Evaluation of Disposable Trap Column nanoLC-FAIMS-MS/MS for the Proteomic Analysis of FFPE Tissue

Proteomic biomarker discovery using formalin-fixed paraffin-embedded (FFPE) tissue requires robust workflows to support the analysis of large cohorts of patient samples. It also requires finding a reasonable balance between achieving a high proteomic depth and limiting the overall analysis time. To this end, we evaluated the merits of online coupling of single-use disposable trap column nanoflow liquid chromatography, high-field asymmetric-waveform ion-mobility spectrometry (FAIMS), and tandem mass spectrometry (nLC-FAIMS-MS/MS). The data show that ≤600 ng of peptide digest should be loaded onto the chromatographic part of the system. Careful characterization of the FAIMS settings enabled the choice of optimal combinations of compensation voltages (CVs) as a function of the employed LC gradient time. We found nLC-FAIMS-MS/MS to be on par with StageTip-based off-line basic pH reversed-phase fractionation in terms of proteomic depth and reproducibility of protein quantification (coefficient of variation ≤15% for 90% of all proteins) but requiring 50% less sample and substantially reducing sample handling. Using FFPE materials from the lymph node, lung, and prostate tissue as examples, we show that nLC-FAIMS-MS/MS can identify 5000-6000 proteins from the respective tissue within a total of 3 h of analysis time.

Stress-primed secretory autophagy promotes extracellular BDNF maturation by enhancing MMP9 secretion

The stress response is an essential mechanism for maintaining homeostasis, and its disruption is implicated in several psychiatric disorders. On the cellular level, stress activates, among other mechanisms, autophagy that regulates homeostasis through protein degradation and recycling. Secretory autophagy is a recently described pathway in which autophagosomes fuse with the plasma membrane rather than with lysosomes. Here, we demonstrate that glucocorticoid-mediated stress enhances secretory autophagy via the stress-responsive co-chaperone FK506-binding protein 51. We identify the matrix metalloproteinase 9 (MMP9) as one of the proteins secreted in response to stress. Using cellular assays and in vivo microdialysis, we further find that stress-enhanced MMP9 secretion increases the cleavage of pro-brain-derived neurotrophic factor (proBDNF) to its mature form (mBDNF). BDNF is essential for adult synaptic plasticity and its pathway is associated with major depression and posttraumatic stress disorder. These findings unravel a cellular stress adaptation mechanism that bears the potential of opening avenues for the understanding of the pathophysiology of stress-related disorders.

Cytomegalovirus subverts macrophage identity

Cytomegaloviruses (CMVs) have co-evolved with their mammalian hosts for millions of years, leading to remarkable host specificity and high infection prevalence. Macrophages, which already populate barrier tissues in the embryo, are the predominant immune cells at potential CMV entry sites. Here we show that, upon CMV infection, macrophages undergo a morphological, immunophenotypic, and metabolic transformation process with features of stemness, altered migration, enhanced invasiveness, and provision of the cell cycle machinery for viral proliferation. This complex process depends on Wnt signaling and the transcription factor ZEB1. In pulmonary infection, mouse CMV primarily targets and reprograms alveolar macrophages, which alters lung physiology and facilitates primary CMV and secondary bacterial infection by attenuating the inflammatory response. Thus, CMV profoundly perturbs macrophage identity beyond established limits of plasticity and rewires specific differentiation processes, allowing viral spread and impairing innate tissue immunity.

Degradation of CCNK/CDK12 is a druggable vulnerability of colorectal cancer

Novel treatment options for metastatic colorectal cancer (CRC) are urgently needed to improve patient outcome. Here, we screen a library of non-characterized small molecules against a heterogeneous collection of patient-derived CRC spheroids. By prioritizing compounds with inhibitory activity in a subset of-but not all-spheroid cultures, NCT02 is identified as a candidate with minimal risk of non-specific toxicity. Mechanistically, we show that NCT02 acts as molecular glue that induces ubiquitination of cyclin K (CCNK) and proteasomal degradation of CCNK and its complex partner CDK12. Knockout of CCNK or CDK12 decreases proliferation of CRC cells in vitro and tumor growth in vivo. Interestingly, sensitivity to pharmacological CCNK/CDK12 degradation is associated with TP53 deficiency and consensus molecular subtype 4 in vitro and in patient-derived xenografts. We thus demonstrate the efficacy of targeted CCNK/CDK12 degradation for a CRC subset, highlighting the potential of drug-induced proteolysis for difficult-to-treat types of cancer.

Identification of 7 000-9 000 Proteins from Cell Lines and Tissues by Single-Shot Microflow LC-MS/MS

A current trend in proteomics is to acquire data in a "single-shot" by LC-MS/MS because it simplifies workflows and promises better throughput and quantitative accuracy than schemes that involve extensive sample fractionation. However, single-shot approaches can suffer from limited proteome coverage when performed by data dependent acquisition (ssDDA) on nanoflow LC systems. For applications where sample quantities are not scarce, this study shows that high proteome coverage can be obtained using a microflow LC-MS/MS system operating a 1 mm i.d. × 150 mm column, at a flow-rate of 50 μL/min and coupled to an Orbitrap HF-X mass spectrometer. The results demonstrate the identification of ∼9 000 proteins from 50 μg of protein digest from Arabidopsis roots, 7 500 from mouse thymus, and 7 300 from human breast cancer cells in 3 h of analysis time in a single run. The dynamic range of protein quantification measured by the iBAQ approach spanned 5 orders of magnitude and replicate analysis showed that the median coefficient of variation was below 20%. Together, this study shows that ssDDA by μLC-MS/MS is a robust method for comprehensive and large-scale proteome analysis and which may be further extended to more rapid chromatography and data independent acquisition approaches in the future.̀.

Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics

Characterizing the human leukocyte antigen (HLA) bound ligandome by mass spectrometry (MS) holds great promise for developing vaccines and drugs for immune-oncology. Still, the identification of non-tryptic peptides presents substantial computational challenges. To address these, we synthesized and analyzed >300,000 peptides by multi-modal LC-MS/MS within the ProteomeTools project representing HLA class I & II ligands and products of the proteases AspN and LysN. The resulting data enabled training of a single model using the deep learning framework Prosit, allowing the accurate prediction of fragment ion spectra for tryptic and non-tryptic peptides. Applying Prosit demonstrates that the identification of HLA peptides can be improved up to 7-fold, that 87% of the proposed proteasomally spliced HLA peptides may be incorrect and that dozens of additional immunogenic neo-epitopes can be identified from patient tumors in published data. Together, the provided peptides, spectra and computational tools substantially expand the analytical depth of immunopeptidomics workflows.

The emerging landscape of single-molecule protein sequencing technologies

Single-cell profiling methods have had a profound impact on the understanding of cellular heterogeneity. While genomes and transcriptomes can be explored at the single-cell level, single-cell profiling of proteomes is not yet established. Here we describe new single-molecule protein sequencing and identification technologies alongside innovations in mass spectrometry that will eventually enable broad sequence coverage in single-cell profiling. These technologies will in turn facilitate biological discovery and open new avenues for ultrasensitive disease diagnostics.

