A label free quantitative proteomic analysis of the Saccharomyces cerevisiae nucleus

Zika virus NS1 drives tunneling nanotube formation for mitochondrial transfer and stealth transmission in trophoblasts

Zika virus (ZIKV) is unique among orthoflaviviruses in its vertical transmission capacity in humans, yet the underlying mechanisms remain incompletely understood. Here, we show that ZIKV induces tunneling nanotubes (TNTs) in placental trophoblasts which facilitate transfer of viral particles, proteins, mitochondria, and RNA to neighboring uninfected cells. TNT formation is driven exclusively via ZIKV non-structural protein 1 (NS1). Specifically, the N-terminal 1-50 amino acids of membrane-bound ZIKV NS1 are necessary for triggering TNT formation in host cells. Trophoblasts infected with TNT-deficient ZIKVΔTNT mutant virus elicited a robust antiviral IFN-λ 1/2/3 response relative to WT ZIKV, suggesting TNT-mediated trafficking allows ZIKV cell-to-cell transmission camouflaged from host defenses. Using affinity purification-mass spectrometry of cells expressing wild-type NS1 or non-TNT forming NS1, we found mitochondrial proteins are dominant NS1-interacting partners. We demonstrate that ZIKV infection or NS1 expression induces elevated mitochondria levels in trophoblasts and that mitochondria are siphoned via TNTs from healthy to ZIKV-infected cells. Together our findings identify a stealth mechanism that ZIKV employs for intercellular spread among placental trophoblasts, evasion of antiviral interferon response, and the hijacking of mitochondria to augment its propagation and survival and offers a basis for novel therapeutic developments targeting these interactions to limit ZIKV dissemination.

Osteomacs promote maintenance of murine hematopoiesis through megakaryocyte-induced upregulation of Embigin and CD166

Maintenance of hematopoietic stem cell (HSC) function in the niche is an orchestrated event. Osteomacs (OM) are key cellular components of the niche. Previously, we documented that osteoblasts, OM, and megakaryocytes interact to promote hematopoiesis. Here, we further characterize OM and identify megakaryocyte-induced mediators that augment the role of OM in the niche. Single-cell mRNA-seq, mass spectrometry, and CyTOF examination of megakaryocyte-stimulated OM suggested that upregulation of CD166 and Embigin on OM augment their hematopoiesis maintenance function. CD166 knockout OM or shRNA-Embigin knockdown OM confirmed that the loss of these molecules significantly reduced the ability of OM to augment the osteoblast-mediated hematopoietic-enhancing activity. Recombinant CD166 and Embigin partially substituted for OM function, characterizing both proteins as critical mediators of OM hematopoietic function. Our data identify Embigin and CD166 as OM-regulated critical components of HSC function in the niche and potential participants in various in vitro manipulations of stem cells.

Zika Virus NS1 Drives Tunneling Nanotube Formation for Mitochondrial Transfer, Enhanced Survival, Interferon Evasion, and Stealth Transmission in Trophoblasts

Zika virus (ZIKV) infection continues to pose a significant public health concern due to limited available preventive measures and treatments. ZIKV is unique among flaviviruses in its vertical transmission capacity (i.e., transmission from mother to fetus) yet the underlying mechanisms remain incompletely understood. Here, we show that both African and Asian lineages of ZIKV induce tunneling nanotubes (TNTs) in placental trophoblasts and multiple other mammalian cell types. Amongst investigated flaviviruses, only ZIKV strains trigger TNTs. We show that ZIKV-induced TNTs facilitate transfer of viral particles, proteins, and RNA to neighboring uninfected cells. ZIKV TNT formation is driven exclusively via its non-structural protein 1 (NS1); specifically, the N-terminal region (50 aa) of membrane-bound NS1 is necessary and sufficient for triggering TNT formation in host cells. Using affinity purification-mass spectrometry of cells infected with wild-type NS1 or non-TNT forming NS1 (pNS1ΔTNT) proteins, we found mitochondrial proteins are dominant NS1-interacting partners, consistent with the elevated mitochondrial mass we observed in infected trophoblasts. We demonstrate that mitochondria are siphoned via TNTs from healthy to ZIKV-infected cells, both homotypically and heterotypically, and inhibition of mitochondrial respiration reduced viral replication in trophoblast cells. Finally, ZIKV strains lacking TNT capabilities due to mutant NS1 elicited a robust antiviral IFN-λ 1/2/3 response, indicating ZIKV's TNT-mediated trafficking also allows ZIKV cell-cell transmission that is camouflaged from host defenses. Together, our findings identify a new stealth mechanism that ZIKV employs for intercellular spread among placental trophoblasts, evasion of antiviral interferon response, and the hijacking of mitochondria to augment its propagation and survival. Discerning the mechanisms of ZIKV intercellular strategies offers a basis for novel therapeutic developments targeting these interactions to limit its dissemination.

Preparative capillary electrophoresis (CE) fractionation of protein digests improves protein and peptide identification in bottom-up proteomics

Reversed-phase liquid chromatography (RPLC) is widely used to reduce sample complexity prior to mass spectrometry (MS) analysis in bottom-up proteomics. Improving peptide separation in complex samples enables lower-abundance proteins to be identified. Multidimensional separations that combine orthogonal separation modes improve protein and peptide identifications over RPLC alone. Here we report a preparative capillary electrophoresis (CE) fractionation method that combines CE and RPLC separations. Using this method, we demonstrate improved protein and peptide identification in a tryptic digest of E. coli cell lysate, with 132 ± 33% more protein identifications and 185 ± 65% more peptide identifications over non-fractionated samples. Fractionation enables detection of lower-abundance proteins in this complex sample. We demonstrate improved coverage of ovarian cancer biomarker MUC16 isolated from conditioned cell media, with 6.73% sequence coverage using CE fractionation compared to 2.74% coverage without preparative fractionation. This new method will allow researchers performing bottom-up proteomics to harness the advantages of CE separations while using widely available LC-MS/MS instrumentation.

