Moonlighting proteins: complications and implications for proteomics research

Moonlighting enzymes: when cellular context defines specificity

It is not often realized that the absolute protein specificity is an exception rather than a rule. Two major kinds of protein multi-specificities are promiscuity and moonlighting. This review discusses the idea of enzyme specificity and then focusses on moonlighting. Some important examples of protein moonlighting, such as crystallins, ceruloplasmin, metallothioniens, macrophage migration inhibitory factor, and enzymes of carbohydrate metabolism are discussed. How protein plasticity and intrinsic disorder enable the removing the distinction between enzymes and other biologically active proteins are outlined. Finally, information on important roles of moonlighting in human diseases is updated.

De novo Prediction of Moonlighting Proteins Using Multimodal Deep Ensemble Learning

Moonlighting proteins (MPs) are a special type of protein with multiple independent functions. MPs play vital roles in cellular regulation, diseases, and biological pathways. At present, very few MPs have been discovered by biological experiments. Due to the lack of data sample, computation-based methods to identify MPs are limited. Currently, there is no de-novo prediction method for MPs. Therefore, systematic research and identification of MPs are urgently required. In this paper, we propose a multimodal deep ensemble learning architecture, named MEL-MP, which is the first de novo computation model for predicting MPs. First, we extract four sequence-based features: primary protein sequence information, evolutionary information, physical and chemical properties, and secondary protein structure information. Second, we select specific classifiers for each kind of feature. Finally, we apply the stacked ensemble to integrate the output of each classifier. Through comprehensive model selection and cross-validation experiments, it is shown that specific classifiers for specific feature types can achieve superior performance. For validating the effectiveness of the fusion-based stacked ensemble, different feature fusion strategies including direct combination and a multimodal deep auto-encoder are used for comparative purposes. MEL-MP is shown to exhibit superior prediction performance (F-score = 0.891), surpassing the existing machine learning model, MPFit (F-score = 0.784). In addition, MEL-MP is leveraged to predict the potential MPs among all human proteins. Furthermore, the distribution of predicted MPs on different chromosomes, the evolution of MPs, the association of MPs with diseases, and the functional enrichment of MPs are also explored. Finally, for maximum convenience, a user-friendly web server is available at: http://ml.csbg-jlu.site/mel-mp/.

Multitalented actors inside and outside the cell: recent discoveries add to the number of moonlighting proteins

During the past few decades, it's become clear that many enzymes evolved not only to act as specific, finely tuned and carefully regulated catalysts, but also to perform a second, completely different function in the cell. In general, these moonlighting proteins have a single polypeptide chain that performs two or more distinct and physiologically relevant biochemical or biophysical functions. This mini-review describes examples of moonlighting proteins that have been found within the past few years, including some that play key roles in human and animal diseases and in the regulation of biochemical pathways in food crops. Several belong to two of the most common subclasses of moonlighting proteins: trigger enzymes and intracellular/surface moonlighting proteins, but a few represent less often observed combinations of functions. These examples also help illustrate some of the current methods used for identifying proteins with multiple functions. In general, a greater understanding about the functions and molecular mechanisms of moonlighting proteins, their roles in the regulation of cellular processes, and their involvement in health and disease could aid in many areas including developing new antibiotics, predicting the functions of the millions of proteins being identified through genome sequencing projects, designing novel proteins, using biological circuitry analysis to construct bacterial strains that are better producers of materials for industrial use, and developing methods to tweak biochemical pathways for increasing yields of food crops.

DextMP: deep dive into text for predicting moonlighting proteins

Motivation

Moonlighting proteins (MPs) are an important class of proteins that perform more than one independent cellular function. MPs are gaining more attention in recent years as they are found to play important roles in various systems including disease developments. MPs also have a significant impact in computational function prediction and annotation in databases. Currently MPs are not labeled as such in biological databases even in cases where multiple distinct functions are known for the proteins. In this work, we propose a novel method named DextMP, which predicts whether a protein is a MP or not based on its textual features extracted from scientific literature and the UniProt database.

Results

DextMP extracts three categories of textual information for a protein: titles, abstracts from literature, and function description in UniProt. Three language models were applied and compared: a state-of-the-art deep unsupervised learning algorithm along with two other language models of different types, Term Frequency-Inverse Document Frequency in the bag-of-words and Latent Dirichlet Allocation in the topic modeling category. Cross-validation results on a dataset of known MPs and non-MPs showed that DextMP successfully predicted MPs with over 91% accuracy with significant improvement over existing MP prediction methods. Lastly, we ran DextMP with the best performing language models and text-based feature combinations on three genomes, human, yeast and Xenopus laevis, and found that about 2.5–35% of the proteomes are potential MPs.

