Qualitative networks: a symbolic approach to analyze biological signaling networks

BACKGROUND: A central goal of Systems Biology is to model and analyze biological signaling pathways that interact with one another to form complex networks. Here we introduce Qualitative networks, an extension of Boolean networks. With this framework, we use formal verification methods to check whether a model is consistent with the laboratory experimental observations on which it is based. If the model does not conform to the data, we suggest a revised model and the new hypotheses are tested in-silico. RESULTS: We consider networks in which elements range over a small finite domain allowing more flexibility than Boolean values, and add target functions that allow to model a rich set of behaviors. We propose a symbolic algorithm for analyzing the steady state of these networks, allowing us to scale up to a system consisting of 144 elements and state spaces of approximately 10(86 )states. We illustrate the usefulness of this approach through a model of the interaction between the Notch and the Wnt signaling pathways in mammalian skin, and its extensive analysis. CONCLUSION: We introduce an approach for constructing computational models of biological systems that extends the framework of Boolean networks and uses formal verification methods for the analysis of the model. This approach can scale to multicellular models of complex pathways, and is therefore a useful tool for the analysis of complex biological systems. The hypotheses formulated during in-silico testing suggest new avenues to explore experimentally. Hence, this approach has the potential to efficiently complement experimental studies in biology

Analysis of Chao’s Immune System Simulation

Computational methods have been developped to simulate the complex interactions between components of the immune system. Chao introduced a method based on a stage structured approach to studying the Cytotoxic T cells response to an infection. In this work, we extend the analyzis of Chao’s simulater by Eric Winnington. We validate the time step choice used in the simulation and analyze the impact of different factors on the occurence of a secondary reaction. We find that the initialization of the simulation, and in particular the generation of the T Cell Receptor Chains and epitopes influences the frequency of this secondary reaction. Furthermore, we note that the secondary reaction arises in a time window when the number of na¨ıve cells population is low, the effector cell population is decreasing after the primary response and the memory T cells are not yet able to take part in the response. We find that the secondary reaction does not question the correctness of the simulation. The question of the adequacy of the biological model however remains open and is not discussed in this project

Survival rates in the world's southernmost forest bird community

Article asserts that the Magellanic sub-Antarctic Forest is home to the world's southernmost avian community and is the only Southern Hemisphere analogue to Northern Hemisphere temperate forests at this latitude. Authors describe annual survival patterns and their association with climate variables using a 20-year mark–recapture data set of five forest bird species in the Cape Horn Biosphere Reserve

Autoimmune Disease Classification by Inverse Association with SNP Alleles

With multiple genome-wide association studies (GWAS) performed across autoimmune diseases, there is a great opportunity to study the homogeneity of genetic architectures across autoimmune disease. Previous approaches have been limited in the scope of their analysis and have failed to properly incorporate the direction of allele-specific disease associations for SNPs. In this work, we refine the notion of a genetic variation profile for a given disease to capture strength of association with multiple SNPs in an allele-specific fashion. We apply this method to compare genetic variation profiles of six autoimmune diseases: multiple sclerosis (MS), ankylosing spondylitis (AS), autoimmune thyroid disease (ATD), rheumatoid arthritis (RA), Crohn's disease (CD), and type 1 diabetes (T1D), as well as five non-autoimmune diseases. We quantify pair-wise relationships between these diseases and find two broad clusters of autoimmune disease where SNPs that make an individual susceptible to one class of autoimmune disease also protect from diseases in the other autoimmune class. We find that RA and AS form one such class, and MS and ATD another. We identify specific SNPs and genes with opposite risk profiles for these two classes. We furthermore explore individual SNPs that play an important role in defining similarities and differences between disease pairs. We present a novel, systematic, cross-platform approach to identify allele-specific relationships between disease pairs based on genetic variation as well as the individual SNPs which drive the relationships. While recognizing similarities between diseases might lead to identifying novel treatment options, detecting differences between diseases previously thought to be similar may point to key novel disease-specific genes and pathways

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

The autocrine role of tumor necrosis factor in the proliferation and functional differentiation of human lymphokine-activated T killer cells (T-LAK) in vitro

The autocrine role of tumor necrosis factor alpha (TNF) in the proliferation and functional differentiation of human lymphokine-activated T-killer cells (T-LAK) in vitro was investigated. Human peripheral blood lymphocytes initially stimulated with IL-2 and phytohemagglutinin-P (PHA) for 48 h will proliferate for long periods in vitro in the presence of IL-2. These T-LAK cells have been shown to be 95% CD3 positive. Employing ELISA techniques, greater than 500 pg/ml of TNF was found to be released in the supernatants of these cells during the first 5 days of culture. However, the levels dropped to 100-200 pg/ml by days 7-10. T-LAK cells grown from days 7 to 10 in the presence of IL-2 and rabbit anti-TNF were significantly growth inhibited (up to 23%). The cytolytic activity of T-LAK cells grown from days 0 to 7 in the presence of anti-TNF was also decreased (up to 75%). Phenotypic analysis of these anti-TNF treated T-LAK cells revealed a decrease in CD8 expression (up to 12%) and increase in CD4 expression (up to 27%) when compared with control cells. The data suggest that TNF has a regulatory role in the growth and functional differentiation of these human T-LAK cells

Multimodal Communication in a Noisy Environment: A Case Study of the Bornean Rock Frog Staurois parvus

High background noise is an impediment to signal detection and perception. We report the use of multiple solutions to improve signal perception in the acoustic and visual modality by the Bornean rock frog, Staurois parvus. We discovered that vocal communication was not impaired by continuous abiotic background noise characterised by fast-flowing water. Males modified amplitude, pitch, repetition rate and duration of notes within their advertisement call. The difference in sound pressure between advertisement calls and background noise at the call dominant frequency of 5578 Hz was 8 dB, a difference sufficient for receiver detection. In addition, males used several visual signals to communicate with conspecifics with foot flagging and foot flashing being the most common and conspicuous visual displays, followed by arm waving, upright posture, crouching, and an open-mouth display. We used acoustic playback experiments to test the efficacy-based alerting signal hypothesis of multimodal communication. In support of the alerting hypothesis, we found that acoustic signals and foot flagging are functionally linked with advertisement calling preceding foot flagging. We conclude that S. parvus has solved the problem of continuous broadband low-frequency noise by both modifying its advertisement call in multiple ways and by using numerous visual signals. This is the first example of a frog using multiple acoustic and visual solutions to communicate in an environment characterised by continuous noise

Comprehensive genomic profiles of small cell lung cancer

We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. In nearly all the tumours analysed we found bi-allelic inactivation of TP53 and RB1, sometimes by complex genomic rearrangements. Two tumours with wild-type RB1 had evidence of chromothripsis leading to overexpression of cyclin D1 (encoded by the CCND1 gene), revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumour suppressors TP53 and RB1 is obligatory in SCLC. We discovered somatic genomic rearrangements of TP73 that create an oncogenic version of this gene, TP73Dex2/3. In rare cases, SCLC tumours exhibited kinase gene mutations, providing a possible therapeutic opportunity for individual patients. Finally, we observed inactivating mutations in NOTCH family genes in 25% of human SCLC. Accordingly, activation of Notch signalling in a pre-clinical SCLC mouse model strikingly reduced the number of tumours and extended the survival of the mutant mice. Furthermore, neuroendocrine gene expression was abrogated by Notch activity in SCLC cells. This first comprehensive study of somatic genome alterations in SCLC uncovers several key biological processes and identifies candidate therapeutic targets in this highly lethal form of cancer