Cancer as a dynamical phase transition

Background

We review and extend the work of Rosen and Casti who discuss category theory with regards to systems biology and manufacturing systems, respectively.

Results

We describe anticipatory systems, or long-range feed-forward chemical reaction chains, and compare them to open-loop manufacturing processes. We then close the loop by discussing metabolism-repair systems and describe the rationality of the self-referential equation f = f (f). This relationship is derived from some boundary conditions that, in molecular systems biology, can be stated as the cardinality of the following molecular sets must be about equal: metabolome, genome, proteome. We show that this conjecture is not likely correct so the problem of self-referential mappings for describing the boundary between living and nonliving systems remains an open question. We calculate a lower and upper bound for the number of edges in the molecular interaction network (the interactome) for two cellular organisms and for two manufacturomes for CMOS integrated circuit manufacturing.

Conclusions

We show that the relevant mapping relations may not be Abelian, and that these problems cannot yet be resolved because the interactomes and manufacturomes are incomplete.     

Biology of Extreme Radiation Resistance: The Way of Deinococcus radiodurans

The bacterium Deinococcus radiodurans is a champion of extreme radiation resistance that is accounted for by a highly efficient protection against proteome, but not genome, damage. A well-protected functional proteome ensures cell recovery from extensive radiation damage to other cellular constituents by molecular repair and turnover processes, including an efficient repair of disintegrated DNA. Therefore, cell death correlates with radiation-induced protein damage, rather than DNA damage, in both robust and standard species. From the reviewed biology of resistance to radiation and other sources of oxidative damage, we conclude that the impact of protein damage on the maintenance of life has been largely underestimated in biology and medicine.Several recent reviews comprehensively present the extraordinary bacterium Deinococcus radiodurans, best known for its biological robustness involving an extremely efficient DNA repair system (Cox and Battista 2005; Blasius et al. 2008; Daly 2009; Slade and Radman 2011). The aim of this short review of the biology of D. radiodurans is to single out a general concept of the primacy of biological function (proteome) over information (genome) in the maintenance of life. A cell dies when its vital functions performed by the proteome cease, for example, because of the direct loss of proteome functionality or via the loss of membrane integrity, whereas genome integrity is required (in addition to an active proteome) for the perpetuation of cells that have survived. But survival itself depends primarily on the proteome rather than the genome. A cell that instantly loses its genome can function for some time, unlike one that loses its proteome. In other words, the proteome sustains and maintains life, whereas the genome ensures the perpetuation of life by renewing the proteome, a process contingent on a preexisting proteome that repairs, replicates, and expresses the genome. In addition to the functional integrity of the proteome, small metabolites and other cofactors for catalysis and protein interactions are equally important for proteome functionality. However, chemical damage to cofactors is not a likely primary bottleneck in survival because of their high molar concentrations, compared with proteins. And, finally, it is the proteome that synthesizes metabolites and imports vital metal cofactors and ions. Although obvious, the concept that the prime target in cell degeneracy and death is proteome activity—ensuring all vital functions including genome integrity—is conspicuously absent in biological and medical sciences. This overview of the biology of a prokaryotic cell that survives conditions lethal to other species is to define and elaborate a general concept of sustainability of life that applies to all living cells.     

Proteomics in radiation research: present status and future perspectives

Rapidly developing postgenome research has made proteins an attractive target for biological analysis. The well-established term of proteome is defined as the complete set of proteins expressed in a given cell, tissue or organism. Unlike the genome, a proteome is rapidly changing as it tends to adapt to microenvironmental signals. The systematic analysis of the proteome at a given time and state is referred to as proteomics. This technique provides information on the molecular and cellular mechanisms that regulate physiology and pathophysiology of the cell. Applications of proteome profiling in radiation research are increasing. However, the large-scale proteomics data sets generated need to be integrated into other fields of radiation biology to facilitate the interpretation of radiation-induced cellular and tissue effects. The aim of this review is to introduce the most recent developments in the field of radiation proteomics.     

Network biology methods integrating biological data for translational science

The explosion of biomedical data, both on the genomic and proteomic side as well as clinical data, will require complex integration and analysis to provide new molecular variables to better understand the molecular basis of phenotype. Currently, much data exist in silos and is not analyzed in frameworks where all data are brought to bear in the development of biomarkers and novel functional targets. This is beginning to change. Network biology approaches, which emphasize the interactions between genes, proteins and metabolites provide a framework for data integration such that genome, proteome, metabolome and other -omics data can be jointly analyzed to understand and predict disease phenotypes. In this review, recent advances in network biology approaches and results are identified. A common theme is the potential for network analysis to provide multiplexed and functionally connected biomarkers for analyzing the molecular basis of disease, thus changing our approaches to analyzing and modeling genome- and proteome-wide data.     

