Research Event

Event participants

HE Nana Akufo-Addo, President of the Republic of Ghana
Chair: Dr Alex Vines OBE, Managing Director, Ethics, Risk & Resilience; Director, Africa Programme, Chatham House

Research Event

Event participants

Jon Temin, Director, Africa Programs, Freedom House
Chair: Rachael Jolley, Editor-in-chief, Index on Censorship 

Research Event

Event participants

Paul Mashatile, Treasurer General, African National Congress (ANC)

Research Event

Event participants

Dr Hafez Ghanem, Vice President for Africa, World Bank
Chair: Elizabeth Donnelly, Deputy Director, Africa Programme, Chatham House

Research Event

Event participants

21 April 2020

23 April 2020

1 May 2020

Research Event

Event participants

Research Event

7 May 2020 , Volume 96, Number 3

7 May 2020

Fatty acid transport protein 2 (FATP2) is highly expressed in the liver, small intestine, and kidney, where it functions in both the transport of exogenous long-chain fatty acids and the activation of very-long-chain fatty acids. Here, using a murine model, we investigated the phenotypic impacts of deleting FATP2, followed by a transcriptomic analysis using unbiased RNA-Seq to identify concomitant changes in the liver transcriptome. WT and FATP2-null (Fatp2−/−) mice (5 weeks) were maintained on a standard chow diet for 6 weeks. The Fatp2−/− mice had reduced weight gain, lowered serum triglyceride, and increased serum cholesterol levels and attenuated dietary fatty acid absorption. Transcriptomic analysis of the liver revealed 258 differentially expressed genes in male Fatp2−/− mice and a total of 91 in female Fatp2−/− mice. These genes mapped to the following gene ontology categories: fatty acid degradation, peroxisome biogenesis, fatty acid synthesis, and retinol and arachidonic acid metabolism. Targeted RT-quantitative PCR verified the altered expression of selected genes. Of note, most of the genes with increased expression were known to be regulated by peroxisome proliferator–activated receptor α (PPARα), suggesting that FATP2 activity is linked to a PPARα-specific proximal ligand. Targeted metabolomic experiments in the Fatp2−/− liver revealed increases of total C16:0, C16:1, and C18:1 fatty acids; increases in lipoxin A4 and prostaglandin J2; and a decrease in 20-hydroxyeicosatetraenoic acid. We conclude that the expression of FATP2 in the liver broadly affects the metabolic landscape through PPARα, indicating that FATP2 provides an important role in liver lipid metabolism through its transport or activation activities.

Leukocyte recruitment is a universal feature of tissue inflammation and regulated by the interactions of chemokines with their G protein–coupled receptors. Activation of CC chemokine receptor 2 (CCR2) by its cognate chemokine ligands, including CC chemokine ligand 2 (CCL2), plays a central role in recruitment of monocytes in several inflammatory diseases. In this study, we used phosphoproteomics to conduct an unbiased characterization of the signaling network resulting from CCL2 activation of CCR2. Using data-independent acquisition MS analysis, we quantified both the proteome and phosphoproteome in FlpIn-HEK293T cells stably expressing CCR2 at six time points after activation with CCL2. Differential expression analysis identified 699 significantly regulated phosphorylation sites on 441 proteins. As expected, many of these proteins are known to participate in canonical signal transduction pathways and in the regulation of actin cytoskeleton dynamics, including numerous guanine nucleotide exchange factors and GTPase-activating proteins. Moreover, we identified regulated phosphorylation sites in numerous proteins that function in the nucleus, including several constituents of the nuclear pore complex. The results of this study provide an unprecedented level of detail of CCR2 signaling and identify potential targets for regulation of CCR2 function.

In bottom-up, label-free discovery proteomics, biological samples are acquired in a data-dependent (DDA) or data-independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance and lead to false positive or false negative conclusions.

We hypothesized that the combined use of MS1 and MS2 quantitative signals could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2-combined method increased the coverage of known activated pathways.

Since recent technological developments continue to increase the quality of MS1 signals (e.g. using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.

Top-down proteomics studies intact proteoform mixtures and offers important advantages over more common bottom-up proteomics technologies, as it avoids the protein inference problem. However, achieving complete molecular characterization of investigated proteoforms using existing technologies remains a fundamental challenge for top-down proteomics. Here, we benchmark the performance of ultraviolet photodissociation (UVPD) using 213 nm photons generated by a solid-state laser applied to the study of intact proteoforms from three organisms. Notably, the described UVPD setup applies multiple laser pulses to induce ion dissociation, and this feature can be used to optimize the fragmentation outcome based on the molecular weight of the analyzed biomolecule. When applied to complex proteoform mixtures in high-throughput top-down proteomics, 213 nm UVPD demonstrated a high degree of complementarity with the most employed fragmentation method in proteomics studies, higher-energy collisional dissociation (HCD). UVPD at 213 nm offered higher average proteoform sequence coverage and degree of proteoform characterization (including localization of post-translational modifications) than HCD. However, previous studies have shown limitations in applying database search strategies developed for HCD fragmentation to UVPD spectra which contains up to nine fragment ion types. We therefore performed an analysis of the different UVPD product ion type frequencies. From these data, we developed an ad hoc fragment matching strategy and determined the influence of each possible ion type on search outcomes. By paring down the number of ion types considered in high-throughput UVPD searches from all types down to the four most abundant, we were ultimately able to achieve deeper proteome characterization with UVPD. Lastly, our detailed product ion analysis also revealed UVPD cleavage propensities and determined the presence of a product ion produced specifically by 213 nm photons. All together, these observations could be used to better elucidate UVPD dissociation mechanisms and improve the utility of the technique for proteomic applications.

