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Motivation: Time-series observations from reporter gene experiments are commonly used for inferring and analyzing dynamical models of regulatory networks. The robust estimation of promoter activities and protein concentrations from primary data is a difficult problem due to measurement noise and the indirect relation between the measurements and quantities of biological interest. Results: We propose a general approach based on regularized linear inversion to solve a range of estimation problems in the analysis of reporter gene data, notably the inference of growth rate, promoter activity, and protein concentration profiles. We evaluate the validity of the approach using in silico simulation studies, and observe that the methods are more robust and less biased than indirect approaches usually encountered in the experimental literature based on smoothing and subsequent processing of the primary data. We apply the methods to the analysis of fluorescent reporter gene data acquired in kinetic experiments with Escherichia coli. The methods are capable of reliably reconstructing time-course profiles of growth rate, promoter activity and protein concentration from weak and noisy signals at low population volumes. Moreover, they capture critical features of those profiles, notably rapid changes in gene expression during growth transitions. [ABSTRACT FROM AUTHOR]

Motivation: Fluorescent and luminescent reporter gene systems in combination with automated microplate readers allow real-time monitoring of gene expression on the population level at high precision and sampling density. This generates large amounts of data for the analysis of which computer tools are missing to date. Results: We have developed WellReader, a MATLAB program for the analysis of fluorescent and luminescent reporter gene data. WellReader allows the user to load the output files of microplate readers, remove outliers, correct for background effects and smooth and fit the data. Moreover, it computes biologically relevant quantities from the measured signals, notably promoter activities and protein concentrations, and compares the resulting expression profiles of different genes under different conditions. [ABSTRACT FROM AUTHOR]

Twelve populations of Escherichia coli evolved in and adapted to a glucose-limited environment from a common ancestor. We used two-dimensional protein electrophoresis to compare two evolved clones, isolated from independently derived populations after 20,000 generations. Exceptional parallelism was detected. We compared the observed changes in protein expression profiles with previously characterized global transcription profiles of the same clones; this is the first time such a comparison has been made in an evolutionary context where these changes are often quite subtle. The two methodologies exhibited some remarkable similarities that highlighted two different levels of parallel regulatory changes that were beneficial during the evolution experiment. First, at the higher level, both methods revealed extensive parallel changes in the same global regulatory network, reflecting the involvement of beneficial mutations in genes that control the ppGpp regulon. Second, both methods detected expression changes of identical gene sets that reflected parallel changes at a lower level of gene regulation. The protein profiles led to the discovery of beneficial mutations affecting the malT gene, with strong genetic parallelism across independently evolved populations. Functional and evolutionary analyses of these mutations revealed parallel phenotypic decreases in the maltose regulon expression and a high level of polymorphism at this locus in the evolved populations. [ABSTRACT FROM AUTHOR]

The genetic bases of adaptation are being investigated in 12 populations of Escherichia coli, founded from a common ancestor and serially propagated for 20,000 generations, during which time they achieved substantial fitness gains. Each day, populations alternated between active growth and nutrient exhaustion. DNA supercoiling in bacteria is influenced by nutritional state, and DNA topology helps coordinate the overall pattern of gene expression in response to environmental changes. We therefore examined whether the genetic controls over supercoiling might have changed during the evolution experiment. Parallel changes in topology occurred in most populations, with the level of DNA supercoiling increasing, usually in the first 2000 generations. Two mutations in the topA and fis genes that control supercoiling were discovered in a population that served as the focus for further investigation. Moving the mutations, alone and in combination, into the ancestral background had an additive effect on supercoiling, and together they reproduced the net change in DNA topology observed in this population. Moreover, both mutations were beneficial in competition experiments. Clonal interference involving other beneficial DNA topology mutations was also detected. These findings define a new class of fitness-enhancing mutations and indicate that the control of DNA supercoiling can be a key target of selection in evolving bacterial populations. [ABSTRACT FROM AUTHOR]