Using iRT, a normalized retention time for more targeted measurement of peptides

Generation of a murine SWATH-MS spectral library to quantify more than 11,000 proteins

Targeted SWATH-MS data analysis is critically dependent on the spectral library. Comprehensive spectral libraries of human or several other organisms have been published, but the extensive spectral library for mouse, a widely used model organism is not available. Here, we present a large murine spectral library covering more than 11,000 proteins and 240,000 proteotypic peptides, which included proteins derived from 9 murine tissue samples and one murine L929 cell line. This resource supports the quantification of 67% of all murine proteins annotated by UniProtKB/Swiss-Prot. Furthermore, we applied the spectral library to SWATH-MS data from murine tissue samples. Data are available via SWATHAtlas (PASS01441).

Measurement(s)	Mouse Protein • mass spectrum • spectral library
Technology Type(s)	mass spectrometry • combined ms-ms + spectral library search
Sample Characteristic - Organism	Mus musculus

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11968230

A Dual Workflow to Improve the Proteomic Coverage in Plasma Using Data-Independent Acquisition-MS

Plasma is one of the most important and common matrices for clinical chemistry and proteomic analyses. Data-independent acquisition (DIA) mass spectrometry has enabled the simultaneous quantitative analysis of hundreds of proteins in plasma samples in support population and disease studies. Depletion of the highest abundant proteins is a common tool to increase plasma proteome coverage, but this strategy can result in the nonspecific depletion of protein subsets with which proteins targeted for depletion interact, adversely affecting their analysis. Our work using an antibody-based depletion column revealed significant complementarity not only in the identification of the proteins derived from depleted and undepleted plasma, but importantly also in the extent to which different proteins can be reproducibly quantified in each fraction. We systematically defined four major quantitative parameters of increasing stringency in both the depleted plasma fraction and in undepleted plasma for 757 observed plasma proteins: Linearity cutoff r² > 0.8; lower limit of quantification (LLOQ); measurement range; limit of detection (LOD). We applied the results of our study to build a web-based tool, PlasmaPilot, that can serve as a protocol decision tree to determine whether the analysis of a specific protein warrants IgY14 mediated depletion.

Proteomic Analysis of the Early Development of the Phalaenopsis amabilis Flower Bud under Low Temperature Induction Using the iTRAQ/MRM Approach

Phalaenopsis amabilis, one of the most important plants in the international flower market due to its graceful shape and colorful flowers, is an orchid that undergoes vernalization and requires low-temperature treatment for flowering. There have been few reports on the proteomics of the development of flower buds. In this study, isobaric tags for relative and absolute quantification (iTRAQ) were used to identify 5064 differentially expressed proteins in P. amabilis under low-temperature treatment; of these, 42 were associated with early floral induction, and 18 were verified by mass spectrometry multi-reaction monitoring (MRM). The data are available via ProteomeXchange under identifier PXD013908. Among the proteins associated with the vernalization pathway, PEQU_11434 (glycine-rich RNA-binding protein GRP1A-like) and PEQU_19304 (FT, VRN3 homolog) were verified by MRM, and some other important proteins related to vernalization and photoperiod pathway that were detected by iTRAQ but not successfully verified by MRM, such as PEQU_11045 (UDP-N-acetylglucosamine diphosphorylase), phytochromes A (PEQU_13449, PEQU_35378), B (PEQU_09249), and C (PEQU_41401). Our data revealed a regulation network of the early development of flower buds in P. amabilis under low temperature induction.

USP16 counteracts mono-ubiquitination of RPS27a and promotes maturation of the 40S ribosomal subunit

Establishment of translational competence represents a decisive cytoplasmic step in the biogenesis of 40S ribosomal subunits. This involves final 18S rRNA processing and release of residual biogenesis factors, including the protein kinase RIOK1. To identify novel proteins promoting the final maturation of human 40S subunits, we characterized pre-ribosomal subunits trapped on RIOK1 by mass spectrometry, and identified the deubiquitinase USP16 among the captured factors. We demonstrate that USP16 constitutes a component of late cytoplasmic pre-40S subunits that promotes the removal of ubiquitin from an internal lysine of ribosomal protein RPS27a/eS31. USP16 deletion leads to late 40S subunit maturation defects, manifesting in incomplete processing of 18S rRNA and retarded recycling of late-acting ribosome biogenesis factors, revealing an unexpected contribution of USP16 to the ultimate step of 40S synthesis. Finally, ubiquitination of RPS27a appears to depend on active translation, pointing at a potential connection between 40S maturation and protein synthesis.

A protocol for studying structural dynamics of proteins by quantitative crosslinking mass spectrometry and data-independent acquisition

Quantitative crosslinking mass spectrometry (QCLMS) reveals structural details of protein conformations in solution. QCLMS can benefit from data-independent acquisition (DIA), which maximises accuracy, reproducibility and throughput of the approach. This DIA-QCLMS protocol comprises of three main sections: sample preparation, spectral library generation and quantitation. The DIA-QCLMS workflow supports isotope-labelling as well as label-free quantitation strategies, uses xiSEARCH for crosslink identification, and xiDIA-Library to create a spectral library for a peptide-centric quantitative approach. We integrated Spectronaut, a leading quantitation software, to analyse DIA data. Spectronaut supports DIA-QCLMS data to quantify crosslinks. It can be used to reveal the structural dynamics of proteins and protein complexes, even against a complex background. In combination with photoactivatable crosslinkers (photo-DIA-QCLMS), the workflow can increase data density and better capture protein dynamics due to short reaction times. Additionally, this can reveal conformational changes caused by environmental influences that would otherwise affect crosslinking itself, such as changing pH conditions. SIGNIFICANCE: This protocol is an detailed step-by-step description on how to implement our previously published DIA-QCLMS workflow (Müller et al. Mol Cell Proteomics. 2019 Apr;18(4):786-795). It includes sample preparation for QCLMS, Optimization of DIA strategies, implementation of the Spectronaut software and required python scripts and guideline on how to analyse quantitative crosslinking data. The DIA-QCLMS workflow widen the scope for a range of new crosslinking applications and this step-by-step protocol enhances the accessibility to a broad scientific user base.

