A proteomic strategy for global analysis of plant protein complexes

The conditional mitochondrial protein complexome in the Arabidopsis thaliana root and shoot

Protein complexes are important for almost all biological processes. Hence, to fully understand how cells work, it is also necessary to characterize protein complexes and their dynamics in response to various cellular cues. Moreover, the dynamics of protein interaction play crucial roles in regulating the (dis)association of protein complexes and, in turn, regulating biological processes such as metabolism. Here, mitochondrial protein complexes were investigated by blue native PAGE and size-exclusion chromatography under conditions of oxidative stress in order to monitor their dynamic (dis)associations. Rearrangements of enzyme interactions and changes in protein complex abundance were observed in response to oxidative stress induced by menadione treatment. These included changes in enzymatic protein complexes involving γ-amino butyric acid transaminase (GABA-T), Δ-ornithine aminotransferase (Δ-OAT), or proline dehydrogenase 1 (POX1) that are expected to affect proline metabolism. Menadione treatment also affected interactions between several enzymes of the tricarboxylic acid (TCA) cycle and the abundance of complexes of the oxidative phosphorylation pathway. In addition, we compared the mitochondrial complexes of roots and shoots. Considerable differences between the two tissues were observed in the mitochondrial import/export apparatus, the formation of super-complexes in the oxidative phosphorylation pathway, and specific interactions between enzymes of the TCA cycle that we postulate may be related to the metabolic/energetic requirements of roots and shoots.

Nuclear export of BATF2 enhances colorectal cancer proliferation through binding to CRM1

BACKGROUND

During the tumourigenesis and development of colorectal cancer (CRC), the inactivation of tumour suppressor genes is closely involved, although detailed molecular mechanisms remain elusive. Accumulating studies, including ours, have demonstrated that basic leucine zipper transcription factor ATF (activating transcription factor)-like 2 (BATF2) is a capable tumour suppressor that localises in the nucleus. However, its different subcellular localisation, potential functions and underlying mechanisms are unclear.

METHODS

The translocation of BATF2 and its clinical relevance were detected using CRC samples, cell lines and xenograft nude mice. Candidate BATF2-binding proteins were screened using co-immunoprecipitation, quantitative label-free liquid chromatography-tandem mass spectrometry proteomic analysis, Western blotting and immunofluorescence. Recombinant plasmids, point mutations and siRNAs were applied to clarify the binding sites between BATF2 and chromosome region maintenance 1 (CRM1).

RESULTS

The present study found that BATF2 was mainly localised in the cytoplasm, rather than nucleus, of CRC cells in vitro and in vivo, while cytoplasmic BATF2 expression was inversely correlated with the prognosis of CRC patients. Furthermore, we identified the nuclear export and subsequent ubiquitin-mediated degradation of BATF2 in CRC cells. Mechanistically, a functional nuclear export sequence (any amino acid) was characterised in BATF2 protein, through which BATF2 bound to CRM1 and translocated out of nucleus, ultimately enhancing CRC growth via inducing activator protein 1 (AP-1)/cyclin D1/phosphorylated retinoblastoma protein (pRb) signalling pathway. Additionally, nuclear export of BATF2 can be retarded by the mutation of NES in BATF2 or the knockdown of CRM1, whereas CRM1 expression was negatively associated with nuclear BATF2 expression and the prognosis of CRC patients.

CONCLUSION

These findings revealed the biological effects and underlying mechanisms of cytoplasmic localisation of BATF2. Furthermore, suppressing nuclear export of BATF2 via mutating its NES region or inhibiting CRM1 expression may serve as a promising therapeutic strategy against CRC.

Don't let go: co-fractionation mass spectrometry for untargeted mapping of protein-metabolite interactomes

The chemical complexity of metabolomes goes hand in hand with their functional diversity. Small molecules have many essential roles, many of which are executed by binding and modulating the function of a protein partner. The complex and dynamic protein-metabolite interaction (PMI) network underlies most if not all biological processes, but remains under-characterized. Herein, we highlight how co-fractionation mass spectrometry (CF-MS), a well-established approach to map protein assemblies, can be used for proteome and metabolome identification of the PMIs. We will review recent CF-MS studies, discuss the main advantages and limitations, summarize the available CF-MS guidelines, and outline future challenges and opportunities.

Analyzing Effect of Multi-Modality in Predicting Protein-Protein Interactions

Nowadays, multiple sources of information about proteins are available such as protein sequences, 3D structures, Gene Ontology (GO), etc. Most of the works on protein-protein interaction (PPI) identification had utilized these information about proteins, mainly sequence-based, but individually. The new advances in deep learning techniques allow us to leverage multiple sources/modalities of proteins, which complement each other. Some recent works have shown that multi-modal PPI models perform better than uni-modal approaches. This paper aims to investigate whether the performance of multi-modal PPI models is always consistent or depends on other factors such as dataset distribution, algorithms used to learn features, etc. We have used three modalities for this study: Protein sequence, 3D structure, and GO. Various techniques, including deep learning algorithms, are employed to extract features from multiple sources of proteins. These feature vectors from different modalities are then integrated in several combinations (bi-modal and tri-modal) to predict PPI. To conduct this study, we have used Human and S. cerevisiae PPI datasets. The obtained results demonstrate the potentiality of a multi-modal approach and deep learning techniques in predicting protein interactions. However, the predictive capability of a model for PPI depends on feature extraction methods as well. Also, increasing the modality does not always ensure performance improvement. In this study, the PPI model integrating two modalities outperforms the designed uni-modal and tri-modal PPI models.

N-terminal modifications, the associated processing machinery, and their evolution in plastid-containing organisms

The N-terminus is a frequent site of protein modifications. Referring primarily to knowledge gained from land plants, here we review the modifications that change protein N-terminal residues and provide updated information about the associated machinery, including that in Archaeplastida. These N-terminal modifications include many proteolytic events as well as small group additions such as acylation or arginylation and oxidation. Compared with that of the mitochondrion, the plastid-dedicated N-terminal modification landscape is far more complex. In parallel, we extend this review to plastid-containing Chromalveolata including Stramenopiles, Apicomplexa, and Rhizaria. We report a well-conserved machinery, especially in the plastid. Consideration of the two most abundant proteins on Earth-Rubisco and actin-reveals the complexity of N-terminal modification processes. The progressive gene transfer from the plastid to the nuclear genome during evolution is exemplified by the N-terminus modification machinery, which appears to be one of the latest to have been transferred to the nuclear genome together with crucial major photosynthetic landmarks. This is evidenced by the greater number of plastid genes in Paulinellidae and red algae, the most recent and fossil recipients of primary endosymbiosis.

