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J Biomol Tech. 2010 December; 21(4): 214–218.
PMCID: PMC2977963

Article Watch, December 2010

This column highlights recently published articles that are of interest to the readership of this publication. We encourage ABRF members to forward information on articles they feel are important and useful to Clive Slaughter, MCG-UGA Medical Partnership, 279 William St., Athens GA 30607-1777. Tel; (706) 369-5945: Fax; (706) 369-5936: E-mail: ude.gcm.liam@rethgualsc; or to any member of the editorial board. Article summaries reflect the reviewer's opinions and not necessarily those of the Association.

DNA SEQUENCING AND CHARACTERIZATION

Teer JK, Bonnycastle LL, Chines PS, Hansen NF, Aoyama N, Swift AJ, Abaan HO, Albert TJ, Program NCS, Margulies EH, Green ED, Collins FS, Mullikin JC, Biesecker LG. Systematic comparison of three genomic enrichment methods for massively parallel DNA sequencing. Genome Research 20;2010:1420–1431.

The targeted capture methods compared in this publication are molecular inversion probes, Agilent's solution hybrid selection, and Roche-NibleGen's microarray-based genomic selection. Genotype sensitivity and accuracy of variant detection are evaluated in relation to relative cost of the methods for capture of the same 2.61 Mb (528 genes) of non-contiguous DNA sequence from an overlapping set of two HapMap DNA samples. All three methods were effective and yielded similar accuracies (compared to high quality, whole-genome shotgun sequencing data). However, they differed in genotype assignment sensitivity as measured by the uniformity in the depth of coverage: as uniformity decreases, certain positions have unnecessary depth of coverage for accurate genotype assignment while others lack adequate coverage leading to absent or inaccurate assignments. Microarray-based selection gave the most uniform depth of coverage, followed by solution hybrid selection and then molecular inversion probes. Two other features of this study will be of interest to readers. The first is a new Bayesian genotype-assigning algorithm called Most Probable Genotype (MPG); and the second is the use of a bar-coding strategy to allow pooling of samples for capture and sequencing.

Varley KE, Mitra RD. Bisulfite Patch PCR enables multiplexed sequencing of promoter methylation across cancer samples. Genome Research 20;2010:1279–1287.

Hypermethylation and consequent gene silencing is probably as important as mutation in driving tumor progression. Genomic capture methods have been combined with massively parallel bisulfite sequencing to enable individual samples to be subjected to methylation surveys, but validation of the results requires study of many loci across large numbers of individual patients, a task not readily achievable. The present paper describes methods allowing multiplexed operation of bisulfite PCR and sequencing across many patient samples. Specific promoters are targeted for PCR amplification by annealing oligonucleotide sequences to the ends of the targeted fragments, and sample-specific DNA barcodes are incorporated into the amplicons to allow pooling of samples for sequencing.

CARBOHYDRATES AND GLYCOCONJUGATES

Mysling S, Palmisano G, Højrup P, Thaysen-Andersen M. Utilizing Ion-Pairing Hydrophilic Interaction Chromatography Solid Phase Extraction for Efficient Glycopeptide Enrichment in Glycoproteomics. Analytical Chemistry 82;2010:5598–5609.

Hydrophilic interaction chromatography (HILIC), a variant of normal-phase chromatography, has become increasingly popular as a method for enrichment of glycopeptides in peptide pools. The method discriminates between glycosylated and non-glycosylated peptides on the basis of their binding to a hydrophilic stationary phase, but overlap between the hydrophilicity between the two peptide groups limits the method's effectiveness. The present paper shows that the presence of trifluoroacetic acid as an ion-pairing reagent in the mobile phase significantly improves discrimination, thereby enhancing glycopeptide detection by MALDI-TOF mass spectrometry. The improved method is implemented in the form of a solid-phase extraction procedure that is applied successfully to samples of varying complexity.

MACROMOLECULAR SYNTHESIS

El-Sagheer AH, Brown T. New strategy for the synthesis of chemically modified RNA constructs exemplified by hairpin and hammerhead ribozymes. Proceedings of the National Academy of Sciences, U.S.A. 107;2010:15329–15334.

