Cancer attractors: A systems view of tumors from a gene network dynamics and developmental perspective

Cell lineage commitment and differentiation are governed by a complex gene regulatory network. Disruption of these processes by inappropriate regulatory signals and by mutational rewiring of the network can lead to tumorigenesis. Cancer cells often exhibit immature or embryonic traits and dysregulated developmental genes can act as oncogenes. However, the prevailing paradigm of somatic evolution and multi-step tumorigenesis, while useful in many instances, offers no logically coherent reason for why oncogenesis recapitulates ontogenesis. The formal concept of “cancer attractors”, derived from an integrative, complex systems approach to gene regulatory network may provide a natural explanation. Here we present the theory of attractors in gene network dynamics and review the concept of cell types as attractors. We argue that cancer cells are trapped in abnormal attractors and discuss this concept in the light of recent ideas in cancer biology, including cancer genomics and cancer stem cells, as well as the implications for differentiation therapy.     

Systems biology strategy to study lipotoxicity and the metabolic syndrome

Systems biology views and studies the biological systems in the context of complex interactions between their building blocks and processes. Given its multi-level complexity, metabolic syndrome (MetS) makes a strong case for adopting the systems biology approach. Despite many MetS traits being highly heritable, it is becoming evident that the genetic contribution to these traits is mediated via gene–gene and gene–environment interactions across several spatial and temporal scales, and that some of these traits such as lipotoxicity may even be a product of long-term dynamic changes of the underlying genetic and molecular networks. This presents several conceptual as well as methodological challenges and may demand a paradigm shift in how we study the undeniably strong genetic component of complex diseases such as MetS. The argument is made here that for adopting systems biology approaches to MetS an integrative framework is needed which glues the biological processes of MetS with specific physiological mechanisms and principles and that lipotoxicity is one such framework. The metabolic phenotypes, molecular and genetic networks can be modeled within the context of such integrative framework and the underlying physiology.     

A scenario-based approach to modeling development: a prototype model of C. elegans vulval fate specification

Studies of developmental biology are often facilitated by diagram “models” that summarize the current understanding of underlying mechanisms. The increasing complexity of our understanding of development necessitates computational models that can extend these representations to include their dynamic behavior. Here we present a prototype model of Caenorhabditis elegans vulval precursor cell fate specification that represents many processes crucial for this developmental event but that are hard to integrate using other modeling methodologies. We demonstrate the integrative capabilities of our methodology by comprehensively incorporating the contents of three seminal papers, showing that this methodology can lead to comprehensive models of developmental biology. The prototype computational model was built and is run using a language (Live Sequence Charts) and tool (the Play-Engine) that facilitate the same conceptual processes biologists use to construct and probe diagram-type models. We demonstrate that this modeling approach permits rigorous tests of mutual consistency between experimental data and mechanistic hypotheses and can identify specific conflicting results, providing a useful approach to probe developmental systems.     

传统中国医药与现代系统生物学研究理论的殊途同归

系统生物学是研究一个生物系统中所有组成成分(基因、mRNA、蛋白质等)的构成与组分之间相互关系的学科,近年来,系统生物学作为后基因组学时代研究的一个重要内容,已广泛深入到生命科学和医药学的各个领域。而作为中国传统医学而言,似乎与之相去甚远,然而当我们对这两个新老学科基础理论进行比较时,我们发现:传统中国医药与现代系统生物学研究理论的殊途同归。有鉴于此,本文论述了系统生物学和中医学的思想起源、相互联系,基于系统生物学的发展、研究思路和方法,阐述了生物学由还原论的研究方法过渡到系统论的研究方法,强调对生命现象从系统和整体的层次进行研究和把握,对传统中医学研究方法的变革起到了推动作用,最后对系统生物学在中医药学未来发展进行了评价。     

Animal models and conserved processes

Background

The concept of conserved processes presents unique opportunities for using nonhuman animal models in biomedical research. However, the concept must be examined in the context that humans and nonhuman animals are evolved, complex, adaptive systems. Given that nonhuman animals are examples of living systems that are differently complex from humans, what does the existence of a conserved gene or process imply for inter-species extrapolation?

