Perspectives on the landscape and flux theory for describing emergent behaviors of the biological systems

We give a review on the landscape theory of the equilibrium biological systems and landscape-flux theory of the nonequilibrium biological systems as the global driving force. The emergences of the behaviors, the associated thermodynamics in terms of the entropy and free energy and dynamics in terms of the rate and paths have been quantitatively demonstrated. The hierarchical organization structures have been discussed. The biological applications ranging from protein folding, biomolecular recognition, specificity, biomolecular evolution and design for equilibrium systems as well as cell cycle, differentiation and development, cancer, neural networks and brain function, and evolution for nonequilibrium systems, cross-scale studies of genome structural dynamics and experimental quantifications/verifications of the landscape and flux are illustrated. Together, this gives an overall global physical and quantitative picture in terms of the landscape and flux for the behaviors, dynamics and functions of biological systems.

     

How Cancer Shapes Evolution and How Evolution Shapes Cancer

Evolutionary theories are critical for understanding cancer development at the level of species as well as at the level of cells and tissues, and for developing effective therapies. Animals have evolved potent tumor-suppressive mechanisms to prevent cancer development. These mechanisms were initially necessary for the evolution of multi-cellular organisms and became even more important as animals evolved large bodies and long lives. Indeed, the development and architecture of our tissues were evolutionarily constrained by the need to limit cancer. Cancer development within an individual is also an evolutionary process, which in many respects mirrors species evolution. Species evolve by mutation and selection acting on individuals in a population; tumors evolve by mutation and selection acting on cells in a tissue. The processes of mutation and selection are integral to the evolution of cancer at every step of multistage carcinogenesis, from tumor genesis to metastasis. Factors associated with cancer development, such as aging and carcinogens, have been shown to promote cancer evolution by impacting both mutation and selection processes. While there are therapies that can decimate a cancer cell population, unfortunately cancers can also evolve resistance to these therapies, leading to the resurgence of treatment-refractory disease. Understanding cancer from an evolutionary perspective can allow us to appreciate better why cancers predominantly occur in the elderly and why other conditions, from radiation exposure to smoking, are associated with increased cancers. Importantly, the application of evolutionary theory to cancer should engender new treatment strategies that could better control this dreaded disease.     

Human Cytokinome: a new challenge for systems biology

Cytokines play an important role in the evolution of inflammatory processes. Therefore, they are also key components of the cancer evolution, a disease recognized to depend on chronic inflammation. On the whole, we define cytokinome as the totality of these proteins and their interactions in and around biological cells. Understanding the complex interaction network of cytokines in patients affected from cancers should be very useful both to follow the cancer evolution from its early steps and to define innovative therapeutic strategies by using systems biology approaches.     

Temporal Ordering of Cancer Microarray Data through a Reinforcement Learning Based Approach

Temporal modeling and analysis and more specifically, temporal ordering are very important problems within the fields of bioinformatics and computational biology, as the temporal analysis of the events characterizing a certain biological process could provide significant insights into its development and progression. Particularly, in the case of cancer, understanding the dynamics and the evolution of this disease could lead to better methods for prediction and treatment. In this paper we tackle, from a computational perspective, the temporal ordering problem, which refers to constructing a sorted collection of multi-dimensional biological data, collection that reflects an accurate temporal evolution of biological systems. We introduce a novel approach, based on reinforcement learning, more precisely, on Q-learning, for the biological temporal ordering problem. The experimental evaluation is performed using several DNA microarray data sets, two of which contain cancer gene expression data. The obtained solutions are correlated either to the given correct ordering (in the cases where this is provided for validation), or to the overall survival time of the patients (in the case of the cancer data sets), thus confirming a good performance of the proposed model and indicating the potential of our proposal.     

