Analysis of the potential role of GluA4 carboxyl-terminus in PDZ interactions

Splicing and editing of ionotropic glutamate receptors: a comprehensive analysis based on human RNA-Seq data

Ionotropic glutamate receptors (iGluRs) play key roles for signaling in the central nervous system. Alternative splicing and RNA editing are well-known mechanisms to increase iGluR diversity and to provide context-dependent regulation. Earlier work on isoform identification has focused on the analysis of cloned transcripts, mostly from rodents. We here set out to obtain a systematic overview of iGluR splicing and editing in human brain based on RNA-Seq data. Using data from two large-scale transcriptome studies, we established a workflow for the de novo identification and quantification of alternative splice and editing events. We detected all canonical iGluR splice junctions, assessed the abundance of alternative events described in the literature, and identified new splice events in AMPA, kainate, delta, and NMDA receptor subunits. Notable events include an abundant transcript encoding the GluA4 amino-terminal domain, GluA4-ATD, a novel C-terminal GluD1 (delta receptor 1) isoform, GluD1-b, and potentially new GluK4 and GluN2C isoforms. C-terminal GluN1 splicing may be controlled by inclusion of a cassette exon, which shows preference for one of the two acceptor sites in the last exon. Moreover, we identified alternative untranslated regions (UTRs) and species-specific differences in splicing. In contrast, editing in exonic iGluR regions appears to be mostly limited to ten previously described sites, two of which result in silent amino acid changes. Coupling of proximal editing/editing and editing/splice events occurs to variable degree. Overall, this analysis provides the first inventory of alternative splicing and editing in human brain iGluRs and provides the impetus for further transcriptome-based and functional investigations.

Molecular mechanisms controlling synaptic recruitment of GluA4 subunit-containing AMPA-receptors critical for functional maturation of CA1 glutamatergic synapses

Synaptic recruitment of AMPA receptors (AMPARs) represents a key postsynaptic mechanism driving functional development and maturation of glutamatergic synapses. At immature hippocampal synapses, PKA-driven synaptic insertion of GluA4 is the predominant mechanism for synaptic reinforcement. However, the physiological significance and molecular determinants of this developmentally restricted form of plasticity are not known. Here we show that PKA activation leads to insertion of GluA4 to synaptic sites with initially weak or silent AMPAR-mediated transmission. This effect depends on a novel mechanism involving the extreme C-terminal end of GluA4, which interacts with the membrane proximal region of the C-terminal domain to control GluA4 trafficking. In the absence of GluA4, strengthening of AMPAR-mediated transmission during postnatal development was significantly delayed. These data suggest that the GluA4-mediated activation of silent synapses is a critical mechanism facilitating the functional maturation of glutamatergic circuitry during the critical period of experience-dependent fine-tuning. This article is part of the Special Issue entitled 'Ionotropic glutamate receptors'.

The N-terminal domain modulates α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor desensitization

AMPA receptors are tetrameric glutamate-gated ion channels that mediate fast synaptic neurotransmission in mammalian brain. Their subunits contain a two-lobed N-terminal domain (NTD) that comprises over 40% of the mature polypeptide. The NTD is not obligatory for the assembly of tetrameric receptors, and its functional role is still unclear. By analyzing full-length and NTD-deleted GluA1-4 AMPA receptors expressed in HEK 293 cells, we found that the removal of the NTD leads to a significant reduction in receptor transport to the plasma membrane, a higher steady state-to-peak current ratio of glutamate responses, and strongly increased sensitivity to glutamate toxicity in cell culture. Further analyses showed that NTD-deleted receptors display both a slower onset of desensitization and a faster recovery from desensitization of agonist responses. Our results indicate that the NTD promotes the biosynthetic maturation of AMPA receptors and, for membrane-expressed channels, enhances the stability of the desensitized state. Moreover, these findings suggest that interactions of the NTD with extracellular/synaptic ligands may be able to fine-tune AMPA receptor-mediated responses, in analogy with the allosteric regulatory role demonstrated for the NTD of NMDA receptors.

Developmental switch in the kinase dependency of long-term potentiation depends on expression of GluA4 subunit-containing AMPA receptors

The AMPA-receptor subunit GluA4 is expressed transiently in CA1 pyramidal neurons at the time synaptic connectivity is forming, but its physiological significance is unknown. Here we show that GluA4 expression is sufficient to alter the signaling requirements of long-term potentiation (LTP) and can fully explain the switch in the LTP kinase dependency from PKA to Ca2(+)/calmodulin-dependent protein kinase II during synapse maturation. At immature synapses, activation of PKA leads to a robust potentiation of AMPA-receptor function via the mobilization of GluA4. Analysis of GluA4-deficient mice indicates that this mechanism is critical for neonatal PKA-dependent LTP. Furthermore, lentiviral expression of GluA4 in CA1 neurons conferred a PKA-dependent synaptic potentiation and LTP regardless of the developmental stage. Thus, GluA4 defines the signaling requirements for LTP and silent synapse activation during a critical period of synapse development.

