Predicting Protein Function via Semantic Integration of Multiple Networks

Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

Incorporating modeling and simulations in undergraduate biophysical chemistry course to promote understanding of structure-dynamics-function relationships in proteins

A project-based biophysical chemistry laboratory course, which is offered to the biochemistry and molecular biology majors in their senior year, is described. In this course, the classroom study of the structure-function of biomolecules is integrated with the discovery-guided laboratory study of these molecules using computer modeling and simulations. In particular, modern computational tools are employed to elucidate the relationship between structure, dynamics, and function in proteins. Computer-based laboratory protocols that we introduced in three modules allow students to visualize the secondary, super-secondary, and tertiary structures of proteins, analyze non-covalent interactions in protein-ligand complexes, develop three-dimensional structural models (homology model) for new protein sequences and evaluate their structural qualities, and study proteins' intrinsic dynamics to understand their functions. In the fourth module, students are assigned to an authentic research problem, where they apply their laboratory skills (acquired in modules 1-3) to answer conceptual biophysical questions. Through this process, students gain in-depth understanding of protein dynamics-the missing link between structure and function. Additionally, the requirement of term papers sharpens students' writing and communication skills. Finally, these projects result in new findings that are communicated in peer-reviewed journals.

Gene Regulatory Network Inference of Immunoresponsive Gene 1 (IRG1) Identifies Interferon Regulatory Factor 1 (IRF1) as Its Transcriptional Regulator in Mammalian Macrophages

Immunoresponsive gene 1 (IRG1) is one of the highest induced genes in macrophages under pro-inflammatory conditions. Its function has been recently described: it codes for immune-responsive gene 1 protein/cis-aconitic acid decarboxylase (IRG1/CAD), an enzyme catalysing the production of itaconic acid from cis-aconitic acid, a tricarboxylic acid (TCA) cycle intermediate. Itaconic acid possesses specific antimicrobial properties inhibiting isocitrate lyase, the first enzyme of the glyoxylate shunt, an anaplerotic pathway that bypasses the TCA cycle and enables bacteria to survive on limited carbon conditions. To elucidate the mechanisms underlying itaconic acid production through IRG1 induction in macrophages, we examined the transcriptional regulation of IRG1. To this end, we studied IRG1 expression in human immune cells under different inflammatory stimuli, such as TNFα and IFNγ, in addition to lipopolysaccharides. Under these conditions, as previously shown in mouse macrophages, IRG1/CAD accumulates in mitochondria. Furthermore, using literature information and transcription factor prediction models, we re-constructed raw gene regulatory networks (GRNs) for IRG1 in mouse and human macrophages. We further implemented a contextualization algorithm that relies on genome-wide gene expression data to infer putative cell type-specific gene regulatory interactions in mouse and human macrophages, which allowed us to predict potential transcriptional regulators of IRG1. Among the computationally identified regulators, siRNA-mediated gene silencing of interferon regulatory factor 1 (IRF1) in macrophages significantly decreased the expression of IRG1/CAD at the gene and protein level, which correlated with a reduced production of itaconic acid. Using a synergistic approach of both computational and experimental methods, we here shed more light on the transcriptional machinery of IRG1 expression and could pave the way to therapeutic approaches targeting itaconic acid levels.

[Intracellular and extracellular functions of phosphorus compound in the body]

Phosphorus, as a phosphate is a component of bone, cellular membrane, and also high-energy phosphate compounds, and nucleic acids. Also phosphate acts as a buffer to maintain the pH and is concerned with functional regulation of several proteins and intracellular signaling through the phosphorylation/dephosphorylation. Thus phosphorus plays a variety of important roles intracellular and extracellular component. A disorder of phosphate homeostasis results bone disorder and general metabolic dysfunction of all body tissues and organs.

