Direct Proteomic Detection and Prioritization of 19 Onchocerciasis Biomarker Candidates in Humans

Onchocerca volvulus, the causative agent of onchocerciasis, infects over 20 million people and can cause severe dermatitis and ocular conditions including blindness. Current treatments employed in mass drug administration programs do not kill adult female worms, and common diagnostic tests cannot reliably assess viability of adult worms. There is an urgent need for better diagnostic tests to facilitate monitoring the efficacy of new treatments and disease elimination efforts. Here, eight plasma samples collected from individuals infected with O. volvulus and seven from uninfected individuals were analyzed by MS/MS spectrometry to directly identify O. volvulus proteins present in infected but absent in uninfected control samples. This direct proteomic approach for biomarker discovery had not been previously employed for onchocerciasis. Among all detected proteins, 19 biomarker candidates were supported by two or more unique peptides, identified in the plasma of at least three O. volvulus-infected human samples and absent in all control samples. Comprehensive analysis and ranking of these candidates included detailed functional annotation and a review of RNA-seq gene expression profiles. Isotope-labeled standard peptides were run in parallel and validated MS/MS peptide identifications for 15 peptides from 11 of the 19 proteins, and two infected urine and one uninfected urine sample was used for additional validation. A major antigen/OVOC11613 was identified as the most promising candidate with eight unique peptides across five plasma samples and one urine sample. Additional strong candidates included OVOC1523/ATP synthase, OVOC247/laminin and OVOC11626/PLK5, and along with OVOC11613, and were also detected in urine samples from onchocerciasis patients. This study has identified a promising novel set of proteins that will be carried forward to develop assays that can be used for diagnosis of O. volvulus infections and for monitoring treatment efficacy.     

Validation of a multiplexed and targeted lipidomics assay for accurate quantification of lipidomes

A major challenge of lipidomics is to determine and quantify the precise content of complex lipidomes to the exact lipid molecular species. Often, multiple methods are needed to achieve sufficient lipidomic coverage to make these determinations. Multiplexed targeted assays offer a practical alternative to enable quantitative lipidomics amenable to quality control standards within a scalable platform. Herein, we developed a multiplexed normal phase liquid chromatography-hydrophilic interaction chromatography multiple reaction monitoring method that quantifies lipid molecular species across over 20 lipid classes spanning wide polarities in a single 20-min run. Analytical challenges such as in-source fragmentation, isomer separations, and concentration dynamics were addressed to ensure confidence in selectivity, quantification, and reproducibility. Utilizing multiple MS/MS product ions per lipid species not only improved the confidence of lipid identification but also enabled the determination of relative abundances of positional isomers in samples. Lipid class-based calibration curves were applied to interpolate lipid concentrations and guide sample dilution. Analytical validation was performed following FDA Bioanalytical Method Validation Guidance for Industry. We report repeatable and robust quantitation of 900 lipid species measured in NIST-SRM-1950 plasma, with over 700 lipids achieving inter-assay variability below 25%. To demonstrate proof of concept for biomarker discovery, we analyzed plasma from mice treated with a glucosylceramide synthase inhibitor, benzoxazole 1. We observed expected reductions in glucosylceramide levels in treated animals but, more notably, identified novel lipid biomarker candidates from the plasma lipidome. These data highlight the utility of this qualified lipidomic platform for enabling biological discovery.     

Proteomic Discovery of Plasma Protein Biomarkers and Development of Models Predicting Prognosis of High-Grade Serous Ovarian Carcinoma