Targeted and proteome-wide analysis of metabolite–protein interactions

Understanding the molecular mechanisms of endogenous and environmental metabolites is crucial for basic biology and drug discovery. With the genome, proteome, and metabolome of many organisms being readily available, researchers now have the opportunity to dissect how key metabolites regulate complex cellular pathways in vivo. Nonetheless, characterizing the specific and functional protein targets of key metabolites associated with specific cellular phenotypes remains a major challenge. Innovations in chemical biology are now poised to address this fundamental limitation in physiology and disease. In this review, we highlight recent advances in chemoproteomics for targeted and proteome-wide analysis of metabolite–protein interactions that have enabled the discovery of unpredicted metabolite–protein interactions and facilitated the development of new small molecule therapeutics.     

代谢组及其在真菌研究中的应用

代谢组学是利用现代分析化学手段对一定条件下生物体内小分子代谢产物（初级和次级代谢产物）定性及定量,从而揭示生命现象及其内在规律的学科。相对于基因组、转录组和蛋白质组,代谢组是一定条件下生物学过程完成后的最终代谢产物的集合,因而是各种组学研究中最接近表型的一种组学,可以直接动态地反映出细胞的生理生化过程,从而有效地检测和发现特定的生化途径,准确地解释生理或者病理现象。代谢组学作为系统生物学中基因组学、转录组学以及蛋白质组学三大组学的延伸和补充,是目前的研究热点之一。目前代谢组学在真菌领域的研究得到日益重视和发展。本文首先从历史发展和技术路线简述了代谢组学的发展历程和常见的代谢组学研究方法。接着从真菌的分类鉴定、生物膜研究、代谢途径、代谢工程、天然产物发现与植物互作这6个方面介绍了代谢组学在真菌研究领域的应用。     

The synthesis of artificial genome as the basis of synthetic biology

Recent achievements in the whole-genome sequencing especially viral and bacterial ones together with the development of methods of bioinformatics and molecular biology, have created preconditions for transition from synthesis of genes to assembly of the whole genomes based on chemically synthesized blocks, oligonucleotides. The creation of artificial genomes and artificial cells will undoubtedly render huge influence on a deepening of knowledge on mechanisms of functioning of living systems at a cellular level, on a way of origin and evolution of life, and also on biotechnology of the future, and will generate preconditions for the further development of synthetic biology and nanobiotechnology.     

Identification of biomarkers for bull fertility using functional genomics

Prediction of bull fertility is critical for the sustainability of both dairy and beef cattle production. Even though bulls produce ample amounts of sperm with normal parameters, some bulls may still suffer from subpar fertility. This causes major economic losses in the cattle industry because using artificial insemination, semen from one single bull can be used to inseminate hundreds of thousands of cows. Although there are several traditional methods to estimate bull fertility, such methods are not sufficient to explain and accurately predict the subfertility of individual bulls. Since fertility is a complex trait influenced by a number of factors including genetics, epigenetics, and environment, there is an urgent need for a comprehensive methodological approach to clarify uncertainty in male subfertility. The present review focuses on molecular and functional signatures of bull sperm associated with fertility. Potential roles of functional genomics (proteome, small noncoding RNAs, lipidome, metabolome) on determining male fertility and its potential as a fertility biomarker are discussed. This review provides a better understanding of the molecular signatures of viable and fertile sperm cells and their potential to be used as fertility biomarkers. This information will help uncover the underlying reasons for idiopathic subfertility.     

Modularity: a new perspective in biology

Several decades of research in biochemistry and molecular biology have been devoted for studies on isolated enzymes and proteins. Recent high throughput technologies in genomics and proteomics have resulted in avalanche of information about several genes, proteins and enzymes in variety of living systems. Though these efforts have greatly contributed to the detailed understanding of a large number of individual genes and proteins, this explosion of information has simultaneously brought out the limitations of reductionism in understanding complex biological processes. The genes or gene products do not function in isolation in vivo. A delicate and dynamic molecular architecture is required for precision of the chemical reactions associated with "life". In future, a paradigm shift is, therefore, envisaged, in biology leading to exploration of molecular organizations in physical and genomic context, a subtle transition from conventional molecular biology to modular biology. A module can be defined as an organization of macromolecules performing a synchronous function in a given metabolic pathway. In modular biology, the biological processes of interest are explored as complex systems of functionally interacting macromolecules. The present article describes the perceptions of the concept of modularity, in terms of associations among genes and proteins, presenting a link between reductionist approach and system biology.