Predicting the functions of a protein from its ability to associate with other molecules

BACKGROUND

All proteins associate with other molecules. These associated molecules are highly predictive of the potential functions of proteins. The association of a protein and a molecule can be determined from their co-occurrences in biomedical abstracts. Extensive semantically related co-occurrences of a protein's name and a molecule's name in the sentences of biomedical abstracts can be considered as indicative of the association between the protein and the molecule. Dependency parsers extract textual relations from a text by determining the grammatical relations between words in a sentence. They can be used for determining the textual relations between proteins and molecules. Despite their success, they may extract textual relations with low precision. This is because they do not consider the semantic relationships between terms in a sentence (i.e., they consider only the structural relationships between the terms). Moreover, they may not be well suited for complex sentences and for long-distance textual relations.

RESULTS

We introduce an information extraction system called PPFBM that predicts the functions of unannotated proteins from the molecules that associate with these proteins. PPFBM represents each protein by the other molecules that associate with it in the abstracts referenced in the protein's entries in reliable biological databases. It automatically extracts each co-occurrence of a protein-molecule pair that represents semantic relationship between the pair. Towards this, we present novel semantic rules that identify the semantic relationship between each co-occurrence of a protein-molecule pair using the syntactic structures of sentences and linguistics theories. PPFBM determines the functions of an un-annotated protein p as follows. First, it determines the set S r of annotated proteins that is semantically similar to p by matching the molecules representing p and the annotated proteins. Then, it assigns p the functional category FC if the significance of the frequency of occurrences of S r in abstracts associated with proteins annotated with FC is statistically significantly different than the significance of the frequency of occurrences of S r in abstracts associated with proteins annotated with all other functional categories. We evaluated the quality of PPFBM by comparing it experimentally with two other systems. Results showed marked improvement.

CONCLUSIONS

The experimental results demonstrated that PPFBM outperforms other systems that predict protein function from the textual information found within biomedical abstracts. This is because these system do not consider the semantic relationships between terms in a sentence (i.e., they consider only the structural relationships between the terms). PPFBM's performance over these system increases steadily as the number of training protein increases. That is, PPFBM's prediction performance becomes more accurate constantly, as the size of training proteins gets larger. This is because every time a new set of test proteins is added to the current set of training proteins. A demo of PPFBM that annotates each input Yeast protein (SGD (Saccharomyces Genome Database). Available at: http://www.yeastgenome.org/download-data/curation) with the functions of Gene Ontology terms is available at: (see Appendix for more details about the demo) http://ecesrvr.kustar.ac.ae:8080/PPFBM/.

Predicting the Subcellular Localization of Proteins with Multiple Sites Based on Multiple Features Fusion

Protein sub-cellular localization prediction has attracted much attention in recent years because of its importance for protein function studying and targeted drug discovery, and that makes it to be an important research field in bioinformatics. Traditional experimental methods which ascertain the protein sub-cellular locations are costly and time consuming. In the last two decades, machine learning methods got increasing development, and a large number of machine learning based protein sub-cellular location predictors have been developed. However, most of such predictors can only predict proteins in only one subcellular location. With the development of biology techniques, more and more proteins which have two or even more sub-cellular locations have been found. It is much more significant to study such proteins because they have extremely useful implication for both basic biology and bioinformatics research. In order to improve the accuracy of prediction, much more feature information which can represent the protein sequence should be extracted. In this paper, several feature extraction methods were fused together to extract the feature information, then the multi-label k nearest neighbors (ML-KNN) algorithm was used to predict protein sub-cellular locations. The best overall accuracies we got for dataset s1 in constructing Gpos-mploc is 66.7304 and 59.9206 percent for dataset s2 in constructing Virus-mPLoc.

Silencing of Paternally Expressed Gene 10 Inhibits Trophoblast Proliferation and Invasion

