Analysis of protein complexes in Arabidopsis leaves using size exclusion chromatography and label-free protein correlation profiling

Revealing the dynamics of fungal disease with proteomics

The occurrence and distribution of new and re-emerging fungal pathogens, along with rates of antifungal resistance, are rising across the globe, and correspondingly, so are our awareness and call for action to address this public health concern. To effectively detect, monitor, and treat fungal infections, biological insights into the mechanisms that regulate pathogenesis, influence survival, and promote resistance are urgently needed. Mass spectrometry-based proteomics is a high-resolution technique that enables the identification and quantification of proteins across diverse biological systems to better understand the biology driving phenotypes. In this review, we highlight dynamic and innovative applications of proteomics to characterize three critical fungal pathogens (i.e., Candida spp., Cryptococcus spp., and Aspergillus spp.) causing disease in humans. We present strategies to investigate the host-pathogen interface, virulence factor production, and protein-level drivers of antifungal resistance. Through these studies, new opportunities for biomarker development, drug target discovery, and immune system remodeling are discussed, supporting the use of proteomics to combat a plethora of fungal diseases threatening global health.

Integrating CORUM and co-fractionation mass spectrometry to create enhanced benchmarks for protein complex predictions

Co-fractionation mass spectrometry (CFMS) enables the discovery of protein complexes and the systems-level analysis of multimer dynamics that facilitate responses to environmental and developmental conditions. A major challenge in CFMS data analysis, and omics approaches in general, is the development of reliable benchmarks for accurate evaluation of prediction methods. CORUM is commonly used as a source of benchmark complexes for protein complex composition predictions; however, its assumption of fully assembled subunit pools often conflicts with size exclusion chromatography (SEC) and interaction predictions from CFMS experiments. To address this, we developed an integrative analysis method that leverages cross-kingdom evolutionary conservation among specific CORUM complexes and high-resolution SEC profile data from cell extracts. The resulting benchmark complexes are supported by statistical significance and consistent sizes between calculated and measured apparent masses. The approach was robust, revealing both conserved and species-specific complexes. Designed specifically for benchmark identification, this method can be applied to any species and used to evaluate protein complex predictions from other studies.

Alternative proteoforms and proteoform-dependent assemblies in humans and plants

The variability of proteins at the sequence level creates an enormous potential for proteome complexity. Exploring the depths and limits of this complexity is an ongoing goal in biology. Here, we systematically survey human and plant high-throughput bottom-up native proteomics data for protein truncation variants, where substantial regions of the full-length protein are missing from an observed protein product. In humans, Arabidopsis, and the green alga Chlamydomonas, approximately one percent of observed proteins show a short form, which we can assign by comparison to RNA isoforms as either likely deriving from transcript-directed processes or limited proteolysis. While some detected protein fragments align with known splice forms and protein cleavage events, multiple examples are previously undescribed, such as our observation of fibrocystin proteolysis and nuclear translocation in a green alga. We find that truncations occur almost entirely between structured protein domains, even when short forms are derived from transcript variants. Intriguingly, multiple endogenous protein truncations of phase-separating translational proteins resemble cleaved proteoforms produced by enteroviruses during infection. Some truncated proteins are also observed in both humans and plants, suggesting that they date to the last eukaryotic common ancestor. Finally, we describe novel proteoform-specific protein complexes, where the loss of a domain may accompany complex formation.

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.

Identification and Mapping of QTLs for Sulfur-Containing Amino Acids in Soybean (Glycine max L.)

Soybean is a major source of high-quality protein for humans and animals. The content of sulfur-containing amino acids (SAA) in soybean is insufficient, which has become the main factor limiting soybean nutrition. In this study, we used the high-density genetic maps derived from Guizao 1 and Brazil 13 to evaluate the quantitative trait loci of cysteine (Cys), methionine (Met), SAA, glycinin (7S), β-conglycinin (11S), ratio of glycinin to β-conglycinin (RGC), and protein content (PC). In genetic map linkage analysis, the major and stable 44 QTLs were detected, which shared nine bin intervals. Among them, the bin interval (bin157-bin160) on chromosome 5 was detected in multiple environments as a stable QTL, which was linked to 11S, 7S, RGC, and SSA. Based on the analysis of bioinformatics and RNA-sequencing data, 16 differentially expressed genes (DEGs) within these QTLs were selected as candidate genes. These results will help to elucidate the genetic mechanism of soybean SAA-related traits and provide the basis for the gene mining of sulfur-containing amino acids.