The presentation of peptides on class I human leukocyte antigen (HLA-I) molecules plays a central role in immune recognition of infected or malignant cells. In cancer, non-self HLA-I ligands can arise from many different alterations, including non-synonymous mutations, gene fusion, cancer-specific alternative mRNA splicing or aberrant post-translational modifications. Identifying HLA-I ligands remains a challenging task that requires either heavy experimental work for in vivo identification or optimized bioinformatics tools for accurate predictions. To date, no HLA-I ligand predictor includes post-translational modifications. To fill this gap, we curated phosphorylated HLA-I ligands from several immunopeptidomics studies (including six newly measured samples) covering 72 HLA-I alleles and retrieved a total of 2,066 unique phosphorylated peptides. We then expanded our motif deconvolution tool to identify precise binding motifs of phosphorylated HLA-I ligands. Our results reveal a clear enrichment of phosphorylated peptides among HLA-C ligands and demonstrate a prevalent role of both HLA-I motifs and kinase motifs on the presentation of phosphorylated peptides. These data further enabled us to develop and validate the first predictor of interactions between HLA-I molecules and phosphorylated peptides.

The blue mold fungus, Penicillium expansum, is a postharvest apple pathogen that contributes to food waste by rotting fruit and by producing harmful mycotoxins (e.g. patulin). To identify genes controlling pathogen virulence, a random T-DNA insertional library was created from wild-type P. expansum strain R19. One transformant, T625, had reduced virulence in apples, blistered mycelial hyphae, and a T-DNA insertion that abolished transcription of the single copy locus in which it was inserted. The gene, Blistering1, encodes a protein with a DnaJ domain, but otherwise has little homology outside the Aspergillaceae, a family of fungi known for producing antibiotics, mycotoxins, and cheese. Because protein secretion is critical for these processes and for host infection, mass spectrometry was used to monitor proteins secreted into liquid media during fungal growth. T625 failed to secrete a set of enzymes that degrade plant cell walls, along with ones that synthesize the three final biosynthetic steps of patulin. Consequently, the culture broth of T625 had significantly reduced capacity to degrade apple tissue and contained 30 times less patulin. Quantitative mass spectrometry of 3,282 mycelial proteins revealed that T625 had altered cellular networks controlling protein processing in the endoplasmic reticulum, protein export, vesicle-mediated transport, and endocytosis. T625 also had reduced proteins controlling mRNA surveillance and RNA processing. Transmission electron microscopy of hyphal cross sections confirmed that T625 formed abnormally enlarged endosomes or vacuoles. These data reveal that Blistering1 affects internal and external protein processing involving vesicle-mediated transport in a family of fungi with medical, commercial, and agricultural importance.

Aberrantly high mTORC1 signaling is a known driver of many cancers and human disorders, yet pharmacological inhibition of mTORC1 rarely confers durable clinical responses. To explore alternative therapeutic strategies, herein we conducted a proteomics survey to identify cell surface proteins upregulated by mTORC1. A comparison of the surfaceome from Tsc1^–/– versus Tsc1^+/+ mouse embryonic fibroblasts revealed 59 proteins predicted to be significantly overexpressed in Tsc1^–/– cells. Further validation of the data in multiple mouse and human cell lines showed that mTORC1 signaling most dramatically induced the expression of the proteases neprilysin (NEP/CD10) and aminopeptidase N (APN/CD13). Functional studies showed that constitutive mTORC1 signaling sensitized cells to genetic ablation of NEP and APN, as well as the biochemical inhibition of APN. In summary, these data show that mTORC1 signaling plays a significant role in the constitution of the surfaceome, which in turn may present novel therapeutic strategies.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with very limited therapeutic options. We have recently shown that the combined inhibition of EGFR and ROCK in TNBC cells results in cell death, however, the underlying mechanisms remain unclear. To investigate this, here we applied a mass spectrometry-based proteomic approach to identify proteins altered on single and combination treatments. Our proteomic data revealed autophagy as the major molecular mechanism implicated in the cells' response to combinatorial treatment. We here show that EGFR inhibition by gefitinib treatment alone induces autophagy, a cellular recycling process that acts as a cytoprotective response for TNBC cells. However, combined inhibition of EGFR and ROCK leads to autophagy blockade and accumulation of autophagic vacuoles. Our data show impaired autophagosome clearance as a likely cause of antitumor activity. We propose that the inhibition of the autophagic flux on combinatorial treatment is attributed to the major cytoskeletal changes induced on ROCK inhibition, given the essential role the cytoskeleton plays throughout the various steps of the autophagy process.

Triple-negative breast cancer (TNBC) is characterized by poor response to therapy and low overall patient survival. Recently, Estrogen Receptor beta (ERβ) has been found to be expressed in a fraction of TNBCs where, because of its oncosuppressive actions on the genome, it represents a potential therapeutic target, provided a better understanding of its actions in these tumors becomes available. To this end, the cell lines Hs 578T, MDA-MB-468 and HCC1806, representing the claudin-low, basal-like 1 and 2 TNBC molecular subtypes respectively, were engineered to express ERβ under the control of a Tetracycline-inducible promoter and used to investigate the effects of this transcription factor on gene activity. The antiproliferative effects of ERβ in these cells were confirmed by multiple functional approaches, including transcriptome profiling and global mapping of receptor binding sites in the genome, that revealed direct negative regulation by ERβ of genes, encoding for key components of cellular pathways associated to TNBC aggressiveness representing novel therapeutic targets such as angiogenesis, invasion, metastasis and cholesterol biosynthesis. Supporting these results, interaction proteomics by immunoprecipitation coupled to nano LC-MS/MS mass spectrometry revealed ERβ association with several potential nuclear protein partners, including key components of regulatory complexes known to control chromatin remodeling, transcriptional and post-transcriptional gene regulation and RNA splicing. Among these, ERβ association with the Polycomb Repressor Complexes 1 and 2 (PRC1/2), known for their central role in gene regulation in cancer cells, was confirmed in all three TNBC subtypes investigated, suggesting its occurrence independently from the cellular context. These results demonstrate a significant impact of ERβ in TNBC genome activity mediated by its cooperation with regulatory multiprotein chromatin remodeling complexes, providing novel ground to devise new strategies for the treatment of these diseases based on ligands affecting the activity of this nuclear receptor or some of its protein partners.

