPD fragments per primer, respectively. The modified richness (modified S) for 17 soils showed that sample 445 had the highest value for average of modi- fied richness (7.09); as soil 457 had the lowest value (2.44) (Table 4). By assigning a standard value of 1 for modified richness for the soil with the highest diversity (445), soils with high richness value were 445, 445 and 443 with 1, 0.95 and 0.91, respectively. The Shannon-Weaver indices (Dsh) for microbial community at RAPD are shown in Table 5. The cumulative diversities of Shannon-Weaver indices for 445 were the highest (3.40), whereas 457 was the lowest (1.16). Coefficient of DNA sequence similarity indicated differences between soils at DNA level (Table 6). Coefficient of DNA sequence similarity was the high- est (73.53) between sample 442 and 446. The similarity coefficient between sample 447 (active Chinstrap penguin rookery) and sample 458 (seal colony rookery) was the lowest (6.07). Lee L-H et al. Table 3: Richness (S) for soil microbial community in 17 soil samples at DNA level. Primer Soil samples 442 443 444 445 446 447 448 449 450 451 452 453 455 456 457 458 460 OPO5 7 10 6 9 11 7 9 9 9 10 5 7 5 6 1 4 9 OPO6 7 9 9 11 11 9 9 8 8 6 9 6 7 11 8 5 9 OPO18 12 11 12 12 10 7 7 7 8 5 7 10 4 11 3 4 8 Total 26 30 27 32 32 23 25 24 25 21 21 23 16 28 12 13 26 Average 8.7 10 9 10.7 10.7 7.7 8.3 8 8.3 7 7 7.7 5.3 9.3 4 4.3 8.7 Table 4: Modified Richness (Modified S) for soil microbial community in 17 soil samples at DNA level. Primer Soil samples 442 443 444 445 446 447 448 449 450 451 452 453 455 456 457 458 460 OPO5 3.50 5.88 3.31 5.69 6.44 3.31 6.56 5.19 6.38 6.56 2.88 4.13 3.63 4.06 0.69 2.63 6.5 OPO6 3.56 5.81 4.56 6.88 7.00 5.00 6.06 4.44 4.63 3.56 6.06 2.94 4.75 7.69 5.19 3.13 5.88 OPO18 7.88 7.69 8.25 8.69 6.81 4.50 4.56 3.56 4.88 3.13 5.00 6.69 2.50 7.25 1.44 2.13 4.94 Average Modified S 4.98 6.46 5.37 7.09 6.75 4.27 5.73 4.40 5.30 4.42 4.65 4.59 3.63 6.33 2.44 2.63 5.77 Relative Value 0.70 0.91 0.76 1 0.95 0.60 0.81 0.62 0.75 0.62 0.66 0.65 0.51 0.89 0.34 0.37 0.81 Table 5: Shannon-Weaver diversity indices (Dsh) of microbial community in 17 soil samples from random amplified polymorphic DNA (RAPD) and community level physi- ological profiles (CLPP) analysis. Methods Soil samples 442 443 444 445 446 447 448 449 450 451 452 453 455 456 457 458 460 RAPD 2.38 3.10 2.58 3.40 3.23 2.04 2.75 2.11 2.55 2.11 2.24 2.21 1.73 3.03 1.16 1.26 2.75 CLPP 2.58 2.63 2.01 1.65 2.32 1.75 1.74 2.84 3.09 2.81 2.90 2.55 2.86 2.49 2.46 3.04 2.54 6 Microbial Community Diversity... Ta bl e 6: J ac ca rd ’s a ve ra ge s im ila ri ty c oe ffi ci en t o f 1 7 so il sa m pl es g en er at ed b y U PG M A a na ly si s. So il sa m pl es 44 2 44 3 44 4 44 5 44 6 44 7 44 8 44 9 45 0 45 1 45 2 45 3 45 5 45 6 45 7 45 8 46 0 44 2 10 0. 00 44 3 58 .2 9 10 0. 00 44 4 47 .1 1 49 .3 7 10 0. 00 44 5 58 .8 9 64 .3 3 48 .8 9 10 0. 00 44 6 73 .5 3 67 .7 1 61 .1 5 61 .6 2 10 0. 00 44 7 50 .3 8 56 .6 7 72 .7 5 40 .7 1 60 .8 8 10 0. 00 44 8 29 .0 2 35 .3 6 22 .9 3 18 .8 6 33 .9 0 23 .6 5 10 0. 00 44 9 46 .9 5 49 .0 3 51 .8 2 35 .3 3 53 .2 9 58 .1 9 33 .3 7 10 0. 00 45 0 43 .1 1 44 .0 2 47 .7 6 41 .6 1 38 .9 3 45 .3 8 18 .5 9 31 .5 0 10 0. 00 45 1 35 .1 0 36 .3 1 30 .6 3 23 .9 7 28 .2 6 24 .8 5 35 .4 5 33 .3 3 30 .8 0 10 0. 00 45 2 46 .6 7 47 .6 2 33 .0 6 35 .5 1 48 .1 1 55 .6 1 14 .6 5 46 .8 3 36 .4 5 23 .6 9 10 0. 00 45 3 32 .9 7 34 .1 7 21 .0 1 32 .2 9 31 .7 7 27 .1 5 37 .8 8 33 .3 3 35 .7 2 25 .9 7 23 .4 9 10 0. 00 45 5 24 .7 8 21 .7 2 33 .7 5 32 .9 2 26 .4 3 22 .0 9 14 .6 1 21 .3 7 20 .7 9 42 .0 3 23 .2 3 23 .7 1 10 0. 00 45 6 45 .8 7 28 .6 9 20 .6 4 37 .1 9 33 .9 9 27 .3 9 26 .1 5 44 .4 5 33 .7 9 27 .6 7 49 .7 5 25 .7 1 30 .4 7 10 0. 00 45 7 20 .4 5 22 .8 2 39 .9 7 35 .9 5 33 .4 3 22 .4 5 12 .9 7 17 .6 3 34 .2 9 34 .7 0 26 .3 9 23 .9 9 26 .6 7 22 .4 5 10 0. 00 45 8 15 .7 9 23 .2 3 17 .2 5 17 .5 0 24 .9 1 6. 07 ** 30 .9 1 6. 67 16 .2 4 13 .8 9 6. 67 29 .2 9 9. 53 19 .4 0 44 .4 5 10 0. 