Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics.

Major aims of single-cell proteomics include increasing the consistency, sensitivity and depth of protein quantification, especially for proteins and modifications of biological interest. Here, to simultaneously advance all these aims, we developed prioritized Single-Cell ProtEomics (pSCoPE). pSCoPE consistently analyzes thousands of prioritized peptides across all single cells (thus increasing data completeness) while maximizing instrument time spent analyzing identifiable peptides, thus increasing proteome depth. These strategies increased the sensitivity, data completeness and proteome coverage over twofold. The gains enabled quantifying protein variation in untreated and lipopolysaccharide-treated primary macrophages. Within each condition, proteins covaried within functional sets, including phagosome maturation and proton transport, similarly across both treatment conditions. This covariation is coupled to phenotypic variability in endocytic activity. pSCoPE also enabled quantifying proteolytic products, suggesting a gradient of cathepsin activities within a treatment condition. pSCoPE is freely available and widely applicable, especially for analyzing proteins of interest without sacrificing proteome coverage. Support for pSCoPE is available at http://scp.slavovlab.net/pSCoPE .

Full Mass Range ΦSDM Orbitrap Mass Spectrometry for DIA Proteome Analysis.

Optimizing data-independent acquisition methods for proteomics applications often requires balancing spectral resolution and acquisition speed. Here, we describe a real-time full mass range implementation of the phase-constrained spectrum deconvolution method (ΦSDM) for Orbitrap mass spectrometry that increases mass resolving power without increasing scan time. Comparing its performance to the standard enhanced Fourier transformation signal processing revealed that the increased resolving power of ΦSDM is beneficial in areas of high peptide density and comes with a greater ability to resolve low-abundance signals. In a standard 2 h analysis of a 200 ng HeLa digest, this resulted in an increase of 16% in the number of quantified peptides. As the acquisition speed becomes even more important when using fast chromatographic gradients, we further applied ΦSDM methods to a range of shorter gradient lengths (21, 12, and 5 min). While ΦSDM improved identification rates and spectral quality in all tested gradients, it proved particularly advantageous for the 5 min gradient. Here, the number of identified protein groups and peptides increased by >15% in comparison to enhanced Fourier transformation processing. In conclusion, ΦSDM is an alternative signal processing algorithm for processing Orbitrap data that can improve spectral quality and benefit quantitative accuracy in typical proteomics experiments, especially when using short gradients.

EASI-tag enables accurate multiplexed and interference-free MS2-based proteome quantification.

We developed EASI-tag (easily abstractable sulfoxide-based isobaric-tag), a new type of amine-derivatizing and sulfoxide-containing isobaric labeling reagents for highly accurate quantitative proteomics analysis using mass spectrometry. We observed that EASI-tag labels dissociate at low collision energy and generate peptide-coupled, interference-free reporter ions with high yield. Efficient isolation of 12C precursors and quantification at the MS2 level allowed accurate determination of quantitative differences between up to six multiplexed samples.

MaxQuant.Live Enables Global Targeting of More Than 25,000 Peptides.

Mass spectrometry (MS)-based proteomics is often performed in a shotgun format, in which as many peptide precursors as possible are selected from full or MS1 scans so that their fragment spectra can be recorded in MS2 scans. Although achieving great proteome depths, shotgun proteomics cannot guarantee that each precursor will be fragmented in each run. In contrast, targeted proteomics aims to reproducibly and sensitively record a restricted number of precursor/fragment combinations in each run, based on prescheduled mass-to-charge and retention time windows. Here we set out to unify these two concepts by a global targeting approach in which an arbitrary number of precursors of interest are detected in real-time, followed by standard fragmentation or advanced peptide-specific analyses. We made use of a fast application programming interface to a quadrupole Orbitrap instrument and real-time recalibration in mass, retention time and intensity dimensions to predict precursor identity. MaxQuant.Live is freely available (www.maxquant.live) and has a graphical user interface to specify many predefined data acquisition strategies. Acquisition speed is as fast as with the vendor software and the power of our approach is demonstrated with the acquisition of breakdown curves for hundreds of precursors of interest. We also uncover precursors that are not even visible in MS1 scans, using elution time prediction based on the auto-adjusted retention time alone. Finally, we successfully recognized and targeted more than 25,000 peptides in single LC-MS runs. Global targeting combines the advantages of two classical approaches in MS-based proteomics, whereas greatly expanding the analytical toolbox.