Rewiring of the protein-protein-metabolite interactome during the diauxic shift in yeast

In budding yeast Saccharomyces cerevisiae, the switch from aerobic fermentation to respiratory growth is separated by a period of growth arrest, known as the diauxic shift, accompanied by a significant metabolic rewiring, including the derepression of gluconeogenesis and the establishment of mitochondrial respiration. Previous studies reported hundreds of proteins and tens of metabolites accumulating differentially across the diauxic shift transition. To assess the differences in the protein-protein (PPIs) and protein-metabolite interactions (PMIs) yeast samples harvested in the glucose-utilizing, fermentative phase, ethanol-utilizing and early stationary respiratory phases were analysed using isothermal shift assay (iTSA) and a co-fractionation mass spectrometry approach, PROMIS. Whereas iTSA monitors changes in protein stability and is informative towards protein interaction status, PROMIS uses co-elution to delineate putative PPIs and PMIs. The resulting dataset comprises 1627 proteins and 247 metabolites, hundreds of proteins and tens of metabolites characterized by differential thermal stability and/or fractionation profile, constituting a novel resource to be mined for the regulatory PPIs and PMIs. The examples discussed here include (i) dissociation of the core and regulatory particle of the proteasome in the early stationary phase, (ii) the differential binding of a co-factor pyridoxal phosphate to the enzymes of amino acid metabolism and (iii) the putative, phase-specific interactions between proline-containing dipeptides and enzymes of central carbon metabolism.

Global Landscape of Native Protein Complexes in Synechocystis sp. PCC 6803

Synechocystis sp. PCC 6803 (hereafter: Synechocystis) is a model organism for studying photosynthesis, energy metabolism, and environmental stress. Although known as the first fully sequenced phototrophic organism, Synechocystis still has almost half of its proteome without functional annotations. In this study, by using co-fractionation coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS), we define 291 multi-protein complexes, encompassing 24,092 protein-protein interactions (PPIs) among 2062 distinct gene products. This information not only reveals the roles of photosynthesis in metabolism, cell motility, DNA repair, cell division, and other physiological processes, but also shows how protein functions vary from bacteria to higher plants due to changes in interaction partners. It also allows us to uncover the functions of hypothetical proteins, such as Sll0445, Sll0446, and Sll0447 involved in photosynthesis and cell motility, and Sll1334 involved in regulation of fatty acid biogenesis. Here we present the most extensive PPI data for Synechocystis so far, which provide critical insights into fundamental molecular mechanisms in cyanobacteria.

Comparative Network Biology Discovers Protein Complexes That Underline Cellular Differentiation in Anabaena sp

The filamentous cyanobacterium Anabaena sp. PCC 7120 can differentiate into heterocysts to fix atmospheric nitrogen. During cell differentiation, cellular morphology and gene expression undergo a series of significant changes. To uncover the mechanisms responsible for these alterations, we built protein–protein interaction (PPI) networks for these two cell types by cofractionation coupled with mass spectrometry. We predicted 280 and 215 protein complexes, with 6322 and 2791 high-confidence PPIs in vegetative cells and heterocysts, respectively. Most of the proteins in both types of cells presented similar elution profiles, whereas the elution peaks of 438 proteins showed significant changes. We observed that some well-known complexes recruited new members in heterocysts, such as ribosomes, diflavin flavoprotein, and cytochrome c oxidase. Photosynthetic complexes, including photosystem I, photosystem II, and phycobilisome, remained in both vegetative cells and heterocysts for electron transfer and energy generation. Besides that, PPI data also reveal new functions of proteins. For example, the hypothetical protein Alr4359 was found to interact with FraH and Alr4119 in heterocysts and was located on heterocyst poles, thereby influencing the diazotrophic growth of filaments. The overexpression of Alr4359 suspended heterocyst formation and altered the pigment composition and filament length. This work demonstrates the differences in protein assemblies and provides insight into physiological regulation during cell differentiation.

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PPIs in two types of cells of Anabaena sp. 7120 were systematically identified.

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10,302 and 8557 high-confidence PPIs were obtained and over 80% were novel.

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About 438 proteins showed significant changes in vegetative cells and heterocysts.

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Protein Alr4359 was found to influence the diazotrophic growth of filaments.

PROMISed: A novel web-based tool to facilitate analysis and visualization of the molecular interaction networks from co-fractionation mass spectrometry (CF-MS) experiments

Co-fractionation mass spectrometry (CF-MS)-based approaches enable cell-wide identification of protein-protein and protein-metabolite complexes present in the cellular lysate. CF-MS combines biochemical separation of molecular complexes with an untargeted mass-spectrometry-based proteomics and/or metabolomics analysis of the obtained fractions, and is used to delineate putative interactors. CF-MS data are a treasure trove for biological discovery. To facilitate analysis and visualization of original or publically available CF-MS datasets, we designed PROMISed, a user-friendly tool available online via https://myshiny.mpimp-golm.mpg.de/PDP1/ or as a repository via https://github.com/DennisSchlossarek/PROMISed. Specifically, starting with raw fractionation profiles, PROMISed (i) contains activities for data pre-processing and normalization, (ii) deconvolutes complex fractionation profiles into single, distinct peaks, (iii) identifies co-eluting protein-protein or protein-metabolite pairs using user-defined correlation methods, and (iv) performs co-fractionation network analysis. Given multiple CF-MS datasets, for instance representing different environmental condition, PROMISed allows to select for proteins and metabolites that differ in their elution profile, which may indicate change in the interaction status. But it also enables the identification of protein-protein and protein-metabolite pairs that co-elute together across multiple datasets. PROMISed enables users to (i) easily adjust parameters at each step of the analysis, (ii) download partial and final results, and (iii) select among different data-visualization options. PROMISed renders CF-MS data accessible to a broad scientific audience, allowing users with no computational or statistical background to look for novel protein-protein and protein-metabolite complexes for further experimental validation.

A co-fractionation mass spectrometry-based prediction of protein complex assemblies in the developing rice aleurone-subaleurone

Multiprotein complexes execute and coordinate diverse cellular processes such as organelle biogenesis, vesicle trafficking, cell signaling, and metabolism. Knowledge about their composition and localization provides useful clues about the mechanisms of cellular homeostasis and system-level control. This is of great biological importance and practical significance in heterotrophic rice (Oryza sativa) endosperm and aleurone-subaleurone tissues, which are a primary source of seed vitamins and stored energy. Dozens of protein complexes have been implicated in the synthesis, transport, and storage of seed proteins, lipids, vitamins, and minerals. Mutations in protein complexes that control RNA transport result in aberrant endosperm with shrunken and floury phenotypes, significantly reducing seed yield and quality. The purpose of this study was to broadly predict protein complex composition in the aleurone-subaleurone layers of developing rice seeds using co-fractionation mass spectrometry. Following orthogonal chromatographic separations of biological replicates, thousands of protein elution profiles were subjected to distance-based clustering to enable large-scale multimerization state measurements and protein complex predictions. The predicted complexes had predicted functions across diverse functional categories, including novel heteromeric RNA binding protein complexes that may influence seed quality. This effective and open-ended proteomics pipeline provides useful clues about system-level posttranslational control during the early stages of rice seed development.

