115th General Meeting Of The American Society For Microbiology Molecular Characterization of Bacteria in Soils obtained from Petroleum Contaminated Sites in Kaduna state, Nigeria Presented at 115th General Meeting Of The American Society For Microbiology May 30 – June 2, 2015 New Orleans, Louisiana By H. M. Raji1*, J. B. Ameh1, S. A. Ado1, S. E. Yakubu1 and A.J. Weightman2 1Dept. of Microbiology, Ahmadu Bello University, Zaria, KD, Nigeria 2School of Biosciences, Cardiff University, Wales, CF, United Kingdom *Corresponding author: e-mail address: habibasalam19@yahoo.com

ABSTRACT Culture–dependent methods of identifying bacteria present in the soil often give limited information about their diversity owing to the fact that a large majority of these bacteria are viable but non-culturable. Metagenomics offer a viable means of depicting microbial taxonomic and functional diversity. Soil samples were collected from three sites exposed to petroleum products in Kaduna state located in the north-western part of Nigeria, these sites are an auto workshop, a trailer park, and a site close to a stream receiving effluent from a petroleum refinery. The samples were collected from two depths (17 – 20 cm, and 37 – 40 cm respectively), and analysed based on physico-chemical parameters, PCR amplification of the partial 16S ribosomal RNA and phylogenetic studies. Genomic DNA was extracted from the samples in triplicates, and PCR-DGGE conducted; the forward primer has a 40 base GC clamp attached to it to enhance analysis with DGGE, the primer pair used is 357F-GC and 518R. Prominent bands on the DGGE gel were excised and sequenced. The sequences obtained were analysed on Finch tv software before subsequently subjected to BLAST analysis on the NCBI website for closest alignments. Sequence alignment and phylogenetic analysis were carried out using the MEGA version 4.0 software. The sequences from the shallow samples from the auto workshop formed a separate cluster from the deep samples; and are all closely affiliated to Proteobacteria. The sequences from the trailer park soil showed closest relations to Gram positive high G+C bacteria and Gram positive low G+C bacteria. The closest relatives to the sequences from the refinery effluent site were members of Proteobacteria, Gram positive high G+C bacteria and Gram positive low G+C bacteria; thus showing more diversity than the other two sites. The study showed that the depth of sampling, anthropogenic activities as well as the soil physico-chemical parameters might play a role on the bacterial diversity of a soil sample. Key words: soil, bacteria, Nigeria

Introduction Nigeria is a country blessed with a lot of natural resources, petroleum inclusive. Activities relating to the drilling, refining and transportation of petroleum and its products often leads to contamination in the environment. The presence of these petroleum hydrocarbons in the terrestrial and/or aquatic environment typically leads to adaptation of these hydrocarbons by indigenous microorganisms, thus utilizing them as sources of Carbon and energy. Bacterial bioremediation of such environments offers a cost effective and eco- friendly solution to the hazard. However, culture dependent methods of determining the bacterial community in the environment are often misleading and inadequate because a large percentage of these bacteria are not culturable thus, are not adequately represented. Thus, Metagenomics plays a major role in determining the phylogenetic as well as functional diversity of these hydrocarbon-degrading bacteria.

Aim and Objectives The aim of this study is to determine the phylogenetic diversity of bacteria present in soils from certain petroleum-contaminated sites in Kaduna state, Nigeria. Objectives: To determine the physicochemical characteristics of soils collected from petroleum-contaminated sites in Kaduna state, Nigeria To conduct PCR amplification and DGGE analysis of the bacterial 16S rRNA gene in petroleum-contaminated soils using the primers, 357F-GC and 518R To perform phylogenetic analysis of the prominent nucleotide sequences obtained from the petroleum-contaminated soils.

