Rafael Silva-Rocha

Noise and Robustness in Prokaryotic Regulatory Networks

Robustness is the quality of any relational object (biological or otherwise) to maintain its components, its structure, and its function despite both external changes and endogenous fluctuations. Live systems are surprisingly robust, as they are able to not only preserve their physicochemical architecture in the face of variable nutritional and environmental conditions, but also tolerate stochastic variability in the concentrations of their components, fix errors resulting from hazardous events, and make virtually perfect copies of themselves. These qualities have started to be comprehended in full only since the application of network theory formalisms to regulatory phenomena. This review addresses the distinct role of network architecture (topology, logic) and biochemical/kinetic parameters in the materialization of various archetypical robust gene expression circuits in prokaryotes. Some take-home lessons for the construction of artificial regulatory networks (one of the trademarks of synthetic biology) are to be derived from such state of affairs.

Mining logic gates in prokaryotic transcriptional regulation networks

Prokaryotic transcriptional networks possess a large number of regulatory modules that formally implement many of the logic gates that are typical of digital, Boolean circuits. Yet, natural regulatory elements appear most often compressed and exaggeratedly context‐dependent for any reliable circuit engineering barely comparable to electronic counterparts. To overcome this impasse, we argue that designing new functions with biological parts requires (i) the recognition of logic gates not yet assigned but surely present in the meta‐genome, (ii) the orthogonalization and disambiguation of natural regulatory modules and (iii) the development of ways to tackle the connectivity and the definition of boundaries between minimal biological components.

Comparative metabolism of cellulose, sophorose and glucose in Trichoderma reesei using high-throughput genomic and proteomic analyses

BackgroundThe filamentous fungus Trichoderma reesei is a major producer of lignocellulolytic enzymes utilized by bioethanol industries. However, to achieve low cost second generation bioethanol production on an industrial scale an efficient mix of hydrolytic enzymes is required for the deconstruction of plant biomass. In this study, we investigated the molecular basis for lignocellulose-degrading enzyme production T. reesei during growth in cellulose, sophorose, and glucose.ResultsWe examined and compared the transcriptome and differential secretome (2D-DIGE) of T. reesei grown in cellulose, sophorose, or glucose as the sole carbon sources. By applying a stringent cut-off threshold 2,060 genes were identified as being differentially expressed in at least one of the respective carbon source comparisons. Hierarchical clustering of the differentially expressed genes identified three possible regulons, representing 123 genes controlled by cellulose, 154 genes controlled by sophorose and 402 genes controlled by glucose. Gene regulatory network analyses of the 692 genes differentially expressed between cellulose and sophorose, identified only 75 and 107 genes as being specific to growth in sophorose and cellulose, respectively. 2D-DIGE analyses identified 30 proteins exclusive to sophorose and 37 exclusive to cellulose. A correlation of 70.17% was obtained between transcription and secreted protein profiles.ConclusionsOur data revealed new players in cellulose degradation such as accessory proteins with non-catalytic functions secreted in different carbon sources, transporters, transcription factors, and CAZymes, that specifically respond in response to either cellulose or sophorose.

Transcriptomic fingerprinting of Pseudomonas putida under alternative physiological regimes

Pseudomonas putida KT2440 is a metabolically versatile soil bacterium useful both as a model biodegradative organism and as a host of catalytic activities of biotechnological interest. In this report, we present the high-resolution transcriptome of P. putida cultured on different carbon sources as revealed by deep sequencing of the corresponding RNA pools. Examination of the data from growth on substrates that are processed through distinct pathways (glucose, fructose, succinate and glycerol) revealed that ≥ 20% of the P. putida genome is differentially expressed depending on the ensuing physiological regime. Changes affected not only metabolic genes but also a suite of global regulators, e.g. the rpoS sigma subunit of RNA polymerase, various cold-shock proteins and the three HU histone-like proteins. Specifically, the genes encoding HU subunit variants hupA, hupB and hupN drastically altered their expression levels (and thus their ability to form heterodimeric combinations) under the diverse growth conditions. Furthermore, we found that two small RNAs, crcZ and crcY, known to inhibit the Crc protein that mediates catabolite repression in P. putida, were both down-regulated by glucose. The raw transcriptomic data generated in this work is made available to the community through the Gene Expression Omnibus database.

