Incorporating efficient radial basis function networks and significant amino acid pairs for predicting GTP binding sites in transport proteins

Background

Guanonine-protein (G-protein) is known as molecular switches inside cells, and is very important in signals transmission from outside to inside cell. Especially in transport protein, most of G-proteins play an important role in membrane trafficking; necessary for transferring proteins and other molecules to a variety of destinations outside and inside of the cell. The function of membrane trafficking is controlled by G-proteins via Guanosine triphosphate (GTP) binding sites. The GTP binding sites active G-proteins initiated to membrane vesicles by interacting with specific effector proteins. Without the interaction from GTP binding sites, G-proteins could not be active in membrane trafficking and consequently cause many diseases, i.e., cancer, Parkinson… Thus it is very important to identify GTP binding sites in membrane trafficking, in particular, and in transport protein, in general.

Results

We developed the proposed model with a cross-validation and examined with an independent dataset. We achieved an accuracy of 95.6% for evaluating with cross-validation and 98.7% for examining the performance with the independent data set. For newly discovered transport protein sequences, our approach performed remarkably better than similar methods such as GTPBinder, NsitePred and TargetSOS. Moreover, a friendly web server was developed for identifying GTP binding sites in transport proteins available for all users.

Conclusions

We approached a computational technique using PSSM profiles and SAAPs for identifying GTP binding residues in transport proteins. When we included SAAPs into PSSM profiles, the predictive performance achieved a significant improvement in all measurement metrics. Furthermore, the proposed method could be a power tool for determining new proteins that belongs into GTP binding sites in transport proteins and can provide useful information for biologists.

     

Effect of everolimus on the glucose metabolic pathway in mouse skeletal muscle cells (C2C12)

Introduction

Everolimus selectively inhibits mammalian target of rapamycin complex 1 (mTORC1) and exerts an antineoplastic effect. Metabolic disturbance has emerged as a common and unique side effect of everolimus.

Objectives

We used targeted metabolomic analysis to investigate the effects of everolimus on the intracellular glycometabolic pathway.

Methods

Mouse skeletal muscle cells (C2C12) were exposed to everolimus for 48 h, and changes in intracellular metabolites were determined by capillary electrophoresis time-of-flight mass spectrometry. mRNA abundance, protein expression and activity were measured for enzymes involved in glycometabolism and related pathways.

Results

Both extracellular and intracellular glucose levels increased with exposure to everolimus. Most intracellular glycometabolites were decreased by everolimus, including those involved in glycolysis and the pentose phosphate pathway, whereas no changes were observed in the tricarboxylic acid cycle. Everolimus suppressed mRNA expression of enzymes related to glycolysis, downstream of mTOR signaling enzymes and adenosine 5′-monophosphate protein kinases. The activity of key enzymes involved in glycolysis and the pentose phosphate pathway were decreased by everolimus. These results show that everolimus impairs glucose utilization in intracellular metabolism.

Conclusions

The present metabolomic analysis indicates that everolimus impairs glucose metabolism in muscle cells by lowering the activities of glycolysis and the pentose phosphate pathway.

     

Fusion to GFP blocks intercellular trafficking of the sucrose transporter SUT1 leading to accumulation in companion cells

Background

Plant phloem consists of an interdependent cell pair, the sieve element / companion cell complex. Sucrose transporters are localized to enucleate sieve elements (SE), despite being transcribed in companion cells (CC). Due to the high turnover of SUT1, sucrose transporter mRNA or protein must traffic from CC to SE via the plasmodesmata. Localization of SUT mRNA at plasmodesmatal orifices connecting CC and SE suggests RNA transport, potentially mediated by RNA binding proteins. In many organisms, polar RNA transport is mediated through RNA binding proteins interacting with the 3'-UTR and controlling localized protein synthesis. To study mechanisms for trafficking of SUT1, GFP-fusions with and without 3'-UTR were expressed in transgenic plants.