Because the synthesis of RNA by automated phosphoramidite methodology is less efficient than the synthesis of DNA, RNA chains longer than about 50 nucleotides are difficult to prepare. However, many biologically active RNAs, including ribozymes, aptamers, and riboswitches, are longer than this. Site-specific incorporation of unnatural chemical groups or linkages precludes transcriptional synthesis; and enzymatic ligation is impeded by poor reaction efficiency and the commonly encountered presence of nucleases in ligase preparations. This paper uses copper-catalyzed 1,3-diolar azide-alkyne cycloaddition (CuAAC), i.e., click ligation, for the synthesis of active RNA constructs. Individual RNA oligonucleotides are assembled by automated solid-phase synthesis, purified by HPLC, and then chemically ligated by click chemistry to produce larger molecules. RNA molecules and DNA/RNA chimeras up to 100 nucleotides in length are here synthesized in this way. Two strategies, cross-strand ligation through neighboring bases, and intra-strand click ligation, are successfully employed. These methods are applicable to the large-scale synthesis of a wide variety of RNA species, including riboswitches, siRNA delivery systems, multivalent aptamers, and components of ribosomes.

SMALL MOLECULE ANALYSIS AND METABOLOMICS

Liu L, Aa J, Wang G, Yan B, Zhang Y, Wang X, Zhao C, Cao B, Shi J, Li M, Zheng T, Zheng Y, Hao G, Zhou F, Sun J, Wu Z. Differences in metabolite profile between blood plasma and serum. Analytical Biochemistry 406;2010:105–112.

The authors of this paper remind us that serum and plasma may not be equivalent sources for analysis of the composition of biological fluids. Low molecular weight compounds are studied from each by gas chromatography/time-of-flight mass spectrometry. Of the 72 compounds identified, 36 discriminate serum from plasma. Serum is recommended as the best choice for metabolomics studies.

Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, Pirruccello JP, Ripatti S, Chasman DI, Willer CJ, Johansen CT, Fouchier SW, Isaacs A, Peloso GM, Barbalic M, Ricketts SL, Bis JC, Aulchenko YS, Thorleifsson G, Feitosa MF, Chambers J, Orho-Melander M, Melander O, Johnson T, Li X, Guo X, Li M, Shin Cho Y, Jin Go M, Jin Kim Y, Lee J-Y, Park T, Kim K, Sim X, Twee-Hee Ong R, Croteau-Chonka DC, Lange LA, Smith JD, Song K, Hua Zhao J, Yuan X, Luan JA, Lamina C, Ziegler A, Zhang W, Zee RYL, Wright AF, Witteman JCM, Wilson JF, Willemsen G, Wichmann HE, Whitfield JB, Waterworth DM, Wareham NJ, Waeber G, Vollenweider P, Voight BF, Vitart V, Uitterlinden AG, Uda M, Tuomilehto J, Thompson JR, Tanaka T, Surakka I, Stringham HM, Spector TD, Soranzo N, Smit JH, Sinisalo J, Silander K, Sijbrands EJG, Scuteri A, Scott J, Schlessinger D, Sanna S, Salomaa V, Saharinen J, Sabatti C, Ruokonen A, Rudan I, Rose LM, Roberts R, Rieder M, Psaty BM, Pramstaller PP, Pichler I, Perola M, Penninx BWJH, Pedersen NL, Pattaro C, Parker AN, Pare G, Oostra BA, O/'Donnell CJ, Nieminen MS, Nickerson DA, Montgomery GW, Meitinger T, Mcpherson R, Mccarthy MI, Mcardle W, Masson D, Martin NG, Marroni F, Mangino M, Magnusson PKE, Lucas G, Luben R, Loos RJF, Lokki M-L, Lettre G, Langenberg C, Launer LJ, Lakatta EG, Laaksonen R, Kyvik KO, Kronenberg F, Konig IR, Khaw K-T, Kaprio J, Kaplan LM, Johansson A, Jarvelin M-R, Cecile JW, Janssens A, Ingelsson E, Igl W, Kees Hovingh G, Hottenga J-J, Hofman A, Hicks AA, Hengstenberg C, Heid IM, Hayward C, Havulinna AS, Hastie ND, Harris TB, Haritunians T, Hall AS, Gyllensten U, Guiducci C, Groop LC, Gonzalez E, Gieger C, Freimer NB, Ferrucci L, Erdmann J, Elliott P, Ejebe KG, Doring A, Dominiczak AF, Demissie S, Deloukas P, De Geus EJC, De Faire U, Crawford G, Collins FS, Chen Y-D I, Caulfield MJ, Campbell H, Burtt NP, Bonnycastle LL, Boomsma DI, Boekholdt SM, Bergman RN, Barroso I, Bandinelli S, Ballantyne CM, Assimes TL, Quertermous T, Altshuler D, Seielstad M, Wong TY, Tai ES, Feranil AB, Kuzawa CW, Adair LS, Taylor Jr HA, Borecki IB, Gabriel SB, Wilson JG, Holm H, Thorsteinsdottir U, Gudnason V, Krauss RM, Mohlke KL, Ordovas JM, Munroe PB, Kooner JS, Tall AR, Hegele RA, Kastelein JJP, Schadt EE, Rotter JI, Boerwinkle E, Strachan DP, Mooser V, Stefansson K, Reilly MP, Samani NJ, Schunkert H, Cupples LA, Sandhu MS, Ridker PM, Rader DJ, Van Duijn CM, Peltonen L, Abecasis GR, Boehnke M, Kathiresan S. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466;2010:707–713.

