Localization Signals In Proteins Research Articles

Digitally predicting protein localization and manipulating protein activity in fluorescence images using 4D reslicing GAN.

While multi-channel fluorescence microscopy is a vital imaging method in biological studies, the number of channels that can be imaged simultaneously is limited by technical and hardware limitations such as emission spectra cross-talk. One solution is using deep neural networks to model the localization relationship between two proteins so that the localization of one protein can be digitally predicted. Furthermore, the input and predicted localization implicitly reflect the modeled relationship. Accordingly, observing the response of the prediction via manipulating input localization could provide an informative way to analyze the modeled relationships between the input and the predicted proteins. We propose a protein localization prediction (PLP) method using a cGAN named 4D Reslicing Generative Adversarial Network (4DR-GAN) to digitally generate additional channels. 4DR-GAN models the joint probability distribution of input and output proteins by simultaneously incorporating the protein localization signals in four dimensions including space and time. Because protein localization often correlates with protein activation state, based on accurate PLP, we further propose two novel tools: digital activation (DA) and digital inactivation (DI) to digitally activate and inactivate a protein, in order to observing the response of the predicted protein localization. Compared with genetic approaches, these tools allow precise spatial and temporal control. A comprehensive experiment on six pairs of proteins shows that 4DR-GAN achieves higher-quality PLP than Pix2Pix, and the DA and DI responses are consistent with the known protein functions. The proposed PLP method helps simultaneously visualize additional proteins, and the developed DA and DI tools provide guidance to study localization-based protein functions. The open-source code is available at https://github.com/YangJiaoUSA/4DR-GAN. Supplementary data are available at Bioinformatics online.

Nuclear dynamics: Formation of bodies and trafficking in plant nuclei.

The existence of the nucleus distinguishes prokaryotes and eukaryotes. Apart from containing most of the genetic material, the nucleus possesses several nuclear bodies composed of protein and RNA molecules. The nucleus is separated from the cytoplasm by a double membrane, regulating the trafficking of molecules in- and outwards. Here, we investigate the composition and function of the different plant nuclear bodies and molecular clues involved in nuclear trafficking. The behavior of the nucleolus, Cajal bodies, dicing bodies, nuclear speckles, cyclophilin-containing bodies, photobodies and DNA damage foci is analyzed in response to different abiotic stresses. Furthermore, we research the literature to collect the different protein localization signals that rule nucleocytoplasmic trafficking. These signals include the different types of nuclear localization signals (NLSs) for nuclear import, and the nuclear export signals (NESs) for nuclear export. In contrast to these unidirectional-movement signals, the existence of nucleocytoplasmic shuttling signals (NSSs) allows bidirectional movement through the nuclear envelope. Likewise, nucleolar signals are also described, which mainly include the nucleolar localization signals (NoLSs) controlling nucleolar import. In contrast, few examples of nucleolar export signals, called nucleoplasmic localization signals (NpLSs) or nucleolar export signals (NoESs), have been reported. The existence of consensus sequences for these localization signals led to the generation of prediction tools, allowing the detection of these signals from an amino acid sequence. Additionally, the effect of high temperatures as well as different post-translational modifications in nuclear and nucleolar import and export is discussed.

NES-REBS: A novel nuclear export signal prediction method using regular expressions and biochemical properties.

A nuclear export signal (NES) is a protein localization signal, which is involved in binding of cargo proteins to nuclear export receptor, thus contributes to regulate localization of cellular proteins. Consensus sequences of NES have been used to detect NES from protein sequences, but suffer from poor predictive power. Some recent peering works were proposed to use biochemical properties of experimental verified NES to refine NES candidates. Those methods can achieve high prediction rates, but their execution time will become unacceptable for large-scale NES searching if too much properties are involved. In this work, we developed a novel computational approach, named NES-REBS, to search NES from protein sequences, where biochemical properties of experimental verified NES, including secondary structure and surface accessibility, are utilized to refine NES candidates obtained by matching popular consensus sequences. We test our method by searching 262 experimental verified NES from 221 NES-containing protein sequences. It is obtained that NES-REBS runs in 2-3[Formula: see text]mins and performs well by achieving precision rate 47.2% and sensitivity 54.6%.