Availability and Implementation

Code available at http://kiharalab.org/DextMP.

Genome-scale prediction of moonlighting proteins using diverse protein association information

MOTIVATION

Moonlighting proteins (MPs) show multiple cellular functions within a single polypeptide chain. To understand the overall landscape of their functional diversity, it is important to establish a computational method that can identify MPs on a genome scale. Previously, we have systematically characterized MPs using functional and omics-scale information. In this work, we develop a computational prediction model for automatic identification of MPs using a diverse range of protein association information.

RESULTS

We incorporated a diverse range of protein association information to extract characteristic features of MPs, which range from gene ontology (GO), protein-protein interactions, gene expression, phylogenetic profiles, genetic interactions and network-based graph properties to protein structural properties, i.e. intrinsically disordered regions in the protein chain. Then, we used machine learning classifiers using the broad feature space for predicting MPs. Because many known MPs lack some proteomic features, we developed an imputation technique to fill such missing features. Results on the control dataset show that MPs can be predicted with over 98% accuracy when GO terms are available. Furthermore, using only the omics-based features the method can still identify MPs with over 75% accuracy. Last, we applied the method on three genomes: Saccharomyces cerevisiae, Caenorhabditis elegans and Homo sapiens, and found that about 2-10% of proteins in the genomes are potential MPs.

AVAILABILITY AND IMPLEMENTATION

Code available at http://kiharalab.org/MPprediction

CONTACT

dkihara@purdue.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Protein species and moonlighting proteins: Very small changes in a protein's covalent structure can change its biochemical function

In the past few decades, hundreds of moonlighting proteins have been identified that perform two or more distinct and physiologically relevant biochemical or biophysical functions that are not due to gene fusions, multiple RNA splice variants, or pleiotropic effects. For this special issue on protein species, this article discusses three topics related to moonlighting proteins that illustrate how small changes or differences in protein covalent structures can result in different functions. Examples are given of moonlighting proteins that switch between functions after undergoing post-translational modifications (PTMs), proteins that share high levels of amino acid sequence identity to a moonlighting protein but share only one of its functions, and several "neomorphic moonlighting proteins" in which a single amino acid mutation results in the addition of a new function.

BIOLOGICAL SIGNIFICANCE

For this special issue on protein species, this article discusses three topics related to moonlighting proteins : Post-translational modifications (PTMs) that can cause a switch between functions, homologs that share only one of multiple functions, and proteins in which a single amino acid mutation results in the creation of a new function. The examples included illustrate that even in an average protein of hundreds of amino acids, a relatively small difference in sequence or PTMs can result in a large difference in function, which can be important in predicting protein functions, regulation of protein functions, and in the evolution of new functions.

Ten years of subproteome investigations in lactic acid bacteria: A key for food starter and probiotic typing

The definition of safety and efficacy of food-employed bacteria as well as probiotic strains is a continuous, often unattended, challenge. Proteomic techniques such as 2DE, DIGE and LC/LC-MS/MS are suitable and powerful tools to reveal new aspects (positive and negative) of "known" and "unknown" strains that can be employed in food making and as nutraceutical supplements for human health. Unfortunately, these techniques are not used as extensively as it should be wise. The present report describes the most significant results obtained by our research group in 10years of study on subproteomes in bacteria, chiefly lactic acid bacteria. Production of desired and undesired metabolites, differences between strains belonging to same species but isolated from different ecological niches, the effect of cryoprotectants on survival to lyophilization as well as the adhesive capability of strains, were elucidated by analysis of cytosolic, membrane-enriched, surface and extracellular proteomes. The present review opens a window on a yet largely underexplored field and highlights the huge potential of subproteome investigations for more rational choice of microbial strains as food starters, probiotics and for production of nutraceuticals. These analyses will hopefully contribute to manufacturing safer and healthier food and food supplements in the near future. This article is part of a Special Issue entitled: HUPO 2014.

Genome-scale identification and characterization of moonlighting proteins

BACKGROUND

Moonlighting proteins perform two or more cellular functions, which are selected based on various contexts including the cell type they are expressed, their oligomerization status, and the binding of different ligands at different sites. To understand overall landscape of their functional diversity, it is important to establish methods that can identify moonlighting proteins in a systematic fashion. Here, we have developed a computational framework to find moonlighting proteins on a genome scale and identified multiple proteomic characteristics of these proteins.

