pyQms enables universal and accurate quantification of mass spectrometry data

Synergistic Effects of PARP Inhibition and Cholesterol Biosynthesis Pathway Modulation

An in-depth multiomic molecular characterization of PARP inhibitors revealed a distinct poly-pharmacology of niraparib (Zejula) mediated by its interaction with lanosterol synthase (LSS), which is not observed with other PARP inhibitors. Niraparib, in a similar way to the LSS inhibitor Ro-48-8071, induced activation of the 24,25-epoxysterol shunt pathway, which is a regulatory signaling branch of the cholesterol biosynthesis pathway. Interestingly, the combination of an LSS inhibitor with a PARP inhibitor that does not bind to LSS, such as olaparib, had an additive effect on killing cancer cells to levels comparable with niraparib as a single agent. In addition, the combination of PARP inhibitors and statins, inhibitors of 3-hydroxy-3-methylglutaryl-coenzyme A reductase, an enzyme catalyzing the rate-limiting step in the mevalonate pathway, had a synergistic effect on tumor cell killing in cell lines and patient-derived ovarian tumor organoids. These observations suggest that concomitant inhibition of the cholesterol biosynthesis pathway and PARP activity might result in stronger efficacy of these inhibitors against tumor types highly dependent on cholesterol metabolism.

SIGNIFICANCE

The presented data indicate, to our knowledge, for the first time, the potential benefit of concomitant modulation of cholesterol biosynthesis pathway and PARP inhibition and highlight the need for further investigation to assess its translational relevance.

Large-Scale Screening of Pharmaceutical Compounds to Explore the Application Space of On-Tissue MALDI and MALDI-2 Mass Spectrometry

The successful application of matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) in pharmaceutical research is strongly dependent on the detection of the drug of interest at physiologically relevant concentrations. Here we explored how insufficient sensitivity due to low ionization efficiency and/or the interaction of the drug molecule with the local biochemical environment of the tissue can be mitigated for many compound classes using the recently introduced MALDI-MSI coupled with laser-induced postionization, known as MALDI-2-MSI. Leveraging a MALDI-MSI screen of about 1,200 medicines/drug-like compounds from a broad range of medicinal application areas, we demonstrate a significant improvement in drug detection and the degree of sensitivity uplift by using MALDI-2 versus traditional MALDI. Our evaluation was made under simulated imaging conditions using liver homogenate sections as substrate, onto which the compounds were spotted to mimic biological conditions to the first order. To enable an evaluable detection by both MALDI and MALDI-2 for the majority of employed compounds, we spotted 1 μL of a 10 mM solution using a spotting robot and performed our experiments with a Bruker timsTOF fleX MALDI-2 instrument in both positive and negative ion modes. Specifically, we demonstrate using a large cohort of drug-like compounds that ∼60% of the tested compounds showed a more than 10-fold increase in signal intensity and ∼16% showed a more than 100-fold increase upon use of MALDI-2 postionization. Such increases in sensitivity could help advance pharmaceutical MALDI-MSI applications toward the single-cell level.

A highly conserved tRNA modification contributes to C. albicans filamentation and virulence

tRNA modifications play important roles in maintaining translation accuracy in all domains of life. Disruptions in the tRNA modification machinery, especially of the anticodon stem loop, can be lethal for many bacteria and lead to a broad range of phenotypes in baker's yeast. Very little is known about the function of tRNA modifications in host-pathogen interactions, where rapidly changing environments and stresses require fast adaptations. We found that two closely related fungal pathogens of humans, the highly pathogenic Candida albicans and its much less pathogenic sister species, Candida dubliniensis, differ in the function of a tRNA-modifying enzyme. This enzyme, Hma1, exhibits species-specific effects on the ability of the two fungi to grow in the hypha morphology, which is central to their virulence potential. We show that Hma1 has tRNA-threonylcarbamoyladenosine dehydratase activity, and its deletion alters ribosome occupancy, especially at 37°C-the body temperature of the human host. A C. albicans HMA1 deletion mutant also shows defects in adhesion to and invasion into human epithelial cells and shows reduced virulence in a fungal infection model. This links tRNA modifications to host-induced filamentation and virulence of one of the most important fungal pathogens of humans.IMPORTANCEFungal infections are on the rise worldwide, and their global burden on human life and health is frequently underestimated. Among them, the human commensal and opportunistic pathogen, Candida albicans, is one of the major causative agents of severe infections. Its virulence is closely linked to its ability to change morphologies from yeasts to hyphae. Here, this ability is linked-to our knowledge for the first time-to modifications of tRNA and translational efficiency. One tRNA-modifying enzyme, Hma1, plays a specific role in C. albicans and its ability to invade the host. This adds a so-far unknown layer of regulation to the fungal virulence program and offers new potential therapeutic targets to fight fungal infections.