Results

In contrast to plants expressing GFP from the strong SUC2 promoter, in RolC-controlled expression GFP is retained in companion cells. The 3'-UTR of SUT1 affected intracellular distribution of GFP but was insufficient for trafficking of SUT1, GFP or their fusions to SEs. Fusion of GFP to SUT1 did however lead to accumulation of SUT1-GFP in the CC, indicating that trafficking was blocked while translational inhibition of SUT1 mRNA was released in CCs.

Conclusion

A fusion with GFP prevents targeting of the sucrose transporter SUT1 to the SE while leading to accumulation in the CC. The 3'-UTR of SUT1 is insufficient for mobilization of either the fusion or GFP alone. It is conceivable that SUT1-GFP protein transport through PD to SE was blocked due to the presence of GFP, resulting in retention in CC particles. Alternatively, SUT1 mRNA transport through the PD could have been blocked due to insertion of GFP between the SUT1 coding sequence and 3'-UTR.

     

Effect of ovarian cancer ascites on SKOV-3 cells proteome: new proteins associated with aggressive phenotype in epithelial ovarian cancer

Background

Epithelial ovarian cancer is the second most lethal gynecological cancer worldwide. Ascites can be found in all clinical stages, however in advanced disease stages IIIC and IV it is more frequent and could be massive, associated with worse prognosis. Due to the above, it was our interest to understanding how the ascites of ovarian cancer patients induces the mechanisms by which the cells present in it acquire a more aggressive phenotype and to know new proteins associated to this process.

Methods

A proteomic analysis of SKOV-3 cells treated with five different EOC ascites was performed by two-dimensional electrophoresis coupled to MALDI-TOF. The level of expression of the proteins of interest was validated by RT-PCR because several of these proteins have only been reported at the messenger level.

Results

Among the proteins identified that increased their expression in ascites-treated SKOV-3 cells, were Ran GTPase, ZNF268, and Synaptotagmin like-3. On the other hand, proteins that were negatively regulated by ascites were HLA-I, HSPB1, ARF1, Synaptotagmin 1, and hnRNPH1, among others. Furthermore, an interactome for every one of these proteins was done in order to identify biological processes, molecular actions, and cellular components in which they may participate.

Conclusions

Identified proteins participate in cellular processes highly relevant to the aggressive phenotype such as nuclear transport, regulation of gene expression, vesicular trafficking, evasion of the immune response, invasion, metastasis, and in resistance to chemotherapy. These proteins may represent a source of information which has the potential to be evaluated for the design of therapies directed against these malignant cells that reside on ovarian cancer ascites.

     

Novel extracellular and nuclear caspase-1 and inflammasomes propagate inflammation and regulate gene expression: a comprehensive database mining study

Background

Caspase-1 is present in the cytosol as an inactive zymogen and requires the protein complexes named “inflammasomes” for proteolytic activation. However, it remains unclear whether the proteolytic activity of caspase-1 is confined only to the cytosol where inflammasomes are assembled to convert inactive pro-caspase-1 to active caspase-1.

Methods

We conducted meticulous data analysis method?s on proteomic, protein interaction, protein intracellular localization, and gene expressions of 114 experimentally identified caspase-1 substrates and 38 caspase-1 interaction proteins in normal physiological conditions and in various pathologies.

Results

We made the following important findings: (1) Caspase-1 substrates and interaction proteins are localized in various intracellular organelles including nucleus and secreted extracellularly; (2) Caspase-1 may get activated in situ in the nucleus in response to intra-nuclear danger signals; (3) Caspase-1 cleaves its substrates in exocytotic secretory pathways including exosomes to propagate inflammation to neighboring and remote cells; (4) Most of caspase-1 substrates are upregulated in coronary artery disease regardless of their subcellular localization but the majority of metabolic diseases cause no significant expression changes in caspase-1 nuclear substrates; and (5) In coronary artery disease, majority of upregulated caspase-1 extracellular substrate-related pathways are involved in induction of inflammation; and in contrast, upregulated caspase-1 nuclear substrate-related pathways are more involved in regulating cell death and chromatin regulation.

Conclusions

Our identification of novel caspase-1 trafficking sites, nuclear and extracellular inflammasomes, and extracellular caspase-1-based inflammation propagation model provides a list of targets for the future development of new therapeutics to treat cardiovascular diseases, inflammatory diseases, and inflammatory cancers.

