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Xiao-Ting Wen
Dec 17, 2020; 0:RA120.002119v1-mcp.RA120.002119
Research

Ka-Won Kang
Nov 30, 2020; 0:RA120.002169v1-mcp.RA120.002169
Research

Daniel J. Geiszler
Dec 1, 2020; 0:TIR120.002216v1-mcp.TIR120.002216
Technological Innovation and Resources

Tirsa L. E. van Westering
Dec 1, 2020; 19:2047-2067
Research

We have observed overexpression of PACS-1, a cytosolic sorting protein in primary cervical tumors. Absence of exonic mutations and overexpression at the RNA level suggested a transcriptional and/or posttranscriptional regulation. University of California Santa Cruz genome browser analysis of PACS-1 micro RNAs (miR), revealed two 8-base target sequences at the 3' terminus for hsa-miR-34a and hsa-miR-449a. Quantitative RT-PCR and Northern blotting studies showed reduced or loss of expression of the two microRNAs in cervical cancer cell lines and primary tumors, indicating dysregulation of these two microRNAs in cervical cancer. Loss of PACS-1 with siRNA or exogenous expression of hsa-miR-34a or hsa-miR-449a in HeLa and SiHa cervical cancer cell lines resulted in DNA damage response, S-phase cell cycle arrest, and reduction in cell growth. Furthermore, the siRNA studies showed that loss of PACS-1 expression was accompanied by increased nuclear γH2AX expression, Lys382-p53 acetylation, and genomic instability. PACS-1 re-expression through LNA-hsa-anti-miR-34a or -449a or through PACS-1 cDNA transfection led to the reversal of DNA damage response and restoration of cell growth. Release of cells post 24-h serum starvation showed PACS-1 nuclear localization at G1-S phase of the cell cycle. Our results therefore indicate that the loss of hsa-miR-34a and hsa-miR-449a expression in cervical cancer leads to overexpression of PACS-1 and suppression of DNA damage response, resulting in the development of chemo-resistant tumors.

RAS genes are the most commonly mutated in human cancers and play critical roles in tumor initiation, progression, and drug resistance. Identification of targets that block RAS signaling is pivotal to develop therapies for RAS-related cancer. As RAS translocation to the plasma membrane (PM) is essential for its effective signal transduction, we devised a high-content screening assay to search for genes regulating KRAS membrane association. We found that the tyrosine phosphatase PTPN2 regulates the plasma membrane localization of KRAS. Knockdown of PTPN2 reduced the proliferation and promoted apoptosis in KRAS-dependent cancer cells, but not in KRAS-independent cells. Mechanistically, PTPN2 negatively regulates tyrosine phosphorylation of KRAS, which, in turn, affects the activation KRAS and its downstream signaling. Consistently, analysis of the TCGA database demonstrates that high expression of PTPN2 is significantly associated with poor prognosis of patients with KRAS-mutant pancreatic adenocarcinoma. These results indicate that PTPN2 is a key regulator of KRAS and may serve as a new target for therapy of KRAS-driven cancer.

Mutations in the GUCY2D gene coding for the dimeric human retinal membrane guanylyl cyclase (RetGC) isozyme RetGC1 cause various forms of blindness, ranging from rod dysfunction to rod and cone degeneration. We tested how the mutations causing recessive congenital stationary night blindness (CSNB), recessive Leber's congenital amaurosis (LCA1), and dominant cone–rod dystrophy-6 (CORD6) affected RetGC1 activity and regulation by RetGC-activating proteins (GCAPs) and retinal degeneration-3 protein (RD3). CSNB mutations R666W, R761W, and L911F, as well as LCA1 mutations R768W and G982VfsX39, disabled RetGC1 activation by human GCAP1, -2, and -3. The R666W and R761W substitutions compromised binding of GCAP1 with RetGC1 in HEK293 cells. In contrast, G982VfsX39 and L911F RetGC1 retained the ability to bind GCAP1 in cyto but failed to effectively bind RD3. R768W RetGC1 did not bind either GCAP1 or RD3. The co-expression of GUCY2D allelic combinations linked to CSNB did not restore RetGC1 activity in vitro. The CORD6 mutation R838S in the RetGC1 dimerization domain strongly dominated the Ca2+ sensitivity of cyclase regulation by GCAP1 in RetGC1 heterodimer produced by co-expression of WT and the R838S subunits. It required higher Ca2+ concentrations to decelerate GCAP-activated RetGC1 heterodimer—6-fold higher than WT and 2-fold higher than the Ser838-harboring homodimer. The heterodimer was also more resistant than homodimers to inhibition by RD3. The observed biochemical changes can explain the dominant CORD6 blindness and recessive LCA1 blindness, both of which affect rods and cones, but they cannot explain the selective loss of rod function in recessive CSNB.

The kinesin-3 family contains the fastest and most processive motors of the three neuronal transport kinesin families, yet the sequence of states and rates of kinetic transitions that comprise the chemomechanical cycle and give rise to their unique properties are poorly understood. We used stopped-flow fluorescence spectroscopy and single-molecule motility assays to delineate the chemomechanical cycle of the kinesin-3, KIF1A. Our bacterially expressed KIF1A construct, dimerized via a kinesin-1 coiled-coil, exhibits fast velocity and superprocessivity behavior similar to WT KIF1A. We established that the KIF1A forward step is triggered by hydrolysis of ATP and not by ATP binding, meaning that KIF1A follows the same chemomechanical cycle as established for kinesin-1 and -2. The ATP-triggered half-site release rate of KIF1A was similar to the stepping rate, indicating that during stepping, rear-head detachment is an order of magnitude faster than in kinesin-1 and kinesin-2. Thus, KIF1A spends the majority of its hydrolysis cycle in a one-head-bound state. Both the ADP off-rate and the ATP on-rate at physiological ATP concentration were fast, eliminating these steps as possible rate-limiting transitions. Based on the measured run length and the relatively slow off-rate in ADP, we conclude that attachment of the tethered head is the rate-limiting transition in the KIF1A stepping cycle. Thus, KIF1A's activity can be explained by a fast rear-head detachment rate, a rate-limiting step of tethered-head attachment that follows ATP hydrolysis, and a relatively strong electrostatic interaction with the microtubule in the weakly bound post-hydrolysis state.