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.

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 proteomics analysis of Arabidopsis thaliana response to light-emitting diode of narrow wavelength 450 nm, 595 nm, and 650 nm

Incident light is a central modulator of plant growth and development. However, there are still open questions surrounding wavelength-specific plant proteomic responses. Here we applied tandem mass tag based quantitative proteomics technology to acquire an in-depth view of proteome changes in Arabidopsis thaliana response to narrow wavelength blue (B; 450 nm), amber (A; 595 nm), or red (R; 650 nm) light treatments. A total of 16,707 proteins were identified with 9120 proteins quantified across all three light treatments in three biological replicates. This enabled examination of changes in the abundance for proteins with low abundance and important regulatory roles including transcription factors and hormone signaling. Importantly, 18% (1631 proteins) of the A. thaliana proteome is differentially abundant in response to narrow wavelength lights, and changes in proteome correlate well with different morphologies exhibited by plants. To showcase the usefulness of this resource, data were placed in the context of more than thirty published datasets, providing orthogonal validation and further insights into light-specific biological pathways, including Systemic Acquired Resistance and Shade Avoidance Syndrome. This high-resolution resource for A. thaliana provides baseline data and a tool for defining molecular mechanisms that control fundamental aspects of plant response to changing light conditions, with implications in plant development and adaptation. SIGNIFICANCE: Understanding of molecular mechanisms involved in wavelength-specific response of plant is question of widespread interest both to basic researchers and to those interested in applying such knowledge to the engineering of novel proteins, as well as targeted lighting systems. Here we sought to generate a high-resolution labeling proteomic profile of plant leaves, based on exposure to specific narrow-wavelength lights. Although changes in plant physiology in response to light spectral composition is well documented, there is limited knowledge on the roles of specific light wavelengths and their impact. Most previous studies have utilized relatively broad wavebands in their experiments. These multi-wavelengths lights function in a complex signaling network, which provide major challenges in inference of wavelength-specific molecular processes that underly the plant response. Besides, most studies have compared the effect of blue and red wavelengths comparing with FL, as control. As FL light consists the mixed spectra composition of both red and blue as well as numerous other wavelengths, comparing undeniably results in inconsistent and overlapping responses that will hamper effects to elucidate the plant response to specific wavelengths [1, 2]. Monitoring plant proteome response to specific wavelengths and further compare the changes to one another, rather than comparing plants proteome to FL, is thus necessary to gain the clear insights to specific underlying biological pathways and their effect consequences in plant response. Here, we employed narrow wavelength LED lights in our design to eliminate the potential overlap in molecular responses by ensuring non-overlapping wavelengths in the light treatments. We further applied TMT-labeling technology to gain a high-resolution view on the associates of proteome changes. Our proteomics data provides an in-depth coverage suitable for system-wide analyses, providing deep insights on plant physiological processes particularly because of the tremendous increase in the amount of identified proteins which outreach the other biological data.

Methods to Analyze the Redox Reactivity of Plant Proteins

Proteins can be covalently modified by a broad range of highly reactive chemicals and redox mechanisms. Reversible redox-mediated post-translational modifications of sensitive cysteine thiol groups in proteins impact protein characteristics such as interaction behavior and activity state. Evaluating the response of proteins to redox perturbation or reactive chemical species is critical for understanding the underlying mechanisms involved and their contribution to plant stress physiology. Here we provide a detailed workflow that includes procedures for (i) purification, processing, and analysis of protein samples with redox agents, (ii) determining redox-modulated monomer to oligomer transitions using size exclusion chromatography, and (iii) activity assays for monitoring the impact of redox agents on purified enzymes and in crude extracts from plants subjected to oxidative stress. We exemplified how to apply several of the methods discussed for analyzing redox-sensing metallopeptidases, such as thimet oligopeptidases. We anticipate that these protocols should find broad applications in monitoring biochemical properties of other classes of redox-sensitive plant proteins.