Systematic analysis of migration factors by MigExpress identifies essential cell migration control genes in non-small cell lung cancer

Cell migration is an essential process in health and in disease, including cancer metastasis. A comprehensive inventory of migration factors is nonetheless lacking-in part due to the difficulty in assessing migration using high-throughput technologies. Hence, there are currently very few screens that systematically reveal factors controlling cell migration. Here, we introduce MigExpress as a platform for the 'identification of Migration control genes by differential Expression'. MigExpress exploits the combination of in-depth molecular profiling and the robust quantitative analysis of migration capacity in a broad panel of samples and identifies migration-associated genes by their differential expression in slow- versus fast-migrating cells. We applied MigExpress to investigate non-small cell lung cancer (NSCLC), which is the most frequent cause of cancer mortality mainly due to metastasis. In 54 NSCLC cell lines, we comprehensively determined mRNA and protein expression. Correlating the transcriptome and proteome profiles with the quantified migration properties led to the discovery and validation of FLNC, DSE, CPA4, TUBB6, and BICC1 as migration control factors in NSCLC cells, which were also negatively correlated with patient survival. Notably, FLNC was the least expressed filamin in NSCLC, but the only one controlling cell migration and correlating with patient survival and metastatic disease stage. In our study, we present MigExpress as a new method for the systematic analysis of migration factors and provide a comprehensive resource of transcriptomic and proteomic data of NSCLC cell lines related to cell migration.

Design, Synthesis, and Evaluation of WD-Repeat-Containing Protein 5 (WDR5) Degraders

Histone H3K4 methylation serves as a post-translational hallmark of actively transcribed genes and is introduced by histone methyltransferase (HMT) and its regulatory scaffolding proteins. One of these is the WD-repeat-containing protein 5 (WDR5) that has also been associated with controlling long noncoding RNAs and transcription factors including MYC. The wide influence of dysfunctional HMT complexes and the typically upregulated MYC levels in diverse tumor types suggested WDR5 as an attractive drug target. Indeed, protein-protein interface inhibitors for two protein interaction interfaces on WDR5 have been developed. While such compounds only inhibit a subset of WDR5 interactions, chemically induced proteasomal degradation of WDR5 might represent an elegant way to target all oncogenic functions. This study presents the design, synthesis, and evaluation of two diverse WDR5 degrader series based on two WIN site binding scaffolds and shows that linker nature and length strongly influence degradation efficacy.

Universal Spectrum Explorer: A Standalone (Web-)Application for Cross-Resource Spectrum Comparison

Here, we present the Universal Spectrum Explorer (USE), a web-based tool based on IPSA for cross-resource (peptide) spectrum visualization and comparison (https://www.proteomicsdb.org/use/). Mass spectra under investigation can be either provided manually by the user (table format) or automatically retrieved from online repositories supporting access to spectral data via the universal spectrum identifier (USI), or requested from other resources and services implementing a newly designed REST interface. As a proof of principle, we implemented such an interface in ProteomicsDB thereby allowing the retrieval of spectra acquired within the ProteomeTools project or real-time prediction of tandem mass spectra from the deep learning framework Prosit. Annotated mirror spectrum plots can be exported from the USE as editable scalable high-quality vector graphics. The USE was designed and implemented with minimal external dependencies allowing local usage and integration into other web sites (https://github.com/kusterlab/universal_spectrum_explorer).

Modeling plasticity and dysplasia of pancreatic ductal organoids derived from human pluripotent stem cells

Personalized in vitro models for dysplasia and carcinogenesis in the pancreas have been constrained by insufficient differentiation of human pluripotent stem cells (hPSCs) into the exocrine pancreatic lineage. Here, we differentiate hPSCs into pancreatic duct-like organoids (PDLOs) with morphological, transcriptional, proteomic, and functional characteristics of human pancreatic ducts, further maturing upon transplantation into mice. PDLOs are generated from hPSCs inducibly expressing oncogenic GNAS, KRAS, or KRAS with genetic covariance of lost CDKN2A and from induced hPSCs derived from a McCune-Albright patient. Each oncogene causes a specific growth, structural, and molecular phenotype in vitro. While transplanted PDLOs with oncogenic KRAS alone form heterogenous dysplastic lesions or cancer, KRAS with CDKN2A loss develop dedifferentiated pancreatic ductal adenocarcinomas. In contrast, transplanted PDLOs with mutant GNAS lead to intraductal papillary mucinous neoplasia-like structures. Conclusively, PDLOs enable in vitro and in vivo studies of pancreatic plasticity, dysplasia, and cancer formation from a genetically defined background.

Chemical Phosphoproteomics Sheds New Light on the Targets and Modes of Action of AKT Inhibitors

Due to its important roles in oncogenic signaling, AKT has been subjected to extensive drug discovery efforts leading to small molecule inhibitors investigated in advanced clinical trials. To better understand how these drugs exert their therapeutic effects at the molecular level, we combined chemoproteomic target affinity profiling using kinobeads and phosphoproteomics to analyze the five clinical AKT inhibitors AZD5363 (Capivasertib), GSK2110183 (Afuresertib), GSK690693, Ipatasertib, and MK-2206 in BT-474 breast cancer cells. Kinobead profiling identified between four and 29 nM targets for these compounds and showed that AKT1 and AKT2 were the only common targets. Similarly, measuring the response of the phosphoproteome to the same inhibitors identified ∼1700 regulated phosphorylation sites, 276 of which were perturbed by all five compounds. This analysis expanded the known AKT signaling network by 119 phosphoproteins that may represent direct or indirect targets of AKT. Within this new network, 41 regulated phosphorylation sites harbor the AKT substrate motif, and recombinant kinase assays validated 16 as novel AKT substrates. These included CEP170 and FAM83H, suggesting a regulatory function of AKT in mitosis and cytoskeleton organization. In addition, a specific phosphorylation pattern on the ULK1-FIP200-ATG13-VAPB complex was found to determine the active state of ULK1, leading to elevated autophagy in response to AKT inhibition.

Spectral Prediction Features as a Solution for the Search Space Size Problem in Proteogenomics

Proteogenomics approaches often struggle with the distinction between true and false peptide-to-spectrum matches as the database size enlarges. However, features extracted from tandem mass spectrometry intensity predictors can enhance the peptide identification rate and can provide extra confidence for peptide-to-spectrum matching in a proteogenomics context. To that end, features from the spectral intensity pattern predictors MS²PIP and Prosit were combined with the canonical scores from MaxQuant in the Percolator postprocessing tool for protein sequence databases constructed out of ribosome profiling and nanopore RNA-Seq analyses. The presented results provide evidence that this approach enhances both the identification rate as well as the validation stringency in a proteogenomic setting.