Ovarian cancer is one of the most lethal female cancers. For accurate prognosis prediction, this study aimed to investigate novel, blood-based prognostic biomarkers for high-grade serous ovarian carcinoma (HGSOC) using mass spectrometry–based proteomics methods. We conducted label-free liquid chromatography–tandem mass spectrometry using frozen plasma samples obtained from patients with newly diagnosed HGSOC (n = 20). Based on progression-free survival (PFS), the samples were divided into two groups: good (PFS ≥18 months) and poor prognosis groups (PFS <18 months). Proteomic profiles were compared between the two groups. Referring to proteomics data that we previously obtained using frozen cancer tissues from chemotherapy-naïve patients with HGSOC, overlapping protein biomarkers were selected as candidate biomarkers. Biomarkers were validated using an independent set of HGSOC plasma samples (n = 202) via enzyme-linked immunosorbent assay (ELISA). To construct models predicting the 18-month PFS rate, we performed stepwise selection based on the area under the receiver operating characteristic curve (AUC) with 5-fold cross-validation. Analysis of differentially expressed proteins in plasma samples revealed that 35 and 61 proteins were upregulated in the good and poor prognosis groups, respectively. Through hierarchical clustering and bioinformatic analyses, GSN, VCAN, SND1, SIGLEC14, CD163, and PRMT1 were selected as candidate biomarkers and were subjected to ELISA. In multivariate analysis, plasma GSN was identified as an independent poor prognostic biomarker for PFS (adjusted hazard ratio, 1.556; 95% confidence interval, 1.073–2.256; p = 0.020). By combining clinical factors and ELISA results, we constructed several models to predict the 18-month PFS rate. A model consisting of four predictors (FIGO stage, residual tumor after surgery, and plasma levels of GSN and VCAN) showed the best predictive performance (mean validated AUC, 0.779). The newly developed model was converted to a nomogram for clinical use. Our study results provided insights into protein biomarkers, which might offer clues for developing therapeutic targets.     

SIMSI-Transfer: Software-Assisted Reduction of Missing Values in Phosphoproteomic and Proteomic Isobaric Labeling Data Using Tandem Mass Spectrum Clustering

Isobaric stable isotope labeling techniques such as tandem mass tags (TMTs) have become popular in proteomics because they enable the relative quantification of proteins with high precision from up to 18 samples in a single experiment. While missing values in peptide quantification are rare in a single TMT experiment, they rapidly increase when combining multiple TMT experiments. As the field moves toward analyzing ever higher numbers of samples, tools that reduce missing values also become more important for analyzing TMT datasets. To this end, we developed SIMSI-Transfer (Similarity-based Isobaric Mass Spectra 2 [MS2] Identification Transfer), a software tool that extends our previously developed software MaRaCluster (© Matthew The) by clustering similar tandem MS2 from multiple TMT experiments. SIMSI-Transfer is based on the assumption that similarity-clustered MS2 spectra represent the same peptide. Therefore, peptide identifications made by database searching in one TMT batch can be transferred to another TMT batch in which the same peptide was fragmented but not identified. To assess the validity of this approach, we tested SIMSI-Transfer on masked search engine identification results and recovered >80% of the masked identifications while controlling errors in the transfer procedure to below 1% false discovery rate. Applying SIMSI-Transfer to six published full proteome and phosphoproteome datasets from the Clinical Proteomic Tumor Analysis Consortium led to an increase of 26 to 45% of identified MS2 spectra with TMT quantifications. This significantly decreased the number of missing values across batches and, in turn, increased the number of peptides and proteins identified in all TMT batches by 43 to 56% and 13 to 16%, respectively.     

ImShot: An Open-Source Software for Probabilistic Identification of Proteins In Situ and Visualization of Proteomics Data

Imaging mass spectrometry (IMS) has developed into a powerful tool allowing label-free detection of numerous biomolecules in situ. In contrast to shotgun proteomics, proteins/peptides can be detected directly from biological tissues and correlated to its morphology leading to a gain of crucial clinical information. However, direct identification of the detected molecules is currently challenging for MALDI–IMS, thereby compelling researchers to use complementary techniques and resource intensive experimental setups. Despite these strategies, sufficient information could not be extracted because of lack of an optimum data combination strategy/software. Here, we introduce a new open-source software ImShot that aims at identifying peptides obtained in MALDI–IMS. This is achieved by combining information from IMS and shotgun proteomics (LC–MS) measurements of serial sections of the same tissue. The software takes advantage of a two-group comparison to determine the search space of IMS masses after deisotoping the corresponding spectra. Ambiguity in annotations of IMS peptides is eliminated by introduction of a novel scoring system that identifies the most likely parent protein of a detected peptide in the corresponding IMS dataset. Thanks to its modular structure, the software can also handle LC–MS data separately and display interactive enrichment plots and enriched Gene Ontology terms or cellular pathways. The software has been built as a desktop application with a conveniently designed graphic user interface to provide users with a seamless experience in data analysis. ImShot can run on all the three major desktop operating systems and is freely available under Massachusetts Institute of Technology license.     

