| 1. |
- Abadikhah, Marie, 1992, et al.
(author)
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Effect of anode material and dispersal limitation on the performance and biofilm community in microbial electrolysis cells
- 2023
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In: Biofilm. - 2590-2075. ; 6
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Journal article (peer-reviewed)abstract
- In a microbial electrolysis cell (MEC), the oxidization of organic compounds is facilitated by an electrogenic biofilm on the anode surface. The biofilm community composition determines the function of the system. Both deterministic and stochastic factors affect the community, but the relative importance of different factors is poorly understood. Anode material is a deterministic factor as materials with different properties may select for different microorganisms. Ecological drift is a stochastic factor, which is amplified by dispersal limitation between communities. Here, we compared the effects of three anode materials (graphene, carbon cloth, and nickel) with the effect of dispersal limitation on the function and biofilm community assembly. Twelve MECs were operated for 56 days in four hydraulically connected loops and shotgun metagenomic sequencing was used to analyse the microbial community composition on the anode surfaces at the end of the experiment. The anode material was the most important factor affecting the performance of the MECs, explaining 54–80 % of the variance observed in peak current density, total electric charge generation, and start-up lag time, while dispersal limitation explained 10–16 % of the variance. Carbon cloth anodes had the highest current generation and shortest lag time. However, dispersal limitation was the most important factor affecting microbial community structure, explaining 61–98 % of the variance in community diversity, evenness, and the relative abundance of the most abundant taxa, while anode material explained 0–20 % of the variance. The biofilms contained nine Desulfobacterota metagenome-assembled genomes (MAGs), which made up 64–89 % of the communities and were likely responsible for electricity generation in the MECs. Different MAGs dominated in different MECs. Particularly two different genotypes related to Geobacter benzoatilyticus competed for dominance on the anodes and reached relative abundances up to 83 %. The winning genotype was the same in all MECs that were hydraulically connected irrespective of anode material used.
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| 2. |
- Abadikhah, Marie, 1992, et al.
(author)
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Evidence of competition between electrogens shaping electroactive microbial communities in microbial electrolysis cells
- 2022
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In: Frontiers in Microbiology. - : Frontiers Media SA. - 1664-302X. ; 13
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Journal article (peer-reviewed)abstract
- In single-chamber microbial electrolysis cells (MECs), organic compounds are oxidized at the anode, liberating electrons that are used for hydrogen evolution at the cathode. Microbial communities on the anode and cathode surfaces and in the bulk liquid determine the function of the MEC. The communities are complex, and their assembly processes are poorly understood. We investigated MEC performance and community composition in nine MECs with a carbon cloth anode and a cathode of carbon nanoparticles, titanium, or stainless steel. Differences in lag time during the startup of replicate MECs suggested that the initial colonization by electrogenic bacteria was stochastic. A network analysis revealed negative correlations between different putatively electrogenic Deltaproteobacteria on the anode. Proximity to the conductive anode surface is important for electrogens, so the competition for space could explain the observed negative correlations. The cathode communities were dominated by hydrogen-utilizing taxa such as Methanobacterium and had a much lower proportion of negative correlations than the anodes. This could be explained by the diffusion of hydrogen throughout the cathode biofilms, reducing the need to compete for space.
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| 3. |
- Aertsen, A., et al.
(author)
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Heat shock protein-mediated resistance to high hydrostatic pressure in Escherichia coli
- 2004
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In: Applied and Environmental Microbiology. - 0099-2240. ; 70:5, s. 2660-2666
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Journal article (peer-reviewed)abstract
- A random library of Escherichia coli MG1655 genomic fragments fused to a promoterless green fluorescent protein (GFP) gene was constructed and screened by differential fluorescence induction for promoters that are induced after exposure to a sublethal high hydrostatic pressure stress. This screening yielded three promoters of genes belonging to the heat shock regulon (dnaK, lon, clpPX), suggesting a role for heat shock proteins in protection against, and/or repair of, damage caused by high pressure. Several further observations provide additional support for this hypothesis: (i) the expression of rpoH, encoding the heat shock-specific sigma factor {sigma}32, was also induced by high pressure; (ii) heat shock rendered E. coli significantly more resistant to subsequent high-pressure inactivation, and this heat shock-induced pressure resistance followed the same time course as the induction of heat shock genes; (iii) basal expression levels of GFP from heat shock promoters, and expression of several heat shock proteins as determined by two-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis of proteins extracted from pulse-labeled cells, was increased in three previously isolated pressure-resistant mutants of E. coli compared to wild-type levels.
