A yeast one-hybrid system to screen for methylated DNA-binding proteins

Dimerization choice and alternative functions of ZBTB transcription factors

Zinc Finger DNA-binding domain-containing proteins are the most populous family among eukaryotic transcription factors. Among these, members of the BTB domain-containing ZBTB sub-family are mostly known for their transcriptional repressive functions. In this Viewpoint article, we explore molecular mechanisms that potentially diversify the function of ZBTB proteins based on their homo and heterodimerization, alternative splicing and post-translational modifications. We describe how the BTB domain is as much a scaffold for the assembly of co-repressors, as a domain that regulates protein stability. We highlight another mechanism that regulates ZBTB protein stability: phosphorylation in the zinc finger domain. We explore the non-transcriptional, structural roles of ZBTB proteins and highlight novel findings that describe the ability of ZBTB proteins to associate with poly adenosine ribose in the nucleus during the DNA damage response. Herein, we discuss the contribution of BTB domain scaffolds to the formation of transcriptional repressive complexes, to chromosome compartmentalization and their non-transcriptional, purely structural functions in the nucleus.

DBPMod: a supervised learning model for computational recognition of DNA-binding proteins in model organisms

DNA-binding proteins (DBPs) play critical roles in many biological processes, including gene expression, DNA replication, recombination and repair. Understanding the molecular mechanisms underlying these processes depends on the precise identification of DBPs. In recent times, several computational methods have been developed to identify DBPs. However, because of the generic nature of the models, these models are unable to identify species-specific DBPs with higher accuracy. Therefore, a species-specific computational model is needed to predict species-specific DBPs. In this paper, we introduce the computational DBPMod method, which makes use of a machine learning approach to identify species-specific DBPs. For prediction, both shallow learning algorithms and deep learning models were used, with shallow learning models achieving higher accuracy. Additionally, the evolutionary features outperformed sequence-derived features in terms of accuracy. Five model organisms, including Caenorhabditis elegans, Drosophila melanogaster, Escherichia coli, Homo sapiens and Mus musculus, were used to assess the performance of DBPMod. Five-fold cross-validation and independent test set analyses were used to evaluate the prediction accuracy in terms of area under receiver operating characteristic curve (auROC) and area under precision-recall curve (auPRC), which was found to be ~89-92% and ~89-95%, respectively. The comparative results demonstrate that the DBPMod outperforms 12 current state-of-the-art computational approaches in identifying the DBPs for all five model organisms. We further developed the web server of DBPMod to make it easier for researchers to detect DBPs and is publicly available at https://iasri-sg.icar.gov.in/dbpmod/. DBPMod is expected to be an invaluable tool for discovering DBPs, supplementing the current experimental and computational methods.

PlDBPred: a novel computational model for discovery of DNA binding proteins in plants

DNA-binding proteins (DBPs) play crucial roles in numerous cellular processes including nucleotide recognition, transcriptional control and the regulation of gene expression. Majority of the existing computational techniques for identifying DBPs are mainly applicable to human and mouse datasets. Even though some models have been tested on Arabidopsis, they produce poor accuracy when applied to other plant species. Therefore, it is imperative to develop an effective computational model for predicting plant DBPs. In this study, we developed a comprehensive computational model for plant specific DBPs identification. Five shallow learning and six deep learning models were initially used for prediction, where shallow learning methods outperformed deep learning algorithms. In particular, support vector machine achieved highest repeated 5-fold cross-validation accuracy of 94.0% area under receiver operating characteristic curve (AUC-ROC) and 93.5% area under precision recall curve (AUC-PR). With an independent dataset, the developed approach secured 93.8% AUC-ROC and 94.6% AUC-PR. While compared with the state-of-art existing tools by using an independent dataset, the proposed model achieved much higher accuracy. Overall results suggest that the developed computational model is more efficient and reliable as compared to the existing models for the prediction of DBPs in plants. For the convenience of the majority of experimental scientists, the developed prediction server PlDBPred is publicly accessible at https://iasri-sg.icar.gov.in/pldbpred/.The source code is also provided at https://iasri-sg.icar.gov.in/pldbpred/source_code.php for prediction using a large-size dataset.

The specific MYB binding sites bound by TaMYB in the GAPCp2/3 promoters are involved in the drought stress response in wheat

BACKGROUND

Drought stress is one of the major abiotic stresses that affects plant growth and productivity. The GAPCp genes play important roles in drought stress tolerance in multiple species. The aim of this experiment was to identify the core cis-regulatory elements that may respond to drought stress in the GAPCp2 and GAPCp3 promoter sequences.