Mycobacterial Ser/Thr protein kinases (STPKs) play a critical role in signal transduction pathways that ultimately determine mycobacterial growth and metabolic adaptation. Identification of key physiological substrates of these protein kinases is, therefore, crucial to better understand how Ser/Thr phosphorylation contributes to mycobacterial environmental adaptation, including response to stress, cell division, and host-pathogen interactions. Various substrate detection methods have been employed with limited success, with direct targets of STPKs remaining elusive. Recently developed mass spectrometry (MS)-based phosphoproteomic approaches have expanded the list of potential STPK substrate identifications, yet further investigation is required to define the most functionally significant phosphosites and their physiological importance. Prior to the application of MS workflows, for instance, GarA was the only known and validated physiological substrate for protein kinase G (PknG) from pathogenic mycobacteria. A subsequent list of at least 28 candidate PknG substrates has since been reported with the use of MS-based analyses. Herein, we integrate and critically review MS-generated datasets available on novel STPK substrates and report new functional and subcellular localization enrichment analyses on novel candidate protein kinase A (PknA), protein kinase B (PknB) and PknG substrates to deduce the possible physiological roles of these kinases. In addition, we assess substrate specificity patterns across different mycobacterial STPKs by analyzing reported sets of phosphopeptides, in order to determine whether novel motifs or consensus regions exist for mycobacterial Ser/Thr phosphorylation sites. This review focuses on MS-based techniques employed for STPK substrate identification in mycobacteria, while highlighting the advantages and challenges of the various applications.

Proteins that bind carbohydrate structures can serve as tools to quantify or localize specific glycans in biological specimens. Such proteins, including lectins and glycan-binding antibodies, are particularly valuable if accurate information is available about the glycans that a protein binds. Glycan arrays have been transformational for uncovering rich information about the nuances and complexities of glycan-binding specificity. A challenge, however, has been the analysis of the data. Because protein-glycan interactions are so complex, simplistic modes of analyzing the data and describing glycan-binding specificities have proven inadequate in many cases. This review surveys the methods for handling high-content data on protein-glycan interactions. We contrast the approaches that have been demonstrated and provide an overview of the resources that are available. We also give an outlook on the promising experimental technologies for generating new insights into protein-glycan interactions, as well as a perspective on the limitations that currently face the field.

Protein-protein interactions play a vital role in nearly all cellular functions. Hence, understanding their interaction patterns and three-dimensional structural conformations can provide crucial insights about various biological processes and underlying molecular mechanisms for many disease phenotypes. Cross-linking mass spectrometry (XL-MS) has the unique capability to detect protein-protein interactions at a large scale along with spatial constraints between interaction partners. The inception of MS-cleavable cross-linkers enabled the MS2-MS3 XL-MS acquisition strategy that provides cross-link information from both MS2 and MS3 level. However, the current cross-link search algorithm available for MS2-MS3 strategy follows a "MS2-centric" approach and suffers from a high rate of mis-identified cross-links. We demonstrate the problem using two new quality assessment metrics ["fraction of mis-identifications" (FMI) and "fraction of interprotein cross-links from known interactions" (FKI)]. We then address this problem, by designing a novel "MS3-centric" approach for cross-link identification and implementing it as a search engine named MaXLinker. MaXLinker outperforms the currently popular search engine with a lower mis-identification rate, and higher sensitivity and specificity. Moreover, we performed human proteome-wide cross-linking mass spectrometry using K562 cells. Employing MaXLinker, we identified a comprehensive set of 9319 unique cross-links at 1% false discovery rate, comprising 8051 intraprotein and 1268 interprotein cross-links. Finally, we experimentally validated the quality of a large number of novel interactions identified in our study, providing a conclusive evidence for MaXLinker's robust performance.

The use of protein biomarkers as surrogates for clinical endpoints requires extensive multilevel validation including development of robust and sensitive assays for precise measurement of protein concentration. Multiple reaction monitoring (MRM) is a well-established mass-spectrometric method that can be used for reproducible protein-concentration measurements in biological specimens collected via microsampling. The dried blood spot (DBS) microsampling technique can be performed non-invasively without the expertise of a phlebotomist, and can enhance analyte stability which facilitate the application of this technique in retrospective studies while providing lower storage and shipping costs, because cold-chain logistics can be eliminated. Thus, precise, sensitive, and multiplexed methods for measuring protein concentrations in DBSs can be used for de novo biomarker discovery and for biomarker quantification or verification experiments. To achieve this goal, MRM assays were developed for multiplexed concentration measurement of proteins in DBSs.

The lower limit of quantification (LLOQ) was found to have a median total coefficient of variation (CV) of 18% for 245 proteins, whereas the median LLOQ was 5 fmol of peptide injected on column, and the median inter-day CV over 4 days for measuring endogenous protein concentration was 8%. The majority (88%) of the assays displayed parallelism, whereas the peptide standards remained stable throughout the assay workflow and after exposure to multiple freeze-thaw cycles. For 190 proteins, the measured protein concentrations remained stable in DBS stored at ambient laboratory temperature for up to 2 months. Finally, the developed assays were used to measure the concentration ranges for 200 proteins in twenty same sex, same race and age matched individuals.

