Normal blood glucose level depends on the availability of insulin and its ability to bind insulin receptor (IR) that regulates the downstream signaling pathway. Insulin sequence and blood glucose level usually vary among animals due to species specificity. The study of genetic variation of insulin, blood glucose level and diabetics symptoms development in Aves is interesting because of its optimal high blood glucose level than mammals. Therefore, it is of interest to study its evolutionary relationship with other mammals using sequence data. Hence, we compiled 32 Aves insulin from GenBank to compare its sequence-structure features with phylogeny for evolutionary inference. The analysis shows long conserved motifs (about 14 residues) for functional inference. These sequences show high leucine content (20%) with high instability index (>40). Amino acid position 11, 14, 16 and 20 are variable that may have contribution to binding to IR. We identified functionally critical variable residues in the dataset for possible genetic implication. Structural models of these sequences were developed for surface analysis towards functional representation. These data find application in the understanding of insulin function across species.
Normal blood glucose level depends on the availability of insulin and its ability to bind insulin receptor (IR) that regulates the downstream signaling pathway. Insulin sequence and blood glucose level usually vary among animals due to species specificity. The study of genetic variation of insulin, blood glucose level and diabetics symptoms development in Aves is interesting because of its optimal high blood glucose level than mammals. Therefore, it is of interest to study its evolutionary relationship with other mammals using sequence data. Hence, we compiled 32 Aves insulin from GenBank to compare its sequence-structure features with phylogeny for evolutionary inference. The analysis shows long conserved motifs (about 14 residues) for functional inference. These sequences show high leucine content (20%) with high instability index (>40). Amino acid position 11, 14, 16 and 20 are variable that may have contribution to binding to IR. We identified functionally critical variable residues in the dataset for possible genetic implication. Structural models of these sequences were developed for surface analysis towards functional representation. These data find application in the understanding of insulin function across species.
Diabetes mellitus (DM) is one of the predominant diseases that
affect presently ~ 382 million people all over the world and its
incidence is expected to increase to 592 million by
2035(according to international diabetes federation). Insulin
level or binding ability to IR is the major determinant factor of
DM. Insulin is a globular protein central to the regulation of
vertebrate carbohydrate metabolism. It is one of the most
important hormones, carrying messages that describe the
amount of available sugar from moment to moment in the
blood. Insulin is the primary regulator of carbohydrate
homeostasis and has effect on lipid and protein metabolism
[1,
2].
The mechanism of action of these hormones is mediated by
their specific binding to the Insulin Receptor (IR) [3]. The
binding of insulin to IR leads to activation of the tyrosine
kinase function of the intracellular part of the receptor and
subsequent transporter activation as well as increase cellular
uptake of glucose [4]. A confirmatory repeat blood sugar level
≥140 mg/100 ml proved valuable in defining a high risk group
for diabetes in human [5]. But there is an unusually high blood
glucose level found in birds without diabetes or any associated
consequences (Figure 1). Normal plasma glucose levels in
some birds is three to four times higher than human
[6]. May
be birds have some intrinsic mechanism to control blood
glucose levels without showing diabetic symptoms.
Comparative analysis of Aves insulin may gives some ideas
about the mechanism.
Figure 1
Variation of normal blood glucose level
[15]. There is
a drastic fluctuation of normal blood glucose level among
Aves, Reptile and Mammal. Aves glucose level is four times
higher than Reptile and seven times higher than Mammal.
Insulin is made in the pancreas and added to the blood after
meals when sugar levels are high. This signal then spreads
throughout the body, to the liver, muscles and fat cells. Insulin
tells these organs to uptake glucose from the blood and stores
in the form of glycogen or fat. The mechanism of insulin
binding to insulin receptor and signal transduction through
the transmembrane domain has vital role to maintain blood
glucose levels [7]. Structure of insulin is the key to protein
function and interaction to IR. Evolution of insulin gene and its
promoter has started over a 450 million-year period
[8]. Protein
structure analysis can provide lots of complex information
about protein functions related disorders. Wet lab based
research requires the trial and error method and cannot make a
prediction before the original result. This problem can be
overcome by the use of computational biology. Alteration in
protein structure leads to altered protein function which in
turn leads to development of diseases [9]. The target of this
research is to give an intrinsic view of Aves insulin that may
suggest an important idea about control mechanism of blood
sugar level as well as recombinant humaninsulin
development.
Methodology
Protein sequence retrieval:
Thirty two Aves insulin and ten mammalianinsulin sequences
were collected from UniProt (http://www.uniprot.org/). We
preferred most commonly available mammal and all Aves
sequences found UniProte database until mid June, 2013.
Those sequences were used for further analysis by online or
freely available computational tools.
Analysis of Physico-chemical properties:
The ProtParam tool (http://web.expasy.org/protparam/ ) of
ExPASy was used to compute amino acid composition (%),
molecular weight, theoretical isoelectric point (pI), number of
positively and negatively charged residues, extinction
coefficient, instability and aliphatic index, Grand Average of
Hydropathy (GRAVY).
Analysis of Secondary structural properties:
Secondary structural properties of the protein including alpha
helix, 310 helix, Pi helix, beta bridge, extended strand, beta
turns, bend region, random coil, ambiguous states and other
states were computed by the use of SOPMA (Self Optimized
Prediction Method with Alignment, http://npsapbil.ibcp.fr/
cgibin/npsa_automat.pl?page=/NPSA/npsa_sopma.html)
tool of NPS (Network Protein Sequence Analysis)
[10].