Real-Time Search-Assisted Acquisition on a Tribrid Mass Spectrometer Improves Coverage in Multiplexed Single-Cell Proteomics

In the young field of single-cell proteomics (scMS), there is a great need for improved global proteome characterization, both in terms of proteins quantified per cell and quantitative performance thereof. The recently introduced real-time search (RTS) on the Orbitrap Eclipse Tribrid mass spectrometer in combination with SPS-MS3 acquisition has been shown to be beneficial for the measurement of samples that are multiplexed using isobaric tags. Multiplexed scMS requires high ion injection times and high-resolution spectra to quantify the single-cell signal; however, the carrier channel facilitates peptide identification and thus offers the opportunity for fast on-the-fly precursor filtering before committing to the time-intensive quantification scan. Here, we compared classical MS2 acquisition against RTS-SPS-MS3, both using the Orbitrap Eclipse Tribrid MS with the FAIMS Pro ion mobility interface and present a new acquisition strategy termed RETICLE (RTS enhanced quant of single cell spectra) that makes use of fast real-time searched linear ion trap scans to preselect MS1 peptide precursors for quantitative MS2 Orbitrap acquisition. We show that classical MS2 acquisition is outperformed by both RTS-SPS-MS3 through increased quantitative accuracy at similar proteome coverage, and RETICLE through higher proteome coverage, with the latter enabling the quantification of over 1000 proteins per cell at an MS2 injection time of 750 ms using a 2 h gradient.     

Resistin,Elastase, and Lactoferrin as Potential Plasma Biomarkers of Pediatric Inflammatory Bowel Disease Based on Comprehensive Proteomic Screens

Inflammatory bowel disease (IBD) is an immune-mediated chronic inflammation of the intestine, which can present in the form of ulcerative colitis (UC) or as Crohn’s disease (CD). Biomarkers are needed for reliable diagnosis and disease monitoring in IBD, especially in pediatric patients. Plasma samples from a pediatric IBD cohort were interrogated using an aptamer-based screen of 1322 proteins. The elevated biomarkers identified using the aptamer screen were further validated by ELISA using an independent cohort of 76 pediatric plasma samples, drawn from 30 CD, 30 UC, and 16 healthy controls. Of the 1322 proteins screened in plasma from IBD patients, 129 proteins were significantly elevated when compared with healthy controls. Of these 15 proteins had a fold change greater than 2 and 28 proteins had a fold change >1.5. Neutrophil and extracellular vesicle signatures were detected among the elevated plasma biomarkers. When seven of these proteins were validated by ELISA, resistin was the only protein that was significantly higher in both UC and CD (p < 0.01), with receiver operating characteristic area under the curve value of 0.82 and 0.77, respectively, and the only protein that exhibited high sensitivity and specificity for both CD and UC. The next most discriminatory plasma proteins were elastase and lactoferrin, particularly for UC, with receiver operating characteristic area under the curve values of 0.74 and 0.69, respectively. We have identified circulating resistin, elastase, and lactoferrin as potential plasma biomarkers of IBD in pediatric patients using two independent diagnostic platforms and two independent patient cohorts.     

Cold-induced phase separation for the simple and reliable extraction of sex hormones for subsequent LC-MS/MS analysis

