Direct analysis and identification of proteins in mixtures by LC/MS/MS and database searching at the low-femtomole level

Multi-omic analysis of meningeal cerebral amyloid angiopathy reveals enrichment of unsubstituted glucosamine and extracellular proteins

Cerebral amyloid angiopathy (CAA) is a common feature of Alzheimer's disease in which amyloid-β (Aβ) deposits in cerebral and leptomeningeal vessel walls, predisposing vessels to micro- and macro-hemorrhages. The vessel walls contain distinct proteins and heparan sulfate (HS), yet how vascular proteins and HS jointly associate with Aβ is unknown. We conducted the first multi-omics study to systematically characterize the proteins as well as the HS abundance, sulfation level, and disaccharide composition of leptomeninges from 23 moderate to severe CAA cases and controls. We then analyzed the associations between Aβ and other proteins, HS, and apolipoprotein E genotype. We found an increase in a minor HS disaccharide containing unsubstituted glucosamine, as well as 6-O sulfated disaccharides; Aβ40 levels positively correlated with unsubstituted glucosamine. There was also an increase in extracellular proteins derived from brain parenchyma or plasma, including olfactomedin-like protein 3, fibrinogen, serum amyloid protein, apolipoprotein E, and secreted frizzled related protein-3. Our findings of vascular HS and protein alterations specific to CAA-affected leptomeningeal vessels provide molecular insight into the extracellular remodeling that co-occurs with Aβ deposits and may indicate a basis for antemortem diagnostic assay development and therapeutic strategies to impede Aβ-HS interactions.

Comparison of the Human Plasma Peptides from the Fit of Fragmentation Spectra versus Accurate Monoisotopic Precursor Mass

In nature, ionized peptides with heavy isotopes and hydrogen rearrangements show a broad mass distribution with signals at discrete delta mass values from -3 to +5 Da by mass spectrometry (MS). For many peptides, the intensity of the +1 or +2 Da isotope exceeds the signal from the monoisotopic mass. Therefore, there is a need for a method that improves peptide identification from heavy isotopes or hydrogen rearrangements based on the fit of tandem mass spectra. Peptides may be identified using an accurate monoisotopic precursor mass with ≤0.1 Da. However, many peptides with heavy isotopes and H-loss can be identified and enumerated based on the fit of their MS/MS spectra alone in the absence of an accurate precursor monoisotopic mass (i.e., ± 3 Da) using the X!TANDEM MS/MS fitting algorithm. In this study, human plasma samples were analyzed with a highly resolving axially harmonic orbital ion trap (OIT) and a sensitive linear quadrupole ion trap (LIT). The MS/MS fragmentation spectra from the OIT can be fit to peptides from the monoisotopic (±0.1 Da) as well as all other precursor masses with a wide mass tolerance (±3 Da). The resulting delta mass distribution can then be plotted and compared to the predicted distribution of heavy isotopes and hydrogen rearrangements to provide a direct biophysical prediction and test the validity of the fit determined by accepting the best-fit MS/MS spectra. The OIT instrument, which has greater resolution, was sampled at 30 nL per minute, while the more sensitive LIT was sampled at 200 nL per minute. The MS/MS spectra generated by each instrument were fit to peptides within a wide window (±3 Da) using the rigorous X!TANDEM algorithm. The OIT and LIT results were compared in an SQL Server database and corrected against analytical and statistical controls. The delta mass distribution of the peptides with hydrogen rearrangements and heavy isotopes was determined from the fit MS/MS spectra using the R statistical program. The OIT sampled MS and MS/MS spectra from the high-intensity precursor ions by focusing on E7 to E9 detector counts. In contrast, the LIT sampled a range of precursor ion intensities focused from E4 to E7 and thus reached lower ion intensity values. As expected, the precursor mass [M + H]+ obtained by the OIT exhibited sharp delta mass peaks at -3, -2, -1, 0, +1, +2, +3, +4, and +5 Da due to naturally occurring heavy isotopes and hydrogen rearrangements. The collection of peptides and proteins identified by OIT and LIT was in qualitative and quantitative agreement with one another, with 99.9% overlap on 2726 protein gene symbols from human plasma and a highly significant relationship by regression analysis. The protein p-values, false discovery rate q-values, and comparisons to the noise MS/MS analytical control and random MS/MS statistical control confirmed the high-confidence MS/MS identifications from both instruments. MS/MS fragmentation spectra from the OIT were fit to peptides. The resulting precursor ion delta mass distribution showed a precise match to the predicted isotope distributions and hydrogen rearrangements of natural peptides. Thus, analysis of delta mass plots provided powerful biophysical evidence for the accuracy of plasma peptide identification from the fit of the MS/MS spectra alone. The high level of agreement on proteins and peptides and the proportional enumeration between proteins identified by the OIT and those identified independently using a LIT confirmed that plasma peptides and proteins may be identified and quantified from MS/MS spectra alone without the need for an accurate measure of the precursor mass. The greater sensitivity and low cost of searching MS/MS spectra in the absence of an accurate mass mean that it is possible to identify and quantify more proteins for the discovery of proteins in clinical populations.

Selected Ion Extraction of Peptides with Heavy Isotopes and Hydrogen Loss Reduces the Type II Error in Plasma Proteomics

Naturally occurring peptides display a wide mass distribution after ionization due to the presence of heavy isotopes of C, H, N, O, and S and hydrogen loss. There is a crucial need for sensitive methods that collect as much information as possible about all plasma peptide forms. Statistical analysis of the delta mass distribution of peptide precursors from MS/MS spectra that were matched to 63,077 peptide sequences by X!TANDEM revealed Gaussian peaks representing heavy isotopes and hydrogen loss at integer delta mass values of -3, -2, -1, 0, +1, +2, +3, +4, and +5 Da. Human plasma samples were precipitated in acetonitrile, and the resulting proteins were collected over a quaternary amine resin, eluted with NaCl, digested with trypsin, and analyzed by nano liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) with an orbital ion trap (OIT). Fragment spectra (MS/MS) generated from the OIT data were fit to human fully tryptic peptides by X!TANDEM, which led to the identification of 3,888 protein gene symbols represented by three or more peptides (n ≥ 3). The peptide counts to plasma proteins from experimental MS/MS spectra were corrected against 29 blank LC-ESI-MS/MS spectra and 30 million random MS/MS control spectra to yield 2,784 true positive proteins (n ≥ 3; q ≤ 0.01). Peptides identified by fragmenting ions with Gaussian heavy isotopes and hydrogen loss that were matched to known plasma proteins, such as albumin (ALB), were shown to be true positives and agreed with the peptide sequences identified in the monoisotopic peak. Accepting the ions from the monoisotopic peak alone (±0.1 Da) yielded only 382 plasma proteins (n ≥ 3; type I error q ≤ 0.01; type II error ∼86%). In contrast, accepting all ions within ±0.1 Da around the hydrogen loss, monoisotopic, and heavy isotopic peaks led to the identification of 963 proteins (n ≥ 3; q ≤ 0.01; type II error ∼60%). Using the power of the OIT to resolve the Gaussian peaks from heavy isotopes and hydrogen loss resulted in the identification of three times more proteins with high confidence and a much lower type II error than analyzing peptides from the monoisotopic peak alone. The resolving power of the OIT may be exploited to increase observation frequencies and provide greater proteomic coverage and statistical power in comparative proteomics studies.

