Lipidomics: analysis of the lipid composition of cells and subcellular organelles by electrospray ionization mass spectrometry.

Lipidomics aims to quantitatively define lipid classes, including their molecular species, in biological systems. Lipidomics has experienced rapid progress, mainly because of continuous technical advances in instrumentation that are now enabling quantitative lipid analyses with an unprecedented level of sensitivity and precision. The still-growing category of lipids includes a broad diversity of chemical structures with a wide range of physicochemical properties. Reflecting this diversity, different methods and strategies are being applied to the quantification of lipids. Here, I review state-of-the-art electrospray ionization tandem mass spectrometric approaches and direct infusion to quantitatively assess lipid compositions of cells and subcellular fractions. Finally, I discuss a few examples of the power of mass spectrometry-based lipidomics in addressing cell biological questions.

Lipid shape and packing are key for optimal design of pH-sensitive mRNA lipid nanoparticles.

The ionizable-lipid component of RNA-containing nanoparticles controls the pH-dependent behavior necessary for an efficient delivery of the cargo-the so-called endosomal escape. However, it is still an empirical exercise to identify optimally performing lipids. Here, we study two well-known ionizable lipids, DLin-MC3-DMA and DLin-DMA using a combination of experiments, multiscale computer simulations, and electrostatic theory. All-atom molecular dynamics simulations, and experimentally measured polar headgroup pKa values, are used to develop a coarse-grained representation of the lipids, which enables the investigation of the pH-dependent behavior of lipid nanoparticles (LNPs) through Monte Carlo simulations, in the absence and presence of RNA molecules. Our results show that the charge state of the lipids is determined by the interplay between lipid shape and headgroup chemistry, providing an explanation for the similar pH-dependent ionization state observed for lipids with headgroup pKa values about one-pH-unit apart. The pH dependence of lipid ionization is significantly influenced by the presence of RNA, whereby charge neutrality is achieved by imparting a finite and constant charge per lipid at intermediate pH values. The simulation results are experimentally supported by measurements of α-carbon 13C-NMR chemical shifts for eGFP mRNA LNPs of both DLin-MC3-DMA and DLin-DMA at various pH conditions. Further, we evaluate the applicability of a mean-field Poisson-Boltzmann theory to capture these phenomena.

Selective adsorption of high ionization potential value organic pollutants in wastewater.

It is imperative to devise effective removal strategies for high ionization potential (IP) organic pollutants in wastewater as their reduced electron-donating capacity challenges the efficiency of advanced oxidation systems in degradation. Against this backdrop, leveraging the metal-based carbon material structure meticulously, we employed metal-pyridine-N (M-N-C, M=Fe, Co, and Ni) as the electron transfer bridge. This distinctive design facilitated the ordered transfer of electrons from the adsorbent surface to the surface of high IP value pollutants, acting as a "supplement" to compensate for their deficient electron-donating capability, thereby culminating in the selective adsorption of these pollutants. Furthermore, this adsorbent also demonstrated effective removal of trace emerging contaminants (2 mg/L), displayed robust resistance to various salts, exhibited reusability, and maintained stability. These findings carry substantial implications for future carbon-based material design, offering a pathway toward exceptional adsorption performance in treating water pollution.

Absolute energy levels of liquid water from many-body perturbation theory with effective vertex corrections.

We demonstrate the importance of addressing the Γ vertex and thus going beyond the GW approximation for achieving the energy levels of liquid water in many-body perturbation theory. In particular, we consider an effective vertex function in both the polarizability and the self-energy, which does not produce any computational overhead compared with the GW approximation. We yield the band gap, the ionization potential, and the electron affinity in good agreement with experiment and with a hybrid functional description. The achieved electronic structure and dielectric screening further lead to a good description of the optical absorption spectrum, as obtained through the solution of the Bethe-Salpeter equation. In particular, the experimental peak position of the exciton is accurately reproduced.

Detection of intact amino acids with a hypervelocity ice grain impact mass spectrometer.

