Selenocysteine - ACS Publications - American Chemical Society

Dec 18, 2015 - Center for Health Informatics and Bioinformatics, New York University ... Department of Biochemistry and Medical Genetics, University o...
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Selenocysteine: Wherefore Art Thou? David Fenyö† and Ronald C. Beavis*,‡ †

Center for Health Informatics and Bioinformatics, New York University Medical School, 227 East 30 Street, New York, New York 10016, United States ‡ Department of Biochemistry and Medical Genetics, University of Manitoba, Faculty of Health Sciences, 744 Bannatyne Avenue, Winnipeg, Manitoba R3E 0W3, Canada ABSTRACT: Selenocysteine is a naturally occurring proteogenic amino acid that is encoded in the genomic sequence of relatively abundant proteins in many of the model species commonly used for biomedical research. On the basis of an analysis of publicly available proteomics information, it was discovered that peptides containing selenocysteine were not being identified in tandem mass spectrometry proteomics data. Once the chemical basis for this exclusion was understood, a simple alteration in search parameters led to the confident identification of selenocysteine containing peptides from existing proteomics data, with no change in experimental protocols required. elenocysteine (commonly abbreviated as either “U” or “Sec”) is one of the rarest of the proteogenic amino acids, and it is encoded in an organism’s genomic sequence in an unusual manner.1 Sec is represented by the codon UGA in a gene’s mRNA, which would normally be interpreted by a ribosome as a STOP codon. To prevent this undesirable sequence translation, the mRNA also contains a “selenocysteine insertion sequence” in the 3′ untranslated region (in eukaryotes) or immediately following the UGA codon (in bacteria). This additional sequence causes the ribosome to correctly translate UGA as selenocysteine. Twenty-five genes in the current human genome (GRCh38) code for proteins that contain at least one Sec, for a total of 46 Sec residues in the human proteome. This amino acid is most commonly found at the active site of peroxidase2 (e.g., GPX2) and reductase enzymes3 (e.g., MSRB1), where the redox potential of selenium makes it an essential choice rather than the sulfur in normal cysteine. Human selenoprotein P (SEPP1) is an exception: It is a small plasma protein that has 10 Sec residues, none of which appear to be directly involved in redox catalytic activity.4 GPMDB is a collection of publicly available protein and peptide identification information obtained from experimental raw data using tandem mass-spectrometry-based “bottom-up” proteomics experiments.5 This information is examined periodically to determine whether there are gaps in the identified peptide sequence coverage obtained from the experimental data that may be caused by unanticipated problems with the search algorithms used to generate these identifications. Several years ago, it was noticed that peptides containing the residue Sec were effectively absent from the database, even though the peptide sequences containing this residue did not have any of the characteristics that would make them difficult to observe (e.g., tryptic peptides that are too

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short, long, or hydrophobic). Some of the Sec-containing proteins were commonly observed with good sequence coverage outside of their Sec-containing domains, so why the presence of Sec in a tryptic peptide sequence should result in the exclusion of these peptides from these observations was not immediately evident. Consideration of the possible effects of normal proteomics sample preparation chemistry on the selenol group of Sec suggested that the selenol should react with thiol blocking reagents (e.g., iodoacetamide, methylmethanethiosulfonate) in the same manner as cysteine. Therefore, in experimental protocols using iodoacetamide to block cysteine thiols, the carbamidomethyl-Se derivative should be present rather than the free selenol H−Se group after treatment. Simply adding Sec to the list of residues fully derivatized by the appropriate thiolblocking reagent compensates for this unintended chemical reaction. The change can be implemented in any peptide identification algorithm that correctly handles Sec residues in protein sequences and including this modification should not affect the run-time of the algorithm for obtaining peptide-tospectrum matches (PSMs). Altering the search parameters to apply the same fixed modifications used for both Cys and Sec led almost immediately to the identification of Sec-containing peptides in GPMDB. As of writing, 4053 PSMs have been assigned to 77 unique Sec-containing human peptide sequences. The number of PSMs assigned to Sec-containing peptides in any particular data set was very small; however, the fraction of these assignments for a particular selenoprotein could be significant. For example, PSMs to Sec-containing peptides amounted to Received: November 8, 2015

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DOI: 10.1021/acs.jproteome.5b01028 J. Proteome Res. XXXX, XXX, XXX−XXX

Letter

Journal of Proteome Research 12% of all spectra assigned to SEPW1, 7% for SELM, and 4% for GPX4. It is our belief that the simplicity of obtaining these additional PSMs, the potential for systematic bias against selenoproteins in quantitation experiments, and their biological importance as being characteristic of catalytic centers in these proteins argue for routinely adding Sec to the list of residues modified by thiol-blocking reagents when performing routine peptide identification analyses.



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.



REFERENCES

(1) Böck, A.; Forchhammer, K.; Heider, J.; Baron, C. Selenoprotein synthesis: an expansion of the genetic code. Trends Biochem. Sci. 1991, 16, 463−7. (2) Hondal, R. J.; Marino, S. M.; Gladyshev, V. N. Selenocysteine in thiol/disulfide-like exchange reactions. Antioxid. Redox Signaling 2013, 18, 1675−89. (3) Achilli, C.; Ciana, A.; Minetti, G. The discovery of methionine sulfoxide reductase enzymes: An historical account and future perspectives. Biofactors. 2015, 41, 135−52. (4) Mao, J.; Teng, W. The relationship between selenoprotein P and glucose metabolism in experimental studies. Nutrients 2013, 5, 1937− 48. (5) Craig, R.; Cortens, J. P.; Beavis, R. C. Open source system for analyzing, validating, and storing protein identification data. J. Proteome Res. 2004, 3, 1234−42.

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DOI: 10.1021/acs.jproteome.5b01028 J. Proteome Res. XXXX, XXX, XXX−XXX