Discovering the N-Terminal Methylome by Repurposing of Proteomic Datasets

Protein α-N-methylation is an underexplored post-translational modification involving the covalent addition of methyl groups to the free α-amino group at protein N-termini. To systematically explore the extent of α-N-terminal methylation in yeast and humans, we reanalyzed publicly accessible proteomic datasets to identify N-terminal peptides contributing to the α-N-terminal methylome. This repurposing approach found evidence of α-N-methylation of established and novel protein substrates with canonical N-terminal motifs of established α-N-terminal methyltransferases, including human NTMT1/2 and yeast Tae1. NTMT1/2 are implicated in cancer and aging processes but have unclear and context-dependent roles. Moreover, α-N-methylation of noncanonical sequences was surprisingly prevalent, suggesting unappreciated and cryptic methylation events. Analysis of the amino acid frequencies of α-N-methylated peptides revealed a [S]1-[S/A/Q]2 pattern in yeast and [A/N/G]1-[A/S/V]2-[A/G]3 in humans, which differs from the canonical motif. We delineated the distribution of the two types of prevalent N-terminal modifications, acetylation and methylation, on amino acids at the first position. We tested three potentially methylated proteins and confirmed the α-N-terminal methylation of Hsp31 by additional proteomic analysis and immunoblotting. The other two proteins, Vma1 and Ssa3, were found to be predominantly acetylated, indicating that proteomic searching for α-N-terminal methylation requires careful consideration of mass spectra. This study demonstrates the feasibility of reprocessing proteomic data for global α-N-terminal methylome investigations.

Phenotypic and functional variation in venom and venom resistance of two sympatric rattlesnakes and their prey

Predator-prey interactions often lead to the coevolution of adaptations associated with avoiding predation and, for predators, overcoming those defences. Antagonistic coevolutionary relationships are often not simple interactions between a single predator and prey but rather a complex web of interactions between multiple coexisting species. Coevolution between venomous rattlesnakes and small mammals has led to physiological venom resistance in several mammalian taxa. In general, viperid venoms contain large quantities of snake venom metalloproteinase toxins (SVMPs), which are inactivated by SVMP inhibitors expressed in resistant mammals. We explored variation in venom chemistry, SVMP expression, and SVMP resistance across four co-distributed species (California Ground Squirrels, Bryant's Woodrats, Southern Pacific Rattlesnakes, and Red Diamond Rattlesnakes) collected from four different populations in Southern California. Our aim was to understand phenotypic and functional variation in venom and venom resistance in order to compare coevolutionary dynamics of a system involving two sympatric predator-prey pairs to past studies that have focused on single pairs. Proteomic analysis of venoms indicated that these rattlesnakes express different phenotypes when in sympatry, with Red Diamonds expressing more typical viperid venom (with a diversity of SVMPs) and Southern Pacifics expressing a more atypical venom with a broader range of non-enzymatic toxins. We also found that although blood sera from both mammals were generally able to inhibit SVMPs from both rattlesnake species, inhibition depended strongly on the snake population, with snakes from one geographic site expressing SVMPs to which few mammals were resistant. Additionally, we found that Red Diamond venom, rather than woodrat resistance, was locally adapted. Our findings highlight the complexity of coevolutionary relationships between multiple predators and prey that exhibit similar offensive and defensive strategies in sympatry.

A proteome-integrated, carbon source dependent genetic regulatory network in Saccharomyces cerevisiae

Integrated regulatory networks can be powerful tools to examine and test properties of cellular systems, such as modelling environmental effects on the molecular bioeconomy, where protein levels are altered in response to changes in growth conditions. Although extensive regulatory pathways and protein interaction data sets exist which represent such networks, few have formally considered quantitative proteomics data to validate and extend them. We generate and consider such data here using a label-free proteomics strategy to quantify alterations in protein abundance for S. cerevisiae when grown on minimal media using glucose, galactose, maltose and trehalose as sole carbon sources. Using a high quality-controlled subset of proteins observed to be differentially abundant, we constructed a proteome-informed network, comprising 1850 transcription factor interactions and 37 chaperone interactions, which defines the major changes in the cellular proteome when growing under different carbon sources. Analysis of the differentially abundant proteins involved in the regulatory network pointed to their significant roles in specific metabolic pathways and function, including glucose homeostasis, amino acid biosynthesis, and carbohydrate metabolic process. We noted strong statistical enrichment in the differentially abundant proteome of targets of known transcription factors associated with stress responses and altered carbon metabolism. This shows how such integrated analysis can lend further experimental support to annotated regulatory interactions, since the proteomic changes capture both magnitude and direction of gene expression change at the level of the affected proteins. Overall this study highlights the power of quantitative proteomics to help define regulatory systems pertinent to environmental conditions.

Mutant thermal proteome profiling for characterization of missense protein variants and their associated phenotypes within the proteome

Temperature-sensitive (TS) missense mutants have been foundational for characterization of essential gene function. However, an unbiased approach for analysis of biochemical and biophysical changes in TS missense mutants within the context of their functional proteomes is lacking. We applied MS-based thermal proteome profiling (TPP) to investigate the proteome-wide effects of missense mutations in an application that we refer to as mutant thermal proteome profiling (mTPP). This study characterized global impacts of temperature sensitivity-inducing missense mutations in two different subunits of the 26S proteasome. The majority of alterations identified by RNA-Seq and global proteomics were similar between the mutants, which could suggest that a similar functional disruption is occurring in both missense variants. Results from mTPP, however, provide unique insights into the mechanisms that contribute to the TS phenotype in each mutant, revealing distinct changes that were not obtained using only steady-state transcriptome and proteome analyses. Computationally, multisite λ-dynamics simulations add clear support for mTPP experimental findings. This work shows that mTPP is a precise approach to measure changes in missense mutant-containing proteomes without the requirement for large amounts of starting material, specific antibodies against proteins of interest, and/or genetic manipulation of the biological system. Although experiments were performed under permissive conditions, mTPP provided insights into the underlying protein stability changes that cause dramatic cellular phenotypes observed at nonpermissive temperatures. Overall, mTPP provides unique mechanistic insights into missense mutation dysfunction and connection of genotype to phenotype in a rapid, nonbiased fashion.