     

Using an NMR metabolomics approach to investigate the pathogenicity of amyloid-beta and alpha-synuclein

Introduction

The pathogenicity at differing points along the aggregation pathway of many fibril-forming proteins associated with neurodegenerative diseases is unclear. Understanding the effect of different aggregation states of these proteins on cellular processes is essential to enhance understanding of diseases and provide future options for diagnosis and therapeutic intervention.

Objectives

To establish a robust method to probe the metabolic changes of neuronal cells and use it to monitor cellular response to challenge with three amyloidogenic proteins associated with neurodegenerative diseases in different aggregation states.

Method

Neuroblastoma SH-SY5Y cells were employed to design a robust routine system to perform a statistically rigorous NMR metabolomics study into cellular effects of sub-toxic levels of alpha-synuclein, amyloid-beta 40 and amyloid-beta 42 in monomeric, oligomeric and fibrillar conformations.

Results

This investigation developed a rigorous model to monitor intracellular metabolic profiles of neuronal cells through combination of existing methods. This model revealed eight key metabolites that are altered when neuroblastoma cells are challenged with proteins in different aggregation states. Metabolic pathways associated with lipid metabolism, neurotransmission and adaptation to oxidative stress and inflammation are the predominant contributors to the cellular variance and intracellular metabolite levels. The observed metabolite changes for monomer and oligomer challenge may represent cellular effort to counteract the pathogenicity of the challenge, whereas fibrillar challenge is indicative of system shutdown. This implies that although markers of stress are more prevalent under oligomeric challenge the fibrillar response suggests a more toxic environment.

Conclusion

This approach is applicable to any cell type that can be cultured in a laboratory (primary or cell line) as a method of investigating how protein challenge affects signalling pathways, providing additional understanding as to the role of protein aggregation in neurodegenerative disease initiation and progression.

     

Eg5 orchestrates porcine oocyte maturational progression by maintaining meiotic organelle arrangement

Background

Kinesin superfamily proteins are microtubule-based molecular motors essential for the intracellular transport of various cargos, including organelles, proteins, and RNAs. However, their exact roles during mammalian oocyte meiosis have not been fully clarified.

Results

Herein, we investigated the critical events during porcine oocyte meiotic maturation with the treatment of Eg5-specific inhibitor monastrol. We found that Eg5 inhibition resulted in oocyte meiotic failure by displaying the poor expansion of cumulus cells and reduced rate of polar body extrusion. In the meantime, the spindle assembly and chromosome alignment were compromised, accompanied by the decreased level of acetylated α-tubulin, indicative of less stable microtubules. Impaired actin dynamics and mitochondria integrity were also observed in Eg5-inhibited oocytes. Additionally, inhibition of Eg5 caused the abnormal distribution of cortical granules and ovastacin, a cortical granule component, potentially leading to the fertilization failure.

Conclusions

Our findings reveal that Eg5 possesses an important function in porcine oocyte meiotic progression by regulating the organelle dynamics and arrangement.

     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

Quantifying the cellular NAD+ metabolome using a tandem liquid chromatography mass spectrometry approach

Introduction

Nicotinamide adenine dinucleotide (NAD⁺) is an essential pyridine nucleotide that serves as a key hydride transfer coenzyme for several oxidoreductases. It is also the substrate for intracellular secondary messenger signalling by CD38 glycohydrolases, DNA repair by poly(adenosine diphosphate ribose) polymerase, and epigenetic regulation of gene expression by a class of histone deacetylase enzymes known as sirtuins. The measurement of NAD⁺ and its related metabolites (hereafter, the NAD⁺ metabolome) represents an important indicator of cellular function.

Objectives

A study was performed to develop a sensitive, selective, robust, reproducible, and rapid method for the concurrent quantitative determination of intracellular levels of the NAD⁺ metabolome in glial and oocyte cell extracts using liquid chromatography coupled to mass spectrometry (LC/MS/MS).

Methods

The metabolites were separated on a versatile amino column using a dual HILIC-RP gradient with heated electrospray (HESI) tandem mass spectrometry detection in mixed polarity multiple reaction monitoring mode.

