Analysis of the catabolic potential of Pseudomonas putida KT2440 against a wide range of natural aromatic compounds and sequence comparisons with the entire genome of this microorganism predicted the existence of at least four main pathways for the catabolism of central aromatic intermediates, that is, the protocatechuate (pca genes) and catechol (cat genes) branches of the beta-ketoadipate pathway, the homogentisate pathway (hmg/fah/mai genes) and the phenylacetate pathway (pha genes). Two additional gene clusters that might be involved in the catabolism of N-heterocyclic aromatic compounds (nic cluster) and in a central meta-cleavage pathway (pcm genes) were also identified. Furthermore, the genes encoding the peripheral pathways for the catabolism of p-hydroxybenzoate (pob), benzoate (ben), quinate (qui), phenylpropenoid compounds (fcs, ech, vdh, cal, van, acd and acs), phenylalanine and tyrosine (phh, hpd) and n-phenylalkanoic acids (fad) were mapped in the chromosome of P. putida KT2440. Although a repetitive extragenic palindromic (REP) element is usually associated with the gene clusters, a supraoperonic clustering of catabolic genes that channel different aromatic compounds into a common central pathway (catabolic island) was not observed in P. putida KT2440. The global view on the mineralization of aromatic compounds by P. putida KT2440 will facilitate the rational manipulation of this strain for improving biodegradation/biotransformation processes, and reveals this bacterium as a useful model system for studying biochemical, genetic, evolutionary and ecological aspects of the catabolism of aromatic compounds.

Genetic circuits in living cells share transcriptional and translational resources that are available in limited amounts. This leads to unexpected couplings among seemingly unconnected modules, which result in poorly predictable circuit behavior. In this study, we determine these interdependencies between products of different genes by characterizing the economy of how transcriptional and translational resources are allocated to the production of proteins in genetic circuits. We discover that, when expressed from the same plasmid, the combinations of attainable protein concentrations are constrained by a linear relationship, which can be interpreted as an isocost line, a concept used in microeconomics. We created a library of circuits with two reporter genes, one constitutive and the other inducible in the same plasmid, without a regulatory path between them. In agreement with the model predictions, experiments reveal that the isocost line rotates when changing the ribosome binding site strength of the inducible gene and shifts when modifying the plasmid copy number. These results demonstrate that isocost lines can be employed to predict how genetic circuits become coupled when sharing resources and provide design guidelines for minimizing the effects of such couplings.

The aerobic catabolism of nicotinic acid (NA) is considered a model system for degradation of N-heterocyclic aromatic compounds, some of which are major environmental pollutants; however, the complete set of genes as well as the structural-functional relationships of most of the enzymes involved in this process are still unknown. We have characterized a gene cluster (nic genes) from Pseudomonas putida KT2440 responsible for the aerobic NA degradation in this bacterium and when expressed in heterologous hosts. The biochemistry of the NA degradation through the formation of 2,5-dihydroxypyridine and maleamic acid has been revisited, and some gene products become the prototype of new types of enzymes with unprecedented molecular architectures. Thus, the initial hydroxylation of NA is catalyzed by a twocomponent hydroxylase (NicAB) that constitutes the first member of the xanthine dehydrogenase family whose electron transport chain to molecular oxygen includes a cytochrome c domain. The Fe 2؉ -dependent dioxygenase (NicX) converts 2,5-dihydroxypyridine into N-formylmaleamic acid, and it becomes the founding member of a new family of extradiol ring-cleavage dioxygenases. Further conversion of N-formylmaleamic acid to formic and maleamic acid is catalyzed by the NicD protein, the only deformylase described so far whose catalytic triad is similar to that of some members of the ␣/␤-hydrolase fold superfamily. This work allows exploration of the existence of orthologous gene clusters in saprophytic bacteria and some pathogens, where they might stimulate studies on their role in virulence, and it provides a framework to develop new biotechnological processes for detoxification/biotransformation of N-heterocyclic aromatic compounds.ring-cleavage dioxygenase ͉ nicotinic acid hydroxylase ͉ heterocyclic compounds

A common approach to design genetic circuits is to compose gene expression cassettes together. While appealing, this modular approach is challenged by the fact that expression of each gene depends on the availability of transcriptional/translational resources, which is in turn determined by the presence of other genes in the circuit. This raises the question of how competition for resources by different genes affects a circuit's behavior. Here, we create a library of genetic activation cascades in bacteria E. coli, where we explicitly tune the resource demand by each gene. We develop a general Hill-function-based model that incorporates resource competition effects through resource demand coefficients. These coefficients lead to non-regulatory interactions among genes that reshape circuit's behavior. For the activation cascade, such interactions result in surprising biphasic or monotonically decreasing responses. Finally, we use resource demand coefficients to guide the choice of ribosome binding site (RBS) and DNA copy number to restore the cascade's intended monotonically increasing response. Our results demonstrate how unintended circuit's behavior arises from resource competition and provide a model-guided methodology to minimize the resulting effects.