Identification and Characterization of Edible Cricket Peptides on Hypertensive and Glycemic In Vitro Inhibition and Their Anti-Inflammatory Activity on RAW 264.7 Macrophage Cells

Recent studies continue to demonstrate the potential of edible insects as a protein base to obtain bioactive peptides applicable for functional food development. This study aimed at identifying antihypertensive, anti-glycemic, and anti-inflammatory peptides derived from the in vitro gastrointestinal digests of cricket protein hydrolysates. After sequential fractionation, the protein digest subfraction containing the lowest molecular weight (<0.5 kDa), hydrophobic (C18) and cationic peptides (IEX) was found responsible for the most bioactivity. The cationic peptide fraction significantly reduced (p < 0.05) α-amylase, α-glucosidase, and angiotensin converting enzyme (ACE) activity in vitro, and also inhibited the expression of NF-κB in RAW 264.7 macrophage cells. A total of 28 peptides were identified with mass spectrometry (LC–MS/MS) and de novo sequencing from the potent fraction. Three novel peptides YKPRP, PHGAP, and VGPPQ were chosen for the molecular docking studies. PHGAP and VGPPQ exhibited a higher degree of non-covalent interactions with the enzyme active site residues and binding energies comparable to captopril. Results from this study demonstrate the bioactive potential of edible cricket peptides, especially as ACE inhibitors.

A Quantitative Global Proteomics Approach Identifies Candidate Urinary Biomarkers That Correlate With Intraductal Papillary Mucinous Neoplasm Dysplasia

OBJECTIVES

A proteomic discovery study was performed to determine if urine possesses a unique biosignature that could form the basis for a noninvasive test able to predict intraductal papillary mucinous neoplasm (IPMN) dysplasia.

METHODS

Urine was collected from patients undergoing surgery for IPMN (72 low/moderate, 27 high-grade/invasive). Quantitative mass spectrometry-based proteomics was performed. Proteins of interest were identified by differential expression analysis followed by principal component analysis.

RESULTS

Proteomics identified greater than 4800 urinary proteins. Low/moderate and high-grade/invasive IPMN were distinguished by 188 proteins (P < 0.05). Following principal component analysis and heatmap visualization, vitamin D binding protein (DBP), apolipoprotein A1 (APOA1), and alpha-1 antitrypsin (A1AT) were selected. The proteomic abundance of DBP (median [interquartile range]) was significantly higher for high-grade/invasive than for low/moderate IPMN (219,735 [128,882-269,943] vs. 112,295 [77,905-180,773] normalized reporter ion intensity units; P = 0.001). Similarly, APOA1 was more abundant in the high-grade/invasive than low/moderate groups (235,420 [144,933-371,247] vs 150,095 [103,419-236,591]; P = 0.0007) as was A1AT (567,514 [358,544-774,801] vs 358,393 [260,850-477,882]; P = 0.0006).

CONCLUSIONS

Urinary DBP, APOA1, and A1AT represent potential biomarker candidates that may provide a noninvasive means of predicting IPMN dysplastic grade.

Cross-linking Mass Spectrometry Analysis of the Yeast Nucleus Reveals Extensive Protein-Protein Interactions Not Detected by Systematic Two-Hybrid or Affinity Purification-Mass Spectrometry

Saccharomyces cerevisiae has the most comprehensively characterized protein-protein interaction network, or interactome, of any eukaryote. This has predominantly been generated through multiple, systematic studies of protein-protein interactions by two-hybrid techniques and of affinity-purified protein complexes. A pressing question is to understand how large-scale cross-linking mass spectrometry (XL-MS) can confirm and extend this interactome. Here, intact yeast nuclei were subject to cross-linking with disuccinimidyl sulfoxide (DSSO) and analyzed using hybrid MS2-MS3 methods. XlinkX identified a total of 2,052 unique residue pair cross-links at 1% FDR. Intraprotein cross-links were found to provide extensive structural constraint data, with almost all intralinks that mapped to known structures and slightly fewer of those mapping to homology models being within 30 Å. Intralinks provided structural information for a further 366 proteins. A method for optimizing interprotein cross-link score cut-offs was developed, through use of extensive known yeast interactions. Its application led to a high confidence, yeast nuclear interactome. Strikingly, almost half of the interactions were not previously detected by two-hybrid or AP-MS techniques. Multiple lines of evidence existed for many such interactions, whether through literature or ortholog interaction data, through multiple unique interlinks between proteins, and/or through replicates. We conclude that XL-MS is a powerful means to measure interactions, that complements two-hybrid and affinity-purification techniques.

Quantitative phosphoproteomic analysis identifies novel functional pathways of tumor suppressor DLC1 in estrogen receptor positive breast cancer