In utero pulse injection of isotopic amino acids quantifies protein turnover rates during murine fetal development

Protein translational control is critical for ensuring that the fetus develops correctly and that necessary organs and tissues are formed and functional. We developed an in utero method to quantify tissue-specific protein dynamics by monitoring amino acid incorporation into the proteome after pulse injection. Fetuses of pregnant mice were injected with isotopically labeled lysine and arginine via the vitelline vein at various embyonic days, and organs and tissues were harvested. By analyzing the nascent proteome, unique signatures of each tissue were identified by hierarchical clustering. In addition, the quantified proteome-wide turnover rates were calculated between 3.81E-5 and 0.424 h-1. We observed similar protein turnover profiles for analyzed organs (e.g., liver vs. brain); however, their distributions of turnover rates vary significantly. The translational kinetic profiles of developing organs displayed differentially expressed protein pathways and synthesis rates, which correlated with known physiological changes during mouse development.

AdductHunter: identifying protein-metal complex adducts in mass spectra

Mass spectrometry (MS) is an analytical technique for molecule identification that can be used for investigating protein-metal complex interactions. Once the MS data is collected, the mass spectra are usually interpreted manually to identify the adducts formed as a result of the interactions between proteins and metal-based species. However, with increasing resolution, dataset size, and species complexity, the time required to identify adducts and the error-prone nature of manual assignment have become limiting factors in MS analysis. AdductHunter is a open-source web-based analysis tool that  automates the peak identification process using constraint integer optimization to find feasible combinations of protein and fragments, and dynamic time warping to calculate the dissimilarity between the theoretical isotope pattern of a species and its experimental isotope peak distribution. Empirical evaluation on a collection of 22 unique MS datasetsshows fast and accurate identification of protein-metal complex adducts in deconvoluted mass spectra.

In utero pulse injection of isotopic amino acids quantifies protein turnover rates during murine fetal development

Protein translational control is highly regulated step in the gene expression program during mammalian development that is critical for ensuring that the fetus develops correctly and that all of the necessary organs and tissues are formed and functional. Defects in protein expression during fetal development can lead to severe developmental abnormalities or premature death. Currently, quantitative techniques to monitor protein synthesis rates in a developing fetus (in utero) are limited. Here, we developed a novel in utero stable isotope labeling approach to quantify tissue-specific protein dynamics of the nascent proteome during mouse fetal development. Fetuses of pregnant C57BL/6J mice were injected with isotopically labeled lysine (Lys8) and arginine (Arg10) via the vitelline vein at various gestational days. After treatment, fetal organs/tissues including brain, liver, lung, and heart were harvested for sample preparation and proteomic analysis. We show that the mean incorporation rate for injected amino acids into all organs was 17.50 ± 0.6%. By analyzing the nascent proteome, unique signatures of each tissue were identified by hierarchical clustering. In addition, the quantified proteome-wide turnover rates (kobs) were calculated between 3.81E-5 and 0.424 hour-1. We observed similar protein turnover profiles for analyzed organs (e.g., liver versus brain), however, their distributions of turnover rates vary significantly. The translational kinetic profiles of developing organs displayed differentially expressed protein pathways and synthesis rates which correlated with known physiological changes during mouse development.

SMITER-A Python Library for the Simulation of LC-MS/MS Experiments

SMITER (Synthetic mzML writer) is a Python-based command-line tool designed to simulate liquid-chromatography-coupled tandem mass spectrometry LC-MS/MS runs. It enables the simulation of any biomolecule amenable to mass spectrometry (MS) since all calculations are based on chemical formulas. SMITER features a modular design, allowing for an easy implementation of different noise and fragmentation models. By default, SMITER uses an established noise model and offers several methods for peptide fragmentation, and two models for nucleoside fragmentation and one for lipid fragmentation. Due to the rich Python ecosystem, other modules, e.g., for retention time (RT) prediction, can easily be implemented for the tailored simulation of any molecule of choice. This facilitates the generation of defined gold-standard LC-MS/MS datasets for any type of experiment. Such gold standards, where the ground truth is known, are required in computational mass spectrometry to test new algorithms and to improve parameters of existing ones. Similarly, gold-standard datasets can be used to evaluate analytical challenges, e.g., by predicting co-elution and co-fragmentation of molecules. As these challenges hinder the detection or quantification of co-eluents, a comprehensive simulation can identify and thus, prevent such difficulties before performing actual MS experiments. SMITER allows the creation of such datasets easily, fast, and efficiently.

