Biosci. Biotech. Res. Comm. 6(2): 150-157 (2013)

Estimation of diversity, abundance and composition of bacterial population in tropical lake sediments using terminal restriction fragment technique

Varsha Wankhade

Department of Zoology, University of Pune, MS, India


Soil bacteria carry out various ecological roles in the ecosystem. Diverse microbial community could be present in the soil. Very less knowledge is available regarding the association between soil structure and bacterial diversity. Soil bacteria are good indica- tors of soil health and soil fertility. The bacterial communities of soil/sediment of lake are affected by the environmental biotic, abiotic, natural and/or man made conditions. In the present study, bacterial diversity of soil/sediment of Sawanga Vithoba lake has been assessed by full form terminal restriction fragment length polymorphism in December and March. Bacterial diversity has been found to be rich, which ranged from 1 to 28 with an average number of restriction fragments 14.



Soil bacteria are vital components of the ecosystems and microbial community in the soil has been reported to be rela- tively diverse (Curtis et al., 2002; Robe et al., 2003), with the highest prokaryotic diversity compared to other environments (Van et al., 2006; Roesch et al., 2007). One gram of soil has been reported to contain up to 10 billion microorganisms and thousands of different species (Knietch et al., 2003). Soil bac- teria are genetically diverse and represent a major unexploited genetic resource (Whitman et al., 1998).

Diversity, abundance and composition of microbial commu- nities within soils are depth dependent. Changes in microbial community structure with soil depth are due to the response of


*Corresponding Author Received 20th October, 2013

Accepted after revision 31st December, 2013 BBRC Print ISSN: 0974-6455

Online ISSN: 2321-4007

©A Society of Science and Nature Publication, 2013. All rights reserved.

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microbes to the physico-chemical conditions (Holden and Fierer, 2005). Environmental factors such as pH (Eichorstet et al., 2007), particle size (Sessitsch et al., 2001), organic carbon content (Zhou et al., 2002), nutrient availability (Fiereret et al., 2003), water content (Treves et al., 2003), and oxygen concentration (Lude- mann et al., 2000) also affect the microbial community com- position and diversity. Thus, the physiology and metabolic potential of microbial communities may vary with location. In the soils/sediments mineral and organic matter components are organized into aggregates with varying size, porosity, pore size and continuity, and composition.

Microaggregates (2 to 20 μm) are considered to be the most favorable habitat for bacteria in most types of soil (Ranjard and Richaume, 2001), with a higher abundance of bacteria located in micropores (~2 μm) of the inner aggregate fraction (Hattori, 1988; Ranjard et al., 2000). Little is known regarding


the association between soil structure and bacterial diversity (Ranjard et al., 2000),

Microbial community composition may change with the location within (Jocteur-Monrozier et al., 1991, Ranjard et al., 1997) and size of (Kanazawa and Filip, 1986; Sessitsch et al., 2001; Vaisanen et al., 2005) soil aggregates. Aggregates of soil may support a diverse microbial community than the bulk soil by imposing size exclusion on selected biota from restricted pore domains (Bales et al., 1989; Champ and Schroeter, 1988), minimizing predation (Wright et al., 1995), and/or decreasing competition as a consequence of lower water tensions (Treves et al., 2003).