Target prediction and validation of microRNAs expressed from FSHR and aromatase genes in human ovarian granulosa cells

MicroRNAs (miRNAs) are known post-transcriptional regulators of various biological processes including ovarian follicle development. We have previously identified miRNAs from human pre-ovulatory ovarian granulosa cells that are expressed from the intronic regions of two key genes in normal follicular development: FSH receptor (FSHR) and CYP19A1, the latter encoding the aromatase enzyme. The present study aims to identify the target genes regulated by these miRNAs: hsa-miR-548ba and hsa-miR-7973, respectively. The miRNAs of interest were transfected into KGN cell line and the gene expression changes were analyzed by Affymetrix microarray. Potential miRNA-regulated genes were further filtered by bioinformatic target prediction algorithms and validated for direct miRNA:mRNA binding by luciferase reporter assay. LIFR, PTEN, NEO1 and SP110 were confirmed as targets for hsa-miR-548ba. Hsa-miR-7973 target genes ADAM19, PXDN and FMNL3 also passed all verification steps. Additionally, the expression pattern of the miRNAs was studied in human primary cumulus granulosa cell culture in relation to the expression of their host genes and FSH stimulation. Based on our findings we propose the involvement of hsa-miR-548ba in the regulation of follicle growth and activation via LIFR and PTEN. Hsa-miR-7973 may be implicated in the modulation of extracellular matrix and cell-cell interactions by regulating the expression of its identified targets.

In silico spectral libraries by deep learning facilitate data-independent acquisition proteomics

Data-independent acquisition (DIA) is an emerging technology for quantitative proteomic analysis of large cohorts of samples. However, sample-specific spectral libraries built by data-dependent acquisition (DDA) experiments are required prior to DIA analysis, which is time-consuming and limits the identification/quantification by DIA to the peptides identified by DDA. Herein, we propose DeepDIA, a deep learning-based approach to generate in silico spectral libraries for DIA analysis. We demonstrate that the quality of in silico libraries predicted by instrument-specific models using DeepDIA is comparable to that of experimental libraries, and outperforms libraries generated by global models. With peptide detectability prediction, in silico libraries can be built directly from protein sequence databases. We further illustrate that DeepDIA can break through the limitation of DDA on peptide/protein detection, and enhance DIA analysis on human serum samples compared to the state-of-the-art protocol using a DDA library. We expect this work expanding the toolbox for DIA proteomics.

Data-independent acquisition (DIA) is an emerging technology in proteomics but it typically relies on spectral libraries built by data-dependent acquisition (DDA). Here, the authors use deep learning to generate in silico spectral libraries directly from protein sequences that enable more comprehensive DIA experiments than DDA-based libraries.

The GTPase Nog1 co-ordinates the assembly, maturation and quality control of distant ribosomal functional centers

Eukaryotic ribosome precursors acquire translation competence in the cytoplasm through stepwise release of bound assembly factors, and proofreading of their functional centers. In case of the pre-60S, these steps include removal of placeholders Rlp24, Arx1 and Mrt4 that prevent premature loading of the ribosomal protein eL24, the protein-folding machinery at the polypeptide exit tunnel (PET), and the ribosomal stalk, respectively. Here, we reveal that sequential ATPase and GTPase activities license release factors Rei1 and Yvh1 to trigger Arx1 and Mrt4 removal. Drg1-ATPase activity removes Rlp24 from the GTPase Nog1 on the pre-60S; consequently, the C-terminal tail of Nog1 is extracted from the PET. These events enable Rei1 to probe PET integrity and catalyze Arx1 release. Concomitantly, Nog1 eviction from the pre-60S permits peptidyl transferase center maturation, and allows Yvh1 to mediate Mrt4 release for stalk assembly. Thus, Nog1 co-ordinates the assembly, maturation and quality control of distant functional centers during ribosome formation.

Uterine Fluid Proteins for Minimally Invasive Assessment of Endometrial Receptivity

CONTEXT

Clinically used endometrial (EM) receptivity assays are based on transcriptomic patterning of biopsies at midsecretory endometrium (MSE) to identify the possible displacement or disruption of window of implantation (WOI) in patients with recurrent implantation failure (RIF). However, biopsies are invasive and cannot be performed in the same cycle with in vitro fertilization embryo transfer, while uterine fluid (UF) analysis is considered minimally invasive and can immediately precede embryo transfer.

OBJECTIVE

To determine whether UF proteome can be used for WOI monitoring and whether it would highlight the etiology of RIF.

PATIENTS

Paired early secretory endometrial (ESE) and MSE UF samples from six fertile control women for discovery, and an additional 11 paired ESE/MSE samples from controls and 29 MSE samples from RIF patients for validation.

RESULTS

Using discovery mass spectrometry (MS) proteomics we detected 3158 proteins from secretory phase UF of which 367 undergo significant (q < 0.05) proteomic changes while transitioning from ESE to MSE. Forty-five proteins were further validated with targeted MS, and 21 were found to display similar levels between control ESE and RIF MSE, indicating displacement of the WOI. A panel of PGR, NNMT, SLC26A2 and LCN2 demonstrated specificity and sensitivity of 91.7% for distinguishing MSE from ESE samples. The same panel distinguished control MSE samples from RIF MSE with a 91.7% specificity and 96.6% sensitivity.

CONCLUSION

UF proteins can be used for estimating uterine receptivity with minimal invasiveness. Women with RIF appear to have altered MSE UF profiles that may contribute to their low IVF success rate.

Role of Era in assembly and homeostasis of the ribosomal small subunit

Assembly factors provide speed and directionality to the maturation process of the 30S subunit in bacteria. To gain a more precise understanding of how these proteins mediate 30S maturation, it is important to expand on studies of 30S assembly intermediates purified from bacterial strains lacking particular maturation factors. To reveal the role of the essential protein Era in the assembly of the 30S ribosomal subunit, we analyzed assembly intermediates that accumulated in Era-depleted Escherichia coli cells using quantitative mass spectrometry, high resolution cryo-electron microscopy and in-cell footprinting. Our combined approach allowed for visualization of the small subunit as it assembled and revealed that with the exception of key helices in the platform domain, all other 16S rRNA domains fold even in the absence of Era. Notably, the maturing particles did not stall while waiting for the platform domain to mature and instead re-routed their folding pathway to enable concerted maturation of other structural motifs spanning multiple rRNA domains. We also found that binding of Era to the mature 30S subunit destabilized helix 44 and the decoding center preventing binding of YjeQ, another assembly factor. This work establishes Era’s role in ribosome assembly and suggests new roles in maintaining ribosome homeostasis.

Mass spectrometric approaches for profiling protein folding and stability

Protein stability reports on protein homeostasis, function, and binding interactions, such as to other proteins, metabolites and drugs. As such, there is a pressing need for technologies that can report on protein stability. The ideal technique could be applied in vitro or in vivo systems, proteome-wide, independently of matrix, under native conditions, with residue-level resolution, and on protein at endogenous levels. Mass spectrometry has rapidly become a preferred technology for identifying and quantifying proteins. As such, it has been increasingly incorporated into methodologies for interrogating protein stability and folding. Although no single technology can satisfy all desired applications, several emerging approaches have shown outstanding success at providing biological insight into the stability of the proteome. This chapter outlines some of these recent emerging technologies.

