scholarly journals Exploiting Complex Fluorophore Interactions to Monitor Virus Capsid Disassembly

Molecules ◽  
2021 ◽  
Vol 26 (19) ◽  
pp. 5750
Author(s):  
Swarupa Chatterjee ◽  
Bram A. Schotpoort ◽  
Thieme Elbert ◽  
Jeroen J. L. M. Cornelissen ◽  
Mireille M. A. E. Claessens ◽  
...  
Keyword(s):  
Protein Complexes ◽  
Drug Carriers ◽  
Low Complexity ◽  
Biological Processes ◽  
Biological Functions ◽  
Protein Assemblies ◽  
Enveloped Viruses ◽  
Virus Capsids ◽  
New Strategy ◽  
Capsid Disassembly

Supramolecular protein complexes are the corner stone of biological processes; they are essential for many biological functions. Unraveling the interactions responsible for the (dis)assembly of these complexes is required to understand nature and to exploit such systems in future applications. Virus capsids are well-defined assemblies of hundreds of proteins and form the outer shell of non-enveloped viruses. Due to their potential as a drug carriers or nano-reactors and the need for virus inactivation strategies, assessing the intactness of virus capsids is of great interest. Current methods to evaluate the (dis)assembly of these protein assemblies are experimentally demanding in terms of instrumentation, expertise and time. Here we investigate a new strategy to monitor the disassembly of fluorescently labeled virus capsids. To monitor surfactant-induced capsid disassembly, we exploit the complex photophysical interplay between multiple fluorophores conjugated to capsid proteins. The disassembly of the capsid changes the photophysical interactions between the fluorophores, and this can be spectrally monitored. The presented data show that this low complexity method can be used to study and monitor the disassembly of supramolecular protein complexes like virus capsids. However, the range of labeling densities that is suitable for this assay is surprisingly narrow.

scholarly journals DISRUPTION OF PROTEIN COMPLEXES

2013 ◽  
Vol 11 (03) ◽  
pp. 1341008 ◽  
Author(s):  
GOLNAZ TAHERI ◽  
MAHNAZ HABIBI ◽  
LIMSOON WONG ◽  
CHANGIZ ESLAHCHI
Keyword(s):  
Protein Complexes ◽  
Biological Properties ◽  
Alternative Methods ◽  
Biological Processes ◽  
Biological Functions ◽  
Yeast Protein ◽  
Minimal Set ◽  
Connection Degree ◽  
Minimum Number ◽  
Molecular Machinery

Protein complexes are a cornerstone of many biological processes and, together, they form various types of molecular machinery that perform a vast array of biological functions. Different complexes perform different functions and, the same complex can perform very different functions that depend on a variety of factors. Thus disruption of protein complexes can be lethal to an organism. It is interesting to identify a minimal set of proteins whose removal would lead to a massive disruption of protein complexes and, to understand the biological properties of these proteins. A method is presented for identifying a minimum number of proteins from a given set of complexes so that a maximum number of these complexes are disrupted when these proteins are removed. The method is based on spectral bipartitioning. This method is applied to yeast protein complexes. The identified proteins participate in a large number of biological processes and functional modules. A large proportion of them are essential proteins. Moreover, removing these identified proteins causes a large number of the yeast protein complexes to break into two fragments of nearly equal size, which minimizes the chance of either fragment being functional. The method is also superior in these aspects to alternative methods based on proteins with high connection degree, proteins whose neighbors have high average degree, and proteins that connect to lots of proteins of high connection degree. Our spectral bipartitioning method is able to efficiently identify a biologically meaningful minimal set of proteins whose removal causes a massive disruption of protein complexes in an organism.

Methods for the Determination of the Purity of Exosomes

2020 ◽  
Vol 25 (42) ◽  
pp. 4464-4485 ◽  
Author(s):  
Katarzyna Kluszczyńska ◽  
Liliana Czernek ◽  
Wojciech Cypryk ◽  
Łukasz Pęczek ◽  
Markus Düchler
Keyword(s):  
Drug Transport ◽  
Biological Fluids ◽  
Drug Carriers ◽  
Biological Functions ◽  
Isolation And Purification ◽  
Pubmed Database ◽  
High Concentrations ◽  
Targeted Release

Background: Exosomes open exciting new opportunities for advanced drug transport and targeted release. Furthermore, exosomes may be used for vaccination, immunosuppression or wound healing. To fully utilize their potential as drug carriers or immune-modulatory agents, the optimal purity of exosome preparations is of crucial importance. Methods: Articles describing the isolation and purification of exosomes were retrieved from the PubMed database. Results: Exosomes are often separated from biological fluids containing high concentrations of proteins, lipids and other molecules that keep vesicle purification challenging. A great number of purification protocols have been published, however, their outcome is difficult to compare because the assessment of purity has not been standardized. In this review, we first give an overview of the generation and composition of exosomes, as well as their multifaceted biological functions that stimulated various medical applications. Finally, we describe various methods that have been used to purify small vesicles and to assess the purity of exosome preparations and critically compare the quality of these evaluation protocols. Conclusion: Combinations of various techniques have to be applied to reach the required purity and quality control of exosome preparations.

