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The horizontal transfer of plasmids is an important driver of microbial evolution, such as conferring antibiotic resistance (AR) to new genotypes. In biofilms, the abundance of cell-cell contacts promotes the frequent transfer of plasmids and their associated genes. In this study, we expand our knowledge about AR-encoding plasmids by investigating their transfer between discrete biofilms as the biofilms grow and physically collide with each other. Using an experimental system consisting of two fluorescently labelledPseudomonas stutzeristrains and anEscherichia colistrain, we show that biofilm collisions promote plasmid transfer along the collision boundaries. The extent of plasmid transfer depends on the plasmid loss probability, the plasmid transfer probability, and the relative growth rates of plasmid-free and plasmid-carrying cells. We further show that the proliferation of plasmids after biofilm collision depends on the spatial positionings of plasmid-carrying cells along the collision boundary, thus establishing a link between the large-scale spatial distribution of discrete biofilms and the small-scale spatial arrangement of cells within individual biofilms. Our study reveals that plasmid transfer during biofilm collisions is determined by spatial factors operating at different organizational levels and length scales, expanding our understanding of the fate of plasmid-encoded traits in microbial communities.

(JSH); Abstract The effective reproductive number Re is a key indicator of the growth of an epidemic. Since the start of the SARS- CoV- 2 pandemic, many methods and online dashboards have sprung up to monitor this number through time. However, these methods are not always thoroughly tested, correctly placed in time, or are overly confident during high incidence periods. Here, we present a method for timely estimation of Re, applied to COVID- 19 epidemic data from 170 countries. We thoroughly evaluate the method on simulated data, and present an intuitive web interface for interactive data exploration. We show that, in early 2020, in the majority of countries the estimated Re dropped below 1 only after the introduction of major non-pharmaceutical interventions. For Europe the implementation of non-pharmaceutical interventions was broadly associated with reductions in the estimated Re. Globally though, relaxing non-pharmaceutical interventions had more varied effects on subsequent Re estimates. Our framework is useful to inform governments and the general public on the status of epidemics in their country, and is used as the official source of Re estimates for SARS- CoV- 2 in Switzerland. It further allows detailed comparison between countries and in relation to covariates such as implemented public health policies, mobility, behaviour, or weather data., eLife, 11, ISSN:2050-084X

Some bacterial resistance mechanisms degrade antibiotics, potentially protecting neighbouring susceptible cells from antibiotic exposure. We do not yet understand how such effects influence bacterial communities of more than two species, which are typical in nature. Here, we used experimental multispecies communities to test the effects of clinically important pOXA-48-plasmid-encoded resistance on community-level responses to antibiotics. We found resistance in one community member reduced antibiotic inhibition of other species, but some benefitted more than others. Further experiments with supernatants and pure-culture growth assays showed the susceptible species profiting most from detoxification were those that grew best at degraded antibiotic concentrations (greater than zero, but lower than the starting concentration). This pattern was also observed on agar surfaces. By contrast, we found no evidence of a role for higher-order interactions or horizontal plasmid transfer in community-level responses to detoxification in our experimental communities. Our findings suggest carriage of an antibiotic-degrading resistance mechanism by one species can drastically alter community-level responses to antibiotics, and the identities of the species that profit most from antibiotic detoxification are predicted by their intrinsic ability to grow at degraded antibiotic concentrations.

The rapid rise of antibiotic resistance, combined with the increasing cost and difficulties to develop new antibiotics, calls for treatment strategies that enable more sustainable antibiotic use. The development of such strategies, however, is impeded by the lack of suitable experimental approaches that allow testing their effects under realistic epidemiological conditions. Here, we present an approach to compare the effect of alternative multidrug treatment strategies in vitro using a robotic liquid-handling platform. We use this framework to study resistance evolution and spread implementing epidemiological population dynamics for treatment, transmission, and patient admission and discharge, as may be observed in hospitals. We perform massively parallel experimental evolution over up to 40 d and complement this with a computational model to infer the underlying population-dynamical parameters. We find that in our study, combination therapy outperforms monotherapies, as well as cycling and mixing, in minimizing resistance evolution and maximizing uninfecteds, as long as there is no influx of double resistance into the focal treated community., Proceedings of the National Academy of Sciences of the United States of America, 118 (13), ISSN:0027-8424, ISSN:1091-6490