Attenuation of Equine Lentivirus Alters Mitochondrial Protein Expression Profile from Inflammation to Apoptosis

Equine infectious anemia virus (EIAV) is an equine lentivirus similar to HIV-1, targets host immune cells, and causes a life-long infection in horses. The Chinese live EIAV vaccine is attenuated from long-term passaging of a highly virulent strain in vitro The parent pathogenic strain (EIAV_DLV34) induces a host inflammatory storm to cause severe pathological injury of animals. However, the vaccine strain (EIAV_DLV121) induces a high level of apoptosis to eliminate infected cells. To investigate how these processes are regulated, we performed a comparative proteomics analysis and functional study in equine monocyte-derived macrophages (eMDMs) and found that the divergent mitochondrial protein expression profiles caused by EIAV strains with different virulence led to disparate mitochondrial function, morphology, and metabolism. This in turn promoted the distinct transformation of macrophage inflammatory polarization and intrinsic apoptosis. In EIAV_DLV34-infected cells, a high level of glycolysis and increased mitochondrial fragmentation were induced, resulting in the M1-polarized proinflammatory-type transformation of macrophages and the subsequent production of a strong inflammatory response. Following infection with EIAV_DLV121, the infected cells were transformed into M2-polarized anti-inflammatory macrophages by inhibition of glycolysis. In this case, a decrease in the mitochondrial membrane potential and impairment of the electron transport chain led to increased levels of apoptosis and reactive oxygen species. These results correlated with viral pathogenicity loss and may help provide an understanding of the key mechanism of lentiviral attenuation.IMPORTANCE Following viral infection, the working pattern and function of the cell can be transformed through the impact on mitochondria. It still unknown how the mitochondrial response changes in cells infected with viruses in the process of virulence attenuation. EIAV_DLV121 is the only effective lentiviral vaccine for large-scale use in the world. EIAV_DLV34 is the parent pathogenic strain. Unlike EIAV_DLV34-induced inflammation storms, EIAV_DLV121 can induce high levels of apoptosis. For the first time, we found that, after the mitochondrial protein expression profile is altered, EIAV_DLV34-infected cells are transformed into M1-polarized-type macrophages and cause inflammatory injury and that the intrinsic apoptosis pathway is activated in EIAV_DLV121-infected cells. These studies shed light on how the mitochondrial protein expression profile changes between cells infected by pathogenic lentivirus strains and cells infected by attenuated lentivirus strains to drive different cellular responses, especially from inflammation to apoptosis.

Prediction of LC-MS/MS Properties of Peptides from Sequence by Deep Learning

Deep learning models for prediction of three key LC-MS/MS properties from peptide sequences were developed. The LC-MS/MS properties or behaviors are indexed retention times (iRT), MS1 or survey scan charge state distributions, and sequence ion intensities of HCD spectra. A common core deep supervised learning architecture, bidirectional long-short term memory (LSTM) recurrent neural networks was used to construct the three prediction models. Two featurization schemes were proposed and demonstrated to allow for efficient encoding of modifications. The iRT and charge state distribution models were trained with on order of 105 data points each. An HCD sequence ion prediction model was trained with 2 × 106 experimental spectra. The iRT prediction model and HCD sequence ion prediction model provide improved accuracies over the start-of-the-art models available in literature. The MS1 charge state distribution prediction model offers excellent performance. The prediction models can be used to enhance peptide identification and quantification in data-dependent acquisition and data-independent acquisition (DIA) experiments as well as to assist MRM (multiple reaction monitoring) and PRM (parallel reaction monitoring) experiment design.

Targeted Quantitative Proteomic Approach for High-Throughput Quantitative Profiling of Small GTPases in Brain Tissues of Alzheimer's Disease Patients

Neurodegenerative disorders, including Alzheimer's disease (AD), are prevalent among the elderly. Small GTPases of the Ras superfamily are essential regulators of intracellular trafficking and signal transduction. In this study, we develop a targeted quantification method for small GTPase proteins, where the method involves scheduled multiple-reaction monitoring analysis and the use of synthetic stable isotope-labeled peptides as internal standards or surrogate standards. We further applied this method to examine the altered expression of small GTPase proteins in post-mortem frontal cortex tissues from AD patients with different degrees of disease severity. We were able to achieve sensitive and reproducible quantifications of 80 small GTPases in brain tissue samples from 15 patients. Our results revealed substantial up-regulations of several synaptic GTPases, i.e., RAB3A/C, RAB4A/B, and RAB27B, in tissues from patients with higher degrees of AD pathology, suggesting that aberrant synaptic trafficking may modulate the progression of AD. The method should be generally applicable for high-throughput targeted quantification of small GTPase proteins in other tissue and cellular samples.

Bioinformatics approaches for improving seminal plasma proteome analysis

Reproduction efficiency of male animals is one of the key factors influencing the sustainability of livestock. Mass spectrometry (MS) based proteomics has become an important tool for studying seminal plasma proteomes. In this review, we summarize bioinformatics analysis strategies for current proteomics approaches, for identifying novel biomarkers of reproductive robustness.

Enhancing cardiac glycolysis causes an increase in PDK4 content in response to short-term high-fat diet

The healthy heart has a dynamic capacity to respond and adapt to changes in nutrient availability. Metabolic inflexibility, such as occurs with diabetes, increases cardiac reliance on fatty acids to meet energetic demands, and this results in deleterious effects, including mitochondrial dysfunction, that contribute to pathophysiology. Enhancing glucose usage may mitigate metabolic inflexibility and be advantageous under such conditions. Here, we sought to identify how mitochondrial function and cardiac metabolism are affected in a transgenic mouse model of enhanced cardiac glycolysis (Glyco^Hi) basally and following a short-term (7-day) high-fat diet (HFD). Glyco^Hi mice constitutively express an active form of phosphofructokinase-2, resulting in elevated levels of the PFK-1 allosteric activator fructose 2,6-bisphosphate. We report that basally Glyco^Hi mitochondria exhibit augmented pyruvate-supported respiration relative to fatty acids. Nevertheless, both WT and Glyco^Hi mitochondria had a similar shift toward increased rates of fatty acid-supported respiration following HFD. Metabolic profiling by GC-MS revealed distinct features based on both genotype and diet, with a unique increase in branched-chain amino acids in the Glyco^Hi HFD group. Targeted quantitative proteomics analysis also supported both genotype- and diet-dependent changes in protein expression and uncovered an enhanced expression of pyruvate dehydrogenase kinase 4 (PDK4) in the Glyco^Hi HFD group. These results support a newly identified mechanism whereby the levels of fructose 2,6-bisphosphate promote mitochondrial PDK4 levels and identify a secondary adaptive response that prevents excessive mitochondrial pyruvate oxidation when glycolysis is sustained after a high-fat dietary challenge.