The private life of environmental bacteria: pollutant biodegradation at the single cell level

Bacteria display considerable cell-to-cell heterogeneity in a number of genetic and physiological traits. Stochastic differences in regulatory patterns (e.g. at the transcriptional level) propagate into the metabolic and physiological status of otherwise isogenic cells, which ultimately results in appearance of sub-populations within the community. As new technologies emerge and because novel single cell strategies are constantly being refined, our knowledge on microbial individuality is in burgeoning and constant expansion. These approaches encompass not only molecular biology tools (e.g. fluorescent-protein based reporters) but also a suite of sophisticated, non-invasive technologies to gain insight into the metabolic state of individual cells. Defining the role of individual heterogeneities is thus instrumental for the population-level understanding of macroscopic processes in both environmental and industrial set-ups. The present article reviews the state-of-the-art methodologies for the investigation of single bacteria at both the genetic and metabolic level, and places the application of currently available tools in the context of microbial ecology and environmental microbiology. As a case example, we examine the stochastic and multi-stable behaviour of the TOL-encoded pathway of Pseudomonas putida mt-2 for the biodegradation of aromatic compounds. Bet-hedging strategies and division of labour are considered as factors pushing forward the evolution of environmental microorganisms.

Reactome array: forging a link between metabolome and genome.

Metabolite Arrays Methods suitable for the biochemical analysis of multiple metabolic pathways in mixed samples are in short supply. Beloqui et al. (p. 252) report a method to sample the global metabolic state of an organism or mixture of organisms using an array of more than 1500 metabolites linked to a glass slide. The substrates are linked to the plate so that the reaction of an enzyme with one of the metabolites releases a fluorescent dye, which allows sensitive detection of the enzymatic activity. From a sample with small numbers of a mixture of bacteria, the authors were able to collect DNA, amplify it in a host bacterium, and measure its encoded metabolic activity with the array. Furthermore, by coating the substrates on nanoparticles with a specially designed linker, the authors could trap and purify enzymes that reacted with the immobilized substrate. The metabolite array may be useful in the characterization of environmental samples, in diagnostic procedures, and in enzyme discovery. A microarray technique uses trapped, dye-associated metabolites to allow rapid global characterization of metabolic activity. We describe a sensitive metabolite array for genome sequence–independent functional analysis of metabolic phenotypes and networks, the reactomes, of cell populations and communities. The array includes 1676 dye-linked substrate compounds collectively representing central metabolic pathways of all forms of life. Application of cell extracts to the array leads to specific binding of enzymes to cognate substrates, transformation to products, and concomitant activation of the dye signals. Proof of principle was shown by reconstruction of the metabolic maps of model bacteria. Utility of the array for unsequenced organisms was demonstrated by reconstruction of the global metabolisms of three microbial communities derived from acidic volcanic pool, deep-sea brine lake, and hydrocarbon-polluted seawater. Enzymes of interest are captured on nanoparticles coated with cognate metabolites, sequenced, and their functions unequivocally established.

The regulatory logic of m-xylene biodegradation by Pseudomonas putida mt-2 exposed by dynamic modelling of the principal node Ps/Pr of the TOL plasmid

The structure of the extant transcriptional control network of the TOL plasmid pWW0 born by Pseudomonas putida mt-2 for biodegradation of m-xylene is far more complex than one would consider necessary from a mere engineering point of view. In order to penetrate the underlying logic of such a network, which controls a major environmental cleanup bioprocess, we have developed a dynamic model of the key regulatory node formed by the Ps/Pr promoters of pWW0, where the clustering of control elements is maximal. The model layout was validated with batch cultures estimating parameter values and its predictive capability was confirmed with independent sets of experimental data. The model revealed how regulatory outputs originated in the divergent and overlapping Ps/Pr segment, which expresses the transcription factors XylS and XylR respectively, are computed into distinct instructions to the upper and lower catabolic xyl operons for either simultaneous or stepwise consumption of m-xylene and/or succinate. In this respect, the model reveals that the architecture of the Ps/Pr is poised to discriminate the abundance of alternative and competing C sources, in particular m-xylene versus succinate. The proposed framework provides a first systemic understanding of the causality and connectivity of the regulatory elements that shape this exemplary regulatory network, facilitating the use of model analysis towards genetic circuit optimization.