Beyond the Usual Suspects: Physiological Roles of the Arabidopsis Amidase Signature (AS) Superfamily Members in Plant Growth Processes and Stress Responses

The diversification of land plants largely relies on their ability to cope with constant environmental fluctuations, which negatively impact their reproductive fitness and trigger adaptive responses to biotic and abiotic stresses. In this limiting landscape, cumulative research attention has centred on deepening the roles of major phytohormones, mostly auxins, together with brassinosteroids, jasmonates, and abscisic acid, despite the signaling networks orchestrating the crosstalk among them are so far only poorly understood. Accordingly, this review focuses on the Arabidopsis Amidase Signature (AS) superfamily members, with the aim of highlighting the hitherto relatively underappreciated functions of AMIDASE1 (AMI1) and FATTY ACID AMIDE HYDROLASE (FAAH), as comparable coordinators of the growth-defense trade-off, by balancing auxin and ABA homeostasis through the conversion of their likely bioactive substrates, indole-3-acetamide and N-acylethanolamine.

Closing the protein gap in plant chronobiology

Our modern understanding of diel cell regulation in plants stems from foundational work in the late 1990s that analysed the dynamics of selected genes and mutants in Arabidopsis thaliana. The subsequent rise of transcriptomics technologies such as microarrays and RNA sequencing has substantially increased our understanding of anticipatory (circadian) and reactive (light- or dark-triggered) diel events in plants. However, it is also becoming clear that gene expression data fail to capture critical events in diel regulation that can only be explained by studying protein-level dynamics. Over the past decade, mass spectrometry technologies and quantitative proteomic workflows have significantly advanced, finally allowing scientists to characterise diel protein regulation at high throughput. Initial proteomic investigations suggest that the diel transcriptome and proteome generally lack synchrony and that the timing of daily regulatory events in plants is impacted by multiple levels of protein regulation (e.g., post-translational modifications [PTMs] and protein-protein interactions [PPIs]). Here, we highlight and summarise how the use of quantitative proteomics to elucidate diel plant cell regulation has advanced our understanding of these processes. We argue that this new understanding, coupled with the extraordinary developments in mass spectrometry technologies, demands greater focus on protein-level regulation of, and by, the circadian clock. This includes hitherto unexplored diel dynamics of protein turnover, PTMs, protein subcellular localisation and PPIs that can be masked by simple transcript- and protein-level changes. Finally, we propose new directions for how the latest advancements in quantitative proteomics can be utilised to answer outstanding questions in plant chronobiology.

Mapping the plant proteome: tools for surveying coordinating pathways

Plants rapidly respond to environmental fluctuations through coordinated, multi-scalar regulation, enabling complex reactions despite their inherently sessile nature. In particular, protein post-translational signaling and protein-protein interactions combine to manipulate cellular responses and regulate plant homeostasis with precise temporal and spatial control. Understanding these proteomic networks are essential to addressing ongoing global crises, including those of food security, rising global temperatures, and the need for renewable materials and fuels. Technological advances in mass spectrometry-based proteomics are enabling investigations of unprecedented depth, and are increasingly being optimized for and applied to plant systems. This review highlights recent advances in plant proteomics, with an emphasis on spatially and temporally resolved analysis of post-translational modifications and protein interactions. It also details the necessity for generation of a comprehensive plant cell atlas while highlighting recent accomplishments within the field.

Nitrogen Uptake in Plants: The Plasma Membrane Root Transport Systems from a Physiological and Proteomic Perspective

Nitrogen nutrition in plants is a key determinant in crop productivity. The availability of nitrogen nutrients in the soil, both inorganic (nitrate and ammonium) and organic (urea and free amino acids), highly differs and influences plant physiology, growth, metabolism, and root morphology. Deciphering this multifaceted scenario is mandatory to improve the agricultural sustainability. In root cells, specific proteins located at the plasma membrane play key roles in the transport and sensing of nitrogen forms. This review outlines the current knowledge regarding the biochemical and physiological aspects behind the uptake of the individual nitrogen forms, their reciprocal interactions, the influences on root system architecture, and the relations with other proteins sustaining fundamental plasma membrane functionalities, such as aquaporins and H⁺-ATPase. This topic is explored starting from the information achieved in the model plant Arabidopsis and moving to crops in agricultural soils. Moreover, the main contributions provided by proteomics are described in order to highlight the goals and pitfalls of this approach and to get new hints for future studies.

Multimerization variants as potential drivers of neofunctionalization

Whole-genome duplications are common during evolution, creating genetic redundancy that can enable cellular innovations. Novel protein-protein interactions provide a route to diversified gene functions, but, at present, there is limited proteome-scale knowledge on the extent to which variability in protein complex formation drives neofunctionalization. Here, we used protein correlation profiling to test for variability in apparent mass among thousands of orthologous proteins isolated from diverse species and cell types. Variants in protein complex size were unexpectedly common, in some cases appearing after relatively recent whole-genome duplications or an allopolyploidy event. In other instances, variants such as those in the carbonic anhydrase orthologous group reflected the neofunctionalization of ancient paralogs that have been preserved in extant species. Our results demonstrate that homo- and heteromer formation have the potential to drive neofunctionalization in diverse classes of enzymes, signaling, and structural proteins.

Protein Complexes Form a Basis for Complex Hybrid Incompatibility

Proteins are the workhorses of the cell and execute many of their functions by interacting with other proteins forming protein complexes. Multi-protein complexes are an admixture of subunits, change their interaction partners, and modulate their functions and cellular physiology in response to environmental changes. When two species mate, the hybrid offspring are usually inviable or sterile because of large-scale differences in the genetic makeup between the two parents causing incompatible genetic interactions. Such reciprocal-sign epistasis between inter-specific alleles is not limited to incompatible interactions between just one gene pair; and, usually involves multiple genes. Many of these multi-locus incompatibilities show visible defects, only in the presence of all the interactions, making it hard to characterize. Understanding the dynamics of protein-protein interactions (PPIs) leading to multi-protein complexes is better suited to characterize multi-locus incompatibilities, compared to studying them with traditional approaches of genetics and molecular biology. The advances in omics technologies, which includes genomics, transcriptomics, and proteomics can help achieve this end. This is especially relevant when studying non-model organisms. Here, we discuss the recent progress in the understanding of hybrid genetic incompatibility; omics technologies, and how together they have helped in characterizing protein complexes and in turn multi-locus incompatibilities. We also review advances in bioinformatic techniques suitable for this purpose and propose directions for leveraging the knowledge gained from model-organisms to identify genetic incompatibilities in non-model organisms.