Glycosylation is a common modification of proteins and critical for a wide range of biological processes. Differences in protein glycosylation between sexes have already been observed in humans, nematodes and trematodes, and have recently also been reported in the rice pest insect Nilaparvata lugens. Although protein N-glycosylation in insects is nowadays of high interest because of its potential for exploitation in pest control strategies, the functionality of differential N-glycosylation between sexes is yet unknown. In this study, therefore, the occurrence and role of sex-related protein N-glycosylation in insects were examined. A comprehensive investigation of the N-glycosylation sites from the adult stages of N. lugens was conducted, allowing a qualitative and quantitative comparison between sexes at the glycopeptide level. N-glycopeptide enrichment via lectin capturing using the high mannose/paucimannose-binding lectin Concanavalin A, or the Rhizoctonia solani agglutinin which interacts with complex N-glycans, resulted in the identification of over 1300 N-glycosylation sites derived from over 600 glycoproteins. Comparison of these N-glycopeptides revealed striking differences in protein N-glycosylation between sexes. Male- and female-specific N-glycosylation sites were identified, and some of these sex-specific N-glycosylation sites were shown to be derived from proteins with a putative role in insect reproduction. In addition, differential glycan composition between males and females was observed for proteins shared across sexes. Both lectin blotting experiments as well as transcript expression analyses with complete insects and insect tissues confirmed the observed differences in N-glycosylation of proteins between sexes. In conclusion, this study provides further evidence for protein N-glycosylation to be sex-related in insects. Furthermore, original data on N-glycosylation sites of N. lugens adults are presented, providing novel insights into planthopper's biology and information for future biological pest control strategies.

Mass spectrometry (MS) and proteomics offer comprehensive characterization and identification of microorganisms and discovery of protein biomarkers that are applicable for diagnostics of infectious diseases. The use of biomarkers for diagnostics is widely applied in the clinic and the use of peptide biomarkers is increasingly being investigated for applications in the clinical laboratory. Respiratory-tract infections are a predominant cause for medical treatment, although, clinical assessments and standard clinical laboratory protocols are time-consuming and often inadequate for reliable diagnoses. Novel methods, preferably applied directly to clinical samples, excluding cultivation steps, are needed to improve diagnostics of infectious diseases, provide adequate treatment and reduce the use of antibiotics and associated development of antibiotic resistance. This study applied nano-liquid chromatography (LC) coupled with tandem MS, with a bioinformatics pipeline and an in-house database of curated high-quality reference genome sequences to identify species-unique peptides as potential biomarkers for four bacterial pathogens commonly found in respiratory tract infections (RTIs): Staphylococcus aureus; Moraxella catarrhalis; Haemophilus influenzae and Streptococcus pneumoniae. The species-unique peptides were initially identified in pure cultures of bacterial reference strains, reflecting the genomic variation in the four species and, furthermore, in clinical respiratory tract samples, without prior cultivation, elucidating proteins expressed in clinical conditions of infection. For each of the four bacterial pathogens, the peptide biomarker candidates most predominantly found in clinical samples, are presented. Data are available via ProteomeXchange with identifier PXD014522. As proof-of-principle, the most promising species-unique peptides were applied in targeted tandem MS-analyses of clinical samples and their relevance for identifications of the pathogens, i.e. proteotyping, was validated, thus demonstrating their potential as peptide biomarker candidates for diagnostics of infectious diseases.

Chronic hyperglycemia is known to disrupt the proteolytic milieu, initiating compensatory and maladaptive pathways in the diabetic kidney. Such changes in intrarenal proteolysis are captured by the urinary peptidome. To elucidate the early kidney response to chronic hyperglycemia, we conducted a peptidomic investigation into urines from otherwise healthy youths with type 1 diabetes and their non-diabetic peers using unbiased and targeted mass spectrometry-based techniques. This cross-sectional study included two separate cohorts for the discovery (n = 30) and internal validation (n = 30) of differential peptide excretion. Peptide bioactivity was predicted using PeptideRanker and subsequently verified in vitro. Proteasix and the Nephroseq database were used to identify putative proteases responsible for peptide generation and examine their expression in diabetic nephropathy. A total of 6550 urinary peptides were identified in the discovery analysis. We further examined the subset of 162 peptides, which were quantified across all thirty samples. Of the 15 differentially excreted peptides (p < 0.05), seven derived from a C-terminal region (⁵⁸⁹SGSVIDQSRVLNLGPITRK⁶⁰⁷) of uromodulin, a kidney-specific protein. Increased excretion of five uromodulin peptides was replicated in the validation cohort using parallel reaction monitoring (p < 0.05). One of the validated peptides (SGSVIDQSRVLNLGPI) activated NFB and AP-1 signaling, stimulated cytokine release, and enhanced neutrophil migration in vitro. In silico analyses highlighted several potential proteases such as hepsin, meprin A, and cathepsin B to be responsible for generating these peptides. In summary, we identified a urinary signature of uromodulin peptides associated with early type 1 diabetes before clinical manifestations of kidney disease and discovered novel bioactivity of uromodulin peptides in vitro. Our present findings lay the groundwork for future studies to validate peptide excretion in larger and broader populations, to investigate the role of bioactive uromodulin peptides in high glucose conditions, and to examine proteases that cleave uromodulin.

