Quantifying E2F1 protein dynamics in single cells.

BACKGROUND: E2F1 protein, a major effector of the Rb/E2F pathway plays a central role in regulating cell-fate decisions involved in proliferation, apoptosis, and differentiation. Its expression is highly dynamic and tightly modulated through a combination of transcriptional, translational and posttranslational controls. However, the mechanisms by which its expression and activity can promote different cellular outcomes remain to be fully elucidated. To better document E2F1 expression in live cells, we have engineered a series of fluorescent E2F1 protein reporters that quantitatively capture E2F1 protein dynamics. METHODS: Reporter constructs, under the control of the mouse or human E2F1 proximal promoter, were designed to express an E2F1-Venus fusion protein incapable of binding DNA. In addition, constructs either included or excluded the 3' untranslated region (3'UTR) of the E2F1 gene. These constructs were introduced into fibroblasts and epithelial cells, and expression of the fusion reporter protein was validated and quantified in single cells using live imaging. RESULTS: In all cases, expression of the reporter protein effectively recapitulated the behavior of E2F1 under various conditions, including cell cycle progression and genotoxic stress. No or little fluorescent signal of the reporter was detected in G0, but as the cycle progressed, expression of the reporter protein steadily increased in the nucleus, peaking a few hours before cell division, but declining to baseline 2-3 h prior to the onset of mitosis. The absence of the E2F1 3'UTR in the constructs led to considerably higher steady-state levels of the fusion protein, which although normally regulated, exhibited a slightly less complex dynamic profile during the cell cycle or genotoxic stress. Lastly, the presence or absence of Rb failed to impact the overall detection and levels of the reporter proteins. CONCLUSIONS: Our validated E2F1 protein reporters complement nicely other reporters of the Rb/E2F pathway and provide a unique tool to follow the complex dynamics of E2F1 expression in real time in single cells.

Kinome screen of ferroptosis reveals a novel role of ATM in regulating iron metabolism.

Ferroptosis is a specialized iron-dependent cell death that is associated with lethal lipid peroxidation. Modulation of ferroptosis may have therapeutic potential since it has been implicated in various human diseases as well as potential antitumor activities. However, much remains unknown about the underlying mechanisms and genetic determinants of ferroptosis. Given the critical role of kinases in most biological processes and the availability of various kinase inhibitors, we sought to systemically identify kinases essential for ferroptosis. We performed a forward genetic-based kinome screen against ferroptosis in MDA-MB-231 cells triggered by cystine deprivation. This screen identified 34 essential kinases involved in TNFα and NF-kB signaling. Unexpectedly, the DNA damage response serine/threonine kinase ATM (mutated in Ataxia-Telangiectasia) was found to be essential for ferroptosis. The pharmacological or genetic inhibition of ATM consistently rescued multiple cancer cells from ferroptosis triggered by cystine deprivation or erastin. Instead of the canonical DNA damage pathways, ATM inhibition rescued ferroptosis by increasing the expression of iron regulators involved in iron storage (ferritin heavy and light chain, FTH1 and FTL) and export (ferroportin, FPN1). The coordinated changes of these iron regulators during ATM inhibition resulted in a lowering of labile iron and prevented the iron-dependent ferroptosis. Furthermore, we found that ATM inhibition enhanced the nuclear translocation of metal-regulatory transcription factor 1 (MTF1), responsible for regulating expression of Ferritin/FPN1 and ferroptosis protection. Genetic depletion of MTF-1 abolished the regulation of iron-regulatory elements by ATM and resensitized the cells to ferroptosis. Together, we have identified an unexpected ATM-MTF1-Ferritin/FPN1 regulatory axis as novel determinants of ferroptosis through regulating labile iron levels.

Author Correction: Division of labour between Myc and G1 cyclins in cell cycle commitment and pace control.

This Article contains errors in Supplementary Table 3, which are described in the Author Correction associated with this Article. The simulation results in the Article were based on the correct formula and thus the results are not affected by this correction. The errors have not been fixed in the original Article.

CoA synthase regulates mitotic fidelity via CBP-mediated acetylation.

