Community-based degradation of 4-chorosalicylate tracked on the single cell level

Genome Analysis and Physiology of Pseudomonas sp. Strain OVF7 Degrading Naphthalene and n-Dodecane

The complete genome of the naphthalene- and n-alkane-degrading strain Pseudomonas sp. strain OVF7 was collected and analyzed. Clusters of genes encoding enzymes for the degradation of naphthalene and n-alkanes are localized on the chromosome. Based on the Average Nucleotide Identity and digital DNA-DNA Hybridization compared with type strains of the group of fluorescent pseudomonads, the bacterium studied probably belongs to a new species. Using light, fluorescent, and scanning electron microscopy, the ability of the studied bacterium to form biofilms of different architectures when cultured in liquid mineral medium with different carbon sources, including naphthalene and n-dodecane, was demonstrated. When grown on a mixture of naphthalene and n-dodecane, the strain first consumed naphthalene and then n-dodecane. Cultivation of the strain on n-dodecane was characterized by a long adaptation phase, in contrast to cultivation on naphthalene and a mixture of naphthalene and n-dodecane.

Population heterogeneity in microbial bioprocesses: origin, analysis, mechanisms, and future perspectives

Population heterogeneity is omnipresent in all bioprocesses even in homogenous environments. Its origin, however, is only so well understood that potential strategies like bet-hedging, noise in gene expression and division of labour that lead to population heterogeneity can be derived from experimental studies simulating the dynamics in industrial scale bioprocesses. This review aims at summarizing the current state of the different parts of single cell studies in bioprocesses. This includes setups to visualize different phenotypes of single cells, computational approaches connecting single cell physiology with environmental influence and special cultivation setups like scale-down reactors that have been proven to be useful to simulate large-scale conditions. A step in between investigation of populations and single cells is studying subpopulations with distinct properties that differ from the rest of the population with sub-omics methods which are also presented here. Moreover, the current knowledge about population heterogeneity in bioprocesses is summarized for relevant industrial production hosts and mixed cultures, as they provide the unique opportunity to distribute metabolic burden and optimize production processes in a way that is impossible in traditional monocultures. In the end, approaches to explain the underlying mechanism of population heterogeneity and the evidences found to support each hypothesis are presented. For instance, population heterogeneity serving as a bet-hedging strategy that is used as coordinated action against bioprocess-related stresses while at the same time spreading the risk between individual cells as it ensures the survival of least a part of the population in any environment the cells encounter.

Diversity-Function Relationships in Natural, Applied, and Engineered Microbial Ecosystems

The connection between ecosystem function and taxonomic diversity has been of interest and relevance to macroecologists for decades. After many years of lagging behind due to the difficulty of assigning both taxonomy and function to poorly distinguishable microscopic cells, microbial ecology now has access to a suite of powerful molecular tools which allow its practitioners to generate data relating to diversity and function of a microbial community on an unprecedented scale. Instead, the problem facing today's microbial ecologists is coupling the ease of generation of these datasets with the formulation and testing of workable hypotheses relating the diversity and function of environmental, host-associated, and engineered microbial communities. Here, we review the current state of knowledge regarding the links between taxonomic alpha- and beta-diversity and ecosystem function, comparing our knowledge in this area to that obtained by macroecologists who use more traditional techniques. We consider the methodologies that can be applied to study these properties and how successful they are at linking function to diversity, using examples from the study of model microbial ecosystems, methanogenic bioreactors (anaerobic digesters), and host-associated microbiota. Finally, we assess ways in which our newly acquired understanding might be used to manipulate diversity in ecosystems of interest in order to improve function for the benefit of us or the environment in general through the provision of ecosystem services.

Model-based quantification of metabolic interactions from dynamic microbial-community data

An important challenge in microbial ecology is to infer metabolic-exchange fluxes between growing microbial species from community-level data, concerning species abundances and metabolite concentrations. Here we apply a model-based approach to integrate such experimental data and thereby infer metabolic-exchange fluxes. We designed a synthetic anaerobic co-culture of Clostridium acetobutylicum and Wolinella succinogenes that interact via interspecies hydrogen transfer and applied different environmental conditions for which we expected the metabolic-exchange rates to change. We used stoichiometric models of the metabolism of the two microorganisms that represents our current physiological understanding and found that this understanding - the model - is sufficient to infer the identity and magnitude of the metabolic-exchange fluxes and it suggested unexpected interactions. Where the model could not fit all experimental data, it indicates specific requirement for further physiological studies. We show that the nitrogen source influences the rate of interspecies hydrogen transfer in the co-culture. Additionally, the model can predict the intracellular fluxes and optimal metabolic exchange rates, which can point to engineering strategies. This study therefore offers a realistic illustration of the strengths and weaknesses of model-based integration of heterogenous data that makes inference of metabolic-exchange fluxes possible from community-level experimental data.

Model-based media selection to minimize the cost of metabolic cooperation in microbial ecosystems

MOTIVATION

Simple forms of mutualism between microorganisms are widespread in nature. Nevertheless, the role played by the environmental nutrient composition in mediating cross-feeding in microbial ecosystems is still poorly understood.

RESULTS

Here, we use mixed-integer bilevel linear programming to investigate the cost of sharing metabolic resources in microbial communities. The algorithm infers an optimal combination of nutrients that can selectively sustain synergistic growth for a pair of species and guarantees minimum cost of cross-fed metabolites. To test model-based predictions, we selected a pair of Escherichia coli single gene knockouts auxotrophic, respectively, for arginine and leucine: ΔargB and ΔleuB and we experimentally verified that model-predicted medium composition significantly favors mutualism. Moreover, mass spectrometry profiling of exchanged metabolites confirmed the predicted cross-fed metabolites, supporting our constraint based modeling approach as a promising tool for engineering microbial consortia.