The effective reproductive number Re is a key indicator of the growth of an epidemic. Since the start of the SARS-CoV-2 pandemic, many methods and online dashboards have sprung up to monitor this number through time. However, these methods are not always thoroughly tested, correctly placed in time, or are overly confident during high incidence periods. Here, we present a method for timely estimation of Re, applied to COVID-19 epidemic data from 170 countries. We thoroughly evaluate the method on simulated data, and present an intuitive web interface for interactive data exploration. We show that, in early 2020, in the majority of countries the estimated Re dropped below 1 only after the introduction of major non-pharmaceutical interventions. For Europe the implementation of non-pharmaceutical interventions was broadly associated with reductions in the estimated Re. Globally though, relaxing non-pharmaceutical interventions had more varied effects on subsequent Re estimates. Our framework is useful to inform governments and the general public on the status of epidemics in their country, and is used as the official source of Re estimates for SARS-CoV-2 in Switzerland. It further allows detailed comparison between countries and in relation to covariates such as implemented public health policies, mobility, behaviour, or weather data.

Eurasian beaver (Castor fiber) has been reintroduced in Switzerland between 1956 and 1977. Individuals from the refugium population in France (C. f. galliae) were released in the Rhone catchment area and in tributaries of the Rhine catchment area in Western Switzerland. Individuals from the refugium populations from Norway (C. f. fiber) and Russia (C. f. orientoeuropaeus) were released in tributaries of the Rhine catchment in Eastern Switzerland. In the Rhine basin beavers of different origins came into contact. This study provides a first evaluation of the reintroduction program of beaver in Switzerland and gives implications for the post-release genetic management of the Swiss beaver population. We report on the genetic monitoring of the beaver population in Switzerland, based on the analysis of 251 dead found individuals collected from 1998 to 2014 and a combination of mitochondrial and nuclear genetic markers. We found no evidence of the presence of North American beaver (Castor canadensis) and we observed three mitochondrial DNA haplotypes, assigned to the refugium populations in France (C. f. galliae), Norway (C. f. fiber) and Germany (C. f. albicus). Based on the analysis of seven microsatellite loci, we inferred that the beaver population in Switzerland consists of two genetic clusters and we found evidence of a zone of secondary contact. We observed low levels of genetic diversity and we could show that individuals separated by distances up to 50 km were closely related.

Bacterial pathogens that carry antibiotic resistance alleles sometimes pay a cost in the form of impaired growth in antibiotic-free conditions. This cost of resistance is expected to be a key parameter for understanding how resistance spreads and persists in pathogen populations. Analysis of individual resistance alleles from laboratory evolution and natural isolates has shown they are typically costly, but these costs are highly variable and influenced by genetic variation at other loci. It therefore remains unclear how strongly resistance is linked to impaired antibiotic-free growth in bacteria from natural and clinical scenarios, where resistance alleles are likely to coincide with other types of genetic variation. To investigate this, we measured the growth of 92 natural and clinical Escherichia coli isolates across three antibiotic-free environments. We then tested whether variation of antibiotic-free growth among isolates was predicted by their resistance to 10 antibiotics, while accounting for the phylogenetic structure of the data. We found that isolates with similar resistance profiles had similar antibiotic-free growth profiles, but it was not simply that higher average resistance was associated with impaired growth. Next, we used whole-genome sequences to identify antibiotic resistance genes and found that isolates carrying a greater number of resistance gene types grew relatively poorly in antibiotic-free conditions, even when the resistance genes they carried were different. This suggests that the resistance of bacterial pathogens is linked to growth costs in nature, but it is the total genetic burden and multivariate resistance phenotype that predict these costs, rather than individual alleles or mean resistance across antibiotics.IMPORTANCE Managing the spread of antibiotic resistance in bacterial pathogens is a major challenge for global public health. Central to this challenge is understanding whether resistance is linked to impaired bacterial growth in the absence of antibiotics, because this determines whether resistance declines when bacteria are no longer exposed to antibiotics. We studied 92 isolates of the key bacterial pathogen Escherichia coli; these isolates varied in both their antibiotic resistance genes and other parts of the genome. Taking this approach, rather than focusing on individual genetic changes associated with resistance as in much previous work, revealed that growth without antibiotics was linked to the number of specialized resistance genes carried and the combination of antibiotics to which isolates were resistant but was not linked to average antibiotic resistance. This approach provides new insights into the genetic factors driving the long-term persistence of antibiotic-resistant bacteria, which is important for future efforts to predict and manage resistance.

