Effect of mass spectrometric parameters on peptide and protein identification rates for shotgun proteomic experiments on an LTQ-orbitrap mass analyzer

Optimization of Mass Spectrometric Parameters in Data Dependent Acquisition for Untargeted Metabolomics on the Basis of Putative Assignments

Optimization of mass spectrometric parameters for a data dependent acquisition (DDA) experiment is essential to increase the MS/MS coverage and hence increase metabolite identifications in untargeted metabolomics. We explored the influence of mass spectrometric parameters including mass resolution, radio frequency (RF) level, signal intensity threshold, number of MS/MS events, cycle time, collision energy, maximum ion injection time (MIT), dynamic exclusion, and automatic gain control (AGC) target value on metabolite annotations on an Exploris 480-Orbitrap mass spectrometer. Optimal annotation results were obtained by performing ten data dependent MS/MS scans with a mass isolation window of 2.0 m/z and a minimum signal intensity threshold of 1 × 104 at a mass resolution of 180,000 for MS and 30,000 for MS/MS, while maintaining the RF level at 70%. Furthermore, combining an AGC target value of 5 × 106 and MIT of 100 ms for MS and an AGC target value of 1 × 105 and an MIT of 50 ms for MS/MS scans provided an improved number of annotated metabolites. A 10 s exclusion duration and a two stepped collision energy were optimal for higher spectral quality. These findings confirm that MS parameters do influence metabolomics results, and propose strategies for increasing metabolite coverage in untargeted metabolomics. A limitation of this work is that our parameters were only optimized for one RPLC method on single matrix and may be different for other protocols. Additionally, no metabolites were identified at level 1 confidence. The results presented here are based on metabolite annotations and need to be validated with authentic standards.

Establishing Quality Control Procedures for Large-Scale Plasma Proteomics Analyses

Proteomics research has been transformed due to high-throughput liquid chromatography (LC-MS/MS) tandem mass spectrometry instruments combined with highly sophisticated automated sample preparation and multiplexing workflows. However, scaling proteomics experiments to large sample cohorts (hundreds to thousands) requires thoughtful quality control (QC) protocols. Robust QC protocols can help with reproducibility, quantitative accuracy, and provide opportunities for more decisive troubleshooting. Our laboratory conducted a plasma proteomics study of a cohort of N = 335 patient samples using tandem mass tag (TMT_pro) 16-plex batches. Over the course of a 10-month data acquisition period for this cohort we collected 271 pooled QC LC-MS/MS result files obtained from MS/MS analysis of a patient-derived pooled plasma sample, representative of the entire cohort population. This sample was tagged with TMT_zero or TMT_pro reagents and used to inform the daily performance of the LC-MS/MS instruments and to allow within and across sample batch normalization. Analytical variability of a number of instrumental and data analysis metrics including protein and peptide identifications, peptide spectral matches (PSMs), number of obtained MS/MS spectra, average peptide abundance, percent of peptides with a Δ m/z between ±0.003 Da, percent of MS/MS spectra obtained at the maximum injection time, and the retention time of selected tracking peptides were evaluated to help inform the design of a robust LC-MS/MS QC workflow for use in future cohort studies. This study also led to general tips for using selected metrics to inform real-time troubleshooting of LC-MS/MS performance issues with daily QC checks.

Statistical Framework for Identifying Differences in Similar Mass Spectra: Expanding Possibilities for Isomer Identification

Isomeric molecules are important analytes in many biological and chemical arenas, yet their similarity poses challenges for many analytical methods, including mass spectrometry (MS). Tandem-MS provides significantly more information about isomers than intact mass analysis, but highly similar fragmentation patterns are common and include cases where no unique m/z peaks are generated between isomeric pairs. However, even in such situations, differences in peak intensity can exist and potentially contain additional information. Herein, we present a framework for comparing mass spectra that differ only in terms of peak intensity and include calculation of a statistical probability that the spectra derive from different analytes. This framework allows for confident identification of peptide isomers by collision-induced dissociation, higher-energy collisional dissociation, electron-transfer dissociation, and radical-directed dissociation. The method successfully identified many types of isomers including various d/l amino acid substitutions, Leu/Ile, and Asp/IsoAsp. The method can accommodate a wide range of changes in instrumental settings including source voltages, isolation widths, and resolution without influencing the analysis. It is shown that quantification of the composition of isomeric mixtures can be enabled with calibration curves, which were found to be highly linear and reproducible. The analysis can be implemented with data collected by either direct infusion or liquid-chromatography MS. Although this framework is presented in the context of isomer characterization, it should also prove useful in many other contexts where similar mass spectra are generated.

Optimized Identification of Triacylglycerols in Milk by HPLC-HRMS

This work has developed an optimized workflow for the targeted analysis of triacylglycerols (TAGs) in milk by liquid chromatography coupled with a Q-Exactive Orbitrap mass spectrometer. First, the effects of resolution (17,500; 35,000; 70,000; 140,000) and automatic gain control target (AGC, from 2×104, 2×105, 1×106, and 3×106) have been optimized with the goal to minimize the injection time, maximize the number of scans, and minimize the mass error. Then, the flow rate of the liquid chromatography system was also optimized by maximizing the number of theoretical plates. The resulting optimized parameters consisted of a flow rate of 200 μL/min, mass resolution of 35,000, and AGC target of 2×105. Such optimal conditions were applied for targeted TAG analysis of milk fat extracts. Up to 14 target triglycerides in milk fat were identified performing a data-dependent HPLC-HRMS-MS2 experiment (t-SIM-ddMS2). The findings reported here can be helpful for MS-based lipidomic workflows and targeted milk lipid analysis.

Enhancing data acquisition for the analysis of complex organic matter in direct-infusion Orbitrap mass spectrometry using micro-scans

RATIONALE

Acquisition quality in analytical science is key to obtaining optimal data from a sample. In very high-resolution mass spectrometry, quality is driven by the optimization of multiple parameters, including the use of scans and micro-scans (or transients) for performing a Fourier transformation.

METHODS

Thirty-nine mass spectra of a single synthesized complex sample were acquired using various numbers of scans and micro-scans determined through a simple experimental design. An electrospray ionization source coupled with an LTQ Orbitrap XL™ mass spectrometer was used, and acquisition was performed using a single mass range. All the resulting spectra were treated in the same way to enable comparisons of assigned stoichiometric formulae between acquisitions.

RESULTS

Converting the number of scans into micro-scans enhances signal quality by lowering noise and reducing artifacts. This modification also increases the number of attributed stoichiometric formulae for an equivalent acquisition time, giving access to a larger molecular diversity for the analyzed complex sample.

CONCLUSIONS

For complex samples, the use of long acquisition times leads to optimal data quality, and the use of micro-scans instead of scans-only maximizes the number of attributed stoichiometric formulae.

