Fully automated four-column capillary LC-MS system for maximizing throughput in proteomic analyses

Deciphering ApoE Genotype-Driven Proteomic and Lipidomic Alterations in Alzheimer's Disease Across Distinct Brain Regions

Alzheimer's disease (AD) is a neurodegenerative disease with a complex etiology influenced by confounding factors such as genetic polymorphisms, age, sex, and race. Traditionally, AD research has not prioritized these influences, resulting in dramatically skewed cohorts such as three times the number of Apolipoprotein E (APOE) ε4-allele carriers in AD relative to healthy cohorts. Thus, the resulting molecular changes in AD have previously been complicated by the influence of apolipoprotein E disparities. To explore how apolipoprotein E polymorphism influences AD progression, 62 post-mortem patients consisting of 33 AD and 29 controls (Ctrl) were studied to balance the number of ε4-allele carriers and facilitate a molecular comparison of the apolipoprotein E genotype. Lipid and protein perturbations were assessed across AD diagnosed brains compared to Ctrl brains, ε4 allele carriers (APOE4+ for those carrying 1 or 2 ε4s and APOE4- for non-ε4 carriers), and differences in ε3ε3 and ε3ε4 Ctrl brains across two brain regions (frontal cortex (FCX) and cerebellum (CBM)). The region-specific influences of apolipoprotein E on AD mechanisms showcased mitochondrial dysfunction and cell proteostasis at the core of AD pathophysiology in the post-mortem brains, indicating these two processes may be influenced by genotypic differences and brain morphology.

Multicolumn Nanoflow Liquid Chromatography with Accelerated Offline Gradient Generation for Robust and Sensitive Single-Cell Proteome Profiling

Peptide separations that combine high sensitivity, robustness, peak capacity, and throughput are essential for extending bottom-up proteomics to smaller samples including single cells. To this end, we have developed a multicolumn nanoLC system with offline gradient generation. One binary pump generates gradients in an accelerated fashion to support multiple analytical columns, and a single trap column interfaces with all analytical columns to reduce required maintenance and simplify troubleshooting. A high degree of parallelization is possible, as one sample undergoes separation while the next sample plus its corresponding mobile phase gradient are transferred into the storage loop and a third sample is loaded into a sample loop. Selective offline elution from the trap column into the sample loop prevents salts and hydrophobic species from entering the analytical column, thus greatly enhancing column lifetime and system robustness. With this design, samples can be analyzed as fast as every 20 min at a flow rate of just 40 nL/min with close to 100% MS utilization time and continuously for as long as several months without column replacement. We utilized the system to analyze the proteomes of single cells from a multiple myeloma cell line upon treatment with the immunomodulatory imide drug lenalidomide.

High-Throughput Proteomics Enabled by a Fully Automated Dual-Trap and Dual-Column LC-MS

This Technical Note describes a dual-column liquid chromatography system coupled to mass spectrometry (LC-MS) for high-throughput bottom-up proteomic analysis. This system made full use of two 2-position 10-port valves and a binary pump with an integrated loading pump of a commercial LC instrument to provide successive operation of two parallel subsystems. Each subsystem consisted of a set of trap columns and an analytical column. A T-junction union was used to split the mobile phase from the loading pump into two parts. This allowed one set of columns to be washed and equilibrated, followed by the injection of the next sample, while the previous sample was eluting and being analyzed on the other set of columns, thereby greatly increasing the analysis throughput. This approach showed high reproducibility for the analysis of HeLa tryptic digests with average relative standard deviation (RSD) values of 1.75%, 6.90%, and 5.19% for the identification number of proteins, peptides, and peptide-spectrum matches (PSMs), respectively, across 10 consecutive runs. The capacity for peptide and protein identification, as well as proteome depth, of the dual-column LC system was comparable to a conventional single-column system. Due to its simple equipment requirements and set up process, this method should be highly accessible for other laboratories.

A compendium of multi-omics data illuminating host responses to lethal human virus infections

Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death. Here, we present experimental methods and multi-omics data capture approaches representing the global host response to infection generated from 45 individual experiments involving human viruses from the Orthomyxoviridae, Filoviridae, Flaviviridae, and Coronaviridae families. Analogous experimental designs were implemented across human or mouse host model systems, longitudinal samples were collected over defined time courses, and global multi-omics data (transcriptomics, proteomics, metabolomics, and lipidomics) were acquired by microarray, RNA sequencing, or mass spectrometry analyses. For comparison, we have included transcriptomics datasets from cells treated with type I and type II human interferon. Raw multi-omics data and metadata were deposited in public repositories, and we provide a central location linking the raw data with experimental metadata and ready-to-use, quality-controlled, statistically processed multi-omics datasets not previously available in any public repository. This compendium of infection-induced host response data for reuse will be useful for those endeavouring to understand viral disease pathophysiology and network biology.

Multidimensional Separations in Top-Down Proteomics

Top-down proteomics (TDP) identifies, quantifies, and characterizes proteins at the intact proteoform level in complex biological samples to understand proteoform function and cellular mechanisms. However, analyzing complex biological samples using TDP is still challenging due to high sample complexity and wide dynamic range. High-resolution separation methods are often applied prior to mass spectrometry (MS) analysis to decrease sample complexity and increase proteomics throughput. These separation methods, however, may not be efficient enough to characterize low abundance intact proteins in complex samples. As such, multidimensional separation techniques (combination of two or more separation methods with high orthogonality) have been developed and applied that demonstrate improved separation resolution and more comprehensive identification in TDP. A suite of multidimensional separation methods that couple various types of liquid chromatography (LC), capillary electrophoresis (CE), and/or gel electrophoresis-based separation approaches have been developed and applied in TDP to analyze complex biological samples. Here, we reviewed multidimensional separation strategies employed for TDP, summarized current applications, and discussed the gaps that may be addressed in the future.

HyperSCP: Combining Isotopic and Isobaric Labeling for Higher Throughput Single-Cell Proteomics

Recent developments in mass spectrometry-based single-cell proteomics (SCP) have resulted in dramatically improved sensitivity, yet the relatively low measurement throughput remains a limitation. Isobaric and isotopic labeling methods have been separately applied to SCP to increase throughput through multiplexing. Here we combined both forms of labeling to achieve multiplicative scaling for higher throughput. Two-plex stable isotope labeling of amino acids in cell culture (SILAC) and isobaric tandem mass tag (TMT) labeling enabled up to 28 single cells to be analyzed in a single liquid chromatography-mass spectrometry (LC-MS) analysis, in addition to carrier, reference, and negative control channels. A custom nested nanowell chip was used for nanoliter sample processing to minimize sample losses. Using a 145-min total LC-MS cycle time, ∼280 single cells were analyzed per day. This measurement throughput could be increased to ∼700 samples per day with a high-duty-cycle multicolumn LC system producing the same active gradient. The labeling efficiency and achievable proteome coverage were characterized for multiple analysis conditions.

