The bottom–up approach to defining life: deciphering the functional organization of biological cells via multi-objective representation of biological complexity from molecules to cells

Abstract

In silico representation of cellular systems needs to represent the adaptive dynamics of biological cells, recognizing a cell's multi-objective topology formed by temporally cohesive intracellular structures. The design of these models needs to address the hierarchical and concurrent nature of cellular functions and incorporate the ability to self-organize in response to transitions between healthy and pathological phases, and adapt accordingly. The functions of biological systems are constantly progressing, due to the ever changing demands of their environment. Biological systems meet these demands by pursuing objectives, aided by their constituents, giving rise to biological functions. A biological cell is organized into an objective/task hierarchy. These objective hierarchy corresponds to the nested nature of temporally cohesive structures and representing them will facilitate in studying pleiotropy and polygeny by modeling causalities propagating across multiple interconnected intracellular processes. Although biological adaptations occur in physiological, developmental and reproductive timescales, the paper is focused on adaptations that occur within physiological timescales, where the biomolecular activities contributing to functional organization, play a key role in cellular physiology. The paper proposes a multi-scale and multi-objective modeling approach from the bottom–up by representing temporally cohesive structures for multi-tasking of intracellular processes. Further the paper characterizes the properties and constraints that are consequential to the adaptive dynamics in biological cells.

Chronic diseases like asthma and COPD: do they truly exist?

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Relevance of Systems Biology to Respiratory Medicine

“…In theory, this holistic, integrative, and dynamic view does not need to be restricted to the molecular biological level and could be used also at the cell level, organ level, or even combining different levels in the same analysis. Multi-level profiling of high-throughput molecular platforms in combination with clinical profiles (i.e., multi-level systems biology) is obviously much more informative but, at the same time, much more complex 11 , so most currently available publications of applications of systems biology to human diseases focus on the molecular level. The methodology, application, and proper validation of this multi-level approach is still, for the most part, in its infancy 11 .…”

“…Multi-level profiling of high-throughput molecular platforms in combination with clinical profiles (i.e., multi-level systems biology) is obviously much more informative but, at the same time, much more complex 11 , so most currently available publications of applications of systems biology to human diseases focus on the molecular level. The methodology, application, and proper validation of this multi-level approach is still, for the most part, in its infancy 11 . Further, it is absolutely necessary to validate such complex results rigorously.…”

“…In biology, the "level" of a "complex system" so defined can range from the molecular, subcellular, and cellular level to organ and organism physiology or even the totality of environmental exposures or exposome 10 , and include all or part of these different levels 1,2 . To date, however, complex systems have been mostly studied at the cellular level 11 . Within this "organizational space", they have the following properties: (i) a hierarchical but concurrent nature of cellular functions 11 ; (ii) adaptive dynamics that incorporate the ability to self-organize in response to transitions between healthy and pathological conditions 11 ; (iii) non-linear relationships between the different elements of the system 12,13 ; and, (iv) emergent properties, that is, one or more properties that cannot be attributed to any element of the system considered separately 3,14 .…”

“…To date, however, complex systems have been mostly studied at the cellular level 11 . Within this "organizational space", they have the following properties: (i) a hierarchical but concurrent nature of cellular functions 11 ; (ii) adaptive dynamics that incorporate the ability to self-organize in response to transitions between healthy and pathological conditions 11 ; (iii) non-linear relationships between the different elements of the system 12,13 ; and, (iv) emergent properties, that is, one or more properties that cannot be attributed to any element of the system considered separately 3,14 . For instance, a plane is a complex (mechanical, not biological) system, composed of many different elements (or nodes), such as wings, engines, wheels, fuel, pilots, so on.…”