Lung cancer (LC) remains the leading cause of mortality from malignant tumors worldwide. In our previous study, we surveyed both IgG and IgM-bound serological biomarkers and validated a panel of IgG-bound autoantigens for early LC diagnosis with 50% sensitivity at 90% specificity. To further improve the performance of these serological biomarkers, we surveyed HuProt arrays, comprised of 20,240 human proteins, for IgA-bound autoantigens because IgAs are a major immunoglobulin isotype in the lung. Integrating with IgG-bound autoantigens, we discovered and validated a combined biomarker panel using ELISA-format tests. Specifically, in Phase I, we obtained IgA-based autoimmune profiles of 69 early stage LC patients, 30 healthy subjects and 25 patients with lung benign lesions (LBL) on HuProt arrays and identified 28 proteins as candidate autoantigens that were significantly associated with early stage LC. In Phase II, we re-purified the autoantigens and converted them into an ELISA-format testing to profile an additional large cohort, comprised of 136 early stage LC patients, 58 healthy individuals, and 29 LBL patients. Integration of IgG autoimmune profiles allowed us to identify and validate a biomarker panel of three IgA autoantigens (i.e. BCL7A, and TRIM33 and MTERF4) and three IgG autoantigens (i.e. CTAG1A, DDX4 and MAGEC2) for diagnosis of early stage LC with 73.5% sensitivity at >85% specificity. In Phase III, the performance of this biomarker panel was confirmed with an independent cohort, comprised of 88 early stage LC patients, 18 LBL patients, and 36 healthy subjects. Finally, a blind test on 178 serum samples was conducted to confirm the performance of the biomarker panel. In summary, this study demonstrates for the first time that an integrated panel of IgA/IgG autoantigens can serve as valuable biomarkers to further improve the performance of early diagnosis of LC.

The prediction of metastatic properties from molecular analyses still poses a major challenge. Here we aimed at the classification of metastasis-related cell properties by proteome profiling making use of cutaneous and brain-metastasizing variants from single melanomas sharing the same genetic ancestry. Previous experiments demonstrated that cultured cells derived from these xenografted variants maintain a stable phenotype associated with a differential metastatic behavior: The brain metastasizing variants produce more spontaneous micro-metastases than the corresponding cutaneous variants. Four corresponding pairs of cutaneous and metastatic cells were obtained from four individual patients, resulting in eight cell-lines presently investigated. Label free proteome profiling revealed significant differences between corresponding pairs of cutaneous and cerebellar metastases from the same patient. Indeed, each brain metastasizing variant expressed several apparently metastasis-associated proteomic alterations as compared with the corresponding cutaneous variant. Among the differentially expressed proteins we identified cell adhesion molecules, immune regulators, epithelial to mesenchymal transition markers, stem cell markers, redox regulators and cytokines. Similar results were observed regarding eicosanoids, considered relevant for metastasis, such as PGE2 and 12-HETE. Multiparametric morphological analysis of cells also revealed no characteristic alterations associated with the cutaneous and brain metastasis variants. However, no correct classification regarding metastatic potential was yet possible with the present data. We thus concluded that molecular profiling is able to classify cells according to known functional categories but is not yet able to predict relevant cell properties emerging from networks consisting of many interconnected molecules. The presently observed broad diversity of molecular patterns, irrespective of restricting to one tumor type and two main classes of metastasis, highlights the important need to develop meta-analysis strategies to predict cell properties from molecular profiling data. Such base knowledge will greatly support future individualized precision medicine approaches.

Adenosine monophosphate-activated protein kinase (AMPK) is an obligate heterotrimer that consists of a catalytic subunit (α) and two regulatory subunits (β and ). AMPK is a key enzyme in the regulation of cellular energy homeostasis. It has been well studied and is known to function in many cellular pathways. However, the interactome of AMPK has not yet been systematically established, although protein-protein interaction is critically important for protein function and regulation. Here, we used tandem-affinity purification, coupled with mass spectrometry (TAP-MS) analysis, to determine the interactome of AMPK and its functions. We conducted a TAP-MS analysis of all seven AMPK subunits. We identified 138 candidate high-confidence interacting proteins (HCIPs) of AMPK, which allowed us to build an interaction network of AMPK complexes. Five candidate AMPK-binding proteins were experimentally validated, underlining the reliability of our data set. Furthermore, we demonstrated that AMPK acts with a strong AMPK-binding protein, Artemis, in non-homologous end joining. Collectively, our study established the first AMPK interactome and uncovered a new function of AMPK in DNA repair.

Recurrent urinary tract infections (UTIs) pose a significant burden on the health care system. Underlying mechanisms predisposing children to UTIs and associated changes in the urinary proteome are not well understood. We aimed to investigate the urinary proteome of a subset of children who have vesicoureteral reflux (VUR) and recurrent UTIs because of their risk of developing infection-related renal damage. Improving diagnostic modalities to identify UTI risk factors would significantly alter the clinical management of children with VUR. We profiled the urinary proteomes of 22 VUR patients with low grade VUR (1–3 out of 5), a history of recurrent UTIs, and renal scarring, comparing them to those obtained from 22 age-matched controls. Urinary proteins were analyzed by mass spectrometry followed by protein quantitation based on spectral counting. Of the 2,551 proteins identified across both cohorts, 964 were robustly quantified, as defined by meeting criteria with spectral count (SC) ≥2 in at least 7 patients in either VUR or control cohort. Eighty proteins had differential expression between the two cohorts, with 44 proteins significantly up-regulated and 36 downregulated (q <0.075, FC ≥1.2). Urinary proteins involved in inflammation, acute phase response (APR), modulation of extracellular matrix (ECM), and carbohydrate metabolism were altered among the study cohort.

Male infertility is widespread and estimated to affect 1 in 20 men. Although in some cases the etiology of the condition is well understood, for at least 50% of men, the underlying cause is yet to be classified. Male infertility, or subfertility, is often diagnosed by looking at total sperm produced, motility of the cells and overall morphology. Although counting spermatozoa and their associated motility is routine, morphology assessment is highly subjective, mainly because of the procedure being based on microscopic examination. A failure to diagnose male-infertility or sub-fertility has led to a situation where assisted conception is often used unnecessarily. As such, biomarkers of male infertility are needed to help establish a more consistent diagnosis. In the present study, we compared nuclear extracts from both high- and low-quality spermatozoa by LC-MS/MS based proteomic analysis. Our data shows that nuclear retention of specific proteins is a common facet among low-quality sperm cells. We demonstrate that the presence of Topoisomerase 2A in the sperm head is highly correlated to poor head morphology. Topoisomerase 2A is therefore a potential new biomarker for confirming male infertility in clinical practice.