Anaerobic microsites within aggregates in aerobic soils may allow for a diverse range of aerobic- and anaerobic-based metabolisms that contribute to the bulk chemical fluxes of nutrients and metabolites within soils. Bacteria such as Cre- narchaeota have been directly linked to chemoautotrophic nitrification (Konneke et al., 2005) and are reported to be involved in carbon metabolism (Kemnitz et al., 2007) and amino acid uptake/assimilation (Ouverney and Fuhrman, 2000; Teira et al., 2006 ). Bacteria play important roles in nitrogen cycling (Kowalchuk and Stephen, 2001; Tiedje and Stevens 1988), carbon cycling (Hogberg et al., 2001), transfor-mation of met- als such as iron, manganese, and mercury (Paul and Clark, 1989), addition of organic humic content (Gobat et al., 2004) as well as soil formation (Rillig and Mummey, 2006). Bacteria are also required for nutrient acquisition in the soil ecosystem and therefore contribute to plant nutrition and health (George and Jakobsen, 1995; Timonen et al., 1996). Soil bacteria can exert positive or negative control over other organisms in the environment through the synthesis of antibiotics or growth factors like vitamins (Gobat et al., 2004). These bacteria are reported to involve in the biodegradation of human-made pol- lutants (Boubakri et al., 2006; Galvao et al., 2005).

Soil bacteria are good indicators of soil health, soil fertility (Yao et al., 2000; O’Donnell et al., 2001) and ecosystem status in much more comprehensive way than physical or chemi- cal measures (Fierer and Jackson, 2006; Winding et al., 2005). Bacteria from specific taxa have been allied to definite eco- logical characteristics. For example, the presence of nitrogen fixers such as Rhizobia and Azotobacter and nitrifying bacteria (Nitroso-) indicates high N levels in the soil. Likewise, presence of copiotrophic bacteria such as Acidobacteria indicates low nutritional status, while the presence of oligotrophic bacte- ria such as ß-Proteobacteria and Bacteriodetes indicates high nutritional status (Fierer et al., 2007).

Bacteria are also responsive to man made activities such as agriculture, pesticide use and pollution (Deiglmayr et al., 2004; Klumpp et al., 2003). Soil microbial communities may alter their metabolic and genetic capability in response to changes in the environmental factors which result in rapid shifts in bacterial diversity within short period of time frame (Schmidt et al., 2007). Understanding soil microbial communities is therefore an ideal method to monitor the ecological changes occurring between seasons as well as over an extended period of time (Hill et al., 2000).

The variability of species richness and diversity index among enzyme digestions may be related to the fact that the same T-RF can be generated by different species of bacteria

Varsha Wankhade

(Marsh et al., 2000). The species of bacteria producing a par- ticular T-RF by one restriction enzyme digestion may produce more than one T-RF by another enzyme digestion, and vice versa. So, the peaks or ’genotypes’ may have different com- positions of species n different enzyme digestions. The number and area of T-RFs varied on the basis of different species com- positions. Accordingly, the species richness and the diversity index changed. Further, the variation among observed and theoretical T-RFs depend on the restriction enzyme selected (Kaplan and Kitts, 2003). The ’precision’ of enzyme digestion affected the definition of T-RFs and consequently determina- tion of the number and area of T-RFs.

In the resent communication, it is hypothesized that soil/ sediment bacterial communities of the Sawanga Vithoba lake do exhibit diversity and affect the ecological processes in the lake. The bacterial communities of soil/sediment of lake are affected by the environmental biotic, abiotic, natural and/or man made conditions. To my knowledge, no previous study has examined the bacterial diversity of the of soil/sediment of Sawanga Vithoba lake. It is hypothesized that the biogeo- graphical patterns exhibited by soil/sediment bacterial com- munities of lake could be fundamentally similar to the patterns observed with plant and animal taxa. Soil/sediment bacterial communities of lake could be a good predictor of the status of the particular ecosystem, metabolic processes going on inside that ecosystem and energy balance. In this study, soil/sedi- ment’s bacterial diversity were studied to monitor the ecologi- cal system in this region by T-RFs.



For the present study, three stations were selected. Station two is west station, station three is north station and station four is south station. Station two is near the village (Sawanga Vithoba). Other stations of the lake are surrounded by veg- etations. Soil(sediment) samples from the lake bottom were collected as described in the soil kit (make: Prerana), samples were transformed to sterilized plastic or glass containers and transported to the laboratory. The bacterial analysis was per- formed in the months of December and March.


a. DNA isolation from environmental samples

For processing of soil samples 0.5g of soil was added to 2ml screw-capped microcentrifuge tubes containing 0.5 g each of 0.1 mm glass beads. STE buffer, lysozyme and proteinase K(10g/ml) were sequentially added for nucleic acid isolation. This method employed the process of NaCl and SDS lysis fol- lowed by Phenol: chloroform: iso-amyl alcohol based organic extraction for purification of nucleic acids.