Metabolic Engineering of Probiotic Saccharomyces boulardii.

Saccharomyces boulardiiis a probiotic yeast that has been used for promoting gut health as well as preventing diarrheal diseases. This yeast not only exhibits beneficial phenotypes for gut health but also can stay longer in the gut than Saccharomyces cerevisiae Therefore, S. boulardiiis an attractive host for metabolic engineering to produce biomolecules of interest in the gut. However, the lack of auxotrophic strains with defined genetic backgrounds has hampered the use of this strain for metabolic engineering. Here, we report the development of well-defined auxotrophic mutants (leu2,ura3,his3, and trp1) through clustered regularly interspaced short palindromic repeat (CRISPR)-Cas9-based genome editing. The resulting auxotrophic mutants can be used as a host for introducing various genetic perturbations, such as overexpression or deletion of a target gene, using existing genetic tools forS. cerevisiae We demonstrated the overexpression of a heterologous gene (lacZ), the correct localization of a target protein (red fluorescent protein) into mitochondria by using a protein localization signal, and the introduction of a heterologous metabolic pathway (xylose-assimilating pathway) in the genome ofS. boulardii We further demonstrated that human lysozyme, which is beneficial for human gut health, could be secreted by S. boulardii Our results suggest that more sophisticated genetic perturbations to improveS. boulardii can be performed without using a drug resistance marker, which is a prerequisite for in vivo applications using engineeredS. boulardii.

Optogenetic characterization methods overcome key challenges in synthetic and systems biology.

Systems biologists aim to understand how organism-level processes, such as differentiation and multicellular development, are encoded in DNA. Conversely, synthetic biologists aim to program systems-level biological processes, such as engineered tissue growth, by writing artificial DNA sequences. To achieve their goals, these groups have adapted a hierarchical electrical engineering framework that can be applied in the forward direction to design complex biological systems or in the reverse direction to analyze evolved networks. Despite much progress, this framework has been limited by an inability to directly and dynamically characterize biological components in the varied contexts of living cells. Recently, two optogenetic methods for programming custom gene expression and protein localization signals have been developed and used to reveal fundamentally new information about biological components that respond to those signals. This basic dynamic characterization approach will be a major enabling technology in synthetic and systems biology.

Genome-wide computational approach for the prediction of duplications generating protein localization signals

Investigating the possible generation of motifs accountable for aberrant protein dislocation subsequent to the rise of short tandem duplications is interesting, given the pathogenic potential of this mechanism, as demonstrated in diseases such adult myeloid leukemia (AML). In this paper we introduce a new computational method for predicting genomic points which, after hypothetical mutation events such as micro-duplications, might encode molecular patterns such as localization or export signals. The proposed framework allows to study motifs of unconstrained length defined as regular expressions at a genome-wide level, providing an in silico platform capable of analyzing the potential effect of duplications on abnormal cellular localization.

Prediction of leucine-rich nuclear export signal containing proteins with NESsential

The classical nuclear export signal (NES), also known as the leucine-rich NES, is a protein localization signal often involved in important processes such as signal transduction and cell cycle regulation. Although 15 years has passed since its discovery, limited structural information and high sequence diversity have hampered understanding of the NES. Several consensus sequences have been proposed to describe it, but they suffer from poor predictive power. On the other hand, the NetNES server provides the only computational method currently available. Although these two methods have been widely used to attempt to find the correct NES position within potential NES-containing proteins, their performance has not yet been evaluated on the basic task of identifying NES-containing proteins. We propose a new predictor, NESsential, which uses sequence derived meta-features, such as predicted disorder and solvent accessibility, in addition to primary sequence. We demonstrate that it can identify promising NES-containing candidate proteins (albeit at low coverage), but other methods cannot. We also quantitatively demonstrate that predicted disorder is a useful feature for prediction and investigate the different features of (predicted) ordered versus disordered NES’s. Finally, we list 70 recently discovered NES-containing proteins, doubling the number available to the community.