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First proteogenomics with PSM rescoring using machine learning–predicted spectra

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Demonstrated on both ribosome profiling and nanopore RNA-Seq–derived databases

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Rescoring leads to elevated stringency and increased identification rates

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Rescoring compensates for the search space size issues in proteogenomics

The IMiD target CRBN determines HSP90 activity toward transmembrane proteins essential in multiple myeloma

The complex architecture of transmembrane proteins requires quality control (QC) of folding, membrane positioning, and trafficking as prerequisites for cellular homeostasis and intercellular communication. However, it has remained unclear whether transmembrane protein-specific QC hubs exist. Here we identify cereblon (CRBN), the target of immunomodulatory drugs (IMiDs), as a co-chaperone that specifically determines chaperone activity of HSP90 toward transmembrane proteins by means of counteracting AHA1. This function is abrogated by IMiDs, which disrupt the interaction of CRBN with HSP90. Among the multiple transmembrane protein clients of CRBN-AHA1-HSP90 revealed by cell surface proteomics, we identify the amino acid transporter LAT1/CD98hc as a determinant of IMiD activity in multiple myeloma (MM) and present an Anticalin-based CD98hc radiopharmaceutical for MM radio-theranostics. These data establish the CRBN-AHA1-HSP90 axis in the biogenesis of transmembrane proteins, link IMiD activity to tumor metabolism, and nominate CD98hc and LAT1 as attractive diagnostic and therapeutic targets in MM.

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CRBN functions as a transmembrane protein-specific co-chaperone of HSP90

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Disruption of CRBN-HSP90 interaction determines the anti-tumor activity of IMiDs

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The CD98hc/LAT1 complex is a central target of IMiDs in multiple myeloma

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CD98hc-Anticalin is a theranostic tool in multiple myeloma

SARS-CoV-2 infection remodels the host protein thermal stability landscape

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global threat to human health and has compromised economic stability. In addition to the development of an effective vaccine, it is imperative to understand how SARS-CoV-2 hijacks host cellular machineries on a system-wide scale so that potential host-directed therapies can be developed. In situ proteome-wide abundance and thermal stability measurements using thermal proteome profiling (TPP) can inform on global changes in protein activity. Here we adapted TPP to high biosafety conditions amenable to SARS-CoV-2 handling. We discovered pronounced temporal alterations in host protein thermostability during infection, which converged on cellular processes including cell cycle, microtubule and RNA splicing regulation. Pharmacological inhibition of host proteins displaying altered thermal stability or abundance during infection suppressed SARS-CoV-2 replication. Overall, this work serves as a framework for expanding TPP workflows to globally important human pathogens that require high biosafety containment and provides deeper resolution into the molecular changes induced by SARS-CoV-2 infection.

Radiosensitization by Kinase Inhibition Revealed by Phosphoproteomic Analysis of Pancreatic Cancer Cells

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers and known for its extensive genetic heterogeneity, high therapeutic resistance, and strong variation in intrinsic radiosensitivity. To understand the molecular mechanisms underlying radioresistance, we screened the phenotypic response of 38 PDAC cell lines to ionizing radiation. Subsequent phosphoproteomic analysis of two representative sensitive and resistant lines led to the reproducible identification of 7,800 proteins and 13,000 phosphorylation sites (p-sites). Approximately 700 p-sites on 400 proteins showed abundance changes after radiation in all cell lines regardless of their phenotypic sensitivity. Apart from recapitulating known radiation response phosphorylation markers such as on proteins involved in DNA damage repair, the analysis uncovered many novel members of a radiation-responsive signaling network that was apparent only at the level of protein phosphorylation. These regulated p-sites were enriched in potential ATM substrates and in vitro kinase assays corroborated 10 of these. Comparing the proteomes and phosphoproteomes of radiosensitive and -resistant cells pointed to additional tractable radioresistance mechanisms involving apoptotic proteins. For instance, elevated NADPH quinine oxidoreductase 1 (NQO1) expression in radioresistant cells may aid in clearing harmful reactive oxygen species. Resistant cells also showed elevated phosphorylation levels of proteins involved in cytoskeleton organization including actin dynamics and focal adhesion kinase (FAK) activity and one resistant cell line showed a strong migration phenotype. Pharmacological inhibition of the kinases FAK by Defactinib and of CHEK1 by Rabusertib showed a statistically significant sensitization to radiation in radioresistant PDAC cells. Together, the presented data map a comprehensive molecular network of radiation-induced signaling, improves the understanding of radioresistance and provides avenues for developing radiotherapeutic strategies.

PROTAC-mediated degradation reveals a non-catalytic function of AURORA-A kinase

The mitotic kinase AURORA-A is essential for cell cycle progression and is considered a priority cancer target. While the catalytic activity of AURORA-A is essential for its mitotic function, recent reports indicate an additional non-catalytic function, which is difficult to target by conventional small molecules. We therefore developed a series of chemical degraders (PROTACs) by connecting a clinical kinase inhibitor of AURORA-A to E3 ligase-binding molecules (e.g. thalidomide). One degrader induced rapid, durable and highly specific degradation of AURORA-A. In addition ,we found that the degrader complex was stabilized by cooperative binding between AURORA-A and CEREBLON. Degrader-mediated AURORA-A depletion caused an S-phase defect, which is not the cell cycle effect observed upon kinase inhibition, supporting an important non-catalytic function of AURORA-A during DNA replication. AURORA-A degradation induced rampant apoptosis in cancer cell lines, and thus represents a versatile starting point for developing new therapeutics to counter AURORA-A function in cancer.

Data, Reagents, Assays and Merits of Proteomics for SARS-CoV-2 Research and Testing

As the COVID-19 pandemic continues to spread, thousands of scientists around the globe have changed research direction to understand better how the virus works and to find out how it may be tackled. The number of manuscripts on preprint servers is soaring and peer-reviewed publications using MS-based proteomics are beginning to emerge. To facilitate proteomic research on SARS-CoV-2, the virus that causes COVID-19, this report presents deep-scale proteomes (10,000 proteins; >130,000 peptides) of common cell line models, notably Vero E6, Calu-3, Caco-2, and ACE2-A549 that characterize their protein expression profiles including viral entry factors such as ACE2 or TMPRSS2. Using the 9 kDa protein SRP9 and the breast cancer oncogene BRCA1 as examples, we show how the proteome expression data can be used to refine the annotation of protein-coding regions of the African green monkey and the Vero cell line genomes. Monitoring changes of the proteome on viral infection revealed widespread expression changes including transcriptional regulators, protease inhibitors, and proteins involved in innate immunity. Based on a library of 98 stable-isotope labeled synthetic peptides representing 11 SARS-CoV-2 proteins, we developed PRM (parallel reaction monitoring) assays for nano-flow and micro-flow LC-MS/MS. We assessed the merits of these PRM assays using supernatants of virus-infected Vero E6 cells and challenged the assays by analyzing two diagnostic cohorts of 24 (+30) SARS-CoV-2 positive and 28 (+9) negative cases. In light of the results obtained and including recent publications or manuscripts on preprint servers, we critically discuss the merits of MS-based proteomics for SARS-CoV-2 research and testing.