Managing the spread of antibiotic resistance in bacterial pathogens is a major challenge for global public health. Central to this challenge is understanding whether resistance is linked to impaired bacterial growth in the absence of antibiotics, because this determines whether resistance declines when bacteria are no longer exposed to antibiotics. We studied 92 isolates of the key bacterial pathogen Escherichia coli; these isolates varied in both their antibiotic resistance genes and other parts of the genome. Taking this approach, rather than focusing on individual genetic changes associated with resistance as in much previous work, revealed that growth without antibiotics was linked to the number of specialized resistance genes carried and the combination of antibiotics to which isolates were resistant but was not linked to average antibiotic resistance. This approach provides new insights into the genetic factors driving the long-term persistence of antibiotic-resistant bacteria, which is important for future efforts to predict and manage resistance., Bacterial pathogens that carry antibiotic resistance alleles sometimes pay a cost in the form of impaired growth in antibiotic-free conditions. This cost of resistance is expected to be a key parameter for understanding how resistance spreads and persists in pathogen populations. Analysis of individual resistance alleles from laboratory evolution and natural isolates has shown they are typically costly, but these costs are highly variable and influenced by genetic variation at other loci. It therefore remains unclear how strongly resistance is linked to impaired antibiotic-free growth in bacteria from natural and clinical scenarios, where resistance alleles are likely to coincide with other types of genetic variation. To investigate this, we measured the growth of 92 natural and clinical Escherichia coli isolates across three antibiotic-free environments. We then tested whether variation of antibiotic-free growth among isolates was predicted by their resistance to 10 antibiotics, while accounting for the phylogenetic structure of the data. We found that isolates with similar resistance profiles had similar antibiotic-free growth profiles, but it was not simply that higher average resistance was associated with impaired growth. Next, we used whole-genome sequences to identify antibiotic resistance genes and found that isolates carrying a greater number of resistance gene types grew relatively poorly in antibiotic-free conditions, even when the resistance genes they carried were different. This suggests that the resistance of bacterial pathogens is linked to growth costs in nature, but it is the total genetic burden and multivariate resistance phenotype that predict these costs, rather than individual alleles or mean resistance across antibiotics. IMPORTANCE Managing the spread of antibiotic resistance in bacterial pathogens is a major challenge for global public health. Central to this challenge is understanding whether resistance is linked to impaired bacterial growth in the absence of antibiotics, because this determines whether resistance declines when bacteria are no longer exposed to antibiotics. We studied 92 isolates of the key bacterial pathogen Escherichia coli; these isolates varied in both their antibiotic resistance genes and other parts of the genome. Taking this approach, rather than focusing on individual genetic changes associated with resistance as in much previous work, revealed that growth without antibiotics was linked to the number of specialized resistance genes carried and the combination of antibiotics to which isolates were resistant but was not linked to average antibiotic resistance. This approach provides new insights into the genetic factors driving the long-term persistence of antibiotic-resistant bacteria, which is important for future efforts to predict and manage resistance.

Background Despite being used by more than 18 million people our understanding of the extent of the effects of antiretrovirals on the human body and other organisms remains incomplete. In addition, the direct effect of antiretrovirals on the gut microbiota of HIV-infected individuals has been largely overlooked in microbiome studies concerned with HIV-infected individuals. Methods Here we tested 25 antiretrovirals on Bacillus subtilis and Escherichia coli using a broth microdilution assay to assess whether these drugs have an antibacterial effect. Results We found that several widely used antiretroviral drugs have in vitro antibacterial activity against both gram-positive and gram-negative commensal bacteria. Efavirenz inhibited the growth of B. subtilis with a minimum inhibitory concentration (MIC) of 16 μg/ml (in all three replicates), while 2‘,3‘-dideoxyinosine and zidovudine inhibited the growth of E. coli with an MIC of 16–32 μg/ml and 0.016–0.125 μg/ml (respectively). Conclusions Given the large and increasing number of individuals on antiretrovirals, and the lifelong nature of HIV treatment, this proof-of-concept report could have several potential implications, including an impact of antiretrovirals on bacterial coinfections, as well as potentials for drug discovery and repositioning.