00 46 0 25 .0 0 29 .8 7 40 .2 7 38 .8 9 34 .7 6 40 .5 1 28 .2 9 13 .0 6 51 .3 6 21 .7 7 37 .7 8 26 .6 7 17 .9 9 30 .2 8 37 .6 8 37 .6 8 10 0. 00 7 RAPD analysis — UPGMA analysis of RAPD profiles RAPD profiles were subjected to clustering based on un- weighted pair group method using arithmetic averages (UPGMA) to identify soil samples that generated pat- terns similar to each other. UPGMA of 17 soil samples using composite analysis of OPO 05, 06 and 18 revealed 8 clusters (Figure 2) that clade together. Within the 8 clusters produced, 5 clusters (I, III, IV, VI, VII) com- prised soil samples from similar type of rookery in each respective cluster. However, some soil samples from dif- ferent type of rookery were clustered together, i.e clus- ter II, V and VIII. Cluster I comprised of 2 abandoned Lee L-H et al. penguin rookeries (452 and 456). Cluster II consisted of 1 abandoned penguin rookery (444) and 2 active Chinstrap rookeries (447 and 449). Cluster III contained 2 active Chinstrap rookeries (442 and 446) at high similarity level of 73.5% (Table 6). Cluster IV comprised 2 abandoned penguin rookeries (443 and 445) while cluster V contained 2 rookeries from abandoned penguin rookery (450) and petrel nest (460). Cluster VI comprised of 2 penguin rest- ing rookeries (448 and 453) whereas cluster VII consisted of 2 active Gentoo rookeries (451 and 455). Lastly cluster VIII comprised of active Gentoo (457) and seal colony (460) type of rookeries. Figure 2. Dendrogram derived from RAPD composite analysis of arbitrary primer OPO 05, 06 and 18. A total of 8 clusters were formed from 17 soil samples used in this study. Biolog analysis — Average well color development AWCD of Biolog Ecoplates is an important index for el- evated diversity of soil microbial biomass function. The values represent the changes of soil bacterial community activity in utilizing catabolic diversity in different type of rookery. The AWCD generally followed the same pattern with incubation time, but the pattern varied for differ- ent soil samples (Figure 3). In general, the AWCD value was the highest in sample 458 (active seal rookery), and lowest in sample 444 (abandoned penguin rookery). The AWCD values represent the metabolic activity of soil mi- crobial community in using the carbon sources, thus pro- posed that the effect of rookery activities have influence on soil bacteria community metabolic function. Biolog analysis — Shannon’s diversity Differences in the Shannon-Weaver index of the soil bac- terial community of different rookery after incubating for 168 h in Biolog Ecoplate were observed (Table 5). The Shannon indices were significantly highest in sample 450, a soil with penguin abandoned type of rookery and soil surface covered by lots of guano. While sample 445 and 448 with low Shannon indices of 1.65 and 1.74, re- spectively showed no guano at that area. Biolog analysis — Principle component analysis The principle component analysis was conducted to bet- ter understand differences in carbon utilization by soil microorganism. The PCA plot shows that carbon sub- strate utilization profiles were able to clearly separate soil samples to group according to type of rookery (Figure 4). Five significant groups were formed (A, B, C, D, E), each according to certain type of rookeries. Group A and B comprised of 3 (443, 444, 445) and 2 (452, 456) aban- doned rookeries, respectively. Group C consisted of soil samples from active Chinstrap penguin rookeries (442, 446, 447, 448). Group D comprised of penguin areas (453, 457) while group E consisted of Gentoo penguin active rookeries (451, 455). 8 Microbial Community Diversity... 