Repeated exposure to epigallocatechin gallate solution or water alters bitterness intensity and salivary protein profile

Polyphenols, bitter and astringent compounds present in many healthy foods, induce varied sensory responses across individuals. These differences in liking and flavor intensity may be attributable, in part, to differences in saliva. In the current study, we tested the effect of repeated consumption of a bitter polyphenol (epigallocatechin gallate, EGCG) solution on perceived bitterness intensity and salivary protein composition. We hypothesized exposure to EGCG would cause an increase in concentrations of salivary proteins that inhibit bitterness of polyphenols. We also hypothesized that participants with higher habitual polyphenol, specifically the flavanols, intake would experience less bitterness from EGCG solutions than those with low habitual intake, and that the high flavanol consumers would be more resistant to salivary alterations. We also tested whether bovine milk casein, a food analog for salivary proteins that may suppress bitterness, would decrease bitterness intensity of the EGCG solution and mitigate effects of the intervention. Participants (N = 37) in our crossover intervention adhered to two-week periods of daily bitter (EGCG) or control (water) solution consumption. Bitterness intensity ratings and citric acid-stimulated saliva were collected at baseline and after each exposure period. Results indicate that bitterness intensity of the EGCG solution decreased after polyphenol (bitter EGCG) exposure compared to control (water) exposure. Casein addition also decreased bitterness intensity of the EGCG solution. While there was not a significant overall main effect of baseline flavanol intake on solution bitterness, there was an interaction between intervention week and baseline flavanol intake. Surprisingly, the higher flavanol intake group rated EGCG solutions as more bitter than the low and medium intake groups. Of proteins relevant to taste perception, several cystatins changed in saliva in response to the intervention. Interestingly, most of these protein alterations occurred more robustly after the control (water) exposure rather than the bitter (EGCG) exposure, suggesting that additional factors not quantified in this work may influence salivary proteins. Thus, we confirm in this study that exposure to bitterness suppresses ratings of bitterness over time, but more work needs to establish the causal factors of how diet influences salivary proteins.

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.

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.

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.

Inclusion of Oat and Yeast Culture in Sow Gestational and Lactational Diets Alters Immune and Antimicrobial Associated Proteins in Milk

Simple Summary

This study investigated the impact that supplementing sow’s gestation and lactation feed with oat alone or together with brewer’s yeast has on milk proteins and piglet growth and health. Oat and yeast supplements increased abundance of several milk proteins involved in immune protection. Piglets born from either the oat- or yeast-supplemented sows had decreased incidence of diarrhea after weaning. The average birth weights for piglets born of dams that consumed Oat were significantly greater than those that did not. However, piglets born to sows that consumed yeast in combination with oat weighed less at weaning and gained the least amount of weight post-weaning. These data suggest that oat, and to a lesser extent, yeast, added to maternal diets during gestation and lactation can positively impact milk, growth, and health of offspring but given in combination can potentially negatively affect piglet weight gain.