PTPN2 Deficiency Enhances Programmed T Cell Expansion and Survival Capacity of Activated T Cells

Manipulating molecules that impact T cell receptor (TCR) or cytokine signaling, such as the protein tyrosine phosphatase non-receptor type 2 (PTPN2), has significant potential for advancing T cell-based immunotherapies. Nonetheless, it remains unclear how PTPN2 impacts the activation, survival, and memory formation of T cells. We find that PTPN2 deficiency renders cells in vivo and in vitro less dependent on survival-promoting cytokines, such as interleukin (IL)-2 and IL-15. Remarkably, briefly ex vivo-activated PTPN2-deficient T cells accumulate in 3- to 11-fold higher numbers following transfer into unmanipulated, antigen-free mice. Moreover, the absence of PTPN2 augments the survival of short-lived effector T cells and allows them to robustly re-expand upon secondary challenge. Importantly, we find no evidence for impaired effector function or memory formation. Mechanistically, PTPN2 deficiency causes broad changes in the expression and phosphorylation of T cell expansion and survival-associated proteins. Altogether, our data underline the therapeutic potential of targeting PTPN2 in T cell-based therapies to augment the number and survival capacity of antigen-specific T cells.

Wnt-driven LARGE2 mediates laminin-adhesive O-glycosylation in human colonic epithelial cells and colorectal cancer

BACKGROUND

Wnt signaling drives epithelial self-renewal and disease progression in human colonic epithelium and colorectal cancer (CRC). Characterization of Wnt effector pathways is key for our understanding of these processes and for developing therapeutic strategies that aim to preserve tissue homeostasis. O-glycosylated cell surface proteins, such as α-dystroglycan (α-DG), mediate cellular adhesion to extracellular matrix components. We revealed a Wnt/LARGE2/α-DG signaling pathway which triggers this mode of colonic epithelial cell-to-matrix interaction in health and disease.

METHODS

Next generation sequencing upon shRNA-mediated silencing of adenomatous polyposis coli (APC), and quantitative chromatin immunoprecipitation (qChIP) combined with CRISPR/Cas9-mediated transcription factor binding site targeting characterized LARGE2 as a Wnt target gene. Quantitative mass spectrometry analysis on size-fractionated, glycoprotein-enriched samples revealed functional O-glycosylation of α-DG by LARGE2 in CRC. The biology of Wnt/LARGE2/α-DG signaling was assessed by affinity-based glycoprotein enrichment, laminin overlay, CRC-to-endothelial cell adhesion, and transwell migration assays. Experiments on primary tissue, human colonic (tumor) organoids, and bioinformatic analysis of CRC cohort data confirmed the biological relevance of our findings.

RESULTS

Next generation sequencing identified the LARGE2 O-glycosyltransferase encoding gene as differentially expressed upon Wnt activation in CRC. Silencing of APC, conditional expression of oncogenic β-catenin and endogenous β-catenin-sequestration affected LARGE2 expression. The first intron of LARGE2 contained a CTTTGATC motif essential for Wnt-driven LARGE2 expression, showed occupation by the Wnt transcription factor TCF7L2, and Wnt activation triggered LARGE2-dependent α-DG O-glycosylation and laminin-adhesion in CRC cells. Colonic crypts and organoids expressed LARGE2 mainly in stem cell-enriched subpopulations. In human adenoma organoids, activity of the LARGE2/α-DG axis was Wnt-dose dependent. LARGE2 expression was elevated in CRC and correlated with the Wnt-driven molecular subtype and intestinal stem cell features. O-glycosylated α-DG represented a Wnt/LARGE2-dependent feature in CRC cell lines and patient-derived tumor organoids. Modulation of LARGE2/α-DG signaling affected CRC cell migration through laminin-coated membranes and adhesion to endothelial cells.

CONCLUSIONS

We conclude that the LARGE2 O-glycosyltransferase-encoding gene represents a direct target of canonical Wnt signaling and mediates functional O-glycosylation of α-dystroglycan (α-DG) in human colonic stem/progenitor cells and Wnt-driven CRC. Our work implies that aberrant Wnt activation augments CRC cell-matrix adhesion by increasing LARGE/α-DG-mediated laminin-adhesiveness. Video abstract.

Loss of the Fanconi anemia-associated protein NIPA causes bone marrow failure

Inherited bone marrow failure syndromes (IBMFSs) are a heterogeneous group of disorders characterized by defective hematopoiesis, impaired stem cell function, and cancer susceptibility. Diagnosis of IBMFS presents a major challenge due to the large variety of associated phenotypes, and novel, clinically relevant biomarkers are urgently needed. Our study identified nuclear interaction partner of ALK (NIPA) as an IBMFS gene, as it is significantly downregulated in a distinct subset of myelodysplastic syndrome-type (MDS-type) refractory cytopenia in children. Mechanistically, we showed that NIPA is major player in the Fanconi anemia (FA) pathway, which binds FANCD2 and regulates its nuclear abundance, making it essential for a functional DNA repair/FA/BRCA pathway. In a knockout mouse model, Nipa deficiency led to major cell-intrinsic defects, including a premature aging phenotype, with accumulation of DNA damage in hematopoietic stem cells (HSCs). Induction of replication stress triggered a reduction in and functional decline of murine HSCs, resulting in complete bone marrow failure and death of the knockout mice with 100% penetrance. Taken together, the results of our study add NIPA to the short list of FA-associated proteins, thereby highlighting its potential as a diagnostic marker and/or possible target in diseases characterized by hematopoietic failure.

ProteomicsDB: a multi-omics and multi-organism resource for life science research

ProteomicsDB (https://www.ProteomicsDB.org) started as a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. The data types and contents grew over time to include RNA-Seq expression data, drug-target interactions and cell line viability data. In this manuscript, we summarize new developments since the previous update that was published in Nucleic Acids Research in 2017. Over the past two years, we have enriched the data content by additional datasets and extended the platform to support protein turnover data. Another important new addition is that ProteomicsDB now supports the storage and visualization of data collected from other organisms, exemplified by Arabidopsis thaliana. Due to the generic design of ProteomicsDB, all analytical features available for the original human resource seamlessly transfer to other organisms. Furthermore, we introduce a new service in ProteomicsDB which allows users to upload their own expression datasets and analyze them alongside with data stored in ProteomicsDB. Initially, users will be able to make use of this feature in the interactive heat map functionality as well as the drug sensitivity prediction, but ultimately will be able to use all analytical features of ProteomicsDB in this way.