DYRK1A interacts with the tuberous sclerosis complex and promotes mTORC1 activity

DYRK1A, a ubiquitously expressed kinase, is linked to the dominant intellectual developmental disorder, microcephaly, and Down syndrome in humans. It regulates numerous cellular processes such as cell cycle, vesicle trafficking, and microtubule assembly. DYRK1A is a critical regulator of organ growth; however, how it regulates organ growth is not fully understood. Here, we show that the knockdown of DYRK1A in mammalian cells results in reduced cell size, which depends on mTORC1. Using proteomic approaches, we found that DYRK1A interacts with the tuberous sclerosis complex (TSC) proteins, namely TSC1 and TSC2, which negatively regulate mTORC1 activation. Furthermore, we show that DYRK1A phosphorylates TSC2 at T1462, a modification known to inhibit TSC activity and promote mTORC1 activity. We also found that the reduced cell growth upon knockdown of DYRK1A can be rescued by overexpression of RHEB, an activator of mTORC1. Our findings suggest that DYRK1A inhibits TSC complex activity through inhibitory phosphorylation on TSC2, thereby promoting mTORC1 activity. Furthermore, using the Drosophila neuromuscular junction as a model, we show that the mnb, the fly homologs of DYRK1A, is rescued by RHEB overexpression, suggesting a conserved role of DYRK1A in TORC1 regulation.

Influence of Software Settings on the Identification Rate, Quantification Results, and Reproducibility in Profiling Post-Translational Modifications by Microflow Liquid Chromatography-Ion Mobility-Quadrupole Time-Of-Flight Analysis Using PEAKS Software

The influence of data evaluation parameters on qualitative and quantitative results of untargeted shotgun profiling of enzymatic and nonenzymatic post-translational modifications (PTMs) was investigated in a model of bovine whey protein α-lactalbumin heated with lactose. Based on the same raw data, individual adjustments to the protein database and enzyme settings of PEAKS studio software increased the identification rate from 27 unmodified peptides to 48 and from 322 peptides in total to 535. The qualitative and quantitative reproducibility was also assessed based on 18 measurements of one sample across three batches. A total of 570 peptides were detected. While 89 peptides were identified in all measurements, the majority of peptides (161) were detected only once and mostly based on nonindicative spectra. The reproducibility of label-free quantification (LFQ) in six measurements of the same sample was similar after processing the data by either the PTM algorithm or the LFQ algorithm. In both cases, about one-third of the peptides showed a coefficient of variation of above 20%. However, the LFQ algorithm increased the number of quantified peptides from 75 to 179. Data are available at the PRIDE Archive with the data set identifier PXD050363.

Transformer-based de novo peptide sequencing for data-independent acquisition mass spectrometry

Tandem mass spectrometry (MS/MS) stands as the predominant high-throughput technique for comprehensively analyzing protein content within biological samples. This methodology is a cornerstone driving the advancement of proteomics. In recent years, substantial strides have been made in Data-Independent Acquisition (DIA) strategies, facilitating impartial and non-targeted fragmentation of precursor ions. The DIA-generated MS/MS spectra present a formidable obstacle due to their inherent high multiplexing nature. Each spectrum encapsulates fragmented product ions originating from multiple precursor peptides. This intricacy poses a particularly acute challenge in de novo peptide/protein sequencing, where current methods are ill-equipped to address the multiplexing conundrum. In this paper, we introduce Casanovo-DIA, a deep-learning model based on transformer architecture. It deciphers peptide sequences from DIA mass spectrometry data. Our results show significant improvements over existing STOA methods, including DeepNovo-DIA and PepNet. Casanovo-DIA enhances precision by 15.14% to 34.8%, recall by 11.62% to 31.94% at the amino acid level, and boosts precision by 59% to 81.36% at the peptide level. Integrating DIA data and our Casanovo-DIA model holds considerable promise to uncover novel peptides and more comprehensive profiling of biological samples. Casanovo-DIA is freely available under the GNU GPL license at https://github.com/Biocomputing-Research-Group/Casanovo-DIA.

Roles for the Synechococcus elongatus RNA-Binding Protein Rbp2 in Regulating the Circadian Clock

The cyanobacterial circadian oscillator, consisting of KaiA, KaiB, and KaiC proteins, drives global rhythms of gene expression and compaction of the chromosome and regulates the timing of cell division and natural transformation. While the KaiABC posttranslational oscillator can be reconstituted in vitro, the Kai-based oscillator is subject to several layers of regulation in vivo. Specifically, the oscillator proteins undergo changes in their subcellular localization patterns, where KaiA and KaiC are diffuse throughout the cell during the day and localized as a focus at or near the pole of the cell at night. Here, we report that the CI domain of KaiC, when in a hexameric state, is sufficient to target KaiC to the pole. Moreover, increased ATPase activity of KaiC correlates with enhanced polar localization. We identified proteins associated with KaiC in either a localized or diffuse state. We found that loss of Rbp2, found to be associated with localized KaiC, results in decreased incidence of KaiC localization and long-period circadian phenotypes. Rbp2 is an RNA-binding protein, and it appears that RNA-binding activity of Rbp2 is required to execute clock functions. These findings uncover previously unrecognized roles for Rbp2 in regulating the circadian clock and suggest that the proper localization of KaiC is required for a fully functional clock in vivo.

Reversed-Phase Liquid Chromatography of Peptides for Bottom-Up Proteomics: A Tutorial

The performance of the current bottom-up liquid chromatography hyphenated with mass spectrometry (LC-MS) analyses has undoubtedly been fueled by spectacular progress in mass spectrometry. It is thus not surprising that the MS instrument attracts the most attention during LC-MS method development, whereas optimizing conditions for peptide separation using reversed-phase liquid chromatography (RPLC) remains somewhat in its shadow. Consequently, the wisdom of the fundaments of chromatography is slowly vanishing from some laboratories. However, the full potential of advanced MS instruments cannot be achieved without highly efficient RPLC. This is impossible to attain without understanding fundamental processes in the chromatographic system and the properties of peptides important for their chromatographic behavior. We wrote this tutorial intending to give practitioners an overview of critical aspects of peptide separation using RPLC to facilitate setting the LC parameters so that they can leverage the full capabilities of their MS instruments. After briefly introducing the gradient separation of peptides, we discuss their properties that affect the quality of LC-MS chromatograms the most. Next, we address the in-column and extra-column broadening. The last section is devoted to key parameters of LC-MS methods. We also extracted trends in practice from recent bottom-up proteomics studies and correlated them with the current knowledge on peptide RPLC separation.