Abstract

Maternal diet supplementation with pro- and prebiotics is associated with decreased incidence of diarrhea and greater piglet performance. This study investigated the impact adding whole ground oat as a prebiotic, alone or in combination with a probiotic, yeast culture (YC) (Saccharomyces cerevisiae), to sow gestation and lactation rations had on milk protein composition, piglet growth, and incidence of post-weaning diarrhea (PWD). Diets: control (CON), CON + yeast culture (YC) [5 g/kg], CON + oat (15% inclusion rate) (Oat) or CON+ YC [5 g/kg] + Oat (15%) were fed the last 30 days of gestation and throughout lactation (18–21 days). Shotgun proteome analysis of day 4 and 7 postpartum milk found 36 differentially abundant proteins (P-adj < 0.1) in both Oat and YC supplemented sows relative to CON. Notable was the increased expression of antimicrobial proteins, lactoferrin and chitinase in milk of Oat and YC sows compared to CON. The levels of IgA, IgM (within colostrum and milk) and IgG (within milk) were similar across treatments. However, colostral IgG levels in Oat-supplemented sows were significantly lower (p < 0.05) than that of the control sows, IgG from Oat-supplemented sows displayed greater reactivity to E. coli-antigens compared with CON and YC. Piglets from sows that consumed Oat alone or in combination weighed significantly more (p < 0.05) at birth compared to CON and YC. However, piglets in the Oat + YC group weighed less at weaning and had the lowest weight gain (p < 0.05) postweaning, compared with CON. Taken together with the observation that piglets of either YC- or Oat-fed sows had less PWD compared to CON and YC+ Oat suggests that Oat or YC supplementation positively impacts piglets through expression of certain milk-associated immune and antimicrobial proteins.

Addition of chocolate milk to diet corresponds to protein concentration changes in human saliva

Salivary proteins have the potential to alter oral sensory perception of foods. In rodents, dietary polyphenol exposure increases salivary concentrations of polyphenol-binding proteins and several cystatins, which correlate with less aversion to polyphenol-rich solutions. If similar salivary shifts occur in humans, then increasing dietary polyphenols may improve orosensory experience of polyphenol-rich foods. We hypothesized that small dietary changes, focused on polyphenols, would increase expression of salivary binding proteins for polyphenols and thus suppress unpleasant polyphenol sensations. However, analogs of salivary polyphenol-binding proteins are found in foods. Thus, we also hypothesized that food-sourced analogs of these salivary proteins would mitigate changes in saliva and sensation. Human subjects (N=55) alternated weeks of consuming a low polyphenol diet and then a regular diet plus a polyphenol-rich chocolate milk (almond, containing no polyphenol-binding proteins, or bovine, containing polyphenol-binding proteins). Statistical analyses revealed both chocolate milk interventions corresponded to changes in relative expression of 96 proteins and calculated concentration of 146 proteins (both after correction for false discovery rate), out of 1,176 proteins identified through proteomics. Of the proteins that changed, proline-rich proteins and cystatins were noticeable, which reflects prior work in animal studies. Subjects rated all chocolate milks as less flavorful after the bovine chocolate milk intervention week compared to low polyphenol weeks, but generally sensory changes were minimal. However, the results confirm that dietary changes coincide with salivary changes, and that some of those changes occur in proteins that have potential to influence oral sensations.

Recent advances on protein separation and purification methods

Protein, as the material basis of vita, is the crucial undertaker of life activities, which constitutes the framework and main substance of human tissues and organs, and takes part in various forms of life activities in organisms. Separating proteins from biomaterials and studying their structures and functions are of great significance for understanding the law of life activities and clarifying the essence of life phenomena. Therefore, scientists have proposed the new concept of proteomics, in which protein separation technology plays a momentous role. It has been diffusely used in the food industry, agricultural biological research, drug development, disease mechanism, plant stress mechanism, and marine environment research. In this paper, combined with the recent research situation, the progress of protein separation technology was reviewed from the aspects of extraction, precipitation, membrane separation, chromatography, electrophoresis, molecular imprinting, microfluidic chip and so on.