Results

Quantification of 17 metabolites in the NAD⁺ metabolome in U251 human astroglioma cells could be achieved. Changes in NAD⁺ metabolism in U251 cell line, and murine oocytes under different culture conditions were also investigated.

Conclusion

This method can be used as a sensitive profiling tool, tailoring chromatography for metabolites that express significant pathophysiological changes in several disease conditions and is indispensable for targeted analysis.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Esub8: A novel tool to predict protein subcellular localizations in eukaryotic organisms

Background

Subcellular localization of a new protein sequence is very important and fruitful for understanding its function. As the number of new genomes has dramatically increased over recent years, a reliable and efficient system to predict protein subcellular location is urgently needed.

Results

Esub8 was developed to predict protein subcellular localizations for eukaryotic proteins based on amino acid composition. In this research, the proteins are classified into the following eight groups: chloroplast, cytoplasm, extracellular, Golgi apparatus, lysosome, mitochondria, nucleus and peroxisome. We know subcellular localization is a typical classification problem; consequently, a one-against-one (1-v-1) multi-class support vector machine was introduced to construct the classifier. Unlike previous methods, ours considers the order information of protein sequences by a different method. Our method is tested in three subcellular localization predictions for prokaryotic proteins and four subcellular localization predictions for eukaryotic proteins on Reinhardt's dataset. The results are then compared to several other methods. The total prediction accuracies of two tests are both 100% by a self-consistency test, and are 92.9% and 84.14% by the jackknife test, respectively. Esub8 also provides excellent results: the total prediction accuracies are 100% by a self-consistency test and 87% by the jackknife test.

Conclusions

Our method represents a different approach for predicting protein subcellular localization and achieved a satisfactory result; furthermore, we believe Esub8 will be a useful tool for predicting protein subcellular localizations in eukaryotic organisms.

     

Crystal structure of <Emphasis Type="Italic">Escherichia coli</Emphasis> protein ybgI,a toroidal structure with a dinuclear metal site

Background

The protein encoded by the gene ybgI was chosen as a target for a structural genomics project emphasizing the relation of protein structure to function.

Results

The structure of the ybgI protein is a toroid composed of six polypeptide chains forming a trimer of dimers. Each polypeptide chain binds two metal ions on the inside of the toroid.

Conclusion

The toroidal structure is comparable to that of some proteins that are involved in DNA metabolism. The di-nuclear metal site could imply that the specific function of this protein is as a hydrolase-oxidase enzyme.

     

Untargeted metabolomics suffers from incomplete raw data processing

Introduction

Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.

Objectives

Assessment of the quality of raw data processing in untargeted metabolomics.

Methods

Five published untargeted metabolomics studies, were reanalyzed.

Results

Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.

Conclusion

Incomplete raw data processing shows unexplored potential of current and legacy data.

     

Identification of an oleosin-like gene in seagrass seeds

Objective

To investigate the oil body protein and function in seeds of mature seagrass, Thalassia hemprichii.

Results

Seeds of mature seagrass T. hemprichii when stained with a fluorescent probe BODIPY showed the presence of oil bodies in intracellular cells. Triacylglycerol was the major lipid class in the seeds. Protein extracted from seagrass seeds was subjected to immunological cross-recognition with land plant seed oil body proteins, such as oleosin and caleosin, resulting in no cross-reactivity. An oleosin-like gene was found in seagrass seeds. Next generation sequencing and sequence alignment indicated that the deduced seagrass seed oleosin-like protein has a central hydrophobic domain responsible for their anchoring onto the surface of oil bodies. Phylogenetic analysis showed that the oleosin-like protein was evolutionarily closer to pollen oleosin than to seed oleosins.

Conclusion

Oil body protein found in seagrass seeds represent a distinct class of land seed oil body proteins.

     

Extraction of natural products from bark of <Emphasis Type="Italic">Betula pendula</Emphasis> using ionic liquids

Introduction

Aqueous–methanol mixtures have successfully been applied to extract a broad range of metabolites from plant tissue. However, a certain amount of material remains insoluble.