Evaluation of Machine Learning Models for Proteoform Retention and Migration Time Prediction in Top-Down Mass Spectrometry

Reversed-phase liquid chromatography (RPLC) and capillary zone electrophoresis (CZE) are two primary proteoform separation methods in mass spectrometry (MS)-based top-down proteomics. Proteoform retention time (RT) prediction in RPLC and migration time (MT) prediction in CZE provide additional information for accurate proteoform identification and quantification. While existing methods are mainly focused on peptide RT and MT prediction in bottom-up MS, there is still a lack of methods for proteoform RT and MT prediction in top-down MS. We systematically evaluated eight machine learning models and a transfer learning method for proteoform RT prediction and five models and the transfer learning method for proteoform MT prediction. Experimental results showed that a gated recurrent unit (GRU)-based model with transfer learning achieved a high accuracy (R = 0.978) for proteoform RT prediction and that the GRU-based model and a fully connected neural network model obtained a high accuracy of R = 0.982 and 0.981 for proteoform MT prediction, respectively.

Polypyrimidine tract binding proteins PTBP1 and PTBP2 interact with distinct proteins under splicing conditions

RNA binding proteins play an important role in regulating alternative pre-mRNA splicing and in turn cellular gene expression. Polypyrimidine tract binding proteins, PTBP1 and PTBP2, are paralogous RNA binding proteins that play a critical role in the process of neuronal differentiation and maturation; changes in the concentration of PTBP proteins during neuronal development direct splicing changes in many transcripts that code for proteins critical for neuronal differentiation. How the two related proteins regulate different sets of neuronal exons is unclear. The distinct splicing activities of PTBP1 and PTBP2 can be recapitulated in an in vitro splicing system with the differentially regulated N1 exon of the c-src pre-mRNA. Here, we conducted experiments under these in vitro splicing conditions to identify PTBP1 and PTBP2 interacting partner proteins. Our results highlight that both PTBPs interact with proteins that participate in chromatin remodeling and transcription regulation. Our data reveal that PTBP1 interacts with many proteins involved in mRNA processing including splicing regulation while PTBP2 does not. Our results also highlight enzymes that can serve as potential "writers" and "erasers" in adding chemical modifications to the PTB proteins. Overall, our study highlights important differences in protein-protein interactions between the PTBP proteins under splicing conditions and supports a role for post-translational modifications in dictating their distinct splicing activities.

Affinity Selection from Synthetic Peptide Libraries Enabled by De Novo MS/MS Sequencing

Recently, de novo MS/MS peptide sequencing has enabled the application of affinity selections to synthetic peptide mixtures that approach the diversity of phage libraries (> 108 random peptides). In conjunction with ‘split-mix’ solid phase synthesis to access equimolar peptide mixtures, this approach provides a straightforward means to examine synthetic peptide libraries of considerably higher diversity than has been feasible historically. Here, we offer a critical perspective on this work, report emerging data, and highlight opportunities for further methods refinement. With continued development, ‘affinity selection–mass spectrometry’ may become a complimentary approach to phage display, in vitro selection, and DNA-encoded libraries for the discovery of synthetic ligands that modulate protein function.

A direct method for detecting proteins in body fluids by Surface-Enhanced Raman Spectroscopy under native conditions

Surface enhanced Raman spectroscopy (SERS) is widely used in biomolecular detection. However, maintaining the native structure of proteins while obtaining sensitive and reproducible SERS signals of unlabeled proteins remains a challenge. In this study, dichloromethane (DCM) and CaCl₂ were used to optimize the aggregation of Ag nanoparticles (AgNPs), and several proteins were analyzed comprehensively. Calcium ions removed citrate ions outside AgNPs, inducing hot spots and achieving high-sensitivity SERS signals of proteins. Furthermore, 20 random samples of 0.5 μg/mL hemoglobin were analyzed by this method. The obtained spectra showed good repeatability and a high quality. Using the peak intensity of DCM as internal parameter, the differences in peak intensities at the same position were analyzed to distinguish different proteins and evaluate changes in protein structure. Subsequently, the protein content in protein mixtures and serum was quantified and a good linear relationship between peak intensity and protein concentration was obtained. This method shows great promise in the fields of food testing and clinical diagnosis.

Bottom-up/cross-linking mass spectrometry via simplified sample processing on anion-exchange solid-phase extraction spin column

We introduce a simple single-column protein digestion method for low-microgram-level samples containing sodium dodecyl sulfate and Coomassie dye that can be completed within a few hours.

Pipelines and Systems for Threshold-Avoiding Quantification of LC-MS/MS Data

The accurate processing of complex liquid chromatography coupled to tandem mass spectrometry (LC–MS/MS) data from biological samples is a major challenge for metabolomics, proteomics, and related approaches. Here, we present the pipelines and systems for threshold-avoiding quantification (PASTAQ) LC–MS/MS preprocessing toolset, which allows highly accurate quantification of data-dependent acquisition LC–MS/MS datasets. PASTAQ performs compound quantification using single-stage (MS1) data and implements novel algorithms for high-performance and accurate quantification, retention time alignment, feature detection, and linking annotations from multiple identification engines. PASTAQ offers straightforward parameterization and automatic generation of quality control plots for data and preprocessing assessment. This design results in smaller variance when analyzing replicates of proteomes mixed with known ratios and allows the detection of peptides over a larger dynamic concentration range compared to widely used proteomics preprocessing tools. The performance of the pipeline is also demonstrated in a biological human serum dataset for the identification of gender-related proteins.

BAC-DROP: Rapid Digestion of Proteome Fractionated via Dissolvable Polyacrylamide Gel Electrophoresis and Its Application to Bottom-Up Proteomics Workflow

The GeLC-MS workflow, which combines low-cost, easy-to-use sodium dodecyl sulfate (SDS)-polyacrylamide gel electrophoresis (SDS-PAGE) with liquid chromatography-mass spectrometry (LC-MS), is very popular in current bottom-up proteomics. However, GeLC-MS requires that PAGE-separated proteins undergo overnight enzymatic digestion in a gel, resulting in more than 20 h of sample preparation for LC-MS. In this study, we overcame the limitations of GeLC-MS by developing a rapid digestion workflow for PAGE separation of proteins using N,N'-bis(acryloyl)cystamine (BAC) cross-linked gels that can be solubilized by reductive treatment. Making use of an established workflow called BAC-DROP (BAC-gel dissolution to digest PAGE-resolved objective proteins), crude proteome samples were fractionated based on molecular weight by BAC cross-linked PAGE. After fractionation, the gel fragments were reductively dissolved in under 5 min, and in-solution trypsin digestion of the protein released from the gel was completed in less than 1 h at 70 °C, equivalent to a 90-95% reduction in time compared to conventional in-gel trypsin digestion. The introduction of the BAC-DROP workflow to the MS assays for inflammatory biomarker CRP and viral marker HBsAg allowed for serum sample preparation to be completed in as little as 5 h, demonstrating successful marker quantification from a 0.5 μL sample of human serum.

