Proteome-scale recombinant standards and a robust high-speed search engine to advance cross-linking MS-based interactomics.

Advancing data analysis tools for proteome-wide cross-linking mass spectrometry (XL-MS) requires ground-truth standards that mimic biological complexity. Here we develop well-controlled XL-MS standards comprising hundreds of recombinant proteins that are systematically mixed for cross-linking. We use one standard dataset to guide the development of Scout, a search engine for XL-MS with MS-cleavable cross-linkers. Using other, independent standard datasets and published datasets, we benchmark the performance of Scout and existing XL-MS software. We find that Scout offers an excellent combination of speed, sensitivity and false discovery rate control. The results illustrate how our large recombinant standard can support the development of XL-MS analysis tools and evaluation of XL-MS results.

RawVegetable 2.0: Refining XL-MS Data Acquisition through Enhanced Quality Control.

We present RawVegetable 2.0, a software tailored for assessing mass spectrometry data quality and fine-tuned for cross-linking mass spectrometry (XL-MS) applications. Building upon the capabilities of its predecessor, RawVegetable 2.0 introduces four main modules, each providing distinct and new functionalities: 1) Pair Finder, which identifies ion doublets characteristic of cleavable cross-linking experiments; 2) Diagnostic Peak Finder, which locates potential reporter ions associated with a specific cross-linker; 3) Precursor Signal Ratio, which computes the ratio between precursor intensity and the total signal in an MS/MS scan; and 4) Xrea, which evaluates spectral quality by analyzing the heterogeneity of peak intensities within a spectrum. These modules collectively streamline the process of optimizing mass spectrometry data acquisition for both Proteomics and XL-MS experiments. RawVegetable 2.0, along with a comprehensive tutorial is freely accessible for academic use at: http://patternlabforproteomics.org/rawvegetable2.

The first multi-tissue genome-scale metabolic model of a woody plant highlights suberin biosynthesis pathways in Quercus suber.

Over the last decade, genome-scale metabolic models have been increasingly used to study plant metabolic behaviour at the tissue and multi-tissue level under different environmental conditions. Quercus suber, also known as the cork oak tree, is one of the most important forest communities of the Mediterranean/Iberian region. In this work, we present the genome-scale metabolic model of the Q. suber (iEC7871). The metabolic model comprises 7871 genes, 6231 reactions, and 6481 metabolites across eight compartments. Transcriptomics data was integrated into the model to obtain tissue-specific models for the leaf, inner bark, and phellogen, with specific biomass compositions. The tissue-specific models were merged into a diel multi-tissue metabolic model to predict interactions among the three tissues at the light and dark phases. The metabolic models were also used to analyse the pathways associated with the synthesis of suberin monomers, namely the acyl-lipids, phenylpropanoids, isoprenoids, and flavonoids production. The models developed in this work provide a systematic overview of the metabolism of Q. suber, including its secondary metabolism pathways and cork formation.

merlin, an improved framework for the reconstruction of high-quality genome-scale metabolic models.

Genome-scale metabolic models have been recognised as useful tools for better understanding living organisms' metabolism. merlin (https://www.merlin-sysbio.org/) is an open-source and user-friendly resource that hastens the models' reconstruction process, conjugating manual and automatic procedures, while leveraging the user's expertise with a curation-oriented graphical interface. An updated and redesigned version of merlin is herein presented. Since 2015, several features have been implemented in merlin, along with deep changes in the software architecture, operational flow, and graphical interface. The current version (4.0) includes the implementation of novel algorithms and third-party tools for genome functional annotation, draft assembly, model refinement, and curation. Such updates increased the user base, resulting in multiple published works, including genome metabolic (re-)annotations and model reconstructions of multiple (lower and higher) eukaryotes and prokaryotes. merlin version 4.0 is the only tool able to perform template based and de novo draft reconstructions, while achieving competitive performance compared to state-of-the art tools both for well and less-studied organisms.

Real-Time Library Search Increases Cross-Link Identification Depth across All Levels of Sample Complexity.