Human Cytomegalovirus Influences Host circRNA Transcriptions during Productive Infection

Human cytomegalovirus (HCMV) is a double-strand DNA virus widely infected in human. Circular RNAs (circRNAs) are non-coding RNAs with most functions of which keep unknown, and the effects of HCMV productive infection on host circRNA transcriptions remain unclear. In this study, we profiled 283 host circRNAs that significantly altered by HCMV productive infection in human embryonic lung fibroblasts (HELF) by RNA deep sequencing and bioinformatics analysis. Among these, circSP100, circMAP3K1, circPLEKHM1, and circTRIO were validated for their transcriptions and sequences. Furthermore, characteristics of circSP100 were investigated by RT-qPCR and northern blot. It was implied that circSP100 was produced from the sense strand of the SP100 gene containing six exons. Kinetics of circSP100 and SP100 mRNA were significantly different after infection: circSP100 levels increased gradually along with infection, whereas SP100 mRNA levels increased in the beginning and dropped at 24 h post-infection (hpi). Meanwhile, a total number of 257 proteins, including 10 HCMV encoding proteins, were identified potentially binding to cytoplasmic circSP100 by RNA antisense purification (RAP) and mass spectrometry. Enrichment analysis showed these proteins were mainly involved in the spliceosome, protein processing, ribosome, and phagosome pathways, suggesting multiple functions of circSP100 during HCMV infection.

Comprehensive structural glycomic characterization of the glycocalyxes of cells and tissues

The glycocalyx comprises glycosylated proteins and lipids and fcorms the outermost layer of cells. It is involved in fundamental inter- and intracellular processes, including non-self-cell and self-cell recognition, cell signaling, cellular structure maintenance, and immune protection. Characterization of the glycocalyx is thus essential to understanding cell physiology and elucidating its role in promoting health and disease. This protocol describes how to comprehensively characterize the glycocalyx N-glycans and O-glycans of glycoproteins, as well as intact glycolipids in parallel, using the same enriched membrane fraction. Profiling of the glycans and the glycolipids is performed using nanoflow liquid chromatography-mass spectrometry (nanoLC-MS). Sample preparation, quantitative LC-tandem MS (LC-MS/MS) analysis, and data processing methods are provided. In addition, we discuss glycoproteomic analysis that yields the site-specific glycosylation of membrane proteins. To reduce the amount of sample needed, N-glycan, O-glycan, and glycolipid analyses are performed on the same enriched fraction, whereas glycoproteomic analysis is performed on a separate enriched fraction. The sample preparation process takes 2-3 d, whereas the time spent on instrumental and data analyses could vary from 1 to 5 d for different sample sizes. This workflow is applicable to both cell and tissue samples. Systematic changes in the glycocalyx associated with specific glycoforms and glycoconjugates can be monitored with quantitation using this protocol. The ability to quantitate individual glycoforms and glycoconjugates will find utility in a broad range of fundamental and applied clinical studies, including glycan-based biomarker discovery and therapeutics.

Integrative analysis of outer membrane vesicles proteomics and whole-cell transcriptome analysis of eravacycline induced Acinetobacter baumannii strains

BACKGROUND

Acinetobacter baumannii is a multidrug-resistant (MDR) hazardous bacterium with very high antimicrobial resistance profiles. Outer membrane vesicles (OMVs) help directly and/or indirectly towards antibiotic resistance in these organisms. The present study aims to look on the proteomic profile of OMV as well as on the bacterial transcriptome upon exposure and induction with eravacycline, a new synthetic fluorocycline. RNA sequencing analysis of whole-cell and LC-MS/MS proteomic profiling of OMV proteome abundance were done to identify the differential expression among the eravacycline-induced A. baumannii ATCC 19606 and A. baumannii clinical strain JU0126.

RESULTS

The differentially expressed genes from the RNA sequencing were analysed using R package and bioinformatics software and tools. Genes encoding drug efflux and membrane transport were upregulated among the DEGs from both ATCC 19606 and JU0126 strains. As evident with the induction of eravacycline resistance, ribosomal proteins were upregulated in both the strains in the transcriptome profiles and also resistance pumps, such as MFS, RND, MATE and ABC transporters. High expression of stress and survival proteins were predominant in the OMVs proteome with ribosomal proteins, chaperons, OMPs OmpA, Omp38 upregulated in ATCC 19606 strain and ribosomal proteins, toluene tolerance protein, siderophore receptor and peptidases in the JU0126 strain. The induction of resistance to eravacycline was supported by the presence of upregulation of ribosomal proteins, resistance-conferring factors and stress proteins in both the strains of A. baumannii ATCC 19606 and JU0126, with the whole-cell gene transcriptome towards both resistance and stress genes while the OMVs proteome enriched more with survival proteins.

CONCLUSION

The induction of resistance to eravacycline in the strains were evident with the increased expression of ribosomal and transcription related genes/proteins. Apart from this resistance-conferring efflux pumps, outer membrane proteins and stress-related proteins were also an essential part of the upregulated DEGs. However, the expression profiles of OMVs proteome in the study was independent with respect to the whole-cell RNA expression profiles with low to no correlation. This indicates the possible role of OMVs to be more of back-up additional protection to the existing bacterial cell defence during the antibacterial stress.

Loss of function mutation of the Rapid Alkalinization Factor (RALF1)-like peptide in the dandelion Taraxacum koksaghyz entails a high-biomass taproot phenotype

The Russian dandelion (Taraxacum koksaghyz) is a promising source of inulin and natural rubber because large amounts of both feedstocks can be extracted from its roots. However, the domestication of T. koksaghyz requires the development of stable agronomic traits such as higher yields of inulin and natural rubber, a higher root biomass, and an agronomically preferable root morphology which is more suitable for cultivation and harvesting. Arabidopsis thaliana Rapid Alkalinisation Factor 1 (RALF1) has been shown to suppress root growth. We identified the T. koksaghyz orthologue TkRALF-like 1 and knocked out the corresponding gene (TkRALFL1) using the CRISPR/Cas9 system to determine its impact on root morphology, biomass, and inulin and natural rubber yields. The TkRALFL1 knockout lines more frequently developed a taproot phenotype which is easier to cultivate and harvest, as well as a higher root biomass and greater yields of both inulin and natural rubber. The TkRALFL1 gene could therefore be suitable as a genetic marker to support the breeding of profitable new dandelion varieties with improved agronomic traits. To our knowledge, this is the first study addressing the root system of T. koksaghyz to enhance the agronomic performance.

Quality control in mass spectrometry-based proteomics

Mass spectrometry is a highly complex analytical technique and mass spectrometry-based proteomics experiments can be subject to a large variability, which forms an obstacle to obtaining accurate and reproducible results. Therefore, a comprehensive and systematic approach to quality control is an essential requirement to inspire confidence in the generated results. A typical mass spectrometry experiment consists of multiple different phases including the sample preparation, liquid chromatography, mass spectrometry, and bioinformatics stages. We review potential sources of variability that can impact the results of a mass spectrometry experiment occurring in all of these steps, and we discuss how to monitor and remedy the negative influences on the experimental results. Furthermore, we describe how specialized quality control samples of varying sample complexity can be incorporated into the experimental workflow and how they can be used to rigorously assess detailed aspects of the instrument performance.

Systematic approach for dissecting the molecular mechanisms of transcriptional regulation in bacteria

Organisms must constantly make regulatory decisions in response to a change in cellular state or environment. However, while the catalog of genomes expands rapidly, we remain ignorant about how the genes in these genomes are regulated. Here, we show how a massively parallel reporter assay, Sort-Seq, and information-theoretic modeling can be used to identify regulatory sequences. We then use chromatography and mass spectrometry to identify the regulatory proteins that bind these sequences. The approach results in quantitative base pair-resolution models of promoter mechanism and was shown in both well-characterized and unannotated promoters in Escherichia coli. Given the generality of the approach, it opens up the possibility of quantitatively dissecting the mechanisms of promoter function in a wide range of bacteria.

