Characterization of the cellular lipid composition during SARS-CoV-2 infection.

Emerging and re-emerging zoonotic viral diseases continue to significantly impact public health. Of particular interest are enveloped viruses (e.g., SARS-CoV-2, the causative pathogen of COVID-19), which include emerging pathogens of highest concern. Enveloped viruses contain a viral envelope that encapsulates the genetic material and nucleocapsid, providing structural protection and functional bioactivity. The viral envelope is composed of a coordinated network of glycoproteins and lipids. The lipid composition of the envelope consists of lipids preferentially appropriated from host cell membranes. Subsequently, changes to the host cell lipid metabolism and an accounting of what lipids are changed during viral infection provide an opportunity to fingerprint the host cell's response to the infecting virus. To address this issue, we comprehensively characterized the lipid composition of VeroE6-TMPRSS2 cells infected with SARS-CoV-2. Our approach involved using an innovative solid-phase extraction technique to efficiently extract cellular lipids combined with liquid chromatography coupled to high-resolution tandem mass spectrometry. We identified lipid changes in cells exposed to SARS-CoV-2, of which the ceramide to sphingomyelin ratio was most prominent. The identification of a lipid profile (i.e., lipid fingerprint) that is characteristic of cellular SARS-CoV-2 infection lays the foundation for targeting lipid metabolism pathways to further understand how enveloped viruses infect cells, identifying opportunities to aid antiviral and vaccine development.

PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements.

Multidimensional measurements using state-of-the-art separations and mass spectrometry provide advantages in untargeted metabolomics analyses for studying biological and environmental bio-chemical processes. However, the lack of rapid analytical methods and robust algorithms for these heterogeneous data has limited its application. Here, we develop and evaluate a sensitive and high-throughput analytical and computational workflow to enable accurate metabolite profiling. Our workflow combines liquid chromatography, ion mobility spectrometry and data-independent acquisition mass spectrometry with PeakDecoder, a machine learning-based algorithm that learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates. We apply PeakDecoder for metabolite profiling of various engineered strains of Aspergillus pseudoterreus, Aspergillus niger, Pseudomonas putida and Rhodosporidium toruloides. Results, validated manually and against selected reaction monitoring and gas-chromatography platforms, show that 2683 features could be confidently annotated and quantified across 116 microbial sample runs using a library built from 64 standards.

Quasi-continuous infrared matrix-assisted laser desorption electrospray ionization source coupled to a quadrupole time-of-flight mass spectrometer for direct analysis from well plates.

High-throughput screening (HTS) is a technique mostly used by pharmaceutical companies to rapidly screen multiple libraries of compounds to find drug hits with biological or pharmaceutical activity. Mass spectrometry (MS) has become a popular option for HTS given that it can simultaneously resolve hundreds to thousands of compounds without additional chemical derivatization. For this application, it is convenient to do direct analysis from well plates. Herein, we present the development of an infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) source coupled directly to an Agilent 6545 for direct analysis from well plates. The source is coupled to a quadrupole time-of-flight (Q-TOF) mass spectrometer to take advantage of the high acquisition rates without sacrificing resolving power as required with Orbitrap or Fourier-transform ion cyclotron resonance (FTICR) instruments. The laser used for this source operates at 100 Hz, firing 1 pulse-per-burst, and delivers around 0.7 mJ per pulse. Continuously firing this laser for an extended duration makes it a quasi-continuous ionization source. Additionally, a metal capillary was constructed to extend the inlet of the mass spectrometer, increase desolvation of electrospray charged droplets, improve ion transmission, and increase sensitivity. Its efficiency was compared with the conventional dielectric glass capillary by measured signal and demonstrated that the metal capillary increased ionization efficiency due to its more uniformly distributed temperature gradient. Finally, we present the functionality of the source by analyzing tune mix directly from well plates. This source is a proof of concept for HTS applications using IR-MALDESI coupled to a different MS platform.

A Novel Solid Phase Extraction Sample Preparation Method for Lipidomic Analysis of Human Plasma Using Liquid Chromatography/Mass Spectrometry.

Lipidomic approaches are widely used to investigate the relationship between lipids, human health, and disease. Conventional sample preparation techniques for the extraction of lipids from biological matrices like human plasma are based on liquid-liquid extraction (LLE). However, these methods are labor-intensive, time-consuming, and can show poor reproducibility and selectivity on lipid extraction. A novel, solid-phase extraction (SPE) approach was demonstrated to extract lipids from human plasma using a lipid extraction SPE in both cartridge and 96-well-plate formats, followed by analysis using a combination of targeted and untargeted liquid chromatography/mass spectrometry. The Lipid Extraction SPE method was compared to traditional LLE methods for lipid class recovery, lipidome coverage, and reproducibility. The novel SPE method used a simplified protocol with significant time and labor savings and provided equivalent or better qualitative and quantitative results than traditional LLE methods with respect to several critical performance metrics; recovery, reproducibility, and lipidome coverage.

SPE-IMS-MS: An automated platform for sub-sixty second surveillance of endogenous metabolites and xenobiotics in biofluids.

