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Constance J. Jeffery - One of the best experts on this subject based on the ideXlab platform.

  • Moonlighting Proteins in the Fuzzy Logic of Cellular Metabolism.
    Molecules (Basel Switzerland), 2020
    Co-Authors: Haipeng Liu, Constance J. Jeffery
    Abstract:

    The numerous interconnected biochemical pathways that make up the metabolism of a living cell comprise a fuzzy logic system because of its high level of complexity and our inability to fully understand, predict, and model the many activities, how they interact, and their regulation. Each cell contains thousands of Proteins with changing levels of expression, levels of activity, and patterns of interactions. Adding more layers of complexity is the number of Proteins that have multiple functions. Moonlighting Proteins include a wide variety of Proteins where two or more functions are performed by one polypeptide chain. In this article, we discuss examples of Proteins with variable functions that contribute to the fuzziness of cellular metabolism.

  • Enzymes, pseudoenzymes, and Moonlighting Proteins: diversity of function in protein superfamilies
    The FEBS journal, 2020
    Co-Authors: Constance J. Jeffery
    Abstract:

    As more genome sequences are elucidated, there is an increasing need for information about the functions of the millions of Proteins they encode. The function of a newly sequenced protein is often estimated by sequence alignment with the sequences of Proteins with known functions. However, protein superfamilies can contain members that share significant amino acid sequence and structural homology yet catalyze different reactions or act on different substrates. Some homologous Proteins differ by having a second or even third function, called Moonlighting Proteins. More recently, it was found that most protein superfamilies also include pseudoenzymes, a protein, or a domain within a protein, that has a three-dimensional fold that resembles a conventional catalytically active enzyme, but has no catalytic activity. In this review, we discuss several examples of protein families that contain enzymes, pseudoenzymes, and Moonlighting Proteins. It is becoming clear that pseudoenzymes and Moonlighting Proteins are widespread in the evolutionary tree, and in many protein families, and they are often very similar in sequence and structure to their monofunctional and catalytically active counterparts. A greater understanding is needed to clarify when similarities and differences in amino acid sequences and structures correspond to similarities and differences in biochemical functions and cellular roles. This information can help improve programs that identify protein functions from sequence or structure and assist in more accurate annotation of sequence and structural databases, as well as in our understanding of the broad diversity of protein functions.

  • Multitalented actors inside and outside the cell: recent discoveries add to the number of Moonlighting Proteins.
    Biochemical Society transactions, 2019
    Co-Authors: Constance J. Jeffery
    Abstract:

    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.

  • An enzyme in the test tube, and a transcription factor in the cell: Moonlighting Proteins and cellular factors that affect their behavior.
    Protein science : a publication of the Protein Society, 2019
    Co-Authors: Constance J. Jeffery
    Abstract:

    In the cell, expression levels, allosteric modulators, post-translational modifications, sequestration, and other factors can affect the level of protein function. For Moonlighting Proteins, cellular factors like these can also affect the kind of protein function. This minireview discusses examples of Moonlighting Proteins that illustrate how a single protein can have different functions in different cell types, in different intracellular locations, or under varying cellular conditions. This variability in the kind of protein activity, added to the variability in the amount of protein activity, contributes to the difficulty in predicting the behavior of Proteins in the cell.

  • Intracellular/surface Moonlighting Proteins that aid in the attachment of gut microbiota to the host.
    AIMS microbiology, 2019
    Co-Authors: Constance J. Jeffery
    Abstract:

    The gut microbiota use Proteins on their surface to form and maintain interactions with host cells and tissues. In recent years, many of these cell surface Proteins have been found to be identical to intracellular enzymes and chaperones. When displayed on the cell surface these Moonlighting Proteins help the microbe attach to the host by interacting with receptors on the surface of host cells, components of the extracellular matrix, and mucin in the mucosal lining of the digestive tract. Binding of these Proteins to the soluble host protein plasminogen promotes the conversion of plasminogen to an active protease, plasmin, which activates other host Proteins that aid in infection and virulence. In this mini-review, we discuss intracellular/surface Moonlighting Proteins of pathogenic and probiotic bacteria and eukaryotic gut microbiota.