Sex hormones, including androgens, estrogens, and progestogens, are important biomarkers for various diseases. Quantification of sex hormones is typically conducted by LC-MS/MS. At present, most methods require liquid-liquid extraction or solid phase extraction for sample preparation. However, these pretreatments are prone to compromise LC-MS/MS throughput. To improve on the current standard practices, we investigated cold-induced phase separation for sex hormone extraction. After protein precipitation with acetonitrile and adjusting the solution constitution with water, samples were stored at ?30°C for 10 min to generate two distinct phases: an acetonitrile-rich layer on top of a water-rich layer. During this process, the hydrophobic sex hormones spontaneously separate into the upper layer. This simple and reliable cold-induced phase separation-based LC-MS/MS methodology was used here to simultaneously detect estrone, estradiol, estriol, testosterone, androstenedione, dehydroepiandrosterone, progesterone, and 17-hydroxyprogesterone in serum. Validation of this method indicated satisfactory performance, including acceptable linearity, accuracy, precision, and tractability. Compared with the mainstream liquid-liquid extraction-based method, this new method exhibits significant progress in throughput, which shortens the time cost of sample preparation from 90 to 40 min. We propose that this method can be an excellent alternative for sex hormone analysis in routine clinical laboratories.     

Plasma S1P and Sphingosine are not Different Prior to Pre-Eclampsia in Women at High Risk of Developing the Disease

Sphingolipids like sphingosine-1-phosphate (S1P) have been implicated in the pathophysiology of pre-eclampsia. We hypothesized that plasma S1P would be increased in women at high risk of developing pre-eclampsia who subsequently develop the disease. Low circulating placental growth factor (PlGF) is known to be associated with development of pre-eclampsia; so further, we hypothesized that increased S1P would be associated with concurrently low PlGF. This was a case-control study using stored maternal blood samples from 14 to 24 weeks of pregnancy, collected from 95 women at increased risk of pre-eclampsia. Pregnancy outcome was classified as uncomplicated, preterm pre-eclampsia (<37 weeks), or term pre-eclampsia. Plasma lipids were extracted and analyzed by ultraperformance liquid chromatography coupled to electrospray ionization MS/MS to determine concentrations of S1P and sphingosine. Median plasma S1P was 0.339 nmol/ml, and median sphingosine was 6.77 nmol/l. There were no differences in the plasma concentrations of S1P or sphingosine in women who subsequently developed pre-eclampsia, no effect of gestational age, fetal sex, ethnicity, or the presence of pre-existing hypertension. There was a correlation between S1P and sphingosine plasma concentration (P < 0.0001). There was no relationship between S1P or sphingosine with PlGF. Previous studies have suggested that plasma S1P may be a biomarker of pre-eclampsia. In our larger study, we failed to demonstrate there are women at high risk of developing the disease. We did not show a relationship with known biomarkers of the disease, suggesting that S1P is unlikely to be a useful predictor of the development of pre-eclampsia later in pregnancy.     

TAILS Identifies Candidate Substrates and Biomarkers of ADAMTS7, a Therapeutic Protease Target in Coronary Artery Disease

Loss-of-function mutations in the secreted enzyme ADAMTS7 (a disintegrin and metalloproteinase with thrombospondin motifs 7) are associated with protection for coronary artery disease. ADAMTS7 catalytic inhibition has been proposed as a therapeutic strategy for treating coronary artery disease; however, the lack of an endogenous substrate has hindered the development of activity-based biomarkers. To identify ADAMTS7 extracellular substrates and their cleavage sites relevant to vascular disease, we used TAILS (terminal amine isotopic labeling of substrates), a method for identifying protease-generated neo–N termini. We compared the secreted proteome of vascular smooth muscle and endothelial cells expressing either full-length mouse ADAMTS7 WT, catalytic mutant ADAMTS7 E373Q, or a control luciferase adenovirus. Significantly enriched N-terminal cleavage sites in ADAMTS7 WT samples were compared to the negative control conditions and filtered for stringency, resulting in catalogs of high confidence candidate ADAMTS7 cleavage sites from our three independent TAILS experiments. Within the overlap of these discovery sets, we identified 24 unique cleavage sites from 16 protein substrates, including cleavage sites in EFEMP1 (EGF-containing fibulin-like extracellular matrix protein 1/Fibulin-3). The ADAMTS7 TAILS preference for EFEMP1 cleavage at the amino acids 123.124 over the adjacent 124.125 site was validated using both endogenous EFEMP1 and purified EFEMP1 in a binary in vitro cleavage assay. Collectively, our TAILS discovery experiments have uncovered hundreds of potential substrates and cleavage sites to explore disease-related biological substrates and facilitate activity-based ADAMTS7 biomarker development.     