A peptide-centric approach to analyse quantitative proteomics data- an application to prostate cancer biomarker discovery

Bottom-up proteomics is a popular approach in molecular biomarker research. However, protein analysts have realized the limitations of protein-based approaches for identifying and quantifying proteins in complex samples, such as the identification of peptides sequences shared by multiple proteins and the difficulty in identifying modified peptides. Thus, there are many exciting opportunities to improve analysis methods. Here, an alternative method focused on peptide analysis is proposed as a complement to the conventional proteomics data analysis. To investigate this hypothesis, a peptide-centric approach was applied to reanalyse a urine proteome dataset of samples from prostate cancer patients and controls. The results were compared with the conventional protein-centric approach. The relevant proteins/peptides to discriminate the groups were detected based on two approaches, p-value and VIP values obtained by a PLS-DA model. A comparison of the two strategies revealed high inconsistency between protein and peptide information and greater involvement of peptides in key PCa processes. This peptide analysis unveiled discriminative features that are lost when proteins are analyzed as homogeneous entities. This type of analysis is innovative in PCa and integrated with the widely used protein-centric approach might provide a more comprehensive view of this disease and revolutionize biomarker discovery. SIGNIFICANCE: In this study, the application of a protein and peptide-centric approaches to reanalyse a urine proteome dataset from prostate cancer (PCa) patients and controls showed that many relevant proteins/peptides are missed by the conservative nature of p-value in statistical tests, therefore, the inclusion of variable selection methods in the analysis of the dataset reported in this work is fruitful. Comparison of protein- and peptide-based approaches revealed a high inconsistency between protein and peptide information and a greater involvement of peptides in key PCa processes. These results provide a new perspective to analyse proteomics data and detect relevant targets based on the integration of peptide and protein information. This data integration allows to unravel discriminative features that normally go unnoticed, to have a more comprehensive view of the disease pathophysiology and to open new avenues for the discovery of biomarkers.

Development of a dual-electrospray ionization source with in-line absorbance-based voltage control

Emitter tip arrays for electrospray ionization have been used for a variety of MS sample introduction purposes, including detection of multiple sample eluent streams and improved accuracy through parallel infusion of an internal standard. User control is typically required for targeted application of high voltage to specific channels to maximize analyte signal and minimize other background signals. In this communication, an automated approach to applying electrospray voltage only when a detectable analyte is present is described. An in-line absorbance detector is used to identify the presence of an analyte in the fluidic path between the sample introduction valve and the mass spectrometer. A Raspberry Pi-controlled system is then used to apply high voltage to a downstream emitter tip at the MS inlet following a delay volume between the detectors. Demonstration of this technique on two parallel sample channels is reported, including a pulsed voltage application to maximize signal when analytes elute on each channel simultaneously.

Let’s Get Small: Miniaturizing Separations for Single-Cell Analysis

Direct profiling of biochemical expression within single cells provides insights into cellular processes that are lost when ensemble averages are measured across populations of cells. Advanced separations coupled with mass spectrometry (MS) can now quantify more than 1000 proteins within single cells. Further miniaturization of separations will greatly extend the reach of single-cell proteomics, metabolomics, and lipidomics, but key challenges in instrumentation, column technology, and ionization sources must be addressed.

Label-Free Profiling of up to 200 Single-Cell Proteomes per Day Using a Dual-Column Nanoflow Liquid Chromatography Platform

Single-cell proteomics (SCP) has great potential to advance biomedical research and personalized medicine. The sensitivity of such measurements increases with low-flow separations (<100 nL/min) due to improved ionization efficiency, but the time required for sample loading, column washing, and regeneration in these systems can lead to low measurement throughput and inefficient utilization of the mass spectrometer. Herein, we developed a two-column liquid chromatography (LC) system that dramatically increases the throughput of label-free SCP using two parallel subsystems to multiplex sample loading, online desalting, analysis, and column regeneration. The integration of MS1-based feature matching increased proteome coverage when short LC gradients were used. The high-throughput LC system was reproducible between the columns, with a 4% difference in median peptide abundance and a median CV of 18% across 100 replicate analyses of a single-cell-sized peptide standard. An average of 621, 774, 952, and 1622 protein groups were identified with total analysis times of 7, 10, 15, and 30 min, corresponding to a measurement throughput of 206, 144, 96, and 48 samples per day, respectively. When applied to single HeLa cells, we identified nearly 1000 protein groups per cell using 30 min cycles and 660 protein groups per cell for 15 min cycles. We explored the possibility of measuring cancer therapeutic targets with a pilot study comparing the K562 and Jurkat leukemia cell lines. This work demonstrates the feasibility of high-throughput label-free single-cell proteomics.

Unveiling molecular signatures of preeclampsia and gestational diabetes mellitus with multi-omics and innovative cheminformatics visualization tools

To fully enable the development of diagnostic tools and progressive pharmaceutical drugs, it is imperative to understand the molecular changes occurring before and during disease onset and progression. Systems biology assessments utilizing multi-omic analyses (e.g. the combination of proteomics, lipidomics, genomics, etc.) have shown enormous value in determining molecules prevalent in diseases and their associated mechanisms. Herein, we utilized multi-omic evaluations, multi-dimensional analysis methods, and new cheminformatics-based visualization tools to provide an in depth understanding of the molecular changes taking place in preeclampsia (PRE) and gestational diabetes mellitus (GDM) patients. Since PRE and GDM are two prevalent pregnancy complications that result in adverse health effects for both the mother and fetus during pregnancy and later in life, a better understanding of each is essential. The multi-omic evaluations performed here provide new insight into the end-stage molecular profiles of each disease, thereby supplying information potentially crucial for earlier diagnosis and treatments.

Proteomic assessment of serum biomarkers of longevity in older men

The biological bases of longevity are not well understood, and there are limited biomarkers for the prediction of long life. We used a high-throughput, discovery-based proteomics approach to identify serum peptides and proteins that were associated with the attainment of longevity in a longitudinal study of community-dwelling men age ≥65 years. Baseline serum in 1196 men were analyzed using liquid chromatography-ion mobility-mass spectrometry, and lifespan was determined during ~12 years of follow-up. Men who achieved longevity (≥90% expected survival) were compared to those who died earlier. Rigorous statistical methods that controlled for false positivity were utilized to identify 25 proteins that were associated with longevity. All these proteins were in lower abundance in long-lived men and included a variety involved in inflammation or complement activation. Lower levels of longevity-associated proteins were also associated with better health status, but as time to death shortened, levels of these proteins increased. Pathway analyses implicated a number of compounds as important upstream regulators of the proteins and implicated shared networks that underlie the observed associations with longevity. Overall, these results suggest that complex pathways, prominently including inflammation, are linked to the likelihood of attaining longevity. This work may serve to identify novel biomarkers for longevity and to understand the biology underlying lifespan.