Characterization of endogenous metabolites and xenobiotics is essential to deconvoluting the genetic and environmental causes of disease. However, surveillance of chemical exposure and disease-related changes in large cohorts requires an analytical platform that offers rapid measurement, high sensitivity, efficient separation, broad dynamic range, and application to an expansive chemical space. Here, we present a novel platform for small molecule analyses that addresses these requirements by combining solid-phase extraction with ion mobility spectrometry and mass spectrometry (SPE-IMS-MS). This platform is capable of performing both targeted and global measurements of endogenous metabolites and xenobiotics in human biofluids with high reproducibility (CV 6 3%), sensitivity (LODs in the pM range in biofluids) and throughput (10-s sample-to-sample duty cycle). We report application of this platform to the analysis of human urine from patients with and without type 1 diabetes, where we observed statistically significant variations in the concentration of disaccharides and previously unreported chemical isomers. This SPE-IMS-MS platform overcomes many of the current challenges of large-scale metabolomic and exposomic analyses and offers a viable option for population and patient cohort screening in an effort to gain insights into disease processes and human environmental chemical exposure.

Plant proteogenomics: from protein extraction to improved gene predictions.

Historically many genome annotation strategies have lacked experimental evidence at the protein level, which and have instead relied heavily on ab initio gene prediction tools, which consequently resulted in many incorrectly annotated genomic sequences. Proteogenomics aims to address these issues using mass spectrometry (MS)-based proteomics, genomic mapping, and providing statistical significance measures such as false discovery rates (FDRs) to validate the mapped peptides. Presented here is a tool capable of meeting this goal, the UCSD proteogenomic pipeline, which maps peptide-spectrum matches (PSMs) to the genome using the Inspect MS/MS database search tool and assigns a statistical significance to the match using a target-decoy search approach to assign estimated FDRs. This pipeline also provides the option of using a more reliable approach to proteogenomics by determining the precise false-positive rates (FPRs) and p-values of each PSM by calculating their spectral probabilities and rescoring each PSM accordingly. In addition to the protein prediction challenges in the rapidly growing number of sequenced plant genomes, it is difficult to extract high-quality protein samples from many plant species. For that reason, this chapter contains methods for protein extraction and trypsin digestion that reliably produce samples suitable for proteogenomic analysis.

RNA-protein analysis using a conditional CRISPR nuclease.

RNA-binding proteins control the fate and function of the transcriptome in all cells. Here we present technology for isolating RNA-protein partners efficiently and accurately using an engineered clustered regularly interspaced short palindromic repeats (CRISPR) endoribonuclease. An inactive version of the Csy4 nuclease binds irreversibly to transcripts engineered with a 16-nt hairpin sequence at their 5' ends. Once immobilized by Csy4 on a solid support, contaminating proteins and other molecules can be removed by extensive washing. Upon addition of imidazole, Csy4 is activated to cleave the RNA, removing the hairpin tag and releasing the native transcript along with its specifically bound protein partners. This conditional Csy4 enzyme enables recovery of specific RNA-binding partners with minimal false-positive contamination. We use this method, coupled with quantitative MS, to identify cell type-specific human pre-microRNA-binding proteins. We also show that this technology is suitable for analyzing diverse size transcripts, and that it is suitable for adaptation to a high-throughput discovery format.

Alpha-arrestins Aly1 and Aly2 regulate intracellular trafficking in response to nutrient signaling.

Extracellular signals regulate trafficking events to reorganize proteins at the plasma membrane (PM); however, few effectors of this regulation have been identified. ß-Arrestins relay signaling cues to the trafficking machinery by controlling agonist-stimulated endocytosis of G-protein-coupled receptors. In contrast, we show that yeast α-arrestins, Aly1 and Aly2, control intracellular sorting of Gap1, the general amino acid permease, in response to nutrients. These studies are the first to demonstrate association of α-arrestins with clathrin and clathrin adaptor proteins (AP) and show that Aly1 and Aly2 interact directly with the γ-subunit of AP-1, Apl4. Aly2-dependent trafficking of Gap1 requires AP-1, which mediates endosome-to-Golgi transport, and the nutrient-regulated kinase, Npr1, which phosphorylates Aly2. During nitrogen starvation, Npr1 phosphorylation of Aly2 may stimulate Gap1 incorporation into AP-1/clathrin-coated vesicles to promote Gap1 trafficking from endosomes to the trans-Golgi network. Ultimately, increased Aly1-/Aly2-mediated recycling of Gap1 from endosomes results in higher Gap1 levels within cells and at the PM by diverting Gap away from trafficking pathways that lead to vacuolar degradation. This work defines a new role for arrestins in membrane trafficking and offers insight into how α-arrestins coordinate signaling events with protein trafficking.

Hydrophobic and electrostatic forces control the retention of membrane peptides and proteins with an immobilised phosphatidic acid column.

The retention behaviour of four membrane-associated peptides and proteins with an immobilized phosphatidic acid (PA) stationary phase was evaluated. The solutes included the cytolytic peptides gramicidin A and melittin, the integral membrane protein bacteriorhodpsin and cytochrome c, a peripheral membrane protein. Gramicidin has no nett charge and exhibited normal reversed phase-like behaviour which was largely independent of mobile phase pH. In contrast, melittin, which has a positively charged C-terminal tail, exhibited reversed phase like retention at pH 5.4 and 7.4, and was not retained at pH 3 reflecting the influence of electrostatic interactions with the negatively charged phosphatidic acid ligand. Bacteriorhodpsin was eluted at high acetonitrile concentrations at pH 3 and 5.4 and cytochrome c was only eluted at pH 3. Moreover, cytochrome c eluted in the breakthrough peak between 0 and 100% acetonitrile, demonstrating the role of electrostatic interactions with the PA surface. Overall, the results demonstrate that pH can be used to optimize the fractionation and separation of membrane proteins with immobilized lipid stationary phases.