Yeast cell responses and survival during periodic osmotic stress are controlled by glucose availability.

Natural environments of living organisms are often dynamic and multifactorial, with multiple parameters fluctuating over time. To better understand how cells respond to dynamically interacting factors, we quantified the effects of dual fluctuations of osmotic stress and glucose deprivation on yeast cells using microfluidics and time-lapse microscopy. Strikingly, we observed that cell proliferation, survival, and signaling depend on the phasing of the two periodic stresses. Cells divided faster, survived longer, and showed decreased transcriptional response when fluctuations of hyperosmotic stress and glucose deprivation occurred in phase than when the two stresses occurred alternatively. Therefore, glucose availability regulates yeast responses to dynamic osmotic stress, showcasing the key role of metabolic fluctuations in cellular responses to dynamic stress. We also found that mutants with impaired osmotic stress response were better adapted to alternating stresses than wild-type cells, showing that genetic mechanisms of adaptation to a persistent stress factor can be detrimental under dynamically interacting conditions.

CyberSco.Py an open-source software for event-based, conditional microscopy.

Timelapse fluorescence microscopy imaging is routinely used in quantitative cell biology. However, microscopes could become much more powerful investigation systems if they were endowed with simple unsupervised decision-making algorithms to transform them into fully responsive and automated measurement devices. Here, we report CyberSco.Py, Python software for advanced automated timelapse experiments. We provide proof-of-principle of a user-friendly framework that increases the tunability and flexibility when setting up and running fluorescence timelapse microscopy experiments. Importantly, CyberSco.Py combines real-time image analysis with automation capability, which allows users to create conditional, event-based experiments in which the imaging acquisition parameters and the status of various devices can be changed automatically based on the image analysis. We exemplify the relevance of CyberSco.Py to cell biology using several use case experiments with budding yeast. We anticipate that CyberSco.Py could be used to address the growing need for smart microscopy systems to implement more informative quantitative cell biology experiments.

A Computational Protocol to Analyze PDZ/PBM Affinity Data Obtained by High-Throughput Holdup Assay.

The holdup assay is an automated high-throughput comparative chromatographic retention approach that allows to measure quantitative binding intensities (BI) for a large number of domain-motif pairs and deduce equilibrium binding affinity constants. We routinely apply this approach to obtain quantitative binding specificity profiles of particular PDZ-binding motifs (PBMs) toward the full library of known human PDZ domains (the PDZome). The quality of the electropherograms extracted from the capillary electrophoresis instrument at the final step of the holdup assay may vary, influencing the accuracy and reproducibility of the measurement. By using bioinformatic tools, we can solve these issues to extract more reliable BIs by means of a better superimposition of the electropherograms. The protocol presented in this chapter describes the main principles and strategies of our curated method to process holdup data and new ways to plot and compare the BIs for the PBM-PDZ interactions. For this particular protocol, all the necessary computing commands are freely available in open Python packages.

Phase relationships in two-dimensional mass spectrometry.

Two-dimensional mass spectrometry (2D MS) is a data-independent tandem mass spectrometry technique in which precursor and fragment ion species can be correlated without the need for prior ion isolation. The behavior of phase in 2D Fourier transform mass spectrometry is investigated with respect to the calculation of phase-corrected absorption-mode 2D mass spectra. 2D MS datasets have a phase that is defined differently in each dimension. In both dimensions, the phase behavior of precursor and fragment ions is found to be different. The dependence of the phase for both precursor and fragment ion signals on various parameters (e.g., modulation frequency, shape of the fragmentation zone) is discussed. Experimental data confirms the theoretical calculations of the phase in each dimension. Understanding the phase relationships in a 2D mass spectrum is beneficial to the development of possible algorithms for phase correction, which may improve both the signal-to-noise ratio and the resolving power of peaks in 2D mass spectra.

Application of Tandem Two-Dimensional Mass Spectrometry for Top-Down Deep Sequencing of Calmodulin.