RESULTS

First, we analyzed Gene Ontology (GO) annotations of known moonlighting proteins. We found that the GO annotations of moonlighting proteins can be clustered into multiple groups reflecting their diverse functions. Then, by considering the observed GO term separations, we identified 33 novel moonlighting proteins in Escherichia coli and confirmed them by literature review. Next, we analyzed moonlighting proteins in terms of protein-protein interaction, gene expression, phylogenetic profile, and genetic interaction networks. We found that moonlighting proteins physically interact with a higher number of distinct functional classes of proteins than non-moonlighting ones and also found that most of the physically interacting partners of moonlighting proteins share the latter's primary functions. Interestingly, we also found that moonlighting proteins tend to interact with other moonlighting proteins. In terms of gene expression and phylogenetically related proteins, a weak trend was observed that moonlighting proteins interact with more functionally diverse proteins. Structural characteristics of moonlighting proteins, i.e. intrinsic disordered regions and ligand binding sites were also investigated.

CONCLUSION

Additional functions of moonlighting proteins are difficult to identify by experiments and these proteins also pose a significant challenge for computational function annotation. Our method enables identification of novel moonlighting proteins from current functional annotations in public databases. Moreover, we showed that potential moonlighting proteins without sufficient functional annotations can be identified by analyzing available omics-scale data. Our findings open up new possibilities for investigating the multi-functional nature of proteins at the systems level and for exploring the complex functional interplay of proteins in a cell.

REVIEWERS

This article was reviewed by Michael Galperin, Eugine Koonin, and Nick Grishin.

Computational characterization of moonlighting proteins

Moonlighting proteins perform multiple independent cellular functions within one polypeptide chain. Moonlighting proteins switch functions depending on various factors including the cell-type in which they are expressed, cellular location, oligomerization status and the binding of different ligands at different sites. Although an increasing number of moonlighting proteins have been experimentally identified in recent years, the quantity of known moonlighting proteins is insufficient to elucidate their overall landscape. Moreover, most moonlighting proteins have been identified as a serendipitous discovery. Hence, characterization of moonlighting proteins using bioinformatics approaches can have a significant impact on the overall understanding of protein function. In this work, we provide a short review of existing computational approaches for illuminating the functional diversity of moonlighting proteins.

An introduction to protein moonlighting

Moonlighting proteins comprise a class of multifunctional proteins in which a single polypeptide chain performs multiple physiologically relevant biochemical or biophysical functions. Almost 300 proteins have been found to moonlight. The known examples of moonlighting proteins include diverse types of proteins, including receptors, enzymes, transcription factors, adhesins and scaffolds, and different combinations of functions are observed. Moonlighting proteins are expressed throughout the evolutionary tree and function in many different biochemical pathways. Some moonlighting proteins can perform both functions simultaneously, but for others, the protein's function changes in response to changes in the environment. The diverse examples of moonlighting proteins already identified, and the potential benefits moonlighting proteins might provide to the organism, such as through coordinating cellular activities, suggest that many more moonlighting proteins are likely to be found. Continuing studies of the structures and functions of moonlighting proteins will aid in predicting the functions of proteins identified through genome sequencing projects, in interpreting results from proteomics experiments, in understanding how different biochemical pathways interact in systems biology, in annotating protein sequence and structure databases, in studies of protein evolution and in the design of proteins with novel functions.

MoonProt: a database for proteins that are known to moonlight

Moonlighting proteins comprise a class of multifunctional proteins in which a single polypeptide chain performs multiple biochemical functions that are not due to gene fusions, multiple RNA splice variants or pleiotropic effects. The known moonlighting proteins perform a variety of diverse functions in many different cell types and species, and information about their structures and functions is scattered in many publications. We have constructed the manually curated, searchable, internet-based MoonProt Database (http://www.moonlightingproteins.org) with information about the over 200 proteins that have been experimentally verified to be moonlighting proteins. The availability of this organized information provides a more complete picture of what is currently known about moonlighting proteins. The database will also aid researchers in other fields, including determining the functions of genes identified in genome sequencing projects, interpreting data from proteomics projects and annotating protein sequence and structural databases. In addition, information about the structures and functions of moonlighting proteins can be helpful in understanding how novel protein functional sites evolved on an ancient protein scaffold, which can also help in the design of proteins with novel functions.

Multifunctional enzymes in archaea: promiscuity and moonlight

Enzymes from many archaea colonizing extreme environments are of great interest because of their potential for various biotechnological processes and scientific value of evolution. Many enzymes from archaea have been reported to catalyze promiscuous reactions or moonlight in different functions. Here, we summarize known archaeal enzymes of both groups that include different kinds of proteins. Knowledge of their biochemical properties and three-dimensional structures has proved invaluable in understanding mechanism, application, and evolutionary implications of this manifestation. In addition, the review also summarizes the methods to unravel the extra function which almost was discovered serendipitously. The study of these amazing enzymes will provide clues to optimize protein engineering applications and how enzymes might have evolved on Earth.