Astrobiology studies are a top priority in answering one of the most fundamental questions in planetary science: Is there life beyond Earth? Saturn's icy moon Enceladus is a prime target in the search for life in our solar system, identified by NASA as the second-highest priority site for a flagship mission in the next decade. The orbital sampling technique of impact ionization mass spectrometry indicated the presence of complex organics in the small icy plume particles ejected by Enceladus encountered previously by Cassini. However, high interaction velocities caused ambiguity as to the origin and identity of the organics. Laboratory validation of this technique is needed to show that biosignature molecules can survive an impact at hypervelocity speeds for detection. Here, we present results on the hypervelocity impact of organic-laden submicron ice grains for in situ mass spectrometric characterization with the first technique to accurately replicate this plume sampling scenario: the Hypervelocity Ice Grain Impact Mass Spectrometer. Our results show good agreement with Cassini data at comparable compositions. We show that amino acids entrained in ice grains can be detected intact after impact at speeds up to 4.2 km/s and that salt reduces their detectability, validating the predictions from other model systems. Our results provide a benchmark for this orbital sampling method to successfully detect signs of life and for the interpretation of past and future data. This work has implications not only for a potential Enceladus mission but also for the forthcoming Europa Clipper mission.

Probing the self-ionization of liquid water with ab initio deep potential molecular dynamics.

The chemical equilibrium between self-ionized and molecular water dictates the acid-base chemistry in aqueous solutions, yet understanding the microscopic mechanisms of water self-ionization remains experimentally and computationally challenging. Herein, Density Functional Theory (DFT)-based deep neural network (DNN) potentials are combined with enhanced sampling techniques and a global acid-base collective variable to perform extensive atomistic simulations of water self-ionization for model systems of increasing size. The explicit inclusion of long-range electrostatic interactions in the DNN potential is found to be crucial to accurately reproduce the DFT free energy profile of solvated water ion pairs in small (64 and 128 H2O) cells. The reversible work to separate the hydroxide and hydronium to a distance [Formula: see text] is found to converge for simulation cells containing more than 500 H2O, and a distance of [Formula: see text] 8 Å is the threshold beyond which the work to further separate the two ions becomes approximately zero. The slow convergence of the potential of mean force with system size is related to a restructuring of water and an increase of the local order around the water ions. Calculation of the dissociation equilibrium constant illustrates the key role of long-range electrostatics and entropic effects in the water autoionization process.

Quantifying the partial ionization effect of gold in the transition region between condensed matter and warm dense matter.

It is now well known that solids under ultra-high-pressure shock compression will enter the warm dense matter (WDM) regime which connects condensed matter and hot plasma. How condensed matter turns into the WDM, however, remains largely unexplored due to the lack of data in the transition pressure range. In this letter, by employing the unique high-Z three-stage gas gun launcher technique developed recently, we compress gold into TPa shock pressure to fill the gap inaccessible by the two-stage gas gun and laser shock experiments. With the aid of high-precision Hugoniot data obtained experimentally, we observe a clear softening behavior beyond ~560 GPa. The state-of-the-art ab-initio molecular dynamics calculations reveal that the softening is caused by the ionization of 5d electrons in gold. This work quantifies the partial ionization effect of electrons under extreme conditions, which is critical to model the transition region between condensed matter and WDM.

Advances in mass spectrometry imaging for plant metabolomics-Expanding the analytical toolbox.

Mass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability to characterize complex chemical, spatial, and temporal aspects of plant metabolism. Over the past decade, as the emerging and unique features of various MSI techniques have continued to support new discoveries in studies of plant metabolism closely associated with various aspects of plant function and physiology, spatial metabolomics based on MSI techniques has positioned it at the forefront of plant metabolic studies, providing the opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges at the levels of spatial resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, and spatial multi-omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview of the emergent MSI techniques widely used in the plant sciences, with particular emphasis on recent advances in methodological breakthroughs. Having established the detailed context of MSI, we outline both the golden opportunities and key challenges currently facing plant metabolomics, presenting our vision as to how the enormous potential of MSI technologies will contribute to progress in plant science in the coming years.

A risk assessment framework for multidrug-resistant Staphylococcus aureus using machine learning and mass spectrometry technology.