Proteomic identification of aerobic glycolysis as a potential metabolic target for methylglyoxal in adipocytes

Obesity is often accompanied by metabolic changes in adipocytes that are closely associated with metabolic disease. Although high sugar consumption contributes to obesity, it may also directly affect adipocytes by increasing the rate of glycolysis and formation of the glycolytic by-product methylglyoxal (MG). MG is a reactive dicarbonyl that irreversibly damages proteins and other cellular components. Although the accumulation of MG is clinically associated with hyperglycemia and diabetic complications, a better understanding of how proteins are regulated by MG is needed to evaluate its role in the pathogenesis of metabolic disease. Because adipocytes rely heavily on glycolysis for glucose disposal, we hypothesized that prolonged MG treatment at nontoxic concentrations would impact the landscape of proteins involved in glucose metabolism. To test this hypothesis, we treated 3T3-L1 adipocytes with MG (100 μmol/L) and used comparative proteomics to assess the effects. We identified 25 differentially expressed proteins in adipocytes treated with MG compared to the control. Our results suggested that MG induced metabolic changes typically associated with aerobic glycolysis, including a lowered expression of proteins involved in oxidative metabolism and increased expression of the glycolytic enzymes L-lactate dehydrogenase and glyceraldehyde-3-phosphate dehydrogenase. The detection of increased lactate secreted into the culture media of adipocytes treated with MG further supported these findings, as did gene expression analysis. In summary, these results indicate MG as a metabolic contributor to aerobic glycolysis in adipocytes, a potential adaptive response to increased glucose flux which over time could lead to permanent metabolic changes.

High-throughput, Label-Free Quantitative Proteomic Studies of the Anticancer Effects of Electrical Pulses with Turmeric Silver Nanoparticles: an in vitro Model Study

Triple negative breast cancer (TNBC) represents 15–20% of the over one million new breast cancer cases occurring each year. TNBC is an aggressive cancer phenotype, with low 5-year survival rates, high 3-year recurrence rates, and increased risk of metastasis. A lack of three commonly exploited hormone receptors renders TNBC resistant to endocrine therapies and lends to its critical absence of viable therapeutic targets. This necessitates the development of alternate and effective novel therapeutic strategies for TNBC. Towards this, our current work seeks to develop the technique of Electrical pulse (EP)-mediated Turmeric silver nanoparticles (TurNP) therapy, known as Electrochemotherapy (ECT), to effectively target TNBC cells. This technique involves the efficient delivery of natural bioactive molecules with anti-cancer effects via a biophysical means. In these experiments, the bioactive molecules are turmeric, a dried rhizome of Curcuma longa that has been used for centuries, both as a dietary supplement and as a medicine in Ayurveda (science of life) in the Indian subcontinent and in traditional Chinese medicine. Our results reveal the combined effect of TurNP + EP treatment in reducing MDA-MB-231 cell viability to as low as 9% at 12 h. Showing biological selectivity, this combination treatment has a substantially lower effect on non-tumorigenic mammary epithelial MCF10A cells (67% viability). To gain mechanistic insights into the actions of TurNP-based ECT treatment, we performed high-throughput, label-free quantitative proteomics studies. Proteomics results indicate that TurNP + EP treatment significantly influenced expression of a diverse list of proteins, including receptors, transcription factors, structural proteins, kinases, and metabolic enzymes. This include the downregulation of 25 proteins in PI3K-Akt signaling pathway (such as GRB2, EGFR, EPHA2, GNB1, GNB2, 14–3–3 family, and Integrin family proteins), and 12 proteins (AKR1A1, ALDOA, ALDOC, PGK1, PGM1, PGAM1, ENO1, ENO2, GAPDH, TPI1, LDHA, and LDHB) in the glycolytic pathway with concomitant reduction in metabolite levels (glucose uptake, and intracellular- lactate, glutamine, and glutamate). Compared to TurNP alone, TurNP + EP treatment upregulated 66 endoplasmic reticulum and 193 mitochondrial proteins, enhancing several processes and pathways, including Pyruvate Metabolism, Tricarboxylic acid (TCA) cycle, and Oxidative Phosphorylation (OXPHOS), which redirected the TNBC metabolism to mitochondria. This switch in the metabolism caused excessive production of H₂O₂ reactive oxygen species (ROS) to inflict cell death in MDA-MB-231 cells, demonstrating the potency of this treatment.