Paternally expressed gene 10 (PEG10) is an imprinted and monoallelic expressed gene. Previous study using a knockout mouse model revealed a crucial role of PEG10 in placental development, yet the exact function of PEG10 during placentation remains to be elucidated. In this study, denuded chorionic villi were prepared from first trimester human placentas, and transduced with PEG10 small interference RNA (siRNA) or non-targeting control sequence by lentiviral infection. Immunohistochemical staining revealed that silencing of PEG10 in the chorionic villous explants resulted in reduced immune-reactivity to CK7, Ki67 and integrin α5, implying that silencing of PEG10 impaired the proliferation of villous trophoblasts and may interfere with the activity of extravillous trophoblasts. We further investigated the role of PEG10 in the proliferation, migration and invasion of JEG-3 trophoblast cell line and the primary chorionic villous cells. PEG10-silenced JEG-3 cells and primary chorionic villous cells displayed a reduced proliferation rate and impaired invasiveness in vitro. Silencing of PEG10 in trophoblast cells led to upregulated expression of tissue inhibitor of metalloproteinase-1 (TIMP-1) as well as downregulated expression of matrix metalloproteinase (MMP)-2 and MMP-9. Furthermore, knockdown of TIMP-1 reversed the suppressed invasiveness of PEG10 siRNA-transduced JEG-3 cells. In conclusion, our study demonstrates that PEG10 plays an important role in trophoblast proliferation and promotes trophoblast invasion through TIMP-1.

Integrated tRNA, transcript, and protein profiles in response to steroid hormone signaling

The accurate and efficient transfer of genetic information into amino acid sequences is carried out through codon-anticodon interactions between mRNA and tRNA, respectively. In this way, tRNAs function at the interface between gene expression and protein synthesis. Whether tRNA levels are dynamically regulated and to what degree tRNA abundance influences the cellular proteome remains largely unexplored. Here we profile tRNA, transcript and protein levels in Drosophila Kc167 cells, a plasmatocyte cell line that, upon treatment with 20-hydroxyecdysone, differentiates into macrophages. We find that high abundance tRNAs associate with codons that are overrepresented in the Kc167 cell proteome, whereas tRNAs that are in low supply associate with codons that are underrepresented. Ecdysone-induced differentiation of Kc167 cells leads to changes in mRNA codon usage in a manner consistent with the developmental progression of the cell. At both early and late time points, ecdysone treatment concomitantly increases the abundance of tRNAThr(CGU), which decodes a differentiation-associated codon that becomes enriched in the macrophage proteome. These results together suggest that tRNA levels may provide a meaningful regulatory mechanism for defining the cellular proteomic landscape.

Systematic Prediction of Scaffold Proteins Reveals New Design Principles in Scaffold-Mediated Signal Transduction

Scaffold proteins play a crucial role in facilitating signal transduction in eukaryotes by bringing together multiple signaling components. In this study, we performed a systematic analysis of scaffold proteins in signal transduction by integrating protein-protein interaction and kinase-substrate relationship networks. We predicted 212 scaffold proteins that are involved in 605 distinct signaling pathways. The computational prediction was validated using a protein microarray-based approach. The predicted scaffold proteins showed several interesting characteristics, as we expected from the functionality of scaffold proteins. We found that the scaffold proteins are likely to interact with each other, which is consistent with previous finding that scaffold proteins tend to form homodimers and heterodimers. Interestingly, a single scaffold protein can be involved in multiple signaling pathways by interacting with other scaffold protein partners. Furthermore, we propose two possible regulatory mechanisms by which the activity of scaffold proteins is coordinated with their associated pathways through phosphorylation process.

Despite their importance in the signaling transduction, there is no systematic effort in identifying and characterizing the scaffold proteins in humans. In this work, we predicted scaffold proteins by integrating the available protein-protein interactions and kinase-substrate relationships. The predicted scaffold proteins showed characteristics for known scaffold proteins, suggesting the fidelity of our prediction. More importantly, the systematic prediction of scaffold proteins provides biological insights in the scaffold-mediated signal transduction. We found that scaffold proteins are likely to form complexes, suggesting that scaffold proteins could participate in diverse signaling pathways through the combinatorial interactions among scaffold proteins. Furthermore, the regulation of scaffold proteins’ activities has not been extensively studied. Our bioinformatics analysis proposed that scaffold proteins themselves might be regulated through phosphorylation process.

Cidec promotes the differentiation of human adipocytes by degradation of AMPKα through ubiquitin-proteasome pathway

BACKGROUND

We previously showed that Cidec was localized on the surface of lipid droplets and could promote the differentiation of human adipocytes, but the molecular mechanism was still unknown.

