Interaction between TATA-Binding Protein (TBP) and Multiprotein Bridging Factor-1 (MBF1) from the Filamentous Insect Pathogenic Fungus Beauveria bassiana

Transcription Cofactor CsMBF1c Enhances Heat Tolerance of Cucumber and Interacts with Heat-Related Proteins CsNFYA1 and CsDREB2

Multiprotein bridging factor 1 (MBF1) is a very important transcription factor (TF) in plants, whose members influence numerous defense responses. Our study found that MBF1c in Cucurbitaceae was highly conserved. CsMBF1c expression was induced by temperature, salt stress, and abscisic acid (ABA) in cucumber. Overexpressed CsMBF1c enhanced the heat resistance of a cucumber, and the Csmbf1c mutant showed decreased resistance to high temperatures (HTs). CsMBF1c played an important role in stabilizing the photosynthetic system of cucumber under HT, and its expression was significantly associated with heat-related TFs and genes related to protein processing in the endoplasmic reticulum (ER). Protein interaction showed that CsMBF1c interacted with dehydration-responsive element binding protein 2 (CsDREB2) and nuclear factor Y A1 (CsNFYA1). Overexpression of CsNFYA1 in Arabidopsis improved the heat resistance. Transcriptional activation of CsNFYA1 was elevated by CsMBF1c. Therefore, CsMBF1c plays an important regulatory role in cucumber's resistance to high temperatures.

Function Analysis of MBF1, a Factor Involved in the Response to Amino Acid Starvation and Virulence in Candida albicans

Candida albicans is a commensal of human mucosae, but also one of the most common fungal pathogens of humans. Systemic infections caused by this fungus, mostly affecting immunocompromised patients, are associated to fatality rates as high as 50% despite the available treatments. In order to improve this situation, it is necessary to fully understand how C. albicans is able to cause disease and how it copes with the host defenses. Our previous studies have revealed the importance of the C. albicans gene MBF1 in virulence and ability to colonize internal organs of mammalian and insect hosts. MBF1 encodes a putative transcriptional regulator, and as such it likely has an impact in the regulation of C. albicans gene expression during host infection. Here, recent advances in RNA-seq technologies were used to obtain a detailed analysis of the impact of MBF1 on C. albicans gene expression both in vitro and during infection. MBF1 was involved in the regulation of several genes with a role in glycolysis and response to stress, particularly to nutritional stress. We also investigated whether an interaction existed between MBF1 and GCN4, a master regulator of response to starvation, and found that both genes were needed for resistance to amino acid starvation, suggesting some level of interaction between the two. Reinforcing this idea, we showed that the proteins encoded by both genes could interact. Consistent with the role of MBF1 in virulence, we also established that GCN4 was necessary for virulence in the mouse model of systemic infection as well as in the Galleria mellonella infection model.

Study on Interaction Between TATA-Box Binding Protein (TBP), TATA-Box and Multiprotein Bridging Factor 1(MBF1) in Beauveria bassiana by Graphene-Based Electrochemical Biosensors

The regulation of transcription level is an important step in gene expression process. Beauveria bassiana is a broad-spectrum insecticidal fungi widely used in the biologic control of arthropod. The regulation of its transcription level is a multilevel complex process. Multiprotein bridging factor 1(MBF1) is a transcriptional co-activator that bridges sequence-specific activators and the TATA-box binding protein(TBP), Little is known about the interaction between MBF1, TBP, and TBP binding to DNA(TATA-sequences)in filamentous fungi of Beauveria bassiana, The binding of TBP to TATA-box and TBP to MBF1 was investigated via electrochemical biosensor. Graphene oxide has an electronic mobility that is unattainable for any metal, so it will be highly sensitive as a test electrode. Hence, we developed a simple, sensitive and specific sensor based on an TBP probe and graphene oxide that successfully detected the interaction of TBP and TATA-box or MBF1. From the electrochemical impedance spectroscopy (EIS), we find that the radius will increase when adding TATA-box or MBF1 buffer to the modified TBP protein electrode. When adding no TATA-box or no MBF1, the radius is relatively unchanged. The interaction between TBP and TATA-box or MBF1 was proved based on the results. These data confirmed the specificity of the interactions, (1) our developed graphene-based electrochemical biosensor can be used for monitoring the interaction between TBP and TATA-box or MBF1, (2) TBP can bind to TATA-box, (3) TBP can bind to MBF1, and (4) TBP mediates the interactions of MBF1 to DNA. Therefore, this work provided a label-free, low-cost and simple detection method for the complex process of eukaryotic gene transcription regulation.