Analytical Guidelines for co-fractionation Mass Spectrometry Obtained through Global Profiling of Gold Standard Saccharomyces cerevisiae Protein Complexes

Co-fractionation MS (CF-MS) is a technique with potential to characterize endogenous and unmanipulated protein complexes on an unprecedented scale. However this potential has been offset by a lack of guidelines for best-practice CF-MS data collection and analysis. To obtain such guidelines, this study thoroughly evaluates novel and published Saccharomyces cerevisiae CF-MS data sets using very high proteome coverage libraries of yeast gold standard complexes. A new method for identifying gold standard complexes in CF-MS data, Reference Complex Profiling, and the Extending 'Guilt-by-Association' by Degree (EGAD) R package are used for these evaluations, which are verified with concurrent analyses of published human data. By evaluating data collection designs, which involve fractionation of cell lysates, it is found that near-maximum recall of complexes can be achieved with fewer samples than published studies. Distributing sample collection across orthogonal fractionation methods, rather than a single high resolution data set, leads to particularly efficient recall. By evaluating 17 different similarity scoring metrics, which are central to CF-MS data analysis, it is found that two metrics rarely used in past CF-MS studies - Spearman and Kendall correlations - and the recently introduced Co-apex metric frequently maximize recall, whereas a popular metric-Euclidean distance-delivers poor recall. The common practice of integrating external genomic data into CF-MS data analysis is also evaluated, revealing that this practice may improve the precision and recall of known complexes but is generally unsuitable for predicting novel complexes in model organisms. If studying nonmodel organisms using orthologous genomic data, it is found that particular subsets of fractionation profiles (e.g. the lowest abundance quartile) should be excluded to minimize false discovery. These assessments are summarized in a series of universally applicable guidelines for precise, sensitive and efficient CF-MS studies of known complexes, and effective predictions of novel complexes for orthogonal experimental validation.

Overexpression of ATP sulfurylase improves the sulfur amino acid content, enhances the accumulation of Bowman-Birk protease inhibitor and suppresses the accumulation of the β-subunit of β-conglycinin in soybean seeds

ATP sulfurylase, an enzyme which catalyzes the conversion of sulfate to adenosine 5'-phosphosulfate (APS), plays a significant role in controlling sulfur metabolism in plants. In this study, we have expressed soybean plastid ATP sulfurylase isoform 1 in transgenic soybean without its transit peptide under the control of the 35S CaMV promoter. Subcellular fractionation and immunoblot analysis revealed that ATP sulfurylase isoform 1 was predominantly expressed in the cell cytoplasm. Compared with that of untransformed plants, the ATP sulfurylase activity was about 2.5-fold higher in developing seeds. High-resolution 2-D gel electrophoresis and immunoblot analyses revealed that transgenic soybean seeds overexpressing ATP sulfurylase accumulated very low levels of the β-subunit of β-conglycinin. In contrast, the accumulation of the cysteine-rich Bowman-Birk protease inhibitor was several fold higher in transgenic soybean plants when compared to the non-transgenic wild-type seeds. The overall protein content of the transgenic seeds was lowered by about 3% when compared to the wild-type seeds. Metabolite profiling by LC-MS and GC-MS quantified 124 seed metabolites out of which 84 were present in higher amounts and 40 were present in lower amounts in ATP sulfurylase overexpressing seeds compared to the wild-type seeds. Sulfate, cysteine, and some sulfur-containing secondary metabolites accumulated in higher amounts in ATP sulfurylase transgenic seeds. Additionally, ATP sulfurylase overexpressing seeds contained significantly higher amounts of phospholipids, lysophospholipids, diacylglycerols, sterols, and sulfolipids. Importantly, over expression of ATP sulfurylase resulted in 37-52% and 15-19% increases in the protein-bound cysteine and methionine content of transgenic seeds, respectively. Our results demonstrate that manipulating the expression levels of key sulfur assimilatory enzymes could be exploited to improve the nutritive value of soybean seeds.

Proteomics: a powerful tool to study plant responses to biotic stress

In recent years, mass spectrometry-based proteomics has provided scientists with the tremendous capability to study plants more precisely than previously possible. Currently, proteomics has been transformed from an isolated field into a comprehensive tool for biological research that can be used to explain biological functions. Several studies have successfully used the power of proteomics as a discovery tool to uncover plant resistance mechanisms. There is growing evidence that indicates that the spatial proteome and post-translational modifications (PTMs) of proteins directly participate in the plant immune response. Therefore, understanding the subcellular localization and PTMs of proteins is crucial for a comprehensive understanding of plant responses to biotic stress. In this review, we discuss current approaches to plant proteomics that use mass spectrometry, with particular emphasis on the application of spatial proteomics and PTMs. The purpose of this paper is to investigate the current status of the field, discuss recent research challenges, and encourage the application of proteomics techniques to further research.

Quantitative proteomic analysis of enhanced cellular effects of electrochemotherapy with Cisplatin in triple-negative breast cancer cells

Due to the lack of the three main receptors, triple negative breast cancer (TNBC) is refractive to standard chemotherapy. Hence, alternate therapies are needed. TNBCs utilize glycolysis, which heightens their growth, proliferation, invasiveness, chemotherapeutic resistance and poor therapeutic response. This calls for novel therapeutic strategies to target these metabolic vulnerabilities present in TNBC. Electroporation-mediated chemotherapy, known as electrochemotherapy (ECT) is gaining momentum as an attractive alternative. However, its molecular mechanisms need better understanding. Towards this, label-free quantitative proteomics is utilized to gain insight into the anticancer mechanisms of ECT using electrical pulses (EP) and Cisplatin (CsP) on MDA-MB-231, human TNBC cells. The results indicate that EP + CsP significantly downregulated 14 key glycolysis proteins (including ENO1, LDHA, LDHB, ACSS2, ALDOA, and PGK1), compared to CsP alone. EP + CsP caused a switch in the metabolism with upregulation of 34 oxidative phosphorylation pathway proteins and 18 tricarboxylic acid (TCA) cycle proteins compared to CsP alone, accompanied by the upregulation of proteins linked to several metabolic reactions, which produce TCA cycle intermediates. Moreover, EP + CsP promoted multiple pathways to cause 1.3-fold increase in the reactive oxygen species concentration and induced apoptosis. The proteomics results correlate well with cell viability, western blot, and qPCR data. While some effects were similar for EP, more comprehensive and long-lasting effects were observed for EP + CsP, which demonstrate the potential of EP + CsP against TNBC cells.

Protein Complex Identification and quantitative complexome by CN-PAGE

The majority of cellular processes are carried out by protein complexes. Various size fractionation methods have previously been combined with mass spectrometry to identify protein complexes. However, most of these approaches lack the quantitative information which is required to understand how changes of protein complex abundance and composition affect metabolic fluxes. In this paper we present a proof of concept approach to quantitatively study the complexome in the model plant Arabidopsis thaliana at the end of the day (ED) and the end of the night (EN). We show that size-fractionation of native protein complexes by Clear-Native-PAGE (CN-PAGE), coupled with mass spectrometry can be used to establish abundance profiles along the molecular weight gradient. Furthermore, by deconvoluting complex protein abundance profiles, we were able to drastically improve the clustering of protein profiles. To identify putative interaction partners, and ultimately protein complexes, our approach calculates the Euclidian distance between protein profile pairs. Acceptable threshold values are based on a cut-off that is optimized by a receiver-operator characteristic (ROC) curve analysis. Our approach shows low technical variation and can easily be adapted to study in the complexome in any biological system.