Priyanka Tripathi
Dec 30, 2020; 0:jlr.RA120001190v1-jlr.RA120001190
Research Articles

This article has been withdrawn by the authors as part of this review overlapped with the contents of Pietrangelo A and Ridgway ND. 2018. Cellular and Molecular Life Sciences. 75; 3079-98.

Mendelian randomization (MR) of lipid traits in coronary artery disease (CAD) has provided evidence for causal associations of low-density lipoprotein cholesterol (LDL-C) and triglycerides (TG) in CAD, but many lipid trait genetic variants have pleiotropic effects on other cardiovascular risk factors that may bias MR associations. The goal of this study was to evaluate pleiotropic effects of lipid trait genetic variants and to account for these effects in MR of lipid traits in CAD. We performed multivariable MR using inverse variance-weighted (IVW) and MR-Egger methods in large (n ≥ 300,000) GWAS datasets. We found that 30% of lipid trait genetic variants have effects on metabolic syndrome traits, including body mass index (BMI), type 2 diabetes (T2D), and systolic blood pressure (SBP). Nonetheless, in multivariable MR analysis, LDL-C, high-density lipoprotein cholesterol (HDL-C), TG, BMI, T2D, and SBP are independently associated with CAD, and each of these associations is robust to adjustment for directional pleiotropy. MR at loci linked to direct effects on HDL-C and TG suggests locus- and mechanism-specific causal effects of these factors on CAD.

Sphingolipids have emerged as bioactive lipids involved in the regulation of many physiological and pathological processes. In the retina, they have been established to participate in numerous processes, such as neuronal survival and death, proliferation and migration of neuronal and vascular cells, inflammation, and neovascularization. Dysregulation of sphingolipids is, therefore, crucial in the onset and progression of retinal diseases. This review examines the involvement of sphingolipids in retinal physiology and diseases. Ceramide (Cer) emerges as a common mediator of inflammation and death of neuronal and retinal pigment epithelium cells in animal models of retinopathies such as glaucoma, age-related macular degeneration (AMD), and retinitis pigmentosa. Sphingosine-1-phosphate (S1P) has opposite roles, preventing photoreceptor and ganglion cell degeneration but also promoting inflammation, fibrosis, and neovascularization in AMD, glaucoma, and pro-fibrotic disorders. Alterations in Cer, S1P, and ceramide-1-phosphate may also contribute to uveitis. Notably, use of inhibitors that either prevent Cer increase or modulate S1P signaling, such as Myriocin, desipramine, and Fingolimod (FTY720), preserves neuronal viability and retinal function. These findings underscore the relevance of alterations in the sphingolipid metabolic network in the etiology of multiple retinopathies and highlight the potential of modulating their metabolism for the design of novel therapeutic approaches.

Microtubules are polymers composed of αβ-tubulin subunits that provide structure to cells and play a crucial role in in the development and function of neuronal processes and cilia, microtubule-driven extensions of the plasma membrane that have sensory (primary cilia) or motor (motile cilia) functions. To stabilize microtubules in neuronal processes and cilia, α tubulin is modified by the posttranslational addition of an acetyl group, or acetylation. We discovered that acetylated tubulin in microtubules interacts with the membrane sphingolipid, ceramide. However, the molecular mechanism and function of this interaction are not understood. Here, we show that in human iPS cell-derived neurons, ceramide stabilizes microtubules, which indicates a similar function in cilia. Using proximity ligation assays, we detected complex formation of ceramide with acetylated tubulin in C. reinhardtii flagella and cilia of human embryonic kidney (HEK293T) cells, primary cultured mouse astrocytes, and ependymal cells. Using incorporation of palmitic azide and click chemistry-mediated addition of fluorophores, we show that a portion of acetylated tubulin is S-palmitoylated. S-palmitoylated acetylated tubulin is colocalized with ceramide-rich platforms (CRPs) in the ciliary membrane, and it is coimmunoprecipitated with Arl13b, a GTPase that mediates transport of proteins into cilia. Inhibition of S-palmitoylation with 2-bromo palmitic acid or inhibition of ceramide biosynthesis with fumonisin B1 reduces formation of the Arl13b-acetylated tubulin complex and its transport into cilia, concurrent with impairment of ciliogenesis. Together, these data show, for the first time, that CRPs mediate membrane anchoring and interaction of S-palmitoylated proteins that are critical for cilium formation, stabilization, and function. 

The acyltransferase LCAT mediates FA esterification of plasma cholesterol. In vitro studies have shown that LCAT also FA-esterifies several oxysterols, but in vivo evidence is lacking. Here, we measured both free and FA-esterified forms of sterols in 206 healthy volunteers and 8 individuals with genetic LCAT deficiency, including familial LCAT deficiency (FLD) and fish-eye disease (FED). In the healthy volunteers, the mean values of the ester-to-total molar ratios of the following sterols varied: 4β-hydroxycholesterol (4βHC), 0.38; 5,6α-epoxycholesterol (5,6αEC), 0.46; 5,6β-epoxycholesterol (5,6βEC), 0.51; cholesterol, 0.70; cholestane-3β,5α,6β-triol (CT), 0.70; 7-ketocholesterol (7KC), 0.75; 24S-hydroxycholesterol (24SHC), 0.80; 25-hydroxycholesterol (25HC), 0.81; 27-hydroxycholesterol (27HC), 0.86; and 7α-hydroxycholesterol (7αHC), 0.89. In the individuals with LCAT deficiency, the plasma levels of the FA-esterified forms of cholesterol, 5,6αEC, 5,6βEC, CT, 7αHC, 7KC, 24SHC, 25HC, and 27HC, were significantly lower than those in the healthy volunteers. The individuals with FLD had significantly lower FA-esterified forms of 7αHC, 24SHC, and 27HC than those with FED. It is of note that, even in the three FLD individuals with negligible plasma cholesteryl ester, substantial amounts of the FA-esterified forms of 4βHC, 5,6αEC, 7αHC, 7KC, and 27HC were present. We conclude that LCAT has a major role in the FA esterification of many plasma oxysterols but contributes little to the FA esterification of 4βHC. Substantial FA esterification of 4βHC, 5,6αEC, 7αHC, 7KC, and 27HC is independent of LCAT.