Overexpression of HbMBF1a, encoding multiprotein bridging factor 1 from the halophyte Hordeum brevisubulatum, confers salinity tolerance and ABA insensitivity to transgenic Arabidopsis thaliana

HbMBF1a was isolated and characterized in H. brevisubulatum, and overexpressed HbMBF1a could enhance the salt tolerance and ABA insensitivity in Arabidopsis thaliana. The transcript levels of stress-responsive genes were significantly increased in the transgenic lines under salt and ABA conditions. Salinity is an abiotic stress that considerably affects plant growth, yield, and distribution. Hordeum brevisubulatum is a halophyte that evolved to become highly tolerant to salinity. Multiprotein bridging factor 1 (MBF1) is a transcriptional coactivator and an important regulator of stress tolerance. In this study, we isolated and characterized HbMBF1a based on the transcriptome data of H. brevisubulatum grown under saline conditions. We overexpressed HbMBF1a in Arabidopsis thaliana and compared the phenotypes of the transgenic lines and the wild-type in response to stresses. The results indicated that HbMBF1a expression was induced by salt and ABA treatments during the middle and late stages. The overexpression of HbMBF1a in A. thaliana resulted in enhanced salt tolerance and ABA insensitivity. More specifically, the enhanced salt tolerance manifested as the increased seed germination and seedling growth and development. Similarly, under ABA treatments, the cotyledon greening rate and seedling root length were higher in the HbMBF1a-overexpressing lines, suggesting the transgenic plants were better adapted to high exogenous ABA levels. Furthermore, the transcript levels of stress-responsive genes were significantly increased in the transgenic lines under salt and ABA conditions. Thus, HbMBF1a is a positive regulator of salt and ABA responses, and the corresponding gene may be useful for producing transgenic plants that are salt tolerant and/or ABA insensitive, with few adverse effects. This study involved a comprehensive analysis of HbMBF1a. The results may provide the basis and insight for the application of MBF1 family genes for developing stress-tolerant crops.

Post hoc support vector machine learning for impedimetric biosensors based on weak protein-ligand interactions

Impedimetric biosensors for measuring small molecules based on weak/transient interactions between bioreceptors and target analytes are a challenge for detection electronics, particularly in field studies or in the analysis of complex matrices. Protein-ligand binding sensors have enormous potential for biosensing, but achieving accuracy in complex solutions is a major challenge. There is a need for simple post hoc analytical tools that are not computationally expensive, yet provide near real time feedback on data derived from impedance spectra. Here, we show the use of a simple, open source support vector machine learning algorithm for analyzing impedimetric data in lieu of using equivalent circuit analysis. We demonstrate two different protein-based biosensors to show that the tool can be used for various applications. We conclude with a mobile phone-based demonstration focused on the measurement of acetone, an important biomarker related to the onset of diabetic ketoacidosis. In all conditions tested, the open source classifier was capable of performing as well as, or better, than the equivalent circuit analysis for characterizing weak/transient interactions between a model ligand (acetone) and a small chemosensory protein derived from the tsetse fly. In addition, the tool has a low computational requirement, facilitating use for mobile acquisition systems such as mobile phones. The protocol is deployed through Jupyter notebook (an open source computing environment available for mobile phone, tablet or computer use) and the code was written in Python. For each of the applications, we provide step-by-step instructions in English, Spanish, Mandarin and Portuguese to facilitate widespread use. All codes were based on scikit-learn, an open source software machine learning library in the Python language, and were processed in Jupyter notebook, an open-source web application for Python. The tool can easily be integrated with the mobile biosensor equipment for rapid detection, facilitating use by a broad range of impedimetric biosensor users. This post hoc analysis tool can serve as a launchpad for the convergence of nanobiosensors in planetary health monitoring applications based on mobile phone hardware.