Cross-linking mass spectrometry (XL-MS) is a universal tool for probing structural dynamics and protein-protein interactions in vitro and in vivo. Although cross-linked peptides are naturally less abundant than their unlinked counterparts, recent experimental advances improved cross-link identification by enriching the cross-linker-modified peptides chemically with the use of enrichable cross-linkers. However, mono-links (i.e., peptides modified with a hydrolyzed cross-linker) still hinder efficient cross-link identification since a large proportion of measurement time is spent on their MS2 acquisition. Currently, cross-links and mono-links cannot be separated by sample preparation techniques or chromatography because they are chemically almost identical. Here, we found that based on the intensity ratios of four diagnostic peaks when using PhoX/tBu-PhoX cross-linkers, cross-links and mono-links can be partially distinguished. Harnessing their characteristic intensity ratios for real-time library search (RTLS)-based triggering of high-resolution MS2 scans increased the number of cross-link identifications from both single protein samples and intact E. coli cells. Specifically, RTLS improves cross-link identification from unenriched samples and short gradients, emphasizing its advantages in high-throughput approaches and when instrument time or sample amount is limited.

TDFragMapper: a visualization tool for evaluating experimental parameters in top-down proteomics.

MOTIVATION: We present a new software-tool allowing an easy visualization of fragment ions and thus a rapid evaluation of key experimental parameters on the sequence coverage obtained for the MS/MS (tandem mass spectrometry) analysis of intact proteins. Our tool can process data obtained from various deconvolution and fragment assignment software. RESULTS: We demonstrate that TDFragMapper can rapidly highlight the experimental fragmentation parameters that are critical to the characterization of intact proteins of various size using top-down proteomics. AVAILABILITY AND IMPLEMENTATION: TDFragMapper, a demonstration video and user tutorial are freely available for academic use at https://msbio.pasteur.fr/tdfragmapper; all data are thus available from the ProteomeXchange consortium (identifier PXD024643). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Increasing confidence in proteomic spectral deconvolution through mass defect.

MOTIVATION: Confident deconvolution of proteomic spectra is critical for several applications such as de novo sequencing, cross-linking mass spectrometry and handling chimeric mass spectra. RESULTS: In general, all deconvolution algorithms may eventually report mass peaks that are not compatible with the chemical formula of any peptide. We show how to remove these artifacts by considering their mass defects. We introduce Y.A.D.A. 3.0, a fast deconvolution algorithm that can remove peaks with unacceptable mass defects. Our approach is effective for polypeptides with less than 10 kDa, and its essence can be easily incorporated into any deconvolution algorithm. AVAILABILITY AND IMPLEMENTATION: Y.A.D.A. 3.0 is freely available for academic use at http://patternlabforproteomics.org/yada3. SUPPLEMENTARY INFORMATION: Supplementary information is available at Bioinformatics online.

Remembering to whom we transmit information during pandemics: the effect of face masks on destination memory.

Considering the global pandemic we currently experience, face masks have become standard in our daily routine. Even though surgical masks are established as a safety measure against the dissemination of COVID-19, previous research showed that their wearing compromises face recognition. Consequently, the capacity to remember to whom we transmit information-destination memory-could also be compromised. In our study, through a between-participants design (experiment 1) and a within-participants design (experiment 2), undergraduate students have to transmit Portuguese proverbs to masked and unmasked celebrity faces. Following our hypothesis, participants who shared information with masked faces had worse destination memory performance than those who shared information with unmasked faces. Also, we observed lower recognition for masked faces compared to unmasked faces. These results were expected since using a surgical mask affects facial recognition, thus making it harder to recognize a person to whom information was previously transmitted. More importantly, these results also support the idea that variables associated with the recipient's face are important for destination memory performance.

"Choose it, and remember it": The impact of choice on destination memory.

Destination memory can be defined as the capacity to remember to whom we transmit information. It is measured through the accuracy of retrieving the association between the information we transmit and the person to whom we transmit it. A destination memory procedure aims to emulate human interaction by sharing facts with celebrities (i.e., familiar faces) since we often communicate with people we know. However, the role of the choice about who we intend to transmit the information to has not been evaluated before. This paper investigated whether deciding with whom to share a piece of information benefits destination memory. We designed two experiments with different levels of cognitive load, increasing it from Experiment 1 to Experiment 2. The experiments included two conditions: the choice condition, in which participants chose from two options to whom they desired to share a fact, and the no-choice condition, in which participants simply shared facts with celebrities without the possibility of a choice. Experiment 1 suggested that a choice component did not affect destination memory. However, when in Experiment 2 we raised the cognitive load by increasing the number of stimuli, we found that selecting the recipient during the more challenging task provided an advantage in destination memory. This result is congruent with the explanation that the shift of the participants' attentional resources to the recipient, caused by the choice component, leads to a destination memory improvement. In sum, it seems that a choice component can improve destination memory only under demanding attentional conditions.

