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57 results for “Pseudomonas fluorescens”
Pseudomonas_E fluorescens_BV MYb184
This is one of the Wormbiome database archive files.<br>This entry includes all the genome annotation files related to Pseudomonas_E fluorescens_BV MYb184, a\(n\) Gammaproteobacteria.<br>The Wormbiome collection is an online database dedicated to centralizing all the information related to bacteria associated with C. elegans. More information on <a href="https://bitbucket.org/the-samuel-lab/wbm_scripts/src/master/DOCS/Annotations_output.md" target="_blank" rel="noopener noreferrer">the documentation page</a>.<br><br>
Fig. 3 in Effects of the Secondary Metabolite Producing Pseudomonas fluorescens CHA0 on Soil Protozoa and Bacteria
Fig. 3. Colony forming curves of culturable bacteria in soil microcosms harvested after 1, 7, and 14 days on non-selective agar media. For each harvest event the same plates were counted repeatedly. Statistical significant differences between the treatments at the last counting event of each harvest are indicated by different letters.
Fig. 4 in Effects of the Secondary Metabolite Producing Pseudomonas fluorescens CHA0 on Soil Protozoa and Bacteria
Fig. 4. Abundance of culturable protozoa in the four different soil microcosms. The protozoa were counted by MPN as fast-growing protozoa after 1 week of incubation and as total protozoa after 3 weeks of incubation by inspecting the same plates twice. Significant differences of treatments within each sampling time and incubation time are shown as different small letters above the bars. After one day protozoa was only counted in the control microcosm. Significant differences between the abundance of protozoa in the control microcosm are shown as capital letters. bd: below detection limit of 157 protozoa g–1 dw. nd: not determined.
Fig. 2 in Effects of the Secondary Metabolite Producing Pseudomonas fluorescens CHA0 on Soil Protozoa and Bacteria
Fig. 2. Fate of inoculated P. fluorescence CHA0/gfp1 and P. fluorescens CHA0/pME3424 during incubation in soil microcosms determined as CFU on selective agar media (see Materials and Methods for selective agents). The individual data points for each replicate are shown along with the linear regression line for each strain.
Fig. 1 in Effects of the Secondary Metabolite Producing Pseudomonas fluorescens CHA0 on Soil Protozoa and Bacteria
Fig. 1. Soil respiration measured as accumulated CO 2 during the incubation of microcosms consisting of soil, shredded barley straw and either of three bacterial inoculants: E. aerogenes, P. fluorescens CHA0/gfp1, P. fluorescens CHA0/pME3424. Control treatment did not receive any bacteria.
Barcoding populations of Pseudomonas fluorescens SBW25
<p>In recent years evolutionary biologists have developed increasing interest in the use of barcoding strategies to study eco-evolutionary dynamics of lineages within evolving populations and communities. Although barcoded populations can deliver unprecedented insight into evolutionary change, barcoding microbes presents specific technical challenges. Here, strategies are described for barcoding populations of the model bacterium Pseudomonas fluorescens SBW25, including the design and cloning of barcoded regions, preparation of libraries for amplicon sequencing, and quantification of resulting barcoded lineages. In so doing, we hope to aid the design and implementation of barcoding methodologies in a broad range of model and non-model organisms. In here we deposit, the raw and processed data we have used during our study.</p>
Data from: Pseudomonas putida and Pseudomonas fluorescens species group recovery from human homes varies seasonally and by environment
By shedding light on variation in time as well as in space, long-term biogeographic studies can help us define organisms' distribution patterns and understand their underlying drivers. Here we examine distributions of Pseudomonas in and around 15 human homes, focusing on the P. putida and P. fluorescens species groups. We describe recovery from 10,941 samples collected during up to 8 visits per home, occurring on average 2.6 times per year. We collected a mean of 141 samples per visit, from sites in most rooms of the house, from the surrounding yards, and from human and pet occupants. We recovered Pseudomonas in 9.7% of samples, with the majority of isolates being from the P. putida and P. fluorescens species groups (approximately 62% and 23% of Pseudomonas samples recovered respectively). Although representatives of both groups were recovered from every season, every house, and every type of environment sampled, recovery was highly variable across houses and samplings. Whereas recovery of P. putida group was higher in summer and fall than in winter and spring, P. fluorescens group isolates were most often recovered in spring. P. putida group recovery from soils was substantially higher than its recovery from all other environment types, while higher P. fluorescens group recovery from soils than from other sites was much less pronounced. Both species groups were recovered from skin and upper respiratory tract samples from healthy humans and pets, although this occurred infrequently. This study indicates that even species that are able to survive under a broad range of conditions can be rare and variable in their distributions in space and in time. For such groups, determining patterns and causes of stochastic and seasonal variability may be more important for understanding the processes driving their biogeography than the identity of the types of environments in which they can be found.
