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Identification-of- Erythrobactor- Sp- Strains- By-16 S- Ribosomal- RNA- Sequence- Analysis

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Identification-of- Erythrobactor- Sp- Strains- By-16 S- Ribosomal- RNA- Sequence- Analysis Powered By Docstoc
					INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 1, ISSUE 6, JULY 2012                                           ISSN 2277-8616




   Identification of Erythrobactor Sp. Strains By
      16S Ribosomal RNA Sequence Analysis
                                         Harikrishna Yadav. Nanganuru, Satish. Mutyala, Ivanova

Abstract---16S ribosomal RNAs (rRNA) of 4 Erythrobacter strains have been almost completely sequenced to establish their phylogenetic relationships.
                                      o
They have shown growth only at 25 C. 16S rRNA sequences of these strains have shown good similarity with Erythrobacter nanhaisediminis T30 (T)
and E. citreus RF35F (1)T in EzTaxon identity analysis results. 16S rRNA fragment of A3e5, A3e7 and D2g2 amplified with 27F and 907R primers were
most closely related with E. citreus RF35F(1)T and they were represented on same branch along with E. citreus RF35F(1)T. A3e7, Np292 and D2g2‘s
16S rRNA fragment amplified with 518F and 1513R primers were closely related with E. nanhaisediminis T30(T) strain. Sequences with more than 97%
similarity with existed database sequences were considered. Using these sequences and most closely related sequences from dat a base were used for
drawing phylogenetic tree.

Keywords—EzTaxon, Erythrobactor, Polymerase chain reaction, Taxonomy and 16S rRNA,


1 Introduction                                                                The primary structure of the 16s rRNA is highly conserved,
The classification of organisms is mainly based on                            and species having 70% or greater DNA similarity usually
similarities in their morphological, developmental, and                       have more than 97% sequence identity. These 3% or 45-
nutritional characteristics [1]. Molecular phylogenetic                       nucleotide differences are not evenly scattered along the
analysis is a potential application to the description of                     primary structure of the molecule but are concentrated
microbes, both eukaryotic and prokaryotic, seems                              mainly in certain hyper variable regions [10]. Phenotypic
desirable. All of the available molecular methods for                         biochemical analysis is not sufficient to identify genus of
evaluating phylogenetic relationships such as DNA-DNA                         bacteria, but sequencing of 16S rRNA gene sequencing is
and DNA-rRNA hybridization, 5S rRNA and protein                               essential for exact identification [11]. Even Systematic
sequencing, 16S rRNA oligonucleotide cataloging,                              bacteriology using 16S rRNA as tool to find unknown
enzymological patterning, etc. have advantages and                            organisms and suggested that, use 16S rDNA as back
limitations. In general, macromolecular sequences seem                        bone to know taxonomic status of unknown strains.
preferred because they permit quantitative inference of                       Universal primers are used for experimental purpose.
relationships [2, 3]. To study bacterial phylogeny and                        These primers used to polymerise entire 16S rRNA gene or
taxonomy, the 16S rRNA gene sequences are very useful                         part of it. In order to know new species, there is a
due to its presence in almost all bacteria, often existing as a               requirement of entire length of sequence (1500bp).
multigene family, or operons, the function of the 16S rRNA                    GenBank maintain these entire databases in their servers.
gene over time has not changed, suggesting that random                        GenBank already saved 90000 16S DNA sequences of
sequence changes are a more accurate measure of time                          bacteria. Unknown bacterial 16S rRNA sequences can be
and the 16S rRNA gene (1,500 bp) is large enough for                          compared with database sequences, in order to know
informatics purposes [4]. Its gene sequence informatics is                    taxonomic position of unknown bacteria. From this, at least
to provide genus and species identification, where the                        genus of particular unknown strain can be defined. 16S
isolates that do not fit any recognized biochemical profiles                  rRNA sequencing starts with DNA isolation from particular
or for taxa that are rarely associated with human infectious                  strain. This DNA used as template for PCR amplification.
diseases. The cumulative results from a limited number of                     Targeting of particular part of 16S rRNA can be done by
studies suggest that 16S rRNA gene sequencing provides                        using universal primers [12]. EzTaxon is database of 16S
genus identification in more than 90% cases and remaining                     rRNA gene and a tool for analysis of sequences. It contain
unidentified after testing [5, 6 and 7]. The usefulness of 16S                BLAST program to identify closest relative to query
rRNA gene sequencing as a tool in microbial identification                    sequence by pair wise alignment. It also contains CLUSTAL
is dependent upon two key elements, deposition of                             W for multiple sequence alignment. These multiple
complete unambiguous nucleotide sequences into public or                      sequence alignments can be used as input for PHYLIP
private databases and applying the correct ―label‖ to each                    program package for phylogenetic tree drawing and
sequence [8, 9].                                                              analysis [13].


