In the last two decades, the widespread application of genetic and genomic approaches has revealed a bacterial world astonishing in its ubiquity and diversity. This review examines how a growing knowledge of the vast range of animal–bacterial interactions, whether in shared ecosystems or intimate symbioses, is fundamentally altering our understanding of animal biology. Specifically, we highlight recent technological and intellectual advances that have changed our thinking about five questions: how have bacteria facilitated the origin and evolution of animals; how do animals and bacteria affect each other’s genomes; how does normal animal development depend on bacterial partners; how is homeostasis maintained between animals and their symbionts; and how can ecological approaches deepen our understanding of the multiple levels of animal–bacterial interaction. As answers to these fundamental questions emerge, all biologists will be challenged to broaden their appreciation of these interactions and to include investigations of the relationships between and among bacteria and their animal partners as we seek a better understanding of the natural world.

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Animals in a bacterial world, a new imperative for the life sciences

Many, if not most, enzymes can promiscuously catalyze reactions, or act on substrates, other than those for which they evolved. Here, we discuss the structural, mechanistic, and evolutionary implications of this manifestation of infidelity of molecular recognition. We define promiscuity and related phenomena and also address their generality and physiological implications. We discuss the mechanistic enzymology of promiscuity—how enzymes, which generally exert exquisite specificity, catalyze other, and sometimes barely related, reactions. Finally, we address the hypothesis that promiscuous enzymatic activities serve as evolutionary starting points and highlight the unique evolutionary features of promiscuous enzyme functions.

Enzyme Promiscuity: A Mechanistic and Evolutionary Perspective

The creation of enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Using new algorithms that rely on hashing techniques to construct active sites for multistep reactions, we designed retro-aldolases that use four different catalytic motifs to catalyze the breaking of a carbon-carbon bond in a nonnatural substrate. Of the 72 designs that were experimentally characterized, 32, spanning a range of protein folds, had detectable retro-aldolase activity. Designs that used an explicit water molecule to mediate proton shuffling were significantly more successful, with rate accelerations of up to four orders of magnitude and multiple turnovers, than those involving charged side-chain networks. The atomic accuracy of the design process was confirmed by the x-ray crystal structure of active designs embedded in two protein scaffolds, both of which were nearly superimposable on the design model.

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De novo computational design of retro-aldol enzymes.

Enzyme promiscuity: evolutionary and mechanistic aspects.

Genome-scale metabolic models bridge the gap between genome-derived biochemical information and metabolic phenotypes in a principled manner, providing a solid interpretative framework for experimental data related to metabolic states, and enabling simple in silico experiments with whole-cell metabolism. Models have been reconstructed for almost 20 bacterial species, so far mainly through expert curation efforts integrating information from the literature with genome annotation. A wide variety of computational methods exploiting metabolic models have been developed and applied to bacteria, yielding valuable insights into bacterial metabolism and evolution, and providing a sound basis for computer-assisted design in metabolic engineering. Recent advances in computational systems biology and high-throughput experimental technologies pave the way for the systematic reconstruction of metabolic models from genomes of new species, and a corresponding expansion of the scope of their applications. In this review, we provide an introduction to the key ideas of metabolic modeling, survey the methods, and resources that enable model reconstruction and refinement, and chart applications to the investigation of global properties of metabolic systems, the interpretation of experimental results, and the re-engineering of their biochemical capabilities.

https://www.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1574-6976.2008.00146.x

Genome‐scale models of bacterial metabolism: reconstruction and applications

Bacterial dehalogenases catalyse the cleavage of carbon-halogen bonds, which is a key step in aerobic mineralization pathways of many halogenated compounds that occur as environmental pollutants. There is a broad range of dehalogenases, which can be classified in different protein superfamilies and have fundamentally different catalytic mechanisms. Identical dehalogenases have repeatedly been detected in organisms that were isolated at different geographical locations, indicating that only a restricted number of sequences are used for a certain dehalogenation reaction in organohalogen-utilizing organisms. At the same time, massive random sequencing of environmental DNA, and microbial genome sequencing projects have shown that there is a large diversity of dehalogenase sequences that is not employed by known catabolic pathways. The corresponding proteins may have novel functions and selectivities that could be valuable for biotransformations in the future. Apparently, traditional enrichment and metagenome approaches explore different segments of sequence space. This is also observed with alkane hydroxylases, a category of proteins that can be detected on basis of conserved sequence motifs and for which a large number of sequences has been found in isolated bacterial cultures and genomic databases. It is likely that ongoing genetic adaptation, with the recruitment of silent sequences into functional catabolic routes and evolution of substrate range by mutations in structural genes, will further enhance the catabolic potential of bacteria toward synthetic organohalogens and ultimately contribute to cleansing the environment of these toxic and recalcitrant chemicals.