For more than two decades naturally presented, human leukocyte antigen (HLA)-restricted peptides (immunopeptidome) have been eluted and sequenced using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Since, identified disease-associated HLA ligands have been characterized and evaluated as potential active substances. Treatments based on HLA-presented peptides have shown promising results in clinical application as personalized T cell-based immunotherapy. Peptide vaccination cocktails are produced as investigational medicinal products under GMP conditions. To support clinical trials based on HLA-presented tumor-associated antigens, in this study the sensitive LC-MS/MS HLA class I antigen identification pipeline was fully validated for our technical equipment according to the current US Food and Drug Administration (FDA) and European Medicines Agency (EMA) guidelines.

The immunopeptidomes of JY cells with or without spiked-in, isotope labeled peptides, of peripheral blood mononuclear cells of healthy volunteers as well as a chronic lymphocytic leukemia and a bladder cancer sample were reliably identified using a data-dependent acquisition method. As the LC-MS/MS pipeline is used for identification purposes, the validation parameters include accuracy, precision, specificity, limit of detection and robustness.

Dynamic tyrosine phosphorylation is fundamental to a myriad of cellular processes. However, the inherently low abundance of tyrosine phosphorylation in the proteome and the inefficient enrichment of phosphotyrosine(pTyr)-containing peptides has led to poor pTyr peptide identification and quantitation, critically hindering researchers' ability to elucidate signaling pathways regulated by tyrosine phosphorylation in systems where cellular material is limited. The most popular approaches to wide-scale characterization of the tyrosine phosphoproteome use pTyr enrichment with pan-specific, anti-pTyr antibodies from a large amount of starting material. Methods that decrease the amount of starting material and increase the characterization depth of the tyrosine phosphoproteome while maintaining quantitative accuracy and precision would enable the discovery of tyrosine phosphorylation networks in rarer cell populations. To achieve these goals, the BOOST (Broad-spectrum Optimization Of Selective Triggering) method leveraging the multiplexing capability of tandem mass tags (TMT) and the use of pervanadate (PV) boost channels (cells treated with the broad-spectrum tyrosine phosphatase inhibitor PV) selectively increased the relative abundance of pTyr-containing peptides. After PV boost channels facilitated selective fragmentation of pTyr-containing peptides, TMT reporter ions delivered accurate quantitation of each peptide for the experimental samples while the quantitation from PV boost channels was ignored. This method yielded up to 6.3-fold boost in pTyr quantification depth of statistically significant data derived from contrived ratios, compared with TMT without PV boost channels or intensity-based label-free (LF) quantitation while maintaining quantitative accuracy and precision, allowing quantitation of over 2300 unique pTyr peptides from only 1 mg of T cell receptor-stimulated Jurkat T cells. The BOOST strategy can potentially be applied in analyses of other post-translational modifications where treatments that broadly elevate the levels of those modifications across the proteome are available.

State-of-the-art proteomics-grade mass spectrometers can measure peptide precursors and their fragments with ppm mass accuracy at sequencing speeds of tens of peptides per second with attomolar sensitivity. Here we describe a compact and robust quadrupole-orbitrap mass spectrometer equipped with a front-end High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Interface. The performance of the Orbitrap Exploris 480 mass spectrometer is evaluated in data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes in combination with FAIMS. We demonstrate that different compensation voltages (CVs) for FAIMS are optimal for DDA and DIA, respectively. Combining DIA with FAIMS using single CVs, the instrument surpasses 2500 peptides identified per minute. This enables quantification of >5000 proteins with short online LC gradients delivered by the Evosep One LC system allowing acquisition of 60 samples per day. The raw sensitivity of the instrument is evaluated by analyzing 5 ng of a HeLa digest from which >1000 proteins were reproducibly identified with 5 min LC gradients using DIA-FAIMS. To demonstrate the versatility of the instrument, we recorded an organ-wide map of proteome expression across 12 rat tissues quantified by tandem mass tags and label-free quantification using DIA with FAIMS to a depth of >10,000 proteins.

We present a technological advancement for the estimation of the affinities of Protein-Protein Interactions (PPIs) in living cells. A novel set of vectors is introduced that enables a quantitative yeast two-hybrid system based on fluorescent fusion proteins. The vectors allow simultaneous quantification of the reaction partners (Bait and Prey) and the reporter at the single-cell level by flow cytometry. We validate the applicability of this system on a small but diverse set of PPIs (eleven protein families from six organisms) with different affinities; the dissociation constants range from 117 pm to 17 μm. After only two hours of reaction, expression of the reporter can be detected even for the weakest PPI. Through a simple gating analysis, it is possible to select only cells with identical expression levels of the reaction partners. As a result of this standardization of expression levels, the mean reporter levels directly reflect the affinities of the studied PPIs. With a set of PPIs with known affinities, it is straightforward to construct an affinity ladder that permits rapid classification of PPIs with thus far unknown affinities. Conventional software can be used for this analysis. To permit automated analysis, we provide a graphical user interface for the Python-based FlowCytometryTools package.

Protein phosphorylation cascades play a central role in the regulation of cell growth and protein kinases PKA, Sch9 and Ypk1 take center stage in regulating this process in S. cerevisiae. To understand how these kinases co-ordinately regulate cellular functions we compared the phospho-proteome of exponentially growing cells without and with acute chemical inhibition of PKA, Sch9 and Ypk1. Sites hypo-phosphorylated upon PKA and Sch9 inhibition were preferentially located in RRxS/T-motifs suggesting that many are directly phosphorylated by these enzymes. Interestingly, when inhibiting Ypk1 we not only detected several hypo-phosphorylated sites in the previously reported RxRxxS/T-, but also in an RRxS/T-motif. Validation experiments revealed that neutral trehalase Nth1, a known PKA target, is additionally phosphorylated and activated downstream of Ypk1. Signaling through Ypk1 is therefore more closely related to PKA- and Sch9-signaling than previously appreciated and may perform functions previously only attributed to the latter kinases.