A Label-free Mass Spectrometry Method to Predict Endogenous Protein Complex Composition

Information on the composition of protein complexes can accelerate mechanistic analyses of cellular systems. Protein complex composition identifies genes that function together and provides clues about regulation within and between cellular pathways. Cytosolic protein complexes control metabolic flux, signal transduction, protein abundance, and the activities of cytoskeletal and endomembrane systems. It has been estimated that one third of all cytosolic proteins in leaves exist in an oligomeric state, yet the composition of nearly all remain unknown. Subunits of stable protein complexes copurify, and combinations of mass-spectrometry-based protein correlation profiling and bioinformatic analyses have been used to predict protein complex subunits. Because of uncertainty regarding the power or availability of bioinformatic data to inform protein complex predictions across diverse species, it would be highly advantageous to predict composition based on elution profile data alone. Here we describe a mass spectrometry-based protein correlation profiling approach to predict the composition of hundreds of protein complexes based on biochemical data. Extracts were obtained from an intact organ and separated in parallel by size and charge under nondenaturing conditions. More than 1000 proteins with reproducible elution profiles across all replicates were subjected to clustering analyses. The resulting dendrograms were used to predict the composition of known and novel protein complexes, including many that are likely to assemble through self-interaction. An array of validation experiments demonstrated that this new method can drive protein complex discovery, guide hypothesis testing, and enable systems-level analyses of protein complex dynamics in any organism with a sequenced genome.

Complexome Profiling Reveals Association of PPR Proteins with Ribosomes in the Mitochondria of Plants

Mitochondrial transcripts are subject to a wealth of processing mechanisms including cis- and trans-splicing events, as well as base modifications (RNA editing). Hundreds of proteins are required for these processes in plant mitochondria, many of which belong to the pentatricopeptide repeat (PPR) protein superfamily. The structure, localization, and function of these proteins is only poorly understood. Here we present evidence that several PPR proteins are bound to mitoribosomes in plants. A novel complexome profiling strategy in combination with chemical crosslinking has been employed to systematically define the protein constituents of the large and the small ribosomal subunits in the mitochondria of plants. We identified more than 80 ribosomal proteins, which include several PPR proteins and other non-conventional ribosomal proteins. These findings reveal a potential coupling of transcriptional and translational events in the mitochondria of plants. Furthermore, the data indicate an extremely high molecular mass of the "small" subunit, even exceeding that of the "large" subunit.

Computational identification of protein-protein interactions in model plant proteomes

Protein-protein interactions (PPIs) play essential roles in many biological processes. A PPI network provides crucial information on how biological pathways are structured and coordinated from individual protein functions. In the past two decades, large-scale PPI networks of a handful of organisms were determined by experimental techniques. However, these experimental methods are time-consuming, expensive, and are not easy to perform on new target organisms. Large-scale PPI data is particularly sparse in plant organisms. Here, we developed a computational approach for detecting PPIs trained and tested on known PPIs of Arabidopsis thaliana and applied to three plants, Arabidopsis thaliana, Glycine max (soybean), and Zea mays (maize) to discover new PPIs on a genome-scale. Our method considers a variety of features including protein sequences, gene co-expression, functional association, and phylogenetic profiles. This is the first work where a PPI prediction method was developed for is the first PPI prediction method applied on benchmark datasets of Arabidopsis. The method showed a high prediction accuracy of over 90% and very high precision of close to 1.0. We predicted 50,220 PPIs in Arabidopsis thaliana, 13,175,414 PPIs in corn, and 13,527,834 PPIs in soybean. Newly predicted PPIs were classified into three confidence levels according to the availability of existing supporting evidence and discussed. Predicted PPIs in the three plant genomes are made available for future reference.

Cytonuclear interactions remain stable during allopolyploid evolution despite repeated whole-genome duplications in Brassica

Several plastid macromolecular protein complexes are encoded by both nuclear and plastid genes. Therefore, cytonuclear interactions are held in place to prevent genomic conflicts that may lead to incompatibilities. Allopolyploidy resulting from hybridization and genome doubling of two divergent species can disrupt these fine-tuned interactions, as newly formed allopolyploid species confront biparental nuclear chromosomes with a uniparentally inherited plastid genome. To avoid any deleterious effects of unequal genome inheritance, preferential transcription of the plastid donor over the other donor has been hypothesized to occur in allopolyploids. We used Brassica as a model to study the effects of paleopolyploidy in diploid parental species, as well as the effects of recent and ancient allopolyploidy in Brassica napus, on genes implicated in plastid protein complexes. We first identified redundant nuclear copies involved in those complexes. Compared with cytosolic protein complexes and with genome-wide retention rates, genes involved in plastid protein complexes show a higher retention of genes in duplicated and triplicated copies. Those redundant copies are functional and are undergoing strong purifying selection. We then compared transcription patterns and sequences of those redundant gene copies between resynthesized allopolyploids and their diploid parents. The neopolyploids showed no biased subgenome expression or maternal homogenization via gene conversion, despite the presence of some non-synonymous substitutions between plastid genomes of parental progenitors. Instead, subgenome dominance was observed regardless of the maternal progenitor. Our results provide new insights on the evolution of plastid protein complexes that could be tested and generalized in other allopolyploid species.

TAT1 and TAT2 tyrosine aminotransferases have both distinct and shared functions in tyrosine metabolism and degradation in Arabidopsis thaliana

Plants produce various l-tyrosine (Tyr)-derived compounds that are critical for plant adaptation and have pharmaceutical or nutritional importance for human health. Tyrosine aminotransferases (TATs) catalyze the reversible reaction between Tyr and 4-hydroxyphenylpyruvate (HPP), representing the entry point in plants for both biosynthesis of various natural products and Tyr degradation in the recycling of energy and nutrients. To better understand the roles of TATs and how Tyr is metabolized in planta, here we characterized single and double loss-of-function mutants of TAT1 (At5g53970) and TAT2 (At5g36160) in the model plant Arabidopsis thaliana As reported previously, tat1 mutants exhibited elevated and decreased levels of Tyr and tocopherols, respectively. The tat2 mutation alone had no impact on Tyr and tocopherol levels, but a tat1 tat2 double mutant had increased Tyr accumulation and decreased tocopherol levels under high-light stress compared with the tat1 mutant. Relative to WT and the tat2 mutant, the tat1 mutant displayed increased vulnerability to continuous dark treatment, associated with an early drop in respiratory activity and sucrose depletion. During isotope-labeled Tyr feeding in the dark, we observed that the tat1 mutant exhibits much slower 13C incorporation into tocopherols, fumarate, and other tricarboxylic acid (TCA) cycle intermediates than WT and the tat2 mutant. These results indicate that TAT1 and TAT2 function together in tocopherol biosynthesis, with TAT2 having a lesser role, and that TAT1 plays the major role in Tyr degradation in planta Our study also highlights the importance of Tyr degradation under carbon starvation conditions during dark-induced senescence in plants.