The logic layout of the TOL network of Pseudomonas putida pWW0 plasmid stems from a metabolic amplifier motif (MAM) that optimizes biodegradation of m-xylene

BackgroundThe genetic network of the TOL plasmid pWW0 of the soil bacterium Pseudomonas putida mt-2 for catabolism of m-xylene is an archetypal model for environmental biodegradation of aromatic pollutants. Although nearly every metabolic and transcriptional component of this regulatory system is known to an extraordinary molecular detail, the complexity of its architecture is still perplexing. To gain an insight into the inner layout of this network a logic model of the TOL system was implemented, simulated and experimentally validated. This analysis made sense of the specific regulatory topology out on the basis of an unprecedented network motif around which the entire genetic circuit for m-xylene catabolism gravitates.ResultsThe most salient feature of the whole TOL regulatory network is the control exerted by two distinct but still intertwined regulators (XylR and XylS) on expression of two separated catabolic operons (upper and lower) for catabolism of m-xylene. Following model reduction, a minimal modular circuit composed by five basic variables appeared to suffice for fully describing the operation of the entire system. In silico simulation of the effect of various perturbations were compared with experimental data in which specific portions of the network were activated with selected inducers: m-xylene, o-xylene, 3-methylbenzylalcohol and 3-methylbenzoate. The results accredited the ability of the model to faithfully describe network dynamics. This analysis revealed that the entire regulatory structure of the TOL system enables the action an unprecedented metabolic amplifier motif (MAM). This motif synchronizes expression of the upper and lower portions of a very long metabolic system when cells face the head pathway substrate, m-xylene.ConclusionLogic modeling of the TOL circuit accounted for the intricate regulatory topology of this otherwise simple metabolic device. The found MAM appears to ensure a simultaneous expression of the upper and lower segments of the m-xylene catabolic route that would be difficult to bring about with a standard substrate-responsive single promoter. Furthermore, it is plausible that the MAM helps to avoid biochemical conflicts between competing plasmid-encoded and chromosomally-encoded pathways in this bacterium.

Engineering multicellular logic in bacteria with metabolic wires

Aromatic biodegradation pathways of environmental bacteria are vast sources of matching trios of enzymes, substrates and regulators that can be refactored to run logic operations through cell-to-cell communication. As a proof of concept, the connection between two Pseudomonas putida strains using benzoic acid as the wiring molecule is presented. In this system, a sender strain harboring the TOL pathway for biodegradation of aromatics processed toluene as input and generated benzoate as the output signal. Diffusion of such metabolic intermediate to the medium was then sensed by a second strain (the receiver) that used benzoate as input for a new logic gate producing a visual output (i.e., light emission). The setup was functional irrespective of whether sender and receiver cells were in direct contact or in liquid culture. These results highlight the potential of environmental metabolic pathways as sources of building blocks for the engineering of multicellular logic in prokaryotic systems.

Expression pattern of cellulolytic and xylanolytic genes regulated by transcriptional factors XYR1 and CRE1 are affected by carbon source in Trichoderma reesei.

Trichoderma reesei is the most important fungus for the industrial production of enzymes to biomass deconstruction. Most of the genes encoding cellulases and hemicellulases are regulated by the transcription factors CRE1 and XYR1. In this work, the regulation of 22 genes of cellulases and xylanases by these transcription factors was investigated under three different carbon sources. Analysis of gene expression and enzymatic profiles of CMCase, β-glucosidase, and xylanases showed different regulation that was depended of the carbon source in both Δxyr1 and Δcre1 mutants. In the presence of glucose, the majority of genes evaluated (82%) showed increased expression levels in the Δcre1 mutant compared to the parental QM9414 strain. In the Δxyr1 mutant, it was observed that expression of cellulase and xylanase genes was reduced compared to the parental QM9414 strain, when cultured in the presence of cellulose or sophorose. Interesting, in the presence of glucose, approximately 60% of the analyzed genes had increased expression in the Δxyr1 mutant compared to parental strain. Furthermore, no correlation between gene expression and the number of putative binding sites of XYR1 and CRE1 to promoter region of cellulolytic and xylanolytic studied genes was observed. Therefore, these results demonstrated that the regulation of cellulase and xylanase by the transcription factors CRE1 and XYR1 is influenced by different carbon sources.