Transformation in Bacillus subtilis: purification and partial characterization of a membrane-bound DNA-binding protein.

In DNA binding-deficient mutants of Bacillus subtilis a competence-specific protein with a subunit molecular weight of 18,000 was absent. The native protein containing this subunit was purified from B. subtilis membranes by chromatography on hydroxyapatite, DEAE-cellulose, and Sephacryl S-200. This protein appeared to be complexed with a second protein of slightly lower molecular weight (17,000) and a different isoelectric point. The native protein complex (apparent molecular weight, 75,000) contained approximately equal amounts of the two polypeptides and showed a strong DNA-binding activity. Incubation of the complex with plasmid and bacteriophage DNA revealed nuclease activity, specifically directed toward double-stranded DNA. Predominantly single-stranded nicks and a limited number of double-stranded breaks were introduced in the presence of Mg2+ ions. In the presence of Mn2+ ions the complex produced low-molecular-weight breakdown products from the DNA.     

Molecular Characterization of Divergent Strawberry Mild Yellow Edge Virus Isolates from Eastern Canada

The complete genome sequences of four new isolates of strawberry mild yellow edge virus (SMYEV) were determined and analysed. The isolates, designated as AB41‐01, AB41‐02, NB1165 and NS26, were found from strawberry fields showing strawberry decline symptoms in eastern Canada. AB41‐01 and AB41‐02 were from a single‐plant sample originating from Prince Edward Island, while NB1165 came from New Brunswick and NS26 from Nova Scotia. Nucleotide sequence identities are 95.8% between AB41‐01 and NB1165, 99.6% between AB41‐02 and NS26, and 84% between AB41‐01/NB1165 and AB41‐02/NS26. The four isolates share nucleotide sequence identities of 83.5–89.9% to two previously identified SMYEV isolates, namely MY18 and D7. Phylogenetic analysis indicates that the four Canadian isolates represented two new SMYEV strain types and the strain divergences were not likely from recombination events among all presently known SMYEV isolates.     

High-level production of the low-calorie sugar sorbitol by Lactobacillus plantarum through metabolic engineering

Sorbitol is a low-calorie sugar alcohol that is largely used as an ingredient in the food industry, based on its sweetness and its high solubility. Here, we investigated the capacity of Lactobacillus plantarum, a lactic acid bacterium found in many fermented food products and in the gastrointestinal tract of mammals, to produce sorbitol from fructose-6-phosphate by reverting the sorbitol catabolic pathway in a mutant strain deficient for both l- and d-lactate dehydrogenase activities. The two sorbitol-6-phosphate dehydrogenase (Stl6PDH) genes (srlD1 and srlD2) identified in the genome sequence were constitutively expressed at a high level in this mutant strain. Both Stl6PDH enzymes were shown to be active, and high specific activity could be detected in the overexpressing strains. Using resting cells under pH control with glucose as a substrate, both Stl6PDHs were capable of rerouting the glycolytic flux from fructose-6-phosphate toward sorbitol production with a remarkably high efficiency (61 to 65% glucose conversion), which is close to the maximal theoretical value of 67%. Mannitol production was also detected, albeit at a lower level than the control strain (9 to 13% glucose conversion), indicating competition for fructose-6-phosphate rerouting by natively expressed mannitol-1-phosphate dehydrogenase. By analogy, low levels of this enzyme were detected in both the wild-type and the lactate dehydrogenase-deficient strain backgrounds. After optimization, 25% of sugar conversion into sorbitol was achieved with cells grown under pH control. The role of intracellular NADH pools in the determination of the maximal sorbitol production is discussed.     

On the influence of vector design on antibody phage display

Phage display technology is an established technology particularly useful for the generation of monoclonal antibodies (mAbs). The isolation of phagemid-encoded mAb fragments depends on several features of a phage preparation. The aims of this study were to optimize phage display vectors, and to ascertain if different virion features can be optimized independently of each other. Comparisons were made between phagemid virions assembled by g3p-deficient helper phage, Hyperphage, Ex-phage or Phaberge, or corresponding g3p-sufficient helper phage, M13K07. All g3p-deficient helper phage provided a similar level of antibody display, significantly higher than that of M13K07. Hyperphage packaged virions at least 100-fold more efficiently than did Ex-phage or Phaberge. Phaberge's packaging efficiency improved by using a SupE strain. Different phagemids were also compared. Removal of a 56 base pair fragment from the promoter region resulted in increased display level and increased virion production. This critical fragment encodes a lacZ'-like peptide and is also present in other commonly used phagemids. Increasing display level did not show statistical correlation with phage production, phage infectivity or bacterial growth rate. However, phage production was positively correlated to phage infectivity. In summary, this study demonstrates simultaneously optimization of multiple and independent features of importance for phage selection.     