High-throughput proteomic analysis of FFPE tissue samples facilitates tumor stratification

Formalin‐fixed, paraffin‐embedded (FFPE), biobanked tissue samples offer an invaluable resource for clinical and biomarker research. Here, we developed a pressure cycling technology (PCT)‐SWATH mass spectrometry workflow to analyze FFPE tissue proteomes and applied it to the stratification of prostate cancer (PCa) and diffuse large B‐cell lymphoma (DLBCL) samples. We show that the proteome patterns of FFPE PCa tissue samples and their analogous fresh‐frozen (FF) counterparts have a high degree of similarity and we confirmed multiple proteins consistently regulated in PCa tissues in an independent sample cohort. We further demonstrate temporal stability of proteome patterns from FFPE samples that were stored between 1 and 15 years in a biobank and show a high degree of the proteome pattern similarity between two types of histological regions in small FFPE samples, that is, punched tissue biopsies and thin tissue sections of micrometer thickness, despite the existence of a certain degree of biological variations. Applying the method to two independent DLBCL cohorts, we identified myeloperoxidase, a peroxidase enzyme, as a novel prognostic marker. In summary, this study presents a robust proteomic method to analyze bulk and biopsy FFPE tissues and reports the first systematic comparison of proteome maps generated from FFPE and FF samples. Our data demonstrate the practicality and superiority of FFPE over FF samples for proteome in biomarker discovery. Promising biomarker candidates for PCa and DLBCL have been discovered.

High-Throughput Targeted Quantitative Analysis of the Interaction between HSP90 and Kinases

Kinases, which function in numerous cell signaling processes, are among the best characterized groups of client proteins for the 90-kDa heat shock protein (HSP90), a molecular chaperone that suppresses the aggregation and maintains the proper folding of its substrate proteins (i.e., clients). No high-throughput proteomic method, however, has been developed for the characterizations of the interactions between HSP90 and the human kinome. Herein, by employing a parallel-reaction monitoring (PRM)-based targeted proteomic method, we found that 99 out of the 249 detected kinase proteins display diminished expression in cultured human cells upon treatment with ganetespib, a small-molecule HSP90 inhibitor. PRM analysis of kinase proteins in the affinity pull-down samples showed that 86 out of the 120 detected kinases are enriched from the CRISPR-engineered cells where a tandem affinity tag was conjugated with the C-terminus of endogenous HSP90β protein over the parental cells. Together, our results from the two complementary quantitative proteomic experiments offer systematic characterizations about the HSP90-kinase interactions at the entire proteome scale and reveal extensive interactions between HSP90 and kinase proteins in human cells.

Intracerebroventricular enzyme replacement therapy with β-galactosidase reverses brain pathologies due to GM1 gangliosidosis in mice

Autosomal recessive mutations in the galactosidase β1 (GLB1) gene cause lysosomal β-gal deficiency, resulting in accumulation of galactose-containing substrates and onset of the progressive and fatal neurodegenerative lysosomal storage disease, GM1 gangliosidosis. Here, an enzyme replacement therapy (ERT) approach in fibroblasts from GM1 gangliosidosis patients with recombinant human β-gal (rhβ-gal) produced in Chinese hamster ovary cells enabled direct and precise rhβ-gal delivery to acidified lysosomes. A single, low dose (3 nm) of rhβ-gal was sufficient for normalizing β-gal activity and mediating substrate clearance for several weeks. We found that rhβ-gal uptake by the fibroblasts is dose-dependent and saturable and can be competitively inhibited by mannose 6-phosphate, suggesting cation-independent, mannose 6-phosphate receptor–mediated endocytosis from the cell surface. A single intracerebroventricularly (ICV) administered dose of rhβ-gal (100 μg) resulted in broad bilateral biodistribution of rhβ-gal to critical regions of pathology in a mouse model of GM1 gangliosidosis. Weekly ICV dosing of rhβ-gal for 8 weeks substantially reduced brain levels of ganglioside and oligosaccharide substrates and reversed well-established secondary neuropathology. Of note, unlike with the ERT approach, chronic lentivirus-mediated GLB1 overexpression in the GM1 gangliosidosis patient fibroblasts caused accumulation of a prelysosomal pool of β-gal, resulting in activation of the unfolded protein response and endoplasmic reticulum stress. This outcome was unsurprising in light of our in vitro biophysical findings for rhβ-gal, which include pH-dependent and concentration-dependent stability and dynamic self-association. Collectively, our results highlight that ICV-ERT is an effective therapeutic intervention for managing GM1 gangliosidosis potentially more safely than with gene therapy approaches.

hSWATH: Unlocking SWATH's Full Potential for an Untargeted Histone Perspective

Mass spectrometry (MS) has become the technique of choice for large-scale analysis of histone post-translational modifications (hPTMs) and their combinatorial patterns, especially in untargeted settings where novel discovery-driven hypotheses are being generated. However, MS-based histone analysis requires a distinct sample preparation, acquisition, and data analysis workflow when compared to traditional MS-based approaches. To this end, sequential window acquisition of all theoretical fragment ion spectra (SWATH) has great potential, as it allows for untargeted accurate identification and quantification of hPTMs. Here, we present a complete SWATH workflow specifically adapted for the untargeted study of histones (hSWATH). We assess its validity on a technical dataset of time-lapse deacetylation of a commercial histone extract using HDAC1, which contains a ground truth, i.e., acetylated substrate peptides reduce in intensity. We successfully apply this workflow in a biological setting and subsequently investigate the differential response to HDAC inhibition in different breast cancer cell lines.

What is Normalization? The Strategies Employed in Top-Down and Bottom-Up Proteome Analysis Workflows

The accurate quantification of changes in the abundance of proteins is one of the main applications of proteomics. The maintenance of accuracy can be affected by bias and error that can occur at many points in the experimental process, and normalization strategies are crucial to attempt to overcome this bias and return the sample to its regular biological condition, or normal state. Much work has been published on performing normalization on data post-acquisition with many algorithms and statistical processes available. However, there are many other sources of bias that can occur during experimental design and sample handling that are currently unaddressed. This article aims to cast light on the potential sources of bias and where normalization could be applied to return the sample to its normal state. Throughout we suggest solutions where possible but, in some cases, solutions are not available. Thus, we see this article as a starting point for discussion of the definition of and the issues surrounding the concept of normalization as it applies to the proteomic analysis of biological samples. Specifically, we discuss a wide range of different normalization techniques that can occur at each stage of the sample preparation and analysis process.