Data from: Pseudomonas putida and Pseudomonas fluorescens species group recovery from human homes varies seasonally and by environment
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Data from: Evolution of fitness trade-offs in locally adapted populations of Pseudomonas fluorescens
Local adaptation seems to be common in natural systems, but the genetic causes of its evolution remain poorly understood. Here we characterize the genetic causes of trade-offs generating local adaptation in populations of Pseudomonas fluorescens that had previously been evolved for specialization on three different carbon resources. We measured the fitness effects of mutations that arose during selection in that environment and in alternative environments to quantify the degree of specialization. We find that all mutations are beneficial in the environment of selection and that those arising later during adaptation are associated with increasingly antagonistic effects in alternative environments compared with those arising earlier, consistent with a multioptima version of Fisher's geometric model of adaptation. We also find that fitness of pairs of beneficial mutations are consistently less than additive in selection environments, producing a pattern of diminishing returns, but are more variable in alternative environments, being either positive or negative. Finally, we find that mutations in genes associated with loss of motility are beneficial across all environments, whereas mutations involving other functions, such as gene regulation, had more variable effects, being more environment specific. Taken together, these results provide a detailed account of the genetics of specialization and suggest that the evolution of trade-offs associated with local adaptation may often result from the antagonistic effects of beneficial mutations substituted later in adaptation.
Data from: Evolutionary rescue in populations of Pseudomonas fluorescens across an antibiotic gradient
Environmental change represents a major threat to species persistence. When change is rapid, a population's only means of persisting may be to evolve resistance. Understanding such 'evolutionary rescues' is important for conservation in the face of global change, but also in the agricultural and medical sciences, where the objective is rather population control or eradication. Theory predicts that evolutionary rescue is fostered by large populations and genetic variation, but this has yet to be tested. We replicated hundreds of populations of the bacterium Pseudomonas fluorescens SBW25 submitted to a range of doses of the antibiotic streptomycin. Consistent with theory, population size, and initial genetic diversity influenced population persistence and the evolution of antibiotic resistance. Although all treated populations suffered initial declines, those experiencing the smallest decreases were most likely to be evolutionarily rescued. Our results contribute to our understanding of how evolution may or may not save populations and species from extinction.
Denitrification performance of pseudomonas fluorescens Z03 immobilized by GO modified PVA-SA gel bead at low temperature
<p>Experimental data monitoring results.</p>
Data from: Adaptive landscapes in evolving populations of Pseudomonas fluorescens
The repeatability of adaptive evolution depends on the ruggedness of the underlying adaptive landscape. We contrasted the relative ruggedness of adaptive landscapes across two environments by measuring the variance in fitness and metabolic phenotype within and among genetically distinct strains of Pseudomonas fluorescens in two environments differing only in the carbon source provided (glucose vs. xylose). Fitness increased in all lines, plateauing in one environment but not the other. The pattern of variance in fitness among replicate lines was unique to the selection environment; it increased over the course of the experiment in xylose but not in glucose. Metabolic phenotypes displayed two results: (1) populations adapted via changes that were distinctive to their selection environment, and (2) endpoint phenotypes were less variable in glucose than in xylose. These results indicate that although the response to selection is highly repeatable at the level of fitness, the underlying genetic routes taken were different for each environment and more variable in xylose. We suggest that this reflects a more rugged adaptive landscape in xylose compared to glucose. Our study demonstrates the utility of using replicate selection lines with different evolutionary starting points to try and quantify the relative ruggedness of adaptive landscapes.