Mass spectrometry-based Cellular Thermal Shift Assay (CETSA®) for target deconvolution in phenotypic drug discovery

The recent renewed interest in phenotypic drug discovery has concomitantly put a focus on target deconvolution in order to achieve drug-target identification. Even though there are prescribed therapies whose mode of action is not fully understood, knowledge of the primary target will inevitably facilitate the discovery and translation of efficacy from bench to bedside. Elucidating targets and subsequent pathways engaged will also facilitate safety studies and overall development of novel drug candidates. Today, there are several techniques available for identifying the primary target, many of which rely on mass spectrometry (MS) to identify compound – target protein interactions. The Cellular Thermal Shift Assay (CETSA®) is well suited for identifying target engagement between ligands and their protein targets. Several studies have shown that CETSA combined with MS is a powerful technique that allows unlabeled target deconvolution in complex samples such as intact cells and tissues in addition to cell lysates and other protein suspensions. The applicability of CETSA MS for target deconvolution purposes will be discussed and exemplified in this mini review.     

P300 Interacted With N-Myc and Regulated Its Protein Stability via Altering Its Post-Translational Modifications in Neuroblastoma

MYCN amplification is an independent risk factor for poor prognosis in neuroblastoma (NB), but its protein product cannot be directly targeted because of protein structure. Thus, this study aimed to explore novel ways to indirectly target N-Myc by regulating its post-translational modifications (PTMs) and therefore protein stability. N-Myc coimmunoprecipitation combined with HPLC–MS/MS identified 16 PTM residues and 114 potential N-Myc-interacting proteins. Notably, both acetylation and ubiquitination were identified on lysine 199 of N-Myc. We then discovered that p300, which can interact with N-Myc, modulated the protein stability of N-Myc in MYCN-amplified NB cell lines and simultaneously regulated the acetylation level and ubiquitination level on lysine-199 of N-Myc protein in vitro. Furthermore, p300 correlated with poor prognosis in NB patients. Taken together, p300 can be considered as a potential therapeutic target to treat MYCN-amplified NB patients, and other identified PTMs and interacting proteins also provide potential targets for further study.     

Measurement of 7-dehydrocholesterol and cholesterol in hair can be used in the diagnosis of Smith-Lemli-Opitz syndrome

7-dehydrocholesterol (7-DHC) and cholesterol (CHOL) are biomarkers of Smith-Lemli-Opitz Syndrome (SLOS), a congenital autosomal recessive disorder characterized by elevated 7-DHC level in patients. Hair samples have been shown to have great diagnostic and research value, which has long been neglected in the SLOS field. In this study, we sought to investigate the feasibility of using hair for SLOS diagnosis. In the presence of antioxidants (2,6-ditert-butyl-4-methylphenol and triphenylphosphine), hair samples were completely pulverized and extracted by micro-pulverized extraction in alkaline solution or in n-hexane. After microwave-assisted derivatization with N,O-Bis(trimethylsilyl)trifluoroacetamide, the analytes were measured by GC-MS. We found that the limits of determination for 7-DHC and CHOL were 10 ng/mg and 8 ng/mg, respectively. In addition, good linearity was obtained in the range of 50–4000 ng/mg and 30–6000 ng/mg for 7-DHC and CHOL, respectively, which fully meets the requirement for SLOS diagnosis and related research. Finally, by applying the proposed method to real hair samples collected from 14 healthy infants and two suspected SLOS patients, we confirmed the feasibility of hair analysis as a diagnostic tool for SLOS. In conclusion, we present an optimized and validated analytical method for the simultaneous determination of two SLOS biomarkers using human hair.     

