Search

Many growth factors and cytokines are produced as larger precursors, containing pro-domains, that require proteolytic processing to release the bioactive ligand. These pro-domains can be significantly larger than the mature domains and can play an active role in the regulation of the ligands. Mining the UniProt database, we identified almost one hundred human growth factors and cytokines with pro-domains. These are spread across several unrelated protein families and vary in both their size and composition. The precise role of each pro-domain varies significantly between the protein families. Typically they are critical for controlling bioactivity and protein localisation, and they facilitate diverse mechanisms of activation. Significant gaps in our understanding remain for pro-domain function — particularly their fate once the bioactive ligand has been released. Here we provide an overview of pro-domain roles in human growth factors and cytokines, their processing, regulation and activation, localisation as well as therapeutic potential.

In this paper, we present a multi-label classification pipeline and a novel feature descriptor for the protein subcellular localisation. The challenge here is the development of a computational model that can classify multi-site proteins on a highly imbalanced dataset with a long-tail distribution and multi-label images. To address this challenge, we design a Location-Sorted Random Projections feature descriptor to represent image intensity and gradient of the protein of interest in reference to the correlated cellular region. Multilabel Synthetic Minority Over-sampling Technique is optimised to generate synthetic features with labels to handle class imbalance. Our method achieves the state-of-the-art performance on a large-scale public dataset and demonstrates excellent performance for the minority classes.

The lipid post-translational modification S-palmitoylation is a vast developing field, with the modification itself and the enzymes that catalyse the reversible reaction implicated in a number of diseases. In this review, we discuss the past and recent advances in the experimental tools used in this field, including pharmacological tools, animal models and techniques to understand how palmitoylation controls protein localisation and function. Additionally, we discuss the obstacles to overcome in order to advance the field, particularly to the point at which modulating palmitoylation may be achieved as a therapeutic strategy.

In the search for the mitochondrion of oxymonads, DNA of Monocercomonoides exilis - an oxymonad isolated from the gut of Chinchilla, was isolated and its genome was sequenced. Sequencing resulted in a fairly complete genome which was extensively searched or genes for mitochondrion related proteins, but no reliable candidate for such gene was identified. Even genes for the ISC pathway, which is responsible for Fe-S cluster assembly and considered to be the only essential function of reduced mitochondrion-like organelles (MROs), were absent. Instead, we were able to detect the presence of a SUF pathway which functionally replaced the ISC pathway. Closer examination of the SUF pathway based on heterologous localisation revealed that this pathway localised in the cytosol. In silico analysis showed that SUF genes are highly conserved at the level of secondary and tertiary structure and most catalytic residues and motifs are present in their sequences. The functionality of these proteins was further indirectly confirmed by complementation experiments in Escherichia coli where SUF proteins of M. exilis were able to restore at least partially Fe-S cluster assembly of strains deficient in the SUF and ISC pathways. We also proved by bacterial adenylate cyclase two-hybrid system that SufB and SufC can form...