Data from: Cheating and resistance to cheating in natural populations of the bacterium Pseudomonas fluorescens
Bacteria perform cooperative behaviours that are exploitable by non-cooperative cheats, and cheats frequently arise and coexist with cooperators in laboratory microcosms. However, evidence of competitive dynamics between cooperators and cheats in nature remains limited. Using the production of pyoverdine, an iron-scavenging molecule, and natural soil populations of Pseudomonas fluorescens, we found that (1) non-producers are present in the population; (2) they co-occur (<1cm3) with pyoverdine producers; (3) they retain functional pyoverdine receptors and (4) they can utilize the pyoverdine of on average 52% of producers. This suggests non-producers can potentially act as social cheats in soil: utilizing the pyoverdine of others while producing little or none themselves. However, we found considerable variation in the extent to which non-producers can exploit cooperators, as some cooperators appear to produce exclusive forms of pyoverdine or kill non-producers with toxins. We examined the consequences of this variation using theoretical modeling. Variance in exploitability leads to some cheats gaining increased fitness benefits and others decreased benefits. However, the absolute gain in fitness from high exploitation is lower than the drop in fitness from low exploitation, decreasing the mean fitness of cheats and subsequently lowering the proportion of cheats maintained in the population Our results suggest that although cooperator-cheat dynamics can occur in soil, a range of mechanisms can prevent non-producers from exploiting cooperators.
Dataset of the bacterial fitness estimation values and mutation identifications from: Rapid decline of adaptation of Pseudomonas fluorescens to soil biotic environment
<p>Interactions between microbes can both constrain and enhance adaptation, but to date, most studies employ simplified communities and environments. We measured fitness of populations of the soil bacterium Pseudomonas fluorescens that have been evolved in both the presence and absence of a natural potting soil microbial community. Populations from both environments showed similar fitness increases with respect to the ancestor in the absence of the community, suggesting no significant cost of evolving with the community. By contrast, fitness in the presence of the community increased for community-evolved populations, but decreased considerably below the ancestral state for populations evolved in the absence of the community. This suggests some abiotic beneficial mutations are costly in the presence of the community, while others are not, with the former only selected against in the presence of the community. Most mutations underpinning fitness changes were clone specific, supporting the view that there are multiple genetic pathways to adaptation in this complex environment. Such extreme mutational effects have not been observed in comparable in vitro studies that employ much simpler abiotic and biotic environments, and suggest that a caution is need when extrapolating results from simplified in vitro systems to real-world contexts.</p>
Fig. 5 in Effects of the Secondary Metabolite Producing Pseudomonas fluorescens CHA0 on Soil Protozoa and Bacteria
Fig. 5. Genetic diversity of the protozoa belonging to the Kinetoplastida. A dendrogram is constructed for each incubation time of the soil microcosms. The scale is the similarity index (S ). E. aer.: Enterobacter aerogenes.
Data from: Evolution of fitness trade-offs in locally adapted populations of Pseudomonas fluorescens
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Data from: Cheating and resistance to cheating in natural populations of the bacterium Pseudomonas fluorescens
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Data from: Evolutionary dynamics of separate and combined exposure of Pseudomonas fluorescens SBW25 to antibiotics and bacteriophage
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Data from: Siderophore cooperation of the bacterium Pseudomonas fluorescens in soil
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Data from: Bacteriocins and the assembly of natural Pseudomonas fluorescens populations
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