Optimized TMT-Based Quantitative Cross-Linking Mass Spectrometry Strategy for Large-Scale Interactomic Studies.

Cross-linking mass spectrometry (XL-MS) is a powerful method for the investigation of protein-protein interactions (PPI) from highly complex samples. XL-MS combined with tandem mass tag (TMT) labeling holds the promise of large-scale PPI quantification. However, a robust and efficient TMT-based XL-MS quantification method has not yet been established due to the lack of a benchmarking dataset and thorough evaluation of various MS parameters. To tackle these limitations, we generate a two-interactome dataset by spiking in TMT-labeled cross-linked Escherichia coli lysate into TMT-labeled cross-linked HEK293T lysate using a defined mixing scheme. Using this benchmarking dataset, we assess the efficacy of cross-link identification and accuracy of cross-link quantification using different MS acquisition strategies. For identification, we compare various MS2- and MS3-based XL-MS methods, and optimize stepped higher energy collisional dissociation (HCD) energies for TMT-labeled cross-links. We observed a need for notably higher fragmentation energies compared to unlabeled cross-links. For quantification, we assess the quantification accuracy and dispersion of MS2-, MS3-, and synchronous precursor selection-MS3-based methods. We show that a stepped HCD-MS2 method with stepped collision energies 36-42-48 provides a vast number of quantifiable cross-links with high quantification accuracy. This widely applicable method paves the way for multiplexed quantitative PPI characterization from complex biological systems.

ProteoCombiner: integrating bottom-up with top-down proteomics data for improved proteoform assessment.

MOTIVATION: We present a high-performance software integrating shotgun with top-down proteomic data. The tool can deal with multiple experiments and search engines. Enable rapid and easy visualization, manual validation and comparison of the identified proteoform sequences including the post-translational modification characterization. RESULTS: We demonstrate the effectiveness of our approach on a large-scale Escherichia coli dataset; ProteoCombiner unambiguously shortlisted proteoforms among those identified by the multiple search engines. AVAILABILITY AND IMPLEMENTATION: ProteoCombiner, a demonstration video and user tutorial are freely available at https://proteocombiner.pasteur.fr, for academic use; all data are thus available from the ProteomeXchange consortium (identifier PXD017618). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Characterizing protein conformers by cross-linking mass spectrometry and pattern recognition.

MOTIVATION: Chemical cross-linking coupled to mass spectrometry (XLMS) emerged as a powerful technique for studying protein structures and large-scale protein-protein interactions. Nonetheless, XLMS lacks software tailored toward dealing with multiple conformers; this scenario can lead to high-quality identifications that are mutually exclusive. This limitation hampers the applicability of XLMS in structural experiments of dynamic protein systems, where less abundant conformers of the target protein are expected in the sample. RESULTS: We present QUIN-XL, a software that uses unsupervised clustering to group cross-link identifications by their quantitative profile across multiple samples. QUIN-XL highlights regions of the protein or system presenting changes in its conformation when comparing different biological conditions. We demonstrate our software's usefulness by revisiting the HSP90 protein, comparing three of its different conformers. QUIN-XL's clusters correlate directly to known protein 3D structures of the conformers and therefore validates our software. AVAILABILITYAND IMPLEMENTATION: QUIN-XL and a user tutorial are freely available at http://patternlabforproteomics.org/quinxl for academic users. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

XlinkCyNET: A Cytoscape Application for Visualization of Protein Interaction Networks Based on Cross-Linking Mass Spectrometry Identifications.