On the possible use of exogenous histones in cell technology

The prospect of developing transport systems using histones for site-specific delivery of therapeutic agents that have poor penetration characteristics through cellular membranes and tissue barriers has been investigated. Histones immobilized on microspheres can also be used to modify surfaces intended for cell cultivation, facilitating adhesion, proliferation and network formation by interactions of cells through contacts with several microspheres. They can be applied to three-dimensional pore matrices that are designed for producing tissue-like structures in vitro.

A leukotriene A4 hydrolase-related aminopeptidase from yeast undergoes induced fit upon inhibitor binding

Vertebrate leukotriene A(4) hydrolases are bifunctional zinc metalloenzymes with an epoxide hydrolase and an aminopeptidase activity. In contrast, highly homologous enzymes from lower organisms only have the aminopeptidase activity. From sequence comparisons, it is not clear why this difference occurs. In order to obtain more information on the evolutionary relationship between these enzymes and their activities, the structure of a closely related leucine aminopeptidase from Saccharomyces cerevisiae that only shows a very low epoxide hydrolase activity was determined. To investigate the molecular architecture of the active site, the structures of both the native protein and the protein in complex with the aminopeptidase inhibitor bestatin were solved. These structures show a more spacious active site, and the protected cavity in which the labile substrate leukotriene A(4) is bound in the human enzyme is partially obstructed and in other parts is more solvent accessible. Furthermore, the enzyme undergoes induced fit upon binding of the inhibitor bestatin, leading to a movement of the C-terminal domain. The main triggers for the domain movement are a conformational change of Tyr312 and a subtle change in backbone conformation of the PYGAMEN fingerprint region for peptide substrate recognition. This leads to a change in the hydrogen-bonding network pulling the C-terminal domain into a different position. Inasmuch as bestatin is a structural analogue of a leucyl dipeptide and may be regarded as a transition state mimic, our results imply that the enzyme undergoes induced fit during substrate binding and turnover.

Moonlighting proteins--an update

A growing number of diverse proteins are being identified that moonlight. Moonlighting proteins comprise an interesting subset of multifunctional proteins in which the two functions are found in a single polypeptide chain. They do not include proteins that are multifunctional due to gene fusions, families of homologous proteins, splice variants, or promiscuous enzyme activities. This review summarizes recent discoveries that add to the list of known moonlighting proteins. They include several different kinds of proteins and combinations of functions. In one case, a novel DNA binding function was found for a biosynthetic enzyme through a proteomics microarray project. The review also summarizes recent X-ray crystal structures that provide clues to the molecular mechanisms of one or both functions, and in some cases how a protein can switch between functions. In addition, the possibility that many proteins with intrinsically unstructured regions might also moonlight is discussed.

Single-gene disorders: what role could moonlighting enzymes play?

Single-gene disorders with "simple" Mendelian inheritance do not always imply that there will be an easy prediction of the phenotype from the genotype, which has been shown for a number of metabolic disorders. We propose that moonlighting enzymes (i.e., metabolic enzymes with additional functional activities) could contribute to the complexity of such disorders. The lack of knowledge about the additional functional activities of proteins could result in a lack of correlation between genotype and phenotype. In this review, we highlight some notable and recent examples of moonlighting enzymes and their possible contributions to human disease. Because knowledge and cataloging of the moonlighting activities of proteins are essential for the study of cellular function and human physiology, we also review recently reported and recommended methods for the discovery of moonlighting activities.

Bacterial multidrug resistance unrelated to multidrug exporters: cell biology insight

Multidrug resistance (MDR) revealed in malignant cell lines was firstly attributed to the activity of multidrug exporters pumping drugs out of the cell. However, mutagenised Escherichia coli develop extraordinary numerous mutants resistant to target inhibitor and we have shown that with mutations mapped around the entire genome most of the mutants were multiple-resistant. In case of one such mutant studied MDR was shown as a sum of individual resistances due to mutations resulted in target and ligand sequestration and induced simultaneously in tightly linked, cassette-like genes. An explanation of local mutagenesis efficiency and the nature of sequestration process is proposed. A cassette-like organization of genes responsible for chemoresistance emergence could promote the local intensity of mutagenesis by a cassette facing the intracellular space and flux and contacting unlike other genes mutagen the first. Target and ligand sequestration could result from clogging the intracellular flux due to cytoplasm geometry alteration attributable to disorder-order transition in natively unfolded proteins affected with mutation.