Objectives

To enlarge the metabolic compendium, two ionic liquids were selected to extract the methanol insoluble part of trunk from Betula pendula.

Methods

The extracted compounds were analyzed by LC/MS and GC/MS.

Results

The results show that 1-butyl-3-methylimidazolium acetate (IL-Ac) predominantly resulted in fatty acids, whereas 1-ethyl-3-methylimidazolium tosylate (IL-Tos) mostly yielded phenolic structures. Interestingly, bark yielded more ionic liquid soluble metabolites compared to interior wood.

Conclusion

From this one can conclude that the application of ionic liquids may expand the metabolic snapshot.

     

ULK1 phosphorylates Sec23A and mediates autophagy-induced inhibition of ER-to-Golgi traffic

Background

Autophagy is an inducible autodigestive process that allows cells to recycle proteins and other materials for survival during stress and nutrient deprived conditions. The kinase ULK1 is required to activate this process. ULK1 phosphorylates a number of target proteins and regulates many cellular processes including the early secretory pathway. Recently, ULK1 has been demonstrated to phosphorylate Sec16 and affects the transport of serotonin transporter at the ER exit sites (ERES), but whether ULK1 may affect the transport of other cargo proteins and general secretion has not been fully addressed.

Results

In this study, we identified Sec23A, a component of the COPII vesicle coat, as a target of ULK1 phosphorylation. Elevated autophagy, induced by amino acid starvation, rapamycin, or overexpression of ULK1 caused aggregation of the ERES, a region of the ER dedicated for the budding of COPII vesicles. Transport of cargo proteins was also inhibited under these conditions and was retained at the ERES. ULK1 phosphorylation of Sec23A reduced the interaction between Sec23A and Sec31A. We identified serine 207, serine 312 and threonine 405 on Sec23A as ULK1 phosphorylation sites. Among these residues, serine 207, when changed to phospho-deficient and phospho-mimicking mutants, most faithfully recapitulated the above-mentioned effects of ULK1 phospho-regulation.

Conclusion

These findings identify Sec23A as a new target of ULK1 and uncover a mechanism of coordinating intracellular protein transport and autophagy.

     

A methodology for elucidating regulatory mechanisms leading to changes in lipid profiles

Introduction

It is difficult to elucidate the metabolic and regulatory factors causing lipidome perturbations.

Objectives

This work simplifies this process.

Methods

A method has been developed to query an online holistic lipid metabolic network (of 7923 metabolites) to extract the pathways that connect the input list of lipids.

Results

The output enables pathway visualisation and the querying of other databases to identify potential regulators. When used to a study a plasma lipidome dataset of polycystic ovary syndrome, 14 enzymes were identified, of which 3 are linked to ELAVL1—an mRNA stabiliser.

Conclusion

This method provides a simplified approach to identifying potential regulators causing lipid-profile perturbations.

     

KniMet: a pipeline for the processing of chromatography–mass spectrometry metabolomics data

Introduction

Data processing is one of the biggest problems in metabolomics, given the high number of samples analyzed and the need of multiple software packages for each step of the processing workflow.

Objectives

Merge in the same platform the steps required for metabolomics data processing.

Methods

KniMet is a workflow for the processing of mass spectrometry-metabolomics data based on the KNIME Analytics platform.

Results

The approach includes key steps to follow in metabolomics data processing: feature filtering, missing value imputation, normalization, batch correction and annotation.

Conclusion

KniMet provides the user with a local, modular and customizable workflow for the processing of both GC–MS and LC–MS open profiling data.

     

Pseudo current density maps of electrophysiological heart,nerve or brain function and their physical basis

Background

In recent years the visualization of biomagnetic measurement data by so-called pseudo current density maps or Hosaka-Cohen (HC) transformations became popular.

Methods

The physical basis of these intuitive maps is clarified by means of analytically solvable problems.

Results

Examples in magnetocardiography, magnetoencephalography and magnetoneurography demonstrate the usefulness of this method.

Conclusion

Hardware realizations of the HC-transformation and some similar transformations are discussed which could advantageously support cross-platform comparability of biomagnetic measurements.