METHODS & RESULTS

In this study, we first sought to identify proteins that interact with Cidec using yeast two-hybrid system. The results revealed that Cidec could directly interact with AMPKα1 subunit. We further showed that AMPKα levels decreased while Cidec increased during the adipogenic differentiation of human adipocytes. Meanwhile, we observed that the increased Cidec could reduce AMPKα level in adipocytes, and the downregulation of AMPKα could help to promote the differentiation of adipocytes. The results of co-immunoprecipitation and immunofluorescent proved that Cidec biochemically interacted and co-localized with AMPKα1, which meant Cidec was a regulator for AMPKα stability through an ubiquitin-proteasome pathway.

CONCLUSION

Our data suggested that Cidec could interact with and down-regulate AMPKα through an ubiquitin-proteasome degradation pathway, which provided a possible mechanism of Cidec in promoting human adipocytes differentiation.

GENERAL SIGNIFICANCE

Our work proposed a new possible mechanism for human adipogenesis, and also provided a potential role of AMPKα as a target in treating obesity or obesity-related diseases.

Involvement of Antizyme Characterized from the Small Abalone Haliotis diversicolor in Gonadal Development

The small abalone Haliotis diversicolor is an economically important mollusk that is widely cultivated in Southern China. Gonad precocity may affect the aquaculture of small abalone. Polyamines, which are small cationic molecules essential for cellular proliferation, may affect gonadal development. Ornithine decarboxylase (ODC) and antizyme (AZ) are essential elements of a feedback circuit that regulates cellular polyamines. This paper presents the molecular cloning and characterization of AZ from small abalone. Sequence analysis showed that the cDNA sequence of H. diversicolor AZ (HdiODCAZ) consisted of two overlapping open reading frames (ORFs) and conformed to the +1 frameshift property of the frame. Thin Layer chromatography (TLC) analysis suggested that the expressed protein encoded by +1 ORF2 was the functional AZ that targets ODC to 26S proteasome degradation. The result demonstrated that the expression level of AZ was higher than that of ODC in the ovary of small abalone. In addition, the expression profiles of ODC and AZ at the different development stages of the ovary indicated that these two genes might be involved in the gonadal development of small abalone.

Ucma, a direct transcriptional target of Runx2 and Osterix, promotes osteoblast differentiation and nodule formation

OBJECTIVE

Runt-related transcription factor 2 (Runx2) and Osterix (Osx) are the master transcription factors in bone formation. Nonetheless, genes acting downstream of both Runx2 and Osx have yet to be fully characterized. Here, we investigate the downstream targets of both Runx2 and Osx in osteoblasts.

MATERIALS AND METHODS

DNA microarray analysis was conducted on calvarial RNA from wild-type, Runx2 heterozygous, Osx heterozygous, and Runx2/Osx double heterozygous embryos. Expression and transcriptional responses of the selected target gene were analyzed in MC3T3-E1 osteoblastic cells.

RESULTS

The expression of unique cartilage matrix-associated protein (Ucma) was decreased in Runx2/Osx double heterozygous embryos. In contrast, Ucma expression was increased in osteoblasts overexpressing both Runx2 and Osx. Ucma expression was initiated mid-way through osteoblast differentiation and continued throughout the differentiation process. Transcriptional activity of the Ucma promoter was increased upon transfection of the cells with both Runx2 and Osx. Runx2-and Osx-mediated activation of the Ucma promoter was directly regulated by Runx2-and/or Sp1-binding sites within its promoter. During osteoblast differentiation, the formation of mineralized nodules in Ucma-overexpressing stable clones occurred earlier and was more enhanced than that in the mock-transfected control. Mineralized nodule formation was strongly augmented in the cells cultured in a medium containing secretory Ucma proteins.

CONCLUSION

Ucma is a novel downstream gene regulated by both Runx2 and Osx and it stimulates osteoblast differentiation and nodule formation.

