Computing life: Add logos to biology and bios to physics

Kolodkin, Alexey; Simeonidis, Evangelos; Westerhoff, Hans V.

doi:10.1016/j.pbiomolbio.2012.10.003

Cited by 9 publications

(7 citation statements)

References 27 publications

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“…Metabolic control analysis has shown experimentally that control in intracellular networks tends to be distributed (536), that some of the key proteins and genes in E. coli failed to exercise control of the growth rate (161,398), and that such control may be distributed even among various levels in an intracellular hierarchy (537), and a combined experimental and modeling approach showed that all of this also seems to apply to ammonium assimilation (44,161). Living organisms are irreducibly (though not infinitely) complex (538,539); their analysis should be made as simple as possible but not simpler.…”

Section: The Metabolic Nitrogen State Of Cellsmentioning

confidence: 99%

“…This picture is based mainly on in vitro knowledge gathered in biochemical experiments with purified enzymes and by simplifications, typically neglecting the smaller of two parallel activities that might well be active simultaneously, as more often, Occam's razor may be deceptive in biology (538,539): that a simple explanation at first glance looks plausible enough to be real is insufficient for living organisms with their networks of irreducible core complexity.…”

Section: Gs-gogat Activity Under Conditions Of Internal Nitrogen Suffmentioning

confidence: 99%

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Nitrogen Assimilation in Escherichia coli: Putting Molecular Data into a Systems Perspective

Heeswijk¹,

Westerhoff

Boogerd³

2013

Microbiol Mol Biol Rev

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228

246

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SUMMARY We present a comprehensive overview of the hierarchical network of intracellular processes revolving around central nitrogen metabolism in Escherichia coli . The hierarchy intertwines transport, metabolism, signaling leading to posttranslational modification, and transcription. The protein components of the network include an ammonium transporter (AmtB), a glutamine transporter (GlnHPQ), two ammonium assimilation pathways (glutamine synthetase [GS]-glutamate synthase [glutamine 2-oxoglutarate amidotransferase {GOGAT}] and glutamate dehydrogenase [GDH]), the two bifunctional enzymes adenylyl transferase/adenylyl-removing enzyme (ATase) and uridylyl transferase/uridylyl-removing enzyme (UTase), the two trimeric signal transduction proteins (GlnB and GlnK), the two-component regulatory system composed of the histidine protein kinase nitrogen regulator II (NRII) and the response nitrogen regulator I (NRI), three global transcriptional regulators called nitrogen assimilation control (Nac) protein, leucine-responsive regulatory protein (Lrp), and cyclic AMP (cAMP) receptor protein (Crp), the glutaminases, and the nitrogen-phosphotransferase system. First, the structural and molecular knowledge on these proteins is reviewed. Thereafter, the activities of the components as they engage together in transport, metabolism, signal transduction, and transcription and their regulation are discussed. Next, old and new molecular data and physiological data are put into a common perspective on integral cellular functioning, especially with the aim of resolving counterintuitive or paradoxical processes featured in nitrogen assimilation. Finally, we articulate what still remains to be discovered and what general lessons can be learned from the vast amounts of data that are available now.

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Section: The Metabolic Nitrogen State Of Cellsmentioning

confidence: 99%

Section: Gs-gogat Activity Under Conditions Of Internal Nitrogen Suffmentioning

confidence: 99%

Nitrogen Assimilation in Escherichia coli: Putting Molecular Data into a Systems Perspective

Heeswijk¹,

Westerhoff

Boogerd³

2013

Microbiol Mol Biol Rev

Self Cite

228

246

View full text Add to dashboard Cite

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“…The more state-dependent information we need, the stronger the emergence is. The degree of state-dependency of the component property is determined by the presence of other components in the system affecting this property, on the flux of matter through the system and on the history of the system (Kolodkin et al, 2012a,b, 2013b). In this context, we can scale and compare the strength of emergence of intelligence for different complex adaptive systems, e.g., for microorganisms, animals or humans.…”

Section: Learning From Intelligence In the Microbial Worldmentioning

confidence: 99%

Macromolecular networks and intelligence in microorganisms

Westerhoff¹,

Brooks²,

Simeonidis³

et al. 2014

Front. Microbiol.

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Living organisms persist by virtue of complex interactions among many components organized into dynamic, environment-responsive networks that span multiple scales and dimensions. Biological networks constitute a type of information and communication technology (ICT): they receive information from the outside and inside of cells, integrate and interpret this information, and then activate a response. Biological networks enable molecules within cells, and even cells themselves, to communicate with each other and their environment. We have become accustomed to associating brain activity – particularly activity of the human brain – with a phenomenon we call “intelligence.” Yet, four billion years of evolution could have selected networks with topologies and dynamics that confer traits analogous to this intelligence, even though they were outside the intercellular networks of the brain. Here, we explore how macromolecular networks in microbes confer intelligent characteristics, such as memory, anticipation, adaptation and reflection and we review current understanding of how network organization reflects the type of intelligence required for the environments in which they were selected. We propose that, if we were to leave terms such as “human” and “brain” out of the defining features of “intelligence,” all forms of life – from microbes to humans – exhibit some or all characteristics consistent with “intelligence.” We then review advances in genome-wide data production and analysis, especially in microbes, that provide a lens into microbial intelligence and propose how the insights derived from quantitatively characterizing biomolecular networks may enable synthetic biologists to create intelligent molecular networks for biotechnology, possibly generating new forms of intelligence, first in silico and then in vivo.

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“…Feedback between the participants at several levels -with oscillations being inherent in the dynamics of this feedback in order to guarantee stability. This rule defines the "first law of system biology": Any complex biological event involves activity at many levels and the properties that emerge from this activity are not necessarily predictable (Kolodkin et al, 2012). .…”

Section: The Wandering Logic Intelligence (Wli)mentioning

confidence: 99%

“…Complementarity is ubiquitous in living systems, because it provides the physicochemical basis for modular, hierarchical ordering and replication necessary for the evolution of the chemical systems upon which life is based (Root-Bernstein & Dillon, 1997;Root-Bernstein, 2012b). Recently, (Kolodkin et al, 2012) argued for replacing the tradition of Occam's razor in science (reflecting the intention to model the system as simply as possible) with a 'law of completeness'.…”

Section: What Is Missing In Current Theoretical Biology?mentioning

confidence: 99%