SugarPy facilitates the universal, discovery-driven analysis of intact glycopeptides

MOTIVATION

Protein glycosylation is a complex post-translational modification with crucial cellular functions in all domains of life. Currently, large-scale glycoproteomics approaches rely on glycan database dependent algorithms and are thus unsuitable for discovery-driven analyses of glycoproteomes.

RESULTS

Therefore, we devised SugarPy, a glycan database independent Python module, and validated it on the glycoproteome of human breast milk. We further demonstrated its applicability by analyzing glycoproteomes with uncommon glycans stemming from the green alga Chlamydomonas reinhardtii and the archaeon Haloferax volcanii. SugarPy also facilitated the novel characterization of glycoproteins from the red alga Cyanidioschyzon merolae.

AVAILABILITY

The source code is freely available on GitHub (https://github.com/SugarPy/SugarPy), and its implementation in Python ensures support for all operating systems.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Modulation of Escherichia coli Translation by the Specific Inactivation of tRNAGly Under Oxidative Stress

Bacterial oxidative stress responses are generally controlled by transcription factors that modulate the synthesis of RNAs with the aid of some sRNAs that control the stability, and in some cases the translation, of specific mRNAs. Here, we report that oxidative stress additionally leads to inactivation of tRNA^Gly in Escherichia coli, inducing a series of physiological changes. The observed inactivation of tRNA^Gly correlated with altered efficiency of translation of Gly codons, suggesting a possible mechanism of translational control of gene expression under oxidative stress. Changes in translation also depended on the availability of glycine, revealing a mechanism whereby bacteria modulate the response to oxidative stress according to the prevailing metabolic state of the cells.

ChimeraUGEM: unsupervised gene expression modeling in any given organism

MOTIVATION

Regulation of the amount of protein that is synthesized from genes has proved to be a serious challenge in terms of analysis and prediction, and in terms of engineering and optimization, due to the large diversity in expression machinery across species.

RESULTS

To address this challenge, we developed a methodology and a software tool (ChimeraUGEM) for predicting gene expression as well as adapting the coding sequence of a target gene to any host organism. We demonstrate these methods by predicting protein levels in seven organisms, in seven human tissues, and by increasing in vivo the expression of a synthetic gene up to 26-fold in the single-cell green alga Chlamydomonas reinhardtii. The underlying model is designed to capture sequence patterns and regulatory signals with minimal prior knowledge on the host organism and can be applied to a multitude of species and applications.

AVAILABILITY AND IMPLEMENTATION

Source code (MATLAB, C) and binaries are freely available for download for non-commercial use at http://www.cs.tau.ac.il/~tamirtul/ChimeraUGEM/, and supported on macOS, Linux and Windows.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Novel Insights Into N-Glycan Fucosylation and Core Xylosylation in C. reinhardtii

Chlamydomonas reinhardtii (C. reinhardtii) N-glycans carry plant typical β1,2-core xylose, α1,3-fucose residues, as well as plant atypical terminal β1,4-xylose and methylated mannoses. In a recent study, XylT1A was shown to act as core xylosyltransferase, whereby its action was of importance for an inhibition of excessive Man1A dependent trimming. N-Glycans found in a XylT1A/Man1A double mutant carried core xylose residues, suggesting the existence of a second core xylosyltransferase in C. reinhardtii. To further elucidate enzymes important for N-glycosylation, novel single knockdown mutants of candidate genes involved in the N-glycosylation pathway were characterized. In addition, double, triple, and quadruple mutants affecting already known N-glycosylation pathway genes were generated. By characterizing N-glycan compositions of intact N-glycopeptides from these mutant strains by mass spectrometry, a candidate gene encoding for a second putative core xylosyltransferase (XylT1B) was identified. Additionally, the role of a putative fucosyltransferase was revealed. Mutant strains with knockdown of both xylosyltransferases and the fucosyltransferase resulted in the formation of N-glycans with strongly diminished core modifications. Thus, the mutant strains generated will pave the way for further investigations on how single N-glycan core epitopes modulate protein function in C. reinhardtii.