A Pan-plant Protein Complex Map Reveals Deep Conservation and Novel Assemblies

Plants are foundational for global ecological and economic systems, but most plant proteins remain uncharacterized. Protein interaction networks often suggest protein functions and open new avenues to characterize genes and proteins. We therefore systematically determined protein complexes from 13 plant species of scientific and agricultural importance, greatly expanding the known repertoire of stable protein complexes in plants. By using co-fractionation mass spectrometry, we recovered known complexes, confirmed complexes predicted to occur in plants, and identified previously unknown interactions conserved over 1.1 billion years of green plant evolution. Several novel complexes are involved in vernalization and pathogen defense, traits critical for agriculture. We also observed plant analogs of animal complexes with distinct molecular assemblies, including a megadalton-scale tRNA multi-synthetase complex. The resulting map offers a cross-species view of conserved, stable protein assemblies shared across plant cells and provides a mechanistic, biochemical framework for interpreting plant genetics and mutant phenotypes.

PROMIS: Global Analysis of PROtein-Metabolite Interactions

Small molecules are not only intermediates of metabolism, but also play important roles in signaling and in controlling cellular metabolism, growth, and development. Although a few systematic studies have been conducted, the true extent of protein-small molecule interactions in biological systems remains unknown. PROtein-metabolite interactions using size separation (PROMIS) is a method for studying protein-small molecule interactions in a non-targeted, proteome- and metabolome-wide manner. This approach uses size-exclusion chromatography followed by proteomics and metabolomics liquid chromatography-mass spectrometry analysis of the collected fractions. Assuming that small molecules bound to proteins would co-fractionate together, we found numerous small molecules co-eluting with proteins, strongly suggesting the formation of stable complexes. Using PROMIS, we identified known small molecule-protein complexes, such as between enzymes and cofactors, and also found novel interactions. © 2019 The Authors. Basic Protocol 1: Preparation of native cell lysate from plant material Support Protocol: Bradford assay to determine protein concentration Basic Protocol 2: Separation of molecular complexes using size-exclusion chromatography Basic Protocol 3: Simultaneous extraction of proteins and metabolites using single-step extraction protocol Basic Protocol 4: Metabolomics analysis Basic Protocol 5: Proteomics analysis.

Next-generation Interactomics: Considerations for the Use of Co-elution to Measure Protein Interaction Networks

Understanding how proteins interact is crucial to understanding cellular processes. Among the available interactome mapping methods, co-elution stands out as a method that is simultaneous in nature and capable of identifying interactions between all the proteins detected in a sample. The general workflow in co-elution methods involves the mild extraction of protein complexes and their separation into several fractions, across which proteins bound together in the same complex will show similar co-elution profiles when analyzed appropriately. In this review we discuss the different separation, quantification and bioinformatic strategies used in co-elution studies, and the important considerations in designing these studies. The benefits of co-elution versus other methods makes it a valuable starting point when asking questions that involve the perturbation of the interactome.

Differential distributions of trafficking and signaling proteins of the maize ER-Golgi apparatus

The Endoplasmic Reticulum (ER)-Golgi apparatus of plants is the site of synthesis of non-cellulosic polysaccharides that then traffic to the cell wall. A two-step protocol of flotation centrifugation followed by free-flow electrophoresis (FFE) resolved ER and Golgi proteins into three profiles: an ER-rich fraction, two Golgi-rich fractions, and an intermediate fraction enriched in cellulose synthases. Nearly three dozen Rab-like proteins of eight different subgroups were distributed differentially in ER- vs. Golgi-rich fractions, whereas seven 14-3-3 proteins co-fractionated with cellulose synthases in the intermediate fraction. FFE offers a powerful means to classify resident and transient proteins in cell-free assays of cellular location.

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.

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.

Performance evaluation measures for protein complex prediction

Protein complexes play a dominant role in cellular organization and function. Prediction of protein complexes from the network of physical interactions between proteins (PPI networks) has thus become one of the important research areas. Recently, many computational approaches have been developed to identify these complexes. Various performance assessment measures have been proposed for evaluating the efficiency of these methods. However, there are many inconsistencies in the definitions and usage of the measures across the literature. To address this issue, we have gathered and presented the most important performance evaluation measures and developed a tool, named CompEvaluator, to critically assess the protein complex prediction methods. The tool and documentation are publicly available at https://sourceforge.net/projects/compevaluator/files/.