DNA-Methylierung ist eine epigenetische Markierung, die eine Rolle in der Embryonalent-wicklung und der Genregulation spielt. DNA-Methyltransferasen (DNMTs) sind Enzyme, welche DNA methylieren. Da DNA-Methylierung zu den „Hallmarks of Cancer“ gehört, ist es besonders von Interesse die Mechanismen, die dabei am Werk sind, weitergehend zu ver-stehen. Es ist bekannt, dass verschiedene Histonmodifizierungen DNMTs durch verschie-dene Enzymdomänen rekrutieren können. Die exakten Funktionen der Proteindomänen wie der N-Terminus und die PWWP-Domäne sowie deren Rolle in der Lokalisierung bei Chro-matin sind hingegen derzeit nicht vollständig geklärt. Basierend auf Experimenten unserer Forschungsgruppe, die die Erhaltung von DNA-Methylierung in Krebszellen durch DNMT3B2 zeigten, war das Ziel dieser Arbeit, den Einfluss der PWWP-Domäne und den N-Terminus des DNMT3B2-Proteins auf die Lokalisierung von DNMT3B2 zu Heterochromatin zu erforschen. Wir observierten DNMT3B2-Lokalisierung in NIH3T3-Zellen mittels Immun-fluoreszenz. Unsere Ergebnisse zeigten, dass die PWWP-Domäne nicht für die Lokalisie-rung zu Heterochromatin benötigt wird, der N-Terminus hingegen schon. DNMT3B2-Lokalisierung wurde auch in lebenden HCT116-Zellen überprüft. Verteilungsmuster von DNMT3B2 mit mutierter PWWP-Domäne oder verkürztem N-Terminus zeigten eine andere Verteilung. Die Muster des Live-imagings unterschieden sich des Weiteren erheblich von den mittels Immunfluoreszenz detektierten Mustern. Dies weist auf eine Auswirkung der Zellfixierung auf die DNMT3B2-Lokalisierung hin. Aus diesem Grund wird für zukünftige Experimente Live-imaging als bevorzugter Ansatz genommen, um die Rekrutierung zu Chromatin durch verschiedene DNMT3B2-Domänen weiter zu erläutern. DNA methylation is an epigenetic mark that plays a role in embryonic development and gene regulation. DNA methyltransferases (DNMTs) are enzymes responsible for DNA methylation. As DNA methylation is a hallmark of cancer, it is of particular interest to further understand the mechanisms at work. It is understood that different histone marks can re-cruit DNMTs through different domains of the enzyme. However, the exact functions of pro-tein domains such as the N-terminus or the PWWP domain and their role in localisation to chromatin has not yet been fully elucidated. Based on previous functional evidence in our lab that DNMT3B2 maintains heterochromatin in cancer cells, the aim of this project was to investigate how the PWWP domain and the N-terminus of DNMT3B2 affect localisation of DNMT3B2 to heterochromatin. We observed DNMT3B2 localisation in NIH3T3 cells using immunofluorescence. Our findings indicated that the PWWP domain is not required for lo-calisation to heterochromatin whereas the N-terminus is. DNMT3B2 localisation was also observed in live HCT116 cells. Patterns of DNMT3B2 with a mutated PWWP domain or truncated N-terminus showed different DNMT3B2 distributions compared to the wild type. The live patterns greatly differed to the ones found in immunofluorescent cells, suggesting that fixation affects DNMT3B2 localisation. Therefore, for future experiments, live-imaging will be the approach of choice to further elucidate recruitment to chromatin through different domains of DNMT3B2.

Summary Electron cryotomography (cryoET), an electron cryomicroscopy (cryoEM) modality, has changed our understanding of biological function by revealing the native molecular details of membranes, viruses, and cells. However, identification of individual molecules within tomograms from cryoET is challenging because of sample crowding and low signal-to-noise ratios. Here, we present a tagging strategy for cryoET that precisely identifies individual protein complexes in tomograms without relying on metal clusters. Our method makes use of DNA origami to produce “molecular signposts” that target molecules of interest, here via fluorescent fusion proteins, providing a platform generally applicable to biological surfaces. We demonstrate the specificity of signpost origami tags (SPOTs) in vitro as well as their suitability for cryoET of membrane vesicles, enveloped viruses, and the exterior of intact mammalian cells., Graphical Abstract, Highlights • Asymmetric DNA signpost origami tags (SPOTs) precisely localize proteins • SPOTs identify specific proteins in electron cryomicroscopy • SPOTs have a high contrast “sign” and functionalized “post” base for targeting • SPOTs recognize fluorescent fusion proteins on vesicles, viruses, and cell surfaces, Large, folded DNA structures, designed to recognize proteins on cell surfaces, facilitate in situ structural analyses.

Highlights • Protein subcellular localisation is essential for cellular homeostasis. • Factors governing protein localisation are poorly understood. • Various different methods exist to study this process. • Recent studies have captured ever higher resolution localisation information. • Orthogonal methods should be used to gain a holistic view of protein localisation., Subcellular protein localisation is essential for the mechanisms that govern cellular homeostasis. The ability to understand processes leading to this phenomenon will therefore enhance our understanding of cellular function. Here we review recent developments in this field with regard to mass spectrometry, fluorescence microscopy and computational prediction methods. We highlight relative strengths and limitations of current methodologies focussing particularly on studies in the yeast Saccharomyces cerevisiae. We further present the first cell-wide spatial proteome map of S. cerevisiae, generated using hyperLOPIT, a mass spectrometry-based protein correlation profiling technique. We compare protein subcellular localisation assignments from this map, with two published fluorescence microscopy studies and show that confidence in localisation assignment is attained using multiple orthogonal methods that provide complementary data.