Rapid Screening of Urinary 1-Hydroxypyrene Glucuronide by Multisegment Injection-Capillary Electrophoresis-Tandem Mass Spectrometry: A High-Throughput Method for Biomonitoring of Recent Smoke Exposures

Urinary 1-hydroxypyrene (HP) is a widely used biomarker of polycyclic aromatic hydrocarbon exposure relevant for biomonitoring the deleterious health impacts from tobacco smoke and ambient air pollution, as well as the hazards of certain occupations. Conventional methods for urinary HP analysis based on liquid chromatography with native fluorescence detection or tandem mass spectrometry (MS/MS) and gas chromatography-mass spectrometry (GC-MS) are limited by low sample throughput and complicated sample workup protocols that are prone to bias. Herein, we introduce a high throughput method to directly analyze the intact glucuronide conjugate of HP (HP-G) in human urine after a simple acidified ether extraction procedure when using multisegment injection-capillary electrophoresis-tandem mass spectrometry (MSI-CE-MS/MS). Multiplexed analyses of 13 independent urine extracts are achieved in a single run (<3 min/sample) with stringent quality control while avoiding enzyme deconjugation and precolumn chemical derivatization. Method validation demonstrates good technical precision (CV = 7.7%, n = 45) and accuracy with a mean recovery of (93 ± 3%) for urinary HP-G at three concentration levels with adequate detection limits (7 ng/L, S/N = 3). An interlaboratory method comparison of urine samples collected from firefighters deployed in the 2016 Fort McMurray wildfire also confirms good mutual agreement with an acceptable negative bias (mean bias = 15%, n = 55) when measuring urinary HP-G by MSI-CE-MS/MS as compared to total hydrolyzed urinary HP by GC-MS due to the low residual levels of free HP and its sulfate conjugate. This multiplexed separation platform is optimal for large-scale biomonitoring studies of air pollution relevant to global health as well as occupational smoke exposures in firefighters susceptible to dermal PAH absorption when using personal protective equipment.

Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography-Mass Spectrometry for High-Throughput Single-Cell Proteomics

Single-cell proteomics can provide critical biological insight into the cellular heterogeneity that is masked by bulk-scale analysis. We have developed a nanoPOTS (nanodroplet processing in one pot for trace samples) platform and demonstrated its broad applicability for single-cell proteomics. However, because of nanoliter-scale sample volumes, the nanoPOTS platform is not compatible with automated LC-MS systems, which significantly limits sample throughput and robustness. To address this challenge, we have developed a nanoPOTS autosampler allowing fully automated sample injection from nanowells to LC-MS systems. We also developed a sample drying, extraction, and loading workflow to enable reproducible and reliable sample injection. The sequential analysis of 20 samples containing 10 ng tryptic peptides demonstrated high reproducibility with correlation coefficients of >0.995 between any two samples. The nanoPOTS autosampler can provide analysis throughput of 9.6, 16, and 24 single cells per day using 120, 60, and 30 min LC gradients, respectively. As a demonstration for single-cell proteomics, the autosampler was first applied to profiling protein expression in single MCF10A cells using a label-free approach. At a throughput of 24 single cells per day, an average of 256 proteins was identified from each cell and the number was increased to 731 when the Match Between Runs algorithm of MaxQuant was used. Using a multiplexed isobaric labeling approach (TMT-11plex), ∼77 single cells could be analyzed per day. We analyzed 152 cells from three acute myeloid leukemia cell lines, resulting in a total of 2558 identified proteins with 1465 proteins quantifiable (70% valid values) across the 152 cells. These data showed quantitative single-cell proteomics can cluster cells to distinct groups and reveal functionally distinct differences.

Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis

Rationale:

The monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment.

Objective:

We utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy.

Methods:

Serum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoaffinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points.

Results:

A total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were significantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status.

Conclusion:

A comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care.

Spatially Resolved Proteome Mapping of Laser Capture Microdissected Tissue with Automated Sample Transfer to Nanodroplets

Current mass spectrometry (MS)-based proteomics approaches are ineffective for mapping protein expression in tissue sections with high spatial resolution because of the limited overall sensitivity of conventional workflows. Here we report an integrated and automated method to advance spatially resolved proteomics by seamlessly coupling laser capture microdissection (LCM) with a recently developed nanoliter-scale sample preparation system termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples). The workflow is enabled by prepopulating nanowells with DMSO, which serves as a sacrificial capture liquid for microdissected tissues. The DMSO droplets efficiently collect laser-pressure catapulted LCM tissues as small as 20 μm in diameter with success rates >87%. We also demonstrate that tissue treatment with DMSO can significantly improve proteome coverage, likely due to its ability to dissolve lipids from tissue and enhance protein extraction efficiency. The LCM-nanoPOTS platform was able to identify 180, 695, and 1827 protein groups on average from 12-μm-thick rat brain cortex tissue sections having diameters of 50, 100, and 200 μm, respectively. We also analyzed 100-μm-diameter sections corresponding to 10-18 cells from three different regions of rat brain and comparatively quantified ∼1000 proteins, demonstrating the potential utility for high-resolution spatially resolved mapping of protein expression in tissues.

Proteomic Analysis of Single Mammalian Cells Enabled by Microfluidic Nanodroplet Sample Preparation and Ultrasensitive NanoLC-MS

We report on the quantitative proteomic analysis of single mammalian cells. Fluorescence-activated cell sorting was employed to deposit cells into a newly developed nanodroplet sample processing chip, after which samples were analyzed by ultrasensitive nanoLC-MS. An average of circa 670 protein groups were confidently identified from single HeLa cells, which is a far greater level of proteome coverage for single cells than has been previously reported. We demonstrate that the single-cell proteomics platform can be used to differentiate cell types from enzyme-dissociated human lung primary cells and identify specific protein markers for epithelial and mesenchymal cells.

Quantifying Kinase-Specific Phosphorylation Stoichiometry Using Stable Isotope Labeling In a Reverse In-Gel Kinase Assay

Despite recent advancements in large-scale phosphoproteomics, methods to quantify kinase-specific phosphorylation stoichiometry of protein substrates are lacking. We developed a method to quantify kinase-specific phosphorylation stoichiometry by combining the reverse in-gel kinase assay (RIKA) with high-resolution liquid chromatography-mass spectrometry (LC-MS). Beginning with predetermined ratios of phosphorylated to nonphosphorylated protein kinase CK2 (CK2) substrate molecules, we employed ¹⁸O-labeled adenosine triphosphate (¹⁸O-ATP) as the phosphate donor in a RIKA, then quantified the ratio of ¹⁸O- versus ¹⁶O-labeled tryptic phosphopeptide using high mass accuracy mass spectrometry (MS). We demonstrate that the phosphorylation stoichiometry determined by this method across a broad percent phosphorylation range correlated extremely well with the predicted value (correlation coefficient = 0.99). This approach provides a quantitative alternative to antibody-based methods of determining the extent of phosphorylation of a substrate pool.

The fungal cultivar of leaf-cutter ants produces specific enzymes in response to different plant substrates

Herbivores use symbiotic microbes to help derive energy and nutrients from plant material. Leaf-cutter ants are a paradigmatic example, cultivating their mutualistic fungus Leucoagaricus gongylophorus on plant biomass that workers forage from a diverse collection of plant species. Here, we investigate the metabolic flexibility of the ants' fungal cultivar for utilizing different plant biomass. Using feeding experiments and a novel approach in metaproteomics, we examine the enzymatic response of L. gongylophorus to leaves, flowers, oats or a mixture of all three. Across all treatments, our analysis identified and quantified 1766 different fungal proteins, including 161 putative biomass-degrading enzymes. We found significant differences in the protein profiles in the fungus gardens of subcolonies fed different plant substrates. When provided with leaves or flowers, which contain the majority of their energy as recalcitrant plant polymers, the fungus gardens produced more proteins predicted to break down cellulose: endoglucanase, exoglucanase and β-glucosidase. Further, the complete metaproteomes for the leaves and flowers treatments were very similar, while the mixed substrate treatment closely resembled the treatment with oats alone. This indicates that when provided a mixture of plant substrates, fungus gardens preferentially break down the simpler, more digestible substrates. This flexible, substrate-specific enzymatic response of the fungal cultivar allows leaf-cutter ants to derive energy from a wide range of substrates, which likely contributes to their ability to be dominant generalist herbivores.