Comparison and Analysis of Computational Methods for Identifying N6 - methyladenosine Sites in Saccharomyces Cerevisiae

2020 ◽  
Vol 26 ◽  
Author(s):  
Pengmian Feng ◽  
Lijing Feng ◽  
Chaohui Tang
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Computational Methods ◽  
Computational Analysis ◽  
Computational Prediction ◽  
Experimental Methods ◽  
Biological Processes ◽  
Biological Functions ◽  
Precise Location ◽  
Future Directions ◽  
The Past

Background and Purpose: N 6 -methyladenosine (m6A) plays critical roles in a broad set of biological processes. Knowledge about the precise location of m6A site in the transcriptome is vital for deciphering its biological functions. Although experimental techniques have made substantial contributions to identify m6A, they are still labor intensive and time consuming. As good complements to experimental methods, in the past few years, a series of computational approaches have been proposed to identify m6A sites. Methods: In order to facilitate researchers to select appropriate methods for identifying m6A sites, it is necessary to give a comprehensive review and comparison on existing methods. Results: Since researches on m6A in Saccharomyces cerevisiae are relatively clear, in this review, we summarized recent progresses on computational prediction of m6A sites in S. cerevisiae and assessed the performance of existing computational methods. Finally, future directions of computationally identifying m6A sites were presented. Conclusion: Taken together, we anticipate that this review will provide important guides for computational analysis of m 6A modifications.

scholarly journals Every laboratory with a fluorescence microscope should consider counting molecules

2014 ◽  
Vol 25 (10) ◽  
pp. 1545-1548 ◽  
Author(s):  
Valerie C. Coffman ◽  
Jian-Qiu Wu
Keyword(s):  
Mathematical Modeling ◽  
Fluorescence Microscopy ◽  
Protein Complexes ◽  
The State ◽  
Fluorescence Microscope ◽  
Cellular Structures ◽  
Biological Processes ◽  
Protein Molecules ◽  
Parameter Values

Protein numbers in cells determine rates of biological processes, influence the architecture of cellular structures, reveal the stoichiometries of protein complexes, guide in vitro biochemical reconstitutions, and provide parameter values for mathematical modeling. The purpose of this essay is to increase awareness of methods for counting protein molecules using fluorescence microscopy and encourage more cell biologists to report these numbers. We address the state of the field in terms of utility and accuracy of the numbers reported and point readers to references for details of specific techniques and applications.

scholarly journals PPInfer: a Bioconductor package for inferring functionally related proteins using protein interaction networks

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 1969
Author(s):  
Dongmin Jung ◽  
Xijin Ge
Keyword(s):  
Protein Interaction ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Biological Processes ◽  
Bioconductor Package ◽  
Biological Functions ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Related Proteins

Interactions between proteins occur in many, if not most, biological processes. This fact has motivated the development of a variety of experimental methods for the identification of protein-protein interaction (PPI) networks. Leveraging PPI data available STRING database, we use network-based statistical learning methods to infer the putative functions of proteins from the known functions of neighboring proteins on a PPI network. This package identifies such proteins often involved in the same or similar biological functions. The package is freely available at the Bioconductor web site (http://bioconductor.org/packages/PPInfer/).

scholarly journals Deep6mA: A deep learning framework for exploring similar patterns in DNA N6-methyladenine sites across different species

2021 ◽  
Vol 17 (2) ◽  
pp. e1008767
Author(s):  
Zutan Li ◽  
Hangjin Jiang ◽  
Lingpeng Kong ◽  
Yuanyuan Chen ◽  
Kun Lang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Prediction Accuracy ◽  
Cross Validation ◽  
Biological Processes ◽  
Biological Functions ◽  
Learning Framework ◽  
Wide Range ◽  
Genomic Scale ◽  
Downstream Gene Expression ◽  
Fold Cross Validation

N6-methyladenine (6mA) is an important DNA modification form associated with a wide range of biological processes. Identifying accurately 6mA sites on a genomic scale is crucial for under-standing of 6mA’s biological functions. However, the existing experimental techniques for detecting 6mA sites are cost-ineffective, which implies the great need of developing new computational methods for this problem. In this paper, we developed, without requiring any prior knowledge of 6mA and manually crafted sequence features, a deep learning framework named Deep6mA to identify DNA 6mA sites, and its performance is superior to other DNA 6mA prediction tools. Specifically, the 5-fold cross-validation on a benchmark dataset of rice gives the sensitivity and specificity of Deep6mA as 92.96% and 95.06%, respectively, and the overall prediction accuracy is 94%. Importantly, we find that the sequences with 6mA sites share similar patterns across different species. The model trained with rice data predicts well the 6mA sites of other three species: Arabidopsis thaliana, Fragaria vesca and Rosa chinensis with a prediction accuracy over 90%. In addition, we find that (1) 6mA tends to occur at GAGG motifs, which means the sequence near the 6mA site may be conservative; (2) 6mA is enriched in the TATA box of the promoter, which may be the main source of its regulating downstream gene expression.

scholarly journals PPInfer: a Bioconductor package for inferring functionally related proteins using protein interaction networks