The emergence of multidrug-resistant bacteria is a critical global crisis that poses a serious threat to public health, particularly with the rise of multidrug-resistant Staphylococcus aureus. Accurate assessment of drug resistance is essential for appropriate treatment and prevention of transmission of these deadly pathogens. Early detection of drug resistance in patients is critical for providing timely treatment and reducing the spread of multidrug-resistant bacteria. This study aims to develop a novel risk assessment framework for S. aureus that can accurately determine the resistance to multiple antibiotics. The comprehensive 7-year study involved ˃20 000 isolates with susceptibility testing profiles of six antibiotics. By incorporating mass spectrometry and machine learning, the study was able to predict the susceptibility to four different antibiotics with high accuracy. To validate the accuracy of our models, we externally tested on an independent cohort and achieved impressive results with an area under the receiver operating characteristic curve of 0. 94, 0.90, 0.86 and 0.91, and an area under the precision-recall curve of 0.93, 0.87, 0.87 and 0.81, respectively, for oxacillin, clindamycin, erythromycin and trimethoprim-sulfamethoxazole. In addition, the framework evaluated the level of multidrug resistance of the isolates by using the predicted drug resistance probabilities, interpreting them in the context of a multidrug resistance risk score and analyzing the performance contribution of different sample groups. The results of this study provide an efficient method for early antibiotic decision-making and a better understanding of the multidrug resistance risk of S. aureus.

Protein analysis by desorption electrospray ionization mass spectrometry.

This review presents progress made in the ambient analysis of proteins, in particular by desorption electrospray ionization-mass spectrometry (DESI-MS). Related ambient ionization techniques are discussed in comparison to DESI-MS only to illustrate the larger context of protein analysis by ambient ionization mass spectrometry. The review describes early and current approaches for the analysis of undigested proteins, native proteins, tryptic digests, and indirect protein determination through reporter molecules. Applications to mass spectrometry imaging for protein spatial distributions, the identification of posttranslational modifications, determination of binding stoichiometries, and enzymatic transformations are discussed. The analytical capabilities of other ambient ionization techniques such as LESA and nano-DESI currently exceed those of DESI-MS for in situ surface sampling of intact proteins from tissues. This review shows, however, that despite its many limitations, DESI-MS is making valuable contributions to protein analysis. The challenges in sensitivity, spatial resolution, and mass range are surmountable obstacles and further development and improvements to DESI-MS is justified.

Mass spectrometry for neurosurgery: Intraoperative support in decision-making.

Ambient ionization mass spectrometry was proved to be a powerful tool for oncological surgery. Still, it remains a translational technique on the way from laboratory to clinic. Brain surgery is the most sensitive to resection accuracy field since the balance between completeness of resection and minimization of nerve fiber damage determines patient outcome and quality of life. In this review, we summarize efforts made to develop various intraoperative support techniques for oncological neurosurgery and discuss difficulties arising on the way to clinical implementation of mass spectrometry-guided brain surgery.

Mass spectrometry of dendrimers.

Mass spectrometry (MS) has become an essential technique to characterize dendrimers as it proved efficient at tackling analytical challenges raised by their peculiar onion-like structure. Owing to their chemical diversity, this review covers benefits of MS methods as a function of dendrimer classes, discussing advantages and limitations of ionization techniques, tandem mass spectrometry (MS/MS) strategies to determine the structure of defective species, as well as most recently demonstrated capabilities of ion mobility spectrometry (IMS) in the field. Complementarily, the well-defined structure of these macromolecules offers major advantages in the development of MS-based method, as reported in a second section reviewing uses of dendrimers as MS and IMS calibration standards and as multifunctional charge inversion reagents in gas phase ion/ion reactions.

Ion Source Complementarity for Characterization of Complex Organic Mixtures Using Fourier Transform Mass Spectrometry: A Review.