An experimental and computational approach for identification of protein-protein interactions by ex vivo chemical crosslinking and mass spectrometry (CLMS) has been developed that takes advantage of the specific characteristics of cyanurbiotindipropionylsuccinimide (CBDPS), an affinity-tagged isotopically coded mass spectrometry (MS)-cleavable crosslinking reagent. Utilizing this reagent in combination with a crosslinker-specific data-dependent acquisition strategy based on MS2 scans, and a software pipeline designed for integrating crosslinker-specific mass spectral information led to demonstrated improvements in the application of the CLMS technique, in terms of the detection, acquisition, and identification of crosslinker-modified peptides. This approach was evaluated on intact yeast mitochondria, and the results showed that hundreds of unique protein-protein interactions could be identified on an organelle proteome-wide scale. Both known and previously unknown protein-protein interactions were identified. These interactions were assessed based on their known sub-compartmental localizations. Additionally, the identified crosslinking distance constraints are in good agreement with existing structural models of protein complexes involved in the mitochondrial electron transport chain.

The cell cycle is a highly conserved process involving the coordinated separation of a single cell into two daughter cells. To relate transcriptional regulation across the cell cycle with oscillatory changes in protein abundance and activity, we carried out a proteome- and phospho-proteome-wide mass spectrometry profiling. We compared protein dynamics with gene transcription, revealing many transcriptionally regulated G2 mRNAs that only produce a protein shift after mitosis. Integration of CRISPR/Cas9 survivability studies further highlighted proteins essential for cell viability. Analyzing the dynamics of phosphorylation events and protein solubility dynamics over the cell cycle, we characterize predicted phospho-peptide motif distributions and predict cell cycle-dependent translocating proteins, as exemplified by the S-adenosylmethionine synthase MAT2A. Our study implicates this enzyme in translocating to the nucleus after the G1/S-checkpoint, which enables epigenetic histone methylation maintenance during DNA replication. Taken together, this data set provides a unique integrated resource with novel insights on cell cycle dynamics.

In osteoarthritis (OA), impairment of cartilage regeneration can be related to a defective chondrogenic differentiation of mesenchymal stromal cells (MSCs). Therefore, understanding the proteomic- and metabolomic-associated molecular events during the chondrogenesis of MSCs could provide alternative targets for therapeutic intervention. Here, a SILAC-based proteomic analysis identified 43 proteins related with metabolic pathways whose abundance was significantly altered during the chondrogenesis of OA human bone marrow MSCs (hBMSCs). Then, the level and distribution of metabolites was analyzed in these cells and healthy controls by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), leading to the recognition of characteristic metabolomic profiles at the early stages of differentiation. Finally, integrative pathway analysis showed that UDP-glucuronic acid synthesis and amino sugar metabolism were downregulated in OA hBMSCs during chondrogenesis compared with healthy cells. Alterations in these metabolic pathways may disturb the production of hyaluronic acid (HA) and other relevant cartilage extracellular matrix (ECM) components. This work provides a novel integrative insight into the molecular alterations of osteoarthritic MSCs and potential therapeutic targets for OA drug development through the enhancement of chondrogenesis.

Systemic infection and proliferation of intracellular pathogens require the biogenesis of a growth-stimulating compartment. The gastrointestinal pathogen Salmonella enterica commonly forms highly dynamic and extensive tubular membrane compartments built from Salmonella-modified membranes (SMMs) in diverse host cells. Although the general mechanism involved in the formation of replication-permissive compartments of S. enterica is well researched, much less is known regarding specific adaptations to different host cell types. Using an affinity-based proteome approach, we explored the composition of SMMs in murine macrophages. The systematic characterization provides a broader landscape of host players to the maturation of Salmonella-containing compartments and reveals core host elements targeted by Salmonella in macrophages as well as epithelial cells. However, we also identified subtle host specific adaptations. Some of these observations, such as the differential involvement of the COPII system, Rab GTPases 2A, 8B, 11 and ER transport proteins Sec61 and Sec22B may explain cell line-dependent variations in the pathophysiology of Salmonella infections. In summary, our system-wide approach demonstrates a hitherto underappreciated impact of the host cell type in the formation of intracellular compartments by Salmonella.

Human leukocyte antigen (HLA) B*51:01 and endoplasmic reticulum aminopeptidase 1 (ERAP1) are strongly genetically associated with Behcet's disease (BD). Previous studies have defined two subgroups of HLA-B*51 peptidome containing proline (Pro) or alanine (Ala) at position 2 (P2). Little is known about the unconventional non-Pro/Ala2 HLA-B*51-bound peptides. We aimed to study the features of this novel subpeptidome, and investigate its regulation by ERAP1. CRISPR-Cas9 was used to generate an HLA-ABC-triple knockout HeLa cell line (HeLa.ABC-KO), which was subsequently transduced to express HLA-B*51:01 (HeLa.ABC-KO.B51). ERAP1 was silenced using lentiviral shRNA. Peptides bound to HLA-B*51:01 were eluted and analyzed by mass spectrometry. The characteristics of non-Pro/Ala2, Pro2, and Ala2 peptides and their alteration by ERAP1 silencing were investigated. Effects of ERAP1 silencing on cell surface expression of HLA-B*51:01 were studied using flow cytometry. More than 20% of peptides eluted from HLA-B*51:01 lacked Pro or Ala at P2. This unconventional group of HLA-B*51:01-bound peptides was relatively enriched for 8-mers (with relatively fewer 9-mers) compared with the Pro2 and Ala2 subpeptidomes and had similar N-terminal and C-terminal residue usages to Ala2 peptides (with the exception of the less abundant leucine at position ). Knockdown of ERAP1 increased the percentage of non-Pro/Ala2 from 20% to ~40%, increased the percentage of longer (10-mer and 11-mer) peptides eluted from HLA-B*51:01 complexes, and abrogated the predominance of leucine at P1. Interestingly knockdown of ERAP1 altered the length and N-terminal residue usage of non-Ala2&Pro2 and Ala2 but not the Pro2 peptides. Finally, ERAP1 silencing regulated the expression levels of cell surface HLA-B*51 in a cell-type-dependent manner. In conclusion, we have used a novel methodology to identify an unconventional but surprisingly abundant non-Pro/Ala2 HLA-B*51:01 subpeptidome. It is increased by knockdown of ERAP1, a gene affecting the risk of developing BD. This has implications for theories of disease pathogenesis.