Prediction of biomarkers of therapeutic effects of patients with lung adenocarcinoma treated with gefitinib based on progression-free-survival by metabolomic fingerprinting

Lung carcinoma is one of the most frequently diagnosed malignancy and threats human life and health. In clinical practice, gefitinib, one of the most well-known epidermal growth factor receptor tyrosine kinase inhibitors, was frequently used in the treatment of non-small cell lung carcinoma. However, this drug is not useful for all non-small cell patients. In this study, the biomarkers were found out to predict the therapeutic effects of gefitinib for lung carcinoma patients. Serum samples were collected from patients with advanced lung adenocarcinoma. The ultra-high performance liquid chromatography (UHPLC)-quadrupole-time of flight mass spectrometry (Q-TOF MS) was conducted to obtain the metabolic data for each patient. Partial least squares-discriminate analysis (PLS-DA) was performed to indicate the differences between metabolites of patients, and Cox proportional hazards regression analysis was used to eliminate the interference of the patient's gender, age, smoking history and disease stage. Thus, differential biomarkers were found. The combination of these biomarkers was statistically significant predictors based on progression-free survival. If these biomarkers can be further confirmed by the clinic, it could suggest the proper therapeutic schedule, and help to reduce patients' economic burden and medication side effects.

Global Proteomic Analysis Reveals an Exclusive Role of Thylakoid Membranes in Bioenergetics of a Model Cyanobacterium

Cyanobacteria are photosynthetic microbes with highly differentiated membrane systems. These organisms contain an outer membrane, plasma membrane, and an internal system of thylakoid membranes where the photosynthetic and respiratory machinery are found. This existence of compartmentalization and differentiation of membrane systems poses a number of challenges for cyanobacterial cells in terms of organization and distribution of proteins to the correct membrane system. Proteomics studies have long sought to identify the components of the different membrane systems in cyanobacteria, and to date about 450 different proteins have been attributed to either the plasma membrane or thylakoid membrane. Given the complexity of these membranes, many more proteins remain to be identified, and a comprehensive catalogue of plasma membrane and thylakoid membrane proteins is needed. Here we describe the identification of 635 differentially localized proteins in Synechocystis sp. PCC 6803 by quantitative iTRAQ isobaric labeling; of these, 459 proteins were localized to the plasma membrane and 176 were localized to the thylakoid membrane. Surprisingly, we found over 2.5 times the number of unique proteins identified in the plasma membrane compared with the thylakoid membrane. This suggests that the protein composition of the thylakoid membrane is more homogeneous than the plasma membrane, consistent with the role of the plasma membrane in diverse cellular processes including protein trafficking and nutrient import, compared with a more specialized role for the thylakoid membrane in cellular energetics. Thus, our data clearly define the two membrane systems with distinct functions. Overall, the protein compositions of the Synechocystis 6803 plasma membrane and thylakoid membrane are quite similar to that of the plasma membrane of Escherichia coli and thylakoid membrane of Arabidopsis chloroplasts, respectively. Synechocystis 6803 can therefore be described as a Gram-negative bacterium with an additional internal membrane system that fulfills the energetic requirements of the cell.

A simple dual online ultra-high pressure liquid chromatography system (sDO-UHPLC) for high throughput proteome analysis

We report a new and simple design of a fully automated dual-online ultra-high pressure liquid chromatography system. The system employs only two nano-volume switching valves (a two-position four port valve and a two-position ten port valve) that direct solvent flows from two binary nano-pumps for parallel operation of two analytical columns and two solid phase extraction (SPE) columns. Despite the simple design, the sDO-UHPLC offers many advantageous features that include high duty cycle, back flushing sample injection for fast and narrow zone sample injection, online desalting, high separation resolution and high intra/inter-column reproducibility. This system was applied to analyze proteome samples not only in high throughput deep proteome profiling experiments but also in high throughput MRM experiments.

Application of a high-throughput, parallel HPLC system for quantitative chiral analysis of pantoprazole

Background: Chromatographic separation of enantiomers is considered a task in analytical chemistry particularly for high sample throughput. This paper describes a high-throughput parallel HPLC–MS/MS method for the determination of pantoprazole enantiomers. Results: Baseline separation of pantoprazole enantiomers was achieved on a Chiralcel OZ-RH column in a run time of 4.5 min. Assays for enantiomers were linear with satisfactory intra- and inter-day precision and accuracy. The assay was suitable for high-throughput analysis as shown by its successful application to a chiral PK study in beagle dog. Conclusion: A high-throughput parallel HPLC–MS/MS assay for pantoprazole has been developed and validated. This method provides nearly twofold increased sample throughput, and was shown to be suitable for application in PK studies.

Multicopy Single-Stranded DNA Directs Intestinal Colonization of Enteric Pathogens

Multicopy single-stranded DNAs (msDNAs) are hybrid RNA-DNA molecules encoded on retroelements called retrons and produced by the action of retron reverse transcriptases. Retrons are widespread in bacteria but the natural function of msDNA has remained elusive despite 30 years of study. The major roadblock to elucidation of the function of these unique molecules has been the lack of any identifiable phenotypes for mutants unable to make msDNA. We report that msDNA of the zoonotic pathogen Salmonella Typhimurium is necessary for colonization of the intestine. Similarly, we observed a defect in intestinal persistence in an enteropathogenic E. coli mutant lacking its retron reverse transcriptase. Under anaerobic conditions in the absence of msDNA, proteins of central anaerobic metabolism needed for Salmonella colonization of the intestine are dysregulated. We show that the msDNA-deficient mutant can utilize nitrate, but not other alternate electron acceptors in anaerobic conditions. Consistent with the availability of nitrate in the inflamed gut, a neutrophilic inflammatory response partially rescued the ability of a mutant lacking msDNA to colonize the intestine. These findings together indicate that the mechanistic basis of msDNA function during Salmonella colonization of the intestine is proper production of proteins needed for anaerobic metabolism. We further conclude that a natural function of msDNA is to regulate protein abundance, the first attributable function for any msDNA. Our data provide novel insight into the function of this mysterious molecule that likely represents a new class of regulatory molecules.

Bayesian proteoform modeling improves protein quantification of global proteomic measurements

As the capability of mass spectrometry-based proteomics has matured, tens of thousands of peptides can be measured simultaneously, which has the benefit of offering a systems view of protein expression. However, a major challenge is that, with an increase in throughput, protein quantification estimation from the native measured peptides has become a computational task. A limitation to existing computationally driven protein quantification methods is that most ignore protein variation, such as alternate splicing of the RNA transcript and post-translational modifications or other possible proteoforms, which will affect a significant fraction of the proteome. The consequence of this assumption is that statistical inference at the protein level, and consequently downstream analyses, such as network and pathway modeling, have only limited power for biomarker discovery. Here, we describe a Bayesian Proteoform Quantification model (BP-Quant)(1) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern or the existence of multiple overexpressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. We verify the approach using a dilution study from mouse plasma samples and demonstrate that BP-Quant achieves similar accuracy as the current state-of-the-art methods at proteoform identification with significantly better specificity. BP-Quant is available as a MatLab® and R packages.