Bacterial transcriptional networks are built on a hierarchy of regulators, on top of which lie the components of the RNA polymerase (in particular the sigma factors) and the global control elements, which play a pivotal role. We have designed a genome-wide oligonucleotide-based DNA microarray for Pseudomonas putida KT2440. In combination with real-time reverse transcription polymerase chain reaction (RT-PCR), we have used it to analyse the expression pattern of the genes encoding the RNA polymerase subunits (the core enzyme and the 24 sigma factors), and various proteins involved in global regulation (Crc, Lrp, Fur, Anr, Fis, CsrA, IHF, HupA, HupB, HupN, BipA and several MvaT-like proteins), during the shift from exponential growth in rich medium into starvation and stress brought about by the entry into stationary phase. Expression of the genes encoding the RNA polymerase core and the vegetative sigma factor decreased in stationary phase, while that of sigma(S) increased. Data obtained for sigma(N), sigma(H), FliA and for the 19 extracytoplasmic function (ECF)-like sigma factors suggested that their mRNA levels change little upon entry into stationary phase. Expression of Crc, BipA, Fis, HupB, HupN and the MvaT-like protein PP3693 decreased in stationary phase, while that of HupA and the MvaT-like protein PP3765 increased significantly. Expression of IHF was indicative of post-transcriptional control. These results provide the first global study of the expression of the transcriptional machinery through the exponential stationary-phase shift in P. putida.

The origin of life is believed to have progressed through an RNA world, in which RNA acted as both genetic material and functional molecules. The structure of the evolutionary fitness landscape of RNA would determine natural selection for the first functional sequences. Fitness landscapes are the subject of much speculation, but their structure is essentially unknown. Here we describe a comprehensive map of a fitness landscape, exploring nearly all of sequence space, for short RNAs surviving selection in vitro. With the exception of a small evolutionary network, we find that fitness peaks are largely isolated from one another, highlighting the importance of historical contingency and indicating that natural selection would be constrained to local exploration in the RNA world.T he nucleotide sequence of an organism's genome determines its fitness in a given selective environment. All possible sequences of length L constitute a discrete sequence space containing 4 L points. Including fitness as another variable creates a "landscape" in sequence space, in which highly fit sequences occupy peaks (1, 2). Evolution can be thought of as a random walk on this landscape with a bias toward climbing peaks (3). Knowledge of the fitness landscape is a fundamental prerequisite for a quantitative understanding of evolution. Although several models of theoretical landscapes have been proposed (reviewed in refs. 4 and 5), there is a lack of empirical data. Landscapes based on RNA secondary structure have been explored computationally, but the relationship to function is unknown (6-10). Experimental efforts at determining a comprehensive fitness landscape are generally stymied by the astronomical size of sequence space, but synthesis of nearly every variant is feasible for relatively short sequences (i.e., RNAs with length L <30 nucleotides). Therefore, complete landscapes for short RNAs could be mapped in principle. Such landscapes are of particular interest for understanding evolution in the RNA world of early life (11)(12)(13)(14).Limited fitness landscapes localized around known functional sequences have been explored for proteins (15-17), viruses (18, 19), and functional nucleic acids, including ribozymes and ribosomal RNA (20-24). The local fitness landscape around a known RNA ligase ribozyme (L = 54) was mapped using highthroughput sequencing (25). However, random sampling of RNA and DNA sequence space can be done by in vitro selection, or SELEX, for de novo discovery of functional molecules (26)(27)(28)(29). Such studies generally take very sparse samples of sequence space, owing to their focus on obtaining functional, and therefore longer, sequences. Thorough sampling techniques have been used to explore all possible DNA targets for a known DNAbinding protein (30). Such studies illuminate the biology of extant organisms but do not address the initial evolution of macromolecular activity. The entirety of a macromolecular fitness landscape has not yet been explored. Therefore, fundamental questions about the shape of fitn...

A common approach to design genetic circuits is to compose gene expression cassettes together. While appealing, this modular approach is challenged by the fact that expression of each gene depends on the availability of transcriptional/translational resources, which is in turn determined by the presence of other genes in the circuit. This raises the question of how competition for resources by different genes affects a circuit's behavior. Here, we create a library of genetic activation cascades in E. coli bacteria, where we explicitly tune the resource demand by each gene. We develop a general Hill-function-based model that incorporates resource competition effects through resource demand coefficients. These coefficients lead to nonregulatory interactions among genes that reshape the circuit's behavior. For the activation cascade, such interactions result in surprising biphasic or monotonically decreasing responses. Finally, we use resource demand coefficients to guide the choice of ribosome binding site and DNA copy number to restore the cascade's intended monotonically increasing response. Our results demonstrate how unintended circuit's behavior arises from resource competition and provide a model-guided methodology to minimize the resulting effects.

SummaryMicrobial communities are increasingly utilized in biotechnology. Efficiency and productivity in many of these applications depends on the presence of cooperative interactions between members of the community. Two key processes underlying these interactions are the production of public goods and metabolic cross‐feeding, which can be understood in the general framework of ecological and evolutionary (eco‐evo) dynamics. In this review, we illustrate the relevance of cooperative interactions in microbial biotechnological processes, discuss their mechanistic origins and analyse their evolutionary resilience. Cooperative behaviours can be damaged by the emergence of ‘cheating’ cells that benefit from the cooperative interactions but do not contribute to them. Despite this, cooperative interactions can be stabilized by spatial segregation, by the presence of feedbacks between the evolutionary dynamics and the ecology of the community, by the role of regulatory systems coupled to the environmental conditions and by the action of horizontal gene transfer. Cooperative interactions enrich microbial communities with a higher degree of robustness against environmental stress and can facilitate the evolution of more complex traits. Therefore, the evolutionary resilience of microbial communities and their ability to constraint detrimental mutants should be considered to design robust biotechnological applications.