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| 4. |
- Alalam, Hanna, et al.
(author)
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A High-Throughput Method for Screening for Genes Controlling Bacterial Conjugation of Antibiotic Resistance.
- 2020
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In: mSystems. - 2379-5077. ; 5:6
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Journal article (peer-reviewed)abstract
- The rapid horizontal transmission of antibiotic resistance genes on conjugative plasmids between bacterial host cells is a major cause of the accelerating antibiotic resistance crisis. There are currently no experimental platforms for fast and cost-efficient screening of genetic effects on antibiotic resistance transmission by conjugation, which prevents understanding and targeting conjugation. We introduce a novel experimental framework to screen for conjugation-based horizontal transmission of antibiotic resistance between >60,000 pairs of cell populations in parallel. Plasmid-carrying donor strains are constructed in high-throughput. We then mix the resistance plasmid-carrying donors with recipients in a design where only transconjugants can reproduce, measure growth in dense intervals, and extract transmission times as the growth lag. As proof-of-principle, we exhaustively explore chromosomal genes controlling F-plasmid donation within Escherichia coli populations, by screening the Keio deletion collection in high replication. We recover all seven known chromosomal gene mutants affecting conjugation as donors and identify many novel mutants, all of which diminish antibiotic resistance transmission. We validate nine of the novel genes' effects in liquid mating assays and complement one of the novel genes' effect on conjugation (rseA). The new framework holds great potential for exhaustive disclosing of candidate targets for helper drugs that delay resistance development in patients and societies and improve the longevity of current and future antibiotics. Further, the platform can easily be adapted to explore interspecies conjugation, plasmid-borne factors, and experimental evolution and be used for rapid construction of strains.IMPORTANCE The rapid transmission of antibiotic resistance genes on conjugative plasmids between bacterial host cells is a major cause of the accelerating antibiotic resistance crisis. There are currently no experimental platforms for fast and cost-efficient screening of genetic effects on antibiotic resistance transmission by conjugation, which prevents understanding and targeting conjugation. We introduce a novel experimental framework to screen for conjugation-based horizontal transmission of antibiotic resistance between >60,000 pairs of cell populations in parallel. As proof-of-principle, we exhaustively explore chromosomal genes controlling F-plasmid donation within E. coli populations. We recover all previously known and many novel chromosomal gene mutants that affect conjugation efficiency. The new framework holds great potential for rapid screening of compounds that decrease transmission. Further, the platform can easily be adapted to explore interspecies conjugation, plasmid-borne factors, and experimental evolution and be used for rapid construction of strains.
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| 5. |
- Alalam, Hanna, et al.
(author)
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Conjugation factors controlling F-plasmid antibiotic resistance transmission
- 2018
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In: BioRxiv. - : Cold Spring Harbor Laboratory.
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Journal article (other academic/artistic)abstract
- The rapid horizontal transmission of many antibiotic resistance genes between bacterial host cells on conjugative plasmids is a major cause of the accelerating antibiotic resistance crisis. Preventing understanding and targeting conjugation, there currently are no experimental platforms for fast and cost-efficient screening of genetic effects on antibiotic resistance transmission by conjugation. We introduce a novel experimental framework to screen for conjugation based horizontal transmission of antibiotic resistance between >60,000 pairs of cell populations in parallel. Plasmid-carrying donor strains are constructed in high throughput. We then mix the resistance plasmid carrying donors with recipients in a design where only transconjugants can reproduce, measure growth in dense intervals and extract transmission times as the growth lag. As proof-of-principle, we exhaustively explored chromosomal genes controlling F plasmid donation within E. coli populations, by screening the Keio deletion collection at high replication. We recover all six known chromosomal gene mutants affecting conjugation and identify >50 novel factors, all of which diminish antibiotic resistance transmission. We verify 10 of the novel genes' effects in a liquid mating assay. The new framework holds great potential for exhaustive disclosing of candidate targets for helper drugs that delay resistance development in patients and societies and improves the longevity of current and future antibiotics.