       Harikrishna      Yadav.      Nanganuru,Master    of
                                                                              2 Material and Methodology
                                                                              Each strain of A3e5, A3e7, Np292 and D2g2               of
       Science,Department        of   Biological sciences,
                                                                              Erythrobacter have taken into four different petri plates.
       Swinburne University of Technology, Melbourne,
                                                                              These were given by research group of Ivanova in
       Australia. Email: harikrishyadav@gmail.com
                                                                              Swinburne University of Technology.
       Satish. Mutyala, Master of Science,Department of
       Biological sciences, Swinburne University of
       Technology, Melbourne, Australia
                                                                              2.1 PCR samples preparation
                                                                              Two types of forward (27F and 518F) and reverse primers
       Ivanova, Department of Biological sciences,
                                                                              (907R and 1513R) were taken. By using 27F: 907R and
       Swinburne University of Technology, Melbourne,
                                                                              518F: 1513R pairs of primers were used to prepare
       Australia
                                                                              Polymerase chain reaction samples for each strain. That
                                                                              means A3e5, A3e7, NP292 and D2g2 were added to both
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samples that is one with 27F: 907R and other one with                 program of PHYLIP package 3.59. Out put file of DNADIST
518F: 1513R. consequently these were named as A3e5.1,                 has taken as input file for NEIGBOR program. Tree result of
A3e7.1, NP292.1 and D2g2.1 for 27F: 907R and A3e5.2,                  NEIGBOR program has taken as input file of Treedyn
A3e7.2, NP292.2 and D2g2.2 for 518F: 1513R. Each PCR                  program. Data and annotation of bacterial species were
sample tube was prepared by adding 25 µl of mango mix, 1              loaded. Result was saved.
µl of forward primer, 1 µl of reverse primer and 23 µl of
water. Then each strain was added to each tube using                  3 Results
sterile loop. These samples were prepared in sterile PCR
tubes and vertexed before keeping in PCR machine.                     3.1 Agarose gel electrophoresis for conformation of
                                                                      16S rRNA gene amplification by
2.2 PCR program for amplification of 16S rRNA gene
A program was set by keeping initial denaturation
temperature as 950c, followed by 1min at 940C, 1min at
550C and 2 min at720C for 30 cycles. Final extension step
was run at 720C for 10min.