Evolutionary biology of cancer

Cancer is driven by the somatic evolution of cell lineages that have escaped controls on replication and by the population-level evolution of genes that influence cancer risk. We describe here how recent evolutionary ecological studies have elucidated the roles of predation by the immune system and competition among normal and cancerous cells in the somatic evolution of cancer. Recent analyses of the evolution of cancer at the population level show how rapid changes in human environments have augmented cancer risk, how strong selection has frequently led to increased cancer risk as a byproduct, and how anticancer selection has led to tumor-suppression systems, tissue designs that slow somatic evolution, constraints on morphological evolution and even senescence itself. We discuss how applications of the tools of ecology and evolutionary biology are poised to revolutionize our understanding and treatment of this disease.     

Sources of spontaneous mutagenesis in bacteria

Mutations in an organism’s genome can arise spontaneously, that is, in the absence of exogenous stress and prior to selection. Mutations are often neutral or deleterious to individual fitness but can also provide genetic diversity driving evolution. Mutagenesis in bacteria contributes to the already serious and growing problem of antibiotic resistance. However, the negative impacts of spontaneous mutagenesis on human health are not limited to bacterial antibiotic resistance. Spontaneous mutations also underlie tumorigenesis and evolution of drug resistance. To better understand the causes of genetic change and how they may be manipulated in order to curb antibiotic resistance or the development of cancer, we must acquire a mechanistic understanding of the major sources of mutagenesis. Bacterial systems are particularly well-suited to studying mutagenesis because of their fast growth rate and the panoply of available experimental tools, but efforts to understand mutagenic mechanisms can be complicated by the experimental system employed. Here, we review our current understanding of mutagenic mechanisms in bacteria and describe the methods used to study mutagenesis in bacterial systems.     

非线性森林发展系统研究进展

就近年来国内外对非线性森林发展系统的研究进展做一综述，介绍了一些非线性森林发展系统模型，分析了非线性森林系统的研究结果。     

Evolution of ABC transporters by gene duplication and their role in human disease

The ATP-binding cassette (ABC) transporter genes represent the largest family of transporters and these genes are abundant in the genome of all vertebrates. Through analysis of the genome sequence databases we have characterized the full complement of ABC genes from several mammals and other vertebrates. Multiple gene duplication and deletion events were identified in ABC genes in different lineages indicating that the process of gene evolution is still ongoing. Gene duplication resulting in either gene birth or gene death plays a major role in the evolution of the vertebrate ABC genes. The understanding of this mechanism is important in the context of human health because these ABC genes are associated with human disease, involving nearly all organ systems of the body. In addition, ABC genes play an important role in the development of drug resistance in cancer cells. Future genetic, functional, and evolutionary studies of ABC transporters will provide important insight into human and animal biology.     

Cancer in light of experimental evolution

Cancer initiation, progression, and the emergence of therapeutic resistance are evolutionary phenomena of clonal somatic cell populations. Studies in microbial experimental evolution and the theoretical work inspired by such studies are yielding deep insights into the evolutionary dynamics of clonal populations, yet there has been little explicit consideration of the relevance of this rapidly growing field to cancer biology. Here, we examine how the understanding of mutation, selection, and spatial structure in clonal populations that is emerging from experimental evolution may be applicable to cancer. Along the way, we discuss some significant ways in which cancer differs from the model systems used in experimental evolution. Despite these differences, we argue that enhanced prediction and control of cancer may be possible using ideas developed in the context of experimental evolution, and we point out some prospects for future research at the interface between these traditionally separate areas.     

Delineating the longitudinal tumor evolution using organoid models

Cancer is an evolutionary process fueled by genetic or epigenetic alterations in the genome. Understanding the evolutionary dynamics that are operative at different stages of tumor progression might inform effective strategies in early detection, diagnosis, and treatment of cancer. However, our understanding on the dynamics of tumor evolution through time is very limited since it is usually impossible to sample patient tumors repeatedly. The recent advances in in vitro 3D organoid culture technologies have opened new avenues for the development of more realistic human cancer models that mimic many in vivo biological characteristics in human tumors. Here, we review recent progresses and challenges in cancer genomic evolution studies and advantages of using tumor organoids to study cancer evolution. We propose to establish an experimental evolution model based on continuous passages of patient-derived organoids and longitudinal sampling to study clonal dynamics and evolutionary patterns over time. Development and integration of population genetic theories and computational models into time-course genomic data in tumor organoids will help to pinpoint the key cellular mechanisms underlying cancer evolutionary dynamics, thus providing novel insights on therapeutic strategies for highly dynamic and heterogeneous tumors.     

