Anil K. Shukla

Tandem mass spectrometry: dissociation of ions by collisional activation

This review presents a brief historical introduction to the development of tandem mass spectrometry and its principal applications. It is placed in the context of the general principles underlying mass spectrometry, particularly the relationships between internal energy and fragmentation kinetics. The center-of-mass framework is presented as a convenient means of applying conservation of momentum to the energy transfer problem in tandem mass spectrometry as a means of deducing energy transfer in the collisional activation step and kinetic energy release as activated ions dissociate into fragment ions and neutrals. The principles of molecular beam methods are summarized and illustrative examples are given for which definitive information on reaction dynamics is available. The importance of scattering-very little appreciated in early discussions of tandem mass spectrometry-is shown to be the natural consequence of impulsive collisions, which appears to be a general mechanism for energy exchange in collisional activation. It is shown that the average energy transferred in single collisions is much less than the theoretical maximum given by the center-of-mass collision energy and the Massey criterion is presented as a simplistic rationale for understanding the essentially exponential decline in the energy transfer function above and below the relative velocity at which the probability for energy transfer is maximized. The issues of energy transfer in collisions of large molecular ions with low-mass neutrals are reviewed and a general description of energy transfer in multiple collisions is presented. It is shown that the center-of-mass and Massey criterion limitations are pragmatically overcome by multiple collision activation in ion traps. Surface-induced dissociation is presented as a viable alternative to multiple collision activation which is especially attractive for activation of large molecular ions. Finally, a few of the emerging dynamics principles governing energy transfer and dissociation of peptides are summarized. Copyright 2000 John Wiley & Sons, Ltd.

Molecular structure and stability of dissolved lithium polysulfide species

The ability to predict the solubility and stability of lithium polysulfide is vital in realizing longer lasting lithium-sulfur batteries. Herein we report combined experimental and computational analyses to understand the dissolution mechanism of lithium polysulfide species in an aprotic solvent medium. Multinuclear NMR, variable temperature ESR and sulfur K-edge XAS analyses reveal that the lithium exchange between polysulfide species and solvent molecules constitutes the first step in the dissolution process. Lithium exchange leads to de-lithiated polysulfide ions (Sn(2-)) which subsequently form highly reactive free radicals through dissociation reaction (Sn(2-) → 2Sn/2˙(-)). The energy required for the dissociation and possible dimer formation reactions of the polysulfide species is analyzed using density functional theory (DFT) based calculations. Based on these findings, we discuss approaches to optimize the electrolyte in order to control the polysulfide solubility.

Pathogenic Influenza Viruses and Coronaviruses Utilize Similar and Contrasting Approaches To Control Interferon-Stimulated Gene Responses

ABSTRACT The broad range and diversity of interferon-stimulated genes (ISGs) function to induce an antiviral state within the host, impeding viral pathogenesis. While successful respiratory viruses overcome individual ISG effectors, analysis of the global ISG response and subsequent viral antagonism has yet to be examined. Employing models of the human airway, transcriptomics and proteomics datasets were used to compare ISG response patterns following highly pathogenic H5N1 avian influenza (HPAI) A virus, 2009 pandemic H1N1, severe acute respiratory syndrome coronavirus (SARS-CoV), and Middle East respiratory syndrome CoV (MERS-CoV) infection. The results illustrated distinct approaches utilized by each virus to antagonize the global ISG response. In addition, the data revealed that highly virulent HPAI virus and MERS-CoV induce repressive histone modifications, which downregulate expression of ISG subsets. Notably, influenza A virus NS1 appears to play a central role in this histone-mediated downregulation in highly pathogenic influenza strains. Together, the work demonstrates the existence of unique and common viral strategies for controlling the global ISG response and provides a novel avenue for viral antagonism via altered histone modifications. IMPORTANCE This work combines systems biology and experimental validation to identify and confirm strategies used by viruses to control the immune response. Using a novel screening approach, specific comparison between highly pathogenic influenza viruses and coronaviruses revealed similarities and differences in strategies to control the interferon and innate immune response. These findings were subsequently confirmed and explored, revealing both a common pathway of antagonism via type I interferon (IFN) delay as well as a novel avenue for control by altered histone modification. Together, the data highlight how comparative systems biology analysis can be combined with experimental validation to derive novel insights into viral pathogenesis. This work combines systems biology and experimental validation to identify and confirm strategies used by viruses to control the immune response. Using a novel screening approach, specific comparison between highly pathogenic influenza viruses and coronaviruses revealed similarities and differences in strategies to control the interferon and innate immune response. These findings were subsequently confirmed and explored, revealing both a common pathway of antagonism via type I interferon (IFN) delay as well as a novel avenue for control by altered histone modification. Together, the data highlight how comparative systems biology analysis can be combined with experimental validation to derive novel insights into viral pathogenesis.