Enhancing bottom-up and top-down proteomic measurements with ion mobility separations

Proteomic measurements with greater throughput, sensitivity, and structural information are essential for improving both in-depth characterization of complex mixtures and targeted studies. While LC separation coupled with MS (LC-MS) measurements have provided information on thousands of proteins in different sample types, the introduction of a separation stage that provides further component resolution and rapid structural information has many benefits in proteomic analyses. Technical advances in ion transmission and data acquisition have made ion mobility separations an opportune technology to be easily and effectively incorporated into LC-MS proteomic measurements for enhancing their information content. Herein, we report on applications illustrating increased sensitivity, throughput, and structural information by utilizing IMS-MS and LC-IMS-MS measurements for both bottom-up and top-down proteomics measurements.

Integration of microfluidic LC with HRMS for the analysis of analytes in biofluids: past, present and future

Capillary LC (cLC) coupled to MS has the potential to improve detection limits, address limited sample volumes and allow multiple analyses from one sample. This is particularly attractive in areas where ultrahigh assay sensitivity, low limits of detection and small sample volumes are becoming commonplace. However, implementation of cLC–MS in the bioanalytical–drug metabolism area had been hampered by the lack of commercial instrumentation and the need for experts to operate the system. Recent advances in microfabricated devices such as chip-cube and ion-key technologies offer the potential for true implementation of cLC in the modern laboratory including the benefits of the combination of this type of separation with high-resolution MS.

Muscle Segment Homeobox Genes Direct Embryonic Diapause by Limiting Inflammation in the Uterus

Embryonic diapause is a reproductive strategy widespread in the animal kingdom. This phenomenon is defined by a temporary arrest in blastocyst growth and metabolic activity within a quiescent uterus without implantation until the environmental and maternal milieu become favorable for pregnancy to progress. We found that uterine Msx expression persists during diapause across species; their inactivation in the mouse uterus results in termination of diapause with the development of implantation-like responses ("pseudoimplantation") that ultimately succumbed to resorption. To understand the cause of this failure, we compared proteome profiles between floxed and Msx-deleted uteri. In deleted uteri, several functional networks, including transcription/translation, ubiquitin-proteasome, inflammation, and endoplasmic reticulum stress, were dysregulated. Computational modeling predicted intersection of these pathways on an enhanced inflammatory signature. Further studies showed that this signature was reflected in increased phosphorylated IκB levels and nuclear NFκB in deleted uteri. This was associated with enhanced proteasome activity and endoplasmic reticulum stress. Interestingly, treatment with anti-inflammatory glucocorticoid (dexamethasone) reduced the inflammatory signature with improvement of the diapause phenotype. These findings highlight an unexpected role of uterine Msx in limiting aberrant inflammatory responses to maintain embryonic diapause.

A Double-Barrel Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) System to Quantify 96 Interactomes per Day

The field of proteomics has evolved hand-in-hand with technological advances in LC-MS/MS systems, now enabling the analysis of very deep proteomes in a reasonable time. However, most applications do not deal with full cell or tissue proteomes but rather with restricted subproteomes relevant for the research context at hand or resulting from extensive fractionation. At the same time, investigation of many conditions or perturbations puts a strain on measurement capacity. Here, we develop a high-throughput workflow capable of dealing with large numbers of low or medium complexity samples and specifically aim at the analysis of 96-well plates in a single day (15 min per sample). We combine parallel sample processing with a modified liquid chromatography platform driving two analytical columns in tandem, which are coupled to a quadrupole Orbitrap mass spectrometer (Q Exactive HF). The modified LC platform eliminates idle time between measurements, and the high sequencing speed of the Q Exactive HF reduces required measurement time. We apply the pipeline to the yeast chromatin remodeling landscape and demonstrate quantification of 96 pull-downs of chromatin complexes in about 1 day. This is achieved with only 500 μg input material, enabling yeast cultivation in a 96-well format. Our system retrieved known complex-members and the high throughput allowed probing with many bait proteins. Even alternative complex compositions were detectable in these very short gradients. Thus, sample throughput, sensitivity and LC/MS-MS duty cycle are improved severalfold compared with established workflows. The pipeline can be extended to different types of interaction studies and to other medium complexity proteomes.

Global analysis of Salmonella alternative sigma factor E on protein translation

The alternative sigma factor E (σ(E)) is critical for response to extracytoplasmic stress in Salmonella. Extensive studies have been conducted on σ(E)-regulated gene expression, particularly at the transcriptional level. Increasing evidence suggests however that σ(E) may indirectly participate in post-transcriptional regulation. In this study, we conducted sample-matched global proteomic and transcriptomic analyses to determine the level of regulation mediated by σ(E) in Salmonella. Samples were analyzed from wild-type and isogenic rpoE mutant Salmonella cultivated in three different conditions: nutrient-rich and conditions that mimic early and late intracellular infection. We found that 30% of the observed proteome was regulated by σ(E) combining all three conditions. In different growth conditions, σ(E) affected the expression of a broad spectrum of Salmonella proteins required for miscellaneous functions. Those involved in transport and binding, protein synthesis, and stress response were particularly highlighted. By comparing transcriptomic and proteomic data, we identified genes post-transcriptionally regulated by σ(E) and found that post-transcriptional regulation was responsible for a majority of changes observed in the σ(E)-regulated proteome. Further, comparison of transcriptomic and proteomic data from hfq mutant of Salmonella demonstrated that σ(E)-mediated post-transcriptional regulation was partially dependent on the RNA-binding protein Hfq.

Changes in protein expression across laboratory and field experiments in Geobacter bemidjiensis

Bacterial extracellular metal respiration, as carried out by members of the genus Geobacter, is of interest for applications including microbial fuel cells and bioremediation. Geobacter bemidjiensis is the major species whose growth is stimulated during groundwater amendment with acetate. We have carried out label-free proteomics studies of G. bemidjiensis grown with acetate as the electron donor and either fumarate, ferric citrate, or one of two hydrous ferric oxide mineral types as electron acceptor. The major class of proteins whose expression changes across these conditions is c-type cytochromes, many of which are known to be involved in extracellular metal reduction in other, better-characterized Geobacter species. Some proteins with multiple homologues in G. bemidjiensis (OmcS, OmcB) had different expression patterns than observed for their G. sulfurreducens homologues under similar growth conditions. We also compared the proteome from our study to a prior proteomics study of biomass recovered from an aquifer in Colorado, where the microbial community was dominated by strains closely related to G. bemidjiensis. We detected an increased number of proteins with functions related to motility and chemotaxis in the Colorado field samples compared to the laboratory samples, suggesting the importance of motility for in situ extracellular metal respiration.