Gene regulation is one of the most ubiquitous processes in biology. However, while the catalog of bacterial genomes continues to expand rapidly, we remain ignorant about how almost all of the genes in these genomes are regulated. At present, characterizing the molecular mechanisms by which individual regulatory sequences operate requires focused efforts using low-throughput methods. Here, we take a first step toward multipromoter dissection and show how a combination of massively parallel reporter assays, mass spectrometry, and information-theoretic modeling can be used to dissect multiple bacterial promoters in a systematic way. We show this approach on both well-studied and previously uncharacterized promoters in the enteric bacterium Escherichia coli. In all cases, we recover nucleotide-resolution models of promoter mechanism. For some promoters, including previously unannotated ones, the approach allowed us to further extract quantitative biophysical models describing input–output relationships. Given the generality of the approach presented here, it opens up the possibility of quantitatively dissecting the mechanisms of promoter function in E. coli and a wide range of other bacteria.

Optimization of mass spectrometric parameters improve the identification performance of capillary zone electrophoresis for single-shot bottom-up proteomics analysis

The effects of MS1 injection time, MS2 injection time, dynamic exclusion time, intensity threshold, and isolation width were investigated on the numbers of peptide and protein identifications for single-shot bottom-up proteomics analysis using CZE-MS/MS analysis of a Xenopus laevis tryptic digest. An electrokinetically pumped nanospray interface was used to couple a linear-polyacrylamide coated capillary to a Q Exactive HF mass spectrometer. A sensitive method that used a 1.4 Th isolation width, 60,000 MS2 resolution, 110 ms MS2 injection time, and a top 7 fragmentation produced the largest number of identifications when the CZE loading amount was less than 100 ng. A programmable autogain control method (pAGC) that used a 1.4 Th isolation width, 15,000 MS2 resolution, 110 ms MS2 injection time, and top 10 fragmentation produced the largest number of identifications for CZE loading amounts greater than 100 ng; 7218 unique peptides and 1653 protein groups were identified from 200 ng by using the pAGC method. The effect of mass spectrometer conditions on the performance of UPLC-MS/MS was also investigated. A fast method that used a 1.4 Th isolation width, 30,000 MS2 resolution, 45 ms MS2 injection time, and top 12 fragmentation produced the largest number of identifications for 200 ng UPLC loading amount (6025 unique peptides and 1501 protein groups). This is the first report where the identification number for CZE surpasses that of the UPLC at the 200 ng loading level. However, more peptides (11476) and protein groups (2378) were identified by using UPLC-MS/MS when the sample loading amount was increased to 2 μg with the fast method. To exploit the fast scan speed of the Q-Exactive HF mass spectrometer, higher sample loading amounts are required for single-shot bottom-up proteomics analysis using CZE-MS/MS.

Selective Proteomic Analysis of Antibiotic-Tolerant Cellular Subpopulations in Pseudomonas aeruginosa Biofilms

Biofilm infections exhibit high tolerance against antibiotic treatment. The study of biofilms is complicated by phenotypic heterogeneity; biofilm subpopulations differ in their metabolic activities and their responses to antibiotics. Here, we describe the use of the bio-orthogonal noncanonical amino acid tagging (BONCAT) method to enable selective proteomic analysis of a Pseudomonas aeruginosa biofilm subpopulation. Through controlled expression of a mutant methionyl-tRNA synthetase, we targeted BONCAT labeling to cells in the regions of biofilm microcolonies that showed increased tolerance to antibiotics. We enriched and identified proteins synthesized by cells in these regions. Compared to the entire biofilm proteome, the labeled subpopulation was characterized by a lower abundance of ribosomal proteins and was enriched in proteins of unknown function. We performed a pulse-labeling experiment to determine the dynamic proteomic response of the tolerant subpopulation to supra-MIC treatment with the fluoroquinolone antibiotic ciprofloxacin. The adaptive response included the upregulation of proteins required for sensing and repairing DNA damage and substantial changes in the expression of enzymes involved in central carbon metabolism. We differentiated the immediate proteomic response, characterized by an increase in flagellar motility, from the long-term adaptive strategy, which included the upregulation of purine synthesis. This targeted, selective analysis of a bacterial subpopulation demonstrates how the study of proteome dynamics can enhance our understanding of biofilm heterogeneity and antibiotic tolerance.

Bacterial growth is frequently characterized by behavioral heterogeneity at the single-cell level. Heterogeneity is especially evident in the physiology of biofilms, in which distinct cellular subpopulations can respond differently to stresses, including subpopulations of pathogenic biofilms that are more tolerant to antibiotics. Global proteomic analysis affords insights into cellular physiology but cannot identify proteins expressed in a particular subpopulation of interest. Here, we report a chemical biology method to selectively label, enrich, and identify proteins expressed by cells within distinct regions of biofilm microcolonies. We used this approach to study changes in protein synthesis by the subpopulation of antibiotic-tolerant cells throughout a course of treatment. We found substantial differences between the initial response and the long-term adaptive strategy that biofilm cells use to cope with antibiotic stress. The method we describe is readily applicable to investigations of bacterial heterogeneity in diverse contexts.

Selective Proteomic Analysis of Antibiotic-Tolerant Cellular Subpopulations in Pseudomonas aeruginosa Biofilms

Biofilm infections exhibit high tolerance against antibiotic treatment. The study of biofilms is complicated by phenotypic heterogeneity; biofilm subpopulations differ in their metabolic activities and their responses to antibiotics. Here, we describe the use of the bio-orthogonal noncanonical amino acid tagging (BONCAT) method to enable selective proteomic analysis of a Pseudomonas aeruginosa biofilm subpopulation. Through controlled expression of a mutant methionyl-tRNA synthetase, we targeted BONCAT labeling to cells in the regions of biofilm microcolonies that showed increased tolerance to antibiotics. We enriched and identified proteins synthesized by cells in these regions. Compared to the entire biofilm proteome, the labeled subpopulation was characterized by a lower abundance of ribosomal proteins and was enriched in proteins of unknown function. We performed a pulse-labeling experiment to determine the dynamic proteomic response of the tolerant subpopulation to supra-MIC treatment with the fluoroquinolone antibiotic ciprofloxacin. The adaptive response included the upregulation of proteins required for sensing and repairing DNA damage and substantial changes in the expression of enzymes involved in central carbon metabolism. We differentiated the immediate proteomic response, characterized by an increase in flagellar motility, from the long-term adaptive strategy, which included the upregulation of purine synthesis. This targeted, selective analysis of a bacterial subpopulation demonstrates how the study of proteome dynamics can enhance our understanding of biofilm heterogeneity and antibiotic tolerance.IMPORTANCE Bacterial growth is frequently characterized by behavioral heterogeneity at the single-cell level. Heterogeneity is especially evident in the physiology of biofilms, in which distinct cellular subpopulations can respond differently to stresses, including subpopulations of pathogenic biofilms that are more tolerant to antibiotics. Global proteomic analysis affords insights into cellular physiology but cannot identify proteins expressed in a particular subpopulation of interest. Here, we report a chemical biology method to selectively label, enrich, and identify proteins expressed by cells within distinct regions of biofilm microcolonies. We used this approach to study changes in protein synthesis by the subpopulation of antibiotic-tolerant cells throughout a course of treatment. We found substantial differences between the initial response and the long-term adaptive strategy that biofilm cells use to cope with antibiotic stress. The method we describe is readily applicable to investigations of bacterial heterogeneity in diverse contexts.