2.3 Agarose gel electrophoresis of samples for
conformation of 16s rRNA gene amplification by
PCR
250 ml of 1X TBE buffer was prepared by adding 225ml of
water to 25ml of 10X TBE buffer. 25 ml of 1% agarose gel
was prepared by adding 25ml of 1X TBE buffer to 0.25gm
agarose. Gel red added after dissolving agarose in TBE
buffer. Agarose gel was casted in electrophoresis tray with
sufficient number of wells. 1XTBE buffer loaded into
electrophoresis tank until gel was submerged. Like this
three sets of electrophoresis trays were filled with gel and
buffer solution. 5µl of each PCR sample A3e5.1, A3e5.2
and A3e7.1 and 1kb ladder were loaded in separate wells.
In second gel electrophoresis set, gel wells were filled with
A3e7.2, Np292.1, Np292.2 and 1kb ladder. Third one was
also filled up its wells with D2g2.1, D2g2.2 and 1kb ladder.
All These samples were run for 25 min at 110V with
constant current supply. After running samples gel was kept                            Gel image 1: It has 1kb ladder, A3e5.1,
in UV illumination chamber to observe DNA bands.                                       A3e5.2 and A3e7.1 PCR samples in 1,
                                                                                       3, 4 and 5th wells respectively.
2.4 AGRF samples preparation
After conformation AGRF (Australian genomic research
foundation) samples were prepared for gene sequences.
For that 11 µl of each strain was added to 1 µl of primer.
Consequently, two samples were made from each strain for
example one sample was prepared by adding 11 µl of
A3e5.1 and 1 µl 27F primer and again one more sample
with 907R with same composition. Like this A3e7.1,
Np292.1 and D2g2.1 were paired up with 27F and 907R
primers. Like that A3e5.2, A3e7.2, Np292.2 and D2g2.2
strains were paired up with 518F and 1513R. These
samples were given to the Australian genomic research
foundation.

2.5 Phylogenetic analysis of sequences
Samples sequences from AGRF were loaded one after
another in EzTaxon. AGRF Sample sequences with reverse
primers were analysed by selecting reverse complementary
sequences. 30 hits were saved for each sequence. Identity
analysis results of each sample sequence were pasted in
one note pad from ‗view all sequences‘. Common
sequences were deleted leaving one of them. These
sequences without common sequences were pasted in                                      Gel image 2: It has 1kb ladder, A3e7.2,
CLUSTAL W program. Out put file of CLUSTAL W was                                       Np292.1 and Np292.2 PCR samples in
saved in ‗Phy‘ format. Bioedit program was used to view                                1, 3, 4 and 5th wells respectively.
multiple sequence alignment as well to edit sequence
length. This file has taken as input file for DNADIST
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   Gel image 3: It has D2g2.1, D2g2.2
   and 1kb ladder PCR samples in 1, 3
   and 5th wells respectively.


3.2 AGRF results

Table 1: Each strain sequence length in bases of AGRF samples
 S.N      Sample      Primer    AGRF name      Sequence length in bases

  1       A3e5.1       907R         MS1                     77
  2       A3e5.2      1513R         MS2                    245
  3       A3e7.1       907R         MS3                    159
  4       A3e7.2      1513R         MS4                    398

  5       Np292.1      907R         MS5                    107

  6       Np292.2     1513R         MS6                    135

  7       D2g2.1       907R         MS7                     83
  8       D2g2.2      1513R         MS8                     67
  9       A3e5.1        27F        MS17                    787
 10       A3e5.2       518F        MS18                    139
 11       A3e7.1        27F        MS19                    858
 12       A3e7.2       518F        MS20                    853
 13       Np292.1       27F        MS21                    793

 14       Np292.2      518F        MS22                    895

 15       D2g2.1        27F        MS23                     48

 16       D2g2.2       518F        MS24                    923



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3.3 EzTaxon identity results