The receptor proteins: pivotal roles in selective autophagy

Autophagy is a highly regulated and multistep biological process whereby cells under metabolic, proteotoxic, or other stresses remove dysfunctional organelles and/or misfolded/polyubiquitinated proteins by shuttling them via specialized structures called autophagosomes to the lysosome for degradation. Although autophagy is generally considered to be a non-selective process, accumulating evidence suggests that it can also selectively degrade specific target cargoes. These selective targets include proteins, mitochondria, and even invading bacteria. The discovery and characterization of autophagic adapters, such as p62/Sequestosome 1 (SQSTM1) and Neighbor of BRCA1 gene 1 (NBR1), have provided mechanistic insights into selective autophagy. These receptors are all able to act as cargo receptors for the degradation of ubiquitinated substrates. This review mainly summarizes the most up-to-date findings regarding the key receptor proteins that play important roles in regulating selective autophagy.

VR-BFDT: A variance reduction based binary fuzzy decision tree induction method for protein function prediction

In protein function prediction (PFP) problem, the goal is to predict function of numerous well-sequenced known proteins whose function is not still known precisely. PFP is one of the special and complex problems in machine learning domain in which a protein (regarded as instance) may have more than one function simultaneously. Furthermore, the functions (regarded as classes) are dependent and also are organized in a hierarchical structure in the form of a tree or directed acyclic graph. One of the common learning methods proposed for solving this problem is decision trees in which, by partitioning data into sharp boundaries sets, small changes in the attribute values of a new instance may cause incorrect change in predicted label of the instance and finally misclassification. In this paper, a Variance Reduction based Binary Fuzzy Decision Tree (VR-BFDT) algorithm is proposed to predict functions of the proteins. This algorithm just fuzzifies the decision boundaries instead of converting the numeric attributes into fuzzy linguistic terms. It has the ability of assigning multiple functions to each protein simultaneously and preserves the hierarchy consistency between functional classes. It uses the label variance reduction as splitting criterion to select the best "attribute-value" at each node of the decision tree. The experimental results show that the overall performance of the proposed algorithm is promising.

Expression profiles of relaxin family peptides and their receptors indicate their influence on spermatogenesis in the domestic cat (Felis catus)

Disturbed spermatogenesis is a common problem in felines. Studying spermatogenesis in the domestic cat can improve the understanding of the biological background and help to counteract fertility problems in other feline species. Here, we analyzed 3 relaxin family peptides (relaxin, relaxin-3, and INSL3) and their receptors (RXFP1, RXFP2, and RXFP3) as potential spermatogenic factors involving their expression in the testis at different stages of its development. It may be concluded from its stage-dependent expression that relaxin, together with RXFP1, appears to be involved in the first stage of spermatogenesis, whereas relaxin-3 via binding to RXFP3 influences spermiogenesis. Furthermore, correlations were observed between relaxin, relaxin-3, RXFP1, RXFP2 and RXFP3 messenger RNA expression, and the relative numbers of haploid cells in testes. The peptide INSL3 was highly expressed at all testis development stages. Because of the low and stage-independent expression of its receptor RXFP2, an auto- and/or paracrine function of INSL3 in spermatogenesis seems unlikely. In the adult testis, messenger RNA expression of relaxin, RXFP1, and RXFP3 predominantly occurs in the tubular testis compartment, whereas INLS3 is mainly expressed in the interstitium.

The role of organic proteins on the crack growth resistance of human enamel

With only 1% protein by weight, tooth enamel is the most highly mineralized tissue in mammals. The focus of this study was to evaluate contributions of the proteins on the fracture resistance of this unique structural material. Sections of enamel were obtained from the cusps of human molars and the crack growth resistance was quantified using a conventional fracture mechanics approach with complementary finite element analysis. In selected specimens the proteins were extracted using a potassium hydroxide treatment. Removal of the proteins resulted in approximately 40% decrease in the fracture toughness with respect to the fully proteinized control. The loss of organic content was most detrimental to the extrinsic toughening mechanisms, causing over 80% reduction in their contribution to the total energy to fracture. This degradation occurred by embrittlement of the unbroken bridging ligaments and consequent reduction in the crack closure stress. Although the organic content of tooth enamel is very small, it is essential to crack growth toughening by facilitating the formation of unbroken ligaments and in fortifying their potency. Replicating functions of the organic content will be critical to the successful development of bio-inspired materials that are designed for fracture resistance.

