Methods designed for the identification and characterization of in vitro and in vivo chromatin assembly mutants in Saccharomyces cerevisiae

Assembly of DNA into chromatin allows for the formation of a barrier that protects naked DNA from protein and chemical agents geared to degrade or metabolize DNA. Chromatin assembly occurs whenever a length of DNA becomes exposed to the cellular elements, whether during DNA synthesis or repair. This report describes tools to study chromatin assembly in the model system Saccharomyces cerevisiae. Modifications to an in vitro chromatin assembly assay are described that allowed a brute force screen of temperature sensitive (ts) yeast strains in order to identify chromatin assembly defective extracts. This screen yielded mutations in genes encoding two ubiquitin protein ligases (E3s): RSP5, and a subunit of the Anaphase Promoting Complex (APC), APC5. Additional modifications are described that allow for a rapid analysis and an in vivo characterization of yeast chromatin assembly mutants, as well as any other mutant of interest. Our analysis suggests that the in vitro and in vivo chromatin assembly assays are responsive to different cellular signals, including cell cycle cues that involve different molecular networks

Role of Duplicate Genes in Robustness against Deleterious Human Mutations

It is now widely recognized that robustness is an inherent property of biological systems [1],[2],[3]. The contribution of close sequence homologs to genetic robustness against null mutations has been previously demonstrated in simple organisms [4],[5]. In this paper we investigate in detail the contribution of gene duplicates to back-up against deleterious human mutations. Our analysis demonstrates that the functional compensation by close homologs may play an important role in human genetic disease. Genes with a 90% sequence identity homolog are about 3 times less likely to harbor known disease mutations compared to genes with remote homologs. Moreover, close duplicates affect the phenotypic consequences of deleterious mutations by making a decrease in life expectancy significantly less likely. We also demonstrate that similarity of expression profiles across tissues significantly increases the likelihood of functional compensation by homologs

Systematic quantification of gene interactions by phenotypic array analysis

A phenotypic array method, developed for quantifying cell growth, was applied to the haploid and homozygous diploid yeast deletion strain sets. A growth index was developed to screen for non-additive interacting effects between gene deletion and induced perturbations. From a genome screen for hydroxyurea (HU) chemical-genetic interactions, 298 haploid deletion strains were selected for further analysis. The strength of interactions was quantified using a wide range of HU concentrations affecting reference strain growth. The selectivity of interaction was determined by comparison with drugs targeting other cellular processes. Bio-modules were defined as gene clusters with shared strength and selectivity of interaction profiles. The functions and connectivity of modules involved in processes such as DNA repair, protein secretion and metabolic control were inferred from their respective gene composition. The work provides an example of, and a general experimental framework for, quantitative analysis of gene interaction networks that buffer cell growth

A large scale survey reveals that chromosomal copy-number alterations significantly affect gene modules involved in cancer initiation and progression

Background Recent observations point towards the existence of a large number of neighborhoods composed of functionally-related gene modules that lie together in the genome. This local component in the distribution of the functionality across chromosomes is probably affecting the own chromosomal architecture by limiting the possibilities in which genes can be arranged and distributed across the genome. As a direct consequence of this fact it is therefore presumable that diseases such as cancer, harboring DNA copy number alterations (CNAs), will have a symptomatology strongly dependent on modules of functionally-related genes rather than on a unique "important" gene. Methods We carried out a systematic analysis of more than 140,000 observations of CNAs in cancers and searched by enrichments in gene functional modules associated to high frequencies of loss or gains. Results The analysis of CNAs in cancers clearly demonstrates the existence of a significant pattern of loss of gene modules functionally related to cancer initiation and progression along with the amplification of modules of genes related to unspecific defense against xenobiotics (probably chemotherapeutical agents). With the extension of this analysis to an Array-CGH dataset (glioblastomas) from The Cancer Genome Atlas we demonstrate the validity of this approach to investigate the functional impact of CNAs. Conclusions The presented results indicate promising clinical and therapeutic implications. Our findings also directly point out to the necessity of adopting a function-centric, rather a gene-centric, view in the understanding of phenotypes or diseases harboring CNAs.Spanish Ministry of Science and Innovation (grant BIO2008-04212)Spanish Ministry of Science and Innovation (grant FIS PI 08/0440)GVA-FEDER (PROMETEO/2010/001)Red Temática de Investigación Cooperativa en Cáncer (RTICC) (grant RD06/0020/1019)Instituto de Salud Carlos III (ISCIII)Spanish Ministry of Science and InnovationSpanish Ministry of Health (FI06/00027

Nowhere to go: How stigma limits the options of female drug users after release from jail