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| 6. |
- Benkwitz-Bedford, Sam, et al.
(author)
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Machine Learning Prediction of Resistance to Subinhibitory Antimicrobial Concentrations from Escherichia coli Genomes.
- 2021
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In: mSystems. - 2379-5077. ; 6:4
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Journal article (peer-reviewed)abstract
- Escherichia coli is an important cause of bacterial infections worldwide, with multidrug-resistant strains incurring substantial costs on human lives. Besides therapeutic concentrations of antimicrobials in health care settings, the presence of subinhibitory antimicrobial residues in the environment and in clinics selects for antimicrobial resistance (AMR), but the underlying genetic repertoire is less well understood. Here, we used machine learning to predict the population doubling time and cell growth yield of 1,407 genetically diverse E. coli strains expanding under exposure to three subinhibitory concentrations of six classes of antimicrobials from single-nucleotide genetic variants, accessory gene variation, and the presence of known AMR genes. We predicted cell growth yields in the held-out test data with an average correlation (Spearman's ρ) of 0.63 (0.36 to 0.81 across concentrations) and cell doubling times with an average correlation of 0.59 (0.32 to 0.92 across concentrations), with moderate increases in sample size unlikely to improve predictions further. This finding points to the remaining missing heritability of growth under antimicrobial exposure being explained by effects that are too rare or weak to be captured unless sample size is dramatically increased, or by effects other than those conferred by the presence of individual single-nucleotide polymorphisms (SNPs) and genes. Predictions based on whole-genome information were generally superior to those based only on known AMR genes and were accurate for AMR resistance at therapeutic concentrations. We pinpointed genes and SNPs determining the predicted growth and thereby recapitulated many known AMR determinants. Finally, we estimated the effect sizes of resistance genes across the entire collection of strains, disclosing the growth effects for known resistance genes in each individual strain. Our results underscore the potential of predictive modeling of growth patterns from genomic data under subinhibitory concentrations of antimicrobials, although the remaining missing heritability poses a challenge for achieving the accuracy and precision required for clinical use. IMPORTANCE Predicting bacterial growth from genome sequences is important for a rapid characterization of strains in clinical diagnostics and to disclose candidate novel targets for anti-infective drugs. Previous studies have dissected the relationship between bacterial growth and genotype in mutant libraries for laboratory strains, yet no study so far has examined the predictive power of genome sequence in natural strains. In this study, we used a high-throughput phenotypic assay to measure the growth of a systematic collection of natural Escherichia coli strains and then employed machine learning models to predict bacterial growth from genomic data under nontherapeutic subinhibitory concentrations of antimicrobials that are common in nonclinical settings. We found a moderate to strong correlation between predicted and actual values for the different collected data sets. Moreover, we observed that the known resistance genes are still effective at sublethal concentrations, pointing to clinical implications of these concentrations.
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| 7. |
- Bourgard, Catarina, 1985, et al.
(author)
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Development of Dicationic Bisguanidine-Arylfuran Derivatives as Potent Agents against Gram-Negative Bacteria.