Christine Brun - One of the best experts on this subject based on the ideXlab platform.

  • Understanding protein multifunctionality: from short linear motifs to cellular functions
    Cellular and Molecular Life Sciences, 2019
    Co-Authors: Andreas Zanzoni, Diogo M Ribeiro, Christine Brun
    Abstract:

    Moonlighting Proteins perform multiple unrelated functions without any change in polypeptide sequence. They can coordinate cellular activities, serving as switches between pathways and helping to respond to changes in the cellular environment. Therefore, regulation of the multiple protein activities, in space and time, is likely to be important for the homeostasis of biological systems. Some Moonlighting Proteins may perform their multiple functions simultaneously while others alternate between functions due to certain triggers. The switch of the Moonlighting protein’s functions can be regulated by several distinct factors, including the binding of other molecules such as Proteins. We here review the approaches used to identify Moonlighting Proteins and existing repositories. We particularly emphasise the role played by short linear motifs and PTMs as regulatory switches of Moonlighting functions.

  • MoonDB 2.0: an updated database of extreme multifunctional and Moonlighting Proteins.
    Nucleic acids research, 2018
    Co-Authors: Diogo M Ribeiro, Galadriel Briere, Benoit Bely, Lionel Spinelli, Christine Brun
    Abstract:

    MoonDB 2.0 (http://moondb.hb.univ-amu.fr/) is a database of predicted and manually curated extreme multifunctional (EMF) and Moonlighting Proteins, i.e. Proteins that perform multiple unrelated functions. We have previously shown that such Proteins can be predicted through the analysis of their molecular interaction subnetworks, their functional annotations and their association to distinct groups of Proteins that are involved in unrelated functions. In MoonDB 2.0, we updated the set of human EMF Proteins (238 Proteins), using the latest functional annotations and protein-protein interaction networks. Furthermore, for the first time, we applied our method to four additional model organisms-mouse, fly, worm and yeast-and identified 54 novel EMF Proteins in these species. In addition to novel predictions , this update contains 63 human and yeast Proteins that were manually curated from literature, including descriptions of Moonlighting functions and associated references. Importantly, MoonDB's interface was fully redesigned and improved, and its entries are now cross-referenced in the UniProt Knowl-edgebase (UniProtKB). MoonDB will be updated once a year with the novel EMF candidates calculated from the latest available protein interactions and functional annotations.

  • Relationships between predicted Moonlighting Proteins, human diseases, and comorbidities from a network perspective
    Frontiers in Physiology, 2015
    Co-Authors: Andreas Zanzoni, Charles E. Chapple, Christine Brun
    Abstract:

    Moonlighting Proteins are a subset of multifunctional Proteins characterized by their multiple, independent, and unrelated biological functions. We recently set up a large-scale identification of Moonlighting Proteins using a protein-protein interaction (PPI) network approach. We established that 3% of the current human interactome is composed of predicted Moonlighting Proteins. We found that disease-related genes are over-represented among those candidates. Here, by comparing Moonlighting candidates to non-candidates as groups, we further show that (7 they are significantly involved in more than one disease, (ii) they contribute to complex rather than monogenic diseases, (iii) the diseases in which they are involved are phenotypically different according to their annotations, finally, (iv) they are enriched for diseases pairs showing statistically significant comorbidity patterns based on Medicare records. Altogether, our results suggest that some observed comorbidities between phenotypically different diseases could be due to a shared protein involved in unrelated biological processes.

  • Extreme multifunctional Proteins identified from a human protein interaction network.
    Nature communications, 2015
    Co-Authors: Charles E. Chapple, Lionel Spinelli, Benoît Robisson, Celine Guien, Emmanuelle Becker, Christine Brun
    Abstract:

    Moonlighting Proteins are a subclass of multifunctional Proteins whose functions are unrelated. Although they may play important roles in cells, there has been no large-scale method to identify them, nor any effort to characterize them as a group. Here, we propose the first method for the identification of ‘extreme multifunctional' Proteins from an interactome as a first step to characterize Moonlighting Proteins. By combining network topological information with protein annotations, we identify 430 extreme multifunctional Proteins (3% of the human interactome). We show that the candidates form a distinct sub-group of Proteins, characterized by specific features, which form a signature of extreme multifunctionality. Overall, extreme multifunctional Proteins are enriched in linear motifs and less intrinsically disordered than network hubs. We also provide MoonDB, a database containing information on all the candidates identified in the analysis and a set of manually curated human Moonlighting Proteins.