Emerging Roles of Single-Cell Multi-Omics in Studying Developmental Temporal Patterning

The complexity of brain structure and function is rooted in the precise spatial and temporal regulation of selective developmental events. During neurogenesis, both vertebrates and invertebrates generate a wide variety of specialized cell types through the expansion and specification of a restricted set of neuronal progenitors. Temporal patterning of neural progenitors rests on fine regulation between cell-intrinsic and cell-extrinsic mechanisms. The rapid emergence of high-throughput single-cell technologies combined with elaborate computational analysis has started to provide us with unprecedented biological insights related to temporal patterning in the developing central nervous system (CNS). Here, we present an overview of recent advances in Drosophila and vertebrates, focusing both on cell-intrinsic mechanisms and environmental influences. We then describe the various multi-omics approaches that have strongly contributed to our current understanding and discuss perspectives on the various -omics approaches that hold great potential for the future of temporal patterning research.

LRRK2 mediates axon development by regulating Frizzled3 phosphorylation and growth cone-growth cone communication

Axon-axon interactions are essential for axon guidance during nervous system wiring. However, it is unknown whether and how the growth cones communicate with each other while sensing and responding to guidance cues. We found that the Parkinson's disease gene, leucine-rich repeat kinase 2 (LRRK2), has an unexpected role in growth cone-growth cone communication. The LRRK2 protein acts as a scaffold and induces Frizzled3 hyperphosphorylation indirectly by recruiting other kinases and also directly phosphorylates Frizzled3 on threonine 598 (T598). In LRRK1 or LRRK2 single knockout, LRRK1/2 double knockout, and LRRK2 G2019S knockin, the postcrossing spinal cord commissural axons are disorganized and showed anterior-posterior guidance errors after midline crossing. Growth cones from either LRRK2 knockout or G2019S knockin mice showed altered interactions, suggesting impaired communication. Intercellular interaction between Frizzled3 and Vangl2 is essential for planar cell polarity signaling. We show here that this interaction is regulated by phosphorylation of Frizzled3 at T598 and can be regulated by LRRK2 in a kinase activity-dependent way. In the LRRK1/2 double knockout or LRRK2 G2019S knockin, the dopaminergic axon bundle in the midbrain was significantly widened and appeared disorganized, showing aberrant posterior-directed growth. Our findings demonstrate that LRRK2 regulates growth cone-growth cone communication in axon guidance and that both loss-of-function mutation and a gain-of-function mutation (G2019S) cause axon guidance defects in development.

The Journey Is the Reward, a Taoist Proverb: John B. Fenn Award for Distinguished Contribution in Mass Spectrometry Lecture

This account provided by John Yates describes his incredible path as a scientist, emphasizing key decisions along the way that shaped his career and led to his landmark contributions to the field of mass spectrometry. Although perhaps best known is the development of the SEQUEST algorithm for automated interpretation of tandem mass spectra of peptides, John's achievements have spanned the field of proteomics and had major impact on the ability to address and solve significant biological problems.

The development and clinical applications of proteomics: an Indian perspective

INTRODUCTION

Proteomic research has been extensively used to identify potential biomarkers or targets for various diseases. Advances in mass spectrometry along with data analytics have led proteomics to become a powerful tool for exploring the critical molecular players associated with diseases, thereby, playing a significant role in the development of proteomic applications for the clinic.

AREAS COVERED

This review presents recent advances in the development and clinical applications of proteomics in India toward understanding various diseases including cancer, metabolic diseases, and reproductive diseases. Keywords combined with 'clinical proteomics in India' 'proteomic research in India' and 'mass spectrometry' were used to search PubMed.

EXPERT OPINION

The past decade has seen a significant increase in research in clinical proteomics in India. This approach has resulted in the development of proteomics-based marker technologies for disease management in the country. The majority of these investigations are still in the discovery phase and efforts have to be made to address the intended clinical use so that the identified potential biomarkers reach the clinic. To move toward this necessity, there is a pressing need to establish some key infrastructure requirements and meaningful collaborations between the clinicians and scientists which will enable more effective solutions to address health issues specific to India.

Estimation of low-level components lost through chromatographic separations with finite detection limits

The search for biomarkers allowing the assessment of disease by early diagnosis is facilitated by liquid chromatography. However, it is not clear how many components are lost due to being present in concentrations below the detection limit and/or being obscured by chromatographic peak overlap. First, we extend the study of missing components undertaken by Enke and Nagels, who employed the log-normal probability density function (pdf) for the distribution of signal intensities (and concentrations) of three mixtures. The Weibull and exponential pdfs, which have a higher probability of small-concentration components than the log-normal pdf, are also investigated. Results show that assessments of the loss of low-intensity signals by curve fitting are ambiguous. Next, we simulate synthetic chromatograms to compare the loss of peaks from superposition (overlap) with neighboring peaks to the loss arising from lying below the limit of detection (LOD) imposed by a finite signal-to-noise ratio (SNR). The simulations are made using amplitude pdfs based on the Enke-Nagels data as functions of relative column efficiency, i.e., saturation, and SNR. Results show that at the highest efficiencies, the lowest-amplitude peaks are lost below the LOD. However, at small and medium efficiencies, peak overlap is the dominant loss mechanism, suggesting that low-level components will not be found easily in liquid chromatography with single channel detectors regardless of SNR. A simple treatment shows that a multichannel detector, e.g., a mass spectrometer, is necessary to expose more low-level components.

SRPK1 acetylation modulates alternative splicing to regulate cisplatin resistance in breast cancer cells

Cisplatin and other platinum-based compounds are frequently used to treat breast cancer, but their utility is severely compromised by drug resistance. Many genes dictating drug responsiveness are subject to pre-mRNA alternative splicing which is regulated by key kinases such as the serine-arginine protein kinase 1 (SRPK1). However, its contribution to drug resistance remains controversial. In this study, we have identified that Tip60-mediated acetylation of SRPK1 is closely associated with chemotherapy sensitivity. In breast cancer cells, cisplatin induced SRPK1 acetylation but in the corresponding resistant cells, it reduced acetylation yet increased phosphorylation and kinase activity of SRPK1, favouring the splicing of some anti-apoptotic variants. Significantly, the cisplatin-resistant cells could be re-sensitized by enhancing SRPK1 acetylation or inhibiting its kinase activity. Hence, our study reveals a key role of SRPK1 in the development of cisplatin resistance in breast cancer cells and suggests a potential therapeutic avenue for overcoming chemotherapy resistance.

Wang et al. find that the therapeutic agent cisplatin has opposite effect on acetylation of serine-arginine protein kinase 1 (SRPK1) in cisplatin-resistant versus – sensitive breast cancer cells. Inhibiting SRPK1 activity or enhancing its acetylation re-sensitises cells to cisplatin, suggesting a potential strategy to treat cancers resistant to platinum-based therapy.

