Spatiotemporal dynamics of Spc105 regulates the assembly of the Drosophila kinetochore

The formation of kinetochores shortly before each cell division is a prerequisite for proper chromosome segregation. The synchronous mitoses of Drosophila syncytial embryos have provided an ideal in vivo system to follow kinetochore assembly kinetics and so address the question of how kinetochore formation is regulated. We found that the nuclear exclusion of the Spc105/KNL1 protein during interphase prevents precocious assembly of the Mis12 complex. The nuclear import of Spc105 in early prophase and its immediate association with the Mis12 complex on centromeres are thus the first steps in kinetochore assembly. The cumulative kinetochore levels of Spc105 and Mis12 complex then determine the rate of Ndc80 complex recruitment commencing only after nuclear envelope breakdown. The carboxy-terminal part of Spc105 directs its nuclear import and is sufficient for the assembly of all core kinetochore components and CENP-C, when localized ectopically to centrosomes. Super-resolution microscopy shows that carboxy-terminus of Spc105 lies at the junction of the Mis12 and Ndc80 complexes on stretched kinetochores. Our study thus indicates that physical accessibility of kinetochore components plays a crucial role in the regulation of Drosophila kinetochore assembly and leads us to a model in which Spc105 is a licensing factor for its onset

DAPPER: a data-mining resource for protein-protein interactions.

BACKGROUND: The identification of interaction networks between proteins and complexes holds the promise of offering novel insights into the molecular mechanisms that regulate many biological processes. With increasing volumes of such datasets, especially in model organisms such as Drosophila melanogaster, there exists a pressing need for specialised tools, which can seamlessly collect, integrate and analyse these data. Here we describe a database coupled with a mining tool for protein-protein interactions (DAPPER), developed as a rich resource for studying multi-protein complexes in Drosophila melanogaster. RESULTS: This proteomics database is compiled through mass spectrometric analyses of many protein complexes affinity purified from Drosophila tissues and cultured cells. The web access to DAPPER is provided via an accelerated version of BioMart software enabling data-mining through customised querying and output formats. The protein-protein interaction dataset is annotated with FlyBase identifiers, and further linked to the Ensembl database using BioMart's data-federation model, thereby enabling complex multi-dataset queries. DAPPER is open source, with all its contents and source code are freely available. CONCLUSIONS: DAPPER offers an easy-to-navigate and extensible platform for real-time integration of diverse resources containing new and existing protein-protein interaction datasets of Drosophila melanogaster.This work was supported financially by grants from the Cancer Research UK (CRUK), the Biotechnology and Biological Sciences Research Council and the Medical Research Council to DMG (C3/A11431, BB/I013938/1, G1001696), by a Cancer Research UK Career Development Fellowship to YK (C40697/A12874), and by Cancer Research UK grants to PPD (C12296/A8039 and C12296/A12541). ZL is on leave from the Biological Research Centre of the Hungarian Academy of Sciences (Institute of Biochemistry, Szeged, Hungary) and was supported by a Long-Term Fellowship of the Federation of European Biochemical Societies (FEBS)

Burden-driven feedback control of gene expression

Cells use feedback regulation to ensure robust growth despite fluctuating demands for resources and differing environmental conditions. However, the expression of foreign proteins from engineered constructs is an unnatural burden that cells are not adapted for. Here we combined RNA-seq with an in vivo assay to identify the major transcriptional changes that occur in Escherichia coli when inducible synthetic constructs are expressed. We observed that native promoters related to the heat-shock response activated expression rapidly in response to synthetic expression, regardless of the construct. Using these promoters, we built a dCas9-based feedback-regulation system that automatically adjusts the expression of a synthetic construct in response to burden. Cells equipped with this general-use controller maintained their capacity for native gene expression to ensure robust growth and thus outperformed unregulated cells in terms of protein yield in batch production. This engineered feedback is to our knowledge the first example of a universal, burden-based biomolecular control system and is modular, tunable and portable

Additional file 2: Table S1. of DAPPER: a data-mining resource for protein-protein interactions

List of unique Baits in DAPPER. (XLSX 31 kb

Additional file 1: Figure S1. of DAPPER: a data-mining resource for protein-protein interactions

An overview of DAPPER retrieval tools. Venn diagram highlighting sections of records which will be retrieved by various tools, when applied to three hypothetical experiments. Each of the three tools can retrieve data in either tab-delimited or HTML format (see DAPPER Results web page for these options). Figure S2. Home page of DAPPER. The search field can be used to retrieve all experiments containing a particular CGID of Drosophila melanogaster. Browse button (MartView link) navigates to DAPPER BioMart interface for custom querying. By default, results are sorted (descending) by “Protein score”. Upload link is currently restricted to DAPPER curators and collaborators only. Figure S3. Stepwise guide to retrieve all proteins and their ontological annotations for a given experiment. The guide also shows how data from an external resource (Ensembl) can be retrieved and seamlessly integrated with DAPPER contents. Figure S4. Stepwise guide to retrieve kinetochore associated Drosophila genes. Gene ontology filter (GO Term Name) is set to “kinetochore” through linking with Ensembl database. Entries retrieved are further sorted by “Protein score” using SORT tool (SORT_HTML) on the Results page. Figure S5. Stepwise guide to compare two (or more) experiments. The results will contain only those hits which are common between the experiments selected for comparison (BubR1 and Polo kinase). Experiments having an entry in common are grouped together for better interpretation of results. (PDF 2334 kb