The genotype-phenotype relationship in multicellular pattern-generating models - the neglected role of pattern descriptors

Background: A deep understanding of what causes the phenotypic variation arising from biological patterning processes, cannot be claimed before we are able to recreate this variation by mathematical models capable of generating genotype-phenotype maps in a causally cohesive way. However, the concept of pattern in a multicellular context implies that what matters is not the state of every single cell, but certain emergent qualities of the total cell aggregate. Thus, in order to set up a genotype-phenotype map in such a spatiotemporal pattern setting one is actually forced to establish new pattern descriptors and derive their relations to parameters of the original model. A pattern descriptor is a variable that describes and quantifies a certain qualitative feature of the pattern, for example the degree to which certain macroscopic structures are present. There is today no general procedure for how to relate a set of patterns and their characteristic features to the functional relationships, parameter values and initial values of an original pattern-generating model. Here we present a new, generic approach for explorative analysis of complex patterning models which focuses on the essential pattern features and their relations to the model parameters. The approach is illustrated on an existing model for Delta-Notch lateral inhibition over a two-dimensional lattice. Results: By combining computer simulations according to a succession of statistical experimental designs, computer graphics, automatic image analysis, human sensory descriptive analysis and multivariate data modelling, we derive a pattern descriptor model of those macroscopic, emergent aspects of the patterns that we consider of interest. The pattern descriptor model relates the values of the new, dedicated pattern descriptors to the parameter values of the original model, for example by predicting the parameter values leading to particular patterns, and provides insights that would have been hard to obtain by traditional methods. Conclusion: The results suggest that our approach may qualify as a general procedure for how to discover and relate relevant features and characteristics of emergent patterns to the functional relationships, parameter values and initial values of an underlying pattern-generating mathematical model

Improvement of Cardiac Function in Mouse Myocardial Infarction after Transplantation of Epigenetically-Modified Bone Marrow Progenitor Cells

OBJECTIVE: To study usefulness of bone marrow progenitor cells (BPCs) epigenetically altered by chromatin modifying agents in mediating heart repair after myocardial infarction in mice. METHODS AND RESULTS: We tested the therapeutic efficacy of bone marrow progenitor cells treated with the clinically-used chromatin modifying agents Trichostatin A (TSA, histone deacetylase inhibitor) and 5Aza-2-deoxycytidine (Aza, DNA methylation inhibitor) in a mouse model of acute myocardial infarction (AMI). Treatment of BPCs with Aza and TSA induced expression of pluripotent genes Oct4, Nanog, Sox2, and thereafter culturing these cells in defined cardiac myocyte-conditioned medium resulted in their differentiation into cardiomyocyte progenitors and subsequently into cardiac myocytes. Their transition was deduced by expression of repertoire of markers: Nkx2.5, GATA4, cardiotroponin T, cardiotroponin I, α-sarcomeric actinin, Mef2c and MHC-α. We observed that the modified BPCs had greater AceH3K9 expression and reduced histone deacetylase1 (HDAC1) and lysine-specific demethylase1 (LSD1) expression compared to untreated BPCs, characteristic of epigenetic changes. Intra-myocardial injection of modified BPCs after AMI in mice significantly improved left ventricular function. These changes were ascribed to differentiation of the injected cells into cardiomyocytes and endothelial cells. CONCLUSION: Treatment of BPCs with Aza and TSA converts BPCs into multipotent cells, which can then be differentiated into myocyte progenitors. Transplantation of these modified progenitor cells into infarcted mouse hearts improved left ventricular function secondary to differentiation of cells in the niche into myocytes and endothelial cells

Mapping of quantitative trait loci for flesh colour and growth traits in Atlantic salmon (Salmo salar)