  • PrOnto database : GO term functional dissimilarity inferred from biological data.
    Frontiers in Genetics, 2015
    Co-Authors: Charles E. Chapple, Carl Herrmann, Christine Brun
    Abstract:

    Moonlighting Proteins are defined by their involvement in multiple, unrelated functions. The computational prediction of such Proteins requires a formal method of assessing the similarity of cellular processes, for example, by identifying dissimilar Gene Ontology terms. While many measures of Gene Ontology term similarity exist, most depend on abstract mathematical analyses of the structure of the GO tree and do not necessarily represent the underlying biology. Here, we propose two metrics of GO term functional dissimilarity derived from biological information, one based on the protein annotations and the other on the interactions between Proteins. They have been collected in the PrOnto database, a novel tool which can be of particular use for the identification of Moonlighting Proteins. The database can be queried via an web-based interface which is freely available at http://tagc.univ-mrs.fr/pronto.

Daisuke Kihara - One of the best experts on this subject based on the ideXlab platform.

  • Identification of Moonlighting Proteins in Genomes Using Text Mining Techniques
    Proteomics, 2018
    Co-Authors: Aashish Jain, Hareesh Gali, Daisuke Kihara
    Abstract:

    Moonlighting Proteins is an emerging concept for considering protein functions, which indicate Proteins with two or more independent and distinct functions. An increasing number of Moonlighting Proteins have been reported in the past years; however, a systematic study of the topic has been hindered because the secondary functions of Proteins are usually found serendipitously by experiments. Toward systematic identification and study of Moonlighting Proteins, computational methods for identifying Moonlighting Proteins from several different information sources, database entries, literature, and large-scale omics data have been developed. In this study, an overview for finding Moonlighting Proteins is discussed. Then, the literature-mining method, DextMP, is applied to find new Moonlighting Proteins in three genomes, Arabidopsis thaliana, Caenorhabditis elegans, and Drosophila melanogaster. Potential Moonlighting Proteins identified by DextMP are further examined by a two-step manual literature checking procedure, which finally yielded 13 new Moonlighting Proteins. Identified Moonlighting Proteins are categorized into two classes based on the clarity of the distinctness of two functions of the Proteins. A few cases of the identified Moonlighting Proteins are described in detail. Further direction for improving the DextMP algorithm is also discussed.

  • DextMP: deep dive into text for predicting Moonlighting Proteins.
    Bioinformatics (Oxford England), 2017
    Co-Authors: Ishita K. Khan, Mansurul Bhuiyan, Daisuke Kihara
    Abstract:

    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 . Contact dkihara@purdue.edu.

  • MPFit: Computational Tool for Predicting Moonlighting Proteins.
    Methods in molecular biology (Clifton N.J.), 2017
    Co-Authors: Ishita K. Khan, Joshua Mcgraw, Daisuke Kihara
    Abstract:

    An increasing number of Proteins have been found which are capable of performing two or more distinct functions. These Proteins, known as Moonlighting Proteins, have drawn much attention recently as they may play critical roles in disease pathways and development. However, because Moonlighting Proteins are often found serendipitously, our understanding of Moonlighting Proteins is still quite limited. In order to lay the foundation for systematic Moonlighting Proteins studies, we developed MPFit, a software package for predicting Moonlighting Proteins from their omics features including protein-protein and gene interaction networks. Here, we describe and demonstrate the algorithm of MPFit, the idea behind it, and provide instruction for using the software.

  • Genome-scale prediction of Moonlighting Proteins using diverse protein association information
    Bioinformatics (Oxford England), 2016
    Co-Authors: Ishita K. Khan, Daisuke Kihara
    Abstract:

    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.