The SysteMHC Atlas project

Mass spectrometry (MS)-based immunopeptidomics investigates the repertoire of peptides presented at the cell surface by major histocompatibility complex (MHC) molecules. The broad clinical relevance of MHC-associated peptides, e.g. in precision medicine, provides a strong rationale for the large-scale generation of immunopeptidomic datasets and recent developments in MS-based peptide analysis technologies now support the generation of the required data. Importantly, the availability of diverse immunopeptidomic datasets has resulted in an increasing need to standardize, store and exchange this type of data to enable better collaborations among researchers, to advance the field more efficiently and to establish quality measures required for the meaningful comparison of datasets. Here we present the SysteMHC Atlas (https://systemhcatlas.org), a public database that aims at collecting, organizing, sharing, visualizing and exploring immunopeptidomic data generated by MS. The Atlas includes raw mass spectrometer output files collected from several laboratories around the globe, a catalog of context-specific datasets of MHC class I and class II peptides, standardized MHC allele-specific peptide spectral libraries consisting of consensus spectra calculated from repeat measurements of the same peptide sequence, and links to other proteomics and immunology databases. The SysteMHC Atlas project was created and will be further expanded using a uniform and open computational pipeline that controls the quality of peptide identifications and peptide annotations. Thus, the SysteMHC Atlas disseminates quality controlled immunopeptidomic information to the public domain and serves as a community resource toward the generation of a high-quality comprehensive map of the human immunopeptidome and the support of consistent measurement of immunopeptidomic sample cohorts.

Mapping the Tooth Enamel Proteome and Amelogenin Phosphorylation Onto Mineralizing Porcine Tooth Crowns

Tooth enamel forms in an ephemeral protein matrix where changes in protein abundance, composition and posttranslational modifications are critical to achieve healthy enamel properties. Amelogenin (AMELX) with its splice variants is the most abundant enamel matrix protein, with only one known phosphorylation site at serine 16 shown in vitro to be critical for regulating mineralization. The phosphorylated form of AMELX stabilizes amorphous calcium phosphate, while crystalline hydroxyapatite forms in the presence of the unphosphorylated protein. While AMELX regulates mineral transitions over space and time, it is unknown whether and when un-phosphorylated amelogenin occurs during enamel mineralization. This study aims to reveal the spatiotemporal distribution of the cleavage products of the most abundant AMLEX splice variants including the full length P173, the shorter leucine-rich amelogenin protein (LRAP), and the exon 4-containing P190 in forming enamel, all within the context of the changing enamel matrix proteome during mineralization. We microsampled permanent pig molars, capturing known stages of enamel formation from both crown surface and inner enamel. Nano-LC-MS/MS proteomic analyses after tryptic digestion rendered more than 500 unique protein identifications in enamel, dentin, and bone. We mapped collagens, keratins, and proteolytic enzymes (CTSL, MMP2, MMP10) and determined distributions of P173, LRAP, and P190 products, the enamel proteins enamelin (ENAM) and ameloblastin (AMBN), and matrix-metalloprotease-20 (MMP20) and kallikrein-4 (KLK4). All enamel proteins and KLK4 were near-exclusive to enamel and in excellent agreement with published abundance levels. Phosphorylated P173 and LRAP products decreased in abundance from recently deposited matrix toward older enamel, mirrored by increasing abundances of testicular acid phosphatase (ACPT). Our results showed that hierarchical clustering analysis of secretory enamel links closely matching distributions of unphosphorylated P173 and LRAP products with ACPT and non-traditional amelogenesis proteins, many associated with enamel defects. We report higher protein diversity than previously published and Gene Ontology (GO)-defined protein functions related to the regulation of mineral formation in secretory enamel (e.g., casein α-S1, CSN1S1), immune response in erupted enamel (e.g., peptidoglycan recognition protein, PGRP), and phosphorylation. This study presents a novel approach to characterize and study functional relationships through spatiotemporal mapping of the ephemeral extracellular matrix proteome.

Targeted Quantitative Proteomics Revealed Arsenite-induced Proteasomal Degradation of RhoB in Fibroblast Cells

Arsenic is a toxicant widely present in the environment. Previous epidemiological and animal studies support that arsenic exposure is associated with elevated incidences of lung and skin cancers. Therefore, it is important to understand the molecular mechanisms through which arsenite initiates malignant transformation of lung and skin tissues. Ras superfamily of small GTPases assumes a crucial role in many cellular processes including transcription, protein synthesis, and trafficking. In addition, small GTPase signaling is known to be altered in many types of cancer. By employing a multiple-reaction monitoring (MRM)-based targeted proteomic method, we found that the protein level of RhoB was substantially decreased in IMR90 human lung fibroblast cells upon a 12-h exposure to 5 μM NaAsO₂. In addition, the protein level of ectopically expressed RhoB was found to decline in a dose-dependent manner upon arsenite exposure in HEK293T, HeLa, and GM00637 cells as well as that of endogenous RhoB protein in IMR90 cells. Moreover, the arsenite-elicited down-regulation of RhoB was found to arise from enhanced proteasomal degradation. Taken together, we demonstrated, for the first time, that exposure to arsenite could attenuate the protein expression of RhoB through proteasomal degradation.

Parallel-Reaction-Monitoring-Based Proteome-Wide Profiling of Differential Kinase Protein Expression during Prostate Cancer Metastasis in Vitro

Prostate cancer is the most common type of cancer in men, and kinases are heavily pursued as drug targets for anticancer therapy. In this study, we applied our recently reported parallel-reaction-monitoring (PRM)-based targeted proteomic method to examine the reprogramming of the human kinome associated with bone metastasis of prostate cancer in vitro. The method displayed superior sensitivity over the shotgun-proteomic approach, and it facilitated the quantification of the relative expression of 276 kinase proteins in a pair of bone metastatic prostate cancer cells. Among the differentially expressed kinases, mitogen-activated protein kinase kinase kinase kinase 4 (MAP4K4) stimulates the migration and invasion of cultured prostate cancer cells, partially by modulating the activity of secreted matrix metalloproteinases 9 (MMP-9). We also found that the upregulation of MAP4K4 in metastatic prostate cancer cells is driven by the MYC proto-oncogene. Cumulatively, we identify MAP4K4 as a potential promoter for prostate cancer metastasis in vitro.