Methods

We surveyed the literature including philosophy of science, biological complexity, conserved processes, evolutionary biology, comparative medicine, anti-neoplastic agents, inhalational anesthetics, and drug development journals in order to determine the value of nonhuman animal models when studying conserved processes.

Results

Evolution through natural selection has employed components and processes both to produce the same outcomes among species but also to generate different functions and traits. Many genes and processes are conserved, but new combinations of these processes or different regulation of the genes involved in these processes have resulted in unique organisms. Further, there is a hierarchy of organization in complex living systems. At some levels, the components are simple systems that can be analyzed by mathematics or the physical sciences, while at other levels the system cannot be fully analyzed by reducing it to a physical system. The study of complex living systems must alternate between focusing on the parts and examining the intact whole organism while taking into account the connections between the two. Systems biology aims for this holism. We examined the actions of inhalational anesthetic agents and anti-neoplastic agents in order to address what the characteristics of complex living systems imply for inter-species extrapolation of traits and responses related to conserved processes.

Conclusion

We conclude that even the presence of conserved processes is insufficient for inter-species extrapolation when the trait or response being studied is located at higher levels of organization, is in a different module, or is influenced by other modules. However, when the examination of the conserved process occurs at the same level of organization or in the same module, and hence is subject to study solely by reductionism, then extrapolation is possible.     

Vector Systems Allowing Efficient Autonomous or Integrative Gene Cloning in Micromonospora sp. Strain 40027

Vector systems allowing autonomous or site-specific integrative gene cloning were developed for Micromonospora sp. strain 40027, a producer of the antibiotic fortimicin A. The autonomous system depends on the discovery of a low-copy-number, self-transmissible covalently closed circular plasmid, pJTU112 (ca. 14.1 kb), which was shown to be present in the progenitor strain in both integrated and autonomous states. The copy numbers of both wild-type pJTU112 and three derivatives of it can be amplified at least sixfold by addition of streptomycin to the culture medium. The integrative system was developed by the use of a pBR322-derived Escherichia coli plasmid vector, pSET152, mediated by the attP site of the Streptomyces phage ΦC31. Both vectors can be transferred by conjugation from E. coli into Micromonospora sp. strain 40027. The heterologous cloning and expression of the dnd gene cluster originating from Streptomyces lividans 1326 into Micromonospora sp. strain 40027 demonstrated the use of the two systems.     

Systems biology of eukaryotic superorganisms and the holobiont concept

The founders of modern biology (Jean Lamarck, Charles Darwin, August Weismann etc.) were organismic life scientists who attempted to understand the morphology and evolution of living beings as a whole (i.e., the phenotype). However, with the emergence of the study of animal and plant physiology in the nineteenth century, this “holistic view” of the living world changed and was ultimately replaced by a reductionistic perspective. Here, I summarize the history of systems biology, i.e., the modern approach to understand living beings as integrative organisms, from genotype to phenotype. It is documented that the physiologists Claude Bernard and Julius Sachs, who studied humans and plants, respectively, were early pioneers of this discipline, which was formally founded 50 years ago. In 1968, two influential monographs, authored by Ludwig von Bertalanffy and Mihajlo D. Mesarovi?, were published, wherein a “systems theory of biology” was outlined. Definitions of systems biology are presented with reference to metabolic or cell signaling networks, analyzed via genomics, proteomics, and other methods, combined with computer simulations/mathematical modeling. Then, key insights of this discipline with respect to epiphytic microbes (Methylobacterium sp.) and simple bacteria (Mycoplasma sp.) are described. The principles of homeostasis, molecular systems energetics, gnotobiology, and holobionts (i.e., complexities of host–microbiota interactions) are outlined, and the significance of systems biology for evolutionary theories is addressed. Based on the microbe—Homo sapiens—symbiosis, it is concluded that human biology and health should be interpreted in light of a view of the biomedical sciences that is based on the holobiont concept.     