Meltome atlas-thermal proteome stability across the tree of life

We have used a mass spectrometry-based proteomic approach to compile an atlas of the thermal stability of 48,000 proteins across 13 species ranging from archaea to humans and covering melting temperatures of 30-90 °C. Protein sequence, composition and size affect thermal stability in prokaryotes and eukaryotic proteins show a nonlinear relationship between the degree of disordered protein structure and thermal stability. The data indicate that evolutionary conservation of protein complexes is reflected by similar thermal stability of their proteins, and we show examples in which genomic alterations can affect thermal stability. Proteins of the respiratory chain were found to be very stable in many organisms, and human mitochondria showed close to normal respiration at 46 °C. We also noted cell-type-specific effects that can affect protein stability or the efficacy of drugs. This meltome atlas broadly defines the proteome amenable to thermal profiling in biology and drug discovery and can be explored online at http://meltomeatlas.proteomics.wzw.tum.de:5003/ and http://www.proteomicsdb.org.

A series of novel aryl-methanone derivatives as inhibitors of FMS-like tyrosine kinase 3 (FLT3) in FLT3-ITD-positive acute myeloid leukemia

Mutants of the FLT3 receptor tyrosine kinase (RTK) with duplications in the juxtamembrane domain (FLT3-ITD) act as drivers of acute myeloid leukemia (AML). Potent tyrosine kinase inhibitors (TKi) of FLT3-ITD entered clinical trials and showed a promising, but transient success due to the occurrence of secondary drug-resistant AML clones. A further caveat of drugs targeting FLT3-ITD is the co-targeting of other RTKs which are required for normal hematopoiesis. This is observed quite frequently. Therefore, novel drugs are necessary to treat AML effectively and safely. Recently bis(1H-indol-2-yl)methanones were found to inhibit FLT3 and PDGFR kinases. In order to optimize these agents we synthesized novel derivatives of these methanones with various substituents. Methanone 16 and its carbamate derivative 17b inhibit FLT3-ITD at least as potently as the TKi AC220 (quizartinib). Models indicate corresponding interactions of 16 and quizartinib with FLT3. The activity of 16 is accompanied by a high selectivity for FLT3-ITD.

Proteomic and Metabolite Profiling Reveals Profound Structural and Metabolic Reorganization of Adipocyte Mitochondria in Obesity

OBJECTIVE

Previous studies have revealed decreased mitochondrial respiration in adipocytes of obese mice. This study aimed to identify the molecular underpinnings of altered mitochondrial metabolism in adipocytes.

METHODS

Untargeted proteomics of mitochondria isolated from adipocytes and metabolite profiling of adipose tissues were conducted in diet-induced obese (DIO) and lean mice. Subcutaneous and intra-abdominal adipose tissues were studied to depict depot-specific alterations.

RESULTS

In subcutaneous adipocytes of DIO mice, changes in proteins related to mitochondrial structure and function were observed. Mitochondrial proteins of the inner and outer membrane were strongly reduced, whereas proteins of key matrix metabolic pathways were increased in the obese versus lean state, as further substantiated by metabolite profiling. A pronounced decrease in the oxidative phosphorylation (OXPHOS) enzymatic equipment and cristae density of the inner membrane was identified. In intra-abdominal adipocytes, similar systematic downregulation of the OXPHOS machinery in obesity occurred, but there was no regulation of outer membrane or matrix proteins.

CONCLUSIONS

Protein components of the OXPHOS machinery are systematically downregulated in adipose tissues of DIO mice compared with lean mice. Loss of the mitochondrial OXPHOS capacity in adipocytes may aggravate the development of metabolic disease.

Identification of molecular targets for the targeted treatment of gastric cancer using dasatinib

Gastric cancer (GC) remains the third leading cause of cancer-related death despite several improvements in targeted therapy. There is therefore an urgent need to investigate new treatment strategies, including the identification of novel biomarkers for patient stratification. In this study, we evaluated the effect of FDA-approved kinase inhibitors on GC. Through a combination of cell growth, migration and invasion assays, we identified dasatinib as an efficient inhibitor of GC proliferation. Mass-spectrometry-based selectivity profiling and subsequent knockdown experiments identified members of the SRC family of kinases including SRC, FRK, LYN and YES, as well as other kinases such as DDR1, ABL2, SIK2, RIPK2, EPHA2, and EPHB2 as dasatinib targets. The expression levels of the identified kinases were investigated on RNA and protein level in 200 classified tumor samples from patients, who had undergone gastrectomy, but had received no treatment. Levels of FRK, DDR1 and SRC expression on both mRNA and protein level were significantly higher in metastatic patient samples regardless of the tumor stage, while expression levels of SIK2 correlated with tumor size. Collectively, our data suggest dasatinib for treatment of GC based on its unique property, inhibiting a small number of key kinases (SRC, FRK, DDR1 and SIK2), highly expressed in GC patients.

Repurposing human kinase inhibitors to create an antibiotic active against drug-resistant Staphylococcus aureus, persisters and biofilms

New drugs are desperately needed to combat methicillin-resistant Staphylococcus aureus (MRSA) infections. Here, we report screening commercial kinase inhibitors for antibacterial activity and found the anticancer drug sorafenib as major hit that effectively kills MRSA strains. Varying the key structural features led to the identification of a potent analogue, PK150, that showed antibacterial activity against several pathogenic strains at submicromolar concentrations. Furthermore, this antibiotic eliminated challenging persisters as well as established biofilms. PK150 holds promising therapeutic potential as it did not induce in vitro resistance, and shows oral bioavailability and in vivo efficacy. Analysis of the mode of action using chemical proteomics revealed several targets, which included interference with menaquinone biosynthesis by inhibiting demethylmenaquinone methyltransferase and the stimulation of protein secretion by altering the activity of signal peptidase IB. Reduced endogenous menaquinone levels along with enhanced levels of extracellular proteins of PK150-treated bacteria support this target hypothesis. The associated antibiotic effects, especially the lack of resistance development, probably stem from the compound's polypharmacology.

The Formation of a Camalexin Biosynthetic Metabolon

Arabidopsis (Arabidopsis thaliana) efficiently synthesizes the antifungal phytoalexin camalexin without the apparent release of bioactive intermediates, such as indole-3-acetaldoxime, suggesting that the biosynthetic pathway of this compound is channeled by the formation of an enzyme complex. To identify such protein interactions, we used two independent untargeted coimmunoprecipitation (co-IP) approaches with the biosynthetic enzymes CYP71B15 and CYP71A13 as baits and determined that the camalexin biosynthetic P450 enzymes copurified with these enzymes. These interactions were confirmed by targeted co-IP and Förster resonance energy transfer measurements based on fluorescence lifetime microscopy (FRET-FLIM). Furthermore, the interaction of CYP71A13 and Arabidopsis P450 Reductase1 was observed. We detected increased substrate affinity of CYP79B2 in the presence of CYP71A13, indicating an allosteric interaction. Camalexin biosynthesis involves glutathionylation of the intermediary indole-3-cyanohydrin, which is synthesized by CYP71A12 and especially CYP71A13. FRET-FLIM and co-IP demonstrated that the glutathione transferase GSTU4, which is coexpressed with Trp- and camalexin-specific enzymes, is physically recruited to the complex. Surprisingly, camalexin concentrations were elevated in knockout and reduced in GSTU4-overexpressing plants. This shows that GSTU4 is not directly involved in camalexin biosynthesis but rather plays a role in a competing mechanism.