International audience; Proteins often act in complexes assembled via protein-protein interaction domains. The sterile alpha motif (SAM) domain is one of the most prominent interaction domains in animals and is present in proteins of diverse functions. This domain allows head-to-tail closed oligomerisation or polymer formation resulting in homo- and/or heterocomplexes that have been shown to be important for proper protein localisation and function. In plants this domain is also present but has been poorly studied except for recent studies on the LEAFY floral regulator and the tRNA import component (TRIC)1/2 proteins. Here we catalogue SAM domain-containing proteins from arabidopsis (Arabidopsis thaliana), compare plant and other eukaryotic SAM domains, and perform homology modelling to probe plant SAM domain interaction capabilities.

The present short introduction to confocal microscopy in plant cell biology is meant to be a reference addressed to those who are approaching these studies. Optical and genetic techniques developed over the last years have revolutionised plant cell biology. They enable in vivo studies of cell organisation, mainly based on the use of confocal microscopy and derivatives of the Green Fluorescent Protein (GFP). Such fluorescent proteins are extremely useful tools for directly monitoring gene expression and protein localisation, and for selectively labelling sub-cellular structures. GFP-expressing plants can be directly examined by confocal microscopy to obtain high-resolution optical sections of intact tissues and to allow time-lapse observation of dynamic processes. The application of such approaches to the investigation of root cell responses during arbuscular mycorrhizal colonisation is discussed.

In biology, localisation is function. Cells display a complex sub-cellular structure with numerous distinct niches responsible for specific biological processes. Consequently, not only must proteins be present in a cell to accomplish their biological functions, but they must be localised in their intended sub-cellular locations. In contrast, mis-localised proteins can have serious advert consequences. In this talk, I will describe how contemporary experimental and computational technologies can be used to produce proteome-wide proteins localisation maps, and how these findings are supported by an open and collaborative suite of software packages.

Here we report the adaptation of the CLARITY technique to plant tissues with addition of enzymatic degradation to improve optical clearing and facilitate antibody probe penetration. Plant-Enzyme-Assisted (PEA)-CLARITY, has allowed deep optical visualisation of stains, expressed fluorescent proteins and IgG-antibodies in Tobacco and Arabidopsis leaves. Enzyme treatment enabled penetration of antibodies into whole tissues without the need for any sectioning of the material, thus facilitating protein localisation of intact tissue in 3D whilst retaining cellular structure.

Background Mutation in the UPF3B gene on chromosome X is implicated in neurodevelopmental disorders including X-linked intellectual disability, autism and schizophrenia. The protein UPF3B is involved in the nonsense-mediated mRNA decay pathway (NMD) that controls mRNA stability and functions in the prevention of the synthesis of truncated proteins. Results Here we show that NMD pathway components UPF3B and UPF1 are down-regulated during differentiation of neural stem cells into neurons. Using tethered function assays we found that UPF3B missense mutations described in families with neurodevelopmental disorders reduced the activity of UPF3B protein in NMD. In neural stem cells, UPF3B protein was detected in the cytoplasm and in the nucleus. Similarly in neurons, UPF3B protein was detected in neurites, the somatic cytoplasm and in the nucleus. In both cell types nuclear UPF3B protein was enriched in the nucleolus. Using GFP tagged UPF3B proteins we found that the missense mutations did not affect the cellular localisation. Expression of missense mutant UPF3B disturbed neuronal differentiation and reduced the complexity of the branching of neurites. Neuronal differentiation was similarly affected in the presence of the NMD inhibitor Amlexanox. The expression of mutant UPF3B proteins lead to a subtle increase in mRNA levels of selected NMD targets. Conclusions Together our findings indicate that, despite the down-regulation of NMD factors, functional NMD is critical for neuronal differentiation. We propose that the neurodevelopmental phenotype of UPF3B missense mutation is caused by impairment of NMD function altering neuronal differentiation. Electronic supplementary material The online version of this article (doi:10.1186/s13041-015-0122-1) contains supplementary material, which is available to authorized users.