- 2022
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In: Antibiotics. - : MDPI AG. - 2079-6382. ; 11:8
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Journal article (peer-reviewed)abstract
- Antibiotic resistance among bacteria is a growing global challenge. A major reason for this is the limited progress in developing new classes of antibiotics active against Gram-negative bacteria. Here, we investigate the antibacterial activity of a dicationic bisguanidine-arylfuran, originally developed as an antitrypanosomal agent, and new derivatives thereof. The compounds showed good activity (EC50 2-20 µM) against antibiotic-resistant isolates of the Gram-negative members of the ESKAPE group (Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp.) and Escherichia coli with different antibiotic susceptibility patterns, including ESBL isolates. Cytotoxicity was moderate, and several of the new derivatives were less cytotoxic than the lead molecule, offering better selectivity indices (40-80 for several ESKAPE isolates). The molecular mechanism for the antibacterial activity of these molecules is unknown, but sensitivity profiling against human ESKAPE isolates and E. coli collections with known susceptibility patterns against established antibiotics indicates that it is distinct from lactam and quinolone antibiotics.
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| 8. |
- Farewell, Anne, 1961
(author)
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Rising to the Top: Promoting Deeper Learning in the Laboratory
- 2018
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In: National Center for Case Study Teaching in Science.
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Book chapter (peer-reviewed)abstract
- Inquiry-based labs differ from cookbook labs in that inquiry-based labs contain an element of experimentation. A cookbook lab can be performed by a student without understanding any of the theory connected with the exercise whereas inquiry-based labs require a degree of conceptual knowledge for a student to perform the lab. Inquiry-based labs also strengthen and deepen students understanding of topics discussed in lectures or reading assignments. There are many variations and degrees of inquiry in these labs ranging from a lab that is entirely designed by the students to those that include small questions requiring that the students predict the outcomes of a lab or fill in missing information (guided inquiry). A simple specific example of a cookbook lab would be instructing students to measure volume changes between ice and liquid water. The students would be given step by step instructions to follow and would not need to apply any conceptual knowledge. An inquiry based lab on the same topic would allow the students to design their own experiment to discover how the volume of liquid water differs from that of ice. One goal of this activity is to introduce inquiry-based lab design. Beyond lab design, lab supervision is crucial to encouraging students to use their conceptual knowledge when doing a practical lab. Lab assistants or teachers who are involved in the lab can use student questions to encourage deeper understanding. This case study includes a role-play exercise for this skill. This case study has been designed to be used in science education courses for both graduate student laboratory assistants and lecturers or professors in natural sciences at the university or college level. It includes discussion and role-play of a hypothetical laboratory. No specific knowledge of biology or chemistry is needed beyond high school level to complete this task, though knowledge of the existence of microorganisms (yeast) and proteins is assumed. In addition, this activity is suitable for participants with little or no pedagogics training.
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| 9. |
- Farewell, Anne, 1961
(author)
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Teaching Science: Design of a Master’s Level Biology Course
- 2015
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In: Pedagogical Essays, The unit for Pedagogical Development and Interactive Learning (PIL). - Göteborg : University of Gothenburg.
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Other publication (other academic/artistic)abstract
- In this work, I describe the development of a Master’s level microbiology course which uses an active learning approach to encourage the students to think scientifically about the course material and gives the students training in experimental design, data analysis, literature research and scientific oral and written presentation. The course combines a case study approach with an inquiry based lab. I discuss how the students are formatively assessed in the course and how this becomes a motivational tool. Finally, I discuss the feedback from the students in terms of course evaluation.
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| 10. |
- Farewell, Anne, 1961, et al.
(author)
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The potential improvement of team-working skills in Biomedical and Natural Science students using a problem-based learning approach.
- 2013
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In: Journal of Problem Based Learning in Higher Education. - 2246-0918. ; 1:1, s. 84-93
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Journal article (peer-reviewed)abstract
- Teamwork has become an integral part of most organisations today, and it is clearly important in Science and other disciplines. In Science, research teams increase in size while the number of single-authored papers and patents decline. Team-work in laboratory sciences permits projects that are too big or complex for one individual to be tackled. This development requires that students gain experience of team-work before they start their professional career. Students working in teams this may increase productivity, confidence, innovative capacity and improvement of interpersonal skills. Problem-based learning (PBL) is an instructional approach focusing on real analytical problems as a means of training an analytical scientist. PBL may have a positive impact on team-work skills that are important for undergraduates and postgraduates to enable effective collaborative work. This survey of the current literature explores the development of the team-work skills in Biomedical Science students using PBL.
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