Basic HTML Version
Bioscience Methods
BM 2011, Vo.2, No.6
http://bm.sophiapublisher.com
- 40 -
Figure 1 JM109
+
cDNA library screening by colony PCR
Note: 1~24: PCR products from different colonies; M: DL 2000
mlecular mrker
were identified from
the JM109
+
cDNA library, of
which 7 come from JM109 genome and 5 from the
plasmid pC-SG, while 2 ESTs from JM109
-
cDNA
library. The annotated function of each non-redundant
EST was indicated in the table.
1.2 Targeting genes known
The
STSSU
gene in the pC-SG was employed to be an
internal reference because of no
STSSU
gene in the
JM109 genome, whereas the
glgC
gene existing in
both the JM109 and plasmid genomes was set up as a
negative control. As expected,
STSSU
was found only
in the JM109
+
cDNA library and
glgC
was not
detected in either library.
To figure out indirectly the efficiency of the TSH
procedure, four of the known genes in the plasmid,
STSSU, SCR, HPT
Ⅱ
and
NPT
Ⅱ
except
glgC
and
GUS
, were set up as targeting genes. The detection
frequency of the targeting genes might represent the
efficiency of the TSH procedure, which higher detection
rate would correspond to a higher efficiency. The
results showed that the four targeting genes were hit in
the JM109
+
cDNA library.
It was reasonable that
GUS
was undetectable in
JM109
+
because
GUS
only existed
in JM109 genome,
which was subtracted in the procedures of THS. As
unexpected 35S promoter was detectable, the reason
was clear that 35S promoter existing in the JM109
+
was no homologous sequence in JM109 genome to be
subtracted. Meanwhile, 72 colonies were selected
randomly from the
JM109
-
cDNA library. Sixteen
positive colonies were obtained from the tested 72
colonies. Subsequently, 10 colonies were selected to
be sequenced. The BLAST results indicated that this
selection contained two non-redundant ESTs shown in
Table 2.
2 Discussions
As yet, it might be difficult to analyze the expression
of genes that are dependent on the expression of another
Table 2 Genes and functions known in plasmid pC-SG
Genes
Functions
Detected
expectation
glgC
E. Coli
ADP-glc PPase
No
STSSU
Potato ADP-glc PPase small subunit
Yes
SCR
Plasmid DNA replicase
Yes
GUS
Beta-glucuronidase
No
HPT
Ⅱ
Hygromycin phospho transferase
Yes
NPT
Ⅱ
Neomycin phosphotransferase`
Yes
genome. However, bacteria such as
E. coli
can provide
a suitable system for such gene analysis due to
independent on plasmid DNA for cell growth. In other
words, plasmids could constitute an alternative optional
“mini-genome” to
E. coli
.
Nowadays,
in silico
tools perform strong abilities to
deal with a huge amount of sequencing information,
which makes it possible to work with non-subtractive
library or full transcriptionist profile and even RNA-Seq.
However, more and more studies focused on the effect
of a single independent variable with small gradual
changes. In this case, subtraction-based library still
has its advantage on low-cost and simplicity. To better
use this technique, it would be certain that reliability
and efficiency of subtractive library has to be improved.
The SSH has a low coverage (less than 60%) of
targeting mRNAs since it is not all cDNA reverse
transcripted from mRNAs to be recognized by endon-
ucleases used in SSH procedures. In addition, mRNA
without poly-adenine tails would be losing during
reaction of reverse transcription. An alternative to
overcome those shortages might be to work with all
RNA with or without the polyadenine tails and to
work with cDNA without endonuclease digestion.
To make suppression subtractive hybridization working
better, evaluating the efficiency of the approach
should be necessary. In this study, we employed total
RNA from the cells and eliminated endonuclease
digestion to evaluate the reliability of TSH with a
precise system. Further study for comparison of TSH
and SSH on reliability will be done in the future.
Although the genome sequences of many
E. coli
strains
are available, genes involving in interactions between
the chromosomal genome and plasmid DNA have yet
to be annotated. TSH approach might be reliable and
precise tool to identify differential expressing genes.