0 0.2 0.4 0.6 0.8 1 1.2 24hrs 48hrs 72hrs 96hrs 120hrs 144hrs 168hrs 442 443 444 445 446 447 448 449 450 451 452 453 455 456 457 458 460 1 Figure 3. Difference in AWCD of soil bacterial community over time for 17 different soil samples. Figure 4. Principle component analysis (PCA) of Biolog EcoPlate data from different soil samples of Barrientos Island. Discussion The potential microbial diversity as an indicator of soil quality is impeded due to the difficulties in measuring[9]. Microbial population in soils are very large, with more than 109 organisms per gram of soil[37,38]. It is also very diverse with more than 104 species per gram of soil[39]. Only 1–10% of these microbes can be isolated and stud- ied in pure culture, therefore, various microbial methods are emerging as useful tools to study microbial commu- nities in soils[9,40]. The difference among microbial species is fundamen- tally signified in their genetic diversity at DNA sequence and their metabolic function. Therefore, molecular meth- od like RAPD and substrate utilization pattern (Biolog Ecoplate) can be used to study soil microbial commu- nity diversity[9]. PCR-based technique like the RAPD has become a popular method to assess soil microbial community as it is simple, rapid and sensitive means to identify small variations between similar genomes[41,42]. The Biolog system was initially developed for bacterial identification. Later the system has found to be useful to characterize soil microbial diversity from various differ- ent environments like soil, sediments, freshwater and sea- water[35]. The substrate utilization patterns of the Biolog system have been used to provide “fingerprints” of micro- bial community structure[43,44] and also as an indication of metabolic potentials[45,46]. The multivariate analysis of the utilization pattern of different carbon substrates generated from the 96-well Biolog Ecoplates enables the classifi- cation of microbial community functional diversity. The substrate utilization patterns in this study successfully dif- ferentiated most of the soil samples according to different type of rookery. 9 Lee L-H et al. In this study, the RAPD analysis demonstrated that dif- ferent type of rookery activities could considerably af- fect soil microbial communities. As 80% (4/5) of high- est RAPD fragment rich samples were from abandoned penguin rookeries (445, 443, 444, 456) (Table 1, Table 3). Compared to soil samples with active breeders’ type of rookeries (i.e. 457, 458, 455) that exhibited average richness range from 4–5.3, soil samples of abandoned penguin rookeries (443, 444, 445, 450, 452, 456) showed much higher average richness with value range from 7–10.7 (Table 3). The Shannon-Weaver indices (Dsh) for the microbial community at RAPD in the 17 soils showed the average Shannon indices for abandoned penguin rookeries (443, 444, 445, 450, 452, 456) were significant- ly higher than that of rookeries with active breeders (i.e. 457, 458, 455). This observation is indeed interesting and warrant further study to understand these patterns. For Biolog Ecoplate analysis of Shannon-Weaver indices, 77% (442, 443, 446, 449, 450, 451, 452, 453, 455, 458) of soil samples with high Shannon index (>2.3) (Table 5) were soil samples covered with guano, these could possibly infer that catabolic diversity of the soil bacte- rial community could be increased with the existence of organic manure like guano [1]. Soil samples namely 445 (3.4 for RAPD) and 450 (3.09 for CLPP) which exhib- ited highest Shannon index for RAPD and CLPP were both from abandoned type of rookeries. Soil samples like 443, 450 and 452 all shared high Shannon index in both RAPD and Biolog methods used. Overall the correlation of Shannon index between RAPD and Biolog is not re- ally strong, this could be due to the variance of targeted microbes in both methods, as Biolog method only reveals fast growth bacteria activity only. In regards to coefficient of DNA sequence similarity, re- sults indicated the possibility of different samples colo- nized by different breeders caused a shift in the species composition of soil microbial communities. As for most of the soil samples colonized by similar breeders, com- paratively higher coefficients of DNA sequence similar- ity were found, like sample 442 and 446 (both active Chinstrap rookery) shared highest similarity in DNA se- quences (73.53) (Table 6). The