Hundreds, may be even thousands of research laboratories in the world have very successfully investigated the physiology, biochemistry, metabolic abilities, and molecular genetics of Escherichia coli and other bacterial species. Despite this wealth of information, it remains extremely difficult to predict the effect of any environmental stress or any particular mutation on the overall behavior of a bacterial population. The outcome of a competition between two genotypes in a particular environment, apart from very trivial cases, is also almost impossible to foresee, leave alone competitions within a complex bacterial population.
This situation prevails because of the high complexity of the bacterial cell, with subtle quantitative variations of different molecules having important effects on the bacterial response to various environmental and genetic fluctuations. The overall behavior of any living organism is indeed based on complex connections between so-called global regulators of gene expression. The highly interdigitated relationships within this regulatory network makes any prediction highly speculative. On the other hand, the development of new technologies, such as DNA chips or proteomics, open the way for accumulating vast amounts of data. Computer applications help to class and interpret these data, thus facilitating the construction of functional models of the biological system. However, only the comparison of the predicted with the observed behavior of the system can assertain the validity of a model or suggest alternative explanations. The simulation of genetic and biochemical networks will therefore represent a new way of answering fundamental questions in biology.
This review will briefly summarize some complex regulatory pathways. The aim is not to draw detailed schemes of these networks, but rather to highlight their high connectivity. Their behavior in response to various stresses is therefore very difficult to predict. Two examples of computational simulations of selected regulatory networks will be briefly described.