Deleted in Liver Cancer-1 (DLC1), a member of the RhoGAP family of proteins, functions as a tumor suppressor in several cancers including breast cancer. However, its clinical relevance is unclear in breast cancer. In this study, expression of DLC1 was correlated with prognosis using publicly available breast cancer gene expression datasets and quantitative Reverse Transcription PCR in cohorts of Estrogen Receptor-positive (ER+) breast cancer. Low expression of DLC1 correlates with poor prognosis in patients with ER+ breast cancer with further decrease in metastatic lesions. The Cancer Genome Atlas (TCGA) data showed that down regulation of DLC1 is not due to methylation or mutations. To seek further insights in understanding the role of DLC1 in ER+ breast cancer, we stably overexpressed DLC1-full-length (DLC1-FL) in T-47D breast cancer cells; this inhibited cell colony formation significantly in vitro compared to its control counterpart. Label-free global proteomic and TiO2 phosphopeptide enrichment assays (ProteomeXchange identifier PXD008220) showed that 205 and 122 phosphopeptides were unique to DLC1-FL cells and T-47D-control cells, respectively, whereas 6,726 were quantified by phosphoproteomics analysis in both conditions. The top three significant clusters of differentially phosphopeptides identified by DAVID pathway analysis represent cell-cell adhesion, mRNA processing and splicing, and transcription regulation. Phosphoproteomics analysis documented an inverse relation between DLC1 expression and several phosphopeptides including epithelial cell transforming sequence 2 (ECT2). Decreased phosphorylation of ECT2 at the residue T359, critical for its active conformational change, was validated by western blot. In addition, the ECT2 T359-containing phosphopeptide was detected in both basal and luminal patient-derived breast cancers breast cancer phosphoproteomics data on the Clinical Proteomic Tumor Analysis Consortium (CPTAC) Assay portal. Together, for the first time, this implicates ECT2 phosphorylation in breast cancer, which has been proposed as a therapeutic target in lung cancer. In conclusion, this data suggests that low expression of DLC1 is associated with poor prognosis. Targeting ECT2 phosphopeptides could provide a promising mechanism for controlling poor prognosis seen in DLC1low ER+ breast cancer.

The human cytoplasmic dynein interactome reveals novel activators of motility

In human cells, cytoplasmic dynein-1 is essential for long-distance transport of many cargos, including organelles, RNAs, proteins, and viruses, towards microtubule minus ends. To understand how a single motor achieves cargo specificity, we identified the human dynein interactome by attaching a promiscuous biotin ligase (‘BioID’) to seven components of the dynein machinery, including a subunit of the essential cofactor dynactin. This method reported spatial information about the large cytosolic dynein/dynactin complex in living cells. To achieve maximal motile activity and to bind its cargos, human dynein/dynactin requires ‘activators’, of which only five have been described. We developed methods to identify new activators in our BioID data, and discovered that ninein and ninein-like are a new family of dynein activators. Analysis of the protein interactomes for six activators, including ninein and ninein-like, suggests that each dynein activator has multiple cargos.

DOI:http://dx.doi.org/10.7554/eLife.28257.001

Deciphering lymphoma pathogenesis via state-of-the-art mass spectrometry-based quantitative proteomics

Mass spectrometry-based quantitative proteomics specifically applied to comprehend the pathogenesis of lymphoma has incremental value in deciphering the heterogeneity in complex deregulated molecular mechanisms/pathways of the lymphoma entities, implementing the current diagnostic and therapeutic strategies. Essential global, targeted and functional differential proteomics analyses although still evolving, have been successfully implemented to shed light on lymphoma pathogenesis to discover and explore the role of potential lymphoma biomarkers and drug targets. This review aims to outline and appraise the present status of MS-based quantitative proteomic approaches in lymphoma research, introducing the current state-of-the-art MS-based proteomic technologies, the opportunities they offer in biological discovery in human lymphomas and the related limitation issues arising from sample preparation to data evaluation. It is a synopsis containing information obtained from recent research articles, reviews and public proteomics repositories (PRIDE). We hope that this review article will aid, assimilate and assess all the information aiming to accelerate the development and validation of diagnostic, prognostic or therapeutic targets for an improved and empowered clinical proteomics application in lymphomas in the nearby future.

Characterizing the nuclear proteome of Paracoccidioides spp

Paracoccidioidomycosis is an endemic disease in Latin America, caused by thermo dimorphic fungi of the genus Paracoccidioides. Although previous proteome analyses of Paracoccidioides spp. have been carried out, the nuclear subproteome of this pathogen has not been described. In this way, we aimed to characterize the nuclear proteome of Paracoccidioides species, in the yeast form. For that, yeast cells were disrupted and submitted to cell fractionation. The purity of the nuclear fraction was confirmed by fluorescence and electron microscopy. Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) allowed the identification of 867 proteins. In order to support our enrichment method for nuclear proteins, bioinformatics analysis were applied that allowed the identification of 281 proteins with nuclear localization. The analysis revealed proteins related to DNA maintenance, gene expression, synthesis and processing of messenger and ribosomal RNAs, likewise proteins of nuclear-cytoplasmic traffic. It was also possible to detect some proteins that are poorly expressed, like transcription factors involved in important roles such as resistance to abiotic stress, sporulation, cellular growth and DNA and chromatin maintenance. This is the first descriptive nuclear proteome of Paracoccidioides spp. that can be useful as an important platform base for fungi-specific nuclear processes.

Effects of low temperature on tropical and temperate isolates of marine Synechococcus

Temperature is an important factor influencing the distribution of marine picocyanobacteria. However, molecular responses contributing to temperature preferences are poorly understood in these important primary producers. We compared the temperature acclimation of a tropical Synechococcus strain WH8102 with temperate strain BL107 at 18 °C relative to 22 °C and examined their global protein expression, growth patterns, photosynthetic efficiency and lipid composition. Global protein expression profiles demonstrate the partitioning of the proteome into major categories: photosynthesis (>40%), translation (10-15%) and membrane transport (2-8%) with distinct differences between and within strains grown at different temperatures. At low temperature, growth and photosynthesis of strain WH8102 was significantly decreased, while BL107 was largely unaffected. There was an increased abundance of proteins involved in protein biosynthesis at 18 °C for BL107. Each strain showed distinct differences in lipid composition with higher unsaturation in strain BL107. We hypothesize that differences in membrane fluidity, abundance of protein biosynthesis machinery and the maintenance of photosynthesis efficiency contribute to the acclimation of strain BL107 to low temperature. Additional proteins unique to BL107 may also contribute to this strain's improved fitness at low temperature. Such adaptive capacities are likely important factors favoring growth of temperate strains over tropical strains in high latitude niches.