Bacteriophage PRD1, which has been studied intensively at the structural and functional levels, still has some gene products with unknown functions and certain aspects of the PRD1 assembly process have remained unsolved. In this study, we demonstrate that the phage-encoded non-structural proteins P17 and P33, either individually or together, complement the defect in a temperature-sensitive GroES mutant of Escherichia coli for host growth and PRD1 propagation. Confocal microscopy of fluorescent fusion proteins revealed co-localisation between P33 and P17 as well as between P33 and the host chaperonin GroEL. A fluorescence recovery after photobleaching assay demonstrated that the diffusion of the P33 fluorescent fusion protein was substantially slower in E. coli than theoretically calculated, presumably resulting from intermolecular interactions. Our results indicate that P33 and P17 function in procapsid assembly, possibly in association with the host chaperonin complex GroEL/GroES.

Background The subcellular localisation of proteins in intact living cells is an important means for gaining information about protein functions. Even dynamic processes can be captured, which can barely be predicted based on amino acid sequences. Besides increasing our knowledge about intracellular processes, this information facilitates the development of innovative therapies and new diagnostic methods. In order to perform such a localisation, the proteins under analysis are usually fused with a fluorescent protein. So, they can be observed by means of a fluorescence microscope and analysed. In recent years, several automated methods have been proposed for performing such analyses. Here, two different types of approaches can be distinguished: techniques which enable the recognition of a fixed set of protein locations and methods that identify new ones. To our knowledge, a combination of both approaches – i.e. a technique, which enables supervised learning using a known set of protein locations and is able to identify and incorporate new protein locations afterwards – has not been presented yet. Furthermore, associated problems, e.g. the recognition of cells to be analysed, have usually been neglected. Results We introduce a novel approach to automated protein localisation in living cells. In contrast to well-known techniques, the protein localisation technique presented in this article aims at combining the two types of approaches described above: After an automatic identification of unknown protein locations, a potential user is enabled to incorporate them into the pre-trained system. An incremental neural network allows the classification of a fixed set of protein location as well as the detection, clustering and incorporation of additional patterns that occur during an experiment. Here, the proposed technique achieves promising results with respect to both tasks. In addition, the protein localisation procedure has been adapted to an existing cell recognition approach. Therefore, it is especially well-suited for high-throughput investigations where user interactions have to be avoided. Conclusion We have shown that several aspects required for developing an automatic protein localisation technique – namely the recognition of cells, the classification of protein distribution patterns into a set of learnt protein locations, and the detection and learning of new locations – can be combined successfully. So, the proposed method constitutes a crucial step to render image-based protein localisation techniques amenable to large-scale experiments.

The automatic subcellular localisation of proteins in living cells is a critical step in determining their function. The evaluation of fluorescence images constitutes a common method of localising these proteins. For this, additional knowledge about the position of the considered cells within an image is required. In an automated system, it is advantageous to recognise these cells in bright-field microscope images taken in parallel with the regarded fluorescence micrographs. Unfortunately, currently available cell recognition methods are only of limited use within the context of protein localisation, since they frequently require microscopy techniques that enable images of higher contrast (e.g. phase contrast microscopy or additional dyes) or can only be employed with too low magnifications. Therefore, this article introduces a novel approach to the robust automatic recognition of unstained living cells in bright-field microscope images. Here, the focus is on the automatic segmentation of cells.

The subcellular localisation of proteins in living cells is a crucial means for the determination of their function. We propose an approach to realise such a protein localisation based on microscope images. In order to reach this goal, appropriate features are selected. Then, the initial feature set is optimised by a genetic algorithm. The actual classification of possible protein localisations is accomplished by an incremental neural network which not only achieves a very high accuracy, but enables on-line learning, as well.