Synechococcus elongatus UTEX 2973, a fast growing cyanobacterial chassis for biosynthesis using light and CO₂

Photosynthetic microbes are of emerging interest as production organisms in biotechnology because they can grow autotrophically using sunlight, an abundant energy source, and CO₂, a greenhouse gas. Important traits for such microbes are fast growth and amenability to genetic manipulation. Here we describe Synechococcuselongatus UTEX 2973, a unicellular cyanobacterium capable of rapid autotrophic growth, comparable to heterotrophic industrial hosts such as yeast. Synechococcus UTEX 2973 can be readily transformed for facile generation of desired knockout and knock-in mutations. Genome sequencing coupled with global proteomics studies revealed that Synechococcus UTEX 2973 is a close relative of the widely studied cyanobacterium Synechococcuselongatus PCC 7942, an organism that grows more than two times slower. A small number of nucleotide changes are the only significant differences between the genomes of these two cyanobacterial strains. Thus, our study has unraveled genetic determinants necessary for rapid growth of cyanobacterial strains of significant industrial potential.

Transcriptomic and proteomic dynamics in the metabolism of a diazotrophic cyanobacterium, Cyanothece sp. PCC 7822 during a diurnal light-dark cycle

Background

Cyanothece sp. PCC 7822 is an excellent cyanobacterial model organism with great potential to be applied as a biocatalyst for the production of high value compounds. Like other unicellular diazotrophic cyanobacterial species, it has a tightly regulated metabolism synchronized to the light–dark cycle. Utilizing transcriptomic and proteomic methods, we quantified the relationships between transcription and translation underlying central and secondary metabolism in response to nitrogen free, 12 hour light and 12 hour dark conditions.

Results

By combining mass-spectrometry based proteomics and RNA-sequencing transcriptomics, we quantitatively measured a total of 6766 mRNAs and 1322 proteins at four time points across a 24 hour light–dark cycle. Photosynthesis, nitrogen fixation, and carbon storage relevant genes were expressed during the preceding light or dark period, concurrent with measured nitrogenase activity in the late light period. We describe many instances of disparity in peak mRNA and protein abundances, and strong correlation of light dependent expression of both antisense and CRISPR-related gene expression. The proteins for nitrogenase and the pentose phosphate pathway were highest in the dark, whereas those for glycolysis and the TCA cycle were more prominent in the light. Interestingly, one copy of the psbA gene encoding the photosystem II (PSII) reaction center protein D1 (psbA4) was highly upregulated only in the dark. This protein likely cannot catalyze O₂ evolution and so may be used by the cell to keep PSII intact during N₂ fixation. The CRISPR elements were found exclusively at the ends of the large plasmid and we speculate that their presence is crucial to the maintenance of this plasmid.

Conclusions

This investigation of parallel transcriptional and translational activity within Cyanothece sp. PCC 7822 provided quantitative information on expression levels of metabolic pathways relevant to engineering efforts. The identification of expression patterns for both mRNA and protein affords a basis for improving biofuel production in this strain and for further genetic manipulations. Expression analysis of the genes encoded on the 6 plasmids provided insight into the possible acquisition and maintenance of some of these extra-chromosomal elements.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1185) contains supplementary material, which is available to authorized users.

Automated genome mining of ribosomal peptide natural products

Ribosomally synthesized and posttranslationally modified peptides (RiPPs), especially from microbial sources, are a large group of bioactive natural products that are a promising source of new (bio)chemistry and bioactivity.1 In light of exponentially increasing microbial genome databases and improved mass spectrometry (MS)-based metabolomic platforms, there is a need for computational tools that connect natural product genotypes predicted from microbial genome sequences with their corresponding chemotypes from metabolomic data sets. Here, we introduce RiPPquest, a tandem mass spectrometry database search tool for identification of microbial RiPPs, and apply it to lanthipeptide discovery. RiPPquest uses genomics to limit search space to the vicinity of RiPP biosynthetic genes and proteomics to analyze extensive peptide modifications and compute p-values of peptide-spectrum matches (PSMs). We highlight RiPPquest by connecting multiple RiPPs from extracts of Streptomyces to their gene clusters and by the discovery of a new class III lanthipeptide, informatipeptin, from Streptomyces viridochromogenes DSM 40736 to reflect that it is a natural product that was discovered by mass spectrometry based genome mining using algorithmic tools rather than manual inspection of mass spectrometry data and genetic information. The presented tool is available at cyclo.ucsd.edu.

Cytomegalovirus pp65 limits dissemination but is dispensable for persistence

The most abundantly produced virion protein in human cytomegalovirus (HCMV) is the immunodominant phosphoprotein 65 (pp65), which is frequently included in CMV vaccines. Although it is nonessential for in vitro CMV growth, pp65 displays immunomodulatory functions that support a potential role in primary and/or persistent infection. To determine the contribution of pp65 to CMV infection and immunity, we generated a rhesus CMV lacking both pp65 orthologs (RhCMVΔpp65ab). While deletion of pp65ab slightly reduced growth in vitro and increased defective particle formation, the protein composition of secreted virions was largely unchanged. Interestingly, pp65 was not required for primary and persistent infection in animals. Immune responses induced by RhCMVΔpp65ab did not prevent reinfection with rhesus CMV; however, reinfection with RhCMVΔUS2-11, which lacks viral-encoded MHC-I antigen presentation inhibitors, was prevented. Unexpectedly, induction of pp65b-specific T cells alone did not protect against RhCMVΔUS2-11 challenge, suggesting that T cells targeting multiple CMV antigens are required for protection. However, pp65-specific immunity was crucial for controlling viral dissemination during primary infection, as indicated by the marked increase of RhCMVΔpp65ab genome copies in CMV-naive, but not CMV-immune, animals. Our data provide rationale for inclusion of pp65 into CMV vaccines but also demonstrate that pp65-induced T cell responses alone do not recapitulate the protective effect of natural infection.

Integrative transcriptomic and proteomic analysis of osteocytic cells exposed to fluid flow reveals novel mechano-sensitive signaling pathways

Osteocytes, positioned within bone׳s porous structure, are subject to interstitial fluid flow upon whole bone loading. Such fluid flow is widely theorized to be a mechanical signal transduced by osteocytes, initiating a poorly understood cascade of signaling events mediating bone adaptation to mechanical load. The objective of this study was to examine the time course of flow-induced changes in osteocyte gene transcript and protein levels using high-throughput approaches. Osteocyte-like MLO-Y4 cells were subjected to 2h of oscillating fluid flow (1Pa peak shear stress) and analyzed following 0, 2, 8, and 24h post-flow incubation. Transcriptomic microarray analysis, followed by gene ontology pathway analysis, demonstrated fluid flow regulation of genes consistent with both known and unknown metabolic and inflammatory responses in bone. Additionally, two of the more highly up-regulated gene products - chemokines Cxcl1 and Cxcl2, supported by qPCR - have not previously been reported as responsive to fluid flow. Proteomic analysis demonstrated greatest up-regulation of the ATP-producing enzyme NDK, calcium-binding Calcyclin, and G protein-coupled receptor kinase 6. Finally, an integrative pathway analysis merging fold changes in transcript and protein levels predicted signaling nodes not directly detected at the sampled time points, including transcription factors c-Myc, c-Jun, and RelA/NF-κB. These results extend our knowledge of the osteocytic response to fluid flow, most notably up-regulation of Cxcl1 and Cxcl2 as possible paracrine agents for osteoblastic and osteoclastic recruitment. Moreover, these results demonstrate the utility of integrative, high-throughput approaches in place of a traditional candidate approach for identifying novel mechano-sensitive signaling molecules.