Complex organic mixtures are found in many areas of research, such as energy, environment, health, planetology, and cultural heritage, to name but a few. However, due to their complex chemical composition, which holds an extensive potential of information at the molecular level, their molecular characterization is challenging. In mass spectrometry, the ionization step is the key step, as it determines which species will be detected. This review presents an overview of the main ionization sources employed to characterize these kinds of samples in Fourier transform mass spectrometry (FT-MS), namely electrospray (ESI), atmospheric pressure photoionization (APPI), atmospheric pressure chemical ionization (APCI), atmospheric pressure laser ionization (APLI), and (matrix-assisted) laser desorption ionization ((MA)LDI), and their complementarity in the characterization of complex organic mixtures. First, the ionization techniques are examined in the common direct introduction (DI) usage. Second, these approaches are discussed in the context of coupling chromatographic techniques such as gas chromatography, liquid chromatography, and supercritical fluid chromatography.

Understanding zwitterionic ring-expansion polymerization through mass spectrometry.

Zwitterionic ring-expansion polymerization (ZREP) is a polymerization method in which a cyclic monomer is converted into a cyclic polymer through a zwitterionic intermediate. In this review, we explored the ZREP of various cyclic polymers and how mass spectrometry assists in identifying the product architectures and understanding their intricate reaction mechanism. For the majority of polymers (from a few thousand to a few million Da) matrix-assisted laser desorption/ionization time-of-flight mass spectrometry is the most effective mass spectrometry technique to determine the true molecular weight (MW) of the resultant product, but only when the dispersity is low (approximately below 1.2). The key topics covered in this study were the ZREP of cyclic polyesters, cyclic polyamides, and cyclic ethers. In addition, this study also addresses a number of other preliminary topics, including the ZREP of cyclic polycarbonates, cyclic polysiloxanes, and cyclic poly(alkylene phosphates). The purity and efficiency of those syntheses largely depend on the catalyst. Among several catalysts, N-heterocyclic carbenes have exhibited high efficiency in the synthesis of cyclic polyesters and polyamides, whereas tris(pentafluorophenyl)borane [B(C6F5)3] is the most optimal catalyst for cyclic polyether synthesis.

Characterization of the degradation products of lignocellulosic biomass by using tandem mass spectrometry experiments, model compounds, and quantum chemical calculations.

Biomass-derived degraded lignin and cellulose serve as possible alternatives to fossil fuels for energy and chemical resources. Fast pyrolysis of lignocellulosic biomass generates bio-oil that needs further refinement. However, as pyrolysis causes massive degradation to lignin and cellulose, this process produces very complex mixtures. The same applies to degradation methods other than fast pyrolysis. The ability to identify the degradation products of lignocellulosic biomass is of great importance to be able to optimize methodologies for the conversion of these mixtures to transportation fuels and valuable chemicals. Studies utilizing tandem mass spectrometry have provided invaluable, molecular-level information regarding the identities of compounds in degraded biomass. This review focuses on the molecular-level characterization of fast pyrolysis and other degradation products of lignin and cellulose via tandem mass spectrometry based on collision-activated dissociation (CAD). Many studies discussed here used model compounds to better understand both the ionization chemistry of the degradation products of lignin and cellulose and their ions' CAD reactions in mass spectrometers to develop methods for the structural characterization of the degradation products of lignocellulosic biomass. Further, model compound studies were also carried out to delineate the mechanisms of the fast pyrolysis reactions of lignocellulosic biomass. The above knowledge was used to assign likely structures to many degradation products of lignocellulosic biomass.

Submicrometer Particle Impact Dynamics and Chemistry.

Experimental studies of the collision phenomena of submicrometer particles is a developing field. This review examines the range of phenomena that can be observed with new experimental approaches. The primary focus is on single-particle impact studies enabled by charge detection mass spectrometry (CDMS) implemented using the Aerosol Impact Spectrometer (AIS) at the University of California, San Diego. The AIS combines electrospray ionization, aerodynamic lens techniques, CDMS, and an electrostatic linear accelerator to study the dynamics of particle impact over a wide range of incident velocities. The AIS has been used for single-particle impact experiments on positively charged particles of diverse composition, including polystyrene latex spheres, tin particles, and ice grains, over a wide range of impact velocities. Detection schemes based on induced charge measurements and time-of-flight mass spectrometry have enabled measurements of the impact inelasticity through the determination of the coefficient of restitution, measurements of the angular distributions of scattered submicrometer particles, and the chemical composition and dissociation of solute molecules in hypervelocity ice grain impacts.

