Molecular Evolutionary Studies of Sequences for NR1subunit of NMDA
Receptor from Diverse Organisms
1: Dept. of Bioinformatics, Bharathiar University, Coimbatore-641046
2: Sophia College for Women, Bhulabai Desai road, Mumbai-400 026
3: Mol. Biol. Division, Bhabha Atomic Research Centre, Mumbai -400085
Abstract:-We have done sequence analysis of NR1 subunit of NMDA receptor taking the sequence data from
NCBI. Phylogenetic analysis of nucleotide sequences by Distance method, Maximum Parsimony method
and Maximum Likelihood gave us three clusters consisting of vertebrates, invertebrates and mollusk
leading us to infer that the mollusks are a class apart from other invertebrates and vertebrates. This
could be related to the structural organization of neurons for a faster conduction rate, where the new
role of NMDA receptor besides excitatory synaptic transmission needs further investigation. The
presence of NR1 subunit like amino acid sequence in Arabidopsis thaliana suggests that cell to cell
signaling by excitatory amino acids existed before the divergence of plants and animals during organic
evolution. Understanding the regulatory role of NR1 subunit in Ca++ permeability and selective
conduction of ions through channel pores in plants and other organisms would enhance the research on
biochemistry of brain functions.
Key-words: - NMDA receptor, NR1 subunit, Cluster analysis, Molecular Evolution, Excitatory
synaptic transmission, Distance method, Maximum parsimony method, Maximum likelihood method.
1 Introduction:
Ionotrophic glutamate
receptors (iGluR’s) (Sprengel et al 1995) are
known to be highly conserved and reported in
diverse life forms. They mediate excitatory
synaptic transmission in neurons of the animals
while their function in plants such as Arabidopsis
thaliana is under investigation. Vertebrate GluR's
are pharmacologically classified as 1)AMPA(-
xazolepropionic acid 2) Kianate 3) NMDA (Nmethyl-D-aspartic acid) receptors. Of these
NMDA receptors display three unique properties:
1-NMDA receptor depends on simultaneous
binding of glutamate from synaptic vesicles and
glycine from the extra cellular fluids which can
modulate the receptor responses. (Johnson and
Ascher 1987; Kleckner and Dingledine 1998).
2-For activation of NMDA receptor the membrane
should be depolarized and the blockage of ion pore
should be removed. (Mac Donald et al., 1982; Myer
et al 1984; Nowak et al 1984)
3-NMDA receptor is highly permeable to calcium
which can further activate several pathways in the
post synaptic neuron.
NMDA receptor has been implicated in
several brain functions such as memory, neuronal
differentiation and synaptic plasticity during
development. Further it is also implicated in
neurotoxical changes in several diseases. It is
therefore a molecule that deserves attention. Like
other iGluR’s, NMDA receptor too is a tetrameric
protein (Hollamnn and Heinemann, 1994; Laube et
al; 1998) containing two subunits NR1 and NR2
with several subtypes of each being reported. NR1
is generated from a single gene through utilization
of alternate RNA splicing, (Anantharam et al.,
1992; Durand et al., 1993; Hollmann et al 1993;
Sugiharal et al., 1992) while NR2 subunit is
encoded by four separate genes (2A/2B/2C/2D)
(Ikeda et al., 1992; Ishii et al., 1993; Kutsuwada et
al., 1992; Meguro et al., 1992; Monyer et al., 1992).
NR1 and NR2 will form functional receptor
complex with varying properties depending on the
subunit composition.
The NMDA receptor protein like other non
NMDA receptors has four distinct structural
1- The amino terminal region forming the extra
cellular part of the receptor.
2- Tran membrane helices TM1, TM3, TM4 and a
pore forming P region.
3- Two segments S1 and S2 which connect the
transmembrane receptor segments (O’Hara et al.,
1993; Stern-Bach et al., 1994) and
4- Intracellular carboxy terminal domain involved
in the protein-protein interactions.