A comparative analysis of computational approaches to relative protein quantification using peptide peak intensities in label-free LC-MS proteomics experiments.

Liquid chromatography coupled with mass spectrometry (LC‐MS) is widely used to identify and quantify peptides in complex biological samples. In particular, label‐free shotgun proteomics is highly effective for the identification of peptides and subsequently obtaining a global protein profile of a sample. As a result, this approach is widely used for discovery studies. Typically, the objective of these discovery studies is to identify proteins that are affected by some condition of interest (e.g. disease, exposure). However, for complex biological samples, label‐free LC‐MS proteomics experiments measure peptides and do not directly yield protein quantities. Thus, protein quantification must be inferred from one or more measured peptides. In recent years, many computational approaches to relative protein quantification of label‐free LC‐MS data have been published. In this review, we examine the most commonly employed quantification approaches to relative protein abundance from peak intensity values, evaluate their individual merits, and discuss challenges in the use of the various computational approaches.

Fundamentals of tandem mass spectrometry: a dynamics study of simple C−C bond cleavage in collision-activated dissociation of polyatomic ions at low energy

The loss of methyl radical in collision-activated dissociation (CAD) of acetone and propane molecular ions has been studied at low energy using a tandem hybrid mass spectrometer. Although the two processes are very similar chemically and energetically, very different dynamical features are observed. Acetyl ions from acetone ion are predominantly backward-scattered, with intensity maxima lying inside and outside the elastic scattering circle, confirming our previous observation that electronically excited states are important in low-energy acetone CAD. Ethyl ions from propane ion show a forward-scattered peak maximum at a nonzero scattering angle, which is consistent with generally accepted models for vibrational excitation and redistribution of energy before dissociation. Both processes demonstrate that CAD at low energy proceeds via small-impact-parameter collisions with momentum transfer. Comparison of the present results with higher energy CAD dynamics studies and earlier work leads to some tentative general conclusions about energy transfer in these processes.

Quantitative site-specific reactivity profiling of S-nitrosylation in mouse skeletal muscle using cysteinyl peptide enrichment coupled with mass spectrometry.