MaxQuant.Live Enables Global Targeting of More Than 25,000 Peptides.

Mass spectrometry (MS)-based proteomics is often performed in a shotgun format, in which as many peptide precursors as possible are selected from full or MS1 scans so that their fragment spectra can be recorded in MS2 scans. Although achieving great proteome depths, shotgun proteomics cannot guarantee that each precursor will be fragmented in each run. In contrast, targeted proteomics aims to reproducibly and sensitively record a restricted number of precursor/fragment combinations in each run, based on prescheduled mass-to-charge and retention time windows. Here we set out to unify these two concepts by a global targeting approach in which an arbitrary number of precursors of interest are detected in real-time, followed by standard fragmentation or advanced peptide-specific analyses. We made use of a fast application programming interface to a quadrupole Orbitrap instrument and real-time recalibration in mass, retention time and intensity dimensions to predict precursor identity. MaxQuant.Live is freely available (www.maxquant.live) and has a graphical user interface to specify many predefined data acquisition strategies. Acquisition speed is as fast as with the vendor software and the power of our approach is demonstrated with the acquisition of breakdown curves for hundreds of precursors of interest. We also uncover precursors that are not even visible in MS1 scans, using elution time prediction based on the auto-adjusted retention time alone. Finally, we successfully recognized and targeted more than 25,000 peptides in single LC-MS runs. Global targeting combines the advantages of two classical approaches in MS-based proteomics, whereas greatly expanding the analytical toolbox. MaxQuant.Live builds on the fast application programming interface of quadrupole Orbitrap mass analyzers to control data acquisition in real-time (freely available at www.maxquant.live). Its graphical user interface enables advanced data acquisition strategies, such as in-depth characterization of peptides of interest. Online recalibration in mass, retention time, and intensity dimensions extends this concept to more than 25,000 peptides per run. Our "global targeting" strategy combines the best of targeted and shotgun approaches.

A polarizable QM/MM approach to the molecular dynamics of amide groups solvated in water.

The infrared (IR) spectra of polypeptides are dominated by the so-called amide bands. Because they originate from the strongly polar and polarizable amide groups (AGs) making up the backbone, their spectral positions sensitively depend on the local electric fields. Aiming at accurate computations of these IR spectra by molecular dynamics (MD) simulations, which derive atomic forces from a hybrid quantum and molecular mechanics (QM/MM) Hamiltonian, here we consider the effects of solvation in bulk liquid water on the amide bands of the AG model compound N-methyl-acetamide (NMA). As QM approach to NMA we choose grid-based density functional theory (DFT). For the surrounding MM water, we develop, largely based on computations, a polarizable molecular mechanics (PMM) model potential called GP6P, which features six Gaussian electrostatic sources (one induced dipole, five static partial charge distributions) and, therefore, avoids spurious distortions of the DFT electron density in hybrid DFT/PMM simulations. Bulk liquid GP6P is shown to have favorable properties at the thermodynamic conditions of the parameterization and beyond. Lennard-Jones (LJ) parameters of the DFT fragment NMA are optimized by comparing radial distribution functions in the surrounding GP6P liquid with reference data obtained from a "first-principles" DFT-MD simulation. Finally, IR spectra of NMA in GP6P water are calculated from extended DFT/PMM-MD trajectories, in which the NMA is treated by three different DFT functionals (BP, BLYP, B3LYP). Method-specific frequency scaling factors are derived from DFT-MD simulations of isolated NMA. The DFT/PMM-MD simulations with GP6P and with the optimized LJ parameters then excellently predict the effects of aqueous solvation and deuteration observed in the IR spectra of NMA. As a result, the methods required to accurately compute such spectra by DFT/PMM-MD also for larger peptides in aqueous solution are now at hand.

Preparation of geometrically highly controlled Ga particle arrays on quasi-planar nanostructured surfaces as a SCALMS model system.