AWCD analysis of Biolog Ecoplates revealed chang- es of soil bacterial community activity in utilizing cata- bolic diversity in different type of rookery. From 10 soil samples with highest AWCD values, 7 were from active breeders’ rookeries and only 3 were from abandoned type of rookeries. The average AWCD value for all the 9 ac- tive breeders rookeries (442, 446, 447, 449, 451, 455, 457, 458, 460) were 0.4203, which is significantly higher than average AWCD of 6 abandoned rookeries (443, 444, 445, 450, 452, 456) with value of 0.2998. Therefore, this suggested that the metabolic activity of soil bacteria was higher in active breeders’ rookeries and lower in aban- doned type of rookeries. As a result, this observation showed that the effects of rookery activities have influ- ence on soil bacteria community metabolic function. The cluster analysis of RAPD profiles by UPGMA showed great similarity in DNA profiles for microbial communities that shared similar type of rookery. Total 63% (5/8) of the clusters formed were from similar type of rookery in each respective cluster (Figure 2). These results suggest that there was a systematic change in the sequence diversity associated with different type of rookery at sampling sites. The PCA results of Ecoplate showed that carbon substrate utilization profiles were able to clearly separate most soil samples (76%) to group according to type of rookery (Figure 4). Sample 458 and 460, inhabited by seal and petrel respectively, both were evidently separated from the rest of the samples which were inhabited by penguins. This observation from CLPP method revealed that there is positive influence of type of rookery and soil condition towards soil microbial com- munity diversity. In generally, combination of molecular methods with other tools can be used to improve our understanding of the effect of different soil characteristics to soil mi- crobial diversity. In this study, the genetic diversity of microbial populations by RAPD genetic fingerprinting and metabolic diversity using Biolog substrate utiliza- tion assays were used to investigate the effect of differ- ent type of rookery activities and characteristics on soil microbial populations. Both RAPD and CLPP method revealed the similar influence of type of rookery and soil condition towards soil microbial community diversity. The results may suggest that the change in microbial community DNA composition is accompanied with the change in microbial functional properties[9]. Nonetheless, both the methods have limitations in determining soil mi- crobial community. The RAPD method may be affected by effects of PCR bias, like the size of random primer, sensitivity to reaction conditions and the possibility of co-migration[47,48]Applications of random amplified poly- morphic DNA (RAPD. The Biolog system assesses the metabolic diversity of culturable bacteria only. It is a sys- tem that could indicate activity of the fast growth bacte- ria or eutrophic bacteria only. Therefore, microorganisms like slow-growing bacteria, fungi and uncultured bacteria activity are expected to have minimal influence on the microbial metabolite profile[49,50]. So, only a part of soil microbial characteristics was discovered by the Biolog Ecoplate method. As a conclusion, it is necessary to incorporate compre- hensive approaches at diverse level, including traditional, metabolic and molecular level to understand more pre- cisely about the changes in the diversity of microbial communities[32,51]. Author Contributions The research and manuscript writing were performed by LH-L, NS-AM and VL. L-HL and Y-KC founded the re- search project. Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. 10 Reference 1. Guanghua W, Junjie L, Xiaoning Q, et al. Effects of fertilization on bacterial community structure and function in a black soil of Dehui region estimated by Biolog and PCR-DGGE methods. Acta Ecologica Sinica 2008; 28(1): 220–226. 2. Zelles L. 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