Resolution Ladder for High-Resolution Mass Spectrometry

High-resolution mass spectrometry has become a key technology in life sciences. Since it is often unfeasible to find pairs of analytes with an appropriate mass difference to actually quantify the resolution experimentally, resolution is usually calculated from the shape of a single mass peak. In this study we show that the commonly employed strategy yields a poor measure of true resolution since it does not account for interactions that take place between ions of very similar mass and might be further distorted by signal processing effects. We present a straightforward and easily adaptable method to create a ladder of mass pairs to experimentally quantify actual mass resolution over a wide m/z range, compare the experimental resolution to the single peak based calculated resolution, and demonstrate the applicability of mass resolution ladders to study interactions of similar ions in various types of widely used mass spectrometers.

Optimization and Modeling of Quadrupole Orbitrap Parameters for Sensitive Analysis toward Single-Cell Proteomics

Single-cell proteomics represents a field of extremely sensitive proteomic analysis, owing to the minute amount of yet complex proteins in a single cell. Without amplification potential as of nucleic acids, single-cell mass spectrometry (MS) analysis demands special instrumentation running with optimized parameters to maximize the sensitivity and throughput for comprehensive proteomic discovery. To facilitate such analysis, we here investigated two factors critical to peptide sequencing and protein detection in shotgun proteomics, i.e. precursor ion isolation window (IW) and maximum precursor ion injection time (ITmax), on an ultrahigh-field quadrupole Orbitrap (Q-Exactive HF). Counterintuitive to the frequently used proteomic parameters for bulk samples (>100 ng), our experimental data and subsequent modeling suggested a universally optimal IW of 4.0 Th for sample quantity ranging from 100 ng to 1 ng, and a sample-quantity dependent ITmax of more than 250 ms for 1-ng samples. Compared with the benchmark condition of IW = 2.0 Th and ITmax = 50 ms, our optimization generated up to 300% increase to the detected protein groups for 1-ng samples. The additionally identified proteins allowed deeper penetration of proteome for better revealing crucial cellular functions such as signaling and cell adhesion. We hope this effort can prompt single-cell and trace proteomic analysis and enable a rational selection of MS parameters.

Thermal Shock Induces Host Proteostasis Disruption and Endoplasmic Reticulum Stress in the Model Symbiotic Cnidarian Aiptasia

Coral bleaching has devastating effects on coral survival and reef ecosystem function, but many of the fundamental cellular effects of thermal stress on cnidarian physiology are unclear. We used label-free liquid chromatography-tandem mass spectrometry to compare the effects of rapidly (33.5 °C, 24 h) and gradually (30 and 33.5 °C, 12 days) elevated temperatures on the proteome of the model symbiotic anemone Aiptasia. We identified 2133 proteins in Aiptasia, 136 of which were differentially abundant between treatments. Thermal shock, but not acclimation, resulted in significant abundance changes in 104 proteins, including those involved in protein folding and synthesis, redox homeostasis, and central metabolism. Nineteen abundant structural proteins showed particularly reduced abundance, demonstrating proteostasis disruption and potential protein synthesis inhibition. Heat shock induced antioxidant mechanisms and proteins involved in stabilizing nascent proteins, preventing protein aggregation and degrading damaged proteins, which is indicative of endoplasmic reticulum stress. Host proteostasis disruption occurred before either bleaching or symbiont photoinhibition was detected, suggesting host-derived reactive oxygen species production as the proximate cause of thermal damage. The pronounced abundance changes in endoplasmic reticulum proteins associated with proteostasis and protein turnover indicate that these processes are essential in the cellular response of symbiotic cnidarians to severe thermal stress.

Comparative transcriptome and proteome analysis reveals a global impact of the nitrogen regulators AreA and AreB on secondary metabolism in Fusarium fujikuroi

The biosynthesis of multiple secondary metabolites in the phytopathogenic ascomycete Fusarium fujikuroi is strongly affected by nitrogen availability. Here, we present the first genome-wide transcriptome and proteome analysis that compared the wild type and deletion mutants of the two major nitrogen regulators AreA and AreB. We show that AreB acts not simply as an antagonist of AreA counteracting the expression of AreA target genes as suggested based on the yeast model. Both GATA transcription factors affect a large and diverse set of common as well as specific target genes and proteins, acting as activators and repressors. We demonstrate that AreA and AreB are not only involved in fungal nitrogen metabolism, but also in the control of several complex cellular processes like carbon metabolism, transport and secondary metabolism. We show that both GATA transcription factors can be considered as master regulators of secondary metabolism as they affect the expression of more than half of the 47 putative secondary metabolite clusters identified in the genome of F. fujikuroi. While AreA acts as a positive regulator of many clusters under nitrogen-limiting conditions, AreB is able to activate and repress gene clusters (e.g. bikaverin) under nitrogen limitation and sufficiency. In addition, ChIP analyses revealed that loss of AreA or AreB causes histone modifications at some of the regulated gene clusters.

The Pyruvate and α-Ketoglutarate Dehydrogenase Complexes of Pseudomonas aeruginosa Catalyze Pyocyanin and Phenazine-1-carboxylic Acid Reduction via the Subunit Dihydrolipoamide Dehydrogenase

Phenazines are a class of redox-active molecules produced by diverse bacteria and archaea. Many of the biological functions of phenazines, such as mediating signaling, iron acquisition, and redox homeostasis, derive from their redox activity. Although prior studies have focused on extracellular phenazine oxidation by oxygen and iron, here we report a search for reductants and catalysts of intracellular phenazine reduction in Pseudomonas aeruginosa Enzymatic assays in cell-free lysate, together with crude fractionation and chemical inhibition, indicate that P. aeruginosa contains multiple enzymes that catalyze the reduction of the endogenous phenazines pyocyanin and phenazine-1-carboxylic acid in both cytosolic and membrane fractions. We used chemical inhibitors to target general enzyme classes and found that an inhibitor of flavoproteins and heme-containing proteins, diphenyleneiodonium, effectively inhibited phenazine reduction in vitro, suggesting that most phenazine reduction derives from these enzymes. Using natively purified proteins, we demonstrate that the pyruvate and α-ketoglutarate dehydrogenase complexes directly catalyze phenazine reduction with pyruvate or α-ketoglutarate as electron donors. Both complexes transfer electrons to phenazines through the common subunit dihydrolipoamide dehydrogenase, a flavoprotein encoded by the gene lpdG Although we were unable to co-crystallize LpdG with an endogenous phenazine, we report its X-ray crystal structure in the apo-form (refined to 1.35 Å), bound to NAD⁺ (1.45 Å), and bound to NADH (1.79 Å). In contrast to the notion that phenazines support intracellular redox homeostasis by oxidizing NADH, our work suggests that phenazines may substitute for NAD⁺ in LpdG and other enzymes, achieving the same end by a different mechanism.