Materials and Methods Soil samples: Three (3) petroleum-contaminated sites in Kaduna state (North western region), Nigeria were the subject of this study, they are as follows: A Mechanic Workshop, a Trailer park, and a Petroleum refinery effluent site. Two (2) samples were collected from each site; the samples were obtained at two depths, 17 – 20 cm and 37 – 40 cm, respectively, making a total of six samples. DNA extraction: Genomic DNA was extracted from 0.5 gram of each soil sample in triplicates, using the Fast DNA Spin kit for soil (MP Biomedicals, U.K), the procedure was carried out using the manufacturer’s instructions. PCR amplification of 16S ribosomal RNA and DGGE analysis of partial 16S rRNA gene: Amplification of 16S rRNA was performed using the primers, 357F-GC* and 518R (Eurofins MWG, U.K), which amplify a product of 201 bp. The GC clamp (40 bp) attached to the forward primer is necessary to enhance separation of the bands during DGGE (30% - 60% urea-formamide). Sequencing of DNA from excised bands and phylogenetic analysis: Aliquots of the reamplified amplicons were sequenced (Eurofins MWG, U.K), the resulting sequences were cleaned by removing GC clamp sequences using Finch tv program. The BLASTN program from the National Center for Biotechnology Information (NCBI) website was used to conduct DNA similarity searches. Of the thirty DNA sequences sequenced, only twenty five were successfully used for phylogenetic analysis. Multiple sequence alignment and evolutionary analysis was carried out using the MEGA 4 program (Tamura et al., 2007).

Table 1: Textural Classification and Physico-chemical analysis of Petroleum-contaminated Soils Sample Textural pH O and G Moisture Organic Nitrogen Available Ca Mg K Na Class Content Carbon Phosphorus USDA   (mg/L) (%) mg/kg T.D Sandy 5.3 140 0.6 43.09 2.8 12.95 4 1.3 0.45 0.25 loam T.S 5.5 1 590 3.1 8.78 0.98 47.6 3.2 1.1 0.44 0.27 M.D Loamy 5.8 1 220 1.4 4.79 0.06 6.48 1 0.3 0.42 0.21 M.S 5.9 1 340 0.8 16.36 1.33 20.3 3.6 1.2 0.41 0.19 R.D 5.4 770 0.75 9.58 1.05 5.43 2 0.9 0.31 0.18 R.S 5 940 10.77 1.19 6.3 2.2 0.34 KEY: MS: Mechanic workshop shallow; MD: Mechanic workshop deep TS: Trailer park shallow; TD: Trailer park deep RS: Refinery effluent shallow; RD: Refinery effluent deep

KEY: MS: Mechanic workshop shallow; MD: Mechanic workshop deep TS: Trailer park shallow; TD: Trailer park deep RS: Refinery effluent shallow; RD: Refinery effluent deep

KEY: M: Molecular marker Lanes 1 – 3: MD (Mechanic workshop deep) Lanes 4 – 6: MS (Mechanic workshop shallow) Lanes 7 – 9: TD (Trailer Park deep) Lanes 10 – 12: TS (Trailer park shallow) Lanes 13 – 15: RD (Refinery effluent deep) Lanes 16 – 18: RS (Refinery effluent shallow)

Fig. 2: Neighbour-Joining Tree showing Phylogenetic Affiliation of 16S rRNA sequences obtained from Petroleum-contaminated Soils KEY: MS: Mechanic workshop shallow; MD: Mechanic workshop deep TS: Trailer park shallow; TD: Trailer park deep RS: Refinery effluent shallow; RD: Refinery effluent deep Yellow highlight: Shallow sampling sites (17 – 20 cm) Red highlight: Deep sampling sites (37 – 40 cm)

Conclusion Heavy metals such as zinc, lead and copper were detected in high quantities in the petroleum contaminated soils sampled in this study The DGGE analysis of soil from Trailer park and Refinery effluent sites showed similar profile in the two sampling depths while, the Mechanic workshop soil had different profiles at both depths. Phylogenetic analysis of the 16S rRNA sequences obtained from the petroleum-contaminated soils revealed members of Alphaproteobacteria, Gammaproteobacteria, Betaproteobacteria, Gram positive low G+C bacteria, Gram positive high G+C bacteria and Acidobacteria The Mechanic workshop soil indicated more bacterial diversity than the Trailer park and Refinery effluent soils respectively.

References Muyzer, G., De Waal, E.C., Uitterlinden, A.G. (1993) Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Applied Environmental Microbiology 59: 695–700. Tamura, K., Dudley, J., Nei, M. and Kumar, S. (2007) MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Molecular Biology and Evolution 24:1596-1599

Acknowledgements: