Investigating evolutionary trade-offs for designing novel strategies to slow down evolution of antibiotic resistance

Antibiotic resistance is a global public health problem. The straightforward solution to this problem is developing new antibiotics that can kill all of the drug resistant bugs, alas; this has not been possible so far due to economic and natural limitations. Another plausible solution to this problem is the effective use of already existing antibiotics by designing novel treatment strategies. However, efforts towards finding such strategies have not been rewarding to the date due to our limited knowledge about the origins of antibiotic resistance at the molecular and population levels. In order to tackle this problem, we performed an extensive laboratory evolution experiment where we evolved drug sensitive E.coli populations against 22 different clinically important antibiotic compounds and systematically phenotyped and genotyped evolved populations. Benefiting from this extensive data set, we identified common genetic targets for resistance conferring mutations and resulting phenotypic changes. Our analysis allows us design effective multidrug treatments strategies that can slow down evolution of antibiotic resistance. We hope that, the methodologies that were developed throughout this study will also be helpful for finding effective therapies for combating cancer and immune disease

Strength of selection pressure is an important parameter contributing to the complexity of antibiotic resistance evolution

Revealing the genetic changes responsible for antibiotic resistance can be critical for developing novel antibiotic therapies. However, systematic studies correlating genotype to phenotype in the context of antibiotic resistance have been missing. In order to fill in this gap, we evolved 88 isogenic Escherichia coli populations against 22 antibiotics for 3 weeks. For every drug, two populations were evolved under strong selection and two populations were evolved under mild selection. By quantifying evolved populations' resistances against all 22 drugs, we constructed two separate cross-resistance networks for strongly and mildly selected populations. Subsequently, we sequenced representative colonies isolated from evolved populations for revealing the genetic basis for novel phenotypes. Bacterial populations that evolved resistance against antibiotics under strong selection acquired high levels of cross-resistance against several antibiotics, whereas other bacterial populations evolved under milder selection acquired relatively weaker cross-resistance. In addition, we found that strongly selected strains against aminoglycosides became more susceptible to five other drug classes compared with their wild-type ancestor as a result of a point mutation on TrkH, an ion transporter protein. Our findings suggest that selection strength is an important parameter contributing to the complexity of antibiotic resistance problem and use of high doses of antibiotics to clear infections has the potential to promote increase of cross-resistance in clinics

3D Organoid modelling of hepatoblast-like and mesenchymal-like hepatocellular carcinoma cell lines

Aim: We wished to establish 3D organoid-like hepatocellular carcinoma (HCC) models from HCC cell lines.Methods: Hep3B, Huh7, HepG2, SNU398, SNU449, and SNU475 cell lines were inoculated into Matrigel and grown up to 9 days in hepatocyte specific or standard RPMI media. Spheroid formation was followed by light microscopy. Matrigel scaffolds were immobilized and embedded in paraffin, and sections were subjected to H&E and immunohistochemical staining for different hepatobiliary biomarkers. Stained material was examined under light microscopy and micro photo were taken.Results: Organoid-like structures were obtained successfully from all selected cell lines except mesenchymal-like SNU475 cells. Hep3B, Huh7, and HepG2 cell lines from hepatoblast-like sub-group formed compact 3D colonies and showed hepatocyte-like morphology and staining with different hepatocyte lineage markers as well as hepatobiliary progenitor markers. SNU398 and SNU449 cell lines from mesenchymal-like group formed irregular and loose 3D colonies that expressed vimentin homogeneously, but also several epithelial and hepatocyte lineage markers. The pattern of biomarker expression was unique for each cell line tested. Such features, not observed in tested monolayer cultures were confirmed with single-cell derived Hep3B cells.Conclusion: We described experimental conditions to obtain organoid-like structures from five different HCC cell lines representing hepatoblast-like and mesenchymal-like subgroups. These models are useful as an alternative to monolayer cultures to study phenotypic features of HCC cells. Our detailed analysis of biomarker expression in five different organoid-like structures provide convincing evidence for highly specific phenotypic features of these cell lines although they share some common or subtype-restricted features also