Label-Free Quantitative Proteomics in Yeast

Label-free bottom-up shotgun MS-based proteomics is an extremely powerful and simple tool to provide high quality quantitative analyses of the yeast proteome with only microgram amounts of total protein. Although the experimental design of this approach is rather straightforward and does not require the modification of growth conditions, proteins or peptides, several factors must be taken into account to benefit fully from the power of this method. Key factors include the choice of an appropriate method for the preparation of protein extracts, careful evaluation of the instrument design and available analytical capabilities, the choice of the quantification method (intensity-based vs. spectral count), and the proper manipulation of the selected quantification algorithm. The elaboration of this robust workflow for data acquisition, processing, and analysis provides unprecedented insight into the dynamics of the yeast proteome.

The Nuclear Proteome of a Vertebrate

The composition of the nucleoplasm determines the behavior of key processes such as transcription, yet there is still no reliable and quantitative resource of nuclear proteins. Furthermore, it is still unclear how the distinct nuclear and cytoplasmic compositions are maintained. To describe the nuclear proteome quantitatively, we isolated the large nuclei of frog oocytes via microdissection and measured the nucleocytoplasmic partitioning of ∼9,000 proteins by mass spectrometry. Most proteins localize entirely to either nucleus or cytoplasm; only ∼17% partition equally. A protein's native size in a complex, but not polypeptide molecular weight, is predictive of localization: partitioned proteins exhibit native sizes larger than ∼100 kDa, whereas natively smaller proteins are equidistributed. To evaluate the role of nuclear export in maintaining localization, we inhibited Exportin 1. This resulted in the expected re-localization of proteins toward the nucleus, but only 3% of the proteome was affected. Thus, complex assembly and passive retention, rather than continuous active transport, is the dominant mechanism for the maintenance of nuclear and cytoplasmic proteomes.

Assessment of a method to characterize antibody selectivity and specificity for use in immunoprecipitation

Antibodies are used in multiple cell biology applications, but there are no standardized methods to assess antibody quality-an absence that risks data integrity and reproducibility. We describe a mass spectrometry-based standard operating procedure for scoring immunoprecipitation antibody quality. We quantified the abundance of all the proteins in immunoprecipitates of 1,124 new recombinant antibodies for 152 chromatin-related human proteins by comparing normalized spectral abundance factors from the target antigen with those of all other proteins. We validated the performance of the standard operating procedure in blinded studies in five independent laboratories. Antibodies for which the target antigen or a member of its known protein complex was the most abundant protein were classified as 'IP gold standard'. This method generates quantitative outputs that can be stored and archived in public databases, and it represents a step toward a platform for community benchmarking of antibody quality.

MS1-based label-free proteomics using a quadrupole orbitrap mass spectrometer

Presented is a data set for benchmarking MS1-based label-free quantitative proteomics using a quadrupole orbitrap mass spectrometer. Escherichia coli digest was spiked into a HeLa digest in four different concentrations, simulating protein expression differences in a background of an unchanged complex proteome. The data set provides a unique opportunity to evaluate the proteomic platform (instrumentation and software) in its ability to perform MS1-intensity-based label-free quantification. We show that the presented combination of informatics and instrumentation produces high precision and quantification accuracy. The data were also used to compare different quantitative protein inference methods such as iBAQ and Hi-N. The data can also be used as a resource for development and optimization of proteomics informatics tools, thus the raw data have been deposited to ProteomeXchange with identifier PXD001385.

Extracting, enriching, and identifying nuclear body sub-complexes using label-based quantitative mass spectrometry

Determining the proteome of a nuclear body is a crucial step toward understanding its function; however, it is extremely challenging to obtain pure nuclear body preparations. Moreover, many nuclear proteins dynamically associate with multiple bodies and subnuclear compartments, confounding analysis. We have found that a more practical approach is to carry out affinity purification of nuclear body sub-complexes via the use of tagged nuclear-body-specific marker proteins. Here we describe in detail the method to identify new nuclear body protein sub-complexes through SILAC (stable isotope labeling by amino acids in culture)-based affinity purification followed by quantitative mass spectrometry.

Proteomics of endosomal compartments from plants case study: isolation of trans-Golgi network vesicles

A detailed understanding of endomembrane processes and their biological roles is vital for a complete picture of plant growth and development; however their highly dynamic nature has complicated comprehensive and rigorous studies so far. Recent pioneering efforts have demonstrated that isolation of vesicles in their native state, paired with a quantitative identification of their cargo, offers a viable and practicable approach for the dissection of endomembrane trafficking pathways. The protocol presented in this chapter describes in detail the isolation of the SYP61 trans-Golgi network vesicles from Arabidopsis. With minor alterations, in a few key parameters, it can be adopted to yield a universal procedure for the broad spectrum of plant vesicles.

Crosstalk between mitochondrial stress signals regulates yeast chronological lifespan

Mitochondrial DNA (mtDNA) exists in multiple copies per cell and is essential for oxidative phosphorylation. Depleted or mutated mtDNA promotes numerous human diseases and may contribute to aging. Reduced TORC1 signaling in the budding yeast, Saccharomyces cerevisiae, extends chronological lifespan (CLS) in part by generating a mitochondrial ROS (mtROS) signal that epigenetically alters nuclear gene expression. To address the potential requirement for mtDNA maintenance in this response, we analyzed strains lacking the mitochondrial base-excision repair enzyme Ntg1p. Extension of CLS by mtROS signaling and reduced TORC1 activity, but not caloric restriction, was abrogated in ntg1Δ strains that exhibited mtDNA depletion without defects in respiration. The DNA damage response (DDR) kinase Rad53p, which transduces pro-longevity mtROS signals, is also activated in ntg1Δ strains. Restoring mtDNA copy number alleviated Rad53p activation and re-established CLS extension following mtROS signaling, indicating that Rad53p senses mtDNA depletion directly. Finally, DDR kinases regulate nucleus-mitochondria localization dynamics of Ntg1p. From these results, we conclude that the DDR pathway senses and may regulate Ntg1p-dependent mtDNA stability. Furthermore, Rad53p senses multiple mitochondrial stresses in a hierarchical manner to elicit specific physiological outcomes, exemplified by mtDNA depletion overriding the ability of Rad53p to transduce an adaptive mtROS longevity signal.

