Our Science – Aladjem Website
Mirit I. Aladjem, Ph.D.
The broad goal of the DNA Replication Group at the Laboratory of Molecular Pharmacology is to understand cellular networks that signal to and from chromatin to modulate DNA replication. Since many regulatory feedback pathways are deregulated in cancer cells, the results of these studies will help our understanding of cancer biology and elucidate how normal and cancer cells regulate DNA replication.
Loss of genetic control of DNA replication is a hallmark of cancer cells. Cell growth is regulated by protein signaling pathways that converge on molecular events that facilitate DNA replication. Replication regulatory pathways can provide good targets for synthetic lethality approaches that specifically kill cancer cells, but replication problems that go undetected can affect genomic integrity, triggering genomic instability that eventually might result in cancer drug resistance. Hence, many anti-cancer drugs target various aspects of DNA replication and the effectiveness of such drugs critically depends on the nature of the lesions affected in particular cancers. To understand how cells regulate their growth, we ask how cells determine where and when DNA replication starts. As part of the Developmental Therapeutic Branch, we are also involved in collaborative studies aimed to develop better ways to describe regulatory feedback networks that modulate cell cycle progression and the response of cells to anti-cancer drugs.
DNA Replication Studies
Because signals from cell cycle regulatory networks ultimately converge on chromatin, we aim to understand how the location and the timing of replication events are linked to particular modifications on chromatin and how replication coordinates with other chromatin transactions such as transcription, DNA repair and chromosome condensation. To that end, we take two complementary approaches. First, we use biochemical and genetic approaches to dissect DNA sequences that facilitate replication and proteins that bind such sequences in an effort to understand how cells determine where and when replication initiates. Second, we use massively parallel sequencing and replication imaging approaches to study the dynamics of DNA replication throughout the genome and determine how replication patterns respond to alterations in gene expression, chromatin modifications and drugs that perturb replication.
For the first approach, we study DNA sequences (termed replicators) that facilitate initiation of DNA replication at their endogenous chromosomal sites or when they are removed from their endogenous location and transferred to ectopic chromosomal sites. In previous studies, we have identified replicator sequences in mammalian cells and dissected the genetic determinants essential for replicator activity in one genomic locus, the human beta globin locus on chromosome 11 (Aladjem, Rodewald et al. 1998; Wang, Lin et al. 2004; Wang, Lin et al. 2006). We have observed that not all potential replicators initiate replication during each cell cycle and that epigenetic processes play a role in determining if and when a particular replicator will be used during each S-phase (Fu, Wang et al. 2006, reviewed in Aladjem, 2007; Conner and Aladjem, 2012). Recently, we identified sites of protein-DNA interactions in replicator sequences and observed that replicator activity depends on the integrity of these protein-binding sites. During the last year, we identified two discrete DNA-protein complexes within a replicator, RepP, located at the human beta globin locus. One RepP-associated complex includes chromatin-remodeling proteins, affects replication timing and transcriptional activity in adjacent sequences and mediates the interaction of the replicator with a distal locus control region (Huang, Fu et al. 2011). The other RepP-associated complex interacts with the pre-replication complex and is essential for initiation of DNA replication. These findings imply that the locations of initiation events depend on interactions of cell cycle regulatory proteins with sequence modules that reside within potential replicators and that the proteins that regulate initiation function in a cooperative and combinatorial manner. Such interactions may underlie the variable use of initiation sites observed in mammalian chromosomes and determine the timing of replication.
To assess how replication associates with gene expression in other loci, we determined the genome-wide distribution of replication initiation events in human cells (Martin, Ryan et al. 2011). The dataset created by the genome-wide studies encompasses the locations of replication initiation sites throughout the entire non-repetitive genomes of the analyzed transformed and non-transformed cells. We found that the frequency of replication initiation events increased in genomic regions that were transcribed in moderate levels but that initiation frequency was reduced in genes with high transcription rates. In concordance, high-resolution mapping showed that replication initiation events were excluded from promoter regions and enriched immediately downstream of transcribed promoters. We also found that the frequency of initiation events was affected by chromatin condensation and methylation at CpG sequences. These findings led us to propose a model suggesting a role for replicator sequences in coordinating replication, transcription and chromatin condensation.
In addition, we utilized single fiber analyses of DNA replication to identify a new pathway involved in the cellular response to replicative stress. We showed that low non-toxic doses of replication inhibitors deccelerate replication by a mechanism involving the cancer-predisposing protein BLM helicase, Mus81 nuclease and ATR kinase. In early stages of the pathway, inhibitors induce transient DNA breaks that are rapidly repaired by the non-homologous end-joining (NHEJ) pathway in a reaction involving DNA-PK and XRCC4. Rapid repair of the DNA breaks prevents cell cycle arrest despite minor changes in the rate of replication fork progression(Shimura, Martin et al. 2007; Shimura, Torres et al. 2008). In other studies, we collaborated with Dr. Pommier's group in LMP to characterize the response of cancer cells to drugs that perturb DNA replication (Seiler, Conti et al. 2007; Conti, Leo et al. 2010; Regairaz et al. 2011). The combination of genome-scale sequencing of replication initiation sites and single fiber analyses provide important insights into the organization of replication initiation events and the cellular responses to signals that might perturb DNA replication. Current studies focus on the impact of the Mus81 endonuclease pathway on the frequency of initiation and the pace of DNA replication.