The temporal activation of kinases and timely ubiquitin-mediated degradation is central to faithful mitosis. Here we present evidence that acetylation controlled by Coenzyme A synthase (COASY) and acetyltransferase CBP constitutes a novel mechanism that ensures faithful mitosis. We found that COASY knockdown triggers prolonged mitosis and multinucleation. Acetylome analysis reveals that COASY inactivation leads to hyper-acetylation of proteins associated with mitosis, including CBP and an Aurora A kinase activator, TPX2. During early mitosis, a transient CBP-mediated TPX2 acetylation is associated with TPX2 accumulation and Aurora A activation. The recruitment of COASY inhibits CBP-mediated TPX2 acetylation, promoting TPX2 degradation for mitotic exit. Consistently, we detected a stage-specific COASY-CBP-TPX2 association during mitosis. Remarkably, pharmacological and genetic inactivation of CBP effectively rescued the mitotic defects caused by COASY knockdown. Together, our findings uncover a novel mitotic regulation wherein COASY and CBP coordinate an acetylation network to enforce productive mitosis.

Cyclin D/CDK4/6 activity controls G1 length in mammalian cells.

The length of the G1 phase in the cell cycle shows significant variability in different cell types and tissue types. To gain insights into the control of G1 length, we generated an E2F activity reporter that captures free E2F activity after dissociation from Rb sequestration and followed its kinetics of activation at the single-cell level, in real time. Our results demonstrate that its activity is precisely coordinated with S phase progression. Quantitative analysis indicates that there is a pre-S phase delay between E2F transcriptional dynamic and activity dynamics. This delay is variable among different cell types and is strongly modulated by the cyclin D/CDK4/6 complex activity through Rb phosphorylation. Our findings suggest that the main function of this complex is to regulate the appropriate timing of G1 length.

Division of labour between Myc and G1 cyclins in cell cycle commitment and pace control.

A body of evidence has shown that the control of E2F transcription factor activity is critical for determining cell cycle entry and cell proliferation. However, an understanding of the precise determinants of this control, including the role of other cell-cycle regulatory activities, has not been clearly defined. Here, recognizing that the contributions of individual regulatory components could be masked by heterogeneity in populations of cells, we model the potential roles of individual components together with the use of an integrated system to follow E2F dynamics at the single-cell level and in real time. These analyses reveal that crossing a threshold amplitude of E2F accumulation determines cell cycle commitment. Importantly, we find that Myc is critical in modulating the amplitude, whereas cyclin D/E activities have little effect on amplitude but do contribute to the modulation of duration of E2F activation, thereby affecting the pace of cell cycle progression.

Cross-platform prediction of gene expression signatures.

Gene expression signatures can predict the activation of oncogenic pathways and other phenotypes of interest via quantitative models that combine the expression levels of multiple genes. However, as the number of platforms to measure genome-wide gene expression proliferates, there is an increasing need to develop models that can be ported across diverse platforms. Because of the range of technologies that measure gene expression, the resulting signal values can vary greatly. To understand how this variation can affect the prediction of gene expression signatures, we have investigated the ability of gene expression signatures to predict pathway activation across Affymetrix and Illumina microarrays. We hybridized the same RNA samples to both platforms and compared the resultant gene expression readings, as well as the signature predictions. Using a new approach to map probes across platforms, we found that the genes in the signatures from the two platforms were highly similar, and that the predictions they generated were also strongly correlated. This demonstrates that our method can map probes from Affymetrix and Illumina microarrays, and that this mapping can be used to predict gene expression signatures across platforms.

FlyRNAi.org--the database of the Drosophila RNAi screening center: 2012 update.

FlyRNAi (http://www.flyrnai.org), the database and website of the Drosophila RNAi Screening Center (DRSC) at Harvard Medical School, serves a dual role, tracking both production of reagents for RNA interference (RNAi) screening in Drosophila cells and RNAi screen results. The database and website is used as a platform for community availability of protocols, tools, and other resources useful to researchers planning, conducting, analyzing or interpreting the results of Drosophila RNAi screens. Based on our own experience and user feedback, we have made several changes. Specifically, we have restructured the database to accommodate new types of reagents; added information about new RNAi libraries and other reagents; updated the user interface and website; and added new tools of use to the Drosophila community and others. Overall, the result is a more useful, flexible and comprehensive website and database.

