Many species have been used to model various aspects of human diseases including mental illness. However, the complexity of human biochemistry, anatomy and behavioral factors are not easily modeled in all species and warrant the use of species which have greater degrees of functional equivalence for the measures under investigation. For example, the experimental use of Macaca mulatta (rhesus monkey) has been essential for expanding our knowledge of neurodevelopmental, neurodegenerative and organic human brain diseases, as well as, for normal brain function due in large part to close similarities in neuroanatomy, neurobiochemistry and behavior compared with other species. Moreover, the use of Macaca mulatta has significant translational value for understanding the influence of alterations in gene and protein expression in human disease processes.

One potential obstacle to comprehensive assessments of protein alterations is the relative paucity of available protein annotations for rhesus monkeys. Currently; NCBInr, Swiss-Prot and TrEMBL list 330210, 14991 and 55805 human protein annotations, respectively. However, NCBInr, Swiss-Prot and TrEMBL list only 41968, 297 and 1801 protein annotations for rhesus monkey, respectively. The highly uncharacterized nature of the rhesus monkey proteome makes it difficult to identify proteins, demonstrate differential regulation of proteins and investigate their post-translational modifications. The characterization of proteins of interest from rhesus monkey using the standard database search engines (e.g., MASCOT) has a limitation in that 'broad species database' searches are needed which results in less than optimal protein annotation. This limitation can be overcome in some respects using a de novo sequencing strategy, in which partial or complete amino acid sequence information is obtained using either manual or automated de novo peptide sequence analysis. This approach has been successfully utilized in recent studies to characterize peptides bound to class I MHC molecule HLA-A2.11, human skin elastin protein2 and proteins from unsequenced genome of Halorhodospira halophila3.

While manual protein sequencing via Edman degradation yields exact amino acid sequence without ambiguity, the procedure is laborious and does not lend itself to high-throughput analysis. It also lacks the sensitivity of mass spectrometry and can be halted by the presence of blocked amino acids. Fortunately, automated software tools have been developed to characterize the amino acid sequences generated from tandem mass spectrometry such as the complex MS/MS fragmentation pattern generated by MALDI-TOF-TOF mass spectrometer. Quality MS/MS spectrum consists of a ladder for y-ions and b-ions peaks. De novo sequencing uses the mass difference between two adjacent ions to deduce the peptide fragment sequence. However, factors such as incomplete fragmentation (whereby not all the y- and b-ions are present in the spectrum), imprecise precursor ion selection due to overlapping peptide fragment masses, low signal-to-noise ratio and unpredicted post-translational modifications (PTMs) complicate the manual de novo sequencing. De novo sequencing enables the analysis of quality MS/MS spectra which fails to generate protein identification after database searches, which is the case for the majority of proteins in rhesus monkeys. In fact, de novo sequencing is the only alternative for study of species with incomplete databases and databases which are not in the public domain 2456. Several strategies have been utilized more recently for de novo sequencing including chemical derivatization that add acidic, fixed charge or basic moieties178910111213. These have included various derivatization protocols such as sulfonation of the peptide N-terminal group. This derivatization creates a strong acidic group which greatly enhances fragmentation ability of tryptic peptides to produce b and y fragments. The use of ¹⁸O incorporation at the C-terminus of peptides during protein hydrolysis has also been applied 1415. The current study shows the utility of underivatized peptides using MALDI-TOF-TOF.

To this end, de novo sequencing of peptides isolated from cytosolic fractions of the ventral striatum of rhesus monkeys was performed. The ventral striatum/nucleus accumbens is an integral component of the cortico-straital-palldial-thalamic/mesencephalic circuit which is involved in sensorimotor integration. Furthermore, dysregulation of the ventral striatum has been implicated in a variety of psychiatric disorders, including substance abuse 1617, schizophrenia 181920 and depression 212223. The use of the ventral striatum tissue and the cytosolic fraction from this region is based on the research interests of our laboratory. However, the de novo sequencing strategy presented here is generalizable to all brain regions, tissues and other protein preparations.

The presented method consists primarily of de novo sequencing of underivatized peptides using the MALDI-TOF-TOF, compared to various derivatizing strategies used recently for various de novo studies. The generated sequences were used to perform homology searches to characterize the protein identification. The current study validates a robust method to confidently characterize proteins from an incomplete sequence database of Macaca mulatta thereby facilitating the use of this animal model in various neuroproteomics studies.

