scholarly journals Step-specific adaptation and trade-off over the course of an infection by GASP-mutation small colony variants

2020 ◽  
Author(s):  
Faucher Christian ◽  
Mazana Vincent ◽  
Kardacz Marion ◽  
Parthuisot Nathalie ◽  
Ferdy Jean-Baptiste ◽  
...  
Keyword(s):  
Drosophila Melanogaster ◽  
Chronic Phase ◽  
Infection Process ◽  
Infection Model ◽  
Xenorhabdus Nematophila ◽  
Trade Off ◽  
Small Colony Variants ◽  
Trade Offs ◽  
Small Colony ◽  
Host Evolution

AbstractDuring an infection, parasites face a succession of challenges, each decisive for disease outcome. The diversity of challenges requires a series of parasite adaptations to successfully multiply and transmit from host to host. Thus, the pathogen genotypes which succeed during one step might be counter-selected in later stages of the infection. Using the bacteria Xenorhabdus nematophila and adult Drosophila melanogaster as hosts, we showed that such step-specific adaptations, here linked to GASP mutations in the X. nematophila master gene regulator lrp, exist and can trade-off with each other. We found that nonsense lrp mutations had lowered ability to resist the host immune response, while all classes of mutations in lrp were associated with a decrease in the ability to proliferate during early infection. We demonstrate that reduced proliferation of X. nematophila best explains diminished virulence in this infection model. Finally, decreased proliferation during the first step of infection is accompanied with improved proliferation during late infection, suggesting a trade-off between the adaptations to each step. Step-specific adaptations could play a crucial role in the chronic phase of infections in any diseases that show similar small colony variants (also known as SCV) to X. nematophila.ImportanceWithin-host evolution has been described in many bacterial diseases, and the genetic basis behind the adaptations stimulated a lot of interest. Yet, the studied adaptations are generally focused on antibiotic resistance, rarely on the adaptation to the environment given by the host, and the potential trade-off hindering adaptations to each step of the infection are rarely considered. Those trade-offs are key to understand intra-host evolution, and thus the dynamics of the infection. However, the understanding of these trade-offs supposes a detailed study of host-pathogen interactions at each step of the infection process, with for each step an adapted methodology. Using Drosophila melanogaster as host and the bacteria Xenorhabdus nematophila, we investigated the bacterial adaptations resulting from GASP mutations known to induce small colony variant (SCV) phenotype positively selected within-the-host over the course of an infection, and the trade-off between step-specific adaptations.

scholarly journals Phenotypic diversification in vivo: Pseudomonas aeruginosa gacS− strains generate small colony variants in vivo that are distinct from in vitro variants

Microbiology ◽  
2010 ◽  
Vol 156 (12) ◽  
pp. 3699-3709 ◽  
Author(s):  
Lisa K. Nelson ◽  
M. Mark Stanton ◽  
Robyn E. A. Elphinstone ◽  
Janessa Helwerda ◽  
Raymond J. Turner ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Phenotypic Variation ◽  
Antimicrobial Agents ◽  
Mucosal Surface ◽  
Infection Model ◽  
Bacterial Survival ◽  
Small Colony Variants ◽  
Small Colony

Pseudomonas aeruginosa has long been known to produce phenotypic variants during chronic mucosal surface infections. These variants are thought to be generated to ensure bacterial survival against the diverse challenges in the mucosal environment. Studies have begun to elucidate the mechanisms by which these variants emerge in vitro; however, too little information exists on phenotypic variation in vivo to draw any links between variants generated in vitro and in vivo. Consequently, in this study, the P. aeruginosa gacS gene, which has previously been linked to the generation of small colony variants (SCVs) in vitro, was studied in an in vivo mucosal surface infection model. More specifically, the rat prostate served as a model mucosal surface to test for the appearance of SCVs in vivo following infections with P. aeruginosa gacS− strains. As in in vitro studies, deletion of the gacS gene led to SCV production in vivo. The appearance of these in vivo SCVs was important for the sustainability of a chronic infection. In the subset of rats in which P. aeruginosa gacS− did not convert to SCVs, clearance of the bacteria took place and healing of the tissue ensued. When comparing the SCVs that arose at the mucosal surface (MS-SCVs) with in vitro SCVs (IV-SCVs) from the same gacS− parent, some differences between the phenotypic variants were observed. Whereas both MS-SCVs and IV-SCVs formed dense biofilms, MS-SCVs exhibited a less diverse resistance profile to antimicrobial agents than IV-SCVs. Additionally, MS-SCVs were better suited to initiate an infection in the rat model than IV-SCVs. Together, these observations suggest that phenotypic variation in vivo can be important for maintenance of infection, and that in vivo variants may differ from in vitro variants generated from the same genetic parent.