Uterine NDRG2 expression is increased at implantation sites during early pregnancy in mice, and its down-regulation inhibits decidualization of mouse endometrial stromal cells

BACKGROUND

N-myc down-regulated gene 2 (NDRG2) is a tumor suppressor involved in cell proliferation and differentiation. The aim of this study was to determine the uterine expression pattern of this gene during early pregnancy in mice.

METHODS

Uterine NDRG2 mRNA and protein expression levels were determined by RT-PCR and Western blot analyses, respectively, during the peri-implantation period in mice. Immunohistochemical (IHC) analysis was performed to examine the spatial localization of NDRG2 expression in mouse uterine tissues. The in vitro decidualization model of mouse endometrial stromal cells (ESCs) was used to evaluate decidualization of ESCs following NDRG2 knock down by small interfering RNA (siRNA). Statistical significance was analyzed by one-way ANOVA using SPSS 19.0 software.

RESULTS

Uterine NDRG2 gene expression was significantly up-regulated and was predominantly localized to the secondary decidual zone on days 5 and 8 of pregnancy in mice. Its increased expression was associated with artificial decidualization as well as the activation of delayed implantation. Furthermore, uterine NDRG2 expression was induced by estrogen and progesterone treatments. The in vitro decidualization of mouse ESCs was accompanied by up-regulation of NDRG2 expression, and knock down of its expression in these cells by siRNA inhibited the decidualization process.

CONCLUSIONS

These results suggest that NDRG2 might play an important role in the process of decidualization during early pregnancy.

DAPD: A Knowledgebase for Diabetes Associated Proteins

Recent advancements in genomics and proteomics provide a solid foundation for understanding the pathogenesis of diabetes. Proteomics of diabetes associated pathways help to identify the most potent target for the management of diabetes. The relevant datasets are scattered in various prominent sources which takes much time to select the therapeutic target for the clinical management of diabetes. However, additional information about target proteins is needed for validation. This lacuna may be resolved by linking diabetes associated genes, pathways and proteins and it will provide a strong base for the treatment and planning management strategies of diabetes. Thus, a web source "Diabetes Associated Proteins Database (DAPD)" has been developed to link the diabetes associated genes, pathways and proteins using PHP, MySQL. The current version of DAPD has been built with proteins associated with different types of diabetes. In addition, DAPD has been linked to external sources to gain the access to more participatory proteins and their pathway network. DAPD will reduce the time and it is expected to pave the way for the discovery of novel anti-diabetic leads using computational drug designing for diabetes management. DAPD is open accessed via following url www.mkarthikeyan.bioinfoau.org/dapd.

Role of intracellular proteins in the regulation of calcium action and transmitter release during exocytosis

A central problem in cellular neurobiology is how the process of exocytosis of transmitters and hormones is regulated at the molecular level. Calcium is important in the process and may act by initiating the formation of fusion complexes of secretory granules to each other and to plasma membranes. We have discovered and isolated a new 47,000 MW protein (synexin) from adrenal medulla tissue that fuses chromaffin granule membranes only in the presence of calcium. Synexin activity was detected in a number of secretory tissues including human platelets and bovine brain, and the synexin molecule was found by immunofluorescent cytochemistry to be localized to the cytoplasm of chromaffin cells. Purified synexin molecules were found to self-associate in the presence of Ca++ to form paracrystalline arrays of 50 X 150 A rods, and the association was dependent on [Ca++] in an identical fashion to the Ca++ dependence of granule membrane fusion. On the basis of these data we suggest that synexin may be the intracellular receptor for calcium during exocytosis. However, the actual release event of 'fission' of the secretory vesicle-plasma membrane complex did not appear to be related to synexin action, and we have considered the hypothesis that the chemiosmotic mechanism for ATP, Cl--dependent chromaffin granule lysis might provide the necessary localized force. We have now shown that the granule model successfully predicts the secretory properties of human platelets, bovine parathyroid cells, and bovine chromaffin cells. Like the granule lysis system, secretion from these cells required specific anions in the medium was inhibited by anion transport blocking drugs and proton ionophores, and was suppressed by elevated osmotic strength. We suggest that secretory granules fused to plasma membranes in secreting cells, perhaps by synexin, may experience net solute uptake and subsequently undergo local, outwardly directed osmotic lysis, or exocytosis.