Bi-factor analysis based on noise-reduction (BIFANR): a new algorithm for detecting coevolving amino acid sites in proteins

Previous statistical analyses have shown that amino acid sites in a protein evolve in a correlated way instead of independently. Even though located distantly in the linear sequence, the coevolved amino acids could be spatially adjacent in the tertiary structure, and constitute specific protein sectors. Moreover, these protein sectors are independent of one another in structure, function, and even evolution. Thus, systematic studies on protein sectors inside a protein will contribute to the clarification of protein function. In this paper, we propose a new algorithm BIFANR (Bi-factor Analysis Based on Noise-reduction) for detecting protein sectors in amino acid sequences. After applying BIFANR on S1A family and PDZ family, we carried out internal correlation test, statistical independence test, evolutionary rate analysis, evolutionary independence analysis, and function analysis to assess the prediction. The results showed that the amino acids in certain predicted protein sector are closely correlated in structure, function, and evolution, while protein sectors are nearly statistically independent. The results also indicated that the protein sectors have distinct evolutionary directions. In addition, compared with other algorithms, BIFANR has higher accuracy and robustness under the influence of noise sites.

Structural position correlation analysis (SPCA) for protein family

Background

The proteins in a family, which perform the similar biological functions, may have very different amino acid composition, but they must share the similar 3D structures, and keep a stable central region. In the conservative structure region similar biological functions are performed by two or three catalytic residues with the collaboration of several functional residues at key positions. Communication signals are conducted in a position network, adjusting the biological functions in the protein family.

Methodology

A computational approach, namely structural position correlation analysis (SPCA), is developed to analyze the correlation relationship between structural segments (or positions). The basic hypothesis of SPCA is that in a protein family the structural conservation is more important than the sequence conservation, and the local structural changes may contain information of biology functional evolution. A standard protein P⁽⁰⁾ is defined in a protein family, which consists of the most-frequent amino acids and takes the average structure of the protein family. The foundational variables of SPCA is the structural position displacements between the standard protein P⁽⁰⁾ and individual proteins P_i of the family. The structural positions are organized as segments, which are the stable units in structural displacements of the protein family. The biological function differences of protein members are determined by the position structural displacements of individual protein P_i to the standard protein P⁽⁰⁾. Correlation analysis is used to analyze the communication network among segments.

Conclusions

The structural position correlation analysis (SPCA) is able to find the correlation relationship among the structural segments (or positions) in a protein family, which cannot be detected by the amino acid sequence and frequency-based methods. The functional communication network among the structural segments (or positions) in protein family, revealed by SPCA approach, well illustrate the distantly allosteric interactions, and contains valuable information for protein engineering study.

Correlation analysis for protein evolutionary family based on amino acid position mutations and application in PDZ domain

BACKGROUND

It has been widely recognized that the mutations at specific directions are caused by the functional constraints in protein family and the directional mutations at certain positions control the evolutionary direction of the protein family. The mutations at different positions, even distantly separated, are mutually coupled and form an evolutionary network. Finding the controlling mutative positions and the mutative network among residues are firstly important for protein rational design and enzyme engineering.

METHODOLOGY

A computational approach, namely amino acid position conservation-mutation correlation analysis (CMCA), is developed to predict mutually mutative positions and find the evolutionary network in protein family. The amino acid position mutative function, which is the foundational equation of CMCA measuring the mutation of a residue at a position, is derived from the MSA (multiple structure alignment) database of protein evolutionary family. Then the position conservation correlation matrix and position mutation correlation matrix is constructed from the amino acid position mutative equation. Unlike traditional SCA (statistical coupling analysis) approach, which is based on the statistical analysis of position conservations, the CMCA focuses on the correlation analysis of position mutations.

CONCLUSIONS

As an example the CMCA approach is used to study the PDZ domain of protein family, and the results well illustrate the distantly allosteric mechanism in PDZ protein family, and find the functional mutative network among residues. We expect that the CMCA approach may find applications in protein engineering study, and suggest new strategy to improve bioactivities and physicochemical properties of enzymes.