scholarly journals Virulence of Staphylococcus aureus Small Colony Variants in the Caenorhabditis elegans Infection Model

2006 ◽  
Vol 74 (2) ◽  
pp. 1091-1096 ◽  
Author(s):  
Costi D. Sifri ◽  
Andrea Baresch-Bernal ◽  
Stephen B. Calderwood ◽  
Christof von Eiff
Keyword(s):  
Staphylococcus Aureus ◽  
Caenorhabditis Elegans ◽  
Infection Model ◽  
Alternative Host ◽  
Antibiotic Resistant ◽  
Small Colony Variants ◽  
C Elegans ◽  
Small Colony ◽  
Morphological Variants ◽  
Slow Growing

ABSTRACT Small colony variants (SCVs) of Staphylococcus aureus are slow-growing morphological variants that have been implicated in persistent, relapsing, and antibiotic-resistant infections. The altered phenotype of SCVs in most strains has been attributed to defects in electron transport due to mutations in hemin or menadione biosynthesis. The pathogenic capacity of SCVs compared to phenotypically normal strains is variable depending on the attribute examined, with some studies showing reduced virulence of SCVs and others demonstrating normal or heightened virulence. Recently, the nematode Caenorhabditis elegans has been successfully employed as an alternative host to investigate virulence mechanisms of a variety of bacterial pathogens, including S. aureus. In this study, we show that clinical SCVs as well as hemB- and menD-deficient mutants of S. aureus are greatly reduced in virulence in the C. elegans infection model.

scholarly journals Rapid evolution of learning and reproduction in natural populations of Drosophila melanogaster

2018 ◽  
Author(s):  
Emily L. Behrman ◽  
Tadeusz J. Kawecki ◽  
Paul Schmidt
Keyword(s):  
Drosophila Melanogaster ◽  
Evolutionary Dynamics ◽  
Rna Binding ◽  
Rapid Evolution ◽  
Learning Ability ◽  
Learning Performance ◽  
General Mechanism ◽  
Behavioural Plasticity ◽  
Trade Off ◽  
Trade Offs

AbstractLearning is a general mechanism of adaptive behavioural plasticity whose benefits and costs depend on the environment. Thus, seasonal oscillations in temperate environments between winter and summer might produce cyclical selection pressures that would drive rapid evolution of learning performance in multivoltine populations. To test this hypothesis, we investigated the evolutionary dynamics of learning ability over this rapid seasonal timescale in a natural population of Drosophila melanogaster. Associative learning was tested in common garden-raised flies collected from nature in the spring and fall over three consecutive years. The spring flies consistently learned better than fall flies, revealing seasonal evolution of improved learning performance in nature. Fecundity showed the opposite seasonal pattern, suggesting a trade-off between learning and reproduction. This trade-off also held within population: more fecund individual females learned less well. This trade-off is mediated at least in part by natural polymorphism in the RNA binding protein couch potato (cpo), with a genotype favoured during summer showing poorer learning performance and higher fecundity than a genotype favoured over winter. Thus, seasonal environments can drive rapid cyclical evolution of learning performance, but the evolutionary dynamics may be driven by trade-offs generated by pleiotropic effects of causative alleles selected for other reasons.

scholarly journals Genomic and transcriptomic characterization of Pseudomonas aeruginosa small colony variants derived from a chronic infection model

2019 ◽  
Vol 5 (4) ◽  
Author(s):  
Sharon Irvine ◽  
Boyke Bunk ◽  
Hannah K. Bayes ◽  
Cathrin Spröer ◽  
James P. R. Connolly ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Chronic Infection ◽  
Infection Model ◽  
Small Colony Variants ◽  
Small Colony

Dual Goals for Speed and Accuracy on the Same Performance Task

2012 ◽  
Vol 11 (3) ◽  
pp. 118-126 ◽  
Author(s):  
Olive Emil Wetter ◽  
Jürgen Wegge ◽  
Klaus Jonas ◽  
Klaus-Helmut Schmidt
Keyword(s):  
Memory Scanning ◽  
Performance Task ◽  
Performance Tasks ◽  
Trade Off ◽  
Test Experiment ◽  
Trade Offs ◽  
New Finding ◽  
Sternberg Paradigm ◽  
Speed Accuracy ◽  
Speed And Accuracy

In most work contexts, several performance goals coexist, and conflicts between them and trade-offs can occur. Our paper is the first to contrast a dual goal for speed and accuracy with a single goal for speed on the same task. The Sternberg paradigm (Experiment 1, n = 57) and the d2 test (Experiment 2, n = 19) were used as performance tasks. Speed measures and errors revealed in both experiments that dual as well as single goals increase performance by enhancing memory scanning. However, the single speed goal triggered a speed-accuracy trade-off, favoring speed over accuracy, whereas this was not the case with the dual goal. In difficult trials, dual goals slowed down scanning processes again so that errors could be prevented. This new finding is particularly relevant for security domains, where both aspects have to be managed simultaneously.