While the NR1 gene is conserved through
the animal world, their subtypes and expression in
different neurons is because of alternative RNA
splicing and may have functional significance. A
cluster analysis of sequences of conserved gene
provides not only phylogenetic information but also
reflects on the evolution of function. NR1 is
therefore a good candidate gene to study the same.
Fig: 1 the general structure of NR1 subunit.
Fig 2: A typical vertebrate NR1 subunit is shown below. Red represents Signal peptide, blue is S1 and S2
domains, Black are TM regions, violet represents highly variable regions across the sequence
2 Materials and Methods:
2.1 Sequences:
2.2.1 Alignment:
The nucleotide sequences of NR1 subunit
used in our study were retrieved from the database
of NCBI (National Centre for Biotechnology
Information) http://www.ncbi.nlm.nih.gov. Table 1
list all these nucleotide sequences with their species
of origin, accession numbers, number of
nucleotides, number of amino acids coded by them
and the symbols used in the phylogenetic trees.
First we started our search using key word
NR1 subunit of NMDA receptor. Later for
retrieving more sequences we did BLAST search
with rat NR1 subunit as query sequence. With
BLAST search we got 100hits from various
species. Of these we selected complete mRNA
sequences of NR1subunit from 12 different species
starting from Protozoan to Mammalians with an
exceptional hit from a plant viz., Arabidopsis
thaliana that we included in our studies.
TABLE 1: The list of NR1 subunit mRNA sequences used in our study
NR1 genes
Coding Regions
Homo Sapiens
1094-3910 (2817)
Rattus norvegicus
Mus Musculus
Gallus galus
Anas platyrhynchos
Xenopus laevis
Apteronotus leptorhychua
Aplysia californica
Drosophila melanogaster
Anopheles gambiae
Apis Mellifera
Caenorapditis elegans
Arabidopsis thaliana
747 bp
266 -3082 (2817)
94 – 2910 (2817)
7– 2904 (2898)
463 – 3360 (2898)
109 -2823 (2715)
29 – 2929 (2901)
204 -2852 (2649)
237 – 3230 (2994)
1 – 2901 ( 2901)
131 – 2992 (2682)
1-3078 (3078)
1-747 ( 747)
Honey bee
2.2 Methodology:
DAMBE (Data Analysis in Molecular Biology and
Evolution), (Xia. 2000) an integrated software
package for analyzing molecular sequence data was
used in our study. We downloaded the DAMBE
through the internet from the website:
mRNA sequences were aligned using the
inbuilt clustal W program in DAMBE with default
parameters using BLOSUM matrix. First the
nucleotide sequences were uploaded as fasta format
files and translated into amino acid sequences to
check their quality. Then the aligned amino acids
are compared against the unaligned nucleotide
sequences. This procedure ensures that no frame
shifting indels are introduced as an alignment
artifact. A tree topology was generated with aligned
Multiple alignment of amino acid
sequences of all NR1 sequences was also carried
out using MULTALIN program (Corpet 1988). We
used Risler substitution matrix for aligning NR1
sequences. Subsequently we took NR1 subunit
proteins of Drosophila, human and sea hare as
representative species from the three different
clusters of invertebrates, vertebrates and mollusks.
We used BLOSUM substitution matrix, for
alignment that gave us a good alignment of
conserved domains in the three amino acid
sequences. Alignment results of these three amino
acid sequences of NR1 are further discussed
2.2.2 Cluster Analysis:
. 1) Distance method, 2) Maximum
parsimony method and 3) Maximum likelihood
methods inbuilt in DAMBE software package were
used for phylogenetic analysis. DAMBE calculated
genetic distances using nucleotide sequences and
the resulting matrix were used for phylogenetic
reconstruction using Kimura’s (Kimura 1980)
distance method. This method operates on genetic
distance matrix based on K80 substitution model.
The results are shown in Figure 1.