Click chemistry-facilitated comprehensive identification of proteins adducted by antimicrobial 5-nitroimidazoles for discovery of alternative drug targets against giardiasis

Giardiasis and other protozoan infections are major worldwide causes of morbidity and mortality, yet development of new antimicrobial agents with improved efficacy and ability to override increasingly common drug resistance remains a major challenge. Antimicrobial drug development typically proceeds by broad functional screens of large chemical libraries or hypothesis-driven exploration of single microbial targets, but both strategies have challenges that have limited the introduction of new antimicrobials. Here, we describe an alternative drug development strategy that identifies a sufficient but manageable number of promising targets, while reducing the risk of pursuing targets of unproven value. The strategy is based on defining and exploiting the incompletely understood adduction targets of 5-nitroimidazoles, which are proven antimicrobials against a wide range of anaerobic protozoan and bacterial pathogens. Comprehensive adductome analysis by modified click chemistry and multi-dimensional proteomics were applied to the model pathogen Giardia lamblia to identify dozens of adducted protein targets common to both 5'-nitroimidazole-sensitive and -resistant cells. The list was highly enriched for known targets in G. lamblia, including arginine deiminase, α-tubulin, carbamate kinase, and heat shock protein 90, demonstrating the utility of the approach. Importantly, over twenty potential novel drug targets were identified. Inhibitors of two representative new targets, NADP-specific glutamate dehydrogenase and peroxiredoxin, were found to have significant antigiardial activity. Furthermore, all the identified targets remained available in resistant cells, since giardicidal activity of the respective inhibitors was not impacted by resistance to 5'-nitroimidazoles. These results demonstrate that the combined use of click chemistry and proteomics has the potential to reveal alternative drug targets for overcoming antimicrobial drug resistance in protozoan parasites.

Application of Solid-State Nanopore in Protein Detection

A protein is a kind of major biomacromolecule of life. Its sequence, structure, and content in organisms contains quite important information for normal or pathological physiological process. However, research of proteomics is facing certain obstacles. Only a few technologies are available for protein analysis, and their application is limited by chemical modification or the need for a large amount of sample. Solid-state nanopore overcomes some shortcomings of the existing technology, and has the ability to detect proteins at a single-molecule level, with its high sensitivity and robustness of device. Many works on detection of protein molecules and discriminating structure have been carried out in recent years. Single-molecule protein sequencing techniques based on solid-state nanopore are also been proposed and developed. Here, we categorize and describe these efforts and progress, as well as discuss their advantages and drawbacks.

Gp4 is a nuclease required for morphogenesis of T4-like bacteriophages

An essential step in the morphogenesis of tailed bacteriophages is the joining of heads and tails to form infectious virions. Our understanding of the maturation of complete virus particles remains incomplete. Through an unknown mechanism, phage T4 gene product 4 (gp4) plays an essential role in the head-tail joining step of T4-like phages. Alignment of T4 gp4 homologs identified a type II restriction endonuclease motif. Purified gp4 from both T4 and a marine T4-like bacteriophage, YC, have non-specific nuclease activity in vitro. Mutation of a single conserved amino acid residue in the endonuclease fold of T4 and YC gp4 abrogates nuclease activity. When expressed in trans, the wild type T4 gp4, but neither the mutated T4 protein nor the YC homolog, rescues a T4 gene 4 amber mutant phage. Thus the nuclease activity appears essential for morphogenesis, potentially by cleaving packaged DNA to enable the joining of heads to tails.

Comparison of CRISPR Genomic Tagging for Affinity Purification and Endogenous Immunoprecipitation Coupled with Quantitative Mass Spectrometry To Identify the Dynamic AMPKα2 Interactome

Recent advances in genome editing technologies have enabled the insertion of epitope tags at endogenous loci with relative efficiency. We describe an approach for investigation of protein interaction dynamics of the AMP-activated kinase complex AMPK using a catalytic subunit AMPKα2 (PRKAA2 gene) as the bait, based on CRISPR/Cas9-mediated genome editing coupled to stable isotope labeling in cell culture, multidimensional protein identification technology, and computational and statistical analyses. Furthermore, we directly compare this genetic epitope tagging approach to endogenous immunoprecipitations of the same gene under homologous conditions to assess differences in observed interactors. Additionally, we directly compared each enrichment strategy in the genetically modified cell-line with two separate endogenous antibodies. For each approach, we analyzed the interaction profiles of this protein complex under basal and activated states, and after implementing the same analytical, computational, and statistical analyses, we found that high-confidence protein interactors vary greatly with each method and between commercially available endogenous antibodies.

A Novel, Highly Related Jumbo Family of Bacteriophages That Were Isolated Against Erwinia

Erwinia amylovora is a plant pathogen from the Erwiniaceae family and a causative agent of the devastating agricultural disease fire blight. Here we characterize eight lytic bacteriophages of E. amylovora that we isolated from the Wasatch front (Utah, United States) that are highly similar to vB_EamM_Ea35-70 which was isolated in Ontario, Canada. With the genome size ranging from 271 to 275 kb, this is a novel jumbo family of bacteriophages. These jumbo bacteriophages were further characterized through genomic and proteomic comparison, mass spectrometry, host range and burst size. Their proteomes are highly unstudied, with over 200 putative proteins with no known homologs. The production of 27 of these putative proteins was confirmed by mass spectrometry analysis. These bacteriophages appear to be most similar to bacteriophages that infect Pseudomonas and Ralstonia rather than Enterobacteriales bacteria by protein similarity, however, we were only able to detect infection of Erwinia and the closely related strains of Pantoea.

Best practices and benchmarks for intact protein analysis for top-down mass spectrometry

One gene can give rise to many functionally distinct proteoforms, each of which has a characteristic molecular mass. Top-down mass spectrometry enables the analysis of intact proteins and proteoforms. Here members of the Consortium for Top-Down Proteomics provide a decision tree that guides researchers to robust protocols for mass analysis of intact proteins (antibodies, membrane proteins and others) from mixtures of varying complexity. We also present cross-platform analytical benchmarks using a protein standard sample, to allow users to gauge their proficiency.

Recent technical advances in proteomics

Mass spectrometry is one of the key technologies of proteomics, and over the last decade important technical advances in mass spectrometry have driven an increased capability for proteomic discovery. In addition, new methods to capture important biological information have been developed to take advantage of improving proteomic tools.

The Regulation of Cbf1 by PAS Kinase Is a Pivotal Control Point for Lipogenesis vs. Respiration in Saccharomyces cerevisiae

PAS kinase 1 (Psk1) is a key regulator of respiration in Saccharomyces cerevisiae. Herein the molecular mechanisms of this regulation are explored through the characterization of its substrate, Centromere binding factor 1 (Cbf1). CBF1-deficient yeast displayed a significant decrease in cellular respiration, while PAS kinase-deficient yeast, or yeast harboring a Cbf1 phosphosite mutant (T211A) displayed a significant increase. Transmission electron micrographs showed an increased number of mitochondria in PAS kinase-deficient yeast consistent with the increase in respiration. Although the CBF1-deficient yeast did not appear to have an altered number of mitochondria, a mitochondrial proteomics study revealed significant differences in the mitochondrial composition of CBF1-deficient yeast including altered Atp3 levels, a subunit of the mitochondrial F₁-ATP synthase complex. Both beta-galactosidase reporter assays and western blot analysis confirmed direct transcriptional control of ATP3 by Cbf1. In addition, we confirmed the regulation of yeast lipid genes LAC1 and LAG1 by Cbf1. The human homolog of Cbf1, Upstream transcription factor 1 (USF1), is also known to be involved in lipid biogenesis. Herein, we provide the first evidence for a role of USF1 in respiration since it appeared to complement Cbf1in vivo as determined by respiration phenotypes. In addition, we confirmed USF1 as a substrate of human PAS kinase (hPASK) in vitro. Combined, our data supports a model in which Cbf1/USF1 functions to partition glucose toward respiration and away from lipid biogenesis, while PAS kinase inhibits respiration in part through the inhibition of Cbf1/USF1.