Prediction of functional properties:
The motif prediction analysis was carried out with the help of
Expasy׳s prosite tool. For functional analysis, the motifs of the
insulin protein sequences were identified by using Prosite
(http://prosite.expasy.org/). Input data type was in FASTA
format and motifs were scanned against prosite patterns.
Identification of Signature Logo using Web tool:
Logo of Aves insulin was generated using Web Logo tool
(
http://weblogo.berkeley.edu/). In this overall height of the
stack indicates the sequence conservation at that position,
while the heights of the symbols within the stack indicate the
relative frequency of each amino acid at that position.
Sequence alignment:
Insulin sequences were align by using MEGA5.1 and identify
the variable region that may be responsible for functional
activity of high plasma glucose level. Direct comparison
between human and turkey insulin sequence is given below
and box shows the changes of amino acids. It indicate
completely different types of (in term of hydrophobic and
hydrophilic) amino acid changes in between this two species.
Thirty two sequences of Aves insulin were aligned by
ClustalW tool and output file of this program was used for
generation of phylogenetic tree (
http:// www.ebi.ac.uk/Tools/msa/clustalw2/)
by using Neighbor-Joining method.
Results & Discussion
The Physiochemical characterization, secondary structure
properties, motif and phylogenetic analysis was done by using
different computational tools for 32 Aves insulin sequences.
Insulin sequences contain leucine around 20% of their amino
acids which is significantly higher than other (Figure 2). The
total number of positively (Arg + Lys) and negatively (Asp +
Glu) charged residues were quite same, that׳s why pI was ~7.
Extinction coefficient for all Insulin was observed higher. High
extinction coefficient means higher concentration of lysine,
tryptophan and tyrosine. This prediction is useful to study
protein-protein interaction studies. The higher aliphatic index
indicates higher thermostability and higher concentration of
alanine, valine, isoleucine and leucine occupying the relative
volume of a protein. A protein is stable or not can be described
by its instability index. Instability index for Insulin in most
case is higher than 40 and thus describing these proteins as
unstable [11].
Figure 2
Percentage of Leuchin in Aves insulin. Around 20 %
of total amino acid in Aves insulin is Leuchin. It is
hydrophobic amino acid and the reason behind this high
percentage of Leu is not fully known yet.
Average of Hydropathy (GRAVY) was computed for all the
members. A broad range of GRAVY value was observed from
0.304 to -0.006 for Insulin Table 1 (see supplementary
material). SOPMA analysis was done for all insulin members
and it showed a high value for random coil in all the members
Table 2 (see supplementary material). High value for random
coil bears important significance in the study of protein tertiary
structure and related functions. Functional analysis of these
proteins includes identification of important motifs
Table 3
(see supplementary material). Only eight proteins show
functional motif within 32 sequences. These motifs were 14
amino acids in length arise because specific residues and
regions proved to be important for the biological function of a
group of proteins, which are conserved in both structure and
sequence during evolution [12]. For observing variability of
Aves insulin sequences, MEGA5.1 software was used
(Figure 3). WebLogo was designed (from weblogo.berkeley.edu) to
show variable and constant amino acid position (Figure 4).
Amino acid position 11, 14, 16 and 20 are variable on species to
species. Phylogenetic tree was constructed with distance based
Neighbor-Joining method. A number of clusters were found
(Figure 5). 3D structure of turkey and humaninsulin are
determined (Figure 6) Proteins in close evolutionary
relationship may be analyzed together for their involvement in
similar biological processes. Another important finding is the
structural differences between IR. There are sequence deletion
found between 743 to 755 and 1007 to 1012 in Aves IR
(comparison between human and turkey). This IR and insulin
sequences differences may play a major role for binding
affinity as well as intracellular signaling pathway that control
blood glucose level.
Figure 3
Multiple (thirty two) Aves insulin sequences
alignment using MEGA5.1 software. It is clearly found that
two particular regions are usually show variability. Left region
show Ile and Tyr are variable and right region show Thr, Gly
and Ala are variable.
Figure 4
WebLogo representation of Aves Insulin. The amino
acid types and position are shown on the x axis. The overall
height of the amino acid stacks, plotted on the y axis, indicates
the sequence conservation at a given position, while the height
of individual symbols within a stack indicates the relative
frequency of an amino acid at that position. Amino acids are
color coded according to their type as basic (blue),
hydrophobic (black), polar/nonpolar (green), and acidic (red).
Figure 5
Phylogenetic tree of Aves insulin sequences by using
Neighbor-Joining Method. Closely related species like Anser
anser (>sp|P68245|)and Cairian moschata (>sp|P68243|) are
found nearby but the location of Melopsittacus undulates
(>tr|Q6XVL9|) is different from them, as it is not there
neighbor species.
Figure 6
3D structure of Turkey (left) and Human (right)
Insulin was determined using SWISS-Model. A chain (light
red) and B chain (light blue) are linked via two inter-chain
disulfide bond among Cys residues and one intra-chain bond
in A chain.
Conclusion
In this study, detail information of Aves insulin was
sequentially identified using various computational tools.
Insulin is related to diabetic, a group of metabolic diseases in
which a person has high blood sugar, either because the
pancreas does not produce enough insulin, or because cells do
not respond to the insulin that is produced
[13]. Some
information influence to carry on the study like South Asian
people have higher blood glucose levels than white European
people [14] and SNP alleles in the IR gene are associated with
typical migraine [15]. Present investigation and information
may provide a possible explanation for high blood glucose in
Aves as well as species specificity of insulin. This information
will help to design effective recombinant insulin for
therapeutic application. However, this finding is not enough to
establish the hypothesis and need further study and validation
by experimental approaches.
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Figure 6