This study establishes a preparative route towards a model system for supported catalytically active liquid metal solutions (SCALMS) on nanostructured substrates. This model is characterized by a uniquely precise geometrical control of the gallium particle size distribution. In a SCALMS system, the Ga serves as a matrix material which can be decorated with a catalytically active material subsequently. The corresponding Ga containing precursor is spin-coated on aluminum based substrates, previously nanostructured by electrochemical anodization. The highly ordered substrates are functionalized with distinct oxide coatings by atomic layer deposition (ALD) independently from the morphology. After preparation of the metal particles on the oxide interface, the characterization of our model system in terms of its geometry parameters (droplet diameter, size distribution and population density) points to SiO2 as the best suited surface for a highly controlled geometry. This flexible model system can be functionalized with a dissolved noble metal catalyst for the application chosen.

Isolated Rh atoms in dehydrogenation catalysis.

Isolated active sites have great potential to be highly efficient and stable in heterogeneous catalysis, while enabling low costs due to the low transition metal content. Herein, we present results on the synthesis, first catalytic trials, and characterization of the Ga9Rh2 phase and the hitherto not-studied Ga3Rh phase. We used XRD and TEM for structural characterization, and with XPS, EDX we accessed the chemical composition and electronic structure of the intermetallic compounds. In combination with catalytic tests of these phases in the challenging propane dehydrogenation and by DFT calculations, we obtain a comprehensive picture of these novel catalyst materials. Their specific crystallographic structure leads to isolated Rhodium sites, which is proposed to be the decisive factor for the catalytic properties of the systems.

MaxDIA enables library-based and library-free data-independent acquisition proteomics.

MaxDIA is a software platform for analyzing data-independent acquisition (DIA) proteomics data within the MaxQuant software environment. Using spectral libraries, MaxDIA achieves deep proteome coverage with substantially better coefficients of variation in protein quantification than other software. MaxDIA is equipped with accurate false discovery rate (FDR) estimates on both library-to-DIA match and protein levels, including when using whole-proteome predicted spectral libraries. This is the foundation of discovery DIA-hypothesis-free analysis of DIA samples without library and with reliable FDR control. MaxDIA performs three- or four-dimensional feature detection of fragment data, and scoring of matches is augmented by machine learning on the features of an identification. MaxDIA's bootstrap DIA workflow performs multiple rounds of matching with increasing quality of recalibration and stringency of matching to the library. Combining MaxDIA with two new technologies-BoxCar acquisition and trapped ion mobility spectrometry-both lead to deep and accurate proteome quantification.

Simulated Solute Tempering in Fully Polarizable Hybrid QM/MM Molecular Dynamics Simulations.

We successfully apply a solute tempering approach, which substantially reduces the large number of temperature rungs required in conventional tempering methods by solvent charge scaling, to hybrid molecular dynamics simulations combining quantum mechanics with molecular mechanics (QM/MM). Specifically, we integrate a combination of density functional theory (DFT) and polarizable MM (PMM) force fields into the simulated solute tempering (SST) concept. We show that the required DFT/PMM-SST weight parameters can be obtained from inexpensive calculations and that for alanine dipeptide (DFT) in PMM water three rungs suffice to cover the temperature range from 300 to 550 K.

Spectroscopic polarizable force field for amide groups in polypeptides.

The infrared spectra of polypeptides are dominated by the so-called amide bands. These bands originate from the electrostatically coupled vibrations of the strongly polar amide groups (AGs) making up the polypeptide backbone. Because the AGs are highly polarizable, external electric fields can shift the frequencies of the amide normal modes over wide spectral ranges. The sensitivity to external fields and the strong polarity are the reasons why the shapes of the amide bands can code the structure of the polypeptide backbone. Aiming at a decoding of these band shapes, Schultheis et al. (J. Phys. Chem. B 2008, 112, 12217) have recently suggested a polarizable molecular mechanics (PMM) force field for AGs, which employs field dependent force constants and enables the computation of the amide bands from molecular dynamics simulations. Here we extend and refine this first suggestion of such a PMM force field. The extension rests on the choice of suitable internal coordinates for the AGs and on the inclusion of the complete AG Hessian and of its field dependence. The force field parameters are calculated from density functional theory. The improved quality of the resulting PMM descriptions is demonstrated using very simple examples and an outlook is given.