  • Genome-scale identification and characterization of Moonlighting Proteins
    Biology direct, 2014
    Co-Authors: Ishita K. Khan, Yuqian Chen, Tiange Dong, Xioawei Hong, Rikiya Takeuchi, Hirotada Mori, Daisuke Kihara
    Abstract:

    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’ sp rimary 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.

Jana Auer - One of the best experts on this subject based on the ideXlab platform.

  • Moonlighting Proteins in sperm egg interactions
    Biochemical Society Transactions, 2014
    Co-Authors: François M. Petit, Catherine Serres, Jana Auer
    Abstract:

    Sperm–egg interaction is a highly species-specific step during the fertilization process. The first steps consist of recognition between Proteins on the sperm head and zona pellucida (ZP) glycoProteins, the acellular coat that protects the oocyte. We aimed to determine which sperm head Proteins interact with ZP2, ZP3 and ZP4 in humans. Two approaches were combined to identify these Proteins: immunoblotting human spermatozoa targeted by antisperm antibodies (ASAs) from infertile men and far-Western blotting of human sperm Proteins overlaid by each of the human recombinant ZP (hrZP) Proteins. We used a proteomic approach with 2D electrophoretic separation of sperm protein revealed using either ASAs eluted from infertile patients or recombinant human ZP glycoProteins expressed in Chinese-hamster ovary (CHO) cells. Only spots highlighted by both methods were analysed by MALDI–MS/MS for identification. We identified Proteins already described in human spermatozoa, but implicated in different metabolic pathways such as glycolytic enzymes [phosphokinase type 3 (PK3), enolase 1 (ENO1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), aldolase A (ALDOA) and triose phosphate isomerase (TPI)], detoxification enzymes [GST Mu (GSTM) and phospholipid hydroperoxide glutathione peroxidase (PHGPx) 4], ion channels [voltage-dependent anion channel 2 (VDAC2)] or structural Proteins (outer dense fibre 2). Several Proteins were localized on the sperm head by indirect immunofluorescence, and their interaction with ZP Proteins was confirmed by co-precipitation experiments. These results confirm the complexity of the sperm–ZP recognition process in humans with the implication of different Proteins interacting with the main three ZP glycoProteins. The multiple roles of these Proteins suggest that they are multifaceted or Moonlighting Proteins.

  • Moonlighting Proteins in sperm–egg interactions
    Biochemical Society transactions, 2014
    Co-Authors: François M. Petit, Catherine Serres, Jana Auer
    Abstract:

    Sperm–egg interaction is a highly species-specific step during the fertilization process. The first steps consist of recognition between Proteins on the sperm head and zona pellucida (ZP) glycoProteins, the acellular coat that protects the oocyte. We aimed to determine which sperm head Proteins interact with ZP2, ZP3 and ZP4 in humans. Two approaches were combined to identify these Proteins: immunoblotting human spermatozoa targeted by antisperm antibodies (ASAs) from infertile men and far-Western blotting of human sperm Proteins overlaid by each of the human recombinant ZP (hrZP) Proteins. We used a proteomic approach with 2D electrophoretic separation of sperm protein revealed using either ASAs eluted from infertile patients or recombinant human ZP glycoProteins expressed in Chinese-hamster ovary (CHO) cells. Only spots highlighted by both methods were analysed by MALDI–MS/MS for identification. We identified Proteins already described in human spermatozoa, but implicated in different metabolic pathways such as glycolytic enzymes [phosphokinase type 3 (PK3), enolase 1 (ENO1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), aldolase A (ALDOA) and triose phosphate isomerase (TPI)], detoxification enzymes [GST Mu (GSTM) and phospholipid hydroperoxide glutathione peroxidase (PHGPx) 4], ion channels [voltage-dependent anion channel 2 (VDAC2)] or structural Proteins (outer dense fibre 2). Several Proteins were localized on the sperm head by indirect immunofluorescence, and their interaction with ZP Proteins was confirmed by co-precipitation experiments. These results confirm the complexity of the sperm–ZP recognition process in humans with the implication of different Proteins interacting with the main three ZP glycoProteins. The multiple roles of these Proteins suggest that they are multifaceted or Moonlighting Proteins.