Discovery of novel disease-specific and membrane-associated candidate markers in a mouse model of multiple sclerosis

Multiple sclerosis is a chronic demyelinating disorder characterized by the infiltration of auto-reactive immune cells from the periphery into the central nervous system resulting in axonal injury and neuronal cell death. Experimental autoimmune encephalomyelitis represents the best characterized animal model as common clinical, histological, and immunological features are recapitulated. A label-free mass spectrometric proteomics approach was used to detect differences in protein abundance within specific fractions of disease-affected tissues including the soluble lysate derived from the spinal cord and membrane protein-enriched peripheral blood mononuclear cells. Tissues were harvested from actively induced experimental autoimmune encephalomyelitis mice and sham-induced ("vehicle" control) counterparts at the disease peak followed by subsequent analysis by nanoflow liquid chromatography tandem mass spectrometry. Relative protein quantitation was performed using both intensity- and fragmentation-based approaches. After statistical evaluation of the data, over 500 and 250 differentially abundant proteins were identified in the spinal cord and peripheral blood mononuclear cell data sets, respectively. More than half of these observations have not previously been linked to the disease. The biological significance of all candidate disease markers has been elucidated through rigorous literature searches, pathway analysis, and validation studies. Results from comprehensive targeted mass spectrometry analyses have confirmed the differential abundance of ∼ 200 candidate markers (≥ twofold dysregulated expression) at a 70% success rate. This study is, to our knowledge, the first to examine the cell-surface proteome of peripheral blood mononuclear cells in experimental autoimmune encephalomyelitis. These data provide a unique mechanistic insight into the dynamics of peripheral immune cell infiltration into CNS-privileged sites at a molecular level and has identified several candidate markers, which represent promising targets for future multiple sclerosis therapies. The mass spectrometry proteomics data associated with this manuscript have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000255.

Characterization, design, and function of the mitochondrial proteome: from organs to organisms

Mitochondria are a common energy source for organs and organisms; their diverse functions are specialized according to the unique phenotypes of their hosting environment. Perturbation of mitochondrial homeostasis accompanies significant pathological phenotypes. However, the connections between mitochondrial proteome properties and function remain to be experimentally established on a systematic level. This uncertainty impedes the contextualization and translation of proteomic data to the molecular derivations of mitochondrial diseases. We present a collection of mitochondrial features and functions from four model systems, including two cardiac mitochondrial proteomes from distinct genomes (human and mouse), two unique organ mitochondrial proteomes from identical genetic codons (mouse heart and mouse liver), as well as a relevant metazoan out-group (drosophila). The data, composed of mitochondrial protein abundance and their biochemical activities, capture the core functionalities of these mitochondria. This investigation allowed us to redefine the core mitochondrial proteome from organs and organisms, as well as the relevant contributions from genetic information and hosting milieu. Our study has identified significant enrichment of disease-associated genes and their products. Furthermore, correlational analyses suggest that mitochondrial proteome design is primarily driven by cellular environment. Taken together, these results connect proteome feature with mitochondrial function, providing a prospective resource for mitochondrial pathophysiology and developing novel therapeutic targets in medicine.

Protein changes in immunodepleted cerebrospinal fluid from a transgenic mouse model of Alexander disease detected using mass spectrometry

Cerebrospinal fluid (CSF) is a low protein content biological fluid with a dynamic range spanning at least 9 orders of magnitude in protein content and is in direct contact with the brain. A modified IgY-14 immunodepletion treatment was performed to enhance analysis of the low volumes of CSF that are obtainable from mice. As a model system in which to test this approach, we utilized transgenic mice that overexpress the intermediate filament glial fibrillary acidic protein (GFAP). These mice are models for Alexander disease (AxD), a severe leukodystrophy in humans. From the CSF of control and transgenic mice we report the identification of 289 proteins, with relative quantification of 103 proteins. Biological and technical triplicates were performed to address animal variability as well as reproducibility in mass spectrometric analysis. Relative quantitation was performed using distributive normalized spectral abundance factor (dNSAF) spectral counting analysis. A panel of biomarker proteins with significant changes in the CSF of GFAP transgenic mice has been identified with validation from enzyme-linked immunosorbent assay (ELISA) and microarray data, demonstrating the utility of our methodology and providing interesting targets for future investigations on the molecular and pathological aspects of AxD.

Label-free quantitative shotgun proteomics using normalized spectral abundance factors

In this chapter we describe the workflow used in our laboratory for label-free quantitative shotgun proteomics based on spectral counting. The main tools used are a series of R modules known collectively as the Scrappy program. We describe how to go from peptide to spectrum matching in a shotgun proteomics experiment using the XTandem algorithm, to simultaneous quantification of up to thousands of proteins, using normalized spectral abundance factors. The outputs of the software are described in detail, with illustrative examples provided for some of the graphical images generated. While it is not strictly within the scope of this chapter, some consideration is given to how best to extract meaningful biological information from quantitative shotgun proteomics data outputs.

Human family with sequence similarity 60 member A (FAM60A) protein: a new subunit of the Sin3 deacetylase complex

Here we describe the function of a previously uncharacterized protein, named family with sequence similarity 60 member A (FAM60A) that maps to chromosome 12p11 in humans. We use quantitative proteomics to determine that the main biochemical partners of FAM60A are subunits of the Sin3 deacetylase complex and show that FAM60A resides in active HDAC complexes. In addition, we conduct gene expression pathway analysis and find that FAM60A regulates expression of genes that encode components of the TGF-beta signaling pathway. Moreover, our studies reveal that loss of FAM60A or another component of the Sin3 complex, SDS3, leads to a change in cell morphology and an increase in cell migration. These studies reveal the function of a previously uncharacterized protein and implicate the Sin3 complex in suppressing cell migration.