PythoMS: A Python Framework To Simplify and Assist in the Processing and Interpretation of Mass Spectrometric Data

Mass spectrometric data are copious and generate a processing burden that is best dealt with programmatically. PythoMS is a collection of tools based on the Python programming language that assist researchers in creating figures and video output that is informative, clear, and visually compelling. The PythoMS framework introduces a library of classes and a variety of scripts that quickly perform time-consuming tasks: making proprietary output readable; binning intensity vs time data to simulate longer scan times (and hence reduce noise); calculating theoretical isotope patterns and overlaying them in histogram form on experimental data (an approach that works even for overlapping signals); rendering videos that enable zooming into the baseline of intensity vs time plots (useful to make sense of data collected over a large dynamic range) or that depict the evolution of different species in a time-lapse format; calculating aggregates; and providing a quick first-pass at identifying fragments in MS/MS spectra. PythoMS is a living project that will continue to evolve as additional scripts are developed and deployed.

High Performance Quantification of Complex High Resolution Polymer Mass Spectra

Modern soft ionization mass spectrometry provides chemical information on various polymers with unparalleled resolution and sensitivity. However, the interpretation of the resulting highly complex mass spectra is hampered by the sheer amount of contributing macromolecular species. For example, state-of-the-art reversible deactivation radical polymerization techniques, which are generally considered to be highly controlled, can still generate tens or even hundreds of species in a narrow mass window. Moreover, the multitude of species typically leads to partially overlapping isotopic patterns, further complicating the data evaluation. Herein, a rapid and powerful three-step methodical approach is introduced that enables the successful identification and quantification of the contributing species. The approach is subsequently implemented in "pyMacroMS", a high performance algorithm that allows for ultrafast processing of high resolution polymer mass spectra with varying complexities. The power of our algorithm is demonstrated on the example of a photochemical atom transfer radical polymerization (photoATRP) of three monomers, ultimately leading to 908 identified species. pyMacroMS is available free of charge under a GNU General Public License v3.0.

Nano LC-MS using capillary columns enables accurate quantification of modified ribonucleosides at low femtomol levels

Post-transcriptional chemical modifications of (t)RNA molecules are crucial in fundamental biological processes, such as translation. Despite their biological importance and accumulating evidence linking them to various human diseases, technical challenges have limited their detection and accurate quantification. Here, we present a sensitive capillary nanoflow liquid chromatography mass spectrometry (nLC-MS) pipeline for quantitative high-resolution analysis of ribonucleoside modifications from complex biological samples. We evaluated two porous graphitic carbon (PGC) materials and one end-capped C18 reference material as stationary phases for reversed-phase separation. We found that these matrices have complementing retention and separation characteristics, including the capability to separate structural isomers. PGC and C18 matrices yielded excellent signal-to-noise ratios in nLC-MS while differing in the separation capability and sensitivity for various nucleosides. This emphasizes the need for tailored LC-MS setups for optimally detecting as many nucleoside modifications as possible. Detection ranges spanning up to six orders of magnitude enable the analysis of individual ribonucleosides down to femtomol concentrations. Furthermore, normalizing the obtained signal intensities to a stable isotope labeled spike-in enabled direct comparison of ribonucleoside levels between different samples. In conclusion, capillary columns coupled to nLC-MS constitute a powerful and sensitive tool for quantitative analysis of modified ribonucleosides in complex biological samples. This setup will be invaluable for further unraveling the intriguing and multifaceted biological roles of RNA modifications.

Structure of a PSI-LHCI-cyt b6f supercomplex in Chlamydomonas reinhardtii promoting cyclic electron flow under anaerobic conditions