Software tools that allow the visualization and analysis of protein interaction networks are essential for studies in systems biology. One of the most popular network visualization tools in biology is Cytoscape, which offers a great selection of plug-ins for the interpretation of network data. Chemical cross-linking coupled to mass spectrometry (XL-MS) is an increasingly important source for protein interaction data; however, to date, no Cytoscape tools are available to analyze XL-MS results. In light of the suitability of the Cytoscape platform and to expand its toolbox, here we introduce XlinkCyNET, an open-source Cytoscape Java plug-in for exploring large-scale XL-MS-based protein interaction networks. XlinkCyNET offers the rapid and easy visualization of intra- and interprotein cross-links in a rectangular-bar style as well as on the 3D structure, allowing the interrogation of protein interaction networks at the residue level. XlinkCyNET is freely available from the Cytoscape App Store (http://apps.cytoscape.org/apps/xlinkcynet) and at the Liu lab webpage (https://www.theliulab.com/software/xlinkcynet).

Optimization of a Top-Down Proteomics Platform for Closely Related Pathogenic Bacterial Discrimination.

The current technique used for microbial identification in hospitals is matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). However, it suffers from important limitations, in particular, for closely related species or when the database used for the identification lacks the appropriate reference. In this work, we set up a liquid chromatography (LC)-MS/MS top-down proteomics platform, which aims at discriminating closely related pathogenic bacteria through the identification of specific proteoforms. Using Escherichia coli as a model, all steps of the workflow were optimized: protein extraction, on-line LC separation, MS method, and data analysis. Using optimized parameters, about 220 proteins, corresponding to more than 500 proteoforms, could be identified in a single run. We then used this platform for the discrimination of enterobacterial pathogens undistinguishable by MALDI-TOF, although leading to very different clinical outcomes. For each pathogen, we identified specific proteoforms that could potentially be used as biomarkers. We also improved the characterization of poorly described bacterial strains. Our results highlight the advantage of addressing proteoforms rather than peptides for accurate bacterial characterization and qualify top-down proteomics as a promising tool in clinical microbiology. Data are available via ProteomeXchange with the identifier PXD019247.

Recognition and naming test of the Portuguese population for national and international celebrities.

Research on familiar faces has been conducted in different countries and resort to celebrities faces, stimuli that are highly constrained by geographic context and cultural peculiarities, since many celebrities are only famous in particular countries. Despite their relevance to psychological research, there are no normative studies of celebrities' facial recognition in Portugal. We developed a database with 160 black and white pictures of famous persons' faces in this work. The data collection took place in two different studies. In study 1, participants were asked to recognize and name celebrity faces; while in study 2, celebrity names were rated for AoA, familiarity, and distinctiveness. Data were gathered from two different samples of Portuguese young adults aged between 18 and 25 years old, and both procedures were performed online through a questionnaire created in Qualtrics software. This database provides ratings of AoA, familiarity, facial distinctiveness, recognition rate, and naming rate for each celebrity, which will allow further selection of celebrities, based on these five attributes, for studies using Portuguese samples. Also, possible relationships between these five variables were analyzed and presented, highlighting facial distinctiveness as a predictor for both naming and recognition rate of celebrity faces.

Top-Down Garbage Collector: a tool for selecting high-quality top-down proteomics mass spectra.

MOTIVATION: We present the first tool for unbiased quality control of top-down proteomics datasets. Our tool can select high-quality top-down proteomics spectra, serve as a gateway for building top-down spectral libraries and, ultimately, improve identification rates. RESULTS: We demonstrate that a twofold rate increase for two E. coli top-down proteomics datasets may be achievable. AVAILABILITY AND IMPLEMENTATION: http://patternlabforproteomics.org/tdgc, freely available for academic use. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Novel Mucoralean Fungus From a Repugnant Substrate: Mucor merdophylus sp. nov., Isolated From Dog Excrement.

The repeated observation of dog dung covered by abundant white cottony mycelium in a private garden in the city of Rio de Janeiro, state of Rio de Janeiro (Brazil) prompted an investigation to clarify the identity of the fungus involved. Three different species of mucoralean fungi (together with some ascomycete asexual morphs) were present. Two were identified as belonging to Mycotypha sp. and Thamnostylum sp., and the third belonged to Mucor sp. This publication deals with the full taxonomic elucidation of the latter. Based on morphological, physiological, and molecular data (ITS and LSU rDNA regions), it was recognized that this Mucor differed from all other species. It produces strongly sympodially circinate branched sporangiophores (some with up to four septa) with numerous swellings resembling abortive sporangia. It also has cylindrical, obovoid, pyriform, or ovoid columellae and its sporangiospores are mostly ellipsoid, although some are subglobose and others are irregular. Based on the evidence of the analyzed datasets, the new species Mucor merdophylus is hereby proposed.