Shotgun proteomic monitoring of Clostridium acetobutylicum during stationary phase of butanol fermentation using xylose and comparison with the exponential phase

Economically viable production of solvents through acetone–butanol–ethanol (ABE) fermentation requires a detailed understanding of Clostridium acetobutylicum. This study focuses on the proteomic profiling of C. acetobutylicum ATCC 824 from the stationary phase of ABE fermentation using xylose and compares with the exponential growth by shotgun proteomics approach. Comparative proteomic analysis revealed 22.9% of the C. acetobutylicum genome and 18.6% was found to be common in both exponential and stationary phases. The proteomic profile of C. acetobutylicum changed during the ABE fermentation such that 17 proteins were significantly differentially expressed between the two phases. Specifically, the expression of five proteins namely, CAC2873, CAP0164, CAP0165, CAC3298, and CAC1742 involved in the solvent production pathway were found to be significantly lower in the stationary phase compared to the exponential growth. Similarly, the expression of fucose isomerase (CAC2610), xylulose kinase (CAC2612), and a putative uncharacterized protein (CAC2611) involved in the xylose utilization pathway were also significantly lower in the stationary phase. These findings provide an insight into the metabolic behavior of C. acetobutylicum between different phases of ABE fermentation using xylose.

Recent advances on multidimensional liquid chromatography-mass spectrometry for proteomics: from qualitative to quantitative analysis--a review

With the acceleration of proteome research, increasing attention has been paid to multidimensional liquid chromatography-mass spectrometry (MDLC-MS) due to its high peak capacity and separation efficiency. Recently, many efforts have been put to improve MDLC-based strategies including "top-down" and "bottom-up" to enable highly sensitive qualitative and quantitative analysis of proteins, as well as accelerate the whole analytical procedure. Integrated platforms with combination of sample pretreatment, multidimensional separations and identification were also developed to achieve high throughput and sensitive detection of proteomes, facilitating highly accurate and reproducible quantification. This review summarized the recent advances of such techniques and their applications in qualitative and quantitative analysis of proteomes.

A metazoan ATAC acetyltransferase subunit that regulates mitogen-activated protein kinase signaling is related to an ancient molybdopterin synthase component

Molybdopterin (MPT) synthase is an essential enzyme involved in the synthesis of the molybdenum cofactor precursor molybdopterin. The molybdenum cofactor biosynthetic pathway is conserved from prokaryotes to Metazoa. CG10238 is the Drosophila homolog of the MoaE protein, a subunit of MPT synthase, and is found in a fusion with the mitogen-activated protein kinase (MAPK)-upstream protein kinase-binding inhibitory protein (MBIP). This fused protein inhibits the activation of c-Jun N-terminal kinase (JNK). dMoaE (CG10238) carries out this function as a subunit of the ATAC histone acetyltransferase complex. In this study, we demonstrate that Drosophila MoaE (CG10238) also interacts with Drosophila MoaD and with itself to form a complex with stoichiometry identical to the MPT synthase holoenzyme in addition to its function in ATAC. We also show that sequence determinants that regulate MAPK signaling are located within the MoaE region of dMoaE (CG10238). Analysis of other metazoan MBIPs reveals that MBIP protein sequences have an N-terminal region that appears to have been derived from the MoaE protein, although it has lost residues responsible for catalytic activity. Thus, intact and modified copies of the MoaE protein may have been conscripted to play a new, noncatalytic role in MAPK signaling in Metazoa as part of the ATAC complex.

Enabling technologies for yeast proteome analysis

Whilst the study of yeast genomes and transcriptomes is in an advanced state, there is still much to learn about the resulting proteins in terms of cataloging, characterization of post-translational modifications, turnover, and the dynamics of sub-cellular localization and interactions. Analysis of the transcripts gives little insight into function or diversity as changes in RNA levels do not always correlate with the resulting protein abundance. A number of global and targeted attempts have been made to catalog and characterize the yeast proteome and we describe here the methods used to gain a greater understanding of the yeast proteome. This comprehensive review also describes future approaches that will aid completion in identifying and characterizing the remaining 20% of the undetermined yeast proteome as well as giving new insight into protein dynamics.

Improving proteomics mass accuracy by dynamic offline lock mass

Several methods to obtain low-ppm mass accuracy have been described. In particular, online or offline lock mass approaches can use background ions, produced by electrospray under ambient conditions, as calibrants. However, background ions such as protonated and ammoniated polydimethylcyclosiloxane ions have relatively weak and fluctuating intensity. To address this issue, we implemented dynamic offline lock mass (DOLM). Within every MS1 survey spectrum, DOLM dynamically selected the strongest n background ions for statistical treatments and m/z recalibration. We systematically optimized the mass profile abstraction method to find one single m/z value to represent an ion and the number of calibrants. To assess the influence of the intensity of the analyte ions, we used tandem mass spectroscopy (MS/MS) datasets obtained from MudPIT analyses of two protein samples with different dynamic ranges. DOLM outperformed both external mass calibration and offline lock mass that used predetermined calibrant ions, especially in the low-ppm range. The unique dynamic feature of DOLM was able to adapt to wide variations in calibrant intensities, leading to averaged mass error center at 0.03 ± 0.50 ppm for precursor ions. Such consistently tight mass accuracies meant that a precursor mass tolerance as low as 1.5 ppm could be used to search or filter post-search DOLM-recalibrated MS/MS datasets.