Stoichiometric distribution models: ecological stoichiometry at the landscape extent

Human activities are altering the fundamental geography of biogeochemicals. Yet we lack an understanding of how the spatial patterns in organismal stoichiometry affect biogeochemical processes and the tools to predict the impacts of global changes on biogeochemical processes. In this contribution we develop stoichiometric distribution models (StDMs), which allow us to map spatial structure in resource elemental composition across a landscape and evaluate spatial responses of consumers. We parameterise StDMs for a consumer‐resource (moose‐white birch) system and demonstrate that we can develop predictive models of resource stoichiometry across a landscape and that such models could improve our predictions of consumer space use. With results from our study system application, we argue that explicit consideration of the spatial patterns in organismal elemental composition may uncover emergent individual, population, community and ecosystem properties that are not revealed at the local extents routinely used in ecological stoichiometry. We discuss perspectives for further developments and application of StDMs to advance three emerging frameworks for spatial ecosystem ecology in an era of global change; meta‐ecosystem theory, macroecological stoichiometry and remotely sensed biogeochemistry. Progress on these emerging frameworks will allow for the integration of ecological stoichiometry and individual space use and fitness.     

Understanding the Adaptive Growth Strategy of Lactobacillus plantarum by In Silico Optimisation

In the study of metabolic networks, optimization techniques are often used to predict flux distributions, and hence, metabolic phenotype. Flux balance analysis in particular has been successful in predicting metabolic phenotypes. However, an inherent limitation of a stoichiometric approach such as flux balance analysis is that it can predict only flux distributions that result in maximal yields. Hence, previous attempts to use FBA to predict metabolic fluxes in Lactobacillus plantarum failed, as this lactic acid bacterium produces lactate, even under glucose-limited chemostat conditions, where FBA predicted mixed acid fermentation as an alternative pathway leading to a higher yield. In this study we tested, however, whether long-term adaptation on an unusual and poor carbon source (for this bacterium) would select for mutants with optimal biomass yields. We have therefore adapted Lactobacillus plantarum to grow well on glycerol as its main growth substrate. After prolonged serial dilutions, the growth yield and corresponding fluxes were compared to in silico predictions. Surprisingly, the organism still produced mainly lactate, which was corroborated by FBA to indeed be optimal. To understand these results, constraint-based elementary flux mode analysis was developed that predicted 3 out of 2669 possible flux modes to be optimal under the experimental conditions. These optimal pathways corresponded very closely to the experimentally observed fluxes and explained lactate formation as the result of competition for oxygen by the other flux modes. Hence, these results provide thorough understanding of adaptive evolution, allowing in silico predictions of the resulting flux states, provided that the selective growth conditions favor yield optimization as the winning strategy.     

Genome-scale metabolic model for Lactococcus lactis MG1363 and its application to the analysis of flavor formation

Lactococcus lactis subsp. cremoris MG1363 is a paradigm strain for lactococci used in industrial dairy fermentations. However, despite of its importance for process development, no genome-scale metabolic model has been reported thus far. Moreover, current models for other lactococci only focus on growth and sugar degradation. A metabolic model that includes nitrogen metabolism and flavor-forming pathways is instrumental for the understanding and designing new industrial applications of these lactic acid bacteria. A genome-scale, constraint-based model of the metabolism and transport in L. lactis MG1363, accounting for 518 genes, 754 reactions, and 650 metabolites, was developed and experimentally validated. Fifty-nine reactions are directly or indirectly involved in flavor formation. Flux Balance Analysis and Flux Variability Analysis were used to investigate flux distributions within the whole metabolic network. Anaerobic carbon-limited continuous cultures were used for estimating the energetic parameters. A thorough model-driven analysis showing a highly flexible nitrogen metabolism, e.g., branched-chain amino acid catabolism which coupled with the redox balance, is pivotal for the prediction of the formation of different flavor compounds. Furthermore, the model predicted the formation of volatile sulfur compounds as a result of the fermentation. These products were subsequently identified in the experimental fermentations carried out. Thus, the genome-scale metabolic model couples the carbon and nitrogen metabolism in L. lactis MG1363 with complete known catabolic pathways leading to flavor formation. The model provided valuable insights into the metabolic networks underlying flavor formation and has the potential to contribute to new developments in dairy industries and cheese-flavor research.