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Bacterial degradation of xenobiotic compounds: evolution and distribution of novel enzyme activities

Most aerobic biodegradation pathways for hydrocarbons involve iron-containing oxygenases. In iron-limited environments, such as the rhizosphere, this may influence the rate of degradation of hydrocarbon pollutants. We investigated the effects of iron limitation on the degradation of toluene by Pseudomonas putida mt2 and the transconjugant rhizosphere bacterium P. putida WCS358(pWWO), both of which contain the pWWO (TOL) plasmid that harbors the genes for toluene degradation. The results of continuous-culture experiments showed that the activity of the upper-pathway toluene monooxygenase decreased but that the activity of benzyl alcohol dehydrogenase was not affected under iron-limited conditions. In contrast, the activities of three meta-pathway (lower-pathway) enzymes were all found to be reduced when iron concentrations were decreased. Additional experiments in which citrate was used as a growth substrate and the pathways were induced with the gratuitous inducer o-xylene showed that expression of the TOL genes increased the iron requirement in both strains. Growth yields were reduced and substrate affinities decreased under iron-limited conditions, suggesting that iron availability can be an important parameter in the oxidative breakdown of hydrocarbons.

/pdf/effects-of-iron-limitation-on-the-degradation-of-toluene-by-4dpsqzjqfn.pdf

Effects of Iron Limitation on the Degradation of Toluene by Pseudomonas Strains Carrying the TOL (pWWO) Plasmid

Rhizoremediation has been suggested as an attractive bioremediation strategy for the effective breakdown of pollutants in soil. The presence of plant root exudates such as organic acids, sugars, and amino acids that may serve as carbon sources or biosynthetic building blocks and the limited bioavailability of iron may influence the degradation of pollutants in the rhizosphere. To test the effect of such compounds on hydrocarbon degradation, trace concentrations of yeast extract or mixtures of organic acids and amino acids were added to continuous cultures of Pseudomonas putida mt2 and P. putida WCS358 (TOL) growing on toluene. By addition of these compounds increased growth yields and higher specific growth rates on toluene were obtained. The effects of iron limitation on the substrate utilization pattern of both strains were tested by growing the strains on a mixture of toluene and the readily degradable carbon source citrate while the iron concentration was varied. Simultaneous use of both substrates under carbon-limited as well as iron-limited conditions was observed. Growth yields were less reduced and iron requirement was lower during iron-limited growth in the toluene + citrate grown cultures compared to cultures in which toluene was used as the sole carbon source. The kinetic properties of the cells for toluene degradation were less hampered by the lack of iron when citrate was used as an additional carbon source. The results indicate that the availability of low concentrations of natural organic compounds, such as produced in the rhizosphere, may positively influence the degradative performance of hydrocarbon-degrading bacteria.

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Simultaneous Growth on Citrate Reduces the Effects of Iron Limitation during Toluene Degradation in Pseudomonas

Differential expression of genes in C. elegans reveals transcriptional responses to indirect-acting xenobiotic compounds and insensitivity to 2,3,7,8-tetrachlorodibenzodioxin.

The use of next-generation sequencing technologies in drinking water distribution systems (DWDS) has shed insight into the microbial communities’ composition, and interaction in the drinking water microbiome. For the past two decades, various studies have been conducted in which metagenomics data have been collected over extended periods and analyzed spatially and temporally to understand the dynamics of microbial communities in DWDS. In this literature review, we outline the findings which were reported in the literature on what kind of occupancy-abundance patterns are exhibited in the drinking water microbiome, how the drinking water microbiome dynamically evolves spatially and temporally in the distribution networks, how different microbial communities co-exist, and what kind of clusters exist in the drinking water ecosystem. While data analysis in the current literature concerns mainly with confirmatory and exploratory questions pertaining to the use of metagenomics data for the analysis of DWDS microbiome, we present also future perspectives and the potential role of artificial intelligence (AI) and mechanistic models to address the predictive and mechanistic questions. The integration of meta-omics, AI, and mechanistic models transcends metagenomics into functional metagenomics, enabling deterministic understanding and control of DWDS for clean and safe drinking water systems of the future.

/pdf/clean-and-safe-drinking-water-systems-via-metagenomics-data-1dv7ns8i.pdf

Inez J. T. Dinkla

Papers

Bacterial degradation of xenobiotic compounds: evolution and distribution of novel enzyme activities

Effects of Iron Limitation on the Degradation of Toluene by Pseudomonas Strains Carrying the TOL (pWWO) Plasmid

Simultaneous Growth on Citrate Reduces the Effects of Iron Limitation during Toluene Degradation in Pseudomonas

Differential expression of genes in C. elegans reveals transcriptional responses to indirect-acting xenobiotic compounds and insensitivity to 2,3,7,8-tetrachlorodibenzodioxin.

Clean and Safe Drinking Water Systems via Metagenomics Data and Artificial Intelligence: State-of-the-Art and Future Perspective