流域水电开发对干热河谷社会-生态系统的影响及意义

西南干热河谷是我国重要生态脆弱区和经济发展落后区,流域大型水电开发是干热河谷重要的人类干扰活动,对生态脆弱区的社会-生态系统造成极大影响。社会-生态系统演变的方向和规律具有复杂性和非线性变化,又涉及到生态保护修复、能源安全、经济发展和乡村振兴等国家重大需求,因此,亟待加强流域社会-生态系统演变和驱动机制方面的研究。通过总结当前研究的进展和不足,提出了加强生态系统演变的长期监测和分析、深入研究流域社会经济演变规律和驱动机制、完善流域生态资产价值评估和生态补偿机制、构建流域社会-生态系统耦合理论与方法等对策建议,从而为脆弱生态区未来可持续发展提供科技支撑。     

The evolution of tumor metastases during clonal expansion

Cancer is a leading cause of morbidity and mortality in many countries. Solid tumors generally initiate at one particular site called the primary tumor, but eventually disseminate and form new colonies in other organs. The development of such metastases greatly diminishes the potential for a cure of patients and is thought to represent the final stage of the multi-stage progression of human cancer. The concept of early metastatic dissemination, however, postulates that cancer cell spread might arise early during the development of a tumor. It is important to know whether metastases are present at diagnosis since this determines treatment strategies and outcome. In this paper, we design a stochastic mathematical model of the evolution of tumor metastases in an expanding cancer cell population. We calculate the probability of metastasis at a given time during tumor evolution, the expected number of metastatic sites, and the total number of cancer cells as well as metastasized cells. Furthermore, we investigate the effect of drug administration and tumor resection on these quantities and predict the survival time of cancer patients. The model presented in this paper allows us to determine the probability and number of metastases at diagnosis and to identify the optimum treatment strategy to maximally prolong survival of cancer patients.     

Evolving concepts of tumor heterogeneity

Past and recent findings on tumor heterogeneity have led clinicians and researchers to broadly define cancer development as an evolving process. This evolutionary model of tumorigenesis has largely been shaped by seminal reports of fitness-promoting mutations conferring a malignant cellular phenotype. Despite the major clinical and intellectual advances that have resulted from studying heritable heterogeneity, it has long been overlooked that compositional tumor heterogeneity and tumor microenvironment (TME)-induced selection pressures drive tumor evolution, significantly contributing to tumor development and outcomes of clinical cancer treatment. In this review, we seek to summarize major milestones in tumor evolution, identify key aspects of tumor heterogeneity in a TME-dependent evolutionary context, and provide insights on the clinical challenges facing researchers and clinicians alike.     

Long-term (trophic) purinergic signalling: purinoceptors control cell proliferation, differentiation and death

The purinergic signalling system, which uses purines and pyrimidines as chemical transmitters, and purinoceptors as effectors, is deeply rooted in evolution and development and is a pivotal factor in cell communication. The ATP and its derivatives function as a ‘danger signal'' in the most primitive forms of life. Purinoceptors are extraordinarily widely distributed in all cell types and tissues and they are involved in the regulation of an even more extraordinary number of biological processes. In addition to fast purinergic signalling in neurotransmission, neuromodulation and secretion, there is long-term (trophic) purinergic signalling involving cell proliferation, differentiation, motility and death in the development and regeneration of most systems of the body. In this article, we focus on the latter in the immune/defence system, in stratified epithelia in visceral organs and skin, embryological development, bone formation and resorption, as well as in cancer.     