Improved Quantitative Plant Proteomics via the Combination of Targeted and Untargeted Data Acquisition

Quantitative proteomics strategies - which are playing important roles in the expanding field of plant molecular systems biology - are traditionally designated as either hypothesis driven or non-hypothesis driven. Many of these strategies aim to select individual peptide ions for tandem mass spectrometry (MS/MS), and to do this mixed hypothesis driven and non-hypothesis driven approaches are theoretically simple to implement. In-depth investigations into the efficacies of such approaches have, however, yet to be described. In this study, using combined samples of unlabeled and metabolically ¹⁵N-labeled Arabidopsis thaliana proteins, we investigate the mixed use of targeted data acquisition (TDA) and data dependent acquisition (DDA) - referred to as TDA/DDA - to facilitate both hypothesis driven and non-hypothesis driven quantitative data collection in individual LC-MS/MS experiments. To investigate TDA/DDA for hypothesis driven data collection, 7 miRNA target proteins of differing size and abundance were targeted using inclusion lists comprised of 1558 m/z values, using 3 different TDA/DDA experimental designs. In samples in which targeted peptide ions were of particularly low abundance (i.e., predominantly only marginally above mass analyser detection limits), TDA/DDA produced statistically significant increases in the number of targeted peptides identified (230 ± 8 versus 80 ± 3 for DDA; p = 1.1 × 10^-3) and quantified (35 ± 3 versus 21 ± 2 for DDA; p = 0.038) per experiment relative to the use of DDA only. These expected improvements in hypothesis driven data collection were observed alongside unexpected improvements in non-hypothesis driven data collection. Untargeted peptide ions with m/z values matching those in inclusion lists were repeatedly identified and quantified across technical replicate TDA/DDA experiments, resulting in significant increases in the percentages of proteins repeatedly quantified in TDA/DDA experiments only relative to DDA experiments only (33.0 ± 2.6% versus 8.0 ± 2.7%, respectively; p = 0.011). These results were observed together with uncompromised broad-scale MS/MS data collection in TDA/DDA experiments relative to DDA experiments. Using our observations we provide guidelines for TDA/DDA method design for quantitative plant proteomics studies, and suggest that TDA/DDA is a broadly underutilized proteomics data acquisition strategy.

Deep Phosphotyrosine Proteomics by Optimization of Phosphotyrosine Enrichment and MS/MS Parameters

Phosphorylation is a major post-translational modification that regulates protein function, with phosphotyrosine (pY) modifications being implicated in oncogenesis. However, global profiling of pY statuses without treatment with a tyrosine phosphatase inhibitor such as pervanadate is still challenging due to the low occupancy of pY sites. In this study, we greatly improved the identification of pY sites by liquid chromatography-tandem mass spectrometry (LC-MS/MS) by optimization of both the pY-immunoprecipitation (pY-IP) protocol and the LC-MS/MS parameters. Our highly sensitive method reproducibly identified more than 1000 pY sites from 8 mg of protein lysate without the need for tyrosine phosphatase inhibitor treatment. Furthermore, >30% of the identified pY sites were not assigned in the PhosphositePlus database. We further applied our method to the comparison of pY status between PC3 cells with and without treatment using the epidermal growth factor receptor (EGFR) inhibitor Erlotinib. Under Erlotinib treatment, we observed not only a decrease in well-known modes of EGFR downstream signaling but also modulations of kinases that are not relevant to the EGFR cascade, such as PTK6 and MAPK13. Our newly developed method for pY proteomics has the potential to reveal unknown pY signaling modes and to identify novel kinase anticancer targets.

Shotgun Proteomics of Tomato Fruits: Evaluation, Optimization and Validation of Sample Preparation Methods and Mass Spectrometric Parameters

An optimized protocol was developed for shotgun proteomics of tomato fruit, which is a recalcitrant tissue due to a high percentage of sugars and secondary metabolites. A number of protein extraction and fractionation techniques were examined for optimal protein extraction from tomato fruits followed by peptide separation on nanoLCMS. Of all evaluated extraction agents, buffer saturated phenol was the most efficient. In-gel digestion [SDS-PAGE followed by separation on LCMS (GeLCMS)] of phenol-extracted sample yielded a maximal number of proteins. For in-solution digested samples, fractionation by strong anion exchange chromatography (SAX) also gave similar high proteome coverage. For shotgun proteomic profiling, optimization of mass spectrometry parameters such as automatic gain control targets (5E+05 for MS, 1E+04 for MS/MS); ion injection times (500 ms for MS, 100 ms for MS/MS); resolution of 30,000; signal threshold of 500; top N-value of 20 and fragmentation by collision-induced dissociation yielded the highest number of proteins. Validation of the above protocol in two tomato cultivars demonstrated its reproducibility, consistency, and robustness with a CV of < 10%. The protocol facilitated the detection of five-fold higher number of proteins compared to published reports in tomato fruits. The protocol outlined would be useful for high-throughput proteome analysis from tomato fruits and can be applied to other recalcitrant tissues.

SutA is a bacterial transcription factor expressed during slow growth in Pseudomonas aeruginosa

Microbial quiescence and slow growth are ubiquitous physiological states, but their study is complicated by low levels of metabolic activity. To address this issue, we used a time-selective proteome-labeling method [bioorthogonal noncanonical amino acid tagging (BONCAT)] to identify proteins synthesized preferentially, but at extremely low rates, under anaerobic survival conditions by the opportunistic pathogen Pseudomonas aeruginosa. One of these proteins is a transcriptional regulator that has no homology to any characterized protein domains and is posttranscriptionally up-regulated during survival and slow growth. This small, acidic protein associates with RNA polymerase, and chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing suggests that the protein associates with genomic DNA through this interaction. ChIP signal is found both in promoter regions and throughout the coding sequences of many genes and is particularly enriched at ribosomal protein genes and in the promoter regions of rRNA genes. Deletion of the gene encoding this protein affects expression of these and many other genes and impacts biofilm formation, secondary metabolite production, and fitness in fluctuating conditions. On the basis of these observations, we have designated the protein SutA (survival under transitions A).

PYCR1 and PYCR2 Interact and Collaborate with RRM2B to Protect Cells from Overt Oxidative Stress

Ribonucleotide reductase small subunit B (RRM2B) is a stress response protein that protects normal human fibroblasts from oxidative stress. However, the underlying mechanism that governs this function is not entirely understood. To identify factors that interact with RRM2B and mediate anti-oxidation function, large-scale purification of human Flag-tagged RRM2B complexes was performed. Pyrroline-5-carboxylate reductase 1 and 2 (PYCR1, PYCR2) were identified by mass spectrometry analysis as components of RRM2B complexes. Silencing of both PYCR1 and PYCR2 by expressing short hairpin RNAs induced defects in cell proliferation, partial fragmentation of the mitochondrial network, and hypersensitivity to oxidative stress in hTERT-immortalized human foreskin fibroblasts (HFF-hTERT). Moderate overexpression of RRM2B, comparable to stress-induced level, protected cells from oxidative stress. Silencing of both PYCR1 and PYCR2 completely abolished anti-oxidation activity of RRM2B, demonstrating a functional collaboration of these metabolic enzymes in response to oxidative stress.