Two-dimensional mass spectrometry (2DMS) involves simultaneous acquisition of the fragmentation patterns of all the analytes in a mixture by correlating their precursor and fragment ions by modulating precursor ions systematically through a fragmentation zone. Tandem two-dimensional mass spectrometry (MS/2DMS) unites the ultra-high accuracy of Fourier transform ion cyclotron resonance (FT-ICR) MS/MS and the simultaneous data-independent fragmentation of 2DMS to achieve extensive inter-residue fragmentation of entire proteins. 2DMS was recently developed for top-down proteomics (TDP), and applied to the analysis of calmodulin (CaM), reporting a cleavage coverage of about ~23% using infrared multiphoton dissociation (IRMPD) as fragmentation technique. The goal of this work is to expand the utility of top-down protein analysis using MS/2DMS in order to extend the cleavage coverage in top-down proteomics further into the interior regions of the protein. In this case, using MS/2DMS, the cleavage coverage of CaM increased from ~23% to ~42%. Graphical Abstract Two-dimensional mass spectrometry, when applied to primary fragment ions from the source, allows deep-sequencing of the protein calmodulin.

Top-Down Deep Sequencing of Ubiquitin Using Two-Dimensional Mass Spectrometry.

Two-dimensional mass spectrometry (2DMS) allows data independent fragmentation of all ions in a sample and correlation of fragment ions to their precursors without isolation prior to fragmentation. Developments in computer capabilities and implementations in Fourier transform ion cyclotron resonance (FTICR) MS over the past decade have allowed the technique to become a useful analytical tool for bottom-up proteomics (BUP) and, more recently, in top-down protein analysis (TDP). In this work, a new method of TDP is developed using 2D FTICR MS, called MS/2D FTICR MS or MS/2DMS. In MS/2DMS, an entire protein is initially fragmented in a hexapole collision cell, e.g., with collisionally activated dissociation (CAD). The primary fragments are then sent to the ICR cell, where 2DMS is performed with infrared multiphoton dissociation (IRMPD) or electron-capture dissociation (ECD). The resulting 2D mass spectra retain information equivalent to a set of TDP MS3 experiments on the selected protein. Up to n - 1 fragmentation steps can be added to the process, as long as an ion of interest can be unambiguously fragmented before the ICR cell, leading to an MS n/2DMS experiment whose output is a 2D mass spectrum retaining information equivalent to MS n. MS/2DMS and MS/MS/2DMS are used in this work for the structural analysis of ubiquitin (Ubi), noting several unique features which aid fragment identification. The use of CAD-MS/IRMPD-2DMS, CAD-MS/ECD-2DMS, and MS2/2DMS using, respectively, in-source dissociation (ISD), CAD, and ECD-2DMS led to 97% cleavage coverage for Ubi.

Can Two-Dimensional IR-ECD Mass Spectrometry Improve Peptide de Novo Sequencing?

Two-dimensional mass spectrometry (2D MS) correlates precursor and fragment ions without ion isolation in a Fourier transform ion cyclotron resonance mass spectrometer (FTICR MS) for tandem mass spectrometry. Infrared activated electron capture dissociation (IR-ECD), using a hollow cathode configuration, generally yields more information for peptide sequencing in tandem mass spectrometry than ECD (electron capture dissociation) alone. The effects of the fragmentation zone on the 2D mass spectrum are investigated as well as the structural information that can be derived from it. The enhanced structural information gathered from the 2D mass spectrum is discussed in terms of how de novo peptide sequencing can be performed with increased confidence. 2D IR-ECD MS is shown to sequence peptides, to distinguish between leucine and isoleucine residues through the production of w ions as well as between C-terminal ( b/ c) and N-terminal ( y/ z) fragments through the use of higher harmonics, and to assign and locate peptide modifications.

Automatic differential analysis of NMR experiments in complex samples.

Liquid state nuclear magnetic resonance (NMR) is a powerful tool for the analysis of complex mixtures of unknown molecules. This capacity has been used in many analytical approaches: metabolomics, identification of active compounds in natural extracts, and characterization of species, and such studies require the acquisition of many diverse NMR measurements on series of samples. Although acquisition can easily be performed automatically, the number of NMR experiments involved in these studies increases very rapidly, and this data avalanche requires to resort to automatic processing and analysis. We present here a program that allows the autonomous, unsupervised processing of a large corpus of 1D, 2D, and diffusion-ordered spectroscopy experiments from a series of samples acquired in different conditions. The program provides all the signal processing steps, as well as peak-picking and bucketing of 1D and 2D spectra, the program and its components are fully available. In an experiment mimicking the search of a bioactive species in a natural extract, we use it for the automatic detection of small amounts of artemisinin added to a series of plant extracts and for the generation of the spectral fingerprint of this molecule. This program called Plasmodesma is a novel tool that should be useful to decipher complex mixtures, particularly in the discovery of biologically active natural products from plants extracts but can also in drug discovery or metabolomics studies.