Photosynthetic linear electron flow (LEF) produces ATP and NADPH, while cyclic electron flow (CEF) exclusively drives photophosphorylation to supply extra ATP. The fine-tuning of linear and cyclic electron transport levels allows photosynthetic organisms to balance light energy absorption with cellular energy requirements under constantly changing light conditions. As LEF and CEF share many electron transfer components, a key question is how the same individual structural units contribute to these two different functional modes. Here, we report the structural identification of a photosystem I (PSI)-light harvesting complex I (LHCI)-cytochrome (cyt) b₆f supercomplex isolated from the unicellular alga Chlamydomonas reinhardtii under anaerobic conditions, which induces CEF. This provides strong evidence for the model that enhanced CEF is induced by the formation of CEF supercomplexes, when stromal electron carriers are reduced, to generate additional ATP. The additional identification of PSI-LHCI-LHCII complexes is consistent with recent findings that both CEF enhancement and state transitions are triggered by similar conditions, but can occur independently from each other. Single molecule fluorescence correlation spectroscopy indicates a physical association between cyt b₆f and fluorescent chlorophyll containing PSI-LHCI supercomplexes. Single particle analysis identified top-view projections of the corresponding PSI-LHCI-cyt b₆f supercomplex. Based on molecular modeling and mass spectrometry analyses, we propose a model in which dissociation of LHCA2 and LHCA9 from PSI supports the formation of this CEF supercomplex. This is supported by the finding that a Δlhca2 knockout mutant has constitutively enhanced CEF.

N-Glycoproteomic Characterization of Mannosidase and Xylosyltransferase Mutant Strains of Chlamydomonasreinhardtii

At present, only little is known about the enzymatic machinery required for N-glycosylation in Chlamydomonas reinhardtii, leading to the formation of N-glycans harboring Xyl and methylated Man. This machinery possesses new enzymatic features, as C. reinhardtii N-glycans are independent of β1,2-N-acetylglucosaminyltransferase I. Here we have performed comparative N-glycoproteomic analyses of insertional mutants of mannosidase 1A (IM Man1A ) and xylosyltransferase 1A (IM XylT1A ). The disruption of man1A affected methylation of Man and the addition of terminal Xyl. The absence of XylT1A led to shorter N-glycans compared to the wild type. The use of a IM Man1A xIM XylT1A double mutant revealed that the absence of Man1A suppressed the IM XylT1A phenotype, indicating that the increased N-glycan trimming is regulated by core β1,2-Xyl and is dependent on Man1A activity. These data point toward an enzymatic cascade in the N-glycosylation pathway of C. reinhardtii with interlinked roles of Man1A and XylT1A. The results described herein represent the first step toward a functional characterization of the enzymatic N-glycosylation machinery in C. reinhardtii.

Establishment of Dimethyl Labeling-based Quantitative Acetylproteomics in Arabidopsis

Protein acetylation, one of many types of post-translational modifications (PTMs), is involved in a variety of biological and cellular processes. In the present study, we applied both CsCl density gradient (CDG) centrifugation-based protein fractionation and a dimethyl-labeling-based 4C quantitative PTM proteomics workflow in the study of dynamic acetylproteomic changes in Arabidopsis. This workflow integrates the dimethyl chemical labeling with chromatography-based acetylpeptide separation and enrichment followed by mass spectrometry (MS) analysis, the extracted ion chromatogram (XIC) quantitation-based computational analysis of mass spectrometry data to measure dynamic changes of acetylpeptide level using an in-house software program, named Stable isotope-based Quantitation-Dimethyl labeling (SQUA-D), and finally the confirmation of ethylene hormone-regulated acetylation using immunoblot analysis. Eventually, using this proteomic approach, 7456 unambiguous acetylation sites were found from 2638 different acetylproteins, and 5250 acetylation sites, including 5233 sites on lysine side chain and 17 sites on protein N termini, were identified repetitively. Out of these repetitively discovered acetylation sites, 4228 sites on lysine side chain (i.e. 80.5%) are novel. These acetylproteins are exemplified by the histone superfamily, ribosomal and heat shock proteins, and proteins related to stress/stimulus responses and energy metabolism. The novel acetylproteins enriched by the CDG centrifugation fractionation contain many cellular trafficking proteins, membrane-bound receptors, and receptor-like kinases, which are mostly involved in brassinosteroid, light, gravity, and development signaling. In addition, we identified 12 highly conserved acetylation site motifs within histones, P-glycoproteins, actin depolymerizing factors, ATPases, transcription factors, and receptor-like kinases. Using SQUA-D software, we have quantified 33 ethylene hormone-enhanced and 31 hormone-suppressed acetylpeptide groups or called unique PTM peptide arrays (UPAs) that share the identical unique PTM site pattern (UPSP). This CDG centrifugation protein fractionation in combination with dimethyl labeling-based quantitative PTM proteomics, and SQUA-D may be applied in the quantitation of any PTM proteins in any model eukaryotes and agricultural crops as well as tissue samples of animals and human beings.