Try or Die: Dynamics of Plant Respiration and How to Survive Low Oxygen Conditions

Fluctuations in oxygen (O2) availability occur as a result of flooding, which is periodically encountered by terrestrial plants. Plant respiration and mitochondrial energy generation rely on O2 availability. Therefore, decreased O2 concentrations severely affect mitochondrial function. Low O2 concentrations (hypoxia) induce cellular stress due to decreased ATP production, depletion of energy reserves and accumulation of metabolic intermediates. In addition, the transition from low to high O2 in combination with light changes—as experienced during re-oxygenation—leads to the excess formation of reactive oxygen species (ROS). In this review, we will update our current knowledge about the mechanisms enabling plants to adapt to low-O2 environments, and how to survive re-oxygenation. New insights into the role of mitochondrial retrograde signaling, chromatin modification, as well as moonlighting proteins and mitochondrial alternative electron transport pathways (and their contribution to low O2 tolerance and survival of re-oxygenation), are presented.

Effect of 2-Cys Peroxiredoxins Inhibition on Redox Modifications of Bull Sperm Proteins

Sperm peroxiredoxins (PRDXs) are moonlighting proteins which, in addition to their antioxidant activity, also act as redox signal transducers through PRDX-induced oxidative post-translational modifications of proteins (oxPTMs). Despite extensive knowledge on the antioxidant activity of PRDXs, the mechanisms related to PRDX-mediated oxPTMs are poorly understood. The present study aimed to investigate the effect of bull sperm 2-Cys PRDX inhibition by Conoidin A on changes in oxPTM levels under control and oxidative stress conditions. The results showed that a group of sperm mitochondrial (LDHAL6B, CS, ACO2, SDHA, ACAPM) and actin cytoskeleton proteins (CAPZB, ALDOA, CCIN) is oxidized due to the action of 2-Cys PRDXs under control conditions. In turn, under oxidative stress conditions, 2-Cys PRDX activity seems to be focused on antioxidant function protecting glycolytic, TCA pathway, and respiratory chain enzymes; chaperones; and sperm axonemal tubulins from oxidative damage. Interestingly, the inhibition of PRDX resulted in oxidation of a group of rate-limiting glycolytic proteins, which is known to trigger the switching of glucose metabolism from glycolysis to pentose phosphate pathway (PPP). The obtained results are expected to broaden the knowledge of the potential role of bull sperm 2-Cys in both redox signal transmission and antioxidant activity.

Leukocyte Membrane Enzymes Play the Cell Adhesion Game

For a long time, proteins with enzymatic activity have not been usually considered to carry out other functions different from catalyzing chemical reactions within or outside the cell. Nevertheless, in the last few years several reports have uncovered the participation of numerous enzymes in other processes, placing them in the category of moonlighting proteins. Some moonlighting enzymes have been shown to participate in complex processes such as cell adhesion. Cell adhesion plays a physiological role in multiple processes: it enables cells to establish close contact with one another, allowing communication; it is a key step during cell migration; it is also involved in tightly binding neighboring cells in tissues, etc. Importantly, cell adhesion is also of great importance in pathophysiological scenarios like migration and metastasis establishment of cancer cells. Cell adhesion is strictly regulated through numerous switches: proteins, glycoproteins and other components of the cell membrane. Recently, several cell membrane enzymes have been reported to participate in distinct steps of the cell adhesion process. Here, we review a variety of examples of membrane bound enzymes participating in adhesion of immune cells.

Towards understanding the novel adhesin function of Candida albicans phosphoglycerate mutase at the pathogen cell surface: some structural analysis of the interactions with human host extracellular matrix proteins

Although many atypical proteinaceous cell wall components that belong to a group of multitasking, "moonlighting" proteins, have been repeatedly identified in numerous pathogenic microorganisms, their novel extracellular functions and secretion mechanisms remain largely unrecognized. In Candida albicans, one of the most common fungal pathogens in humans, phosphoglycerate mutase (Gpm1) - a cytoplasmic enzyme involved in the glycolysis pathway - has been shown to occur on the cell surface and has been identified as a potentially important virulence factor. In this study, we demonstrated tight binding of C. albicans Gpm1 to the candidal cell surface, thus suggesting that the readsorption of soluble Gpm1 from the external environment could be a likely mechanism leading to the presence of this moonlighting protein on the pathogen surface. Several putative Gpm1-binding receptors on the yeast surface were identified. The affinities of Gpm1 to human vitronectin (VTR) and fibronectin (FN) were characterized with surface plasmon resonance measurements, and the dissociation constants of the complexes formed were determined to be in the order of 10–8 M. The internal Gpm1 sequence motifs, directly interacting with VTR (aa 116-158) and FN (aa 138-175) were mapped using chemical crosslinking and mass spectrometry. Synthetic peptides with matching sequences significantly inhibited formation of the Gpm1-VTR and Gpm1-FN complexes. A molecular model of the Gpm1-VTR complex was developed. These results provide the first structural insights into the adhesin function of candidal surface-exposed Gpm1.