As science progresses in its understanding of diseases and their treatment, advances have been made in the biotechnology used in disease therapy. Most gene therapy approaches utilise viral vectors to deliver genes of interest. However, multiple proteins are often involved in disease processes and there is often a need to efficiently deliver more than one gene. Researchers have employed several strategies to accomplish this goal. When designing vectors to express multiple genes, there are several factors that need to be taken into account, including cell type, the activity of the protein of interest and subcellular protein localisation. In most cases, it is ideal for each protein to be expressed at comparable levels, a leading issue with traditional strategies for multigene expression. This review describes some of the techniques that have been used to express multiple genes, and will focus on the use of 2A peptides or 2A peptide-like sequences in the design of multicistronic vectors that may alleviate some of these issues.

There are so many existing classification methods from diverse fields including statistics, machine learning and pattern recognition. New methods have been invented constantly that claim superior performance over classical methods. It has become increasingly difficult for practitioners to choose the right kind of the methods for their applications. So this paper is not about the suggestion of another classification algorithm, but rather about conveying the message that some existing algorithms, if properly used, can lead to better solutions to some of the challenging real-world problems. This paper will look at some important problems in bioinformatics for which the best solutions were known and shows that improvement over those solutions can be achieved with a form of feed-forward neural networks by applying more advanced schemes for network supervised learning. The results are evaluated against those from other commonly used classifiers, such as the K nearest neighbours using cross validation, and their statistical significance is assessed using the nonparametric Wilcoxon test.

Fluorescent proteins are indispensable tools in the study of protein localisation in living cells. To study protein dynamics, however, it is necessary to selectively mark a sub-population of protein molecules. This is possible using Photoactivatable Green Fluorescent Protein (PA-GFP). In this article, the evolution and characteristics of PA-GFP are described together with the hardware and software solutions that allow researchers to easily perform PA-GFP experiments.

We present NetLoc, a novel diffusion Kernel-based Logistic Regression (KLR) algorithm for predicting protein subcellular localisation using four types of protein networks including physical PPI networks, genetic Protein-Protein Interaction (PPI) networks, mixed PPI networks and co-expression networks. NetLoc is applied to yeast protein localisation prediction. The results showed that protein networks can provide rich information for protein localisation prediction, achieving Area Under Curve (AUC) score of 0.93. We also showed that networks with high connectivity and high percentage of co-localised PPI lead to better prediction performance. Investigation showed that NetLoc is a very robust approach which can produce good performance (AUC = 0.75) only using 30% of original interactions and capable of producing overall accuracy greater than 0.5 only with 20% annotation coverage. Compared to the previous network feature based prediction algorithm which achieved AUC scores of 0.49 and 0.52 on the yeast PPI network, NetLoc achieved significantly better overall performance with the AUC of 0.74.

This paper introduces a combining classifier using two proposed precision indexes: precision index (PIN) and class specific precision index (PIC). Comparison of combining methods typically fails to consider high precision performance. This new combining method generates predictions with higher precision and recall than other methods. The proposed method is especially useful for efficient screening of predictions where actual verification is time consuming and costly. The performance of the proposed method is compared to majority voting, stacking, and cluster-selection for two well-known datasets: 1vowel recognition (Hastie et al., 2009) 2yeast protein localisation (Frank and Asuncion, 2010). The precisions obtained exceeded results previously reported for protein localisation data (Horton and Nakai, 1997; Chen, 2010) and for vowel recognition data (Hastie et al., 2009). A weighted precision index using PIC and PIN indexes outperformed all combining methods at higher precisions.

It is well recognised that there are pitfalls when defining the subcellular localisation of a protein with immunocytochemistry. Accurate protein localisation to particular cellular micro-architecture is crucial in defining its role within the cell. Huntingtin (HTT), the protein mutated in the neurodegenerative disorder Huntington's disease (HD) is a large protein of ill-defined function. Bearing little resemblance to other proteins, its function has been difficult to assign, therefore localising this protein with precision within the cell may provide further clues as to its normal and pathological function. Lack of consistency between methods employed in different studies has resulted in varying conclusions as to its subcellular localisation. This technical review investigates the effects that different immunocytological methods can have upon the apparent subcellular localisation of the huntingtin protein, and discusses the implications this may have.