Top-down proteomics of a drop of blood for diabetes monitoring

The most common markers for monitoring patients with diabetes are glucose and HbA1c, but additional markers such as glycated human serum albumin (HSA) have been identified that could address the glycation gap and bridge the time scales of glycemia between transient and 2-3 months. However, there is currently no technical platform that could measure these markers concurrently in a cost-effective manner. We have developed a new assay that is able to measure glucose, HbA1c, glycated HSA, and glycated apolipoprotein A-I (apoA-I) for monitoring of individual blood glycemia, as well as cysteinylated HSA, S-nitrosylated HbA, and methionine-oxidized apoA-I for gauging oxidative stress and cardiovascular risks, all in 5 μL of blood. The assay utilizes our proprietary multinozzle emitter array chip technology to enable the analysis of small volumes of blood, without complex sample preparation prior to the online and on-chip liquid chromatography-nanoelectrospray ionization mass spectrometry. Importantly, the assay employs top-down proteomics for more accurate quantitation of protein levels and for identification of post-translational modifications. Further, the assay provides multimarker, multitime-scale, and multicompartment monitoring of blood glycemia. Our assay readily segregates healthy controls from Type 2 diabetes patients and may have the potential to enable better long-term monitoring and disease management of diabetes.

The succinated proteome

The post-translational modifications (PTMs) of cysteine residues include oxidation, S-glutathionylation, S-nitrosylation, and succination, all of which modify protein function or turnover in response to a changing intracellular redox environment. Succination is a chemical modification of cysteine in proteins by the Krebs cycle intermediate, fumarate, yielding S-(2-succino)cysteine (2SC). Intracellular fumarate concentration and succination of proteins are increased by hyperpolarization of the inner mitochondrial membrane, in concert with mitochondrial, endoplasmic reticulum (ER) and oxidative stress in 3T3 adipocytes grown in high glucose medium and in adipose tissue in obesity and diabetes in mice. Increased succination of proteins is also detected in the kidney of a fumarase deficient conditional knock-out mouse which develops renal cysts. A wide range of proteins are subject to succination, including enzymes, adipokines, cytoskeletal proteins, and ER chaperones with functional cysteine residues. There is also some overlap between succinated and glutathionylated proteins, suggesting that the same low pKa thiols are targeted by both. Succination of adipocyte proteins in diabetes increases as a result of nutrient excess derived mitochondrial stress and this is inhibited by uncouplers, which discharge the mitochondrial membrane potential (ΔΨm) and relieve the electron transport chain. 2SC therefore serves as a biomarker of mitochondrial stress or dysfunction in chronic diseases, such as obesity, diabetes, and cancer, and recent studies suggest that succination is a mechanistic link between mitochondrial dysfunction, oxidative and ER stress, and cellular progression toward apoptosis. In this article, we review the history of the succinated proteome and the challenges associated with measuring this non-enzymatic PTM of proteins by proteomics approaches.

Metabolic reprogramming during purine stress in the protozoan pathogen Leishmania donovani

The ability of Leishmania to survive in their insect or mammalian host is dependent upon an ability to sense and adapt to changes in the microenvironment. However, little is known about the molecular mechanisms underlying the parasite response to environmental changes, such as nutrient availability. To elucidate nutrient stress response pathways in Leishmania donovani, we have used purine starvation as the paradigm. The salvage of purines from the host milieu is obligatory for parasite replication; nevertheless, purine-starved parasites can persist in culture without supplementary purine for over three months, indicating that the response to purine starvation is robust and engenders parasite survival under conditions of extreme scarcity. To understand metabolic reprogramming during purine starvation we have employed global approaches. Whole proteome comparisons between purine-starved and purine-replete parasites over a 6–48 h span have revealed a temporal and coordinated response to purine starvation. Purine transporters and enzymes involved in acquisition at the cell surface are upregulated within a few hours of purine removal from the media, while other key purine salvage components are upregulated later in the time-course and more modestly. After 48 h, the proteome of purine-starved parasites is extensively remodeled and adaptations to purine stress appear tailored to deal with both purine deprivation and general stress. To probe the molecular mechanisms affecting proteome remodeling in response to purine starvation, comparative RNA-seq analyses, qRT-PCR, and luciferase reporter assays were performed on purine-starved versus purine-replete parasites. While the regulation of a minority of proteins tracked with changes at the mRNA level, for many regulated proteins it appears that proteome remodeling during purine stress occurs primarily via translational and/or post-translational mechanisms.

Leishmania, the cause of a deadly spectrum of diseases in humans, surmounts a number of environmental challenges, including changes in the availability of salvageable nutrients, to successfully colonize its host. Adaptation to environmental stress is clearly of significance in parasite biology, but the underlying mechanisms are not well understood. To simulate the response to periodic nutrient scarcity in vivo, we have induced purine starvation in vitro. Purines are essential for growth and viability, and serve as the major energy currency of cells. Leishmania cannot synthesize purines and must salvage them from the surroundings. Extracellular purine depletion in culture induces a robust survival response in Leishmania, whereby growth arrests, but parasites persist for months. To profile the events that enable endurance of purine starvation, we used shotgun proteomics. Our data suggest that purine starvation induces extensive proteome remodeling, tailored to enhance purine capture and recycling, reduce energy expenditures, and maintain viability of the metabolically active, non-dividing population. Through global and targeted approaches, we reveal that proteome remodeling is multifaceted, and occurs through an array of responses at the mRNA, translational, and post-translational level. Our data provide one of the most inclusive views of adaptation to microenvironmental stress in Leishmania.

Automated data extraction from in situ protein-stable isotope probing studies

Protein-stable isotope probing (protein-SIP) has strong potential for revealing key metabolizing taxa in complex microbial communities. While most protein-SIP work to date has been performed under controlled laboratory conditions to allow extensive isotope labeling of the target organism(s), a key application will be in situ studies of microbial communities for short periods of time under natural conditions that result in small degrees of partial labeling. One hurdle restricting large-scale in situ protein-SIP studies is the lack of algorithms and software for automated data processing of the massive data sets resulting from such studies. In response, we developed Stable Isotope Probing Protein Extraction Resources software (SIPPER) and applied it for large-scale extraction and visualization of data from short-term (3 h) protein-SIP experiments performed in situ on phototrophic bacterial mats isolated from Yellowstone National Park. Several metrics incorporated into the software allow it to support exhaustive analysis of the complex composite isotopic envelope observed as a result of low amounts of partial label incorporation. SIPPER also enables the detection of labeled molecular species without the need for any prior identification.