Accompanied with nutrition transition, non-HDL-C levels of individuals in Asian countries has increased rapidly, which has caused the global epicenter of nonoptimal cholesterol to shift from Western countries to Asian countries. Thus, it is critical to underline major genetic and dietary determinants. In the current study of 2,330 Chinese individuals, genetic risk scores (GRSs) were calculated for total cholesterol (TC; GRS_TC, 57 SNPs), LDL-C (GRS_LDL-C, 45 SNPs), and HDL-C (GRS_HDL-C, 65 SNPs) based on SNPs from the Global Lipid Genetics Consortium study. Cholesterol intake was estimated by a 74-item food-frequency questionnaire. Associations of dietary cholesterol intake with plasma TC and LDL-C strengthened across quartiles of the GRS_TC (effect sizes: –0.29, 0.34, 2.45, and 6.47; P_interaction = 0.002) and GRS_LDL-C (effect sizes: –1.35, 0.17, 5.45, and 6.07; P_interaction = 0.001), respectively. Similar interactions with non-HDL-C were observed between dietary cholesterol and GRS_TC (P_interaction = 0.001) and GRS_LDL-C (P_interaction = 0.004). The adverse effects of GRS_TC on TC (effect sizes across dietary cholesterol quartiles: 0.51, 0.82, 1.21, and 1.31; P_interaction = 0.023) and GRS_LDL-C on LDL-C (effect sizes across dietary cholesterol quartiles: 0.66, 0.52, 1.12, and 1.56; P_interaction = 0.020) were more profound in those having higher cholesterol intake compared with those with lower intake. Our findings suggest significant interactions between genetic susceptibility and dietary cholesterol intake on plasma cholesterol profiles in a Chinese population.

Familial LCAT deficiency (FLD) is a rare genetic disorder of HDL metabolism, caused by loss-of-function mutations in the LCAT gene and characterized by a variety of symptoms including corneal opacities and kidney failure. Renal disease represents the leading cause of morbidity and mortality in FLD cases. However, the prognosis is not known and the rate of deterioration of kidney function is variable and unpredictable from patient to patient. In this article, we present data from a follow-up of the large Italian cohort of FLD patients, who have been followed for an average of 12 years. We show that renal failure occurs at the median age of 46 years, with a median time to a second recurrence of 10 years. Additionally, we identify high plasma unesterified cholesterol level as a predicting factor for rapid deterioration of kidney function. In conclusion, this study highlights the severe consequences of FLD, underlines the need of correct early diagnosis and referral of patients to specialized centers, and highlights the urgency for effective treatments to prevent or slow renal disease in patients with LCAT deficiency.

The dominant role of CaV2 voltage-gated calcium channels for driving neurotransmitter release is broadly conserved. Given the overlapping functional properties of CaV2 and CaV1 channels, and less so CaV3 channels, it is unclear why there have not been major shifts toward dependence on other CaV channels for synaptic transmission. Here, we provide a structural and functional profile of the CaV2 channel cloned from the early-diverging animal Trichoplax adhaerens, which lacks a nervous system but possesses single gene homologues for CaV1–CaV3 channels. Remarkably, the highly divergent channel possesses similar features as human CaV2.1 and other CaV2 channels, including high voltage–activated currents that are larger in external Ba2+ than in Ca2+; voltage-dependent kinetics of activation, inactivation, and deactivation; and bimodal recovery from inactivation. Altogether, the functional profile of Trichoplax CaV2 suggests that the core features of presynaptic CaV2 channels were established early during animal evolution, after CaV1 and CaV2 channels emerged via proposed gene duplication from an ancestral CaV1/2 type channel. The Trichoplax channel was relatively insensitive to mammalian CaV2 channel blockers ω-agatoxin-IVA and ω-conotoxin-GVIA and to metal cation blockers Cd2+ and Ni2+. Also absent was the capacity for voltage-dependent G-protein inhibition by co-expressed Trichoplax Gβγ subunits, which nevertheless inhibited the human CaV2.1 channel, suggesting that this modulatory capacity evolved via changes in channel sequence/structure, and not G proteins. Last, the Trichoplax channel was immunolocalized in cells that express an endomorphin-like peptide implicated in cell signaling and locomotive behavior and other likely secretory cells, suggesting contributions to regulated exocytosis.

Ion mobility brings an additional dimension of separation to LC–MS, improving identification of peptides and proteins in complex mixtures. A recently introduced timsTOF mass spectrometer (Bruker) couples trapped ion mobility separation to TOF mass analysis. With the parallel accumulation serial fragmentation (PASEF) method, the timsTOF platform achieves promising results, yet analysis of the data generated on this platform represents a major bottleneck. Currently, MaxQuant and PEAKS are most used to analyze these data. However, because of the high complexity of timsTOF PASEF data, both require substantial time to perform even standard tryptic searches. Advanced searches (e.g. with many variable modifications, semi- or non-enzymatic searches, or open searches for post-translational modification discovery) are practically impossible. We have extended our fast peptide identification tool MSFragger to support timsTOF PASEF data, and developed a label-free quantification tool, IonQuant, for fast and accurate 4-D feature extraction and quantification. Using a HeLa data set published by Meier et al. (2018), we demonstrate that MSFragger identifies significantly (~30%) more unique peptides than MaxQuant (1.6.10.43), and performs comparably or better than PEAKS X+ (~10% more peptides). IonQuant outperforms both in terms of number of quantified proteins while maintaining good quantification precision and accuracy. Runtime tests show that MSFragger and IonQuant can fully process a typical two-hour PASEF run in under 70 min on a typical desktop (6 CPU cores, 32 GB RAM), significantly faster than other tools. Finally, through semi-enzymatic searching, we significantly increase the number of identified peptides. Within these semi-tryptic identifications, we report evidence of gas-phase fragmentation before MS/MS analysis.