Single-stranded DNA binding protein facilitates specific enrichment of circular DNA molecules using rolling circle amplification

Many techniques in molecular biology require the use of pure nucleic acids in general and circular DNA (plasmid or mitochondrial) in particular. We have developed a method to separate these circular molecules from a mixture containing different species of nucleic acids using rolling circle amplification (RCA). RCA of plasmid or genomic DNA using random hexamers and bacteriophage Phi29 DNA polymerase has become increasingly popular for the amplification of template DNA in DNA sequencing protocols. Recently, we reported that the mutant single-stranded DNA binding protein (SSB) from Thermus thermophilus (TthSSB) HB8 eliminates nonspecific DNA products in RCA reactions. We developed this method for separating circular nucleic acids from a mixture having different species of nucleic acids. Use of the mutant TthSSB resulted in an enhancement of plasmid or mitochondrial DNA content in the amplified product by approximately 500×. The use of mutant TthSSB not only promoted the amplification of circular target DNA over the background but also could be used to enhance the amplification of circular targets over linear targets.     

Hybrid semi-parametric mathematical systems: bridging the gap between systems biology and process engineering

Systems biology is an integrative science that aims at the global characterization of biological systems. Huge amounts of data regarding gene expression, proteins activity and metabolite concentrations are collected by designing systematic genetic or environmental perturbations. Then the challenge is to integrate such data in a global model in order to provide a global picture of the cell. The analysis of these data is largely dominated by nonparametric modelling tools. In contrast, classical bioprocess engineering has been primarily founded on first principles models, but it has systematically overlooked the details of the embedded biological system. The full complexity of biological systems is currently assumed by systems biology and this knowledge can now be taken by engineers to decide how to optimally design and operate their processes. This paper discusses possible methodologies for the integration of systems biology and bioprocess engineering with emphasis on applications involving animal cell cultures. At the mathematical systems level, the discussion is focused on hybrid semi-parametric systems as a way to bridge systems biology and bioprocess engineering.     

Genomic insights into ayurvedic and western approaches to personalized medicine

Ayurveda, an ancient Indian system of medicine documented and practised since 1500 B.C., follows a systems approach that has interesting parallels with contemporary personalized genomic medicine approaches to the understanding and management of health and disease. It is based on the trisutra, which are the three aspects of causes, features and therapeutics that are interconnected through a common organizing principle termed ‘tridosha’. Tridosha comprise three ascertainable physiological entities; vata (kinetic), pitta (metabolic) and kapha (potential) that are pervasive across systems, work in conjunction with each other, respond to the external environment and maintain homeostasis. Each individual is born with a specific proportion of tridosha that are not only genetically determined but also influenced by the environment during foetal development. Jointly they determine a person’s basic constitution, which is termed their ‘prakriti’. Development and progression of different diseases with their subtypes are thought to depend on the origin and mechanism of perturbation of the doshas, and the aim of therapeutic practice is to ensure that the doshas retain their homeostatic state. Similarly, western systems biology epitomized by translational P4 medicine envisages the integration of multiscalar genetic, cellular, physiological and environmental networks to predict phenotypic outcomes of perturbations. In this perspective article, we aim to outline the shape of a unifying scaffold that may allow the two intellectual traditions to enhance one another. Specifically, we illustrate how a unique integrative ‘Ayurgenomics’ approach can be used to integrate the trisutra concept of Ayurveda with genomics. We observe biochemical and molecular correlates of prakriti and show how these differ significantly in processes that are linked to intermediate patho-phenotypes, known to take different course in diseases. We also observe a significant enrichment of the highly connected hub genes which could explain differences in prakriti, focussing on EGLN1, a key oxygen sensor that differs between prakriti types and is linked to high altitude adaptation. Integrating our observation with the current literature, we demonstrate how EGLN1 could qualify as a molecular equivalent of tridosha that can modulate different phenotypic outcomes, where hypoxia is a cause or a consequence both during health and diseased states. Our studies affirm that integration of the trisutra framework through Ayurgenomics can guide the identification of predisposed groups of individuals and enable discovery of actionable therapeutic points in an individualized manner.     