Predicting the subcellular localisation of proteins is crucial for the determination of protein functions. In this paper, we present a computational method for protein localisation prediction. We start with a simple approach that predicts protein localisation based on Euclidian distance computed from residue composition. Then the performance is gradually improved by introducing a weighted Euclidian distance, including homologous information, and using feature selection. The final method achieves 90.3% accuracy in assigning proteins into five subcellular locations. Comparisons with CELLO, PSORT-B and P-CLASSIFIER show that our method outperforms the others.

TrypTag is a major resource which will contain the localisation of every protein encoded in the Trypanosoma brucei genome. Localisations of over 2000 proteins are already available via http://tryptag.org. This will be a transformative resource for enabling sophisticated analysis of conserved eukaryotic and parasite specific cell biology.

Microscopy-based localisation of proteins during malaria parasite (Plasmodium) invasion of the erythrocyte is widely used for tentative assignment of protein function. To date, however, imaging has been limited by the rarity of invasion events and the poor resolution available, given the micron size of the parasite, which leads to a lack of quantitative measures for definitive localisation. Here, using computational image analysis we have attempted to assign relative protein localisation during invasion using wide-field deconvolution microscopy. By incorporating three-dimensional information we present a detailed assessment of known parasite effectors predicted to function during entry but as yet untested or for which data are equivocal. Our method, termed longitudinal intensity profiling, resolves confusion surrounding the localisation of apical membrane antigen 1 (AMA1) at the merozoite-erythrocyte junction and predicts that the merozoite thrombospondin-related anonymous protein (MTRAP) is unlikely to play a direct role in the mechanics of entry, an observation supported with additional biochemical evidence. This approach sets a benchmark for imaging of complex micron-scale events and cautions against simplistic interpretations of small numbers of representative images for the assignment of protein function or prioritisation of candidates as therapeutic targets.

Adeno-associated virus (AAV) is a small DNA virus belonging to the family of the parvoviridae. AAV infects the human population, however no disease has been associated with this virus. On the contrary, AAV was reported to have oncosuppressive activities. The AAV genome contains two genes: the Rep gene encoding four non-structural proteins (Rep78, 68, 52 and 40) and the Cap gene encoding the three capsid proteins. Rep78 is implicated in transcription, replication and site-specific integration of the viral DNA. It has been shown to block the cell cycle in G1, G2 and S phase with a complete inhibition of DNA synthesis. To be able to induce such a strong cell cycle arrest, Rep78 affects several proteins implicated in the regulation of the cell cycle, such as the family of the cell division cycle 25 (Cdc25) phosphatases. Rep78 has been shown to inactivate Cdc25A by binding to it and preventing it from accessing its substrates. Cdc25B shares conserved domains with Cdc25A and moreover has an important role in cell cycle regulation, especially in giving the signal for entry into mitosis. Thus, in this work, the interaction between Cdc25B and Rep78 was examined in more detail. Rep78 was found to bind to Cdc25B and to alter its intracellular localisation. Cdc25B is nuclear, but has to migrate into the cytoplasm at the end of the G2 phase to activate proteins needed for the entry into mitosis. The expression of Rep78, which is nuclear, leads to the sequestration of Cdc25B in the nucleus. Moreover, Rep78 by interacting with Cdc25B not only changes its localisation, but also inhibits its phosphatase activity. Our model is that Rep78 interacts with Cdc25B and thus retains it in the nucleus. This sequestration of Cdc25B in the nucleus prevents it from activating the proteins in the cytoplasm needed to give the entry signal into mitosis, thus contributing to the G2/M arrest induced by Rep78. Moreover, the inhibition of Cdc25B phosphatase activity by Rep78 may also contribute to the cell cycle block. Rep78 also interacts with a number of cellular proteins implicated in DNA replication, DNA repair or recombination. Interactions between Rep78 and mini-chromosome maintenance 3 (MCM3), DNA polymerases α and δ, proliferating cell nuclear antigen (PCNA), Rad50 and Rad51 were identified in this work as well as possible interactions between Rep78 and Ataxia telangiectasia mutated (ATM) or Ataxia telangiectasia and Rad3 related (ATR) proteins. These interactions may contribute to AAV genome replication as well as its integration into the host DNA.