A Trichomonas vaginalis Rhomboid Protease and Its Substrate Modulate Parasite Attachment and Cytolysis of Host Cells

Trichomonas vaginalis is an extracellular eukaryotic parasite that causes the most common, non-viral sexually transmitted infection worldwide. Although disease burden is high, molecular mechanisms underlying T. vaginalis pathogenesis are poorly understood. Here, we identify a family of putative T. vaginalis rhomboid proteases and demonstrate catalytic activity for two, TvROM1 and TvROM3, using a heterologous cell cleavage assay. The two T. vaginalis intramembrane serine proteases display different subcellular localization and substrate specificities. TvROM1 is a cell surface membrane protein and cleaves atypical model rhomboid protease substrates, whereas TvROM3 appears to localize to the Golgi apparatus and recognizes a typical model substrate. To identify TvROM substrates, we interrogated the T. vaginalis surface proteome using both quantitative proteomic and bioinformatic approaches. Of the nine candidates identified, TVAG_166850 and TVAG_280090 were shown to be cleaved by TvROM1. Comparison of amino acid residues surrounding the predicted cleavage sites of TvROM1 substrates revealed a preference for small amino acids in the predicted transmembrane domain. Over-expression of TvROM1 increased attachment to and cytolysis of host ectocervical cells. Similarly, mutations that block the cleavage of a TvROM1 substrate lead to its accumulation on the cell surface and increased parasite adherence to host cells. Together, these data indicate a role for TvROM1 and its substrate(s) in modulating attachment to and lysis of host cells, which are key processes in T. vaginalis pathogenesis.

Trichomonas vaginalis, a common pathogen with a worldwide distribution, causes a sexually transmitted infection and exacerbates other diseases. Estimated to infect over a million people annually in the United States alone, the Center for Disease Control and Prevention categorized trichomoniasis as one of five neglected parasitic diseases in the US in 2014. Only one class of drug is available to treat T. vaginalis infection, making discovery of parasite factors contributing to host colonization critical for the development of new therapeutics. Here we report the first characterization of T. vaginalis intramembrane rhomboid proteases. One protease, TvROM1, is shown to increase the parasite’s association with and destruction of host cells. We further identified two TvROM1 substrates, one of which we demonstrate is involved in modulating host: parasite interactions. This study highlights the involvement of rhomboid proteases in T. vaginalis pathogenic processes, and provides further support for targeting parasite surface proteases for therapeutic intervention.

Time-resolved proteomic analysis of quorum sensing in Vibrio harveyi

Bacteria use a process of chemical communication called quorum sensing to assess their population density and to change their behavior in response to fluctuations in the cell number and species composition of the community. In this work, we identified the quorum-sensing-regulated proteome in the model organism Vibrio harveyi by bio-orthogonal non-canonical amino acid tagging (BONCAT). BONCAT enables measurement of proteome dynamics with temporal resolution on the order of minutes. We deployed BONCAT to characterize the time-dependent transition of V. harveyi from individual- to group-behaviors. We identified 176 quorum-sensing-regulated proteins at early, intermediate, and late stages of the transition, and we mapped the temporal changes in quorum-sensing proteins controlled by both transcriptional and post-transcriptional mechanisms. Analysis of the identified proteins revealed 86 known and 90 new quorum-sensing-regulated proteins with diverse functions, including transcription factors, chemotaxis proteins, transport proteins, and proteins involved in iron homeostasis.

Differences in the Elemental Isotope Definition May Lead to Errors in Modern Mass-Spectrometry-Based Proteomics

The elemental isotope definition used to calculate the theoretical masses and isotope distribution of (bio)molecules is considered to be a fixed, universal standard in mass-spectrometry-based proteomics. However, this is an incorrect assumption. In view of the ongoing advances in mass spectrometry technology, and in particular the ever-increasing mass precision, the elemental isotope definition and its variations should be taken into account. We illustrate the effect of the elemental isotope uncertainty on the theoretical and experimental masses with theoretical calculations and examples.

Performance metrics for evaluating system suitability in liquid chromatography--Mass spectrometry peptide mass mapping of protein therapeutics and monoclonal antibodies

The use of liquid chromatography--mass spectrometry (LC-MS) for the characterization of proteins can provide a plethora of information related to their structure, including amino acid sequence determination and analysis of posttranslational modifications. The variety of LC-MS based applications has led to the use of LC-MS characterization of therapeutic proteins and monoclonal antibodies as an integral part of the regulatory approval process. However, the improper use of an LC-MS system, related to intrinsic instrument limitations, improper tuning parameters, or poorly optimized methods may result in the production of low quality data. Improper system performance may arise from subtle changes in operating conditions that limit the ability to detect low abundance species. To address this issue, we systematically evaluated LC-MS/MS operating parameters to identify a set of metrics that can be used in a workflow to determine if a system is suitable for its intended purpose. Development of this workflow utilized a bovine serum albumin (BSA) digest standard spiked with synthetic peptides present at 0.1% to 100% of the BSA digest peptide concentration to simulate the detection of low abundance species using a traditional bottom-up workflow and data-dependent MS(2) acquisition. BSA sequence coverage, a commonly used indicator for instrument performance did not effectively identify settings that led to limited dynamic range or poorer absolute mass accuracy on 2 separate LC-MS systems. Additional metrics focusing on the detection limit and sensitivity for peptide identification were determined to be necessary to establish system suitability for protein therapeutic characterization by LC-MS.

Renal and Hematological Effects of CLCF-1, a B-Cell-Stimulating Cytokine of the IL-6 Family

CLCF-1 is a cytokine known for B-cell stimulation and for neurotrophic properties. We have identified CLCF-1 as a potential injurious factor in the human renal disease focal segmental glomerulosclerosis (FSGS). We investigated its effects on renal cells and renal function in in vitro and in vivo studies. Methods include measurement of the effect of CLCF-1 on phosphorylation of target molecules of the JAK/STAT pathway, on cytoskeleton and cell morphology in cultured podocytes, on albumin permeability of isolated rat glomeruli, and on tissue phosphorylation and urine albumin after acute or chronic CLCF-1 injection. In addition, cell sorting was performed to determine the presence of cells expressing CLCF-1 in spleen and bone marrow of normal mice and the effect of CLCF-1 infusion on splenic B-cell populations. CLCF-1 increased phosphorylation of STAT3 in multiple cell types, activated podocytes leading to formation of lamellipodia and decrease in basal stress fibers, increased glomerular albumin permeability, and increased STAT3 phosphorylation of peripheral blood cells and renal cortex. CLCF-1 increased urine albumin/creatinine ratio in mice and increased B-cell expression of IgG in mouse spleen. We conclude that CLCF-1 has potentially important systemic effects, alters podocyte function, and may contribute to renal dysfunction and albuminuria.

The Xist lncRNA interacts directly with SHARP to silence transcription through HDAC3

Many long non-coding RNAs (lncRNAs) affect gene expression, but the mechanisms by which they act are still largely unknown. One of the best-studied lncRNAs is Xist, which is required for transcriptional silencing of one X chromosome during development in female mammals. Despite extensive efforts to define the mechanism of Xist-mediated transcriptional silencing, we still do not know any proteins required for this role. The main challenge is that there are currently no methods to comprehensively define the proteins that directly interact with a lncRNA in the cell. Here we develop a method to purify a lncRNA from cells and identify proteins interacting with it directly using quantitative mass spectrometry. We identify ten proteins that specifically associate with Xist, three of these proteins--SHARP, SAF-A and LBR--are required for Xist-mediated transcriptional silencing. We show that SHARP, which interacts with the SMRT co-repressor that activates HDAC3, is not only essential for silencing, but is also required for the exclusion of RNA polymerase II (Pol II) from the inactive X. Both SMRT and HDAC3 are also required for silencing and Pol II exclusion. In addition to silencing transcription, SHARP and HDAC3 are required for Xist-mediated recruitment of the polycomb repressive complex 2 (PRC2) across the X chromosome. Our results suggest that Xist silences transcription by directly interacting with SHARP, recruiting SMRT, activating HDAC3, and deacetylating histones to exclude Pol II across the X chromosome.