S-nitrosylation, the formation of S-nitrosothiol (SNO), is an important reversible thiol oxidation event that has been increasingly recognized for its role in cell signaling. Although many proteins susceptible to S-nitrosylation have been reported, site-specific identification of physiologically relevant SNO modifications remains an analytical challenge because of the low abundance and labile nature of this modification. Herein we present further improvement and optimization of the recently reported resin-assisted cysteinyl peptide enrichment protocol for SNO identification and its application to mouse skeletal muscle to identify specific cysteine sites sensitive to S-nitrosylation by a quantitative reactivity profiling strategy. Our results indicate that the protein- and peptide-level enrichment protocols provide comparable specificity and coverage of SNO-peptide identifications. S-nitrosylation reactivity profiling was performed by quantitatively comparing the site-specific SNO modification levels in samples treated with S-nitrosoglutathione, an NO donor, at two different concentrations (i.e., 10 and 100 μM). The reactivity profiling experiments led to the identification of 488 SNO-modified sites from 197 proteins with specificity of ∼95% at the unique peptide level, i.e., ∼95% of enriched peptides contain cysteine residues as the originally SNO-modified sites. Among these sites, 281 from 145 proteins were considered more sensitive to S-nitrosylation based on the ratios of observed SNO levels between the two treatments. These SNO-sensitive sites are more likely to be physiologically relevant. Many of the SNO-sensitive proteins are localized in mitochondria, contractile fiber, and actin cytoskeleton, suggesting the susceptibility of these subcellular compartments to redox regulation. Moreover, these observed SNO-sensitive proteins are primarily involved in metabolic pathways, including the tricarboxylic acid cycle, glycolysis/gluconeogenesis, glutathione metabolism, and fatty acid metabolism, suggesting the importance of redox regulation in muscle metabolism and insulin action.

Mechanisms of Severe Acute Respiratory Syndrome Coronavirus-Induced Acute Lung Injury

ABSTRACT Systems biology offers considerable promise in uncovering novel pathways by which viruses and other microbial pathogens interact with host signaling and expression networks to mediate disease severity. In this study, we have developed an unbiased modeling approach to identify new pathways and network connections mediating acute lung injury, using severe acute respiratory syndrome coronavirus (SARS-CoV) as a model pathogen. We utilized a time course of matched virologic, pathological, and transcriptomic data within a novel methodological framework that can detect pathway enrichment among key highly connected network genes. This unbiased approach produced a high-priority list of 4 genes in one pathway out of over 3,500 genes that were differentially expressed following SARS-CoV infection. With these data, we predicted that the urokinase and other wound repair pathways would regulate lethal versus sublethal disease following SARS-CoV infection in mice. We validated the importance of the urokinase pathway for SARS-CoV disease severity using genetically defined knockout mice, proteomic correlates of pathway activation, and pathological disease severity. The results of these studies demonstrate that a fine balance exists between host coagulation and fibrinolysin pathways regulating pathological disease outcomes, including diffuse alveolar damage and acute lung injury, following infection with highly pathogenic respiratory viruses, such as SARS-CoV. IMPORTANCE Severe acute respiratory syndrome coronavirus (SARS-CoV) emerged in 2002 and 2003, and infected patients developed an atypical pneumonia, acute lung injury (ALI), and acute respiratory distress syndrome (ARDS) leading to pulmonary fibrosis and death. We identified sets of differentially expressed genes that contribute to ALI and ARDS using lethal and sublethal SARS-CoV infection models. Mathematical prioritization of our gene sets identified the urokinase and extracellular matrix remodeling pathways as the most enriched pathways. By infecting Serpine1-knockout mice, we showed that the urokinase pathway had a significant effect on both lung pathology and overall SARS-CoV pathogenesis. These results demonstrate the effective use of unbiased modeling techniques for identification of high-priority host targets that regulate disease outcomes. Similar transcriptional signatures were noted in 1918 and 2009 H1N1 influenza virus-infected mice, suggesting a common, potentially treatable mechanism in development of virus-induced ALI. Severe acute respiratory syndrome coronavirus (SARS-CoV) emerged in 2002 and 2003, and infected patients developed an atypical pneumonia, acute lung injury (ALI), and acute respiratory distress syndrome (ARDS) leading to pulmonary fibrosis and death. We identified sets of differentially expressed genes that contribute to ALI and ARDS using lethal and sublethal SARS-CoV infection models. Mathematical prioritization of our gene sets identified the urokinase and extracellular matrix remodeling pathways as the most enriched pathways. By infecting Serpine1-knockout mice, we showed that the urokinase pathway had a significant effect on both lung pathology and overall SARS-CoV pathogenesis. These results demonstrate the effective use of unbiased modeling techniques for identification of high-priority host targets that regulate disease outcomes. Similar transcriptional signatures were noted in 1918 and 2009 H1N1 influenza virus-infected mice, suggesting a common, potentially treatable mechanism in development of virus-induced ALI.