<p>Abstract</p> <p>Background</p> <p>Flesh colour and growth related traits in salmonids are both commercially important and of great interest from a physiological and evolutionary perspective. The aim of this study was to identify quantitative trait loci (QTL) affecting flesh colour and growth related traits in an F2 population derived from an isolated, landlocked wild population in Norway (Byglands Bleke) and a commercial production population.</p> <p>Methods</p> <p>One hundred and twenty-eight informative microsatellite loci distributed across all 29 linkage groups in Atlantic salmon were genotyped in individuals from four F2 families that were selected from the ends of the flesh colour distribution. Genotyping of 23 additional loci and two additional families was performed on a number of linkage groups harbouring putative QTL. QTL analysis was performed using a line-cross model assuming fixation of alternate QTL alleles and a half-sib model with no assumptions about the number and frequency of QTL alleles in the founder populations.</p> <p>Results</p> <p>A moderate to strong phenotypic correlation was found between colour, length and weight traits. In total, 13 genome-wide significant QTL were detected for all traits using the line-cross model, including three genome-wide significant QTL for flesh colour (Chr 6, Chr 26 and Chr 4). In addition, 32 suggestive QTL were detected (chromosome-wide P < 0.05). Using the half-sib model, six genome-wide significant QTL were detected for all traits, including two for flesh colour (Chr 26 and Chr 4) and 41 suggestive QTL were detected (chromosome-wide P < 0.05). Based on the half-sib analysis, these two genome-wide significant QTL for flesh colour explained 24% of the phenotypic variance for this trait.</p> <p>Conclusions</p> <p>A large number of significant and suggestive QTL for flesh colour and growth traits were found in an F2 population of Atlantic salmon. Chr 26 and Chr 4 presented the strongest evidence for significant QTL affecting flesh colour, while Chr 10, Chr 5, and Chr 4 presented the strongest evidence for significant QTL affecting growth traits (length and weight). These QTL could be strong candidates for use in marker-assisted selection and provide a starting point for further characterisation of the genetic components underlying flesh colour and growth.</p

A Combined Epigenetic and Non-Genetic Approach for Reprogramming Human Somatic Cells

Reprogramming of somatic cells to different extents has been reported using different methods. However, this is normally accompanied by the use of exogenous materials, and the overall reprogramming efficiency has been low. Chemicals and small molecules have been used to improve the reprogramming process during somatic cell nuclear transfer (SCNT) and induced pluripotent stem (iPS) cell generation. We report here the first application of a combined epigenetic and non-genetic approach for reprogramming somatic cells, i.e., DNA methyltransferase (DNMT) and histone deacetylase (HDAC) inhibitors, and human embryonic stem cell (hESC) extracts. When somatic cells were pretreated with these inhibitors before exposure to hESC (MEL1) extracts, morphological analysis revealed a higher rate of hESC-like colony formation than without pretreatment. Quantitative PCR (qPCR) demonstrated that pluripotency genes were upregulated when compared to those of somatic cells or treated with hESC extracts alone. Overall changes in methylation and acetylation levels of pretreated somatic cells suggests that epigenetic states of the cells have an effect on reprogramming efficiency induced by hESC extracts. KnockOutserum replacement (KOSR™) medium (KO-SR) played a positive role in inducing expression of the pluripotency genes. hESC extracts could be an alternative approach to reprogram somatic cells without introducing exogenous materials. The epigenetic pre-treatment of somatic cells could be used to improve the efficiency of reprogramming process. Under differentiation conditions, the reprogrammed cells exhibited differentiation ability into neurons suggesting that, although fully reprogramming was not achieved, the cells could be transdifferentiated after reprogramming

Regeneration of Soft Tissues Is Promoted by MMP1 Treatment after Digit Amputation in Mice

The ratio of matrix metalloproteinases (MMPs) to the tissue inhibitors of metalloproteinases (TIMPs) in wounded tissues strictly control the protease activity of MMPs, and therefore regulate the progress of wound closure, tissue regeneration and scar formation. Some amphibians (i.e. axolotl/newt) demonstrate complete regeneration of missing or wounded digits and even limbs; MMPs play a critical role during amphibian regeneration. Conversely, mammalian wound healing re-establishes tissue integrity, but at the expense of scar tissue formation. The differences between amphibian regeneration and mammalian wound healing can be attributed to the greater ratio of MMPs to TIMPs in amphibian tissue. Previous studies have demonstrated the ability of MMP1 to effectively promote skeletal muscle regeneration by favoring extracellular matrix (ECM) remodeling to enhance cell proliferation and migration. In this study, MMP1 was administered to the digits amputated at the mid-second phalanx of adult mice to observe its effect on digit regeneration. Results indicated that the regeneration of soft tissue and the rate of wound closure were significantly improved by MMP1 administration, but the elongation of the skeletal tissue was insignificantly affected. During digit regeneration, more mutipotent progenitor cells, capillary vasculature and neuromuscular-related tissues were observed in MMP1 treated tissues; moreover, there was less fibrotic tissue formed in treated digits. In summary, MMP1 was found to be effective in promoting wound healing in amputated digits of adult mice. © 2013 Mu et al