Network calisthenics: control of E2F dynamics in cell cycle entry.

Stimulation of quiescent mammalian cells with mitogens induces an abrupt increase in E2F1-3 expression just prior to the onset of DNA synthesis, followed by a rapid decline as replication ceases. This temporal adaptation in E2F facilitates a transient pattern of gene expression that reflects the ordered nature of DNA replication. The challenge to understand how E2F dynamics coordinate molecular events required for high-fidelity DNA replication has great biological implications. Indeed, precocious, prolonged, elevated or reduced accumulation of E2F can generate replication stress that culminates in either arrest or death. Accordingly, temporal characteristics of E2F are regulated by several network modules that include feedforward and autoregulatory loops. In this review, we discuss how these network modules contribute to "shaping" E2F dynamics in the context of mammalian cell cycle entry.

A pathway-based classification of human breast cancer.

The hallmark of human cancer is heterogeneity, reflecting the complexity and variability of the vast array of somatic mutations acquired during oncogenesis. An ability to dissect this heterogeneity, to identify subgroups that represent common mechanisms of disease, will be critical to understanding the complexities of genetic alterations and to provide a framework to develop rational therapeutic strategies. Here, we describe a classification scheme for human breast cancer making use of patterns of pathway activity to build on previous subtype characterizations using intrinsic gene expression signatures, to provide a functional interpretation of the gene expression data that can be linked to therapeutic options. We show that the identified subgroups provide a robust mechanism for classifying independent samples, identifying tumors that share patterns of pathway activity and exhibit similar clinical and biological properties, including distinct patterns of chromosomal alterations that were not evident in the heterogeneous total population of tumors. We propose that this classification scheme provides a basis for understanding the complex mechanisms of oncogenesis that give rise to these tumors and to identify rational opportunities for combination therapies.

A case study of the reproducibility of transcriptional reporter cell-based RNAi screens in Drosophila.

Off-target effects have been demonstrated to be a major source of false-positives in RNA interference (RNAi) high-throughput screens. In this study, we re-assess the previously published transcriptional reporter-based whole-genome RNAi screens for the Wingless and Hedgehog signaling pathways using second generation double-stranded RNA libraries. Furthermore, we investigate other factors that may influence the outcome of such screens, including cell-type specificity, robustness of reporters, and assay normalization, which determine the efficacy of RNAi-knockdown of target genes.

Design and implementation of high-throughput RNAi screens in cultured Drosophila cells.

This protocol describes the various steps and considerations involved in planning and carrying out RNA interference (RNAi) genome-wide screens in cultured Drosophila cells. We focus largely on the procedures that have been modified as a result of our experience over the past 3 years and of our better understanding of the underlying technology. Specifically, our protocol offers a set of suggestions and considerations for screen optimization and a step-by-step description of the procedures successfully used at the Drosophila RNAi Screening Center for screen implementation, data collection and analysis to identify potential hits. In addition, this protocol briefly covers postscreen analysis approaches that are often needed to finalize the hit list. Depending on the scope of the screen and subsequent analysis and validation involved, the full protocol can take anywhere from 3 months to 2 years to complete.

Drug-target identification in Drosophila cells: combining high-throughout RNAi and small-molecule screens.

RNA interference (RNAi) and small-molecule approaches are synergistic on multiple levels, from technology and high-throughput screen development to target identification and functional studies. Here, we describe the RNAi screening platform that we have established and made available to the community through the Drosophila RNAi Screening Center at Harvard Medical School. We then illustrate how the combination of RNAi and small-molecule HTS can lead to effective identification of targets in drug discovery.

Applications of high-throughput RNA interference screens to problems in cell and developmental biology.

RNA interference (RNAi) in tissue culture cells has emerged as an excellent methodology for identifying gene functions systematically and in an unbiased manner. Here, we describe how RNAi high-throughput screening (HTS) in Drosophila cells are currently being performed and emphasize the strengths and weaknesses of the approach. Further, to demonstrate the versatility of the technology, we provide examples of the various applications of the method to problems in signal transduction and cell and developmental biology. Finally, we discuss emerging technological advances that will extend RNAi-based screening methods.