Spatial location and emotion modulate voice perception.

How do we perceive voices coming from different spatial locations, and how is this affected by emotion? The current study probed the interplay between space and emotion during voice perception. Thirty participants listened to nonverbal vocalizations coming from different locations around the head (left vs. right; front vs. back), and differing in valence (neutral, positive [amusement] or negative [anger]). They were instructed to identify the location of the vocalizations (Experiment 1) and to evaluate their emotional qualities (Experiment 2). Emotion-space interactions were observed, but only in Experiment 1: emotional vocalizations were better localised than neutral ones when they were presented from the back and the right side. In Experiment 2, emotion recognition accuracy was increased for positive vs. negative and neutral vocalizations, and perceived arousal was increased for emotional vs. neutral vocalizations, but this was independent of spatial location. These findings indicate that emotional salience affects how we perceive the spatial location of voices. They additionally suggest that the interaction between spatial ("where") and emotional ("what") properties of the voice differs as a function of task.

Clinical Measures Related to Forward Shoulder Posture: A Reliability and Correlational Study.

OBJECTIVES: The purpose of this study was to examine the reliability of clinical measures related to forward shoulder posture (pectoralis minor index [PMI], scapular index [SI], abduction index [AI], acromion to the wall index [AWI] acromion to the treatment table index [ATI], and thoracic curvature [TC]), and to investigate the association (redundancy) among these measures. METHODS: Twenty-one asymptomatic participants participated in this study. Two physiotherapists were trained to perform the clinical measurements. Intraclass correlation coefficients (ICC2,k) were calculated to assess intra- and interrater reliabilities. Pearson product moment correlation was used to investigate the existence of possible redundancy between the measures that showed high intra- and interrater reliabilities. RESULTS: The measures showed ICCs between 0.30 and 0.97. Five measures, PMI, SI, AWI, ATI, and TC, showed appropriate values for intrarater reliability (ICCs 0.77-0.94), and 3 measures, AWI, ATI, and TC, for interrater reliability (ICCs 0.82-0.85). Among measures that showed acceptable intra- and interrater reliability values, 2 measures were redundant, showing high association (AWI vs ATI) (r = 0.80, P < .001). CONCLUSION: For PMI, SI, AWI, ATI, and TC measures, adequate values of intrarater reliability were observed. For AWI, ATI, and TC, adequate values of interrater reliability were found. Two pairs of measures were highly associated (PMI with SI; AWI with ATI), which indicates redundancy among them. Our results suggest that, when the same examiner performs the assessment, the combined use of the PMI, AWI, and TC measures allows a quick but comprehensive evaluation of the presence of forward shoulder posture.

XPlex: An Effective, Multiplex Cross-Linking Chemistry for Acidic Residues.

Cross-linking/Mass spectrometry (XLMS) is a consolidated technique for structural characterization of proteins and protein complexes. Despite its success, the cross-linking chemistry currently used is mostly based on N-hydroxysuccinimide (NHS) esters, which react primarily with lysine residues. One way to expand the current applicability of XLMS into several new areas is to increase the number of cross-links obtainable for a target protein. We introduce a multiplex chemistry (denoted XPlex) that targets Asp, Glu, Lys, and Ser residues. XPlex can generate significantly more cross-links with reactions occurring at lower temperatures and enables targeting proteins that are not possible with NHS ester-based cross-linkers. We demonstrate the effectiveness of our approach in model proteins as well as a target Lys-poor protein, SalBIII. Identification of XPlex spectra requires a search engine capable of simultaneously considering multiple cross-linkers on the same run; to achieve this, we updated the SIM-XL search algorithm with a search mode tailored toward XPlex. In summary, we present a complete chemistry/computational solution for significantly increasing the number of possible distance constraints by mass spectrometry experiments, and thus, we are convinced that XPlex poses as a real complementary approach for structural proteomics studies.