F1000Research ◽  
2018 ◽  
Vol 6 ◽  
pp. 1969 ◽  
Author(s):  
Dongmin Jung ◽  
Xijin Ge
Keyword(s):  
Protein Interaction ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Biological Processes ◽  
Bioconductor Package ◽  
Biological Functions ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Related Proteins

Interactions between proteins occur in many, if not most, biological processes. This fact has motivated the development of a variety of experimental methods for the identification of protein-protein interaction (PPI) networks. Leveraging PPI data available in the STRING database, we use a network-based statistical learning methods to infer the putative functions of proteins from the known functions of neighboring proteins on a PPI network. This package identifies such proteins often involved in the same or similar biological functions. The package is freely available at the Bioconductor web site (http://bioconductor.org/packages/PPInfer/).

scholarly journals Role of Main RNA Methylation in Hepatocellular Carcinoma: N6-Methyladenosine, 5-Methylcytosine, and N1-Methyladenosine

2021 ◽  
Vol 9 ◽  
Author(s):  
Yating Xu ◽  
Menggang Zhang ◽  
Qiyao Zhang ◽  
Xiao Yu ◽  
Zongzong Sun ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cellular Differentiation ◽  
Molecular Mechanisms ◽  
Gene Sequence ◽  
Epigenetic Modification ◽  
Biological Processes ◽  
Biological Functions ◽  
Rna Detection ◽  
Rna Methylation

RNA methylation is considered a significant epigenetic modification, a process that does not alter gene sequence but may play a necessary role in multiple biological processes, such as gene expression, genome editing, and cellular differentiation. With advances in RNA detection, various forms of RNA methylation can be found, including N6-methyladenosine (m6A), N1-methyladenosine (m1A), and 5-methylcytosine (m5C). Emerging reports confirm that dysregulation of RNA methylation gives rise to a variety of human diseases, particularly hepatocellular carcinoma. We will summarize essential regulators of RNA methylation and biological functions of these modifications in coding and noncoding RNAs. In conclusion, we highlight complex molecular mechanisms of m6A, m5C, and m1A associated with hepatocellular carcinoma and hope this review might provide therapeutic potent of RNA methylation to clinical research.

Non-histone methylation of SET7/9 and its biological functions

2021 ◽  
Vol 16 ◽  
Author(s):  
Lili Gao ◽  
Weiping Yu ◽  
Peng Song ◽  
Qing Li
Keyword(s):  
Cancer Progression ◽  
Histone Methylation ◽  
Biological Processes ◽  
Biological Functions ◽  
Set Domain ◽  
Cell Cycle Protein ◽  
Cardiac Morphogenesis ◽  
Histone 3 ◽  
Development Methods ◽  
Human Carotid

Background: (su(var)-3-9,enhancer-of-zeste,trithorax) domain-containing protein 7/9 (SET7/9) is a member of the protein lysine methyltransferases (PLMTs or PKMTs) family. It contains a SET domain. Recent studies demonstrate that SET7/9 methylates both lysine 4 of histone 3 (H3-K4) and lysine(s) of non-histone proteins, including transcription factors, tumor suppressors, and membrane-associated receptors. Objective: This article mainly reviews the non-histone methylation effects of SET7/9 and its functions in tumorigenesis and development. Methods: PubMed was screened for this information. Results: SET7/9 plays a key regulatory role in various biological processes such as cell proliferation, transcription regulation, cell cycle, protein stability, cardiac morphogenesis, and development. In addition, SET7/9 is involved in the pathogenesis of hair loss, breast cancer progression, human carotid plaque atherosclerosis, chronic kidney disease, diabetes, obesity, ovarian cancer, prostate cancer, hepatocellular carcinoma, and pulmonary fibrosis. Conclusion: SET7/9 is an important methyltransferase, which can catalyze the methylation of a variety of proteins. Its substrates are closely related to the occurrence and development of tumors.

scholarly journals In Vitro Anticancer Properties of Copper Metallodendrimers

Biomolecules ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 155 ◽  
Author(s):  
Hołota ◽  
Magiera ◽  
Michlewska ◽  
Kubczak ◽  
del Olmo ◽  
...  
Keyword(s):  
Fluorescence Anisotropy ◽  
Drug Carriers ◽  
Haemolytic Activity ◽  
Surface Groups ◽  
Biological Processes ◽  
Normal Cells ◽  
Anticancer Properties ◽  
Transmission Electron ◽  
Anti Cancer

Newly synthesized carbosilane copper dendrimers (CCD) with chloride and nitrate surface groups seem to be good candidates to be used as gene and drug carriers in anti-cancer therapy, due to their properties such as size and surface charge. Copper attached to the nanoparticles is an important element of many biological processes and recently their anti-cancer properties have been widely examined. Zeta size and potential, transmission electron microscopy (TEM), circular dichroism (CD), analysis of haemolytic activity, and fluorescence anisotropy techniques were used to characterize copper dendrimers. Additionally, their cytotoxic properties toward normal (PBMC) and cancer (1301; HL-60) cells were examined. All tested dendrimers were more cytotoxic against cancer cells in comparison with normal cells.

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