Sensitive Quantitative Proteomics of Human Hematopoietic Stem and Progenitor Cells by Data-independent Acquisition Mass Spectrometry

Physiological processes in multicellular organisms depend on the function and interactions of specialized cell types operating in context. Some of these cell types are rare and thus obtainable only in minute quantities. For example, tissue-specific stem and progenitor cells are numerically scarce, but functionally highly relevant, and fulfill critical roles in development, tissue maintenance, and disease. Whereas low numbers of cells are routinely analyzed by genomics and transcriptomics, corresponding proteomic analyses have so far not been possible due to methodological limitations. Here we describe a sensitive and robust quantitative technique based on data-independent acquisition mass spectrometry. We quantified the proteome of sets of 25,000 human hematopoietic stem/multipotent progenitor cells (HSC/MPP) and three committed progenitor cell subpopulations of the myeloid differentiation pathway (common myeloid progenitors, megakaryocyte-erythrocyte progenitors, and granulocyte-macrophage progenitors), isolated by fluorescence-activated cell sorting from five healthy donors. On average, 5,851 protein groups were identified per sample. A subset of 4,131 stringently filtered protein groups was quantitatively compared across the 20 samples, defining unique signatures for each subpopulation. A comparison of proteomic and transcriptomic profiles indicated HSC/MPP-specific divergent regulation of biochemical functions such as telomerase maintenance and quiescence-inducing enzymes, including isocitrate dehydrogenases. These are essential for maintaining stemness and were detected at proteome, but not transcriptome, level. The method is equally applicable to almost any rare cell type, including healthy and cancer stem cells or physiologically and pathologically infiltrating cell populations. It thus provides essential new information toward the detailed biochemical understanding of cell development and functionality in health and disease.

DART-ID increases single-cell proteome coverage

Analysis by liquid chromatography and tandem mass spectrometry (LC-MS/MS) can identify and quantify thousands of proteins in microgram-level samples, such as those comprised of thousands of cells. This process, however, remains challenging for smaller samples, such as the proteomes of single mammalian cells, because reduced protein levels reduce the number of confidently sequenced peptides. To alleviate this reduction, we developed Data-driven Alignment of Retention Times for IDentification (DART-ID). DART-ID implements principled Bayesian frameworks for global retention time (RT) alignment and for incorporating RT estimates towards improved confidence estimates of peptide-spectrum-matches. When applied to bulk or to single-cell samples, DART-ID increased the number of data points by 30-50% at 1% FDR, and thus decreased missing data. Benchmarks indicate excellent quantification of peptides upgraded by DART-ID and support their utility for quantitative analysis, such as identifying cell types and cell-type specific proteins. The additional datapoints provided by DART-ID boost the statistical power and double the number of proteins identified as differentially abundant in monocytes and T-cells. DART-ID can be applied to diverse experimental designs and is freely available at http://dart-id.slavovlab.net.

Abundance of bacterial Type VI secretion system components measured by targeted proteomics

The Type VI secretion system (T6SS) is important for bacterial competition as well as virulence in many Gram-negative bacteria and its dynamics and regulation varies significantly between species. To gain insights into the mechanisms regulating T6SS assembly, we apply targeted proteomics to determine the abundance of the key T6SS components in Vibrio cholerae, Pseudomonas aeruginosa and Acinetobacter baylyi. We show that while there are species specific exceptions, the abundance of most components is similar in all three bacteria and ranges from less than hundred to tens of thousands of copies per cell. The comparison of T6SS dynamics and protein abundance in V. cholerae grown under various conditions suggests that the critical component TssE and the secreted protein VasX are unstable and this diminishes T6SS assembly when protein synthesis is limited. Our quantitative analysis opens possibilities to build realistic models of T6SS assembly and to identify principles of T6SS regulation in various species.

Type VI secretion systems (T6SS) are important for bacterial interaction, competition and virulence, but the abundance and assembly of their components is still not well understood. Here, the authors apply targeted proteomics to measure the abundance of T6SS components across different species and conditions.

Targeted Quantitative Proteomic Approach for Probing Altered Protein Expression of Small GTPases Associated with Colorectal Cancer Metastasis

Genes encoding the small GTPases of the Ras superfamily are among the most frequently mutated or dysregulated in human cancer. No systematic studies, however, have yet been conducted for assessing the implications of small GTPases in the metastatic transformation of colorectal cancer (CRC). By utilizing a recently established high-throughput multiple-reaction monitoring (MRM)-based workflow together with stable isotope labeling by amino acids in cell culture (SILAC), we investigated comprehensively the relative expression of the small GTPase proteome in a pair of matched primary/metastatic CRC cell lines (SW480/SW620). Among the 83 quantified small GTPases, 25 exhibited at least a 1.5-fold difference in protein expression in SW480 and SW620 cells. In particular, SAR1B protein was found to be substantially down-regulated in SW620 relative to SW480 cells. In addition, bioinformatic analyses revealed that diminished SAR1B mRNA expression is significantly associated with higher CRC stages and unfavorable patient prognosis, in support of a potential role of SAR1B in suppressing CRC metastasis. In addition, diminished SAR1B expression could stimulate epithelial-mesenchymal transition (EMT), thereby promoting motility and in vitro metastasis of SW480 cells. In summary, we profiled systematically, by employing an MRM-based targeted proteomic method, the differential expression of small GTPase proteins in a matched pair of primary/metastatic CRC cell lines. Our results revealed the potential roles of SAR1B in suppressing CRC metastasis and in the prognosis of CRC patients.

Quantitative Interrogation of the Human Kinome Perturbed by Two BRAF Inhibitors

Oncogenic BRAF mutations contribute to the development of a number of cancers, and small-molecule BRAF inhibitors have been approved by the Food and Drug Administration (FDA) for anticancer therapy. In this study, we employed two targeted quantitative proteomics approaches for monitoring separately the alterations in protein expression and ATP binding affinities of kinases in cultured human melanoma cells elicited by two FDA-approved small-molecule BRAF inhibitors, dabrafenib and vemurafenib. Our results showed that treatment with the two inhibitors led to markedly different reprograming of the human kinome. Furthermore, we confirmed that vemurafenib could compromise the ATP binding capacity of MAP2K5 in vitro and inhibit its kinase activity in cells. Together, our targeted quantitative proteomic methods revealed profound changes in expression levels of kinase proteins in cultured melanoma cells upon treatment with clinically used BRAF inhibitors and led to the discovery of novel putative target kinases for these inhibitors.

Mapping Citrullinated Sites in Multiple Organs of Mice Using Hypercitrullinated Library

Protein citrullination (or deimination), an irreversible post-translational modification, has been implicated in several physiological and pathological processes, including gene expression regulation, apoptosis, rheumatoid arthritis, and Alzheimer's disease. Several research studies have been carried out on citrullination under many conditions. However, until now, challenges in sample preparation and data analysis have made it difficult to confidently identify a citrullinated protein and assign the citrullinated site. To overcome these limitations, we generated a mouse hyper-citrullinated spectral library and set up coordinates to confidently identify and validate citrullinated sites. Using this workflow, we detect a four-fold increase in citrullinated proteome coverage across six mouse organs compared with the current state-of-the art techniques. Our data reveal that the subcellular distribution of citrullinated proteins is tissue-type-dependent and that citrullinated targets are involved in fundamental physiological processes, including the metabolic process. These data represent the first report of a hyper-citrullinated library for the mouse and serve as a central resource for exploring the role of citrullination in this organism.