Global Identification of Protein Complexes within the Membrane Proteome of Arabidopsis Roots Using a SEC-MS Approach

Biological processes consist of several consecutive and interacting steps as, for example, in signal transduction cascades or metabolic reaction chains. These processes are regulated by protein-protein interactions and the formation of larger protein complexes, which also occur within biological membranes. To gain a large-scale overview of complex-forming proteins and the composition of such complexes within the cellular membranes of Arabidopsis roots, we use the combination of size-exclusion chromatography and mass spectrometry. First, we identified complex-forming proteins by a retention shift analysis relative to expected retention times of monomeric proteins during size-exclusion chromatography. In a second step we predicted complex composition through pairwise correlation of elution profiles. As result we present an interactome of 963 proteins within cellular membranes of Arabidopsis roots. Identification of complex-forming proteins was highly robust between two independently grown root proteomes. The protein complex composition derived from pairwise correlations of coeluting proteins reproducibly identified stable protein complexes (ribosomes, proteasome, mitochondrial respiratory chain supercomplexes) but showed higher variance between replicates regarding transient interactions (e.g., interactions with kinases) within membrane protein complexes.

Analysis of Protein Complexes in the Unicellular Cyanobacterium Cyanothece ATCC 51142

The unicellular cyanobacterium Cyanothece ATCC 51142 is capable of oxygenic photosynthesis and biological N₂ fixation (BNF), a process highly sensitive to oxygen. Previous work has focused on determining protein expression levels under different growth conditions. A major gap of our knowledge is an understanding on how these expressed proteins are assembled into complexes and organized into metabolic pathways, an area that has not been thoroughly investigated. Here, we combined size-exclusion chromatography (SEC) with label-free quantitative mass spectrometry (MS) and bioinformatics to characterize many protein complexes from Cyanothece 51142 cells grown under a 12 h light-dark cycle. We identified 1386 proteins in duplicate biological replicates, and 64% of those proteins were identified as putative complexes. Pairwise computational prediction of protein-protein interaction (PPI) identified 74 822 putative interactions, of which 2337 interactions were highly correlated with published protein coexpressions. Many sequential glycolytic and TCA cycle enzymes were identified as putative complexes. We also identified many membrane complexes that contain cytoplasmic domains. Subunits of NDH-1 complex eluted in a fraction with an approximate mass of ∼669 kDa, and subunits composition revealed coexistence of distinct forms of NDH-1 complex subunits responsible for respiration, electron flow, and CO₂ uptake. The complex form of the phycocyanin beta subunit was nonphosphorylated, and the monomer form was phosphorylated at Ser20, suggesting phosphorylation-dependent deoligomerization of the phycocyanin beta subunit. This study provides an analytical platform for future studies to reveal how these complexes assemble and disassemble as a function of diurnal and circadian rhythms.

IAS: Interaction Specific GO Term Associations for Predicting Protein-Protein Interaction Networks

Proteins carry out their function in a cell through interactions with other proteins. A large scale protein-protein interaction (PPI) network of an organism provides static yet an essential structure of interactions, which is valuable clue for understanding the functions of proteins and pathways. PPIs are determined primarily by experimental methods; however, computational PPI prediction methods can supplement or verify PPIs identified by experiment. Here, we developed a novel scoring method for predicting PPIs from Gene Ontology (GO) annotations of proteins. Unlike existing methods that consider functional similarity as an indication of interaction between proteins, the new score, named the protein-protein Interaction Association Score (IAS), was computed from GO term associations of known interacting protein pairs in 49 organisms. IAS was evaluated on PPI data of six organisms and found to outperform existing GO term-based scoring methods. Moreover, consensus scoring methods that combine different scores further improved performance of PPI prediction.

Hit-Gel: Streamlining in-gel protein digestion for high-throughput proteomics experiments

In-gel digestion has been used as a standard method for the preparation of protein samples for mass spectrometry analysis for over 25 years. Traditional in gel-digestion procedures require extensive sample handling, are prone to contamination and not compatible with high-throughput sample preparation. To address these shortcomings, we have modified the conventional in-gel digestion procedure for high-throughput proteomics studies. The modified method, termed “High Throughput in Gel digestion” (HiT-Gel), is based on a 96-well plate format which results in a drastic reduction in labour intensity and sample handling. Direct comparison revealed that HiT-Gel reduces technical variation and significantly decreases sample contamination over the conventional in-gel digestion method. HiT-Gel also produced superior results when a single protein band was excised from a gel and processed by in-gel digestion. Moreover, we applied Hit-Gel for a mass spectrometry analysis of Arabidopsis thaliana protein complexes separated by native PAGE in 24 fractions and four biological replicates. We show that the high throughput capacity of HiT-Gel facilitates large scale studies with high sample replication or detailed fractionation. Our method can easily be implemented as it does not require specialised laboratory equipment.

PROMIS, global analysis of PROtein-metabolite interactions using size separation in Arabidopsis thaliana

Small molecules not only represent cellular building blocks and metabolic intermediates, but also regulatory ligands and signaling molecules that interact with proteins. Although these interactions affect cellular metabolism, growth, and development, they have been largely understudied. Herein, we describe a method, which we named PROtein–Metabolite Interactions using Size separation (PROMIS), that allows simultaneous, global analysis of endogenous protein–small molecule and of protein–protein complexes. To this end, a cell-free native lysate from Arabidopsis thaliana cell cultures was fractionated by size-exclusion chromatography, followed by quantitative metabolomic and proteomic analyses. Proteins and small molecules showing similar elution behavior, across protein-containing fractions, constituted putative interactors. Applying PROMIS to an A. thaliana extract, we ascertained known protein–protein (PPIs) and protein–metabolite (PMIs) interactions and reproduced binding between small-molecule protease inhibitors and their respective proteases. More importantly, we present examples of two experimental strategies that exploit the PROMIS dataset to identify novel PMIs. By looking for similar elution behavior of metabolites and enzymes belonging to the same biochemical pathways, we identified putative feedback and feed-forward regulations in pantothenate biosynthesis and the methionine salvage cycle, respectively. By combining PROMIS with an orthogonal affinity purification approach, we identified an interaction between the dipeptide Tyr–Asp and the glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase. In summary, we present proof of concept for a powerful experimental tool that enables system-wide analysis of PMIs and PPIs across all biological systems. The dataset obtained here comprises nearly 140 metabolites and 5000 proteins, which can be mined for putative interactors.

Analysis of Human Nuclear Protein Complexes by Quantitative Mass Spectrometry Profiling

Analysis of protein complexes provides insights into how the ensemble of expressed proteome is organized into functional units. While there have been advances in techniques for proteome-wide profiling of cytoplasmic protein complexes, information about human nuclear protein complexes are very limited. To close this gap, we combined native size exclusion chromatography (SEC) with label-free quantitative MS profiling to characterize hundreds of nuclear protein complexes isolated from human glioblastoma multiforme T98G cells. We identified 1794 proteins that overlapped between two biological replicates of which 1244 proteins were characterized as existing within stably associated putative complexes. co-IP experiments confirmed the interaction of PARP1 with Ku70/Ku80 proteins and HDAC1 (histone deacetylase complex 1) and CHD4. HDAC1/2 also co-migrated with various SIN3A and nucleosome remodeling and deacetylase components in SEC fractionation including SIN3A, SAP30, RBBP4, RBBP7, and NCOR1. Co-elution of HDAC1/2/3 with both the KDM1A and RCOR1 further confirmed that these proteins are integral components of human deacetylase complexes. Our approach also demonstrated the ability to identify potential moonlighting complexes and novel complexes containing uncharacterized proteins. Overall, the results demonstrated the utility of SEC fractionation and LC-MS analysis for system-wide profiling of proteins to predict the existence of distinct forms of nuclear protein complexes.