Rise of the RNA Machines: Exploring the Structure of Long Non-Coding RNAs

Novel, profound and unexpected roles of long non-coding RNAs (lncRNAs) are emerging in critical aspects of gene regulation. Thousands of lncRNAs have been recently discovered in a wide range of mammalian systems, related to development, epigenetics, cancer, brain function and hereditary disease. The structural biology of these lncRNAs presents a brave new RNA world, which may contain a diverse zoo of new architectures and mechanisms. While structural studies of lncRNAs are in their infancy, we describe existing structural data for lncRNAs, as well as crystallographic studies of other RNA machines and their implications for lncRNAs. We also discuss the importance of dynamics in RNA machine mechanism. Determining commonalities between lncRNA systems will help elucidate the evolution and mechanistic role of lncRNAs in disease, creating a structural framework necessary to pursue lncRNA-based therapeutics.     

The century for cytopathology

By the end of the 19th century, exfoliated cancer cells had been described in all of the types of specimen in which we find them today. However, it was not until Drs. Papanicolaou and Traut published their account of the diagnosis of uterine cancer from exfoliated cells (1941 and 1943) that cytopathology acquired the momentum to develop into the powerful presence that it has in human medicine today. These and the subsequent publications by Papanicolaou stimulated the development and application of cytopathology worldwide, resulting in abundant literature on the subject and a galaxy of outstanding practitioners. The 1980s saw the development and widespread use of aspiration cytology. This was followed in the 1990s by the development of automated screening systems, marking the latest stage in the evolution of cytopathology. These and other events and achievements in cytopathology, from its meager beginnings in the early 20th century to its worldwide use and acceptance today, mark this century as the "century for cytopathology."     

Macro- and microevolution of bacteria in symbiotic systems

Using the examples of diverse interactions among prokaryotes and eukaryotes, the relationships between molecular and population mechanisms of evolution of symbiotic bacteria are addressed. Their circulation in host-environment systems activates microevolutionary factors that direct combinative or reductive genome evolution in facultative, ecologically obligatory, and genetically obligatory symbioses. Due to intense systemic intra-genome rearrangements and horizontal gene transfer, two types of gene systems evolve in these bacteria: (1) controlling the pathogenesis-like processes of host recognition and penetration and (2) responsible for mutualistic interactions that are related to nitrogen fixation and its transfer to the host. The evolution of gene systems of type 1 is directed by individual (Darwinian, frequency-dependent) selection, which is responsible for gene-for-gene interactions between the partners. In the evolution of the type 2 systems, group (interdeme, kin) selection plays the key role, being responsible for the development of bacterial traits beneficial for the host. Using the legume--rhizobia symbiosis as an example, it is shown that evolution of mutualism can be described in terms of biological altruism, whose regularities are common for intraspecific and interspecific relationships. Macroevolutionary rearrangements of bacterial genomes result from the structural changes in their populations, wherein various selection modes are combined with stochastic processes (genetic drift, population waves) induced in the symbiotic systems.     

Migration-Induced Architectures of Planetary Systems

The recent increase in number of known multi-planet systems gives a unique opportunity to study the processes responsible for planetary formation and evolution. Special attention is given to the occurrence of mean-motion resonances, because they carry important information about the history of the planetary systems. At the early stages of the evolution, when planets are still embedded in a gaseous disc, the tidal interactions between the disc and planets cause the planetary orbital migration. The convergent differential migration of two planets embedded in a gaseous disc may result in the capture into a mean-motion resonance. The orbital migration taking place during the early phases of the planetary system formation may play an important role in shaping stable planetary configurations. An understanding of this stage of the evolution will provide insight on the most frequently formed architectures, which in turn are relevant for determining the planet habitability. The aim of this paper is to present the observational properties of these planetary systems which contain confirmed or suspected resonant configurations. A complete list of known systems with such configurations is given. This list will be kept by us updated from now on and it will be a valuable reference for studying the dynamics of extrasolar systems and testing theoretical predictions concerned with the origin and the evolution of planets, which are the most plausible places for existence and development of life.     

Questions regarding the predictive value of one evolved complex adaptive system for a second: Exemplified by the SOD1 mouse

We surveyed the scientific literature regarding amyotrophic lateral sclerosis, the SOD1 mouse model, complex adaptive systems, evolution, drug development, animal models, and philosophy of science in an attempt to analyze the SOD1 mouse model of amyotrophic lateral sclerosis in the context of evolved complex adaptive systems.