Dataset Information

Resolving the Complexity of Ubiquitin Networks.

ABSTRACT: Ubiquitination regulates nearly all cellular processes by coordinated activity of ubiquitin writers (E1, E2, and E3 enzymes), erasers (deubiquitinating enzymes) and readers (proteins that recognize ubiquitinated proteins by their ubiquitin-binding domains). By differentially modifying cellular proteome and by recognizing these ubiquitin modifications, ubiquitination machinery tightly regulates execution of specific cellular events in space and time. Dynamic and complex ubiquitin architecture, ranging from monoubiquitination, multiple monoubiquitination, eight different modes of homotypic and numerous types of heterogeneous polyubiquitin linkages, enables highly dynamic and complex regulation of cellular processes. We discuss available tools and approaches to study ubiquitin networks, including methods for the identification and quantification of ubiquitin-modified substrates, as well as approaches to quantify the length, abundance, linkage type and architecture of different ubiquitin chains. Furthermore, we also summarize the available approaches for the discovery of novel ubiquitin readers and ubiquitin-binding domains, as well as approaches to monitor and visualize activity of ubiquitin conjugation and deconjugation machineries. We also discuss benefits, drawbacks and limitations of available techniques, as well as what is still needed for detailed spatiotemporal dissection of cellular ubiquitination networks.

SUBMITTER: Kliza K

PROVIDER: S-EPMC7056813 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Resolving the Complexity of Ubiquitin Networks.

Kliza Katarzyna K Husnjak Koraljka K

Frontiers in molecular biosciences 20200227

Ubiquitination regulates nearly all cellular processes by coordinated activity of ubiquitin writers (E1, E2, and E3 enzymes), erasers (deubiquitinating enzymes) and readers (proteins that recognize ubiquitinated proteins by their ubiquitin-binding domains). By differentially modifying cellular proteome and by recognizing these ubiquitin modifications, ubiquitination machinery tightly regulates execution of specific cellular events in space and time. Dynamic and complex ubiquitin architecture, ra ...[more]

PMID: 32175328

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Project description:Network analysis has been used for many years in ecological research to analyze organismal associations, for example in food webs, plant-plant or plant-animal interactions. Although network analysis is widely applied in microbial ecology, only recently has it entered the realms of soil microbial ecology, shown by a rapid rise in studies applying co-occurrence analysis to soil microbial communities. While this application offers great potential for deeper insights into the ecological structure of soil microbial ecosystems, it also brings new challenges related to the specific characteristics of soil datasets and the type of ecological questions that can be addressed. In this Perspectives Paper we assess the challenges of applying network analysis to soil microbial ecology due to the small-scale heterogeneity of the soil environment and the nature of soil microbial datasets. We review the different approaches of network construction that are commonly applied to soil microbial datasets and discuss their features and limitations. Using a test dataset of microbial communities from two depths of a forest soil, we demonstrate how different experimental designs and network constructing algorithms affect the structure of the resulting networks, and how this in turn may influence ecological conclusions. We will also reveal how assumptions of the construction method, methods of preparing the dataset, and definitions of thresholds affect the network structure. Finally, we discuss the particular questions in soil microbial ecology that can be approached by analyzing and interpreting specific network properties. Targeting these network properties in a meaningful way will allow applying this technique not in merely descriptive, but in hypothesis-driven research. Analysing microbial networks in soils opens a window to a better understanding of the complexity of microbial communities. However, this approach is unfortunately often used to draw conclusions which are far beyond the scientific evidence it can provide, which has damaged its reputation for soil microbial analysis. In this Perspectives Paper, we would like to sharpen the view for the real potential of microbial co-occurrence analysis in soils, and at the same time raise awareness regarding its limitations and the many ways how it can be misused or misinterpreted.

Dataset Information

Resolving the Complexity of Ubiquitin Networks.

Publications

Resolving the Complexity of Ubiquitin Networks.

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