Functional Crypto-Adenylate Cyclases Operate in Complex Plant Proteins

Adenylyl cyclases (ACs) and their catalytic product cAMP are regulatory components of many plant responses. Here, we show that an amino acid search motif based on annotated adenylate cyclases (ACs) identifies 12 unique Arabidopsis thaliana candidate ACs, four of which have a role in the biosynthesis of the stress hormone abscisic acid (ABA). One of these, the 9-cis-epoxycarotenoid dioxygenase (NCED3 and At3g14440), was identified by sequence and structural analysis as a putative AC and then tested experimentally with two different methods. Given that the in vitro activity is low (fmoles cAMP pmol−1 protein min−1), but highly reproducible, we term the enzyme a crypto-AC. Our results are consistent with a role for ACs with low activities in multi-domain moonlighting proteins that have at least one other distinct molecular function, such as catalysis or ion channel activation. We propose that crypto-ACs be examined from the perspective that considers their low activities as an innate feature of regulatory ACs embedded within multi-domain moonlighting proteins. It is therefore conceivable that crypto-ACs form integral components of complex plant proteins participating in intra-molecular regulatory mechanisms, and in this case, potentially linking cAMP to ABA synthesis.

IdentPMP: identification of moonlighting proteins in plants using sequence-based learning models

Background A moonlighting protein refers to a protein that can perform two or more functions. Since the current moonlighting protein prediction tools mainly focus on the proteins in animals and microorganisms, and there are differences in the cells and proteins between animals and plants, these may cause the existing tools to predict plant moonlighting proteins inaccurately. Hence, the availability of a benchmark data set and a prediction tool specific for plant moonlighting protein are necessary. Methods This study used some protein feature classes from the data set constructed in house to develop a web-based prediction tool. In the beginning, we built a data set about plant protein and reduced redundant sequences. We then performed feature selection, feature normalization and feature dimensionality reduction on the training data. Next, machine learning methods for preliminary modeling were used to select feature classes that performed best in plant moonlighting protein prediction. This selected feature was incorporated into the final plant protein prediction tool. After that, we compared five machine learning methods and used grid searching to optimize parameters, and the most suitable method was chosen as the final model. Results The prediction results indicated that the eXtreme Gradient Boosting (XGBoost) performed best, which was used as the algorithm to construct the prediction tool, called IdentPMP (Identification of Plant Moonlighting Proteins). The results of the independent test set shows that the area under the precision-recall curve (AUPRC) and the area under the receiver operating characteristic curve (AUC) of IdentPMP is 0.43 and 0.68, which are 19.44% (0.43 vs. 0.36) and 13.33% (0.68 vs. 0.60) higher than state-of-the-art non-plant specific methods, respectively. This further demonstrated that a benchmark data set and a plant-specific prediction tool was required for plant moonlighting protein studies. Finally, we implemented the tool into a web version, and users can use it freely through the URL: http://identpmp.aielab.net/.

Pathogen Moonlighting Proteins: From Ancestral Key Metabolic Enzymes to Virulence Factors

Moonlighting and multitasking proteins refer to proteins with two or more functions performed by a single polypeptide chain. An amazing example of the Gain of Function (GoF) phenomenon of these proteins is that 25% of the moonlighting functions of our Multitasking Proteins Database (MultitaskProtDB-II) are related to pathogen virulence activity. Moreover, they usually have a canonical function belonging to highly conserved ancestral key functions, and their moonlighting functions are often involved in inducing extracellular matrix (ECM) protein remodeling. There are three main questions in the context of moonlighting proteins in pathogen virulence: (A) Why are a high percentage of pathogen moonlighting proteins involved in virulence? (B) Why do most of the canonical functions of these moonlighting proteins belong to primary metabolism? Moreover, why are they common in many pathogen species? (C) How are these different protein sequences and structures able to bind the same set of host ECM protein targets, mainly plasminogen (PLG), and colonize host tissues? By means of an extensive bioinformatics analysis, we suggest answers and approaches to these questions. There are three main ideas derived from the work: first, moonlighting proteins are not good candidates for vaccines. Second, several motifs that might be important in the adhesion to the ECM were identified. Third, an overrepresentation of GO codes related with virulence in moonlighting proteins were seen.