Paving the way to single-molecule protein sequencing

Proteins are major building blocks of life. The protein content of a cell and an organism provides key information for the understanding of biological processes and disease. Despite the importance of protein analysis, only a handful of techniques are available to determine protein sequences, and these methods face limitations, for example, requiring a sizable amount of sample. Single-molecule techniques would revolutionize proteomics research, providing ultimate sensitivity for the detection of low-abundance proteins and the realization of single-cell proteomics. In recent years, novel single-molecule protein sequencing schemes that use fluorescence, tunnelling currents and nanopores have been proposed. Here, we present a review of these approaches, together with the first experimental efforts towards their realization. We discuss their advantages and drawbacks, and present our perspective on the development of single-molecule protein sequencing techniques.

Re-evaluation of the rabbit myosin protein standard used to create the empirical statistical model for decoy library searching

A Rabbit myosin standard, like that used to create the empirical statistical model, was randomly and independently sampled by liquid chromatography micro electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS) with a linear quadrupole ion trap. The rabbit myosin protein standard appeared pure by SDS-PAGE and CBBR staining but showed many other proteins by silver staining. The LC-MS intensity from myosin and IgG samples were above the 99% safe limit of detection and quantification computed from 36 blank LC-ESI-MS/MS runs. The myosin contained ≤406 Gene Symbols, open reading frames or loci where 79 protein types showed ≥3 peptides from X!TANDEM. Myosins, actin, troponin, other proteins showed 95%-100% homology between the rabbit versus the human decoy library. The myosin protein complex from STRING was true positive compared to random or noise spectra MS/MS with a low type I error (p-value) and low FDR (q-value) computed in R. SDS-PAGE, Western blot, comparison to random and noise MS/MS spectra, X!TANDEM p-values, FDR corrected q-values, and STRING all agreed that the error rate of LC-ESI-MS/MS with a quadrupole ion trap is far below that assumed a priori by the design of the empirical statistical model for decoy library searching.

The Proteome of Cataract Markers: Focus on Crystallins

Cataract is a major cause of blindness worldwide. It is characterized by lens opacification and is accompanied by extensive posttranslational modifications (PTMs) in various proteins. PTMs play an essential role in lens opacification. Several PTMs have been described in proteins isolated from relatively old human lenses, including phosphorylation, deamidation, racemization, truncation, acetylation, and methylation. An overwhelming majority of previous cataract proteomic studies have exclusively focused on crystallin proteins, which are the most abundant proteome components of the lens. To investigate the proteome of cataract markers, this chapter focuses on the proteomic research on the functional relevance of the major PTMs in crystallins of human cataractous lenses. Elucidating the role of these modifications in cataract formation has been a challenging task because they are among the most difficult PTMs to study analytically. The proteomic status of some amides presents similar properties in normal aged and cataractous lenses, whereas some may undergo greater PTMs in cataract. Therefore, it is of great importance to review the current proteomic research on crystallins, the major protein markers in different types of cataract, to elucidate the pathogenesis of this major human-blinding condition.

Characterization of two related Erwinia myoviruses that are distant relatives of the PhiKZ-like Jumbo phages

Bacteriophages are a major force in the evolution of bacteria due to their sheer abundance as well as their ability to infect and kill their hosts and to transfer genetic material. Bacteriophages that infect the Enterobacteriaceae family are of particular interest because this bacterial family contains dangerous animal and plant pathogens. Herein we report the isolation and characterization of two jumbo myovirus Erwinia phages, RisingSun and Joad, collected from apple trees. These two genomes are nearly identical with Joad harboring two additional putative gene products. Despite mass spectrometry data that support the putative annotation, 43% of their gene products have no significant BLASTP hit. These phages are also more closely related to Pseudomonas and Vibrio phages than to published Enterobacteriaceae phages. Of the 140 gene products with a BLASTP hit, 81% and 63% of the closest hits correspond to gene products from Pseudomonas and Vibrio phages, respectively. This relatedness may reflect their ecological niche, rather than the evolutionary history of their host. Despite the presence of over 800 Enterobacteriaceae phages on NCBI, the uniqueness of these two phages highlights the diversity of Enterobacteriaceae phages still to be discovered.

DDX3 suppresses type I interferons and favors viral replication during Arenavirus infection

Several arenaviruses cause hemorrhagic fever (HF) diseases that are associated with high morbidity and mortality in humans. Accordingly, HF arenaviruses have been listed as top-priority emerging diseases for which countermeasures are urgently needed. Because arenavirus nucleoprotein (NP) plays critical roles in both virus multiplication and immune-evasion, we used an unbiased proteomic approach to identify NP-interacting proteins in human cells. DDX3, a DEAD-box ATP-dependent-RNA-helicase, interacted with NP in both NP-transfected and virus-infected cells. Importantly, DDX3 deficiency compromised the propagation of both Old and New World arenaviruses, including the HF arenaviruses Lassa and Junin viruses. The DDX3 role in promoting arenavirus multiplication associated with both a previously un-recognized DDX3 inhibitory role in type I interferon production in arenavirus infected cells and a positive DDX3 effect on arenavirus RNA synthesis that was dependent on its ATPase and Helicase activities. Our results uncover novel mechanisms used by arenaviruses to exploit the host machinery and subvert immunity, singling out DDX3 as a potential host target for developing new therapies against highly pathogenic arenaviruses.

Convergence of Wnt, growth factor, and heterotrimeric G protein signals on the guanine nucleotide exchange factor Daple

Cellular proliferation, differentiation, and morphogenesis are shaped by multiple signaling cascades, and their dysregulation plays an integral role in cancer progression. Three cascades that contribute to oncogenic potential are those mediated by Wnt proteins and the receptor Frizzled (FZD), growth factor receptor tyrosine kinases (RTKs), and heterotrimeric G proteins and associated GPCRs. Daple is a guanine nucleotide exchange factor (GEF) for the G protein G_αi Daple also binds to FZD and the Wnt/FZD mediator Dishevelled (Dvl), and it enhances β-catenin-independent Wnt signaling in response to Wnt5a-FZD7 signaling. We identified Daple as a substrate of multiple RTKs and non-RTKs and, hence, as a point of convergence for the three cascades. We found that phosphorylation near the Dvl-binding motif in Daple by both RTKs and non-RTKs caused Daple/Dvl complex dissociation and augmented the ability of Daple to bind to and activate G_αi, which potentiated β-catenin-independent Wnt signals and stimulated epithelial-mesenchymal transition (EMT) similarly to Wnt5a/FZD7 signaling. Although Daple acts as a tumor suppressor in the healthy colon, the concurrent increased abundance of Daple and epidermal growth factor receptor (EGFR) in colorectal tumors was associated with poor patient prognosis. Thus, the Daple-dependent activation of G_αi and the Daple-dependent enhancement of β-catenin-independent Wnt signals are not only stimulated by Wnt5a/FZD7 to suppress tumorigenesis but also hijacked by growth factor-activated RTKs to enhance tumor progression. These findings identify a cross-talk paradigm among growth factor RTKs, heterotrimeric G proteins, and the Wnt/FZD pathway in cancer.