Matter arising: off-targets and genome-scale RNAi screens in Drosophila.

Recently, the issue of off-target effects (OTEs) associated with long double stranded RNAs (dsRNAs) used in RNAi screens, such as those performed at the Drosophila RNAi Screening Center and other laboratories, has become a focus of great interest and some concern. Although OTEs have been recognized as an important source of false positives in mammalian studies (where short siRNAs are used as triggers), they were generally thought to be inconsequential in Drosophila RNAi experiments because of the use of long dsRNAs. Two recent papers have disputed this contention and show that significant off-target effects can take place with the use of some long dsRNAs in Drosophila cells. Together, these studies provide evidence that OTEs mediated by short homology stretches of 19nt or greater within long dsRNAs can contribute to false positives in Drosophila RNAi screens. Here, we address how widespread the occurrence of OTE is in Drosophila screens, focusing on the DRSC dsRNA collections, and we discuss the implication for the interpretation of results reported in RNAi screens to-date. Lastly, we summarize steps taken by the DRSC to redress that situation and include a set of recommendations to observe in future RNAi screens.

Minimizing the risk of reporting false positives in large-scale RNAi screens.

Large-scale RNA interference (RNAi)-based analyses, very much as other 'omic' approaches, have inherent rates of false positives and negatives. The variability in the standards of care applied to validate results from these studies, if left unchecked, could eventually begin to undermine the credibility of RNAi as a powerful functional approach. This Commentary is an invitation to an open discussion started among various users of RNAi to set forth accepted standards that would insure the quality and accuracy of information in the large datasets coming out of genome-scale screens.

Evidence of off-target effects associated with long dsRNAs in Drosophila melanogaster cell-based assays.

To evaluate the specificity of long dsRNAs used in high-throughput RNA interference (RNAi) screens performed at the Drosophila RNAi Screening Center (DRSC), we performed a global analysis of their activity in 30 genome-wide screens completed at our facility. Notably, our analysis predicts that dsRNAs containing > or = 19-nucleotide perfect matches identified in silico to unintended targets may contribute to a significant false positive error rate arising from off-target effects. We confirmed experimentally that such sequences in dsRNAs lead to false positives and to efficient knockdown of a cross-hybridizing transcript, raising a cautionary note about interpreting results based on the use of a single dsRNA per gene. Although a full appreciation of all causes of false positive errors remains to be determined, we suggest simple guidelines to help ensure high-quality information from RNAi high-throughput screens.

FlyRNAi: the Drosophila RNAi screening center database.

RNA interference (RNAi) has become a powerful tool for genetic screening in Drosophila. At the Drosophila RNAi Screening Center (DRSC), we are using a library of over 21,000 double-stranded RNAs targeting known and predicted genes in Drosophila. This library is available for the use of visiting scientists wishing to perform full-genome RNAi screens. The data generated from these screens are collected in the DRSC database (http://flyRNAi.org/cgi-bin/RNAi_screens.pl) in a flexible format for the convenience of the scientist and for archiving data. The long-term goal of this database is to provide annotations for as many of the uncharacterized genes in Drosophila as possible. Data from published screens are available to the public through a highly configurable interface that allows detailed examination of the data and provides access to a number of other databases and bioinformatics tools.

High-throughput RNA interference screens in Drosophila tissue culture cells.

This chapter describes the method used to conduct high-throughput screening (HTs) by RNA interference in Drosophila tissue culture cells. It covers four main topics: (1) a brief description of the existing platforms to conduct RNAi-screens in cell-based assays; (2) a table of the Drosophila cell lines available for these screens and a brief mention of the need to establish other cell lines as well as cultures of primary cells; (3) a discussion of the considerations and protocols involved in establishing assays suitable for HTS in a 384-well format; and (A) a summary of the various ways of handling raw data from an ongoing screen, with special emphasis on how to apply normalization for experimental variation and statistical filters to sort out noise from signals.