For Maximum parsimony (Baldi and Brunak
1998) analysis, the parsimony algorithm
DNAPARS implemented in DAMBE was used
with default parameters choosing seahare as the out
group. The results are shown in Figure 2. This
method assumes that the substitutions are rare,
uniform and the substitution rate is constant over
time in different lineages.
For Maximum likelihood analysis
DNAML program implemented in DAMBE was
used with the nucleotide substitution model F84
that includes both frequency parameters as well as
rate-ratio parameters. The results are shown in
Figure 3. The underlying assumption in this method
is that the substitutions occur independently in
different sites and different lineages by a stationary
Markov process.
3 Results and Discussion:
3.1 Neuronal Conduction :
The origin of every thought or action is a
co -ordination of nerve impulses that travel through
the neurons. These impulses are generated by the
movement of electrically charged inorganic
molecules through the neural membranes with the
help of channels embedded in them. These channels
are large proteins and their properties are
determined by the genome, itself the result of
evolution. The fundamental property of this
membrane is that it is semi-permeable i.e. it allows
some charged molecules, known as ions, to pass
through more easily than others. Among these ions
that play an important role in the nervous system,
potassium (K+), which is positively charged, is the
one that passes most easily through a neural
membrane in its resting state and is involved in the
process of synaptic transmission. The process that
enables a nerve impulse to pass from one neuron to
another is called synaptic transmission. This
transmission is effected by neurotransmitters,
which bind to the specific receptors. It is through
variations in the amount of neurotransmitters
released, the receptors available, and the affinity
between the two that the synapses undergo changes
and enable learning. Synaptic transmission is an
omnipresent mechanism that is the source of the
brain’s great plasticity. This synaptic plasticity is
the key role of NMDA receptors and is crucial for
memory. NMDA receptor is highly permeable to
Ca++ which activates intracellular signals that can
modify the synaptic function (Dunn et. Al. 1999).
3.2 Cluster Analysis of NMDA receptor in
various organisms:
While a high percentage identity was seen
among all organisms, according to our analysis
carried out by three different methods in DAMBE
the mRNA sequences of NR1 subunit grouped into
three clusters. The phylogenetic trees obtained by
DAMBE are shown in Fig. 1, 2 and 3.
Honeybee and C. elegans which appear early in the
evolutionary tree.
Cluster two included the vertebrates viz.,
Human, Rat, Mouse, Duck, Chick, Frog and Fish
which appear much later in the evolution.
Very interestingly NR1 subunit of
Seahare which is a Mollusc is clustering
independent of the two clusters of vertebrates and
A. thaliana NR1 in our analysis is
clustering with invertebrates in Figure 1 and 3 but
differently in Figure 2.
To study the details of functional evolution
of NR1, we further did multiple alignment of amino
acid sequences of one organism from each cluster
viz. human, drosophila and seahare. The Tran
membrane regions are integral part of the
membrane. The TM1, TM2 and TM3 domains were
found to be highly similar while variability is found
in N-terminal extra cellular domains and C-terminal
intracellular domains of NR1 sequence. The
Domain names were used as such to represent
human amino acid sequences in all the alignment
pictures shown below.
TM1 REGION: This region is about 21aminoacids
long and is conserved across the phyla. There are
however four regions where variations are seen.
Substitution mutations seemed to have occurred in
these sites during the evolution.
TM3 REGION: This region spans across the
membrane and is 21 amino acids long. This region
is highly conserved with no variable sites across the
TM4 REGION: This is the most variable segment of
the protein. Apart from first 6 amino acids which
are identical in all phyla, the region is highly
variable , though not variable in actual size.
S2 DOMAIN: This region is found in between TM3
and TM4 and is of 20 residues long. This along
with S1and TM regions plays a role in ligand
binding. Consensus are low in this region.