Identification of the S-transferase like superfamily bacillithiol transferases encoded by Bacillus subtilis

Bacillithiol is a low molecular weight thiol found in Firmicutes that is analogous to glutathione, which is absent in these bacteria. Bacillithiol transferases catalyze the transfer of bacillithiol to various substrates. The S-transferase-like (STL) superfamily contains over 30,000 putative members, including bacillithiol transferases. Proteins in this family are extremely divergent and are related by structural rather than sequence similarity, leaving it unclear if all share the same biochemical activity. Bacillus subtilis encodes eight predicted STL superfamily members, only one of which has been shown to be a bacillithiol transferase. Here we find that the seven remaining proteins show varying levels of metal dependent bacillithiol transferase activity. We have renamed the eight enzymes BstA-H. Mass spectrometry and gene expression studies revealed that all of the enzymes are produced to varying levels during growth and sporulation, with BstB and BstE being the most abundant and BstF and BstH being the least abundant. Interestingly, several bacillithiol transferases are induced in the mother cell during sporulation. A strain lacking all eight bacillithiol transferases showed normal growth in the presence of stressors that adversely affect growth of bacillithiol-deficient strains, such as paraquat and CdCl₂. Thus, the STL bacillithiol transferases represent a new group of proteins that play currently unknown, but potentially significant roles in bacillithiol-dependent reactions. We conclude that these enzymes are highly divergent, perhaps to cope with an equally diverse array of endogenous or exogenous toxic metabolites and oxidants.

Random and independent sampling of endogenous tryptic peptides from normal human EDTA plasma by liquid chromatography micro electrospray ionization and tandem mass spectrometry

Background

Normal human EDTA plasma samples were collected on ice, processed ice cold, and stored in a freezer at – 80 °C prior to experiments. Plasma test samples from the – 80 °C freezer were thawed on ice or intentionally warmed to room temperature.

Methods

Protein content was measured by CBBR binding and the release of alcohol soluble amines by the Cd ninhydrin assay. Plasma peptides released over time were collected over C18 for random and independent sampling by liquid chromatography micro electrospray ionization and tandem mass spectrometry (LC–ESI–MS/MS) and correlated with X!TANDEM.

Results

Fully tryptic peptides by X!TANDEM returned a similar set of proteins, but was more computationally efficient, than “no enzyme” correlations. Plasma samples maintained on ice, or ice with a cocktail of protease inhibitors, showed lower background amounts of plasma peptides compared to samples incubated at room temperature. Regression analysis indicated that warming plasma to room temperature, versus ice cold, resulted in a ~ twofold increase in the frequency of peptide identification over hours–days of incubation at room temperature. The type I error rate of the protein identification from the X!TANDEM algorithm combined was estimated to be low compared to a null model of computer generated random MS/MS spectra.

Conclusion

The peptides of human plasma were identified and quantified with low error rates by random and independent sampling that revealed 1000s of peptides from hundreds of human plasma proteins from endogenous tryptic peptides.

Electronic supplementary material

The online version of this article (10.1186/s12014-017-9176-7) contains supplementary material, which is available to authorized users.

The proteins cleaved by endogenous tryptic proteases in normal EDTA plasma by C18 collection of peptides for liquid chromatography micro electrospray ionization and tandem mass spectrometry

The tryptic peptides from ice cold versus room temperature plasma were identified by C18 liquid chromatography and micro electrospray ionization tandem mass spectrometry (LC–ESI–MS/MS). Samples collected on ice showed low levels of endogenous tryptic peptides compared to the same samples incubated at room temperature. Plasma on ice contained peptides from albumin, complement, and apolipoproteins and others that were observed by the X!TANDEM and SEQUEST algorithms. In contrast to ice cold samples, after incubation at room temperature, greater numbers of tryptic peptides from well characterized plasma proteins, and from cellular proteins were observed. A total of 583,927 precursor ions and MS/MS spectra were correlated to 94,669 best fit peptides that reduced to 22,287 correlations to the best accession within a gene symbol and to 7174 correlations to at least 510 gene symbols with ≥ 5 independent MS/MS correlations (peptide counts) that showed FDR q-values ranging from E−9 (i.e. FDR = 0.000000001) to E−227. A set of 528 gene symbols identified by X!TANDEM and SEQUEST including C4B showed ≥ fivefold variation between ice cold versus room temperature incubation. STRING analysis of the protein gene symbols observed from endogenous peptides in normal plasma revealed an extensive protein-interaction network of cellular factors associated with cell signalling and regulation, the formation of membrane bound organelles, cellular exosomes and exocytosis network proteins. Taken together the results indicated that a pool of cellular proteins, or protein complexes, in plasma are apparently not stable and degrade soon after incubation at room temperature.

Rotator cuff tear state modulates self-renewal and differentiation capacity of human skeletal muscle progenitor cells

Full thickness rotator cuff tendon (RCT) tears have long-term effects on RC muscle atrophy and fatty infiltration, with lasting damage even after surgical tendon repair. Skeletal muscle progenitor cells (SMPs) are critical for muscle repair in response to injury, but the inability of RC muscles to recover from chronic RCT tear indicates possible deficits in repair mechanisms. Here we investigated if muscle injury state was a crucial factor during human SMP expansion and differentiation ex vivo. SMPs were isolated from muscles in patients with no, partial-thickness (PT), or full-thickness (FT) RCT tears. Despite using growth factors, physiological niche stiffness, and muscle-mimetic extracellular matrix (ECM) proteins, we found that SMPs isolated from human RC muscle with RCT tears proliferated slower but fused into myosin heavy chain (MHC)-positive myotubes at higher rates than SMPs from untorn RCTs. Proteomic analysis of RC muscle tissue revealed shifts in muscle composition with pathology, as muscle from massive RCT tears had increased ECM deposition compared with no tear RC muscle. Together these data imply that the remodeled niche in a torn RCT primes SMPs not for expansion but for differentiation, thus limiting longer-term self-renewal necessary for regeneration after surgical repair. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:1816-1823, 2017.