A meta-analysis of the results of genome-wide association studies involving more than 100,000 individuals is here used to screen the human genome for common genetic variants affecting plasma levels of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides. These levels are among the most important risk factors for coronary artery disease. Ninety-five distinct loci are identified with high probability, including genes previously identified through the effects of rare variants that cause extreme changes in blood lipid levels, through candidate-gene studies, or as the targets of lipid-lowering drugs. Fifty-nine of the loci are associated with plasma lipid levels for the first time. The association with three of the novel loci is validated in experiments with mouse models. Despite the power of this methodology to increase our understanding of lipid homeostasis, and the effort involved in such large genome-wide association studies, it is noteworthy that the 95 loci identified in the present analysis account for only 10–12% of the total variance in blood lipid levels, or 25–30% of the genetic variance.

MASS SPECTROMETRY

Geiger T, Cox J, Mann M. Proteomics on an Orbitrap Benchtop Mass Spectrometer Using All-ion Fragmentation. Molecular & Cellular Proteomics 9;2010:2252–2261.

The newly introduced Exactive mass spectrometer system from ThermoFisher Scientific is intended primarily for small-molecule analysis. It consists of an Orbitrap mass analyzer with a C-trap for ion storage and a high-energy collision dissociation (HCD) cell for fragmentation. It lacks the capability for precursor ion selection incorporated in the hybrid LTQ-Orbitrap and LTQ-Orbitrap Velos instruments, which have a linear ion-trap for the purpose. The present study shows that despite its simplified instrument architecture and the consequent lack of ability to select precursors for targeted fragmentation, the Exactive system identies the majority of components in the ABRF 49-protein equimolar standard mixture (suppplied by Sigma). This result is rendered possible by recovering precursor-product relationships by monitoring correlated time-dependent changes in signal intensity as precursors elute from a liquid chromatograph, and by making use of the high mass accuracy provided by the mass spectrometer. Gel bands also yield protein mixtures of modest complexity that the instrument is shown to be capable of handling.

Wang J, Pérez-Santiago J, Katz J E, Mallick P, Bandeira N. Peptide Identification from Mixture Tandem Mass Spectra. Molecular & Cellular Proteomics 9;2010:1476–1485.

During LC-MS/MS analysis of complex peptide samples, the probably frequent acquisition of product ion spectra that are derived from mixtures of precursors rather than the assumed single precursor is believed to represent an important limitation in proteome methodology. An approach to ameliorating the effects of this problem is offered here. Peptides are identified by spectral library searching, and mixture-spectra are treated as linear, pairwise combinations of single-peptide spectra. The spectral library is not prefiltered: i.e., observed spectra are searched for matches with all available library spectra, not just with spectra from peptides with similar mass. Assignments are made on the basis of the similarity between observed and target spectra, and peaks from the assigned peptide are then subtracted from the mixture spectrum so that the remaining peaks can be matched in a second library search. This process is economical because it avoids having to search all possible pairwise combinations of peptides in the spectral library. Mixture spectra can be assigned rapidly even when searched against large peptide libraries.

PROTEINS—PURIFICATION AND CHARACTERIZATION

Trnka MJ, Burlingame AL. Topographic Studies of the GroEL-GroES Chaperonin Complex by Chemical Cross-linking Using Diformyl Ethynylbenzene. Molecular & Cellular Proteomics 9;2010:2306–2317.