Mass spectrometry has become an indispensable tool for the characterization of glycosylation across biological systems. Our ability to generate rich fragmentation of glycopeptides has dramatically improved over the last decade yet our informatic approaches still lag behind. Although glycoproteomic informatics approaches using glycan databases have attracted considerable attention, database independent approaches have not. This has significantly limited high throughput studies of unusual or atypical glycosylation events such as those observed in bacteria. As such, computational approaches to examine bacterial glycosylation and identify chemically diverse glycans are desperately needed. Here we describe the use of wide-tolerance (up to 2000 Da) open searching as a means to rapidly examine bacterial glycoproteomes. We benchmarked this approach using N-linked glycopeptides of Campylobacter fetus subsp. fetus as well as O-linked glycopeptides of Acinetobacter baumannii and Burkholderia cenocepacia revealing glycopeptides modified with a range of glycans can be readily identified without defining the glycan masses before database searching. Using this approach, we demonstrate how wide tolerance searching can be used to compare glycan use across bacterial species by examining the glycoproteomes of eight Burkholderia species (B. pseudomallei; B. multivorans; B. dolosa; B. humptydooensis; B. ubonensis, B. anthina; B. diffusa; B. pseudomultivorans). Finally, we demonstrate how open searching enables the identification of low frequency glycoforms based on shared modified peptides sequences. Combined, these results show that open searching is a robust computational approach for the determination of glycan diversity within bacterial proteomes.

Influenza A virus (IAV) mutates rapidly, resulting in antigenic drift and poor year-to-year vaccine effectiveness. One challenge in designing effective vaccines is that genetic mutations frequently cause amino acid variations in IAV envelope protein hemagglutinin (HA) that create new N-glycosylation sequons; resulting N-glycans cause antigenic shielding, allowing viral escape from adaptive immune responses. Vaccine candidate strain selection currently involves correlating antigenicity with HA protein sequence among circulating strains, but quantitative comparison of site-specific glycosylation information may likely improve the ability to design vaccines with broader effectiveness against evolving strains. However, there is poor understanding of the influence of glycosylation on immunodominance, antigenicity, and immunogenicity of HA, and there are no well-tested methods for comparing glycosylation similarity among virus samples. Here, we present a method for statistically rigorous quantification of similarity between two related virus strains that considers the presence and abundance of glycopeptide glycoforms. We demonstrate the strength of our approach by determining that there was a quantifiable difference in glycosylation at the protein level between WT IAV HA from A/Switzerland/9715293/2013 (SWZ13) and a mutant strain of SWZ13, even though no N-glycosylation sequons were changed. We determined site-specifically that WT and mutant HA have varying similarity at the glycosylation sites of the head domain, reflecting competing pressures to evade host immune response while retaining viral fitness. To our knowledge, our results are the first to quantify changes in glycosylation state that occur in related proteins of considerable glycan heterogeneity. Our results provide a method for understanding how changes in glycosylation state are correlated with variations in protein sequence, which is necessary for improving IAV vaccine strain selection. Understanding glycosylation will be especially important as we find new expression vectors for vaccine production, as glycosylation state depends greatly on the host species.

In-depth coverage of proteomic analysis could enhance our understanding to the mechanism of the protein functions. Unfortunately, many highly hydrophobic proteins and low-abundance proteins, which play critical roles in signaling networks, are easily lost during sample preparation, mainly attributed to the fact that very few extractants can simultaneously satisfy the requirements on strong solubilizing ability to membrane proteins and good enzyme compatibility. Thus, it is urgent to screen out ideal extractant from the huge compound libraries in a fast and effective way. Herein, by investigating the interior mechanism of extractants on the membrane proteins solubilization and trypsin compatibility, a molecular dynamics simulation system was established as complement to the experimental procedure to narrow down the scope of candidates for proteomics analysis. The simulation data shows that the van der Waals interaction between cation group of ionic liquid and membrane protein is the dominant factor in determining protein solubilization. In combination with the experimental data, 1-dodecyl-3-methylimidazolium chloride (C12Im-Cl) is on the shortlist for the suitable candidates from comprehensive aspects. Inspired by the advantages of C12Im-Cl, an ionic liquid-based filter-aided sample preparation (i-FASP) method was developed. Using this strategy, over 3,300 proteins were confidently identified from 10³ HeLa cells (~100 ng proteins) in a single run, an improvement of 53% over the conventional FASP method. Then the i-FASP method was further successfully applied to the label-free relative quantitation of human liver cancer and para-carcinoma tissues with obviously improved accuracy, reproducibility and coverage than the commonly used urea-based FASP method. The above results demonstrated that the i-FASP method could be performed as a versatile tool for the in-depth coverage proteomic analysis of biological samples.

Tandem mass tag (TMT) is a multiplexing technology widely-used in proteomic research. It enables relative quantification of proteins from multiple biological samples in a single MS run with high efficiency and high throughput. However, experiments often require more biological replicates or conditions than can be accommodated by a single run, and involve multiple TMT mixtures and multiple runs. Such larger-scale experiments combine sources of biological and technical variation in patterns that are complex, unique to TMT-based workflows, and challenging for the downstream statistical analysis. These patterns cannot be adequately characterized by statistical methods designed for other technologies, such as label-free proteomics or transcriptomics. This manuscript proposes a general statistical approach for relative protein quantification in MS- based experiments with TMT labeling. It is applicable to experiments with multiple conditions, multiple biological replicate runs and multiple technical replicate runs, and unbalanced designs. It is based on a flexible family of linear mixed-effects models that handle complex patterns of technical artifacts and missing values. The approach is implemented in MSstatsTMT, a freely available open-source R/Bioconductor package compatible with data processing tools such as Proteome Discoverer, MaxQuant, OpenMS, and SpectroMine. Evaluation on a controlled mixture, simulated datasets, and three biological investigations with diverse designs demonstrated that MSstatsTMT balanced the sensitivity and the specificity of detecting differentially abundant proteins, in large-scale experiments with multiple biological mixtures.