TM2 REGION: This is the main segment of the
pore complex and does not span across the
membrane but is associated with the cytoplasmic
side. Except few point mutations this region is
totally conserved. Strong functional constraints of
this region are reflected in its very low variability.
540 residues long and is the N-terminal part of the
protein. This region contains the S1 segment of
ligand binding pocket. High variability is observed
in this region .The glycosylation sites were mainly
concentrated in this zone, which may thought to
have some functional importance.
domain varies from 50-197 amino acids and is the
C-terminal domain. There is no consensus in this
segment. This segment is not involved in ligand
binding and is suggested to be involved in species
specific protein protein interactions.
We have come to two conclusions from these
1: Regions of the protein that are functionally
involved in ligand binding or in the pore formation
are highly conserved.
2: Variations are restricted to amino and carboxy
terminal regions which are known to be spliced
Though these variable regions are not involved
directly in ligand binding or calcium channel
function, these regions of the molecule are
important in differential control of NMDA receptor
mediated responses. The variability in NR1 is being
generated by differential splicing. The splicing of
C-terminal region has been shown to be different in
teleost fish and human and it has been proposed
that evolution of this molecular strategy predates
divergence of mammals and teleost fish [Dunn et
al., 2003]. Our studies demonstrate that variability
in the C-terminal is essentially responsible for the
three clusters with invertebrates, vertebrates and
mollusks forming the 3 diverged groups. This
suggests that mollusks had an evolutionary history
of neuronal development independent of other
Interestingly mollusks are known to diverge
separately from invertebrates and vertebrates in
their strategy of increasing conduction efficiency of
their neurons. Unlike other invertebrates they have
big neurons with larger axons. Vertebrates on the
other hand have evolved better conduction by
developing myelination. This strictly reinforces the
divergence of mollusks nervous system from other
invertebrates that may also reflect in its molecular
mechanism of processing post-synaptic response to
NMDA stimulation and deserves to be investigated
in detail. Especially divergence in the C-terminus
of NR1 subunit suggests that differential protein protein interactions are possible and need to be
Figure 3 : Phylogenetic tree obtained by Distance method. The symbols represent data as given in table1.
Figure 4 : Phylogenetic Tree obtained by Maximum Parsimony method.
Figure 5 : Phylogenetic Tree obtained by Maximum Likelihood method-DNAML
3.3 Role of NMDA like receptors in Plants:
Plants possess NMDA like receptors
generically referred to as GluR’s that bind to
glutamate (Joanna Chiu et al 1998). During our
studies, BLAST search of the database with rat
NR1 subunit, gave us one NMDA like receptor
from Arabidopsis thaliana. Though it is much
smaller compared to other NR1 sequences, we have
included it in our analysis. The role of NR1 subunit
like protein in plants is very interesting. As NMDA
receptors are subfamily of GluR’s and are
important in ion conduction further investigation is
GluR’s are
demonstrated to be
involved in the synergistic action of glutamate and
glycine to control ligand gated calcium intake
(Christian Dubos et al., 2003). The presence of
glutamate receptors in plants suggests that NMDA
receptor like molecules have evolved even before
the divergence of plants and animals. Similar
inferences were drawn by Joanna Chiu et al 1999
on the basis of theoretical analysis of GluR
sequences. They stated that the signaling by
excitatory amino acids in human brain has evolved
from a primitive signaling mechanism that existed
prior to the divergence of plants and animals.
AS the NMDA receptors play a key role in
long term potentiation (LTP) and depression
(LTD) which underlie learning and memory, the
differences with respect to the ligand binding
domains and cytoplasmic C-terminal domain are
thought to be responsible for different types of
protein-protein interactions in these clusters.
Whether these differences could be correlated to
the memory formation needs to be understood. Also
the role of NMDA in relation to the speed of
conduction apart from synaptic transmission has to
be investigated in detail. Understanding of physicochemical basis of NMDA mediated excitatory
synaptic transmission would enable identification
of potential target molecules in neurological
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