The redox-based modifications of cysteine residues in proteins regulate their function in many biological processes. The gas molecule H₂S has been shown to persulfidate redox sensitive cysteine residues resulting in an H₂S-modified proteome known as the sulfhydrome. Tandem Mass Tags (TMT) multiplexing strategies for large-scale proteomic analyses have become increasingly prevalent in detecting cysteine modifications. Here we developed a TMT-based proteomics approach for selectively trapping and tagging cysteine persulfides in the cellular proteomes. We revealed the natural protein sulfhydrome of two human cell lines, and identified insulin as a novel substrate in pancreatic beta cells. Moreover, we showed that under oxidative stress conditions, increased H₂S can target enzymes involved in energy metabolism by switching specific cysteine modifications to persulfides. Specifically, we discovered a Redox Thiol Switch, from protein S-glutathioinylation to S-persulfidation (RTS^GS). We propose that the RTS^GS from S-glutathioinylation to S-persulfidation is a potential mechanism to fine tune cellular energy metabolism in response to different levels of oxidative stress.

Laser-capture microdissection (LCM) allows the visualization and isolation of morphologically distinct subpopulations of cells from heterogeneous tissue specimens. In combination with formalin-fixed and paraffin-embedded (FFPE) tissue it provides a powerful tool for retrospective and clinically relevant studies of tissue proteins in a healthy and diseased context. We first optimized the protocol for efficient LCM analysis of FFPE tissue specimens. The use of SDS containing extraction buffer in combination with the single-pot solid-phase-enhanced sample preparation (SP3) digest method gave the best results regarding protein yield and protein/peptide identifications. Microdissected FFPE human substantia nigra tissue samples (~3,000 cells) were then analyzed, using tandem mass tag (TMT) labeling and LC-MS/MS, resulting in the quantification of >5,600 protein groups. Nigral proteins were classified and analyzed by abundance, showing an enrichment of extracellular exosome and neuron-specific gene ontology (GO) terms among the higher abundance proteins. Comparison of microdissected samples with intact tissue sections, using a label-free shotgun approach, revealed an enrichment of neuronal cell type markers, such as tyrosine hydroxylase and alpha-synuclein, as well as proteins annotated with neuron-specific GO terms. Overall, this study provides a detailed protocol for laser-capture proteomics using FFPE tissue and demonstrates the efficiency of LCM analysis of distinct cell subpopulations for proteomic analysis using low sample amounts.

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100x) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ~2500 proteins and precise quantification of ~1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

The respiratory epithelium comprises polarized cells at the interface between the environment and airway tissues. Polarized apical and basolateral protein secretions are a feature of airway epithelium homeostasis. Human respiratory syncytial virus (hRSV) is a major human pathogen that primarily targets the respiratory epithelium. However, the consequences of hRSV infection on epithelium secretome polarity and content remain poorly understood. To investigate the hRSV-associated apical and basolateral secretomes, a proteomics approach was combined with an ex vivo pediatric human airway epithelial (HAE) model of hRSV infection (data are available via ProteomeXchange and can be accessed at https://www.ebi.ac.uk/pride/ with identifier PXD013661). Following infection, a skewing of apical/basolateral abundance ratios was identified for several individual proteins. Novel modulators of neutrophil and lymphocyte activation (CXCL6, CSF3, SECTM1 or CXCL16), and antiviral proteins (BST2 or CEACAM1) were detected in infected, but not in uninfected cultures. Importantly, CXCL6, CXCL16, CSF3 were also detected in nasopharyngeal aspirates (NPA) from hRSV-infected infants but not healthy controls. Furthermore, the antiviral activity of CEACAM1 against RSV was confirmed in vitro using BEAS-2B cells. hRSV infection disrupted the polarity of the pediatric respiratory epithelial secretome and was associated with immune modulating proteins (CXCL6, CXCL16, CSF3) never linked with this virus before. In addition, the antiviral activity of CEACAM1 against hRSV had also never been previously characterized. This study, therefore, provides novel insights into RSV pathogenesis and endogenous antiviral responses in pediatric airway epithelium.

The study of protein subcellular distribution, their assembly into complexes and the set of proteins with which they interact with is essential to our understanding of fundamental biological processes. Complementary to traditional assays, proximity-dependent biotinylation (PDB) approaches coupled with mass spectrometry (such as BioID or APEX) have emerged as powerful techniques to study proximal protein interactions and the subcellular proteome in the context of living cells and organisms. Since their introduction in 2012, PDB approaches have been used in an increasing number of studies and the enzymes themselves have been subjected to intensive optimization. How these enzymes have been optimized and considerations for their use in proteomics experiments are important questions. Here, we review the structural diversity and mechanisms of the two main classes of PDB enzymes: the biotin protein ligases (BioID) and the peroxidases (APEX). We describe the engineering of these enzymes for PDB and review emerging applications, including the development of PDB for coincidence detection (split-PDB). Lastly, we briefly review enzyme selection and experimental design guidelines and reflect on the labeling chemistries and their implication for data interpretation.