Table 2: Similarity percentages of AGRF samples from EzTaxon
EzTaxon name        Hit             Sample    Primer     AGRF name     Similarity %
                    Erythrobacter
MS3                 citreus         A3e7.1    907R       MS3           75.549
                    RE35F/1(T)
                    Erythrobacter
MS4                 nanhaisedimin A3e7.2      1513R      MS4           90.462
                    is T30(T)
                    Erythrobacter
MS5                 citreus         Np292.1 907R         MS5           89.362
                    RE35F/1(T)
                    Erythrobacter
MS17F               nanhaisedimin A3e5.1      27F        MS17          98.020
                    is T30(T)
                    Erythrobacter
MS18F               citreus         A3e5.2    518F       MS18          83.944
                    RE35F/1(T)
                    Erythrobacter
MS19F               nanhaisedimin A3e7.1      27F        MS19          97.411
                    is T30(T)
                    Erythrobacter
MS20F               citreus         A3e7.2    518F       MS20          97.906
                    RE35F/1(T)
                    Erythrobacter
MS21F               citreus         Np292.1 27F          MS21          97.464
                    RE35F/1(T)
                    Erythrobacter
MS22F               nanhaisedimin Np292.2 518F           MS22          97.386
                    is T30(T)
                    Erythrobacter
MS24F               citreus         D2g2.2    518F       MS24          97.510
                    RE35F/1(T)