Genome-wide association studies and systems biology: together at last

Following the widespread use of genome-wide association studies to elucidate the genetic architectures of complex phenotypes, there has been a push to augment existing observational studies with additional layers of molecular information. The resulting high-dimensional data have led the emergence of research in integrative systems biology. Here, we examine recent progress in characterizing biological networks as well as the corresponding conceptual and analytical challenges. Using examples from metabolomics, we contend that integrative systems biology should prompt a re-examination of conventional phenotypic measures where heterogeneous or correlated phenotypes can be fine-mapped. Although still in its infancy, it is apparent that the large-scale characterization of molecular systems will transform our understanding of phenotype, biology and pathogenesis.     

More on how and why: cause and effect in biology revisited

In 1961, Ernst Mayr published a highly influential article on the nature of causation in biology, in which he distinguished between proximate and ultimate causes. Mayr argued that proximate causes (e.g. physiological factors) and ultimate causes (e.g. natural selection) addressed distinct ‘how’ and ‘why’ questions and were not competing alternatives. That distinction retains explanatory value today. However, the adoption of Mayr’s heuristic led to the widespread belief that ontogenetic processes are irrelevant to evolutionary questions, a belief that has (1) hindered progress within evolutionary biology, (2) forged divisions between evolutionary biology and adjacent disciplines and (3) obstructed several contemporary debates in biology. Here we expand on our earlier (Laland et al. in Science 334:1512–1516, 2011) argument that Mayr’s dichotomous formulation has now run its useful course, and that evolutionary biology would be better served by a concept of reciprocal causation, in which causation is perceived to cycle through biological systems recursively. We further suggest that a newer evolutionary synthesis is unlikely to emerge without this change in thinking about causation.     

DNA Codes and Information: Formal Structures and Relational Causes

Recently the terms "codes" and "information" as used in the context of molecular biology have been the subject of much discussion. Here I propose that a variety of structural realism can assist us in rethinking the concepts of DNA codes and information apart from semantic criteria. Using the genetic code as a theoretical backdrop, a necessary distinction is made between codes qua symbolic representations and information qua structure that accords with data. Structural attractors are also shown to be entailed by the mapping relation that any DNA code is a part of (as the domain). In this framework, these attractors are higher-order informational structures that obviate any "DNA-centric" reductionism. In addition to the implications that are discussed, this approach validates the array of coding systems now recognized in molecular biology.     

Translational systems biology of inflammation

Inflammation is a complex, multi-scale biologic response to stress that is also required for repair and regeneration after injury. Despite the repository of detailed data about the cellular and molecular processes involved in inflammation, including some understanding of its pathophysiology, little progress has been made in treating the severe inflammatory syndrome of sepsis. To address the gap between basic science knowledge and therapy for sepsis, a community of biologists and physicians is using systems biology approaches in hopes of yielding basic insights into the biology of inflammation. “Systems biology” is a discipline that combines experimental discovery with mathematical modeling to aid in the understanding of the dynamic global organization and function of a biologic system (cell to organ to organism). We propose the term translational systems biology for the application of similar tools and engineering principles to biologic systems with the primary goal of optimizing clinical practice. We describe the efforts to use translational systems biology to develop an integrated framework to gain insight into the problem of acute inflammation. Progress in understanding inflammation using translational systems biology tools highlights the promise of this multidisciplinary field. Future advances in understanding complex medical problems are highly dependent on methodological advances and integration of the computational systems biology community with biologists and clinicians.     