Wangfei Wang - One of the best experts on this subject based on the ideXlab platform.

  • MoonProt 2.0: An Expansion and Update of the Moonlighting Proteins Database
    Nucleic acids research, 2017
    Co-Authors: Chang Chen, Wangfei Wang, Shadi Zabad, Haipeng Liu, Constance J. Jeffery
    Abstract:

    MoonProt 2.0 (http://MoonlightingProteins.org) is an updated, comprehensive and open-access database storing expert-curated annotations for Moonlighting Proteins. Moonlighting Proteins contain two or more physiologically relevant distinct functions performed by a single polypeptide chain. Here, we describe developments in the MoonProt website and database since our previous report in the Database Issue of Nucleic Acids Research. For this V 2.0 release, we expanded the number of Proteins annotated to 370 and modified several dozen protein annotations with additional or updated information, including more links to protein structures in the Protein Data Bank, compared with the previous release. The new entries include more examples from humans and several model organisms, more Proteins involved in disease, and Proteins with different combinations of functions. The updated web interface includes a search function using BLAST to enable users to search the database for Proteins that share amino acid sequence similarity with a protein of interest. The updated website also includes additional background information about Moonlighting Proteins and an expanded list of links to published articles about Moonlighting Proteins.

  • An analysis of surface proteomics results reveals novel candidates for intracellular/surface Moonlighting Proteins in bacteria.
    Molecular bioSystems, 2016
    Co-Authors: Wangfei Wang, Constance J. Jeffery
    Abstract:

    Proteins expressed on the bacterial cell surface play important roles in infection and virulence and can be targets for vaccine development or used as biomarkers. Surprisingly, an increasing number of surface Proteins are being found to be identical to intracellular enzymes and chaperones, and a few dozen intracellular/surface Moonlighting Proteins have been found that have different functions inside the cell and on the cell surface. The results of twenty-two published bacterial surface proteomics studies were analyzed using bioinformatics tools to consider how many additional intracellular Proteins are also found on the cell surface. More than 1000 out of the 3619 Proteins observed on the cell surface lack the transmembrane alpha-helices or transmembrane beta-barrels found in integral membrane Proteins and also lack the signal peptides found in Proteins secreted through the Sec pathway. Many of the Proteins found on the cell surface are intracellular chaperones or enzymes involved in central metabolic pathways, including some that have previously been shown to have a Moonlighting function on the cell surface in at least one species, such as Hsp60/GroEL, DnaK, glyceraldehyde 3-phosphate dehydrogenase, enolase, and fructose 1,6-bisphosphate aldolase. The results of the proteomics studies suggest they could also be Moonlighting on the surface of many other species. Hundreds of other intracellular Proteins are also found on the cell surface, although a second function on the surface has not yet been demonstrated, for example, glutamine synthetase, gamma-glutamyl phosphate reductase, and cysteine desulfurase. The presence of intracellular Proteins on the cell surface is more common than previously expected and suggests that many additional Proteins might be candidates for being intracellular/surface Moonlighting Proteins.

  • an analysis of surface proteomics results reveals novel candidates for intracellular surface Moonlighting Proteins in bacteria
    Molecular BioSystems, 2016
    Co-Authors: Wangfei Wang, Constance J. Jeffery
    Abstract:

    Proteins expressed on the bacterial cell surface play important roles in infection and virulence and can be targets for vaccine development or used as biomarkers. Surprisingly, an increasing number of surface Proteins are being found to be identical to intracellular enzymes and chaperones, and a few dozen intracellular/surface Moonlighting Proteins have been found that have different functions inside the cell and on the cell surface. The results of twenty-two published bacterial surface proteomics studies were analyzed using bioinformatics tools to consider how many additional intracellular Proteins are also found on the cell surface. More than 1000 out of the 3619 Proteins observed on the cell surface lack the transmembrane alpha-helices or transmembrane beta-barrels found in integral membrane Proteins and also lack the signal peptides found in Proteins secreted through the Sec pathway. Many of the Proteins found on the cell surface are intracellular chaperones or enzymes involved in central metabolic pathways, including some that have previously been shown to have a Moonlighting function on the cell surface in at least one species, such as Hsp60/GroEL, DnaK, glyceraldehyde 3-phosphate dehydrogenase, enolase, and fructose 1,6-bisphosphate aldolase. The results of the proteomics studies suggest they could also be Moonlighting on the surface of many other species. Hundreds of other intracellular Proteins are also found on the cell surface, although a second function on the surface has not yet been demonstrated, for example, glutamine synthetase, gamma-glutamyl phosphate reductase, and cysteine desulfurase. The presence of intracellular Proteins on the cell surface is more common than previously expected and suggests that many additional Proteins might be candidates for being intracellular/surface Moonlighting Proteins.