Preparation of methanediamine (CH2(NH2)2)-A precursor to nucleobases in the interstellar medium.

Although methanediamine (CH2(NH2)2) has historically been the subject of theoretical scrutiny, it has never been isolated to date. Here, we report the preparation of methanediamine (CH2(NH2)2)-the simplest diamine. Low-temperature interstellar analog ices composed of ammonia and methylamine were exposed to energetic electrons which act as proxies for secondary electrons produced in the track of galactic cosmic rays. These experimental conditions, which simulate the conditions within cold molecular clouds, result in radical formation and initiate aminomethyl (CH2NH2) and amino ([Formula: see text]2) radical chemistry. Exploiting tunable photoionization reflectron time-of-flight mass spectrometry (PI-ReToF-MS) to make isomer-specific assignments, methanediamine was identified in the gas phase upon sublimation, while its isomer methylhydrazine (CH3NHNH2) was not observed. The molecular formula was confirmed to be CH6N2 through the use of isotopically labeled reactants. Methanediamine is the simplest molecule to contain the NCN moiety and could be a vital intermediate in the abiotic formation of heterocyclic and aromatic systems such as nucleobases, which all contain the NCN moiety.

Toward a molecular understanding of the surface composition of atmospherically relevant organic particles.

Many mass spectrometry methods using various ionization sources provide bulk composition of airborne particles, but little is known about the surface species that play a major role in determining their physicochemical properties that impact air quality, climate, and health. The present work shows that the composition of surface layers of atmospherically relevant submicron organic particles can be probed without the use of an external ionization source. Solid dicarboxylic acid particles are used as models, with glutaric acid being the most efficient at generating ions. Coating with small diacids or products from α-pinene ozonolysis demonstrates that ions are ejected from the surface, providing surface molecular characterization of organic particles on the fly. This unique approach provides a path forward for elucidating the role of the surface in determining chemical and physical properties of particles, including heterogeneous reactions, particle growth, water uptake, and interactions with biological systems.

Mapping the self-generated magnetic fields due to thermal Weibel instability.

The origin of the seed magnetic field that is amplified by the galactic dynamo is an open question in plasma astrophysics. Aside from primordial sources and the Biermann battery mechanism, plasma instabilities have also been proposed as a possible source of seed magnetic fields. Among them, thermal Weibel instability driven by temperature anisotropy has attracted broad interests due to its ubiquity in both laboratory and astrophysical plasmas. However, this instability has been challenging to measure in a stationary terrestrial plasma because of the difficulty in preparing such a velocity distribution. Here, we use picosecond laser ionization of hydrogen gas to initialize such an electron distribution function. We record the 2D evolution of the magnetic field associated with the Weibel instability by imaging the deflections of a relativistic electron beam with a picosecond temporal duration and show that the measured [Formula: see text]-resolved growth rates of the instability validate kinetic theory. Concurrently, self-organization of microscopic plasma currents is observed to amplify the current modulation magnitude that converts up to ~1% of the plasma thermal energy into magnetic energy, thus supporting the notion that the magnetic field induced by the Weibel instability may be able to provide a seed for the galactic dynamo.

Charge site manipulation to enhance top-down fragmentation efficiency.

In recent years, top-down mass spectrometry has become a widely used approach to study proteoforms; however, improving sequence coverage remains an important goal. Here, two different proteins, α-synuclein and bovine carbonic anhydrase, were subjected to top-down collision-induced dissociation (CID) after electrospray ionisation. Two high-boiling solvents, DMSO and propylene carbonate, were added to the protein solution in low concentration (2%) and the effects on the top-down fragmentation patterns of the proteins were systematically investigated. Each sample was measured in triplicate, which revealed highly reproducible differences in the top-down CID fragmentation patterns in the presence of a solution additive, even if the same precursor charge state was isolated in the quadrupole of the instrument. Further investigation supports the solution condition-dependent selective formation of different protonation site isomers as the underlying cause of these differences. Higher sequence coverage was often observed in the presence of additives, and the benefits of this approach became even more evident when datasets from different solution conditions were combined, as increases up to 35% in cleavage coverage were obtained. Overall, this approach therefore represents a promising opportunity to increase top-down fragmentation efficiency.