Using a simple, environment friendly proteome extraction (TOP), we were able to optimize the analysis of clinical samples. Using our TOP method we analyzed a clinical cohort of microsatellite stable (MSS) and unstable (MSI-H) colorectal carcinoma (CRC). We identified a tumor cell specific, STAT1-centered, immune signature expressed by the MSI-H tumor cells. We then showed that long, but not short, exposure to Interferon- induces a similar signature in vitro. We identified 10 different temporal protein expression patterns, classifying the Interferon- protein temporal regulation in CRC. Our data sheds light on the changes that tumor cells undergo under long-term immunological pressure in vivo, the importance of STAT proteins in specific biological scenarios. The data generated could help find novel clinical biomarkers and therapeutic approaches.

Co-fractionation MS (CF-MS) is a technique with potential to characterize endogenous and unmanipulated protein complexes on an unprecedented scale. However this potential has been offset by a lack of guidelines for best-practice CF-MS data collection and analysis. To obtain such guidelines, this study thoroughly evaluates novel and published Saccharomyces cerevisiae CF-MS data sets using very high proteome coverage libraries of yeast gold standard complexes. A new method for identifying gold standard complexes in CF-MS data, Reference Complex Profiling, and the Extending 'Guilt-by-Association' by Degree (EGAD) R package are used for these evaluations, which are verified with concurrent analyses of published human data. By evaluating data collection designs, which involve fractionation of cell lysates, it is found that near-maximum recall of complexes can be achieved with fewer samples than published studies. Distributing sample collection across orthogonal fractionation methods, rather than a single high resolution data set, leads to particularly efficient recall. By evaluating 17 different similarity scoring metrics, which are central to CF-MS data analysis, it is found that two metrics rarely used in past CF-MS studies – Spearman and Kendall correlations – and the recently introduced Co-apex metric frequently maximize recall, whereas a popular metric—Euclidean distance—delivers poor recall. The common practice of integrating external genomic data into CF-MS data analysis is also evaluated, revealing that this practice may improve the precision and recall of known complexes but is generally unsuitable for predicting novel complexes in model organisms. If studying nonmodel organisms using orthologous genomic data, it is found that particular subsets of fractionation profiles (e.g. the lowest abundance quartile) should be excluded to minimize false discovery. These assessments are summarized in a series of universally applicable guidelines for precise, sensitive and efficient CF-MS studies of known complexes, and effective predictions of novel complexes for orthogonal experimental validation.

Renal Cell Carcinoma (RCC) is one of the most commonly diagnosed cancers worldwide with research efforts dramatically improving understanding of the biology of the disease. To investigate the role of the immune system in treatment-naïve clear cell Renal Cell Carcinoma (ccRCC), we interrogated the immune infiltrate in patient-matched ccRCC tumor samples, benign normal adjacent tissue (NAT) and peripheral blood mononuclear cells (PBMCs isolated from whole blood, focusing our attention on the myeloid cell infiltrate. Using flow cytometric, MS, and ExCYT analysis, we discovered unique myeloid populations in PBMCs across patient samples. Furthermore, normal adjacent tissues and ccRCC tissues contained numerous myeloid populations with a unique signature for both tissues. Enrichment of the immune cell (CD45⁺) fraction and subsequent gene expression analysis revealed a number of myeloid-related genes that were differentially expressed. These data provide evidence, for the first time, of an immunosuppressive and pro-tumorigenic role of myeloid cells in early, clinically localized ccRCC. The identification of a number of immune proteins for therapeutic targeting provides a rationale for investigation into the potential efficacy of earlier intervention with single-agent or combination immunotherapy for ccRCC.

Cross-linking MS (XL-MS) has been recognized as an effective source of information about protein structures and interactions. In contrast to regular peptide identification, XL-MS has to deal with a quadratic search space, where peptides from every protein could potentially be cross-linked to any other protein. To cope with this search space, most tools apply different heuristics for search space reduction. We introduce a new open-source XL-MS database search algorithm, OpenPepXL, which offers increased sensitivity compared with other tools. OpenPepXL searches the full search space of an XL-MS experiment without using heuristics to reduce it. Because of efficient data structures and built-in parallelization OpenPepXL achieves excellent runtimes and can also be deployed on large compute clusters and cloud services while maintaining a slim memory footprint. We compared OpenPepXL to several other commonly used tools for identification of noncleavable labeled and label-free cross-linkers on a diverse set of XL-MS experiments. In our first comparison, we used a data set from a fraction of a cell lysate with a protein database of 128 targets and 128 decoys. At 5% FDR, OpenPepXL finds from 7% to over 50% more unique residue pairs (URPs) than other tools. On data sets with available high-resolution structures for cross-link validation OpenPepXL reports from 7% to over 40% more structurally validated URPs than other tools. Additionally, we used a synthetic peptide data set that allows objective validation of cross-links without relying on structural information and found that OpenPepXL reports at least 12% more validated URPs than other tools. It has been built as part of the OpenMS suite of tools and supports Windows, macOS, and Linux operating systems. OpenPepXL also supports the MzIdentML 1.2 format for XL-MS identification results. It is freely available under a three-clause BSD license at https://openms.org/openpepxl.