Simple Sodium Dodecyl Sulfate-Assisted Sample Preparation Method for LC-MS-Based Proteomics Applications

Sodium dodecyl sulfate (SDS) is one of the most popular laboratory reagents used for biological sample extraction; however, the presence of this reagent in samples challenges LC-MS-based proteomics analyses because it can interfere with reversed-phase LC separations and electrospray ionization. This study reports a simple SDS-assisted proteomics sample preparation method facilitated by a novel peptide-level SDS removal step. In an initial demonstration, SDS was effectively (>99.9%) removed from peptide samples through ion substitution-mediated DS(-) precipitation using potassium chloride (KCl), and excellent peptide recovery (>95%) was observed for <20 μg of peptides. Further experiments demonstrated the compatibility of this protocol with LC-MS/MS analyses. The resulting proteome coverage obtained for both mammalian tissues and bacterial samples was comparable to or better than that obtained for the same sample types prepared using standard proteomics preparation methods and analyzed using LC-MS/MS. These results suggest the SDS-assisted protocol is a practical, simple, and broadly applicable proteomics sample processing method, which can be particularly useful when dealing with samples difficult to solubilize by other methods.

Release of Severe Acute Respiratory Syndrome Coronavirus Nuclear Import Block Enhances Host Transcription in Human Lung Cells

ABSTRACT The severe acute respiratory syndrome coronavirus accessory protein ORF6 antagonizes interferon signaling by blocking karyopherin-mediated nuclear import processes. Viral nuclear import antagonists, expressed by several highly pathogenic RNA viruses, likely mediate pleiotropic effects on host gene expression, presumably interfering with transcription factors, cytokines, hormones, and/or signaling cascades that occur in response to infection. By bioinformatic and systems biology approaches, we evaluated the impact of nuclear import antagonism on host expression networks by using human lung epithelial cells infected with either wild-type virus or a mutant that does not express ORF6 protein. Microarray analysis revealed significant changes in differential gene expression, with approximately twice as many upregulated genes in the mutant virus samples by 48 h postinfection, despite identical viral titers. Our data demonstrated that ORF6 protein expression attenuates the activity of numerous karyopherin-dependent host transcription factors (VDR, CREB1, SMAD4, p53, EpasI, and Oct3/4) that are critical for establishing antiviral responses and regulating key host responses during virus infection. Results were confirmed by proteomic and chromatin immunoprecipitation assay analyses and in parallel microarray studies using infected primary human airway epithelial cell cultures. The data strongly support the hypothesis that viral antagonists of nuclear import actively manipulate host responses in specific hierarchical patterns, contributing to the viral pathogenic potential in vivo. Importantly, these studies and modeling approaches not only provide templates for evaluating virus antagonism of nuclear import processes but also can reveal candidate cellular genes and pathways that may significantly influence disease outcomes following severe acute respiratory syndrome coronavirus infection in vivo.

Identification of widespread adenosine nucleotide binding in mycobacterium tuberculosis

Computational prediction of protein function is frequently error-prone and incomplete. In Mycobacterium tuberculosis (Mtb), ~25% of all genes have no predicted function and are annotated as hypothetical proteins, severely limiting our understanding of Mtb pathogenicity. Here, we utilize a high-throughput quantitative activity-based protein profiling (ABPP) platform to probe, annotate, and validate ATP-binding proteins in Mtb. We experimentally validate prior in silico predictions of >240 proteins and identify 72 hypothetical proteins as ATP binders. ATP interacts with proteins with diverse and unrelated sequences, providing an expanded view of adenosine nucleotide binding in Mtb. Several hypothetical ATP binders are essential or taxonomically limited, suggesting specialized functions in mycobacterial physiology and pathogenicity.