Interaction of 2',3'-cAMP with Rbp47b Plays a Role in Stress Granule Formation

2',3'-cAMP is an intriguing small molecule that is conserved among different kingdoms. 2',3'-cAMP is presumably produced during RNA degradation, with increased cellular levels observed especially under stress conditions. Previously, we observed the presence of 2',3'-cAMP in Arabidopsis (Arabidopsis thaliana) protein complexes isolated from native lysate, suggesting that 2',3'-cAMP has potential protein partners in plants. Here, affinity purification experiments revealed that 2',3'-cAMP associates with the stress granule (SG) proteome. SGs are aggregates composed of protein and mRNA, which enable cells to selectively store mRNA for use in response to stress such as heat whereby translation initiation is impaired. Using size-exclusion chromatography and affinity purification analyses, we identified Rbp47b, the key component of SGs, as a potential interacting partner of 2',3'-cAMP. Furthermore, SG formation was promoted in 2',3'-cAMP-treated Arabidopsis seedlings, and interactions between 2',3'-cAMP and RNA-binding domains of Rbp47b, RRM2 and RRM3, were confirmed in vitro using microscale thermophoresis. Taken together, these results (1) describe novel small-molecule regulation of SG formation, (2) provide evidence for the biological role of 2',3'-cAMP, and (3) demonstrate an original biochemical pipeline for the identification of protein-metabolite interactors.

Cadmium specific proteomic responses of a highly resistantPseudomonas aeruginosasan ai

Pseudomonas aeruginosa san ai is a promising candidate for bioremediation of cadmium pollution, as it resists a high concentration of up to 7.2 mM of cadmium. Leaving biomass of P. aeruginosa san ai exposed to cadmium has a large biosorption potential, implying its capacity to extract heavy metal from contaminated medium. In the present study, we investigated tolerance and accumulation of cadmium on protein level by shotgun proteomics approach based on liquid chromatography and tandem mass spectrometry coupled with bioinformatics to identify proteins. Size exclusion chromatography was used for protein prefractionation to preserve native forms of metalloproteins and protein complexes. Using this approach a total of 60 proteins were observed as up-regulated in cadmium-amended culture. Almost a third of the total numbers of up-regulated were metalloproteins. Particularly interesting are denitrification proteins which are over expressed but not active, suggesting their protective role in conditions of heavy metal exposure. P. aeruginosa san ai developed a complex mechanism to adapt to cadmium, based on: extracellular biosorption, bioaccumulation, the formation of biofilm, controlled siderophore production, enhanced respiration and modified protein profile. An increased abundance of proteins involved in: cell energy metabolism, including denitrification proteins; amino acid metabolism; cell motility and posttranslational modifications, primarily based on thiol-disulfide exchange, were observed. Enhanced oxygen consumption of biomass in cadmium-amended culture versus control was found. Our results signify that P. aeruginosa san ai is naturally well equipped to overcome and survive high doses of cadmium and, as such, has a great potential for application in bioremediation of cadmium polluted sites.

When exposed to cadmium a highly resistant strain P. aeruginosa san ai responds by an increased metalloprotein expression (particularly denitrification proteins), an enhanced respiration, and a pronounced thiol-disulfide protein modifications.

Optimizing FRET-FLIM Labeling Conditions to Detect Nuclear Protein Interactions at Native Expression Levels in Living Arabidopsis Roots

Protein complex formation has been extensively studied using Förster resonance energy transfer (FRET) measured by Fluorescence Lifetime Imaging Microscopy (FLIM). However, implementing this technology to detect protein interactions in living multicellular organism at single-cell resolution and under native condition is still difficult to achieve. Here we describe the optimization of the labeling conditions to detect FRET-FLIM in living plants. This study exemplifies optimization procedure involving the identification of the optimal position for the labels either at the N or C terminal region and the selection of the bright and suitable, fluorescent proteins as donor and acceptor labels for the FRET study. With an effective optimization strategy, we were able to detect the interaction between the stem cell regulators SHORT-ROOT and SCARECROW at endogenous expression levels in the root pole of living Arabidopsis embryos and developing lateral roots by FRET-FLIM. Using this approach we show that the spatial profile of interaction between two transcription factors can be highly modulated in reoccurring and structurally resembling organs, thus providing new information on the dynamic redistribution of nuclear protein complex configurations in different developmental stages. In principle, our optimization procedure for transcription factor complexes is applicable to any biological system.

Global Analysis of Membrane-associated Protein Oligomerization Using Protein Correlation Profiling

Membrane-associated proteins are required for essential processes like transport, organelle biogenesis, and signaling. Many are expected to function as part of an oligomeric protein complex. However, membrane-associated proteins are challenging to work with, and large-scale data sets on the oligomerization state of this important class of proteins is missing. Here we combined cell fractionation of Arabidopsis leaves with nondenaturing detergent solubilization and LC/MS-based profiling of size exclusion chromatography fractions to measure the apparent masses of >1350 membrane-associated proteins. Our method identified proteins from all of the major organelles, with more than 50% of them predicted to be part of a stable complex. The plasma membrane was the most highly enriched in large protein complexes compared with other organelles. Hundreds of novel protein complexes were identified. Over 150 proteins had a complicated localization pattern, and were clearly partitioned between cytosolic and membrane-associated pools. A subset of these dual localized proteins had oligomerization states that differed based on localization. Our data set is an important resource for the community that includes new functionally relevant data for membrane-localized protein complexes that could not be predicted based on sequence alone. Our method enables the analysis of protein complex localization and dynamics, and is a first step in the development of a method in which LC/MS profile data can be used to predict the composition of membrane-associated protein complexes.

Spatial Organization of Metabolic Enzyme Complexes in Cells

The organization of metabolic multienzyme complexes has been hypothesized to benefit metabolic processes and provide a coordinated way for the cell to regulate metabolism. Historically, their existence has been supported by various in vitro techniques. However, it is only recently that the existence of metabolic complexes inside living cells has come to light to corroborate this long-standing hypothesis. Indeed, subcellular compartmentalization of metabolic enzymes appears to be widespread and highly regulated. On the other hand, it is still challenging to demonstrate the functional significance of these enzyme complexes in the context of the cellular milieu. In this review, we discuss the current understanding of metabolic enzyme complexes by primarily focusing on central carbon metabolism and closely associated metabolic pathways in a variety of organisms, as well as their regulation and functional contributions to cells.