A personal view on systems medicine and the emergence of proactive P4 medicine: predictive, preventive, personalized and participatory

Systems biology and the digital revolution are together transforming healthcare to a proactive P4 medicine that is predictive, preventive, personalized and participatory. Systems biology - holistic, global and integrative in approach - has given rise to systems medicine, a systems approach to health and disease. Systems medicine promises to (1) provide deep insights into disease mechanisms, (2) make blood a diagnostic window for viewing health and disease for the individual, (3) stratify complex diseases into their distinct subtypes for a impedance match against proper drugs, (4) provide new approaches to drug target discovery and (5) generate metrics for assessing wellness. P4 medicine, the clinical face of systems medicine, has two major objectives: to quantify wellness and to demystify disease. Patients and consumers will be a major driver in the realization of P4 medicine through their participation in medically oriented social networks directed at improving their own healthcare. P4 medicine has striking implications for society - including the ability to turn around the ever-escalating costs of healthcare. The challenge in bringing P4 medicine to patients and consumers is twofold: first, inventing the strategies and technologies that will enable P4 medicine and second, dealing with the impact of P4 medicine on society - including key ethical, social, legal, regulatory, and economic issues. Managing the societal problems will pose the most significant challenges. Strategic partnerships of a variety of types will be necessary to bring P4 medicine to patients.     

Catenation and supercoiling in the products of bacteriophage λ integrative recombination in vitro

Catenanes (interlocked circular DNA molecules) are the exclusive products of the bacteriophage λ integrative recombination reaction in vitro when the substrate is a supercoiled DNA molecule containing both the attP and attB sites. It is proposed that the catenation results from the superhelical form of the substrate DNA. We also show that both circular DNA products of a single recombination event can be recovered as superhelical molecules with a superhelical density approximately that of the substrate DNA. The recombination reaction must therefore occur as a coupled process which does not permit free rotation around single-strand breaks at any stage.     

An Efficient Algorithm for Computing Attractors of Synchronous And Asynchronous Boolean Networks

Biological networks, such as genetic regulatory networks, often contain positive and negative feedback loops that settle down to dynamically stable patterns. Identifying these patterns, the so-called attractors, can provide important insights for biologists to understand the molecular mechanisms underlying many coordinated cellular processes such as cellular division, differentiation, and homeostasis. Both synchronous and asynchronous Boolean networks have been used to simulate genetic regulatory networks and identify their attractors. The common methods of computing attractors are that start with a randomly selected initial state and finish with exhaustive search of the state space of a network. However, the time complexity of these methods grows exponentially with respect to the number and length of attractors. Here, we build two algorithms to achieve the computation of attractors in synchronous and asynchronous Boolean networks. For the synchronous scenario, combing with iterative methods and reduced order binary decision diagrams (ROBDD), we propose an improved algorithm to compute attractors. For another algorithm, the attractors of synchronous Boolean networks are utilized in asynchronous Boolean translation functions to derive attractors of asynchronous scenario. The proposed algorithms are implemented in a procedure called geneFAtt. Compared to existing tools such as genYsis, geneFAtt is significantly faster in computing attractors for empirical experimental systems.

Availability

The software package is available at https://sites.google.com/site/desheng619/download.     

Biological systems modeling and analysis: a biomolecular technique of the twenty-first century.

It is proposed that computational systems biology should be considered a biomolecular technique of the twenty-first century, because it complements experimental biology and bioinformatics in unique ways that will eventually lead to insights and a depth of understanding not achievable without systems approaches. This article begins with a summary of traditional and novel modeling techniques. In the second part, it proposes concept map modeling as a useful link between experimental biology and biological systems modeling and analysis. Concept map modeling requires the collaboration between biologist and modeler. The biologist designs a regulated connectivity diagram of processes comprising a biological system and also provides semi-quantitative information on stimuli and measured or expected responses of the system. The modeler converts this information through methods of forward and inverse modeling into a mathematical construct that can be used for simulations and to generate and test new hypotheses. The biologist and the modeler collaboratively interpret the results and devise improved concept maps. The third part of the article describes software, BST-Box, supporting the various modeling activities.