Comparison of the rhesus monkey de novo sequences with sequences in the human protein database enabled the validation of the de novo capabilities of the present method. This was accomplished by performing the detailed de novo method on tandem mass spectrometer spectra from Homo sapiens samples and objectively assessing the accuracy of the de novo sequencing by performing conventional database search (MASCOT) on the same spectra. Figure 1 shows the preliminary separation of proteins from nucleus accumbens of Macaca mulatta using the two-dimensional gel electrophoresis. The protein spots selected for de novo sequencing analysis ranged between 11- to 70-KDa and pI of 4.5–6.5 with a uniform distribution over the entire 2-D gel with respect to the M_r and pI. The labeled protein spots were subjected to in-gel trypsin digestion after de-staining the gel plugs. The peptide fragments extracted from the gel plugs were then subjected to tandem-mass spectrometry using the ABI 4700 proteomics analyzer (MALDI-TOF-TOF).

Tandem-mass spectra were then submitted for database searching (GPS Explorer: MASCOT), allowing to be searched with and without all known post-translational modifications, for protein characterization using the limited Macaca mulatta database. The majority of spectral analyses yielded no positive characterization, at which point spectra were subjected to PEAKS de novo analysis. According to the manufacturer, "the algorithm first computes a y-ion matching score and a b-ion matching score at each mass value according to the peaks around it. If there are no peaks around a mass value, a penalty value is assigned. The algorithm then efficiently computes many amino acid sequences that maximize the total scores at the mass values of b-ions and y-ions. These candidate sequences are further evaluated by a more accurate scoring function, which also considers other ion types such as immonium ions and internal-cleavage ions (Figure 2). The problem of ion absence is addressed because the PEAKS model assigns a score (or penalty) for each mass value. The software also computes a 'positional confidence' for each amino acid in the final result by examining the consensus of the top-scoring peptides" 4.

Thirteen targeted protein spots (Figure 1) were identified by MALDI-TOF-TOF followed by peptide sequencing using PEAKS Studio 4.0 de novo sequencing software. The generalized schematic of the methodology used in the current study to compile a database for Macaca mulatta is depicted in Figure 3. Detailed information of the confirmed protein characterization are elaborated in Table 1 with respect to the precursor mass, m/z error (ppm), PEAKS and SPIDER score for confidence interval (%) for the PEAKS de novo generated peptide sequences and their corresponding homology searches. This method characterized 13 protein spots out of 30 protein spots initially selected for de novo analysis.

The tandem-mass spectra were analyzed by PEAKS de novo sequencing software to generate amino acid sequences (Figure 2). All tandem-mass spectra were deconvoluted to minimize the error in de novo sequencing. Figure 2 shows the fragmentation pattern of a precursor ion with m/z of 1967.8951. As has been documented previously and can be noted in the spectrum (Figure 2), complementary information is not always available for all b-ions and y-ions and not all the immonium ions are represented in the spectra. Spectral analysis is further complicated by the appearance of some a-ions, neutral losses of water and ammonia for b-ions and y-ions. These analysis caveats render the ability to obtain a manual de novo sequence tedious if not impossible. As elaborated in the Methods Section, the PEAKS de novo sequencing utilizes most abundant peptide fragments 'b-ions and y-ions'; the less abundant peptide fragments 'a-ions'; the neutral losses of water and ammonia for b-ions and y-ions; as well as the immonium ions to develop confident and complete peptide sequences de novo from MS/MS spectra24. The b-, y-, a-, and immonium-ions as well as the neutral losses of water and ammonia for y-ions are tabulated in Figure 2 for the amino-acid sequence 'RSALQAAHDAVAQEGQCR'. The tandem-mass spectrum in Figure 2 is representative of the similar analysis performed on the remaining protein spots from Figure 1.