The DNA was deproteinised thrice with Tris-satured phe- nol (phenol:CHCl3: iso-amyl alcohol, 50:48:2), and then with CHCl3:iso-amyl alcohol (24:1) and precipitated with 2% sodium

Varsha Wankhade

acetate and absolute ethanol. Dried DNA was dissolved in 30μl nuclease free water. Quality assessment of genomic DNA was performed by 1% agarose gel electrophoresis and estimated using aQubit^TM Fluorometer(Invitrogen,USA). DNA extrac- tion from positive control sample (E. Coli) was also performed to rule out the possibility of extraction failure. Similarly, a negative control (plain saline) was also subjected to extraction to establish the clean reagents.

b. PCR amplification of the 16S gene

The bacterial 16 S rRNA gene was amplified by PCR using the primer set 8F:5’-AGAGTTTGATCATGGCT CAG-3’ and 1491R; 5’-GGCTACCTTGCCACGACTTC-3’ (Lane, 1991). The 8F primer was labeled at the 5’end with HEX fluorescent dye. The PCR mixture was 0.5μl of each primer (10mM), 5μl of the PCR buffer,1μl of dNTP (2.5mM), 0.5μl of Taq polymerase( 2.5 U/μl) and double-distilled water for final reaction volume of 50μl. PCR was performed at 95°C for 5 min; 30 cycles of 95°C for 1 min, 55°C for 1 min and 72°C for 1 min; and 72°C for 10 min. PCR products were checked on 1% agarose gels and purified with the gene O-spin PCR purification kit(geneOmbio Technologies,India) according to the manufacturer’s protocol.

c. Restriction digestion and desalting of digested products

Following PCR, 10μl of PCR products were digested with 0.5 U of Taq I restriction enzymes (New England Biolabs) for 3 hours at 37°C in 20μl reaction volumes. Digests were separated on 3% agarose gels in 1X TBE buffer containing ethidium bro- mide, and visualized under UV light.

10μl of the digested DNA was desalted using the follow- ing procedure: 2.5μl of 125mM EDTA and 1/10 volume of 3M sodium Acetate pH 5.2 was added to 10μl of digested DNA. Further 2.5 volume of ice cold ethanol was added into the tubes and mixed well. Tubes were then centrifuged at 12000 RPM for 20 minutes at 18°C. Supernatant was removed being careful not to dislodge the pellet. Pellet was then washed with 60μl of 70% Ehtanol twice with centrifugation at 12000RPM for 20 minutes at 18°C temperature. Pellet was then dried at 37°C for 30 minutes.

d. Sample preparation and loading

Hi-Di Formamide (9.7μl) from Applied iosystems was added to the dried pellet. Each sample was added with 0.3μl GenScan 500 LIZ Internal size standard. This mixture was denatured at 95°C for 3 minutes and immediately chilled on ice before loading. The samples were then subjected to electrophoresis on the 3130 Genetic Analyzer using the FA 36 POP-7TM run module and G5 dye set.