Interactions between Transport Protein Particle (TRAPP) complexes and Rab GTPases in Arabidopsis

Transport Protein Particle II (TRAPPII) is essential for exocytosis, endocytosis, protein sorting and cytokinesis. In spite of a considerable understanding of its biological role, little information is known about Arabidopsis TRAPPII complex topology and molecular function. In this study, independent proteomic approaches initiated with TRAPP components or Rab-A GTPase variants converge on the TRAPPII complex. We show that the Arabidopsis genome encodes the full complement of 13 TRAPPC subunits, including four previously unidentified components. A dimerization model is proposed to account for binary interactions between TRAPPII subunits. Preferential binding to dominant negative (GDP-bound) versus wild-type or constitutively active (GTP-bound) RAB-A2a variants discriminates between TRAPPII and TRAPPIII subunits and shows that Arabidopsis complexes differ from yeast but resemble metazoan TRAPP complexes. Analyzes of Rab-A mutant variants in trappii backgrounds provide genetic evidence that TRAPPII functions upstream of RAB-A2a, allowing us to propose that TRAPPII is likely to behave as a guanine nucleotide exchange factor (GEF) for the RAB-A2a GTPase. GEFs catalyze exchange of GDP for GTP; the GTP-bound, activated, Rab then recruits a diverse local network of Rab effectors to specify membrane identity in subsequent vesicle fusion events. Understanding GEF-Rab interactions will be crucial to unravel the co-ordination of plant membrane traffic.

ProteomicsDB

ProteomicsDB (https://www.ProteomicsDB.org) is a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. ProteomicsDB was first released in 2014 to enable the interactive exploration of the first draft of the human proteome. To date, it contains quantitative data from 78 projects totalling over 19k LC–MS/MS experiments. A standardized analysis pipeline enables comparisons between multiple datasets to facilitate the exploration of protein expression across hundreds of tissues, body fluids and cell lines. We recently extended the data model to enable the storage and integrated visualization of other quantitative omics data. This includes transcriptomics data from e.g. NCBI GEO, protein–protein interaction information from STRING, functional annotations from KEGG, drug-sensitivity/selectivity data from several public sources and reference mass spectra from the ProteomeTools project. The extended functionality transforms ProteomicsDB into a multi-purpose resource connecting quantification and meta-data for each protein. The rich user interface helps researchers to navigate all data sources in either a protein-centric or multi-protein-centric manner. Several options are available to download data manually, while our application programming interface enables accessing quantitative data systematically.

MOGSA: Integrative Single Sample Gene-set Analysis of Multiple Omics Data

Gene-set analysis (GSA) summarizes individual molecular measurements to more interpretable pathways or gene-sets and has become an indispensable step in the interpretation of large-scale omics data. However, GSA methods are limited to the analysis of single omics data. Here, we introduce a new computation method termed multi-omics gene-set analysis (MOGSA), a multivariate single sample gene-set analysis method that integrates multiple experimental and molecular data types measured over the same set of samples. The method learns a low dimensional representation of most variant correlated features (genes, proteins, etc.) across multiple omics data sets, transforms the features onto the same scale and calculates an integrated gene-set score from the most informative features in each data type. MOGSA does not require filtering data to the intersection of features (gene IDs), therefore, all molecular features, including those that lack annotation may be included in the analysis. Using simulated data, we demonstrate that integrating multiple diverse sources of molecular data increases the power to discover subtle changes in gene-sets and may reduce the impact of unreliable information in any single data type. Using real experimental data, we demonstrate three use-cases of MOGSA. First, we show how to remove a source of noise (technical or biological) in integrative MOGSA of NCI60 transcriptome and proteome data. Second, we apply MOGSA to discover similarities and differences in mRNA, protein and phosphorylation profiles of a small study of stem cell lines and assess the influence of each data type or feature on the total gene-set score. Finally, we apply MOGSA to cluster analysis and show that three molecular subtypes are robustly discovered when copy number variation and mRNA data of 308 bladder cancers from The Cancer Genome Atlas are integrated using MOGSA. MOGSA is available in the Bioconductor R package "mogsa."

PROTEOFORMER 2.0: Further Developments in the Ribosome Profiling-assisted Proteogenomic Hunt for New Proteoforms

PROTEOFORMER is a pipeline that enables the automated processing of data derived from ribosome profiling (RIBO-seq, i.e. the sequencing of ribosome-protected mRNA fragments). As such, genome-wide ribosome occupancies lead to the delineation of data-specific translation product candidates and these can improve the mass spectrometry-based identification. Since its first publication, different upgrades, new features and extensions have been added to the PROTEOFORMER pipeline. Some of the most important upgrades include P-site offset calculation during mapping, comprehensive data pre-exploration, the introduction of two alternative proteoform calling strategies and extended pipeline output features. These novelties are illustrated by analyzing ribosome profiling data of human HCT116 and Jurkat data. The different proteoform calling strategies are used alongside one another and in the end combined together with reference sequences from UniProt. Matching mass spectrometry data are searched against this extended search space with MaxQuant. Overall, besides annotated proteoforms, this pipeline leads to the identification and validation of different categories of new proteoforms, including translation products of up- and downstream open reading frames, 5' and 3' extended and truncated proteoforms, single amino acid variants, splice variants and translation products of so-called noncoding regions. Further, proof-of-concept is reported for the improvement of spectrum matching by including Prosit, a deep neural network strategy that adds extra fragmentation spectrum intensity features to the analysis. In the light of ribosome profiling-driven proteogenomics, it is shown that this allows validating the spectrum matches of newly identified proteoforms with elevated stringency. These updates and novel conclusions provide new insights and lessons for the ribosome profiling-based proteogenomic research field. More practical information on the pipeline, raw code, the user manual (README) and explanations on the different modes of availability can be found at the GitHub repository of PROTEOFORMER: https://github.com/Biobix/proteoformer.

