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Moreover, this can also be used to define life as we know it very well. Our earthly life

understands the genetic language of DNA.

The nice thing about this definition is that it can of course be extended to any other kind

of life. But this (e.g. synthetic life; Bedau 2003) would then again use other storage mol­

ecules (e.g. PNA, so-called peptide nucleic acids; Nielsen et al. 1991; Nelson et al. 2000)

because of “once-for-all selection” (Eigen and Schuster 1979; Eigen and Winkler 1975)

during natural emergence. One then defines for these other types of living organisms again

central storage molecules, survival-coded, cellular processes and analyzes the contextual­

ity of the remaining molecules in the cell and what this then implies again evolution,

metabolism and replication.

Conclusion

• Life is always developing new information in dialogue with the environment. It

is important to see that all molecules of a cell are closely related to each other and

help together so that all processes run in an orderly manner and metabolism and

signalling cascades united help that the cell has optimal chances of survival. Only

this contextual information has real meaning. It conveys the behavior of the cell

that is important and correct for survival. Misprints are constantly selected away

in the population.

• Molecular words only ever make sense in the context of the cell. Database

searches and sequence comparisons reveal the biological meaning (in practice,

usually the function of the compared molecule). This is strongly linked to

sequence elements and a defined structure. Random sequences usually do not

make biological sense. Fascinatingly, this allows me to model in detail, for exam­

ple, how antibiotic resistance develops in bacteria (combination of protein struc­

ture and phylogenetic tree analysis) or how a protein code is optimally formulated

for an organism (for example, if I want to produce insulin with optimal yield).

• The contextuality of biological information is repeated at all levels. The domains

in an enzyme relate to each other, e.g. in glutathione reductase: To the catalytic

domain there are the matching two cofactor domains (for FAD, NAD), the opti­

mal regulatory domain and also the dimerization domain, otherwise the enzyme

would not function. Similarly, I check the consistency of sequence analyses.

Everything must fit together; if contradictions arise, one of the partial analysisv

results was not yet correctly classified. Since everything relates correctly to each

other at the protein network level, there is considerable biological redundancy

and robustness. This can be deciphered by network analyses to very efficiently

identify central proteins (hubs), signaling cascades and interfering signals, and

modifying input (cross-talk). A fascinating and illustrative example are the

KEGG maps of cancer pathways.

12  Life Continuously Acquires New Information in Dialogue with the Environment