The effect of medium and light wavelength towards Stichococcus bacillaris fatty acid production and composition

WOS: 000475746800129PubMed: 31323717Introduction of novel species will highlight technical feasibility of microalgae-based biofuels for commercial applications. This paper reports the effect of culture medium and light wavelength on biomass and fatty acid production of S. bacillaris which holds some advantages as short life cycle, easy cultivation, high lipid content, diversity of fatty acids and stability under harsh environmental conditions. the results displayed that, soil extract (SE) greatly enhance growth rate of cultures. Maximum biomass and lipid productivity were achieved in TAP medium as 81 mg/L.day, 19.44 mg/L.day; respectively. Light wavelength didn't significantly change growth kinetics but played a critical role on chlorophyll-a accumulation. C14:0, C16:0 and C18:0 fatty acids were abundant which are suitable for biodiesel conversion. Interestingly, blue and red light increased longer chain fatty acids content. These results indicated that; S. bacillaris holds potential for further development of biodiesel production and feasibility of algal biodiesel for fundamental and applied sciences

Do error predictions of perceived exertion inform the level of running pleasure? Stage 2 Registered Report

Humans have the ability to mentally project themselves into future events (prospective thinking) to promote the implementation of health-oriented behaviors, such as the planning of daily physical exercise sessions. Nevertheless, it is currently unclear whether and how prospective thinking can assist individuals in generating future predictions about their own bodily states, such as when anticipating the level of perceived exertion to be experienced in a forthcoming physical exercise session, and whether these predictions influence the subjective experience of pleasure in a session. Here, based on the literature on reward prediction errors, we argue that running sessions that are experienced with a lower intensity of ratings of perceived exertion (RPE) than expected are associated with a higher level of pleasure, and vice versa. To test this hypothesis, we created a novel marker, the RPE-based prediction error, by comparing RPE before (prospective RPE) and after (retrospective RPE) each running session among participants in a start-to-run program (N = 66). Retrospective ratings of running pleasure was assessed by the participant after each running session of the program. Using this approach, linear mixed models showed that a positive RPE-based prediction error (lower score of retrospective RPE than prospective RPE) is associated with a higher level of retrospective pleasure. This study thus demonstrates that the use of prospective and retrospective RPE is beneficial for predicting the experience of running pleasure. We further discuss how future studies should help to better understand the impact of RPE-based prediction error on exercise pleasure and whether this new marker may be used to ultimately impact humans' commitment to physical exercise

Modular Fabrication of Polymer Brush Coated Magnetic Nanoparticles: Engineering the Interface for Targeted Cellular Imaging

Development of efficient and rapid protocols for diversification of functional magnetic nanoparticles (MNPs) would enable identification of promising candidates using high-throughput protocols for applications such as diagnostics and cure through early detection and localized delivery. Polymer brush coated magnetic nanoparticles find use in many such applications. A protocol that allows modular diversification of a pool of parent polymer coated nanoparticles will lead to a library of functional materials with improved uniformity. In the present study, polymer brush coated parent magnetic nanoparticles obtained using reversible addition–fragmentation chain transfer (RAFT) polymerization are modified to obtain nanoparticles with different “clickable” groups. In this design, trithiocarbonate group terminated polymer brushes are “grafted from” MNPs using a catechol group bearing initiator. A postpolymerization radical exchange reaction allows installation of “clickable” functional groups like azides and maleimides on the chain ends of the polymers. Thus, modified MNPs can be functionalized using alkyne-containing and thiol-containing moieties like peptides and dyes using the alkyne–azide cycloaddition and the thiol–ene conjugation, respectively. Using the approach outlined here, a cell surface receptor targeting cyclic peptide and a fluorescent dye are attached onto nanoparticle surface. This multifunctional construct allows selective recognition of cancer cells that overexpress integrin receptors. Furthermore, the approach outlined here is not limited to the installation of azide and maleimide functional groups but can be expanded to a variety of “clickable” groups to allow nanoparticle modification using a broad range of chemical conjugations

Comparison of physical activity levels among different sub-types of axial spondyloarthritis patients and healthy controls

Objective