Phosphorylation of synaptic GTPase-activating protein (synGAP) by Ca2+/calmodulin-dependent protein kinase II (CaMKII) and cyclin-dependent kinase 5 (CDK5) alters the ratio of its GAP activity toward Ras and Rap GTPases

synGAP is a neuron-specific Ras and Rap GTPase-activating protein (GAP) found in high concentrations in the postsynaptic density (PSD) fraction from the mammalian forebrain. We have previously shown that, in situ in the PSD fraction or in recombinant form in Sf9 cell membranes, synGAP is phosphorylated by Ca(2+)/calmodulin-dependent protein kinase II (CaMKII), another prominent component of the PSD. Here, we show that recombinant synGAP (r-synGAP), lacking 102 residues at the N terminus, can be purified in soluble form and is phosphorylated by cyclin-dependent kinase 5 (CDK5) as well as by CaMKII. Phosphorylation of r-synGAP by CaMKII increases its HRas GAP activity by 25% and its Rap1 GAP activity by 76%. Conversely, phosphorylation by CDK5 increases r-synGAP's HRas GAP activity by 98% and its Rap1 GAP activity by 20%. Thus, phosphorylation by both kinases increases synGAP activity; CaMKII shifts the relative GAP activity toward inactivation of Rap1, and CDK5 shifts the relative activity toward inactivation of HRas. GAP activity toward Rap2 is not altered by phosphorylation by either kinase. CDK5 phosphorylates synGAP primarily at two sites, Ser-773 and Ser-802. Phosphorylation at Ser-773 inhibits r-synGAP activity, and phosphorylation at Ser-802 increases it. However, the net effect of concurrent phosphorylation of both sites, Ser-773 and Ser-802, is an increase in GAP activity. synGAP is phosphorylated at Ser-773 and Ser-802 in the PSD fraction, and its phosphorylation by CDK5 and CaMKII is differentially regulated by activation of NMDA-type glutamate receptors in cultured neurons.

Identification and characterization of HTLV-1 HBZ post-translational modifications

Human T-cell leukemia virus type-1 (HTLV-1) is estimated to infect 15–25 million people worldwide, with several areas including southern Japan and the Caribbean basin being endemic. The virus is the etiological agent of debilitating and fatal diseases, for which there is currently no long-term cure. In the majority of cases of leukemia caused by HTLV-1, only a single viral gene, hbz, and its cognate protein, HBZ, are expressed and their importance is increasingly being recognized in the development of HTLV-1-associated disease. We hypothesized that HBZ, like other HTLV-1 proteins, has properties and functions regulated by post-translational modifications (PTMs) that affect specific signaling pathways important for disease development. To date, PTM of HBZ has not been described. We used an affinity-tagged protein and mass spectrometry method to identify seven modifications of HBZ for the first time. We examined how these PTMs affected the ability of HBZ to modulate several pathways, as measured using luciferase reporter assays. Herein, we report that none of the identified PTMs affected HBZ stability or its regulation of tested pathways.

Quantitative, time-resolved proteomic analysis by combining bioorthogonal noncanonical amino acid tagging and pulsed stable isotope labeling by amino acids in cell culture

An approach to proteomic analysis that combines bioorthogonal noncanonical amino acid tagging (BONCAT) and pulsed stable isotope labeling with amino acids in cell culture (pSILAC) provides accurate quantitative information about rates of cellular protein synthesis on time scales of minutes. The method is capable of quantifying 1400 proteins produced by HeLa cells during a 30 min interval, a time scale that is inaccessible to isotope labeling techniques alone. Potential artifacts in protein quantification can be reduced to insignificant levels by limiting the extent of noncanonical amino acid tagging. We find no evidence for artifacts in protein identification in experiments that combine the BONCAT and pSILAC methods.

The emerging field of chemo- and pharmacoproteomics

The emerging field of chemo- and pharmacoproteomics studies the mechanisms of action of bioactive molecules in a systems pharmacology context. In contrast to traditional drug discovery, pharmacoproteomics integrates the mechanism of a drug's action, its side effects including toxicity, and the discovery of new drug targets in a single approach. Thus, it determines early favorable (e.g. multiple kinase target in cancer drugs) and unfavorable (e.g. side effects) polypharmacology. Target profiling is accomplished using either active site-labeling probes or immobilized drugs. This strategy identifies direct targets and has in fact enabled even the determination of binding curves and half maximum inhibitory concentrations of these targets. In addition, the enrichment greatly reduces the complexity of the proteome to be analyzed by quantitative MS. Complementary to these approaches, global proteomics profiling studying drug treatement-induced changes in protein expression levels and/or post-translational modification status have started to become possible mostly due to significant improvements in instrumentation. Particularly, when using multidimensional separations, a considerable proteome depth of up to 10 000 proteins can be achieved with current state-of-the-art mass spectrometers and bioinformatics tools. In summary, chemo- and pharmacoproteomics has already contributed significantly to the identification of novel drug targets and their mechanisms of action(s). Aided by further technological advancements, this interdisciplinary approach will likely be used more broadly in the future.

Comprehensive proteomic profiling of outer membrane vesicles from Campylobacter jejuni

Gram-negative bacteria constitutively release outer membrane vesicles (OMVs) during cell growth that play significant roles in bacterial survival, virulence and pathogenesis. In this study, comprehensive proteomic analysis of OMVs from a human gastrointestinal pathogen Campylobacter jejuni NCTC11168 was performed using high-resolution mass spectrometry. The OMVs of C. jejuni NCTC11168 were isolated from culture supernatants then characterized using electron microscopy and dynamic light scattering revealing spherical OMVs of an average diameter of 50nm. We then identified 134 vesicular proteins using high-resolution LTQ-Orbitrap mass spectrometry. Subsequent functional analysis of the genes revealed the relationships of the vesicular proteins. Furthermore, known N-glycoproteins were identified from the list of the vesicular proteome, implying the potential role of the OMVs as a delivery means for biologically relevant bacterial glycoproteins. These results enabled us to elucidate the overall proteome profile of pathogenic bacterium C. jejuni and to speculate on the function of OMVs in bacterial infections and communication.

BIOLOGICAL SIGNIFICANCE

This work demonstrates the importance of understanding vesicular proteomes from a human pathogen Campylobacter jejuni. From the secreted outer membrane vesicles (OMVs) of C. jejuni NCTC11168, we found a variety of virulence factors and essential proteins for bacterial survival. Bioinformatics analysis of these proteins predicted functional enrichment and localization. The most highly enriched were redox enzymes, which are considered to be essential for survival in oxygen-limiting environments and are predicted to be on the twin-arginine translocation (Tat) pathway suggesting a role for this pathway in the biogenesis of OMVs. This study additionally implicates a biological role for N-linked glycoproteins in OMVs. These approaches allow for a better understanding of the physiology of this important human pathogen.