The Effects of Decision Time on Perceptions of Decisions and Decision Makers in (Moral) Trade-Off Scenarios

2019 ◽  
Author(s):  
Anna Katharina Spälti ◽  
Mark John Brandt ◽  
Marcel Zeelenberg
Keyword(s):  
Decision Process ◽  
Decision Time ◽  
Decision Makers ◽  
Process Information ◽  
Total N ◽  
Trade Off ◽  
Financial Gain ◽  
Trade Offs ◽  
Sacred Values ◽  
Moral Context

People often have to make trade-offs. We study three types of trade-offs: 1) "secular trade-offs" where no moral or sacred values are at stake, 2) "taboo trade-offs" where sacred values are pitted against financial gain, and 3) "tragic trade-offs" where sacred values are pitted against other sacred values. Previous research (Critcher et al., 2011; Tetlock et al., 2000) demonstrated that tragic and taboo trade-offs are not only evaluated by their outcomes, but are also evaluated based on the time it took to make the choice. We investigate two outstanding questions: 1) whether the effect of decision time differs for evaluations of decisions compared to decision makers and 2) whether moral contexts are unique in their ability to influence character evaluations through decision process information. In two experiments (total N = 1434) we find that decision time affects character evaluations, but not evaluations of the decision itself. There were no significant differences between tragic trade-offs and secular trade-offs, suggesting that the decisions structure may be more important in evaluations than moral context. Additionally, the magnitude of the effect of decision time shows us that decision time, may be of less practical use than expected. We thus urge, to take a closer examination of the processes underlying decision time and its perception.

Predicting Undesired Treatment Outcome in Mental Healthcare: Machine Learning Study (Preprint)

2019 ◽  
Author(s):  
Kasper Van Mens ◽  
Joran Lokkerbol ◽  
Richard Janssen ◽  
Robert de Lange ◽  
Bea Tiemens
Keyword(s):  
Machine Learning ◽  
Treatment Outcome ◽  
Mental Health Treatment ◽  
Mental Healthcare ◽  
Machine Learning Algorithms ◽  
Gradient Boosting ◽  
Trade Off ◽  
Trade Offs ◽  
Outcome Monitoring ◽  
Extreme Gradient Boosting

BACKGROUND It remains a challenge to predict which treatment will work for which patient in mental healthcare. OBJECTIVE In this study we compare machine algorithms to predict during treatment which patients will not benefit from brief mental health treatment and present trade-offs that must be considered before an algorithm can be used in clinical practice. METHODS Using an anonymized dataset containing routine outcome monitoring data from a mental healthcare organization in the Netherlands (n = 2,655), we applied three machine learning algorithms to predict treatment outcome. The algorithms were internally validated with cross-validation on a training sample (n = 1,860) and externally validated on an unseen test sample (n = 795). RESULTS The performance of the three algorithms did not significantly differ on the test set. With a default classification cut-off at 0.5 predicted probability, the extreme gradient boosting algorithm showed the highest positive predictive value (ppv) of 0.71(0.61 – 0.77) with a sensitivity of 0.35 (0.29 – 0.41) and area under the curve of 0.78. A trade-off can be made between ppv and sensitivity by choosing different cut-off probabilities. With a cut-off at 0.63, the ppv increased to 0.87 and the sensitivity dropped to 0.17. With a cut-off of at 0.38, the ppv decreased to 0.61 and the sensitivity increased to 0.57. CONCLUSIONS Machine learning can be used to predict treatment outcomes based on routine monitoring data.This allows practitioners to choose their own trade-off between being selective and more certain versus inclusive and less certain.

Challenges in the Empirical Study of Global Governance Legitimacy

2018 ◽  
Author(s):  
Steven Bernstein
Keyword(s):  
Empirical Study ◽  
Global Governance ◽  
Research Agenda ◽  
Cultural Factors ◽  
Theory Building ◽  
Trade Off ◽  
Trade Offs ◽  
Different Types ◽  
Political Communities

This commentary discusses three challenges for the promising and ambitious research agenda outlined in the volume. First, it interrogates the volume’s attempts to differentiate political communities of legitimation, which may vary widely in composition, power, and relevance across institutions and geographies, with important implications not only for who matters, but also for what gets legitimated, and with what consequences. Second, it examines avenues to overcome possible trade-offs from gains in empirical tractability achieved through the volume’s focus on actor beliefs and strategies. One such trade-off is less attention to evolving norms and cultural factors that may underpin actors’ expectations about what legitimacy requires. Third, it addresses the challenge of theory building that can link legitimacy sources, (de)legitimation practices, audiences, and consequences of legitimacy across different types of institutions.

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