Discovery Proteomics Analysis Determines That Driver Oncogenes Suppress Antiviral Defense Pathways Through Reduction in Interferon-β Autocrine Stimulation

Since the discovery of oncogenes, there has been tremendous interest to understand their mechanistic basis and to develop broadly actionable therapeutics. Some of the most frequently activated oncogenes driving diverse cancers are c-MYC, EGFR, HER2, AKT, KRAS, BRAF, and MEK. Using a reductionist approach, we explored how cellular proteomes are remodeled in isogenic cell lines engineered with or without these driver oncogenes. The most striking discovery for all oncogenic models was the systematic downregulation of scores of antiviral proteins regulated by type 1 interferon. These findings extended to cancer cell lines and patient-derived xenograft models of highly refractory pancreatic cancer and osteosarcoma driven by KRAS and MYC oncogenes. The oncogenes reduced basal expression of and autocrine stimulation by type 1 interferon causing remarkable convergence on common phenotypic and functional profiles. In particular, there was dramatically lower expression of dsRNA sensors including DDX58 (RIG-I) and OAS proteins, which resulted in attenuated functional responses when the oncogenic cells were treated with the dsRNA mimetic, polyI:C, and increased susceptibility to infection with an RNA virus shown using SARS-CoV-2. Our reductionist approach provides molecular and functional insights connected to immune evasion hallmarks in cancers and suggests therapeutic opportunities.     

An Optimized Proteomics Approach Reveals Novel Alternative Proteins in Mouse Liver Development

Alternative ORFs (AltORFs) are unannotated sequences in genome that encode novel peptides or proteins named alternative proteins (AltProts). Although ribosome profiling and bioinformatics predict a large number of AltProts, mass spectrometry as the only direct way of identification is hampered by the short lengths and relative low abundance of AltProts. There is an urgent need for improvement of mass spectrometry methodologies for AltProt identification. Here, we report an approach based on size-exclusion chromatography for simultaneous enrichment and fractionation of AltProts from complex proteome. This method greatly simplifies the variance of AltProts discovery by enriching small proteins smaller than 40 kDa. In a systematic comparison between 10 methods, the approach we reported enabled the discovery of more AltProts with overall higher intensities, with less cost of time and effort compared to other workflows. We applied this approach to identify 89 novel AltProts from mouse liver, 39 of which were differentially expressed between embryonic and adult mice. During embryonic development, the upregulated AltProts were mainly involved in biological pathways on RNA splicing and processing, whereas the AltProts involved in metabolisms were more active in adult livers. Our study not only provides an effective approach for identifying AltProts but also novel AltProts that are potentially important in developmental biology.     

A Novel Spectral Annotation Strategy Streamlines Reporting of Mono-ADP-ribosylated Peptides Derived from Mouse Liver and Spleen in Response to IFN-γ

Mass-spectrometry-enabled ADP-ribosylation workflows are developing rapidly, providing researchers a variety of ADP-ribosylome enrichment strategies and mass spectrometric acquisition options. Despite the growth spurt in upstream technologies, systematic ADP-ribosyl (ADPr) peptide mass spectral annotation methods are lacking. HCD-dependent ADP-ribosylome studies are common, but the resulting MS2 spectra are complex, owing to a mixture of b/y-ions and the m/p-ion peaks representing one or more dissociation events of the ADPr moiety (m-ion) and peptide (p-ion). In particular, p-ions that dissociate further into one or more fragment ions can dominate HCD spectra but are not recognized by standard spectral annotation workflows. As a result, annotation strategies that are solely reliant upon the b/y-ions result in lower spectral scores that in turn reduce the number of reportable ADPr peptides. To improve the confidence of spectral assignments, we implemented an ADPr peptide annotation and scoring strategy. All MS2 spectra are scored for the ADPr m-ions, but once spectra are assigned as an ADPr peptide, they are further annotated and scored for the p-ions. We implemented this novel workflow to ADPr peptides enriched from the liver and spleen isolated from mice post 4 h exposure to systemic IFN-γ. HCD collision energy experiments were first performed on the Orbitrap Fusion Lumos and the Q Exactive, with notable ADPr peptide dissociation properties verified with CID (Lumos). The m-ion and p-ion series score distributions revealed that ADPr peptide dissociation properties vary markedly between instruments and within instrument collision energy settings, with consequences on ADPr peptide reporting and amino acid localization. Consequentially, we increased the number of reportable ADPr peptides by 25% (liver) and 17% (spleen) by validation and the inclusion of lower confidence ADPr peptide spectra. This systematic annotation strategy will streamline future reporting of ADPr peptides that have been sequenced using any HCD/CID-based method.