A new chemical cross-linker designed for facile mass spectrometric identification of cross-linked peptides is described. The reagent, 1,3-diformyl-5-ethenylbenzene (DEB), forms Schiff bases with the ε-amino groups of lysine residues at protein-protein interfaces and conjugates proteins via secondary amino linkages. This chemistry preserves the cross-linked residues as sites of protonation. This feature is helpful when using electron transfer dissociation, a technique in which high charge-states favor informative fragmentation. Furthermore, charge-dependent precursor selection is employed strategically to disfavor unmodified and dead-end modified peptides. Electron transfer induces dissociation of DEB cross-links to yield a diagnostic pair of products in which the unmodified species with neutral lysyl amino group is generated from one peptide and the cross-linker adduct plus hydrogen is generated at the lysyl residue of the other peptide. This characteristic matched pair is observed for all cross-linked peptide species. High yields of cross-linked peptides are observed with this methodology, and electron transfer produces consistently informative peptide fragmentation.

Papalia G, Myszka D. Exploring minimal biotinylation conditions for biosensor analysis using capture chips. Analytical Biochemistry 403;2010:30–35.

A new biotin capture kit has been released by GE Healthcare Biosciences to assist in immobilizing proteins for study in Biacore biosensors. The chips have an oligonucleotide-derivatized surface that hybridizes with a complementary oligonucleotide-linked streptavidin. Biotinylated target proteins bind to the streptavidin, but despite the high affinity interaction, the surface can be readily stripped by dissociating the oligonucleotide duplex. For optimal performance, target proteins must be mono-biotinylated. The present work comprises a systematic investigation of conditions for this minimal biotinylation. It illustrates how to optimize conditions for the biotinylation reaction, how to make the choice between amino- and carboxyl-biotinylation chemistry, and how to choose a desalting method to remove unbound biotin after the reaction. The study also highlights the detrimental effects of over-biotinylation on surface binding capacity.

Rich RL, Myszka DG. Kinetic analysis and fragment screening with Fujifilm AP-3000. Analytical Biochemistry 402;2010:170–178.

The Fujifilm AP-3000 is a new surface plasmon resonance-based biosensor that is marketed for drug-screening. Results from this instrument are here compared to those obtained with the Biacore T100 from GE Healthcare Biosciences. Data are acquired for the interaction between biotinylated carbonic anhydrase II and a set of sulfonamide inhibitors ranging in molecular weight from 98 to 341 Da and in affinity from 0.4 mM to 20 nM. The AP-3000 uses a stop-flow analyte delivery protocol. This complicates the shapes of association and dissociation curves, but the results could be compared with those from the T100 by restricting attention to responses recorded under flow conditions. Results acquired with the two instruments were in good accord. A fragment screening assay was also conducted on the AP-3000 for a 3500-compound library binding to carbonic anhydrase II to test the processing steps required to account for drifting baselines and loss of target activity in long runs. The instrument successfully tested ten 384-well plates in 24 hours, indicating its suitability for such demanding applications.

PROTEOMICS

Karp NA, Huber W, Sadowski PG, Charles PD, Hester SV, Lilley KS. Addressing Accuracy and Precision Issues in iTRAQ Quantitation. Molecular & Cellular Proteomics 9;2010:1885–1897.

Data analysis issues with protein quantification by the iTRAQ method are systematically re-examined in this report. Recommendations are made on the basis of the error structure for data from same-same comparisons, and on the basis of accuracy revealed in measurements on 4-protein mixtures in which the known relative quantities of the components span 1 to 4 orders of magnitude. To account for error values that characteristically increase at lower abundance levels, the authors recommend decoupling variance from signal intensity by using a generalized logarithmic transformation. This approach allows low intensity readings to be included for quantification rather than simply being discarded. The calculations are performed with an open-source software package,“variance-stabilizing normalization.” Exaggeration of errors at low signal intensity is suggesed to be due in part to contributions from small, basal, non-specific background signals. As has been observed by others, expression ratios are compressed toward 1: i.e., expression differences are underestimated. The authors support the view that this effect is due to contamination during precursor ion selection. They advocate the use of correction factors to deal with this problem. These could be calculated for each new study by spiking in proteins at known ratios. This approach handles in a global manner the variation in peptide complexity from study to study that determines how much precursor contamination is likely to arise.

FUNCTIONAL GENOMICS AND PROTEOMICS

Levin JZ, Yassour M, Adiconis X, Nusbaum C, Thompson DA, Friedman N, Gnirke A, Regev A. Comprehensive comparative analysis of strand-specific RNA sequencing methods. Nature Methods 7;2010:709–715.