e. Gene Mapper data analysis

Gene Mapper software based analysis was performed for frag- ment analysis after completion of the capillary electrophoresis. Output from automated sequencers is in the form of an elec- tropherogram, with peaks representing fluorescently labeled T-RFs detected over time in relation to the size standard. The duration and intensity of the fluorescent signal from T-RFs is reflected in the area and height of each peak detected, respec-

tively. Software specific to each sequencing unit collects data from each run. The ABI 3730 capillary sequencer operates, Gene Mapper v3.5 (Applied Biosystem), which performs the functions of both GeneScan and Genotyper. Either data col- lection program provides researcher with several algorithms for sizing sample fragments by comparing their mobility with that of the size standard. Once data are processed and frag- ment lengths assigned, the data set is typically imported into a spreadsheet program, such as Microsoft Excel (Microsoft Corp., Redmond, WA). In the spread-sheet, sample identifiers can be added and presence/absence (1,0) matrices developed. Other manipulations, such as matrix inversions, can also be performed. The T-RFs for each sample run should be closely examined and the entire run evaluated for the average number of T-RFs detected per sample and the number of T-RFs con- tained in the various size classes.


After T-RFs analysis, different restriction fragments were observed. It was observed that all the sediment samples of the selected stations contain diversed bacterial community. It was also observed that the highest number of the restriction fragments were at station number three which is the north station of the lake. At this station total number of the restric- tion fragments was 28. Total numbers of restriction fragments were more in the month of March. At station two (east sta- tion, which is near village), on March 6 restriction fragments were observed. Station three is the north station which is sur- rounded by vegetation showed 03 restriction fragments in December while 28 in March. Station four is the south station which is also surrounded by vegetation shows 05 restriction fragments in December and 08 in March. The restriction frag- ments are depicted in table1. The average restriction fragments for the sediments of the lake was found to be 04 in December while in March it was 14 . Bacterial population was found to be more in the month of March.


TABLE 1: Total number of terminal Restriction Fragments(T-RFs) generated for each sample

Total No of T-RFs


The bacterial richness is the types of fragments obtained and elucidated in the T-RFLP technique, where each fragment is considered to arise from a different bacterial strain. Bacterial richness ranged from 1 to 05 in December with an average of 4 while range from 1 to 28 with an average of 14 in March. The highest richness was observed in the sample of station 3 which

is a north station of the lake. Total number of 50 different taxa (designated as allele in the supplementary data) were observed as per the size of the T-RFs.


The result of a T-RFLP profiling is a graph called Electro- pherogram,which is an intensity plot representation of an electro- phoresis experiment(gel or capillary).In an electropherogram the X-axis marks the sizes of the fragments (basepairs) while the Y-axis marks the fluorescence intensity in fluorescent unit of each frag- ment. Thus, what appears on an electrophoresis gel as a band appears as a peak on the electropherogram whose integral is its total fluo- rescence. In a T-RFLP profile each peak assumingly corresponds to one genetic variant in the original sample while its height corre- sponds to its relative abundance in the specific community. Often, several different bacteria in a population might give a single peak on the electropherogram due to the presence of a restriction site for the particular restriction enzyme used in the experiment at the same position. T-RFs having size less than 40 bases were eliminated from the analysis as they might result from primer-dimers. Fluorescent signal threshold was set to 400 fluorescent units as per the standards to minimize the background signal and signals arising from ssDNA non-specific amplicons/fragments.

In the present study, bacterial diversity of soil/sediment of lake Sawanga (Vithoba) was assessed. The soil /sediment bac- teria were tried to identify upto phylum level by 16S rDNA. Employing the 16S rDNA gene for this purpose is proper due to the ubiquitous nature of the gene and extremely low mutation rate and its phylogenetic significance (Ludwig1999; Ludwig and Schleifer1994). RFLP analysis of the 16S rDNA was used

Varsha Wankhade

as an initial estimator of bacterial diversity. Indeed, it is well established that RFLP analysis of 16S rDNA can be used to study bacterial diversity (Moyer et al., 1994; Moyer, 1996).

In Table No. 4, the probable bacteria in the sediment/soil sample of the Sawanga Vithoba lake have been tested.

The composition and diversity of soil bacterial communities have a straight effect on many ecosystem processes (Schimel, 1995; Balser et al., 2002). Diversity of soil bacterial com- munities, soil microbial ecology, diversity of soil bacteria are affected by environmental biotic and abiotic factors (Buckley and Schmidt, 2002).