RESULTS

In this study, the promoters of GAPCp2 and GAPCp3 were cloned. The promoter activities were significantly improved under abiotic stress via regulation of Rluc reporter gene expression, while promoter sequence analysis indicated that these fragments were not almost identical. In transgenic Arabidopsis with the expression of the GUS reporter gene under the control of one of these promoters, the activities of GUS were strong in almost all tissues except the seeds, and the activities were induced after abiotic stress. The yeast one-hybrid system and EMSA demonstrated that TaMYB bound TaGAPCp2P/3P. By analyzing different 5' deletion mutants of these promoters, it was determined that TaGAPCp2P (- 1312~ - 528) and TaGAPCp3P (- 2049~ - 610), including the MYB binding site, contained enhancer elements that increased gene expression levels under drought stress. We used an effector and a reporter to co-transform tobacco and found that TaMYB interacted with the specific MYB binding sites of TaGAPCp2P (- 1197~ - 635) and TaGAPCp3P (- 1456~ - 1144 and - 718~ - 610) in plant cells. Then, the Y1H system and EMSA assay demonstrated that these MYB binding sites in TaGAPCp2P (- 1135 and - 985) and TaGAPCp3P (- 1414 and - 665) were the target cis-elements of TaMYB. The deletion of the specific MYB binding sites in the promoter fragments significantly restrained the drought response, and these results confirmed that these MYB binding sites (AACTAAA/C) play vital roles in improving the transcription levels under drought stress. The results of qRT-PCR in wheat protoplasts transiently overexpressing TaMYB indicated that the expression of TaGAPCp2/3 induced by abiotic stress was upregulated by TaMYB.

CONCLUSION

The MYB binding sites (AACTAAA/C) in TaGAPCp2P/3P were identified as the key cis-elements for responding to drought stress and were bound by the transcription factor TaMYB.

Epigenetic mechanisms in microbial members of the human microbiota: current knowledge and perspectives

The human microbiota and epigenetic processes have both been shown to play a crucial role in health and disease. However, there is extremely scarce information on epigenetic modulation of microbiota members except for a few pathogens. Mainly DNA adenine methylation has been described extensively in modulating the virulence of pathogenic bacteria in particular. It would thus appear likely that such mechanisms are widespread for most bacterial members of the microbiota. This review will present briefly the current knowledge on epigenetic processes in bacteria, give examples of known methylation processes in microbial members of the human microbiota and summarize the knowledge on regulation of host epigenetic processes by the human microbiota.

The power of the yeast two-hybrid system in the identification of novel drug targets: building and modulating PPP1 interactomes

Since the description of the yeast two-hybrid (Y2H) method, it has become more and more evident that it is the most commonly used method to identify protein-protein interactions (PPIs). The improvements in the original Y2H methodology in parallel with the idea that PPIs are promising drug targets, offer an excellent opportunity to apply the principles of this molecular biology technique to the pharmaceutical field. Additionally, the theoretical developments in the networks field make PPI networks very useful frameworks that facilitate many discoveries in biomedicine. This review highlights the relevance of Y2H in the determination of PPIs, specifically phosphoprotein phosphatase 1 interactions, and its possible outcomes in pharmaceutical research.

Detecting protein-DNA interactions using a modified yeast one-hybrid system

The yeast one-hybrid (Y1H) system has been among the methods of choice to detect protein-DNA interactions. However, conventional Y1H systems with a single auxotrophic reporter gene often suffer from high incidence of false positives to demonstrate a limited power in large-scale screenings. Here we describe a refined Y1H system that uses two independent bait sequences, each controlling a distinct reporter gene integrated in the host genome. With these modifications and a method of targeted DNA methylation, we succeeded in efficient isolation of clones for methylated DNA-binding proteins from mammalian cDNA libraries.

Diversity in genetic in vivo methods for protein-protein interaction studies: from the yeast two-hybrid system to the mammalian split-luciferase system

The yeast two-hybrid system pioneered the field of in vivo protein-protein interaction methods and undisputedly gave rise to a palette of ingenious techniques that are constantly pushing further the limits of the original method. Sensitivity and selectivity have improved because of various technical tricks and experimental designs. Here we present an exhaustive overview of the genetic approaches available to study in vivo binary protein interactions, based on two-hybrid and protein fragment complementation assays. These methods have been engineered and employed successfully in microorganisms such as Saccharomyces cerevisiae and Escherichia coli, but also in higher eukaryotes. From single binary pairwise interactions to whole-genome interactome mapping, the self-reassembly concept has been employed widely. Innovative studies report the use of proteins such as ubiquitin, dihydrofolate reductase, and adenylate cyclase as reconstituted reporters. Protein fragment complementation assays have extended the possibilities in protein-protein interaction studies, with technologies that enable spatial and temporal analyses of protein complexes. In addition, one-hybrid and three-hybrid systems have broadened the types of interactions that can be studied and the findings that can be obtained. Applications of these technologies are discussed, together with the advantages and limitations of the available assays.

Advances in the study of protein-DNA interaction

Protein-DNA interaction plays an important role in many biological processes. The classical methods and the novel technologies advanced have been developed for the interaction of protein-DNA. Recent developments of these methods and research achievements have been reviewed in this paper.