Trypsin is the protease of choice in bottom-up proteomics. However, its application can be limited by the amino acid composition of target proteins and the pH of the digestion solution. In this study we characterize ProAlanase, a protease from the fungus Aspergillus niger that cleaves primarily on the C-terminal side of proline and alanine residues. ProAlanase achieves high proteolytic activity and specificity when digestion is carried out at acidic pH (1.5) for relatively short (2 h) time periods. To elucidate the potential of ProAlanase in proteomics applications, we conducted a series of investigations comprising comparative multi-enzymatic profiling of a human cell line proteome, histone PTM analysis, ancient bone protein identification, phosphosite mapping and de novo sequencing of a proline-rich protein and disulfide bond mapping in mAb. The results demonstrate that ProAlanase is highly suitable for proteomics analysis of the arginine- and lysine-rich histones, enabling high sequence coverage of multiple histone family members. It also facilitates an efficient digestion of bone collagen thanks to the cleavage at the C terminus of hydroxyproline which is highly prevalent in collagen. This allows to identify complementary proteins in ProAlanase- and trypsin-digested ancient bone samples, as well as to increase sequence coverage of noncollagenous proteins. Moreover, digestion with ProAlanase improves protein sequence coverage and phosphosite localization for the proline-rich protein Notch3 intracellular domain (N3ICD). Furthermore, we achieve a nearly complete coverage of N3ICD protein by de novo sequencing using the combination of ProAlanase and tryptic peptides. Finally, we demonstrate that ProAlanase is efficient in disulfide bond mapping, showing high coverage of disulfide-containing regions in a nonreduced mAb.

Over the past decade, modern methods of MS (MS) have emerged that allow reliable, fast and cost-effective identification of pathogenic microorganisms. Although MALDI-TOF MS has already revolutionized the way microorganisms are identified, recent years have witnessed also substantial progress in the development of liquid chromatography (LC)-MS based proteomics for microbiological applications. For example, LC-tandem MS (LC-MS²) has been proposed for microbial characterization by means of multiple discriminative peptides that enable identification at the species, or sometimes at the strain level. However, such investigations can be laborious and time-consuming, especially if the experimental LC-MS² data are tested against sequence databases covering a broad panel of different microbiological taxa. In this proof of concept study, we present an alternative bottom-up proteomics method for microbial identification. The proposed approach involves efficient extraction of proteins from cultivated microbial cells, digestion by trypsin and LC–MS measurements. Peptide masses are then extracted from MS¹ data and systematically tested against an in silico library of all possible peptide mass data compiled in-house. The library has been computed from the UniProt Knowledgebase covering Swiss-Prot and TrEMBL databases and comprises more than 12,000 strain-specific in silico profiles, each containing tens of thousands of peptide mass entries. Identification analysis involves computation of score values derived from correlation coefficients between experimental and strain-specific in silico peptide mass profiles and compilation of score ranking lists. The taxonomic positions of the microbial samples are then determined by using the best-matching database entries. The suggested method is computationally efficient – less than 2 mins per sample - and has been successfully tested by a test set of 39 LC-MS¹ peak lists obtained from 19 different microbial pathogens. The proposed method is rapid, simple and automatable and we foresee wide application potential for future microbiological applications.

Pathway analyses are key methods to analyze 'omics experiments. Nevertheless, integrating data from different 'omics technologies and different species still requires considerable bioinformatics knowledge.

Here we present the novel ReactomeGSA resource for comparative pathway analyses of multi-omics datasets. ReactomeGSA can be used through Reactome's existing web interface and the novel ReactomeGSA R Bioconductor package with explicit support for scRNA-seq data. Data from different species is automatically mapped to a common pathway space. Public data from ExpressionAtlas and Single Cell ExpressionAtlas can be directly integrated in the analysis. ReactomeGSA greatly reduces the technical barrier for multi-omics, cross-species, comparative pathway analyses.

We used ReactomeGSA to characterize the role of B cells in anti-tumor immunity. We compared B cell rich and poor human cancer samples from five of the Cancer Genome Atlas (TCGA) transcriptomics and two of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteomics studies. B cell-rich lung adenocarcinoma samples lacked the otherwise present activation through NFkappaB. This may be linked to the presence of a specific subset of tumor associated IgG+ plasma cells that lack NFkappaB activation in scRNA-seq data from human melanoma. This showcases how ReactomeGSA can derive novel biomedical insights by integrating large multi-omics datasets.

The absence of the dystrophin protein in Duchenne muscular dystrophy (DMD) results in myofiber fragility and a plethora of downstream secondary pathologies. Although a variety of experimental therapies are in development, achieving effective treatments for DMD remains exceptionally challenging, not least because the pathological consequences of dystrophin loss are incompletely understood. Here we have performed proteome profiling in tibialis anterior muscles from two murine DMD models (mdx and mdx52) at three ages (8, 16, and 80 weeks of age), all n = 3. High-resolution isoelectric focusing liquid chromatography-tandem MS (HiRIEF-LC–MS/MS) was used to quantify the expression of 4974 proteins across all 27 samples. The two dystrophic models were found to be highly similar, whereas multiple proteins were differentially expressed relative to WT (C57BL/6) controls at each age. Furthermore, 1795 proteins were differentially expressed when samples were pooled across ages and dystrophic strains. These included numerous proteins associated with the extracellular matrix and muscle function that have not been reported previously. Pathway analysis revealed multiple perturbed pathways and predicted upstream regulators, which together are indicative of cross-talk between inflammatory, metabolic, and muscle growth pathways (e.g. TNF, INF, NF-B, SIRT1, AMPK, PGC-1α, PPARs, ILK, and AKT/PI3K). Upregulation of CAV3, MVP and PAK1 protein expression was validated in dystrophic muscle by Western blot. Furthermore, MVP was upregulated during, but not required for, the differentiation of C2C12 myoblasts suggesting that this protein may affect muscle regeneration. This study provides novel insights into mutation-independent proteomic signatures characteristic of the dystrophic phenotype and its progression with aging.