  • intracellular surface Moonlighting Proteins
    Biophysical Journal, 2016
    Co-Authors: Constance J. Jeffery, Wangfei Wang
    Abstract:

    Cell surface Proteins of bacterial pathogens play key roles in invasion and virulence. Colonization of the host requires adhesion of the bacterium to host tissues, so some surface Proteins bind to Proteins in the extracellular matrix or directly to host cells. Others bind to plasminogen, which, when converted to the active protease plasmin, aids in degradation and invasion of host tissues. Surprisingly, a growing number of the cell surface Proteins that bind to host cells, extracellular matrix, or plasminogen were previously identified as intracellular enzymes or chaperones, and we refer to them as intracellular/surface Moonlighting Proteins. Moonlighting Proteins are a subset of multifunctional Proteins in which multiple biochemical or biophysical functions in one polypeptide chain are not due to gene fusions, families of homologous Proteins, promiscuous enzyme activity or pleiotropic effects.It is not known how most intracellular/cell surface Moonlighting Proteins are secreted. These Proteins do not possess signal peptides for secretion by the canonical Sec pathway. Their secretion may involve a novel version of another known secretion pathway or it may involve an as yet unknown secretion pathway. In addition, they do not contain sequence motifs known to be involved in attachment to the cell surface. This could also involve a new version of a known mechanism or it may involve an as yet unknown mechanism. With the increasing problem of antibiotic resistance, new targets for inhibiting bacterial infection and virulence are needed. Understanding how intracellular/cell surface Moonlighting Proteins are targeted to the surface of a pathogen might lead to a method to decrease the ability of bacteria to bind to and degrade host tissues and could provide new targets for developing therapeutics to treat infections.

  • Intracellular/Surface Moonlighting Proteins
    Biophysical Journal, 2016
    Co-Authors: Constance J. Jeffery, Wangfei Wang
    Abstract:

    Cell surface Proteins of bacterial pathogens play key roles in invasion and virulence. Colonization of the host requires adhesion of the bacterium to host tissues, so some surface Proteins bind to Proteins in the extracellular matrix or directly to host cells. Others bind to plasminogen, which, when converted to the active protease plasmin, aids in degradation and invasion of host tissues. Surprisingly, a growing number of the cell surface Proteins that bind to host cells, extracellular matrix, or plasminogen were previously identified as intracellular enzymes or chaperones, and we refer to them as intracellular/surface Moonlighting Proteins. Moonlighting Proteins are a subset of multifunctional Proteins in which multiple biochemical or biophysical functions in one polypeptide chain are not due to gene fusions, families of homologous Proteins, promiscuous enzyme activity or pleiotropic effects.It is not known how most intracellular/cell surface Moonlighting Proteins are secreted. These Proteins do not possess signal peptides for secretion by the canonical Sec pathway. Their secretion may involve a novel version of another known secretion pathway or it may involve an as yet unknown secretion pathway. In addition, they do not contain sequence motifs known to be involved in attachment to the cell surface. This could also involve a new version of a known mechanism or it may involve an as yet unknown mechanism. With the increasing problem of antibiotic resistance, new targets for inhibiting bacterial infection and virulence are needed. Understanding how intracellular/cell surface Moonlighting Proteins are targeted to the surface of a pathogen might lead to a method to decrease the ability of bacteria to bind to and degrade host tissues and could provide new targets for developing therapeutics to treat infections.