Molecular Interaction Maps (MIMs)
One of the main stumbling blocks to organizing molecular knowledge is the lack of a common language that allows scientists to integrate data in a clear, standardized, and preferably computer-readable format. To that end, we implemented the Molecular Interaction Map (MIM) language, a diagrammatic annotation first proposed by Kurt Kohn, which encodes molecular information in the form of diagrams (molecular interaction maps or MIMs). These MIMs are used to represent and analyze molecular interactions in the same way that circuit diagrams are used to trouble-shoot electronic devices.
For this project, we closely collaborate with Dr. Kohn's group in LMP to achieve two goals. First, we have recently developed and released several tools for creating and editing MIM diagrams (Luna, Karac et al. 2011; Luna, Sunshine et al. 2011; Chandan et al. 2011). These tools should make it easier for developers to build MIM-related software, users to create and edit MIM diagrams, and also, help bridge differences between features found in MIM and related notations, such as the systems biology graphical notation (SBGN) that is developed by an international consortium with our participation (Le Novere, Hucka et al. 2009; van Iersel et al. 2012).
In a separate line of study, we use MIMs as a basis for mathematical modeling of cellular regulatory networks in an effort to shed light on basic feedback mechanisms that modulate cell proliferation. The first network we have investigated describes the regulation of tumor suppressor p53 by Mdm2 and MdmX in response to DNA damage (Kim, Aladjem et al. 2010). The simplified network model was derived from a detailed molecular interaction map (MIM) that exhibited four coherent DNA damage response pathways. The results suggest that MdmX may amplify or stabilize DNA damage-induced p53 responses via non-enzymatic interactions. These studies led us to suggest a possible role of MdmX in the response of p53 to DNA damage. This model is currently under experimental investigation. Recently, we have also created an extended computational model of a mammalian circadian clock to provide insight into the regulation of circadian rhythms and their potential role in cancer biology. Results from this model may also add to knowledge on the role of circadian rhythms on the toxicity and activity of therapeutics, including common cancer drugs.
Aladjem, MI. (2007). Replication in context: dynamic regulation of DNA replication patterns in metazoans. Nat Rev Genet 8(8): 588-600.
Aladjem MI, Rodewald LW, et al. (1998). Genetic dissection of a mammalian replicator in the human beta-globin locus. Science 281(5379): 1005-1009.
Chandan K, van Iersel MP, Aladjem MI, Kohn KW, and Luna A. (2012). PathVisio-Validator: a rule-based validation plugin for graphical pathway notations. Bioinformatics 28: 889-90.
Conner AL, Aladjem MI. (2012). The chromatin backdrop of DNA replication: Lessons from genetics and genome-scale analyses. Biochim Biophys Acta 1819: 794-801.
Conti C, Leo E, et al. (2010). Inhibition of histone deacetylase in cancer cells slows down replication forks, activates dormant origins, and induces DNA damage. Cancer Res 70(11): 4470-4480.
Fu H, Wang L, et al. (2006). Preventing gene silencing with human replicators. Nat Biotechnol 24(5): 572-576.
Huang L, Fu H, et al. (2011). Prevention of transcriptional silencing by a replicator-binding complex consisting of SWI/SNF, MeCP1, and hnRNP C1/C2. Mol Cell Biol 31(16): 3472-3484.
Kim S, Aladjem MI, et al. (2010). Predicted functions of MdmX in fine-tuning the response of p53 to DNA damage. PLoS Comput Biol 6(2): e1000665.
Le Novere N, Hucka M, et al. (2009). The Systems Biology Graphical Notation. Nat Biotechnol 27(8): 735-741.
Luna A, Karac EI, et al. (2011). A formal MIM specification and tools for the common exchange of MIM diagrams: an XML-Based format, an API, and a validation method. BMC Bioinformatics 12(1): 167.
Luna A, Sunshine ML, et al. (2011). PathVisio-MIM: PathVisio plugin for creating and editing molecular interaction maps (MIMs). Bioinformatics 27(15): 2165-2166.
Martin MM, Ryan M, et al. (2011). Genome-wide depletion of replication initiation events in highly transcribed regions. Genome Res. 21(11):1822-32.
Seiler JA, Conti C, et al. (2007). The intra-S-phase checkpoint affects both DNA replication initiation and elongation: single-cell and -DNA fiber analyses. Mol Cell Biol 27(16): 5806-5818.
Shimura T, Martin MM, et al. (2007). DNA-PK is involved in repairing a transient surge of DNA breaks induced by deceleration of DNA replication. J Mol Biol 367(3): 665-680.
Shimura T, Torres MJ, et al. (2008). Bloom's syndrome helicase and Mus81 are required to induce transient double-strand DNA breaks in response to DNA replication stress. J Mol Biol 375(4): 1152-1164.
van Iersel MP, Villeger AC, Czauderna T, Boyd SE, Bergmann FT, Luna A, Demir E, Sorokin A, Dogrusoz U, Matsuoka Y, Funahashi A, Aladjem MI, Mi H, Moodie SL, Kitano H, Le Novere N, Schreiber F. (2012) Software support for SBGN maps: SBGN-ML and LibSBGN. Bioinformatics 28:2016-2021.
Wang L, Lin CM, et al. (2004). The human beta-globin replication initiation region consists of two modular independent replicators. Mol Cell Biol 24(8): 3373-3386.
Wang L, Lin CM, et al. (2006). Cooperative sequence modules determine replication initiation sites at the human beta-globin locus. Hum Mol Genet 15(17): 2613-2622.
This page was last updated on 3/31/2014.