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.

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.

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World

The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.

Diet Impacts Pre-implantation Histotroph Proteomes in Beef Cattle

In ruminants, the period from fertilization to implantation is relatively prolonged, and the survival of embryos depends on uterine secretions known as histotroph. Our objective was to determine if the pre-breeding diet affected histotroph proteomes in beef cattle. Cows were assigned to one of four diets: a control diet (CON), a high-protein diet (PROT), a high-fat diet (OIL), or a high-protein and high-fat diet (PROT + OIL). After 185 days on these diets, an intravaginal progesterone implant (CIDR) was inserted for 7 days. At 9 days after CIDR removal, animals with a corpus luteum were selected ( n = 16; 4 per treatment). Proteins were isolated from the histotroph collected by uterine lavage and analyzed with liquid chromatography-tandem mass spectrometry. Over 2000 proteins were expressed ( n ≥ 3 cows per treatment), with 1239 proteins being common among all of the groups. There were 20, 37, 85, and 123 proteins unique to CON, PROT + OIL, PROT, and OIL, respectively. Relative to CON, 23, 14, and 51 proteins were differentially expressed in PROT + OIL, PROT, and OIL, respectively. Functional analysis found that 53% of histotroph proteins were categorized as extracellular exosome, 3.28% as cell-cell adhesion, and 17.4% in KEGG metabolic pathways. Differences in proteomes among treatments support the idea that pre-breeding diet affects histotroph. Understanding the impact of diet on histotroph proteins may help improve conception rates.

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.

MADS transcription factors cooperate: complexities of complex formation

This article comments on: Rümpler F, Theißen G, Melzer R. 2018. A conserved leucine zipper-like motif accounts for strong tetramerization capabilities of SEPALLATA-like MADS-domain transcription factors. Journal of Experimental Botany 69, 1943–1954.

Proteomic analysis of RAW macrophages treated with cGAMP or c-di-GMP reveals differentially activated cellular pathways

Global and quantitative analysis of the proteome help to reveal how host cells sense invading bacteria and respond to bacterial signaling molecules. Here, we performed label free quantitative proteomic analysis of RAW macrophages treated with host-derived cGAMP and bacterial-derived c-di-GMP, in an attempt to identify cellular pathways impacted by these dinucleotides and determine if the host responds differentially to these two cyclic dinucleotides. We identified a total of 3811 proteins of which abundances of 404 proteins in cGAMP and 236 proteins in c-di-GMP treated cells were significantly different compared to the control. Many of the proteins that were strongly and commonly upregulated, such as interferon-induced proteins 47, 202 and 204 (Ifi47, Ifi202, Ifi204), ubiquitin-activating enzyme E7 (Uba7), interferon-induced protein with tetratricopeptide repeats 1, 2 or 3 (Ifit1, Ifit2, Ifit3), ubiquitin-like protein ISG15 (ISG15), might be due to the fact that both dinucleotides promote the production of interferons, which induce the expression of many proteins. However, there were also other proteins that were differentially affected by cGAMP or c-di-GMP treatment, including probable ATP-dependent RNA helicase DHX58 (Dhx58), nuclear autoantigen Sp-100 (Sp100), MARCKS-related protein (Marcksl1) and antigen peptide transporter 2 (Tap2). This is probably due to the differential levels of IFNs produced by the dinucleotides or may indicate that non-STING activation might also contribute to the host's response to c-di-GMP and cGAMP. Interestingly Trex1, a nuclease that degrades DNA (an activator of cGAS to produce cGAMP), was upregulated (3.22 fold) upon cGAMP treatment, hinting at a possible feedback loop to regulate cGAMP synthesis. These results lay a foundation for future studies to better characterize and understand the complex c-di-GMP and cGAMP signaling network.

cGAMP modulates proteins involved in antigen presentation and inflammation.

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.