Rebuilding core abscisic acid signaling pathways of Arabidopsis in yeast

The phytohormone abscisic acid (ABA) regulates plant responses to abiotic stress, such as drought and high osmotic conditions. The multitude of functionally redundant components involved in ABA signaling poses a major challenge for elucidating individual contributions to the response selectivity and sensitivity of the pathway. Here, we reconstructed single ABA signaling pathways in yeast for combinatorial analysis of ABA receptors and coreceptors, downstream‐acting SnRK2 protein kinases, and transcription factors. The analysis shows that some ABA receptors stimulate the pathway even in the absence of ABA and that SnRK2s are major determinants of ABA responsiveness by differing in the ligand‐dependent control. Five SnRK2s, including SnRK2.4 known to be active under osmotic stress in plants, activated ABA‐responsive transcription factors and were regulated by ABA receptor complexes in yeast. In the plant tissue, SnRK2.4 and ABA receptors competed for coreceptor interaction in an ABA‐dependent manner consistent with a tight integration of SnRK2.4 into the ABA signaling pathway. The study establishes the suitability of the yeast system for the dissection of core signaling cascades and opens up future avenues of research on ligand‐receptor regulation.

TMT Labeling for the Masses: A Robust and Cost-efficient, In-solution Labeling Approach

Isobaric stable isotope labeling using, for example, tandem mass tags (TMTs) is increasingly being applied for large-scale proteomic studies. Experiments focusing on proteoform analysis in drug time course or perturbation studies or in large patient cohorts greatly benefit from the reproducible quantification of single peptides across samples. However, such studies often require labeling of hundreds of micrograms of peptides such that the cost for labeling reagents represents a major contribution to the overall cost of an experiment. Here, we describe and evaluate a robust and cost-effective protocol for TMT labeling that reduces the quantity of required labeling reagent by a factor of eight and achieves complete labeling. Under- and overlabeling of peptides derived from complex digests of tissues and cell lines were systematically evaluated using peptide quantities of between 12.5 and 800 μg and TMT-to-peptide ratios (wt/wt) ranging from 8:1 to 1:2 at different TMT and peptide concentrations. When reaction volumes were reduced to maintain TMT and peptide concentrations of at least 10 mm and 2 g/l, respectively, TMT-to-peptide ratios as low as 1:1 (wt/wt) resulted in labeling efficiencies of > 99% and excellent intra- and interlaboratory reproducibility. The utility of the optimized protocol was further demonstrated in a deep-scale proteome and phosphoproteome analysis of patient-derived xenograft tumor tissue benchmarked against the labeling procedure recommended by the TMT vendor. Finally, we discuss the impact of labeling reaction parameters for N-hydroxysuccinimide ester-based chemistry and provide guidance on adopting efficient labeling protocols for different peptide quantities.

Detection of plasmid-mediated colistin resistance, mcr-1 gene, in Escherichia coli isolated from high-risk patients with acute leukemia in Spain

BACKGROUND

Bacterial infections in immunocompromised patients are associated with a high mortality and morbidity rate. In this high-risk group, the presence of multidrug-resistant (MDR) bacteria, particularly bacteria that harbor a transferable antibiotic resistance gene, complicates the management of bacterial infections. In this study, we investigated the presence of the transferable colistin resistance mcr genes in patients with leukemia in Spain.

METHODS

217 fecal samples collected in 2013-2015 from 56 patients with acute leukemia and colonized with MDR Enterobacteriaceae strains, were screened on September 2017 for the presence of the colistin resistance mcr genes (mcr-1 to -5) by multiplex PCR. mcr positive strains selected on LBJMR and MacConkey supplemented with colistin (2 μg/ml) media were phenotypically and molecularly characterized by antimicrobial susceptibility testing, minimum inhibitory concentration, multilocus sequence typing and plasmid characterization.

RESULTS

Among 217 fecal samples, 5 samples collected from 3 patients were positive for the presence of the mcr-1 colistin-resistance gene. Four Escherichia coli strains were isolated and exhibited resistance to colistin with MIC = 4 μg/ml. Other genes conferring the resistance to β-lactam antibiotics have also been identified in mcr-1 positive strains, including bla_TEM-206 and bla_TEM-98. Three different sequence types were identified, including ST1196, ST140 and ST10. Plasmid characterization allowed us to detect the mcr-1 colistin resistance gene on conjugative IncP plasmid type.

CONCLUSION

To the best of our knowledge, we have identified the mcr-1 gene for the first time in leukemia patients in Spain. In light of these results, strict measures have been implemented to prevent its dissemination.

Chemoproteomic Selectivity Profiling of PIKK and PI3K Kinase Inhibitors

Chemical proteomic approaches utilizing immobilized, broad-selective kinase inhibitors (Kinobeads) have proven valuable for the elucidation of a compound's target profile under close-to-physiological conditions and often revealed potentially synergistic or toxic off-targets. Current Kinobeads enrich more than 300 native protein kinases from cell line or tissue lysates but do not systematically cover phosphatidylinositol 3-kinases (PI3Ks) and phosphatidylinositol 3-kinase-related kinases (PIKKs). Some PIKKs and PI3Ks show aberrant activation in many human diseases and are indeed validated drug targets. Here, we report the development of a novel version of Kinobeads that extends kinome coverage to these proteins. This is achieved by inclusion of two affinity probes derived from the clinical PI3K/MTOR inhibitors Omipalisib and BGT226. We demonstrate the utility of the new affinity matrix by the profiling of 13 clinical and preclinical PIKK/PI3K inhibitors. The large discrepancies between the PI3K affinity values obtained and reported results from recombinant assays led us to perform a phosphoproteomic experiment showing that the chemoproteomic assay is the better approximation of PI3K inhibitor action in cellulo. The results further show that NVP-BEZ235 is not a PI3K inhibitor. Surprisingly, the designated ATM inhibitor CP466722 was found to bind strongly to ALK2, identifying a new chemotype for drug discovery to treat fibrodysplasia ossificans progressiva.

CiRCus: A Framework to Enable Classification of Complex High-Throughput Experiments

Despite the increasing use of high-throughput experiments in molecular biology, methods for evaluating and classifying the acquired results have not kept pace, requiring significant manual efforts to do so. Here, we present CiRCus, a framework to generate custom machine learning models to classify results from high-throughput proteomics binding experiments. We show the experimental procedure that guided us to the layout of this framework as well as the usage of the framework on an example data set consisting of 557 166 protein/drug binding curves achieving an AUC of 0.9987. By applying our classifier to the data, only 6% of the data might require manual investigation. CiRCus bundles two applications, a minimal interface to label a training data set (CindeR) and an interface for the generation of random forest classifiers with optional optimization of pretrained models (CurveClassification). CiRCus is available on https://github.com/kusterlab accompanied by an in-depth user manual and video tutorial.

A deep proteome and transcriptome abundance atlas of 29 healthy human tissues

Genome-, transcriptome- and proteome-wide measurements provide insights into how biological systems are regulated. However, fundamental aspects relating to which human proteins exist, where they are expressed and in which quantities are not fully understood. Therefore, we generated a quantitative proteome and transcriptome abundance atlas of 29 paired healthy human tissues from the Human Protein Atlas project representing human genes by 18,072 transcripts and 13,640 proteins including 37 without prior protein-level evidence. The analysis revealed that hundreds of proteins, particularly in testis, could not be detected even for highly expressed mRNAs, that few proteins show tissue-specific expression, that strong differences between mRNA and protein quantities within and across tissues exist and that protein expression is often more stable across tissues than that of transcripts. Only 238 of 9,848 amino acid variants found by exome sequencing could be confidently detected at the protein level showing that proteogenomics remains challenging, needs better computational methods and requires rigorous validation. Many uses of this resource can be envisaged including the study of gene/protein expression regulation and biomarker specificity evaluation.