Advancing the high throughput identification of liver fibrosis protein signatures using multiplexed ion mobility spectrometry

Rapid diagnosis of disease states using less invasive, safer, and more clinically acceptable approaches than presently employed is a crucial direction for the field of medicine. While MS-based proteomics approaches have attempted to meet these objectives, challenges such as the enormous dynamic range of protein concentrations in clinically relevant biofluid samples coupled with the need to address human biodiversity have slowed their employment. Herein, we report on the use of a new instrumental platform that addresses these challenges by coupling technical advances in rapid gas phase multiplexed ion mobility spectrometry separations with liquid chromatography and MS to dramatically increase measurement sensitivity and throughput, further enabling future high throughput MS-based clinical applications. An initial application of the liquid chromatography--ion mobility spectrometry-MS platform analyzing blood serum samples from 60 postliver transplant patients with recurrent fibrosis progression and 60 nontransplant patients illustrates its potential utility for disease characterization.

Proteomic profiling of exosomes leads to the identification of novel biomarkers for prostate cancer

BACKGROUND

Current markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, the complexity of body fluids often hampers biomarker discovery. An attractive alternative approach is the isolation of small vesicles, i.e. exosomes, ∼100 nm, which contain proteins that are specific to the tissue from which they are derived and therefore can be considered as treasure chests for disease-specific biomarker discovery.

MATERIALS AND METHODS

Exosomes were isolated from 2 immortalized primary prostate epithelial cells (PNT2C2 and RWPE-1) and 2 PCa cell lines (PC346C and VCaP) by ultracentrifugation. After tryptic digestion, proteomic analyses utilized a nanoLC coupled with an LTQ-Orbitrap operated in tandem MS (MS/MS) mode. Accurate Mass and Time (AMT) tag approach was employed for peptide identification and quantitation. Candidate biomarkers were validated by Western blotting and Immunohistochemistry.

RESULTS

Proteomic characterization resulted in the identification of 248, 233, 169, and 216 proteins by at least 2 peptides in exosomes from PNT2C2, RWPE-1, PC346C, and VCaP, respectively. Statistical analyses revealed 52 proteins differently abundant between PCa and control cells, 9 of which were more abundant in PCa. Validation by Western blotting confirmed a higher abundance of FASN, XPO1 and PDCD6IP (ALIX) in PCa exosomes.

CONCLUSIONS

Identification of exosomal proteins using high performance LC-FTMS resulted in the discovery of PDCD6IP, FASN, XPO1 and ENO1 as new candidate biomarkers for prostate cancer.

Resin-assisted enrichment of thiols as a general strategy for proteomic profiling of cysteine-based reversible modifications

Reversible modifications of cysteine thiols have a key role in redox signaling and regulation. A number of reversible redox modifications, including disulfide formation, S-nitrosylation (SNO) and S-glutathionylation (SSG), have been recognized for their significance in various physiological and pathological processes. Here we describe a procedure for the enrichment of peptides containing reversible cysteine modifications. Starting with tissue or cell lysate samples, all of the unmodified free thiols are blocked using N-ethylmaleimide (NEM). This is followed by the selective reduction of those cysteines bearing the reversible modification(s) of interest. The reduction is achieved by using different reducing reagents that react specifically with each type of cysteine modification (e.g., ascorbate for SNO). This protocol serves as a general approach for enrichment of thiol-containing proteins or peptides derived from reversibly modified proteins. The approach uses a commercially available thiol-affinity resin (thiopropyl Sepharose 6B) to directly capture free thiol-containing proteins through a disulfide exchange reaction, followed by on-resin protein digestion and multiplexed isobaric labeling to facilitate liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based quantitative site-specific analysis of cysteine-based reversible modifications. The overall approach requires a simpler workflow with increased specificity compared with the commonly used biotinylation-based assays. The procedure for selective enrichment and analyses of SNO and the level of total reversible cysteine modifications (or total oxidation) is presented to demonstrate the utility of this general strategy. The entire protocol requires ∼3 d for sample processing with an additional day for LC-MS/MS and data analysis.

Proteomic and transcriptomic analyses of "Candidatus Pelagibacter ubique" describe the first PII-independent response to nitrogen limitation in a free-living Alphaproteobacterium

Nitrogen is one of the major nutrients limiting microbial productivity in the ocean, and as a result, most marine microorganisms have evolved systems for responding to nitrogen stress. The highly abundant alphaproteobacterium "Candidatus Pelagibacter ubique," a cultured member of the order Pelagibacterales (SAR11), lacks the canonical GlnB, GlnD, GlnK, and NtrB/NtrC genes for regulating nitrogen assimilation, raising questions about how these organisms respond to nitrogen limitation. A survey of 266 Alphaproteobacteria genomes found these five regulatory genes nearly universally conserved, absent only in intracellular parasites and members of the order Pelagibacterales, including "Ca. Pelagibacter ubique." Global differences in mRNA and protein expression between nitrogen-limited and nitrogen-replete cultures were measured to identify nitrogen stress responses in "Ca. Pelagibacter ubique" strain HTCC1062. Transporters for ammonium (AmtB), taurine (TauA), amino acids (YhdW), and opines (OccT) were all elevated in nitrogen-limited cells, indicating that they devote increased resources to the assimilation of nitrogenous organic compounds. Enzymes for assimilating amine into glutamine (GlnA), glutamate (GltBD), and glycine (AspC) were similarly upregulated. Differential regulation of the transcriptional regulator NtrX in the two-component signaling system NtrY/NtrX was also observed, implicating it in control of the nitrogen starvation response. Comparisons of the transcriptome and proteome supported previous observations of uncoupling between transcription and translation in nutrient-deprived "Ca. Pelagibacter ubique" cells. Overall, these data reveal a streamlined, PII-independent response to nitrogen stress in "Ca. Pelagibacter ubique," and likely other Pelagibacterales, and show that they respond to nitrogen stress by allocating more resources to the assimilation of nitrogen-rich organic compounds.

IMPORTANCE

Pelagibacterales are extraordinarily abundant and play a pivotal role in marine geochemical cycles, as one of the major recyclers of labile dissolved organic matter. They are also models for understanding how streamlining selection can reshape chemoheterotroph metabolism. Streamlining and its broad importance to environmental microbiology are emerging slowly from studies that reveal the complete genomes of uncultured organisms. Here, we report another remarkable example of streamlined metabolism in Pelagibacterales, this time in systems that control nitrogen assimilation. Pelagibacterales are major contributors to metatranscriptomes and metaproteomes from ocean systems, where patterns of gene expression are used to gain insight into ocean conditions and geochemical cycles. The data presented here supply background that is essential to interpreting data from field studies.

Increasing Confidence of LC-MS Identifications by Utilizing Ion Mobility Spectrometry

Ion mobility spectrometry in conjunction with liquid chromatography separations and mass spectrometry offers a range of new possibilities for analyzing complex biological samples. To fully utilize the information obtained from these three measurement dimensions, informatics tools based on the accurate mass and time tag methodology were modified to incorporate ion mobility spectrometry drift times for peptides observed in human serum. In this work a reference human serum database was created for 12,139 peptides and populated with the monoisotopic mass, liquid chromatography normalized elution time, and ion mobility spectrometry drift time(s) for each. We demonstrate that the use of three dimensions for peak matching during the peptide identification process resulted in an increased numbers of identifications and a lower false discovery rate relative to only using the mass and normalized elution time dimensions.