Moonlighting Proteins: The Case of the Hexokinases

Moonlighting proteins are defined as proteins with two or more functions that are unrelated and independent to each other, so that inactivation of one of them should not affect the second one and vice versa. Intriguingly, all the glycolytic enzymes are described as moonlighting proteins in some organisms. Hexokinase (HXK) is a critical enzyme in the glycolytic pathway and displays a wide range of functions in different organisms such as fungi, parasites, mammals, and plants. This review discusses HXKs moonlighting functions in depth since they have a profound impact on the responses to nutritional, environmental, and disease challenges. HXKs’ activities can be as diverse as performing metabolic activities, as a gene repressor complexing with other proteins, as protein kinase, as immune receptor and regulating processes like autophagy, programmed cell death or immune system responses. However, most of those functions are particular for some organisms while the most common moonlighting HXK function in several kingdoms is being a glucose sensor. In this review, we also analyze how different regulation mechanisms cause HXK to change its subcellular localization, oligomeric or conformational state, the response to substrate and product concentration, and its interactions with membrane, proteins, or RNA, all of which might impact the HXK moonlighting functions.

Moonlighting protein prediction using physico-chemical and evolutional properties via machine learning methods

Background Moonlighting proteins (MPs) are a subclass of multifunctional proteins in which more than one independent or usually distinct function occurs in a single polypeptide chain. Identification of unknown cellular processes, understanding novel protein mechanisms, improving the prediction of protein functions, and gaining information about protein evolution are the main reasons to study MPs. They also play an important role in disease pathways and drug-target discovery. Since detecting MPs experimentally is quite a challenge, most of them are detected randomly. Therefore, introducing an appropriate computational approach to predict MPs seems reasonable. Results In this study, we introduced a competent model for detecting moonlighting and non-MPs through extracted features from protein sequences. We attempted to set up a well-judged scheme for detecting outlier proteins. Consequently, 37 distinct feature vectors were utilized to study each protein’s impact on detecting MPs. Furthermore, 8 different classification methods were assessed to find the best performance. To detect outliers, each one of the classifications was executed 100 times by tenfold cross-validation on feature vectors; proteins which misclassified 90 times or more were grouped. This process was applied to every single feature vector and eventually the intersection of these groups was determined as the outlier proteins. The results of tenfold cross-validation on a dataset of 351 samples (containing 215 moonlighting and 136 non-moonlighting proteins) reveal that the SVM method on all feature vectors has the highest performance among all methods in this study and other available methods. Besides, the study of outliers showed that 57 of 351 proteins in the dataset could be an appropriate candidate for the outlier. Among the outlier proteins, there were non-MPs (such as P69797) that have been misclassified in 8 different classification methods with 16 different feature vectors. Because these proteins have been obtained by computational methods, the results of this study could reduce the likelihood of hypothesizing whether these proteins are non-moonlighting at all. Conclusions MPs are difficult to be identified through experimentation. Using distinct feature vectors, our method enabled identification of novel moonlighting proteins. The study also pinpointed that a number of non-MPs are likely to be moonlighting.

Moonlighting in Bacillus subtilis: The Small Proteins SR1P and SR7P Regulate the Moonlighting Activity of Glyceraldehyde 3-Phosphate Dehydrogenase A (GapA) and Enolase in RNA Degradation

Moonlighting proteins are proteins with more than one function. During the past 25 years, they have been found to be rather widespread in bacteria. In Bacillus subtilis, moonlighting has been disclosed to occur via DNA, protein or RNA binding or protein phosphorylation. In addition, two metabolic enzymes, enolase and phosphofructokinase, were localized in the degradosome-like network (DLN) where they were thought to be scaffolding components. The DLN comprises the major endoribonuclease RNase Y, 3′-5′ exoribonuclease PnpA, endo/5′-3′ exoribonucleases J1/J2 and helicase CshA. We have ascertained that the metabolic enzyme GapA is an additional component of the DLN. In addition, we identified two small proteins that bind scaffolding components of the degradosome: SR1P encoded by the dual-function sRNA SR1 binds GapA, promotes the GapA-RNase J1 interaction and increases the RNase J1 activity. SR7P encoded by the dual-function antisense RNA SR7 binds to enolase thereby enhancing the enzymatic activity of enolase bound RNase Y. We discuss the role of small proteins in modulating the activity of two moonlighting proteins.