Targeted Quantitative Kinome Analysis Identifies PRPS2 as a Promoter for Colorectal Cancer Metastasis

Kinases are among the most important families of enzymes involved in cell signaling. In this study, we employed a recently developed parallel-reaction monitoring (PRM)-based targeted proteomic method to examine the reprogramming of the human kinome during colorectal cancer (CRC) metastasis. We were able to quantify the relative expression of 299 kinase proteins in a pair of matched primary/metastatic CRC cell lines. We also found that, among the differentially expressed kinases, phosphoribosyl pyrophosphate synthetase 2 (PRPS2) promotes the migration and invasion of cultured CRC cells through regulating the activity of matrix metalloproteinase 9 (MMP-9) and the expression of E-cadherin. Moreover, we found that the up-regulation of PRPS2 in metastatic CRC cells could be induced by the MYC proto-oncogene. Together, our unbiased kinome profiling approach led to the identification, for the first time, of PRPS2 as a promoter for CRC metastasis.

DIAlignR Provides Precise Retention Time Alignment Across Distant Runs in DIA and Targeted Proteomics

Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectra (SWATH-MS) is widely used for proteomics analysis given its high throughput and reproducibility, but ensuring consistent quantification of analytes across large-scale studies of heterogeneous samples such as human plasma remains challenging. Heterogeneity in large-scale studies can be caused by large time intervals between data acquisition, acquisition by different operators or instruments, and intermittent repair or replacement of parts, such as the liquid chromatography column, all of which affect retention time (RT) reproducibility and, successively, performance of SWATH-MS data analysis. Here, we present a novel algorithm for RT alignment of SWATH-MS data based on direct alignment of raw MS2 chromatograms using a hybrid dynamic programming approach. The algorithm does not impose a chronological order of elution and allows for alignment of elution-order-swapped peaks. Furthermore, allowing RT mapping in a certain window around a coarse global fit makes it robust against noise. On a manually validated dataset, this strategy outperformed the current state-of-the-art approaches. In addition, on real-world clinical data, our approach outperformed global alignment methods by mapping 98% of peaks compared with 67% cumulatively. DIAlignR reduced alignment error up to 30-fold for extremely distant runs. The robustness of technical parameters used in this pairwise alignment strategy is also demonstrated. The source code is released under the BSD license at https://github.com/Roestlab/DIAlignR.

Imatinib-Induced Changes in Protein Expression and ATP-Binding Affinities of Kinases in Chronic Myelocytic Leukemia Cells

Kinases are crucial components in numerous cell signaling pathways. Aberrant expression and activation of protein kinases are known to be accompanied by many types of cancer, and more than 30 small-molecule kinase inhibitors have been approved by the Food and Drug Administration (FDA) for cancer chemotherapy. Biological and clinical applications of small-molecule kinase inhibitors require comprehensive characterizations about how these inhibitors modulate the protein expression and activities of kinases at the entire proteome scale. In this study, we developed a parallel-reaction monitoring (PRM)-based targeted proteomic method to monitor the alterations in protein expression of kinases in K-562 chronic myelocytic leukemia (CML) cells elicited by treatment with imatinib, an ABL kinase inhibitor approved by the FDA for CML treatment. By employing isotope-coded ATP affinity probes together with liquid chromatography-multiple-reaction monitoring (LC-MRM) analysis, we also examined the modulation of the ATP-binding affinities of kinases induced by imatinib treatment. The results revealed profound increases in protein expression levels of a large number of kinases in K-562 cells upon treatment with imatinib, which is accompanied by substantial decreases in ATP-binding capacities of many kinases. Apart from ABL kinases, we identified a number of other kinases whose ATP-binding affinities are markedly diminished upon imatinib treatment, including CHK1, a checkpoint kinase involved in DNA damage response signaling. Together, our targeted quantitative proteomic methods enabled, for the first time, dual assessments of small-molecule kinase inhibitor-induced changes in protein expression and ATP-binding affinities of kinases in live cells.

iTRAQ-based pharmacoproteomics reveals potential targets of berberine, a promising therapy for ulcerative colitis

Previous studies by us and others have indicated that berberine is a promising therapy for ulcerative colitis (UC). However, the mechanisms of UC and the therapeutic targets of berberine are poorly understood. iTRAQ-based proteomics was utilized to characterize the proteins and pathways associated with the development of colitis and its improvement after berberine treatment. By using a modified dextran sodium sulfate (DSS) colitis as the UC model, confirmed that berberine significantly attenuated clinical symptoms and colon shorting of the colitis mice. Proteomics identified 140 and 391 proteins that were differentially expressed in the colons of DSS- or DSS plus berberine-treated mice, respectively. Subsequent verification of 15 selected differentially expressed proteins (DEPs) by multiple reaction monitoring confirmed the reliability of the iTRAQ data. Further comparisons and bioinformatics analysis demonstrated that among the identified DEPs, 26, including Hist2h2be, Tubb3, and five immunoglobulins, were oppositely regulated by DSS and DSS plus berberine treatments. In addition, five commonly dysregulated pathways, including natural killer cell-mediated cytotoxicity and RRAR signaling were identified. Network analysis revealed that proteins involved in 7 and 11 pathways in DSS and DSS plus berberine treated mice, respectively, engaged in protein-protein interactions. Our study provides the first pharmacoproteomics profiling of colitis and its recovery after berberine treatment. The proteins, pathways and networks identified provide novel insights into the pathogenesis of colitis and the action mechanism of berberine, demonstrating their values for validation in human UC which could serve as targets for the development of novel therapies for UC.

A rapid methods development workflow for high-throughput quantitative proteomic applications

Recent improvements in the speed and sensitivity of liquid chromatography-mass spectrometry systems have driven significant progress toward system-wide characterization of the proteome of many species. These efforts create large proteomic datasets that provide insight into biological processes and identify diagnostic proteins whose abundance changes significantly under different experimental conditions. Yet, these system-wide experiments are typically the starting point for hypothesis-driven, follow-up experiments to elucidate the extent of the phenomenon or the utility of the diagnostic marker, wherein many samples must be analyzed. Transitioning from a few discovery experiments to quantitative analyses on hundreds of samples requires significant resources both to develop sensitive and specific methods as well as analyze them in a high-throughput manner. To aid these efforts, we developed a workflow using data acquired from discovery proteomic experiments, retention time prediction, and standard-flow chromatography to rapidly develop targeted proteomic assays. We demonstrated this workflow by developing MRM assays to quantify proteins of multiple metabolic pathways from multiple microbes under different experimental conditions. With this workflow, one can also target peptides in scheduled/dynamic acquisition methods from a shotgun proteomic dataset downloaded from online repositories, validate with appropriate control samples or standard peptides, and begin analyzing hundreds of samples in only a few minutes.