Quantification and discovery of sequence determinants of protein-per-mRNA amount in 29 human tissues

Despite their importance in determining protein abundance, a comprehensive catalogue of sequence features controlling protein-to-mRNA (PTR) ratios and a quantification of their effects are still lacking. Here, we quantified PTR ratios for 11,575 proteins across 29 human tissues using matched transcriptomes and proteomes. We estimated by regression the contribution of known sequence determinants of protein synthesis and degradation in addition to 45 mRNA and 3 protein sequence motifs that we found by association testing. While PTR ratios span more than 2 orders of magnitude, our integrative model predicts PTR ratios at a median precision of 3.2-fold. A reporter assay provided functional support for two novel UTR motifs, and an immobilized mRNA affinity competition-binding assay identified motif-specific bound proteins for one motif. Moreover, our integrative model led to a new metric of codon optimality that captures the effects of codon frequency on protein synthesis and degradation. Altogether, this study shows that a large fraction of PTR ratio variation in human tissues can be predicted from sequence, and it identifies many new candidate post-transcriptional regulatory elements.

Expanding the Use of Spectral Libraries in Proteomics

The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion on the current state and future directions of the generation and use of peptide tandem mass spectrometry spectral libraries. Their use in proteomics is growing slowly, but there are multiple challenges in the field that must be addressed to further increase the adoption of spectral libraries and related techniques. The primary bottlenecks are the paucity of high quality and comprehensive libraries and the general difficulty of adopting spectral library searching into existing workflows. There are several existing spectral library formats, but none captures a satisfactory level of metadata; therefore, a logical next improvement is to design a more advanced, Proteomics Standards Initiative-approved spectral library format that can encode all of the desired metadata. The group discussed a series of metadata requirements organized into three designations of completeness or quality, tentatively dubbed bronze, silver, and gold. The metadata can be organized at four different levels of granularity: at the collection (library) level, at the individual entry (peptide ion) level, at the peak (fragment ion) level, and at the peak annotation level. Strategies for encoding mass modifications in a consistent manner and the requirement for encoding high-quality and commonly seen but as-yet-unidentified spectra were discussed. The group also discussed related topics, including strategies for comparing two spectra, techniques for generating representative spectra for a library, approaches for selection of optimal signature ions for targeted workflows, and issues surrounding the merging of two or more libraries into one. We present here a review of this field and the challenges that the community must address in order to accelerate the adoption of spectral libraries in routine analysis of proteomics datasets.

ProteomeTools: Systematic Characterization of 21 Post-translational Protein Modifications by Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) Using Synthetic Peptides

The analysis of the post-translational modification (PTM) state of proteins using mass spectrometry-based bottom-up proteomic workflows has evolved into a powerful tool for the study of cellular regulatory events that are not directly encoded at the genome level. Besides frequently detected modifications such as phosphorylation, acetylation and ubiquitination, many low abundant or less frequently detected PTMs are known or postulated to serve important regulatory functions. To more broadly understand the LC-MS/MS characteristics of PTMs, we synthesized and analyzed ∼5,000 peptides representing 21 different naturally occurring modifications of lysine, arginine, proline and tyrosine side chains and their unmodified counterparts. The analysis identified changes in retention times, shifts of precursor charge states and differences in search engine scores between modifications. PTM-dependent changes in the fragmentation behavior were evaluated using eleven different fragmentation modes or collision energies. We also systematically investigated the formation of diagnostic ions or neutral losses for all PTMs, confirming 10 known and identifying 5 novel diagnostic ions for lysine modifications. To demonstrate the value of including diagnostic ions in database searching, we reprocessed a public data set of lysine crotonylation and showed that considering the diagnostic ions increases confidence in the identification of the modified peptides. To our knowledge, this constitutes the first broad and systematic analysis of the LC-MS/MS properties of common and rare PTMs using synthetic peptides, leading to direct applicable utility for bottom-up proteomic experiments.

NVP-BHG712: Effects of Regioisomers on the Affinity and Selectivity toward the EPHrin Family

Erythropoietin-producing hepatocellular (EPH) receptors are transmembrane receptor tyrosine kinases. Their extracellular domains bind specifically to ephrin A/B ligands, and this binding modulates intracellular kinase activity. EPHs are key players in bidirectional intercellular signaling, controlling cell morphology, adhesion, and migration. They are increasingly recognized as cancer drug targets. We analyzed the binding of NVP-BHG712 (NVP) to EPHA2 and EPHB4. Unexpectedly, all tested commercially available NVP samples turned out to be a regioisomer (NVPiso) of the inhibitor, initially described in a Novartis patent application. They only differ by the localization of a single methyl group on either one of two adjacent nitrogen atoms. The two compounds of identical mass revealed different binding modes. Furthermore, both in vitro and in vivo experiments showed that the isomers differ in their kinase affinity and selectivity.

Dynamic Proteome Alteration and Functional Modulation of Human Saliva Induced by Dietary Chemosensory Stimuli

Saliva flow measurements and SDS-PAGE separation of human whole saliva freshly collected after oral stimulation with citric acid (sour), aspartame (sweet), iso-α-acids (bitter), mono sodium l-glutamate (umami), NaCl (salty), 6-gingerol (pungent), hydroxy-α-sanshool (tingling), and hydroxy-β-sanshool (numbing), followed by tryptic digestion, nano-HPLC-MS/MS, and label-free protein quantitation demonstrated a stimulus- and time-dependent influence of the dietary chemosensates on salivation and the salivary proteome composition. Gene ontology enrichment analysis showed evidence for stimulus-induced alterations of the saliva proteome to boot an efficient molecular defense network of the oral cavity, e.g., 6-gingerol increased salivary lactoperoxidase activity, catalyzing the oxidation of thiocyanate to produce the antimicrobial and antifungal hypothiocyanate, from 0.37 ± 0.02 to 0.91 ± 0.05 mU/mL 45 s after stimulation. In comparison, oral citric acid stimulation induced an increase of myeloperoxidase activity, catalyzing the chloride oxidation to generate antimicrobial hypochloride in saliva, from 0.24 ± 0.04 to 0.70 ± 0.1 mU/mL as well as an increase of salivary levels of lysozyme, exhibiting antimicrobial activity on Gram-positive bacteria, from 6.0-10 to 100-150 μg/mL. Finally, microbial growth experiments clearly demonstrated for the first time that the increase of the salivary lysozyme abundance upon oral citric acid stimulation translates into an enhanced biological function, that is an almost complete growth inhibition of the two lysozyme-sensitive Gram-positive bacteria tested.