Understanding Communication Signals during Mycobacterial Latency through Predicted Genome-Wide Protein Interactions and Boolean Modeling

About 90% of the people infected with Mycobacterium tuberculosis carry latent bacteria that are believed to get activated upon immune suppression. One of the fundamental challenges in the control of tuberculosis is therefore to understand molecular mechanisms involved in the onset of latency and/or reactivation. We have attempted to address this problem at the systems level by a combination of predicted functional protein∶protein interactions, integration of functional interactions with large scale gene expression studies, predicted transcription regulatory network and finally simulations with a Boolean model of the network. Initially a prediction for genome-wide protein functional linkages was obtained based on genome-context methods using a Support Vector Machine. This set of protein functional linkages along with gene expression data of the available models of latency was employed to identify proteins involved in mediating switch signals during dormancy. We show that genes that are up and down regulated during dormancy are not only coordinately regulated under dormancy-like conditions but also under a variety of other experimental conditions. Their synchronized regulation indicates that they form a tightly regulated gene cluster and might form a latency-regulon. Conservation of these genes across bacterial species suggests a unique evolutionary history that might be associated with M. tuberculosis dormancy. Finally, simulations with a Boolean model based on the regulatory network with logical relationships derived from gene expression data reveals a bistable switch suggesting alternating latent and actively growing states. Our analysis based on the interaction network therefore reveals a potential model of M. tuberculosis latency

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models

Stem Cell Therapy: Pieces of the Puzzle

Acute ischemic injury and chronic cardiomyopathies can cause irreversible loss of cardiac tissue leading to heart failure. Cellular therapy offers a new paradigm for treatment of heart disease. Stem cell therapies in animal models show that transplantation of various cell preparations improves ventricular function after injury. The first clinical trials in patients produced some encouraging results, despite limited evidence for the long-term survival of transplanted cells. Ongoing research at the bench and the bedside aims to compare sources of donor cells, test methods of cell delivery, improve myocardial homing, bolster cell survival, and promote cardiomyocyte differentiation. This article reviews progress toward these goals

The macrophage in HIV-1 infection: From activation to deactivation?

Macrophages play a crucial role in innate and adaptative immunity in response to microorganisms and are an important cellular target during HIV-1 infection. Recently, the heterogeneity of the macrophage population has been highlighted. Classically activated or type 1 macrophages (M1) induced in particular by IFN-γ display a pro-inflammatory profile. The alternatively activated or type 2 macrophages (M2) induced by Th-2 cytokines, such as IL-4 and IL-13 express anti-inflammatory and tissue repair properties. Finally IL-10 has been described as the prototypic cytokine involved in the deactivation of macrophages (dM). Since the capacity of macrophages to support productive HIV-1 infection is known to be modulated by cytokines, this review shows how modulation of macrophage activation by cytokines impacts the capacity to support productive HIV-1 infection. Based on the activation status of macrophages we propose a model starting with M1 classically activated macrophages with accelerated formation of viral reservoirs in a context of Th1 and proinflammatory cytokines. Then IL-4/IL-13 alternatively activated M2 macrophages will enter into the game that will stop the expansion of the HIV-1 reservoir. Finally IL-10 deactivation of macrophages will lead to immune failure observed at the very late stages of the HIV-1 disease

A framework for evolutionary systems biology

<p>Abstract</p> <p>Background</p> <p>Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.</p> <p>Results</p> <p>Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions <it>in silico</it>. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.</p> <p>Conclusion</p> <p>EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.</p