Twenty peptide sequences were characterized by PEAKS de novo sequence analysis software from 13 protein spots (Table 1). The generated sequences were used to perform homology searches to characterize proteins. As a standard measure, all de novo generated amino-acid sequences were searched further for homologous sequences using the PEAKS homology search engine against the Mammalian database. Out of the twenty de novo generated sequences subjected to PEAKS homology search, thirteen yielded positive protein characterization (Table 1). All peptide sequences exhibited homology to Homo sapiens, with the exception of the sequence from one spot (GST pi enzyme: Macaca mulatta), The inability of the PEAKS homology search to resolve the remaining seven sequences may be attributed to the fact that the software assumes that the de novo sequence is 100% correct. Whereas standard BLAST assumes 100% accuracy of the de novo sequence, SPIDER software accounts for possible errors in de novo sequencing. Also, it should be noted that the conventional search engines such as BLAST and FASTA are designed to handle queries which are longer than 35 amino acids. Prototypically, the peptide sequences obtained after trypsin digestion are not longer than 10–15 amino acids. SPIDER software was utilized for homology based database searches in instances where PEAKS homology searches failed to provide positive protein identification. Such errors were characteristically due to partially correct sequence tags and replacement of an amino acid segment by another segment with approximately the same mass. The criteria used for the SPIDER based searches were as follows: non-gapped homology match; mass tolerance of 0.1 Da; NCBInr database; leucine equals isoleucine; lysine equals glutamine; carbamidomethylation and methionine in oxidized form. The approach yielded positive characterization of the remaining seven peptide sequences. Of these, five peptide sequences resulted in the characterization of three new proteins previously not characterized by the PEAKS homology search. The remaining two peptides correspond to previously identified proteins; however, the peptides represent new characterizations.

Table 1 also shows that the peptide sequences generated by the PEAKS de novo sequencing software returned identical sequences when searched for homologous sequences in the database, with the exception of four peptides belonging to three proteins. Thus, the PEAKS de novo sequencing software was able to provide positive protein identification in most instances. An example of the added benefit of coupling PEAKS de novo sequencing software with the SPIDER homology search is shown in Figure 2. The original sequence generated by the PEAKS de novo software was '[RS]A [L]QAAHDAVAQEGQCR', whereas the SPIDER homology search returned a sequence of '[NE]A [I]QAAHDAVAQEGQCR' with a unequivocal score of 10 and associated to protein ubiquitin carboxyl-terminal esterase L1 (Homo Sapiens). At least a part of the error of the PEAKS de novo software was due to the I/L ambiguity.

Thirteen targeted protein spots (Figure 1) were identified by MALDI-TOF-TOF followed by peptide sequencing using PEAKS Studio 4.0 de novo sequencing software (e.g. Figure 2). The generalized schematic of the methodology used in the current study to compile a database for Macaca mulatta is depicted in Figure 3. The detailed information of the confirmed protein characterization are elaborated in Table 1 with respect to the precursor mass, m/z error (ppm), PEAKS and SPIDER score for confidence interval (%) for the PEAKS de novo generated peptide sequences and their corresponding homology searches. This method characterized 13 protein spots out of 30 protein spots initially selected for de novo analysis.

Contemporary proteomics requires prompt and confident protein identification of proteins of interest. The ability to utilize animal models to study the biochemical correlates of human disease requires a more complete database of those species as a prerequisite. To this end, the de novo sequencing strategy presented here provides a rapid and reliable means to identify proteins in Macaca mulatta – a species for which publicly available protein databases are very limited. However, it is important to note that this strategy is generalizable to other tissues, protein preparations and species and is not exclusive for Macaca mulatta or for cytosolic protein fractions from brain.

From 30 excised gel spots 13 were identified by mass spectrometry coupled with PEAKS de novo analysis software. Among the proteins were receptor-associated proteins, proteins involved in intra-cellular signaling, cytoskeletal structure, protein folding, hormonal changes and regulation of oxidative stress. The current study was undertaken to delineate a preliminary proteomics scale methodology to identify proteins de novo from NAc cytosol in the primate brain. Following mass spectrometric analysis, the most abundant peptides in the mixture led to the most accurate protein identification – hence, less abundant proteins may be overlooked. However, this caveat holds for all two dimensional gel-based proteomic approaches for studying disease states. Nevertheless, the present results provide the first preliminary de novo proteomic profile from Macaca mulatta and will form the basis of the future proteomics scale studies using non-human primate.

NAc; nucleus accumbens, 2 DGE; two dimensional gel electrophoresis, 2-D; two dimensional, MALDI-TOF-TOF; matrix assisted laser desorption ionization-time of flight-time of flight, MS; mass spectrometry, MS/MS; tandem mass spectrometry PAGE; Polyacrylamide Gel Electrophoresis, RB; re-hydration buffer, IEF; isoelectric focusing, DTT; dithiothreitol, m/z; mass/charge, PMF; Peptide mass fingerprint

The studies were conducted in the lab of SEH. SEH procured and dissected the tissue, isolated the cytosolic fractions and participated in the writing of the manuscript. NST conceived the study and its design. NST carried out the sample preparation and 2D-PAGE; produced and analyzed MALDI-TOF-TOF data; performed de novo sequencing and drafted the manuscript. Both the authors read and approved the final manuscript.