Development of an off-line capillary column IMAC phosphopeptide enrichment method for label-free phosphorylation relative quantification

Immobilized metal affinity chromatography (IMAC) and metal oxide type affinity chromatography (MOAC) techniques have been widely used for mass spectrometry-based phosphorylation analysis. Unlike MOAC techniques, IMAC requires rather complete removals of buffering reagents, salts and high concentrations of denaturant prior to sample loading in order for the successful enrichment of phosphopeptides. In this study, a simple off-line capillary column-based IMAC phosphopeptide enrichment method can shorten sample preparation time by eliminating the speed-vac step from the desalting process. Tryptic digest peptide samples containing 2M urea can be directly processed and the entire IMAC procedure can be completed within 6 h. When tryptic digest peptide samples prepared from mouse whole brain tissues were analyzed using our method, an average of 249 phosphoproteins and 463 unique phosphopeptides were identified from single 2-h RPLC-MS/MS analysis (~88% specificity). An additional advantage of this method is the significantly improved reproducibility of the phosphopeptide enrichment results. When four independent phosphopeptide enrichment experiments were carried out, the peak areas of phosphopeptides identified among four enrichment experiments were relatively similar (less than 16.2% relative standard dev.). Because of this increased reproducibility, relative phosphorylation quantification analysis of major phosphoproteins appears to be feasible without the need for stable isotope labeling techniques.

Hemoglobin promotes Staphylococcus aureus nasal colonization

Staphylococcus aureus nasal colonization is an important risk factor for community and nosocomial infection. Despite the importance of S. aureus to human health, molecular mechanisms and host factors influencing nasal colonization are not well understood. To identify host factors contributing to nasal colonization, we collected human nasal secretions and analyzed their ability to promote S. aureus surface colonization. Some individuals produced secretions possessing the ability to significantly promote S. aureus surface colonization. Nasal secretions pretreated with protease no longer promoted S. aureus surface colonization, suggesting the involvement of protein factors. The major protein components of secretions were identified and subsequent analysis revealed that hemoglobin possessed the ability to promote S. aureus surface colonization. Immunoprecipitation of hemoglobin from nasal secretions resulted in reduced S. aureus surface colonization. Furthermore, exogenously added hemoglobin significantly decreased the inoculum necessary for nasal colonization in a rodent model. Finally, we found that hemoglobin prevented expression of the agr quorum sensing system and that aberrant constitutive expression of the agr effector molecule, RNAIII, resulted in reduced nasal colonization of S. aureus. Collectively our results suggest that the presence of hemoglobin in nasal secretions contributes to S. aureus nasal colonization.

Nuclear proteomic changes linked to soybean rust resistance

Soybean rust, caused by the fungus Phakopsora pachyrhizi, is an emerging threat to the US soybean crop. In an effort to identify proteins that contribute to disease resistance in soybean we compared a susceptible Williams 82 cultivar to a resistant Williams 82 inbred isoline harboring the Rpp1 resistance gene (R-gene). Approximately 4975 proteins from nuclear preparations of leaves were detected using a high-throughput liquid chromatography-mass spectrometry method. Many of these proteins have predicted nuclear localization signals, have homology to transcription factors and other nuclear regulatory proteins, and are phosphorylated. Statistics of summed spectral counts revealed sets of proteins with differential accumulation changes between susceptible and resistant plants. These protein accumulation changes were compared to previously reported gene expression changes and very little overlap was found. Thus, it appears that numerous proteins are post-translationally affected in the nucleus after infection. To our knowledge, this is the first indication of large-scale proteomic change in a plant nucleus after infection. Furthermore, the data reveal distinct proteins under control of Rpp1 and show that this disease resistance gene regulates nuclear protein accumulation. These regulated proteins likely influence broader defense responses, and these data may facilitate the development of plants with improved resistance.

Less label, more free: approaches in label-free quantitative mass spectrometry

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and cost-effective alternative to labelled quantitation.

Highly reproducible label free quantitative proteomic analysis of RNA polymerase complexes

The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports.

Relative, label-free protein quantitation: spectral counting error statistics from nine replicate MudPIT samples

Nine replicate samples of peptides from soybean leaves, each spiked with a different concentration of bovine apotransferrin peptides, were analyzed on a mass spectrometer using multidimensional protein identification technology (MudPIT). Proteins were detected from the peptide tandem mass spectra, and the numbers of spectra were statistically evaluated for variation between samples. The results corroborate prior knowledge that combining spectra from replicate samples increases the number of identifiable proteins and that a summed spectral count for a protein increases linearly with increasing molar amounts of protein. Furthermore, statistical analysis of spectral counts for proteins in two- and three-way comparisons between replicates and combined replicates revealed little significant variation arising from run-to-run differences or data-dependent instrument ion sampling that might falsely suggest differential protein accumulation. In these experiments, spectral counting was enabled by PANORAMICS, probability-based software that predicts proteins detected by sets of observed peptides. Three alternative approaches to counting spectra were also evaluated by comparison. As the counting thresholds were changed from weaker to more stringent, the accuracy of ratio determination also changed. These results suggest that thresholds for counting can be empirically set to improve relative quantitation. All together, the data confirm the accuracy and reliability of label-free spectral counting in the relative, quantitative analysis of proteins between samples.

Comparative profiling of highly enriched 22L and Chandler mouse scrapie prion protein preparations

Transmissible spongiform encephalopathies (TSEs) or prion diseases are characterized by the accumulation of an aggregated isoform of the prion protein (PrP). This pathological isoform, termed PrP(Sc), appears to be the primary component of the TSE infectious agent or prion. However, it is not clear to what extent other protein cofactors may be involved in TSE pathogenesis or whether there are PrP(Sc)-associated proteins which help to determine TSE strain-specific disease phenotypes. We enriched PrP(Sc) from the brains of mice infected with either 22L or Chandler TSE strains and examined the protein content of these samples using nanospray LC-MS/MS. These samples were compared with "mock" PrP(Sc) preparations from uninfected brains. PrP was the major component of the infected samples and ferritin was the most abundant impurity. Mock enrichments contained no detectable PrP but did contain a significant amount of ferritin. Of the total proteins identified, 32% were found in both mock and infected samples. The similarities between PrP(Sc) samples from 22L and Chandler TSE strains suggest that the non-PrP(Sc) protein components found in standard enrichment protocols are not strain specific.