3.4 Phylogenetic tree

Tree: Evolution of given samples were identified from the phylogenetic tree




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4 Discussion                                                            rRNA gene. But after tree drawing with PHYLIP package,
From 1980s scientists tried to standardise the technique to             16S rRNA fragment of A3e5, A3e7 and Np292 amplified
identify new bacteria. They recognised that stable or                   with 27F and 907R primer are closely related with E.citreus
standard part of genome is essential to draw phylogenetic               RE35 (1)T. And 16S rRNA fragments of A3e7, Np292 and
relationship between different bacteria. At that time they felt         D2g2 amplified with 518F and 1513R are closely related
that all ribosomal genes are stable. Even though there is               with E. nanhaisediminis T30 (T). In EzTaxon pair wise
sufficient technology to sequence entire genome of                      alignment was used for similarity value search. Multiple
unknown bacteria, they are using only16S rRNA gene or                   sequence alignment had done with CLUSTAL W and it was
16s rDNA for phylogentic analysis. Because it is difficult to           used in phylogentic tree drawing procedure. There was
analyse entire sequence of genome. Moreover both kinds                  clear difference observed in the similarity values of
of phylogenetic analysis gave almost similar kind of                    EzTaxon and phylogenetic tree similarity due to use of
phylogenetic trees. It possible to identify rarely isolated             different algorithms used in EzTaxon and phylogenetic tree
bacterial species by using 16S rRNA gene analysis. Colony               [13].
PCR was used for amplification of 16S rRNA gene.
Because it can directly amplify DNA without the isolation of            5 Conclusion
DNA [14]. Approximate length of amplified fragment of 16S               16S rRNA gene phylogenetic analysis, DNA- DNA
rRNA gene by 27F/907R and 518F/1513R was 900 to                         hybridization analysis, other individual biochemical tests
1000bp. Because number of primers indicate first position               and chemotaxonomic analysis of components of cells and
of 16S rRNA gene where primer binds [15]. For                           comparison of these results with already known species are
confirmation of 16S rRNA gene, agarose gel was run for 25               essential to identify a new strain.
min. because there is no need of clear separation, in order
to show amplification that much time is enough. Gel Images              6 Reference
1, 2 and 3 represents 16S rRNA gene fragments were                      [1] Stackebrandt, E. & Woese, C. R. (1981) in Molecular
purified. By observing image 1, 2, and 3, gene amplified by             and Cellular Aspects of Microbial Evolution, eds. Carlisle,
27F and 907R moved longer distance than 518F and                        M. J., Collins, J. R. & Moseley, B. E. B. (University Press,
1513R set. Because 16S rRNA gene amplified by 518F and                  Cambridge), pp. 1-31.
1513R was bigger than 27F and 907R fragment. AGRF
recommends 18 to 30 ng/12 µl of sample [16]. AGRF                       [2] Zuckerkandl, E. & Pauling, L. (1965) J. Theor. Biol. 8,
samples prepared with reverse primers were purified with                357-366.
manual gel elute extraction kit. Expected length of AGRF
sequences is around 900bp [15] but samples with reverse                 [3] Fitch, W. M. & Margoliash, E. (1967) Science 155, 279-
primers were less than 400bp (Table 1). DNA recovery                    284.
efficiency of this kit is 60- 95% [17]. There is a chance to
get poor recovery (60%). This may be one of the reasons                 [4] Patel, J. B. 2001. 16S rRNA gene sequencing for
for poor recovery of DNA and poor sequencing. Another                   bacterial pathogen identification in the clinical laboratory.
reason for poor sequencing due to contaminants such as                  Mol. Diagn. 6:313–321.
proteins, RNA, buffers etc [16]. AGRF sequences prepared
with forward were purified from gel with Wizard SV Gel and              [5] Drancourt, M., C. Bollet, A. Carlioz, R. Martelin, J.-P.
PCR clean up system. Recovery efficiency of this kit was 70             Gayral, and D. Raoult. 2000. 16S ribosomal DNA sequence
to 95% [18]. There is chance to get two extreme quantities              analysis of a large collection of environmental and clinical
of recovery. This one may be the reason for poor                        unidentifiable bacterial isolates. J. Clin. Microbiol. 38:3623–
sequencing of MS18 and MS19 and another reason may be                   3630.
due to contaminants in AGRF samples [16]. EzTaxon was
used for sequence similarity search, because it contain only            [6] Mignard, S., and J. P. Flandrois. 2006. 16S rRNA
prokaryotes 16S rRNA gene database and programming                      sequencing in routine bacterial identification: a 30-month
tools to find closely related sequences in database [13].               experiment. J. Microbiol. Methods 67: 574–581.
Only identity analysis was performed in this site, because
remaining tools in this site were not working. AGRF                     [7] Woo, P. C. Y., K. H. I. Ng, S. K. P. Lau, K.-T. Yip, A. M.
sequencing was done with forward primers except MS18                    Y. Fung, K.-W. Leung, D. M. W. Tam, T.-L. Que, and K.-Y.
and MS23 were shown good similarity with database                       Yuen. 2003. Usefulness of the MicroSeq 500 16S ribosomal
sequences i.e. above 97% similarity (Table 2). It can                   DNA-based identification system for identification of
describe taxa of species if similarity value above 97% [10,             clinically significant bacterial isolates with ambiguous
13]. These six sequences shown most similarity with                     biochemical profiles. J. Clin. Microbiol. 41:1996– 2001.
Erythrobacter nanhaisediminis T30(T) and E. citreus
RF35F(1)T. 16S rRNA gene fragment of A3e7 amplified                     [8] Heikens, E., A. Fleer, A. Paauw, A. Florijn, and A. C.
with 27F and 907R primer shown most similarity with E.                  Fluitt. 2005. Comparison of genotypic and phenotypic
nanhaisediminis T30(T) and same strain fragment amplified               methods for species-level identification of clinical isolates of
with 518F and 1513R shown most similarity with E. citreus               oagulase-negative staphylococci. J. Clin. Microbiol. 43:
RF35F(1)T. Np292‘s 16S rRNA gene fragment amplified                     2286–2290.
with 27F and 907R shown most similarity with E. citreus
RF35F(1)T and same gene amplified with 518F and 1513R                   [9] Petti, C. A. 2007. Detection and identification of
shown most similarity with E. nanhaisediminis T30(T). This              microorganisms by gene amplification and sequencing.
may be due to base difference in amplified sequence of16S               Clin. Infect. Dis. 44:1108–1114.
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[10] Stackebrandt, E., W. Liesack, and D. Witt. 1992.
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[12] Clarridge iii, JE 2004, ‗gram negative identification test
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[13] Chun, J, Lee, JH, Jung, Y, Kim, M, Kim, S, Kim, BK
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[14] Colony PCR 2010, KapaBiosystems, < http://www.
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[15] Doud, M, Zeng, E, Scheper, L, Narasimhan, G and
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[16] Guide to sequencing services 2010, agrf,
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[17] Gel Elute Agarose gel extraction protocol, Manual
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