Systems biology relies on data sets in which the same group of proteins is consistently identified and precisely quantified across multiple samples, a requirement that is only partially achieved by current proteomics approaches. Selected reaction monitoring (SRM)—also called multiple reaction monitoring—is emerging as a technology that ideally complements the discovery capabilities of shotgun strategies by its unique potential for reliable quantification of analytes of low abundance in complex mixtures. In an SRM experiment, a predefined precursor ion and one of its fragments are selected by the two mass filters of a triple quadrupole instrument and monitored over time for precise quantification. A series of transitions (precursor/fragment ion pairs) in combination with the retention time of the targeted peptide can constitute a definitive assay. Typically, a large number of peptides are quantified during a single LC‐MS experiment. This tutorial explains the application of SRM for quantitative proteomics, including the selection of proteotypic peptides and the optimization and validation of transitions. Furthermore, normalization and various factors affecting sensitivity and accuracy are discussed. Mol Syst Biol. 4: 222

Absolute protein quantification via the measurement of protein copy numbers has the potential to provide important information about biological processes, but apart from the special case of brewers yeast, this has not proved possible using standard proteomics procedures. Now, with the leptospirosis pathogen Leptospira interrogans as the first target, a new mass spectrometry-based strategy that should be generally applicable to many other biological systems has been used to determine absolute protein abundance for a significant fraction of a proteome. The results show how L. interrogans adapts to changing environments by adjusting proteome homeostasis while the total protein copy numbers remain constant. Absolute protein concentration measurements of a considerable fraction of the proteome have, until now, only been derived from genetically altered Saccharomyces cerevisiae cells, using a technique that is not directly portable from yeast to other species. A mass-spectrometry-based method is now used to determine the absolute protein abundance for a significant fraction of the proteome of the human pathogen Leptospira interrogans. Mass-spectrometry-based methods for relative proteome quantification have broadly affected life science research. However, important research directions, particularly those involving mathematical modelling and simulation of biological processes, also critically depend on absolutely quantitative data—that is, knowledge of the concentration of the expressed proteins as a function of cellular state. Until now, absolute protein concentration measurements of a considerable fraction of the proteome (73%) have only been derived from genetically altered Saccharomyces cerevisiae cells1, a technique that is not directly portable from yeast to other species. Here we present a mass-spectrometry-based strategy to determine the absolute quantity, that is, the average number of protein copies per cell in a cell population, for a large fraction of the proteome in genetically unperturbed cells. Applying the technology to the human pathogen Leptospira interrogans, a spirochete responsible for leptospirosis2, we generated an absolute protein abundance scale for 83% of the mass-spectrometry-detectable proteome, from cells at different states. Taking advantage of the unique cellular dimensions of L. interrogans, we used cryo-electron tomography morphological measurements to verify, at the single-cell level, the average absolute abundance values of selected proteins determined by mass spectrometry on a population of cells. Because the strategy is relatively fast and applicable to any cell type, we expect that it will become a cornerstone of quantitative biology and systems biology.

The detection and quantification of plasma (serum) proteins at or below the ng/ml concentration range are of critical importance for the discovery and evaluation of new protein biomarkers. This has been achieved either by the development of high sensitivity ELISA or other immunoassays for specific proteins or by the extensive fractionation of the plasma proteome followed by the mass spectrometric analysis of the resulting fractions. The first approach is limited by the high cost and time investment for assay development and the requirement of a validated target. The second, although reasonably comprehensive and unbiased, is limited by sample throughput. Here we describe a method for the detection of plasma proteins at concentrations in the ng/ml or sub-ng/ml range and their accurate quantification over 5 orders of magnitude. The method is based on the selective isolation of N-glycosites from the plasma proteome and the detection and quantification of targeted peptides in a quadrupole linear ion trap instrument operated in the multiple reaction monitoring (MRM) mode. The unprecedented sensitivity of the mass spectrometric analysis of minimally fractionated plasma samples is the result of the significantly reduced sample complexity of the isolated N-glycosites compared with whole plasma proteome digests and the selectivity of the MRM process. Precise quantification was achieved via stable isotope dilution by adding ¹³C- and/or ¹⁵N-labeled reference analytes. We also demonstrate the possibility of significantly expanding the number of MRM measurements during one single LC-MS run without compromising sensitivity by including elution time constraints for the targeted transitions, thus allowing quantification of large sets of peptides in a single analysis.

Background: A close match of the HLA alleles between donor and recipient is an important prerequisite for successful unrelated hematopoietic stem cell transplantation. To increase the chances of finding an unrelated donor, registries recruit many hundred thousands of volunteers each year. Many registries with limited resources have had to find a trade-off between cost and resolution and extent of typing for newly recruited donors in the past. Therefore, we have taken advantage of recent improvements in NGS to develop a workflow for low-cost, high-resolution HLA typing. Results: We have established a straightforward three-step workflow for high-throughput HLA typing: Exons 2 and 3 of HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1 are amplified by PCR on Fluidigm Access Array microfluidic chips. Illumina sequencing adapters and sample specific tags are directly incorporated during PCR. Upon pooling and cleanup, 384 samples are sequenced in a single Illumina MiSeq run. We developed “neXtype” for streamlined data analysis and HLA allele assignment. The workflow was validated with 1140 samples typed at 6 loci. All neXtype results were concordant with the Sanger sequences, demonstrating error-free typing of more than 6000 HLA loci. Current capacity in routine operation is 12,000 samples per week. Conclusions: The workflow presented proved to be a cost-efficient alternative to Sanger sequencing for high-throughput HLA typing. Despite the focus on cost efficiency, resolution exceeds the current standards of Sanger typing for donor registration.

Protein complexes can be detected, counted and localized within the bacterium Leptospira interrogans by combining quantitative mass spectrometry–based proteomics analysis with cryo-electron tomography, with the aid of an improved template-matching method. Systems biology conceptualizes biological systems as dynamic networks of interacting elements, whereby functionally important properties are thought to emerge from the structure of such networks. Owing to the ubiquitous role of complexes of interacting proteins in biological systems, their subunit composition and temporal and spatial arrangement within the cell are of particular interest. 'Visual proteomics' attempts to localize individual macromolecular complexes inside of intact cells by template matching reference structures into cryo-electron tomograms. Here we combined quantitative mass spectrometry and cryo-electron tomography to detect, count and localize specific protein complexes in the cytoplasm of the human pathogen Leptospira interrogans. We describe a scoring function for visual proteomics and assess its performance and accuracy under realistic conditions. We discuss current and general limitations of the approach, as well as expected improvements in the future.

In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially perturbed cell states. The high degree of reproducibility required for such experiments has not been achieved by classical mass spectrometry-based proteomics methods. In this study we describe the implementation of a targeted quantitative approach by which predetermined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples. This approach consists of three steps. First, the proteome is extensively mapped out by multidimensional fractionation and tandem mass spectrometry, and the data generated are assembled in the PeptideAtlas database. Second, based on this proteome map, peptides uniquely identifying the proteins of interest, proteotypic peptides, are selected, and multiple reaction monitoring (MRM) transitions are established and validated by MS2 spectrum acquisition. This process of peptide selection, transition selection, and validation is supported by a suite of software tools, TIQAM (Targeted Identification for Quantitative Analysis by MRM), described in this study. Third, the selected target protein set is quantified in multiple samples by MRM. Applying this approach we were able to reliably quantify low abundance virulence factors from cultures of the human pathogen Streptococcus pyogenes exposed to increasing amounts of plasma. The resulting quantitative protein patterns enabled us to clearly define the subset of virulence proteins that is regulated upon plasma exposure.