Generation of a zebrafish SWATH-MS spectral library to quantify 10,000 proteins

Sequential window acquisition of all theoretical mass spectra (SWATH-MS) requires a spectral library to extract quantitative measurements from the mass spectrometry data acquired in data-independent acquisition mode (DIA). Large combined spectral libraries containing SWATH assays have been generated for humans and several other organisms, but so far no publicly available library exists for measuring the proteome of zebrafish, a rapidly emerging model system in biomedical research. Here, we present a large zebrafish SWATH spectral library to measure the abundance of 104,185 proteotypic peptides from 10,405 proteins. The library includes proteins expressed in 9 different zebrafish tissues (brain, eye, heart, intestine, liver, muscle, ovary, spleen, and testis) and provides an important new resource to quantify 40% of the protein-coding zebrafish genes. We employ this resource to quantify the proteome across brain, muscle, and liver and characterize divergent expression levels of paralogous proteins in different tissues. Data are available via ProteomeXchange (PXD010876, PXD010869) and SWATHAtlas (PASS01237).

Targeted Proteomics Comes to the Benchside and the Bedside: Is it Ready for Us?

While mass spectrometry (MS)-based quantification of small molecules has been successfully used for decades, targeted MS has only recently been used by the proteomics community to investigate clinical questions such as biomarker verification and validation. Targeted MS holds the promise of a paradigm shift in the quantitative determination of proteins. Nevertheless, targeted quantitative proteomics requires improvisation in making sample processing, instruments, and data analysis more accessible. In the backdrop of the genomic era reaching its zenith, certain questions arise: is the proteomic era about to come? If we are at the beginning of a new future for protein quantification, are we prepared to incorporate targeted proteomics at the benchside for basic research and at the bedside for the good of patients? Here, an overview of the knowledge required to perform targeted proteomics as well as its applications is provided. A special emphasis is placed on upcoming areas such as peptidomics, proteoform research, and mass spectrometry imaging, where the utilization of targeted proteomics is expected to bring forth new avenues. The limitations associated with the acceptance of this technique for mainstream usage are also highlighted. Also see the video abstract here https://youtu.be/mieB47B8gZw.

Targeted Profiling of Heat Shock Proteome in Radioresistant Breast Cancer Cells

Breast cancer is the most commonly diagnosed cancer and the second leading cause of cancer death in women. Radioresistance remains one of the most critical barriers in radiation therapy for breast cancer. In this study, we employed a parallel-reaction monitoring (PRM)-based targeted proteomic method to examine the reprogramming of the heat shock proteome during the development of radioresistance in breast cancer. In particular, we investigated the differential expression of heat shock proteins (HSPs) in two pairs of matched parental/radioresistant breast cancer cell lines. We were able to quantify 43 and 42 HSPs in the MCF-7 and MDA-MB-231 pairs of cell lines, respectively. By analyzing the commonly altered proteins, we found that several members of the HSP70 and HSP40 subfamilies of HSPs exhibited substantially altered expression upon development of radioresistance. Moreover, the expression of HSPB8 is markedly elevated in the radioresistant lines relative to the parental MCF-7 and MDA-MB-231 cells. Together, our PRM-based targeted proteomics method revealed the reprogramming of the heat shock proteome during the development of radioresistance in breast cancer cells and offered potential targets for sensitizing breast cancer cells toward radiation therapy.

Identification of Hybrid Insulin Peptides (HIPs) in Mouse and Human Islets by Mass Spectrometry

We recently discovered hybrid insulin peptides (HIPs) as a novel class of post-translationally modified peptides in murine-derived beta cell tumors, and we demonstrated that these molecules are autoantigens in type 1 diabetes (T1D). A HIP consists of an insulin fragment linked to another secretory granule peptide via a peptide bond. We verified that autoreactive CD4 T cells in both mouse and human autoimmune diabetes recognize these modified peptides. Here, we use mass spectrometric analyses to confirm the presence of HIPs in both mouse and human pancreatic islets. We also present criteria for the confident identification of these peptides. This work supports the hypothesis that HIPs are autoantigens in human T1D and provides a foundation for future efforts to interrogate this previously unknown component of the beta cell proteome.

Development of a Highly Multiplexed SRM Assay for Biomarker Discovery in Formalin-Fixed Paraffin-Embedded Tissues

The search for novel and clinically relevant biomarkers still represents a major clinical challenge and mass-spectrometry-based technologies are essential tools to help in this process. In this application, we demonstrate how selected reaction monitoring (SRM) can be applied in a highly multiplexed way to analyze formalin-fixed paraffin-embedded (FFPE) tissues. Such an assay can be used to analyze numerous samples for narrowing down a list of potential biomarkers to the most relevant candidates. The use of FFPE tissues is of high relevance in this context as large sample collections linked with valuable clinical information are available in hospitals around the world. Here we describe in detail how we proceeded to develop such an assay for 200 proteins in breast tumor FFPE tissues. We cover the selection of suitable peptides, which are different in FFPE compared to fresh frozen tissues and show how we deliberately biased our assay toward proteins with a high probability of being measurable in human clinical samples.

Surpassing 10 000 identified and quantified proteins in a single run by optimizing current LC-MS instrumentation and data analysis strategy

Optimization of chromatography and data analysis resulted in more than 10 000 proteins in a single shot at a validated FDR of 1% (two-species test) and revealed deep insights into the testis cancer physiology.

Universal retention standard for peptide separations using various modes of high-performance liquid chromatography

Peptide retention standards are widely used by chromatography specialists. They can be used for quality control of peptide separations (separation efficiency, selectivity, retention values) and for accurate concatenation of retention data from multiple acquisitions in proteomics. So far the repertoire of available retention standards is mostly limited to reversed-phase separations. We introduce a synthetic peptide mixture which can be used in conjunction with the most popular peptide separation techniques: reversed-phase (RPLC), strong-cation exchange (SCX), (strong-anion exchange) SAX and hydrophilic interaction liquid chromatography (HILIC). Target sequences were first designed in-silico using Sequence-Specific Retention Calculator models covering all major peptide separation mechanisms. Peptides were also designed while keeping in mind the simplicity of retention time assignment using MS detection: they all have nearly identical masses and identical intense y₃ fragment ions. This contribution demonstrates the application of this mixture for characterization of eight HILIC as well as SAX, SCX and C18 columns.