Deciphering the cryptic genome: genome-wide analyses of the rice pathogen Fusarium fujikuroi reveal complex regulation of secondary metabolism and novel metabolites

The fungus Fusarium fujikuroi causes "bakanae" disease of rice due to its ability to produce gibberellins (GAs), but it is also known for producing harmful mycotoxins. However, the genetic capacity for the whole arsenal of natural compounds and their role in the fungus' interaction with rice remained unknown. Here, we present a high-quality genome sequence of F. fujikuroi that was assembled into 12 scaffolds corresponding to the 12 chromosomes described for the fungus. We used the genome sequence along with ChIP-seq, transcriptome, proteome, and HPLC-FTMS-based metabolome analyses to identify the potential secondary metabolite biosynthetic gene clusters and to examine their regulation in response to nitrogen availability and plant signals. The results indicate that expression of most but not all gene clusters correlate with proteome and ChIP-seq data. Comparison of the F. fujikuroi genome to those of six other fusaria revealed that only a small number of gene clusters are conserved among these species, thus providing new insights into the divergence of secondary metabolism in the genus Fusarium. Noteworthy, GA biosynthetic genes are present in some related species, but GA biosynthesis is limited to F. fujikuroi, suggesting that this provides a selective advantage during infection of the preferred host plant rice. Among the genome sequences analyzed, one cluster that includes a polyketide synthase gene (PKS19) and another that includes a non-ribosomal peptide synthetase gene (NRPS31) are unique to F. fujikuroi. The metabolites derived from these clusters were identified by HPLC-FTMS-based analyses of engineered F. fujikuroi strains overexpressing cluster genes. In planta expression studies suggest a specific role for the PKS19-derived product during rice infection. Thus, our results indicate that combined comparative genomics and genome-wide experimental analyses identified novel genes and secondary metabolites that contribute to the evolutionary success of F. fujikuroi as a rice pathogen.

Perturbations to the ubiquitin conjugate proteome in yeast δubx mutants identify Ubx2 as a regulator of membrane lipid composition

Yeast Cdc48 (p97/VCP in human cells) is a hexameric AAA ATPase that is thought to use ATP hydrolysis to power the segregation of ubiquitin-conjugated proteins from tightly bound partners. Current models posit that Cdc48 is linked to its substrates through adaptor proteins, including a family of seven proteins (13 in human) that contain a Cdc48-binding UBX domain. However, few substrates for specific UBX proteins are known, and hence the generality of this hypothesis remains untested. Here, we use mass spectrometry to identify ubiquitin conjugates that accumulate in cdc48 and ubx mutants. Different ubx mutants exhibit unique patterns of conjugate accumulation that point to functional specialization of individual Ubx proteins. To validate our findings, we examined in detail the endoplasmic reticulum-bound transcription factor Spt23, which we identified as a putative Ubx2 substrate. Mutant ubx2Δ cells are deficient in both cleaving the ubiquitinated 120 kDa precursor of Spt23 to form active p90 and in localizing p90 to the nucleus, resulting in reduced expression of the target gene OLE1, which encodes fatty acid desaturase. Our findings provide a resource for future investigations on Cdc48, illustrate the utility of proteomics to identify ligands for specific ubiquitin receptor pathways, and uncover Ubx2 as a key player in the regulation of membrane lipid biosynthesis.

Evaluation and optimization of mass spectrometric settings during data-dependent acquisition mode: focus on LTQ-Orbitrap mass analyzers

Mass-spectrometry-based proteomics has evolved as the preferred method for the analysis of complex proteomes. Undoubtedly, recent advances in mass spectrometry instrumentation have greatly enhanced proteomic analysis. A popular instrument platform in proteomics research is the LTQ-Orbitrap mass analyzer. In this tutorial, we discuss the significance of evaluating and optimizing mass spectrometric settings on the LTQ-Orbitrap during CID data-dependent acquisition (DDA) mode to improve protein and peptide identification rates. We focus on those MS and MS/MS parameters that have been systematically examined and evaluated by several researchers and are commonly used during DDA. More specifically, we discuss the effect of mass resolving power, preview mode for FTMS scan, monoisotopic precursor selection, signal threshold for triggering MS/MS events, number of microscans per MS/MS scan, number of MS/MS events, automatic gain control target value (ion population) for MS and MS/MS, maximum ion injection time for MS/MS, rapid and normal scan rate, and prediction of ion injection time. We furthermore present data from the latest generation LTQ-Orbitrap system, the Orbitrap Elite, along with recommended MS and MS/MS parameters. The Orbitrap Elite outperforms the Orbitrap Classic in terms of scan speed, sensitivity, dynamic range, and resolving power and results in higher identification rates. Several of the optimized MS parameters determined on the LTQ-Orbitrap Classic and XL were easily transferable to the Orbitrap Elite, whereas others needed to be reevaluated. Finally, the Q Exactive and HCD are briefly discussed, as well as sample preparation, LC-optimization, and bioinformatics analysis. We hope this tutorial will serve as guidance for researchers new to the field of proteomics and assist in achieving optimal results.

Protein profile of rice (Oryza sativa) seeds

Seeds are the most important plant storage organ and play a central role in the life cycle of plants. Since little is known about the protein composition of rice (Oryza sativa) seeds, in this work we used proteomic methods to obtain a reference map of rice seed proteins and identify important molecules. Overall, 480 reproducible protein spots were detected by two-dimensional electrophoresis on pH 4-7 gels and 302 proteins were identified by MALDI-TOF MS and database searches. Together, these proteins represented 252 gene products and were classified into 12 functional categories, most of which were involved in metabolic pathways. Database searches combined with hydropathy plots and gene ontology analysis showed that most rice seed proteins were hydrophilic and were related to binding, catalytic, cellular or metabolic processes. These results expand our knowledge of the rice proteome and improve our understanding of the cellular biology of rice seeds.

Performance comparisons of nano-LC systems, electrospray sources and LC-MS-MS platforms

Selecting a suitable nano-liquid chromatography system (LC), ionization source and mass spectrometer for LC-tandem mass spectrometry (MS-MS) studies is complicated by numerous competing technologies. This study compares four popular nano-LC systems, four ionization sources and three MS facilities that use completely different LC-MS-MS systems. Statistically significant differences in LC performance were identified with similarly performing Proxeon, Waters and Eksigent nanoLC-Ultra systems [retention time routinely at 0.7-0.9% relative standard deviation (RSD)], and all outperformed the Eksigent nanoLC-2D (RSD ∼2%). In addition, compatibility issues were identified between the Bruker HCT ion trap mass spectrometer and both the Eksigent nanoLC-2D and the Bruker nanoelectrospray source. The electrospray source itself had an unexpected and striking effect on chromatographic reproducibility on the Bruker HCT ion trap. The New Objective nanospray source significantly outperformed the Bruker nanospray source in retention time RSD (1% RSD versus 14% RSD, respectively); and the Bruker nebulized nanospray source outperformed both of these traditional, non-nebulized sources (0.5% RSD in retention time). Finally, to provide useful benchmarks for overall proteomics sensitivity, different LC-MS-MS platforms were compared by analyzing a range of concentrations of tryptic digests of bovine serum albumin at three MS facilities. The results indicate that similar sensitivity can be realized with a Bruker HCT-Ultra ion trap, a Thermo LTQ-Velos Linear ion trap and a Thermo LTQ-Orbitrap XL-ETD.