Ecological monitoring is crucial for assessing the environ- mental effects. There are previous studies on characterization of the dominant bacteria in environmental samples by using 16S rDNA molecular signatures . RFLP analysis of 16S rDNA can be used to study bacterial diversity. The bacterial diversity in soil is high (Dunbar et al., 2002; Tringe et al., 2005). More species could be found with greater sampling sizes. Thus, this study has been successful at establishing a baseline of bacte- rial diversity in soil/sediment of Sawanga (Vithoba) lake of Pune, India.


Special thanks to Director of ISRO-UoP for providing us finan- cial assistance. The author is also grateful to The Principal hief onservator of Forest (P F), Government of Maharash- tra for giving permission to conduct the present study. The author is also thankful to BCUD, University of Pune for partial

financial support.

FIGURE 1: Bacterial analysis of Sawanga Vithoba lake sediment samples in ecember (winter) and in March (summer).

Varsha Wankhade

FIGURE 2: Electropherogram of the bacterial popu- lation for the North station in December.

FIGURE 3: Electropherogram of the bacterial population for the South station in December.

FIGURE 4: Electropherogram of the bacterial population for the station two (west station) in March.

FIGURE 5: Electropherogram of the bacterial pulation for the station three (north station) in March.

FIGURE 6: Electropherogram of the bacterial population for the station four(south station) in March.

Varsha Wankhade

TABLE 2: Probable bacterial communities in Sawanga-Vithoba lake soil

TA LE 3: Probable bacterial communities in Sawanga-

Vithoba lake soil of station 2

2EF528288 acillus subtilis subsp.

3EF656455 acillus licheniformis W-2

4GQ903382 Bacillus firmus XJSL1-3.

5GU097448 Rhizobium sp. R5.

6AY191846 Ralstonia sp. 12D.

7A 091196 Frateuria aurantia IFO3249.

8EF620455 Stenotrophomonas maltophilia.

9AB091201 Frateuria aurantia

10EU624430 Bacillus cereus S6-08.

11GQ903396 Bacillus firmus XJSL2-7.

12EU248957 Geobacillus sp. H6a.

13GQ903410 Salimicrobium halophilum XJSL4-1.

14AJ301830 Enterococcus faecium (T) LMG 11423.

15Ay685145 Selenomonas ruminantium L6.

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TABLE 4: Probable bacterial communities in Sawanga- Vithoba lake soil of station 3

1AF300975 Bacterium C16S.

2AM111055 Psychrobacter sp. 7317.

3AB188223 Isoptericola sp. TUT1252.

4AM111092 Pseudomonas sp. 8058.

5EF528288 Bacillus subtilis subsp. Subtilis

6EF656455 Bacillus licheniformis W-2.

7EF656456 Bacillus subtilis subsp. Subtilis

8GQ903382 Bacillus firmus XJSL1-3.

9AJ222546 Anaerobacter polyendosporus.

10Am167521 Streptomyces qinlingensis type

11GU097448 Rhizobium sp. R5.

12AY191846 Ralstonia sp. 12D.

13FM957478 Vibrio sp. MY-2008-U64.

14AB091196 Frateuria aurantia IFO3249.

15EF620455 Stenotrophomonas maltophilia

16AB353074 Stenotrophomonas maltophilia MPU98.

17AB091201 Frateuria aurantia IFO13333.

18EU685825 Bacillus sp. PK-6.

19EU624430 Bacillus cereus S6-08.

20EU248957 Geobacillus sp. H6a.

21GQ903410 Salimicrobium halophilum XJSL4-1.

22DQ358727 Paenibacillus zanthoxyli Jh95.

23AJ301830 Enterococcus faecium (T) LMG 11423.

24Ay685145 Selenomonas ruminantium L6.

2568315145 Stridium botulinum 468 toxin type


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