Bottom-Up Two-Dimensional Electron-Capture Dissociation Mass Spectrometry of Calmodulin.

Two-dimensional mass spectrometry (2D MS) is a tandem mass spectrometry technique that allows data-independent fragmentation of all precursors in a mixture without previous isolation, through modulation of the ion cyclotron frequency in the ICR-cell prior to fragmentation. Its power as an analytical technique has been proven particularly for proteomics. Recently, a comparison study between 1D and 2D MS has been performed using infrared multiphoton dissociation (IRMPD) on calmodulin (CaM), highlighting the capabilities of the technique in both top-down (TDP) and bottom-up proteomics (BUP). The goal of this work is to expand this study on CaM using electron-capture dissociation (ECD) 2D MS as a single complementary BUP experiment in order to enhance the cleavage coverage of the protein under analysis. By adding the results of the BUP 2D ECD MS to the 2D IRMPD MS analysis of CaM, the total cleavage coverage increased from ~40% to ~68%. Graphical abstract ᅟ.

Nonuniform Sampling Acquisition of Two-Dimensional Fourier Transform Ion Cyclotron Resonance Mass Spectrometry for Increased Mass Resolution of Tandem Mass Spectrometry Precursor Ions.

Obtaining the full MS/MS map for fragments and precursors of complex mixtures without hyphenation with chromatographic separation by a data-independent acquisition is a challenge in mass spectrometry which is solved by two-dimensional (2D) Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS). Until now 2D FTICR MS afforded only a moderate resolution for precursor ion since this resolution is limited by the number of evolution interval steps to which the number of scans, the acquisition time, and the sample consumption are proportional. An overnight acquisition is already required to reach a quadrupole mass filter-like unit mass resolution. Here, we report that 2D FTICR MS using nonuniform sampling (NUS) obtained by randomly skipping points in the first dimension corresponding to the precursor selection gives access, after data processing, to the same structural information contained in a complex mixture. The resolution increases roughly as the inverse of the NUS ratio, up to 26 times at NUS 1/32, leading to an acquisition time reduced in the same ratio compared to a classical acquisition at the same resolution. As an example, the analysis of a natural oil is presented.

Polymer Analysis in the Second Dimension: Preliminary Studies for the Characterization of Polymers with 2D MS.

Two-dimensional Fourier transform ion cyclotron resonance mass spectrometry (2D FTICR MS or 2D MS) allows direct correlation between precursor and fragment ions without isolation prior to fragmentation. The method has been optimized for the analysis of complex mixtures and used so far for the analysis of small molecules and peptides obtained by tryptic digestion of proteins and entire proteins. In this work, a 2D MS method is developed to characterize complex mixtures of polymers using infrared multiphoton decay (IRMPD) and electron capture dissociation (ECD) as fragmentation techniques, and D-α-tocopheryl polyethylene glycol 1000 succinate (TPGS), Polysorbate 80, and poly(methyl methacrylate) (PMMA) as analytes. The use of 2D MS allowed generation of fragment m/z values for all the compounds in the mixture at once and allowed tandem mass spectrometry of species very close in m/z that would have been difficult to isolate with a quadrupole for standard MS/MS. Furthermore, the use of unique features of 2D MS such as the extraction of neutral-loss lines allowed the successful assignment of peaks from low abundant species that would have been more difficult with standard MS/MS. For all the samples, the amount of information obtained with 2D MS was comparable with what obtained with multiple 1D MS/MS experiments targeted on each individual component within each mixture but required a single experiment of about 20-40 min.

2D FT-ICR MS of Calmodulin: A Top-Down and Bottom-Up Approach.

Two-dimensional Fourier transform ion cyclotron resonance mass spectrometry (2D FT-ICR MS) allows data-independent fragmentation of all ions in a sample and correlation of fragment ions to their precursors through the modulation of precursor ion cyclotron radii prior to fragmentation. Previous results show that implementation of 2D FT-ICR MS with infrared multi-photon dissociation (IRMPD) and electron capture dissociation (ECD) has turned this method into a useful analytical tool. In this work, IRMPD tandem mass spectrometry of calmodulin (CaM) has been performed both in one-dimensional and two-dimensional FT-ICR MS using a top-down and bottom-up approach. 2D IRMPD FT-ICR MS is used to achieve extensive inter-residue bond cleavage and assignment for CaM, using its unique features for fragment identification in a less time- and sample-consuming experiment than doing the same thing using sequential MS/MS experiments. Graphical Abstract ᅟ.