Massively parallel cDNA sequencing, also known as RNAseq, affords the capability to analyze the full transcript repertoire in order to define the transcript sequences, including their 5' and 3' ends and splice junctions, quantify their expression levels, and measure the extent of alternative splicing. Standard libraries for RNAseq, however, do not preserve information about which strand was originally transcribed, because synthesis of randomly primed double-stranded cDNA followed by addition of adaptors for massively parallel sequencing leads to loss of this information. A variety of methods for strand-specific RNAseq have been suggested. The present paper evaluates seven of these methods using the well-annotated Saccharomyces cerevisiae transcriptome as a benchmark. Differences in strand specificity, library complexity, evenness and continuity of coverage, agreement with known annotations and accuracy for expression profiling are noted. Two methods, the dUTP second-strand marking method (which benefits from the availability of paired end sequencing) and the Illumina RNA ligation method, are judged to be superior to the rest.

Griffith M, Griffith OL, Mwenifumbo J, Goya R, Morrissy AS, Morin RD, Corbett R, Tang MJ, Hou Y-C, Pugh TJ, Robertson G, Chittaranjan S, Ally A, Asano JK, Chan SY, Li HI, Mcdonald H, Teague K, Zhao Y, Zeng T, Delaney A, Hirst M, Morin GB, Jones SJM, Tai IT, Marra MA. Alternative expression analysis by RNA sequencing. Nature Methods 7;2010:843–847.

The diversity of expressed proteins is greatly augmented by alternative transcript initiation, alternative splicing, and alternative polyadenylation processes. The operation of these processes is amenable to study by RNAseq, but methods for cataloging alternative transcripts and measuring their differential expression in different cell and tissue types are still in their early stages of development. This paper presents methods for assessing expression, differential expression, and alternative expression of known and predicted mRNA isoforms, including reciprocal expression of alternative isoforms. Databases for alternative expression annotation, source code, and a data viewer are available at http://www.alexaplatform.org/alexa_seq/.

Taniguchi Y, Choi PJ, Li G-W, Chen H, Babu M, Hearn J, Emili A, Xie XS. Quantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells. Science 329;2010:533–538.

Using a newly constructed yellow fluorescent protein fusion library for E. coli containing 1018 genes, the authors employ fluorescence microscopy to count numbers of protein molecules in individual bacterial cells. They also count mRNA molecules for a smaller subset of 137 genes. Cells are found to contain between 0.1 and 10,000 copies of each protein species, and 0.05 and 5 copies of each mRNA species. The ratio of mRNA to protein ranged from 1:100 to 1:10,000, and there is no correlation between numbers of mRNA molecules and protein molecules at the level of individual cells at a given instant in time. This observation is related to the large difference in lifetimes of mRNA and protein molecules, and to stochastic variation in the apportionment of molecules during cell division. For low abundance proteins, the level of cell-to-cell variation decreases as abundance increases, but noise levels remain high even for abundant proteins. This is ascribed to stochastic variation in the synthesis of mRNA and protein molecules due to the presence of just a single copy of each gene and small numbers of transcriptional activator molecules. Variation is anticipated to be as large or larger among individual cells in higher eukaryotes, suggesting that much remains to be discovered about the control of metabolic processes at the single cell level.

BIOINFORMATICS/POLICY

Shah AR, Davidson J, Monroe ME, Mayampurath AM, Danielson WF, Shi Y, Robinson AC, Clowers BH, Belov ME, Anderson GA, Smith RD. An Efficient Data Format for Mass Spectrometry-Based Proteomics. Journal of the American Society for Mass Spectrometry 21;2010:1784–1788.

Efforts to facilitate data exchange within the proteomics community have led to the broad acceptance of eXtensible Markup Language (XML) documents for publication and dissemination of data. The present article argues that while the adoption of a standard format is an important step, XML is not ideal for storing large, multidimensional data sets. For example, storing LC-coupled ion mobility-based data in XML would require producing multiple XML files, one for each ion mobility acquisition frame—a data management nightmare. The authors here advocate instead the use of a relational database management system-based strategy. This is familiar to engineers and scientists, permits significant space-saving in storage of raw data, and is already associated with standard query language (SQL) as a common application programming interface for accessing data. A format based on standard database principles is described in this paper that facilitates processing, offers fast data retrieval, and accommodates multidimensional separation schemes.


Articles from Journal of Biomolecular Techniques : JBT are provided here courtesy of The Association of Biomolecular Resource Facilities