Assembly of a nucleus-like structure during viral replication in bacteria

We observed the assembly of a nucleus-like structure in bacteria during viral infection. Using fluorescence microscopy and cryo-electron tomography, we showed that Pseudomonas chlororaphis phage 201φ2-1 assembled a compartment that separated viral DNA from the cytoplasm. The phage compartment was centered by a bipolar tubulin-based spindle, and it segregated phage and bacterial proteins according to function. Proteins involved in DNA replication and transcription localized inside the compartment, whereas proteins involved in translation and nucleotide synthesis localized outside. Later during infection, viral capsids assembled on the cytoplasmic membrane and moved to the surface of the compartment for DNA packaging. Ultimately, viral particles were released from the compartment and the cell lysed. These results demonstrate that phages have evolved a specialized structure to compartmentalize viral replication.

The diverse and expanding role of mass spectrometry in structural and molecular biology

The emergence of proteomics has led to major technological advances in mass spectrometry (MS). These advancements not only benefitted MS-based high-throughput proteomics but also increased the impact of mass spectrometry on the field of structural and molecular biology. Here, we review how state-of-the-art MS methods, including native MS, top-down protein sequencing, cross-linking-MS, and hydrogen-deuterium exchange-MS, nowadays enable the characterization of biomolecular structures, functions, and interactions. In particular, we focus on the role of mass spectrometry in integrated structural and molecular biology investigations of biological macromolecular complexes and cellular machineries, highlighting work on CRISPR-Cas systems and eukaryotic transcription complexes.

Determination of Flow Rates in Capillary Liquid Chromatography Coupled to a Nanoelectrospray Source using Droplet Image Analysis Software

Liquid chromatography coupled to electrospray tandem mass spectrometry (LC-ESI-MS/MS) is widely used in proteomic and metabolomic workflows. Considerable analytical improvements have been observed when the components of LC systems are scaled down. Currently, nano-ESI is typically done at capillary LC flow rates ranging from 200 to 300 nL/min. At these flow rates, trouble shooting and leak detection of LC systems has become increasingly challenging. In this paper we present a novel proof-of-concept approach to measure flow rates at the tip of electrospray emitters when the ionization voltage is turned off. This was achieved by estimating the changes in the droplet volume over time using digital image analysis. The results are comparable with the traditional methods of measuring flow rates, with the potential advantages of being fully automatable and nondisruptive.

Circulating adipocyte-derived extracellular vesicles are novel markers of metabolic stress

We recently reported that stressed adipocytes release extracellular vesicles (EVs) that act as "find-me" signals to promote macrophage migration and activation. In this study, we performed a comprehensive characterization of stressed adipocyte-derived EVs, assessing their antigenic composition, lipidomics, and RNA profiles. Perilipin A was identified as one of the adipose-specific proteins and studied as a potential novel biomarker to detect adipocyte-derived EVs in circulation. Circulating EVs were significantly increased in mice with diet-induced obesity (DIO) and in obese humans with metabolic syndrome compared to lean controls. This increase was associated with decreased glucose tolerance in the DIO mice and metabolic dysfunction, elevated insulin, and homeostatic model assessment of insulin resistance (HOMA-IR) in the obese humans. EVs from both DIO mice and obese humans were enriched in perilipin A, a central gatekeeper of the adipocyte lipid storehouse and a marker of adipocyte differentiation. In obese humans, circulating levels of EVs enriched in perilipin A were dynamic, decreasing 35 % (p < 0.05) after a 3-month reduced calorie diet intervention. This translational study provides an extensive characterization of adipocyte-derived EVs. The findings identify perilipin A as a novel biomarker of circulating EVs of adipocyte origin and support the development of circulating perilipin A-positive EVs as indicators of adipose tissue health.

KEY MESSAGE

• Extensive characterization of 3T3L1 EVs identified perilipin A in their composition. • Circulating EVs are elevated in obese mice and associated with glucose intolerance. • Circulating EVs are elevated in obese human and correlated with metabolic factors. • Perilipin A and EV levels are increased in the circulation of obese mice and human. • Circulating EV and perilipin A levels decrease with low calorie intervention.

Shotgun Proteomics of Tomato Fruits: Evaluation, Optimization and Validation of Sample Preparation Methods and Mass Spectrometric Parameters

An optimized protocol was developed for shotgun proteomics of tomato fruit, which is a recalcitrant tissue due to a high percentage of sugars and secondary metabolites. A number of protein extraction and fractionation techniques were examined for optimal protein extraction from tomato fruits followed by peptide separation on nanoLCMS. Of all evaluated extraction agents, buffer saturated phenol was the most efficient. In-gel digestion [SDS-PAGE followed by separation on LCMS (GeLCMS)] of phenol-extracted sample yielded a maximal number of proteins. For in-solution digested samples, fractionation by strong anion exchange chromatography (SAX) also gave similar high proteome coverage. For shotgun proteomic profiling, optimization of mass spectrometry parameters such as automatic gain control targets (5E+05 for MS, 1E+04 for MS/MS); ion injection times (500 ms for MS, 100 ms for MS/MS); resolution of 30,000; signal threshold of 500; top N-value of 20 and fragmentation by collision-induced dissociation yielded the highest number of proteins. Validation of the above protocol in two tomato cultivars demonstrated its reproducibility, consistency, and robustness with a CV of < 10%. The protocol facilitated the detection of five-fold higher number of proteins compared to published reports in tomato fruits. The protocol outlined would be useful for high-throughput proteome analysis from tomato fruits and can be applied to other recalcitrant tissues.

A novel protein isoform of the RON tyrosine kinase receptor transforms human pancreatic duct epithelial cells

The MST1R gene is overexpressed in pancreatic cancer producing elevated levels of the RON tyrosine kinase receptor protein. While mutations in MST1R are rare, alternative splice variants have been previously reported in epithelial cancers. We report the discovery of a novel RON isoform discovered in human pancreatic cancer. Partial splicing of exons 5 and 6 (P5P6) produces a RON isoform that lacks the first extracellular immunoglobulin-plexin-transcription domain. The splice variant is detected in 73% of xenografts derived from pancreatic adenocarcinoma patients and 71% of pancreatic cancer cell lines. Peptides specific to RON P5P6 detected in human pancreatic cancer specimens by mass spectrometry confirm translation of the protein isoform. The P5P6 isoform is found to be constitutively phosphorylated, present in the cytoplasm, and it traffics to the plasma membrane. Expression of P5P6 in immortalized human pancreatic duct epithelial (HPDE) cells activates downstream AKT, and in human pancreatic epithelial nestin-expressing cells, activates both the AKT and MAPK pathways. Inhibiting RON P5P6 in HPDE cells using a small molecule inhibitor BMS-777607 blocked constitutive activation and decreased AKT signaling. P5P6 transforms NIH3T3 cells and induces tumorigenicity in HPDE cells. Resultant HPDE-P5P6 tumors develop a dense stromal compartment similar to that seen in pancreatic cancer. In summary, we have identified a novel and constitutively active isoform of the RON tyrosine kinase receptor that has transforming activity and is expressed in human pancreatic cancer. These findings provide additional insight into the biology of the RON receptor in pancreatic cancer and are clinically relevant to the study of RON as a potential therapeutic target.