AVAILABILITY AND IMPLEMENTATION

The software is freely available as a matlab script in the Supplementary materials.

CONTACT

zampieri@imsb.biol.ethz.ch

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Synthetic microbial ecosystems: an exciting tool to understand and apply microbial communities

Many microbial ecologists have described the composition of microbial communities in a plenitude of environments, which has greatly improved our basic understanding of microorganisms and ecosystems. However, the factors and processes that influence the behaviour and functionality of an ecosystem largely remain black boxes when using conventional approaches. Therefore, synthetic microbial ecology has gained a lot of interest in the last few years. Because of their reduced complexity and increased controllability, synthetic communities are often preferred over complex communities to examine ecological theories. They limit the factors that influence the microbial community to a minimum, allowing their management and identifying specific community responses. However, besides their use for basic research, synthetic ecosystems also found their way towards different applications, like industrial fermentation and bioremediation. Here, we review why and how synthetic microbial communities are applied for research purposes and for which applications they have been and could be successfully used.

Advanced tool for characterization of microbial cultures by combining cytomics and proteomics

Flow cytometry approaches are applicable to recover sub-populations of microbial cultures in a purified form. To examine the characteristics of each sorted cell population, Omics technologies can be used for comprehensively monitoring cellular physiology, adaptation reactions, and regulated processes. In this study, we combined flow cytometry and gel-free proteomic analysis to investigate an artificial mixed bacterial culture consisting of Escherichia coli K-12 and Pseudomonas putida KT2440. Therefore, a filter-based device technique and an on-membrane digestion protocol were combined in conjunction with liquid chromatography and mass spectrometry. This combination enabled us to identify 903 proteins from sorted E. coli K-12 and 867 proteins from sorted P. putida KT2440 bacteria from only 5 x 10(6) cells of each. Comparative proteomic analysis of sorted and non-sorted samples was done to prove that sorting did not significantly influence the bacterial proteome profile. We further investigated the physicochemical properties, namely M (r), pI, hydropathicity, and transmembrane helices of the proteins covered. The on-membrane digestion protocol applied did not require conventional detergents or urea, but exhibited similar recovery of all protein classes as established protocols with non-sorted bacterial samples.

Characterization of a gene cluster involved in 4-chlorocatechol degradation by Pseudomonas reinekei MT1

Pseudomonas reinekei MT1 has previously been reported to degrade 4- and 5-chlorosalicylate by a pathway with 4-chlorocatechol, 3-chloromuconate, 4-chloromuconolactone, and maleylacetate as intermediates, and a gene cluster channeling various salicylates into an intradiol cleavage route has been reported. We now report that during growth on 5-chlorosalicylate, besides a novel (chloro)catechol 1,2-dioxygenase, C12O(ccaA), a novel (chloro)muconate cycloisomerase, MCI(ccaB), which showed features not yet reported, was induced. This cycloisomerase, which was practically inactive with muconate, evolved for the turnover of 3-substituted muconates and transforms 3-chloromuconate into equal amounts of cis-dienelactone and protoanemonin, suggesting that it is a functional intermediate between chloromuconate cycloisomerases and muconate cycloisomerases. The corresponding genes, ccaA (C12O(ccaA)) and ccaB (MCI(ccaB)), were located in a 5.1-kb genomic region clustered with genes encoding trans-dienelactone hydrolase (ccaC) and maleylacetate reductase (ccaD) and a putative regulatory gene, ccaR, homologous to regulators of the IclR-type family. Thus, this region includes genes sufficient to enable MT1 to transform 4-chlorocatechol to 3-oxoadipate. Phylogenetic analysis showed that C12O(ccaA) and MCI(ccaB) are only distantly related to previously described catechol 1,2-dioxygenases and muconate cycloisomerases. Kinetic analysis indicated that MCI(ccaB) and the previously identified C12O(salD), rather than C12O(ccaA), are crucial for 5-chlorosalicylate degradation. Thus, MT1 uses enzymes encoded by a completely novel gene cluster for degradation of chlorosalicylates, which, together with a gene cluster encoding enzymes for channeling salicylates into the ortho-cleavage pathway, form an effective pathway for 4- and 5-chlorosalicylate mineralization.

Dynamics of polyphosphate-accumulating bacteria in wastewater treatment plant microbial communities detected via DAPI (4',6'-diamidino-2-phenylindole) and tetracycline labeling

Wastewater treatment plants with enhanced biological phosphorus removal represent a state-of-the-art technology. Nevertheless, the process of phosphate removal is prone to occasional failure. One reason is the lack of knowledge about the structure and function of the bacterial communities involved. Most of the bacteria are still not cultivable, and their functions during the wastewater treatment process are therefore unknown or subject of speculation. Here, flow cytometry was used to identify bacteria capable of polyphosphate accumulation within highly diverse communities. A novel fluorescent staining technique for the quantitative detection of polyphosphate granules on the cellular level was developed. It uses the bright green fluorescence of the antibiotic tetracycline when it complexes the divalent cations acting as a countercharge in polyphosphate granules. The dynamics of cellular DNA contents and cell sizes as growth indicators were determined in parallel to detect the most active polyphosphate-accumulating individuals/subcommunities and to determine their phylogenetic affiliation upon cell sorting. Phylotypes known as polyphosphate-accumulating organisms, such as a "Candidatus Accumulibacter"-like phylotype, were found, as well as members of the genera Pseudomonas and Tetrasphaera. The new method allows fast and convenient monitoring of the growth and polyphosphate accumulation dynamics of not-yet-cultivated bacteria in wastewater bacterial communities.