Two-Dimensional Mass Spectrometry for Proteomics, a Comparative Study with Cytochrome c.

Two-dimensional Fourier transform ion cyclotron resonance mass spectrometry (2D FT-ICR MS) allows the correlation between precursor and fragment ions in tandem mass spectrometry without the need to isolate the precursor ion beforehand. 2D FT-ICR MS has been optimized as a data-independent method for the structural analysis of compounds in complex samples. Data processing methods and denoising algorithms have been developed to use it as an analytical tool. In the present study, the capabilities of 2D FT-ICR MS are explored with a tryptic digest of cytochrome c with both ECD and IRMPD as fragmentation modes. The 2D mass spectra showed useful fragmentation patterns of peptides over a dynamic range of almost 400. By using a quadratic calibration, fragment ion peaks could be successfully assigned. The correlation between precursor and fragment ions in the 2D mass spectra was more accurate than in MS/MS spectra after quadrupole isolation, due to the limitations of quadrupole isolation. The use of the second dimension allowed for successful fragment assignment from precursors that were separated by only m/z 0.0156. The resulting cleavage coverage of cytochrome c almost matched data provided by high-resolution FT-ICR MS/MS analysis, but the 2D FT-ICR MS method required only one experimental scan.

Differentiating Fragmentation Pathways of Cholesterol by Two-Dimensional Fourier Transform Ion Cyclotron Resonance Mass Spectrometry.

Two-dimensional Fourier transform ion cyclotron resonance mass spectrometry is a data-independent analytical method that records the fragmentation patterns of all the compounds in a sample. This study shows the implementation of atmospheric pressure photoionization with two-dimensional (2D) Fourier transform ion cyclotron resonance mass spectrometry. In the resulting 2D mass spectrum, the fragmentation patterns of the radical and protonated species from cholesterol are differentiated. This study shows the use of fragment ion lines, precursor ion lines, and neutral loss lines in the 2D mass spectrum to determine fragmentation mechanisms of known compounds and to gain information on unknown ion species in the spectrum. In concert with high resolution mass spectrometry, 2D Fourier transform ion cyclotron resonance mass spectrometry can be a useful tool for the structural analysis of small molecules. Graphical Abstract ᅟ.

Efficient denoising algorithms for large experimental datasets and their applications in Fourier transform ion cyclotron resonance mass spectrometry.

Modern scientific research produces datasets of increasing size and complexity that require dedicated numerical methods to be processed. In many cases, the analysis of spectroscopic data involves the denoising of raw data before any further processing. Current efficient denoising algorithms require the singular value decomposition of a matrix with a size that scales up as the square of the data length, preventing their use on very large datasets. Taking advantage of recent progress on random projection and probabilistic algorithms, we developed a simple and efficient method for the denoising of very large datasets. Based on the QR decomposition of a matrix randomly sampled from the data, this approach allows a gain of nearly three orders of magnitude in processing time compared with classical singular value decomposition denoising. This procedure, called urQRd (uncoiled random QR denoising), strongly reduces the computer memory footprint and allows the denoising algorithm to be applied to virtually unlimited data size. The efficiency of these numerical tools is demonstrated on experimental data from high-resolution broadband Fourier transform ion cyclotron resonance mass spectrometry, which has applications in proteomics and metabolomics. We show that robust denoising is achieved in 2D spectra whose interpretation is severely impaired by scintillation noise. These denoising procedures can be adapted to many other data analysis domains where the size and/or the processing time are crucial.

Two-dimensional ECD FT-ICR mass spectrometry of peptides and glycopeptides.

2D FT-ICR MS allows the correlation between precursor and fragment ions by modulating ion cyclotron radii for fragmentation modes with radius-dependent efficiency in the ICR cell without the need for prior ion isolation. This technique has been successfully applied to ion-molecule reactions, Collision-induced dissociation and infrared multiphoton dissociation. In this study, we used electron capture dissociation for 2D FT-ICR MS for the first time, and we recorded two-dimensional mass spectra of peptides and a mixture of glycopeptides that showed fragments that are characteristic of ECD for each of the precursor ions in the sample. We compare the sequence coverage obtained with 2D ECD FT-ICR MS with the sequence coverage obtained with ECD MS/MS and compare the sensitivities of both techniques. We demonstrate how 2D ECD FT-ICR MS can be implemented to identify peptides and glycopeptides for proteomics analysis.