CIDEC/FSP27 is regulated by peroxisome proliferator-activated receptor alpha and plays a critical role in fasting- and diet-induced hepatosteatosis

The cell death-inducing DNA fragmentation factor alpha-like effector c (CIDEC; also known in rodents as FSP27 or fat-specific protein 27) is a lipid droplet-associated protein that promotes intracellular triglyceride (TAG) storage. CIDEC/Fsp27 is highly expressed in adipose tissue, but undetectable in normal liver. However, its hepatic expression rises during fasting or under genetic or diet-induced hepatosteatosis in both mice and patients. Herein, we demonstrate that CIDEC/Fsp27 is a direct transcriptional target of the nuclear receptor PPARα (peroxisome proliferator-activated receptor alpha) in both mouse and human hepatocytes, and that preventing Fsp27 induction accelerates PPARα-stimulated fatty acid oxidation. We show that adenoviral-mediated silencing of hepatic Fsp27 abolishes fasting-induced liver steatosis in the absence of changes in plasma lipids. Finally, we report that anti-Fsp27 short hairpin RNA and PPARα agonists synergize to ameliorate hepatosteatosis in mice fed a high fat diet.

CONCLUSIONS

Together, our data highlight the physiological importance of CIDEC/Fsp27 in TAG homeostasis under both physiological and pathological liver steatosis. Our results also suggest that patients taking fibrates likely have elevated levels of hepatic CIDEC, which may limit the efficient mobilization and catabolism of hepatic TAGs.

Molecular and functional analyses of a maize autoactive NB-LRR protein identify precise structural requirements for activity

Plant disease resistance is often mediated by nucleotide binding-leucine rich repeat (NLR) proteins which remain auto-inhibited until recognition of specific pathogen-derived molecules causes their activation, triggering a rapid, localized cell death called a hypersensitive response (HR). Three domains are recognized in one of the major classes of NLR proteins: a coiled-coil (CC), a nucleotide binding (NB-ARC) and a leucine rich repeat (LRR) domains. The maize NLR gene Rp1-D21 derives from an intergenic recombination event between two NLR genes, Rp1-D and Rp1-dp2 and confers an autoactive HR. We report systematic structural and functional analyses of Rp1 proteins in maize and N. benthamiana to characterize the molecular mechanism of NLR activation/auto-inhibition. We derive a model comprising the following three main features: Rp1 proteins appear to self-associate to become competent for activity. The CC domain is signaling-competent and is sufficient to induce HR. This can be suppressed by the NB-ARC domain through direct interaction. In autoactive proteins, the interaction of the LRR domain with the NB-ARC domain causes de-repression and thus disrupts the inhibition of HR. Further, we identify specific amino acids and combinations thereof that are important for the auto-inhibition/activity of Rp1 proteins. We also provide evidence for the function of MHD2, a previously uncharacterized, though widely conserved NLR motif. This work reports several novel insights into the precise structural requirement for NLR function and informs efforts towards utilizing these proteins for engineering disease resistance.

Prolyl isomerization and its catalysis in protein folding and protein function

Prolyl isomerizations are intrinsically slow processes. They determine the rates of many protein folding reactions and control regulatory events in folded proteins. Prolyl isomerases are able to catalyze these isomerizations, and thus, they have the potential to assist protein folding and to modulate protein function. Here, we provide examples for how prolyl isomerizations limit protein folding and are accelerated by prolyl isomerases and how native-state prolyl isomerizations regulate protein functions. The roles of prolines in protein folding and protein function are closely interrelated because both of them depend on the coupling between cis/trans isomerization and conformational changes that can involve extended regions of a protein.