Electrospray ionization is today the most widely used ionization technique in chemical and bio-chemical analysis. Interfaced with a mass spectrometer it allows to investigate the molecular composition of liquid samples. With electrospray a large variety of chemical substances can be ionized. There is no limitation in mass which enables even the investigation of large non-covalent protein complexes. Its high ionization efficiency profoundly changed bio-molecular sciences because proteins can be identified and quantified on trace amounts in a high throughput fashion. This review article focusses mainly on the exploration of the underlying ionization mechanism. Some ionization characteristics are discussed which are related to this mechanism. Typical spectra of peptides, proteins and non-covalent complexes are shown and the quantitative character of spectra is highlighted. Finally the possibilities and limitations in measuring the association constant of bivalent non-covalent complexes are described.

Growing implications of glycosylation in physiological occurrences and human disease have prompted intensive focus on revealing glycomic perturbations through absolute and relative quantification. Empowered by seminal methodologies and increasing capacity for detection, identification, and characterization, the past decade has provided a significant increase in the number of suitable strategies for glycan and glycopeptide quantification. Mass spectrometry-based strategies for glycomic quantitation have grown to include metabolic incorporation of stable isotopes, deposition of mass difference and mass defect isotopic labels, and isobaric chemical labeling, providing researchers with ample tools for accurate and robust quantitation. Beyond this, workflows have been designed to harness instrument capability for label-free quantification and numerous software packages have been developed to facilitate reliable spectrum scoring. In this review, we present and highlight the most recent advances in chemical labeling and associated techniques for glycan and glycopeptide quantification.

CD4+ T cell responses are crucial for inducing and maintaining effective anti-cancer immunity, and the identification of human leukocyte antigen class II (HLA-II) cancer-specific epitopes is key to the development of potent cancer immunotherapies. In many tumor types, and especially in glioblastoma (GBM), HLA-II complexes are hardly ever naturally expressed. Hence, little is known about immunogenic HLA-II epitopes in GBM. With stable expression of the class II major histocompatibility complex transactivator (CIITA) coupled to a detailed and sensitive mass spectrometry based immunopeptidomics analysis, we here uncovered a remarkable breadth of the HLA-ligandome in HROG02, HROG17 and RA GBM cell lines. The effect of CIITA expression on the induction of the HLA-II presentation machinery was striking in each of the three cell lines, and it was significantly higher compared to interferon gamma (IFN) treatment. In total, we identified 16,123 unique HLA-I peptides and 32,690 unique HLA-II peptides. In order to genuinely define the identified peptides as true HLA ligands, we carefully characterized their association with the different HLA allotypes. In addition, we identified 138 and 279 HLA-I and HLA-II ligands, respectively, most of which are novel in GBM, derived from known GBM-associated tumor-antigens that have been used as source proteins for a variety of GBM vaccines. Our data further indicate that CIITA-expressing GBM cells acquired an antigen presenting cell-like phenotype as we found that they directly present external proteins as HLA-II ligands. Not only that CIITA-expressing GBM cells are attractive models for antigen discovery endeavors, but also such engineered cells have great therapeutic potential through massive presentation of a diverse antigenic repertoire.

The increasing consumption of high-fat foods combined with a lack of exercise is a major contributor to the burden of obesity in humans. Aerobic exercise such as running is known to provide metabolic benefits, but how the over-consumption of a high fat diet (HFD) and exercise interact is not well characterized at the molecular level. Here, we examined the plasma proteome in mice for the effects of aerobic exercise as both a treatment and as a preventative regime for animals on either HFD or a healthy control diet. This analysis detected large changes in the plasma proteome induced by the HFD, such as increased abundance of SERPINA7, ALDOB, and down-regulation of SERPINA1E, CFD (adipsin). Some of these changes were significantly reverted using exercise as a preventative measure, but not as a treatment regime. To determine if either the intensity, or duration, of exercise influenced the outcome, we compared high-intensity interval training (HIIT) and endurance running. Endurance running slightly out-performed HIIT exercise, but overall, both provided similar reversion in abundance of plasma proteins modulated by the high-fat diet including SERPINA7, APOE, SERPINA1E, and CFD. Finally, we compared the changes induced by over-consumption of HFD to previous data from mice fed an isocaloric high saturated fat (SFA) or polyunsaturated fat (PUFA) diet. This identified several common changes including increased APOC2 and APOE, but also highlighted changes specific for either over-consumption of HFD (ALDOB, SERPINA7, CFD), SFA-based diets (SERPINA1E), or PUFA-based diets (Haptoglobin - Hp). Together, these data highlight the importance of early intervention with exercise to revert HFD-induced phenotypes and suggest some of the molecular mechanisms leading to the changes in the plasma proteome generated by high fat diet consumption. Web-based interactive visualizations are provided for this dataset (larancelab.com/hfd-exercise), which give insight into diet and exercise phenotypic interactions on the plasma proteome.

We developed a simple and rapid method to enrich protein N-terminal peptides, in which the protease TrypN is first employed to generate protein N-terminal peptides without Lys or Arg and internal peptides with two positive charges at their N-termini, and then the N-terminal peptides with or without N-acetylation are separated from the internal peptides by strong cation exchange chromatography according to a retention model based on the charge/orientation of peptides. This approach was applied to 20 μg of human HEK293T cell lysate proteins to profile the N-terminal proteome. On average, 1,550 acetylated and 200 unmodified protein N-terminal peptides were successfully identified in a single LC/MS/MS run with less than 3% contamination with internal peptides, even when we accepted only canonical protein N-termini registered in the Swiss-Prot database. Since this method involves only two steps, protein digestion and chromatographic separation, without the need for tedious chemical reactions, it should be useful for comprehensive profiling of protein N-termini, including proteoforms with neo-N-termini.