Lentiviral vector-based assay system for quantitative detection of intracellular translocations of recombinant proteins

An enzymatic assay system is described that allows quantitative localization within different cellular structures of recombinant proteins. The system is based on alpha-complementation of beta-galactosidase. The large omega-fragment of beta-galactosidase is expressed in predefined cellular structures with the aid of attached protein localization signals. The obtained reporter cell lines are used for the introduction of a second construct that expresses a protein of study fused with a shorter alpha-fragment of beta-galactosidase. Physical proximity of the two recombinant proteins carrying beta-galactosidase fragments results in reconstitution of an active enzyme, and the activity can be measured in a plate reader. The recombinant constructs are based on lentiviral vectors, which allows rapid and efficient introduction of recombinant proteins into cells by infection with stocks of lentiviral particles. The efficiency of the system is demonstrated with transcriptional factor FOXO3A, which is shuttling between cytoplasm and nuclei in model colon carcinoma cell line RKO.

Analysis of Nuclear Localization Signals Using a Green Fluorescent Protein-Fusion Protein Library

We describe here an efficient method for identifying intracellular localization signals in proteins with stereospecific intracellular localizations in culture cells. The method involves rapid fluorescence screening of cells transfected with a cDNA library in which cDNAs are fused to the gene encoding the Aequorea victoria green fluorescent protein (GFP). We analyzed nuclear localization and nuclear localization signals (NLSs) in a model application of this method. As a result, we identified classical NLSs in 75% of nuclear localized proteins. We identified some novel NLS candidates among the classical NLS-negative sequences whose nuclear localization was also identified in another cell line and with other molecular tag sequences. This method will be useful for identifying intracellular localization signals and for more detailed analysis of intracellular architecture.

Partial Characterization of the Streptomyces lividans xlnB Promoter and Its Use for Expression of a Thermostable Xylanase from Thermotoga maritima

Xylanase activity assays were used to screen a Streptomyces coelicolor genomic library in Escherichia coli, and a xylanase gene that is 99% identical to the xylanase B gene (xlnB) of S. lividans (GenBank accession no. M64552) was identified. The promoter region of this gene was identified by using a transcriptional fusion between the upstream region of the S. coelicolor xlnB gene and the xylE reporter gene. Transcription from the xlnB promoter was found to be induced by xylan and repressed by glucose. A single apparent transcription start site was identified by both primer extension analysis and in vitro run off transcription assays. Analysis of deletions of the promoter identified a region required for glucose repression. By using the transcriptional and protein localization signals of the Streptomyces xlnB gene, an in-frame translational fusion between the end of the xlnB signal sequence and the ATG of the Thermotoga maritima xynA gene was constructed. The xynA gene encodes a thermostable xylanase that has been demonstrated to be useful in the bleaching of Kraft pulp. The xlnB-xynA gene fusion was expressed in Streptomyces, and the activity of the protein produced was thermostable and was localized to the supernatant fraction of harvested cells.

Localization signals in proteins internalized from the cell surface.

Localization signals in proteins internalized from the cell surface.

Biophysical studies of signal peptides: Implications for signal sequence functions and the involvement of lipid in protein export

This review discusses efforts to understand the mode of action of signal sequences by biophysical study of synthetic peptides corresponding to these protein localization signals. On the basis of reports from several laboratories, it is now clear that signal peptides may adopt a variety of conformations, depending on their local environment. In membrane-mimetic systems like detergent micelles or lipid vesicles, they have a high tendency to form alpha helices. Ability to take up a helical conformation appears to be required at some point in the function of a signal sequence, since some peptides corresponding to export-defective signal sequences display reduced helical potential. By contrast, functional signal sequences share a high capacity to adopt alpha helices. High affinity for organized lipid assemblies, like monolayers or vesicles, is also a property of functional signal sequences. This correlation suggests a role for direct interaction of signal sequences with the lipids of the cytoplasmic membrane in vivo. Supporting this role are studies of the influence of signal peptides on lipid structure, which reveal an ability of these peptides to perturb lipid packing and to alter the phase state of the lipids. Insertion of the signal sequence in vivo could substantially reduce the barrier for translocation of the mature chain. Lastly, synthetic signal peptides have been added to native membranes and found to inhibit translocation of precursor proteins. This approach bridges the biophysical and the biochemical aspects of protein export and promises to shed light on the functional correlates of the properties and interactions observed in model systems.