<p>Abstract</p> <p>Background</p> <p>Drug and alcohol using women leaving prison or jail face many challenges to successful re-integration in the community and are severely hampered in their efforts by the stigma of drug or alcohol use compounded by the stigma of incarceration.</p> <p>Methods</p> <p>This qualitative study is based on individual semi-structured interviews and focus groups with 17 women who had recently left jail about the challenges they faced on reentry.</p> <p>Results</p> <p>Our analysis identified three major themes, which are related by the overarching influence of stigma: survival (jobs and housing), access to treatment services, and family and community reintegration.</p> <p>Conclusion</p> <p>Stigma based on drug use and incarceration works to increase the needs of women for health and social services and at the same time, restricts their access to these services. These specific forms of stigma may amplify gender and race-based stigma. Punitive drug and social policies related to employment, housing, education, welfare, and mental health and substance abuse treatment make it extremely difficult for women to succeed.</p

Holding blame at bay? ‘Gene talk’ in family members’ accounts of schizophrenia aetiology

We provide the first detailed analysis of how, for what purposes and with what consequences people related to someone with a diagnosis of schizophrenia use ‘gene talk'. The article analyses findings from a qualitative interview study conducted in London and involving 19 participants (mostly women). We transcribed the interviews verbatim and analysed them using grounded theory methods. We analyse how and for what purposes participants mobilized ‘gene talk' in their affectively freighted encounter with an unknown interviewer. Gene talk served to (re)position blame and guilt, and was simultaneously used imaginatively to forge family history narratives. Family members used ‘gene talk' to recruit forebears with no psychiatric diagnosis into a family history of mental illness, and presented the origins of the diagnosed family member's schizophrenia as lying temporally before, and hence beyond the agency of the immediate family. Gene talk was also used in attempts to dislodge the distressing figure of the schizophrenia-inducing mother. ‘Gene talk', however, ultimately displaced, rather than resolved, the (self-)blame of many family members, particularly mothers. Our article challenges the commonly expressed view that genetic accounts will absolve family members' sense of (self-)blame in relation to their relative's/relatives' diagnosis

Mining and state-space modeling and verification of sub-networks from large-scale biomolecular networks

<p>Abstract</p> <p>Background</p> <p>Biomolecular networks dynamically respond to stimuli and implement cellular function. Understanding these dynamic changes is the key challenge for cell biologists. As biomolecular networks grow in size and complexity, the model of a biomolecular network must become more rigorous to keep track of all the components and their interactions. In general this presents the need for computer simulation to manipulate and understand the biomolecular network model.</p> <p>Results</p> <p>In this paper, we present a novel method to model the regulatory system which executes a cellular function and can be represented as a biomolecular network. Our method consists of two steps. First, a novel scale-free network clustering approach is applied to the large-scale biomolecular network to obtain various sub-networks. Second, a state-space model is generated for the sub-networks and simulated to predict their behavior in the cellular context. The modeling results represent <it>hypotheses </it>that are tested against high-throughput data sets (microarrays and/or genetic screens) for both the natural system and perturbations. Notably, the dynamic modeling component of this method depends on the automated network structure generation of the first component and the sub-network clustering, which are both essential to make the solution tractable.</p> <p>Conclusion</p> <p>Experimental results on time series gene expression data for the human cell cycle indicate our approach is promising for sub-network mining and simulation from large-scale biomolecular network.</p

EAPP: Gatekeeper at the crossroad of apoptosis and p21-mediated cell-cycle arrest

We previously identified and characterized E2F-associated phospho-protein (EAPP), a nuclear phosphoprotein that interacts with the activating members of the E2F transcription factor family. EAPP levels are frequently elevated in transformed human cells. To examine the biological relevance of EAPP, we studied its properties in stressed and unstressed cells. Overexpression of EAPP in U2OS cells increased the fraction of G1 cells and lead to heightened resistance against DNA damage- or E2F1-induced apoptosis in a p21-dependent manner. EAPP itself becomes upregulated in confluent cells and after DNA damage and stimulates the expression of p21 independently of p53. It binds to the p21 promoter and seems to be required for the assembly of the transcription initiation complex. RNAi-mediated knockdown of EAPP expression brought about increased sensitivity towards DNA damage and resulted in apoptosis even in the absence of stress. Our results indicate that the level of EAPP is critical for cellular homeostasis. Too much of it results in G1 arrest and resistance to apoptosis, which, paradoxically, might favor cellular transformation. Too little EAPP seems to retard the expression not only of the p21 gene, but also of a number of other genes and ultimately results in apoptosis

Protein Networks as Logic Functions in Development and Cancer

Many biological and clinical outcomes are based not on single proteins, but on modules of proteins embedded in protein networks. A fundamental question is how the proteins within each module contribute to the overall module activity. Here, we study the modules underlying three representative biological programs related to tissue development, breast cancer metastasis, or progression of brain cancer, respectively. For each case we apply a new method, called Network-Guided Forests, to identify predictive modules together with logic functions which tie the activity of each module to the activity of its component genes. The resulting modules implement a diverse repertoire of decision logic which cannot be captured using the simple approximations suggested in previous work such as gene summation or subtraction. We show that in cancer, certain combinations of oncogenes and tumor suppressors exert competing forces on the system, suggesting that medical genetics should move beyond cataloguing individual cancer genes to cataloguing their combinatorial logic