Extracellular vesicle (EV) proteins from acute myeloid leukemia (AML) cell lines were analyzed using mass spectrometry. The analyses identified 2450 proteins, including 461 differentially expressed proteins (290 upregulated and 171 downregulated). CD53 and CD47 were upregulated and were selected as candidate biomarkers. The association between survival of patients with AML and the expression levels of CD53 and CD47 at diagnosis was analyzed using mRNA expression data from The Cancer Genome Atlas database. Patients with higher expression levels showed significantly inferior survival than those with lower expression levels. Enzyme-linked immunosorbent assay results of the expression levels of CD53 and CD47 from EVs in the bone marrow of patients with AML at diagnosis and at the time of complete remission with induction chemotherapy revealed that patients with downregulated CD53 and CD47 expression appeared to relapse less frequently. Network model analysis of EV proteins revealed several upregulated kinases, including LYN, CSNK2A1, SYK, CSK, and PTK2B. The potential cytotoxicity of several clinically applicable drugs that inhibit these kinases was tested in AML cell lines. The drugs lowered the viability of AML cells. The collective data suggest that AML-derived EVs could reflect essential leukemia biology.

Open searching has proven to be an effective strategy for identifying both known and unknown modifications in shotgun proteomics experiments. Rather than being limited to a small set of user-specified modifications, open searches identify peptides with any mass shift that may correspond to a single modification or a combination of several modifications. Here we present PTM-Shepherd, a bioinformatics tool that automates characterization of PTM profiles detected in open searches based on attributes such as amino acid localization, fragmentation spectra similarity, retention time shifts, and relative modification rates. PTM-Shepherd can also perform multi-experiment comparisons for studying changes in modification profiles, e.g. in data generated in different laboratories or under different conditions. We demonstrate how PTM-Shepherd improves the analysis of data from formalin-fixed paraffin-embedded samples, detects extreme underalkylation of cysteine in some datasets, discovers an artefactual modification introduced during peptide synthesis, and uncovers site-specific biases in sample preparation artifacts in a multi-center proteomics profiling study.

To identify novel autoantibodies of Takayasu arteritis (TAK) using HuProt array-based approach. A two-phase approach was adopted. In Phase I, serum samples collected from 40 TAK patients, 15 autoimmune disease patients, and 20 healthy subjects were screened to identify TAK-specific autoantibodies using human protein (HuProt) arrays. In Phase II, the identified candidate autoantibodies were validated with TAK-focused arrays using an additional cohort comprised of 109 TAK patients, 110 autoimmune disease patients, and 96 healthy subjects. Subsequently, the TAK-specific autoantibodies validated in Phase II were further confirmed using Western blot analysis. We identified and validated eight autoantibodies as potential TAK-specific diagnostic biomarkers, including anti-SPATA7, -QDPR, -SLC25A2, -PRH2, -DIXDC1, -IL17RB, -ZFAND4, and -NOLC1 antibodies, with AUC of 0.803, 0.801, 0.780, 0.696, 0.695, 0.678, 0.635 and 0.613, respectively. SPATA7 could distinguish TAK from healthy and disease controls with 73.4% sensitivity at 85.4% specificity, while QDPR showed 71.6% sensitivity at 86.4% specificity. SLC25A22 showed the highest sensitivity of 80.7%, but at lower specificity of 67.0%. In addition, PRH2, IL17RB and NOLC1 showed good specificities of 88.3%, 85.9% and 86.9%, respectively, but at lower sensitivities (<50%). Finally, DIXDC1 and ZFAND4 showed moderate performance as compared with the other autoantibodies. Using a decision tree model, we could reach a specificity of 94.2% with AUC of 0.843, a significantly improved performance as compared to that by each individual biomarker. The performance of three autoantibodies, namely anti-SPATA7, -QDPR and -PRH2, were successfully confirmed with Western blot analysis. Using this two-phase strategy, we identified and validated eight novel autoantibodies as TAK–specific biomarker candidates, three of which could be readily adopted in a clinical setting.

Recent advances in MS-based proteomics have vastly increased the quality and scope of biological information that can be derived from human samples. These advances have rendered current workflows increasingly applicable in biomedical and clinical contexts. As proteomics is poised to take an important role in the clinic, associated ethical responsibilities increase in tandem with the impact on the health, privacy, and well-being of individuals. Here we conducted and report a systematic literature review of ethical issues in clinical proteomics. We add our perspectives from a background of bioethics, the results of our accompanying paper extracting individual-sensitive results from patient samples, and the literature addressing similar issues in genomics. The spectrum of potential issues ranges from patient re-identification to incidental findings of clinical significance. The latter can be divided into actionable and unactionable findings. Some of these have the potential to be employed in discriminatory or privacy-infringing ways. However, incidental findings may also have great positive potential. A plasma proteome profile, for instance, could inform on the general health or disease status of an individual regardless of the narrow diagnostic question that prompted it. We suggest that early discussion of ethical issues in clinical proteomics is important to ensure that eventual regulations reflect the considered judgment of the community as well as to anticipate opportunities and problems that may arise as the technology matures further.

Tectonic Politics: Global Political Risk in an Age of Transformation Book sysadmin 7 May 2019

Political risk now affects more markets and countries than ever before and that risk will continue to rise. But traditional methods of managing political risk are no longer legitimate or effective.

In Tectonic Politics, Nigel Gould-Davies explores the complex, shifting landscape of political risk and how to navigate it. He analyses trends in each form of political risk: the power to destroy, seize, regulate, and tax.

He shows how each of these forms reflects a deeper transformation of the global political economy that is reordering the relationship between power, wealth, and values. In a world where everything is political, the craft of engagement is as important as the science of production and the art of the deal.

The successful company must integrate that craft—the engager’s way of seeing and doing—into strategy and culture.

Drawing on a career in academia, business, and diplomacy, Gould-Davies provides corporate leaders, scholars, and engaged citizens with a groundbreaking study of the fastest-rising political risk today. ‘As tectonic plates shape the earth,’ he writes, ‘so tectonic politics forges its governance.’

The book is published as part of the Insights series.

Praise for Tectonic Politics

About the author

Nigel Gould-Davies was an associate fellow of the Russia and Eurasia Programme at Chatham House.

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