Affinity purification with metabolomic and proteomic analysis unravels diverse roles of nucleoside diphosphate kinases

Interactions between metabolites and proteins play an integral role in all cellular functions. Here we describe an affinity purification (AP) approach in combination with LC/MS-based metabolomics and proteomics that allows, to our knowledge for the first time, analysis of protein-metabolite and protein-protein interactions simultaneously in plant systems. More specifically, we examined protein and small-molecule partners of the three (of five) nucleoside diphosphate kinases present in the Arabidopsis genome (NDPK1-NDPK3). The bona fide role of NDPKs is the exchange of terminal phosphate groups between nucleoside diphosphates (NDPs) and triphosphates (NTPs). However, other functions have been reported, which probably depend on both the proteins and small molecules specifically interacting with the NDPK. Using our approach we identified 23, 17, and 8 novel protein partners of NDPK1, NDPK2, and NDPK3, respectively, with nucleotide-dependent proteins such as actin and adenosine kinase 2 being enriched. Particularly interesting, however, was the co-elution of glutathione S-transferases (GSTs) and reduced glutathione (GSH) with the affinity-purified NDPK1 complexes. Following up on this finding, we could demonstrate that NDPK1 undergoes glutathionylation, opening a new paradigm of NDPK regulation in plants. The described results extend our knowledge of NDPKs, the key enzymes regulating NDP/NTP homeostasis.

Affinity purification with metabolomic and proteomic analysis unravels diverse roles of nucleoside diphosphate kinases

Interactions between metabolites and proteins play an integral role in all cellular functions. Here we describe an affinity purification (AP) approach in combination with LC/MS-based metabolomics and proteomics that allows, to our knowledge for the first time, analysis of protein-metabolite and protein-protein interactions simultaneously in plant systems. More specifically, we examined protein and small-molecule partners of the three (of five) nucleoside diphosphate kinases present in the Arabidopsis genome (NDPK1-NDPK3). The bona fide role of NDPKs is the exchange of terminal phosphate groups between nucleoside diphosphates (NDPs) and triphosphates (NTPs). However, other functions have been reported, which probably depend on both the proteins and small molecules specifically interacting with the NDPK. Using our approach we identified 23, 17, and 8 novel protein partners of NDPK1, NDPK2, and NDPK3, respectively, with nucleotide-dependent proteins such as actin and adenosine kinase 2 being enriched. Particularly interesting, however, was the co-elution of glutathione S-transferases (GSTs) and reduced glutathione (GSH) with the affinity-purified NDPK1 complexes. Following up on this finding, we could demonstrate that NDPK1 undergoes glutathionylation, opening a new paradigm of NDPK regulation in plants. The described results extend our knowledge of NDPKs, the key enzymes regulating NDP/NTP homeostasis.

Biochemical properties and subcellular localization of tyrosine aminotransferases in Arabidopsis thaliana

Plants produce various L-tyrosine (Tyr)-derived compounds that are of pharmaceutical or nutritional importance to humans. Tyr aminotransferase (TAT) catalyzes the reversible transamination between Tyr and 4-hydroxyphenylpyruvate (HPP), the initial step in the biosynthesis of many Tyr-derived plant natural products. Herein reported is the biochemical characterization and subcellular localization of TAT enzymes from the model plant Arabidopsis thaliana. Phylogenetic analysis showed that Arabidopsis has at least two homologous TAT genes, At5g53970 (AtTAT1) and At5g36160 (AtTAT2). Their recombinant enzymes showed distinct biochemical properties: AtTAT1 had the highest activity towards Tyr, while AtTAT2 exhibited a broad substrate specificity for both amino and keto acid substrates. Also, AtTAT1 favored the direction of Tyr deamination to HPP, whereas AtTAT2 preferred transamination of HPP to Tyr. Subcellular localization analysis using GFP-fusion proteins and confocal microscopy showed that AtTAT1, AtTAT2, and HPP dioxygenase (HPPD), which catalyzes the subsequent step of TAT, are localized in the cytosol, unlike plastid-localized Tyr and tocopherol biosynthetic enzymes. Furthermore, subcellular fractionation indicated that, while HPPD activity is restricted to the cytosol, TAT activity is detected in both cytosolic and plastidic fractions of Arabidopsis leaf tissue, suggesting that an unknown aminotransferase(s) having TAT activity is also present in the plastids. Biochemical and cellular analyses of Arabidopsis TATs provide a fundamental basis for future in vivo studies and metabolic engineering for enhanced production of Tyr-derived phytochemicals in plants.

Proteomics: Technologies and Their Applications

Proteomics involves the applications of technologies for the identification and quantification of overall proteins present content of a cell, tissue or an organism. It supplements the other "omics" technologies such as genomic and transcriptomics to expound the identity of proteins of an organism, and to cognize the structure and functions of a particular protein. Proteomics-based technologies are utilized in various capacities for different research settings such as detection of various diagnostic markers, candidates for vaccine production, understanding pathogenicity mechanisms, alteration of expression patterns in response to different signals and interpretation of functional protein pathways in different diseases. Proteomics is practically intricate because it includes the analysis and categorization of overall protein signatures of a genome. Mass spectrometry with LC-MS-MS and MALDI-TOF/TOF being widely used equipment is the central among current proteomics. However, utilization of proteomics facilities including the software for equipment, databases and the requirement of skilled personnel substantially increase the costs, therefore limit their wider use especially in the developing world. Furthermore, the proteome is highly dynamic because of complex regulatory systems that control the expression levels of proteins. This review efforts to describe the various proteomics approaches, the recent developments and their application in research and analysis.

Global profiling of protein complexes: current approaches and their perspective in biomedical research

INTRODUCTION

Despite the rapid evolution of proteomic methods, protein interactions and their participation in protein complexes - an important aspect of their function - has rarely been investigated on the proteome-wide level. Disease states, such as muscular dystrophy or viral infection, are induced by interference in protein-protein interactions within complexes. The purpose of this review is to describe the current methods for global complexome analysis and to critically discuss the challenges and opportunities for the application of these methods in biomedical research. Areas covered: We discuss advancements in experimental techniques and computational tools that facilitate profiling of the complexome. The main focus is on the separation of native protein complexes via size exclusion chromatography and gel electrophoresis, which has recently been combined with quantitative mass spectrometry, for a global protein-complex profiling. The development of this approach has been supported by advanced bioinformatics strategies and fast and sensitive mass spectrometers that have allowed the analysis of whole cell lysates. The application of this technique to biomedical research is assessed, and future directions are anticipated. Expert commentary: The methodology is quite new, and has already shown great potential when combined with complementary methods for detection of protein complexes.

Unravelling plant molecular machineries through affinity purification coupled to mass spectrometry

Rather than functioning independently, proteins tend to work in concert with each other and with other macromolecules to form macromolecular complexes. Affinity purification coupled to mass spectrometry (AP-MS) can lead to a better understanding of the cellular functions of these complexes. With the development of easy purification protocols and ultra-sensitive MS, AP-MS is currently widely used for screening co-complex membership in plants. Studying complexes in their developmental context through the isolation of specific organs and tissues has now become feasible. Besides, the tagged protein can be employed for probing other interactions like protein-DNA and protein-RNA interactions. With the tools at hand, protein-centred interaction studies will greatly improve our knowledge of how plant cells wire their functional components in relation to their function.