Antibiotic resistance can impair bacterial growth or competitive ability in the absence of antibiotics, frequently referred to as a ‘cost’ of resistance. Theory and experiments emphasize the importance of such effects for the distribution of resistance in pathogenic populations. However, recent work shows that costs of resistance are highly variable depending on environmental factors such as nutrient supply and population structure, as well as genetic factors including the mechanism of resistance and genetic background. Here, we suggest that such variation can be better understood by distinguishing between the effects of resistance mechanisms on individual traits such as growth rate or yield (‘trait effects’) and effects on genotype frequencies over time (‘selective effects’). We first give a brief overview of the biological basis of costs of resistance and how trait effects may translate to selective effects in different environmental conditions. We then review empirical evidence of genetic and environmental variation of both types of effects and how such variation may be understood by combining molecular microbiological information with concepts from evolution and ecology. Ultimately, disentangling different types of costs may permit the identification of interventions that maximize the cost of resistance and therefore accelerate its decline., Evolutionary Applications, 8 (3), ISSN:1752-4571, ISSN:1752-4563

Activation of N-methyl-D-aspartate (NMDA) receptors is essential for synaptic plasticity in the central nervous system and contributes to neuronal death under various pathological conditions. Although several subunits have been cloned, the structure of NMDA receptors in situ is unresolved. By using a photoreactive antagonist with nanomolar affinity to the NMDA-binding site, three types of receptors were differentiated by their pattern of photoaffinity-labeled subunits. In adult brain, a protein of 175-kDa was photoreactive that displayed a profile of ligand binding and autoradiographical distribution corresponding to NMDA receptors. In contrast, in early postnatal brain, proteins of both 175 kDa and 115 kDa were photolabeled. This labeling pattern is switched to that of adult brain around postnatal day 10, pointing to a structural maturation of NMDA receptors. A third type of receptor could be identified in cerebellar granule cell cultures, where NMDA receptors mediate trophic effects and photolabeling was exclusively targeted to a 115-kDa protein. To identify the proteins labeled in situ, recombinant receptors were subjected to photolabeling. When the NR1 subunit was coexpressed with either the NR2A, NR2B, or NR2C subunit, only the combination of NR1/NR2A was photoreactive. Both the NR1 and NR2A subunits were photolabeled, corresponding in size to the proteins labeled in situ. However, the lack of subunit-selectivity in photolabeling the NR1/NR2A combination suggests the presence of additional receptor components in situ to explain the subunit-selective photoreactivity in adult brain (175 kDa) and in cerebellar granule cells (115 kDa). The subunit combination NR1/NR2A by itself appears insufficient to describe a major population of NMDA receptors, in particular, in adult brain.

The aim of this study is to evaluate test methods regarding their suitability to replace the Fraass breaking point as prescribed by European standards. To achieve this, a variety of modified and unmodified binders have been investigated at low and intermediate temperatures with the following series of mechanical test methods: Fraass breaking point; Bending Beam Rheometer (BBR) according to AASHTO; Direct Tensile test according to prEN; Dynamic shear rheometer (DSR) according to AASHTO; Dynamic coaxial shear test for bituminous binders (CAST-BIN); and Dynamic CAST-BIN crack resistance test newly developed by EMPA. Some of these methods can be considered as candidates for standardization, others are pure research tools designed to test a binder under conditions as close as possible to the loading during crack formation. The evaluation of the test methods regarding standardization focused on the following criteria: (1) Ranking of the results of the different tests; (2) Similarity of the test to practical loading; and (3) Information about precision and repeatability. For the covering abstract see ITRD E117423.

Elevated fasting levels of total homocysteine are now accepted as an independent risk factor for the development of arteriosclerotic vascular diseases. A polymorphism in the gene encoding methylenetetrahydrofolate reductase (MTHFR), caused by the C677T point mutation, leads to increased thermolability of the enzyme, with reduced enzyme activity. We studied the frequency of this mutation in different groups of the Swiss adult population.DNA from 361 subjects was screened for the thermolabile MTHFR variant with PCR. Included were healthy subjects without vascular disease (n = 118), older healthy subjects (n = 106), patients with coronary artery disease (CAD, n = 75), and patients with peripheral arterial occlusive disease (PAOD, n = 63).In the different groups studied, homozygosity for the mutation ranged from 4.8 to 16.2%, with a frequency of 16.2% in the healthy cohort. The allele frequencies of the thermolabile allele were 38.5 and 27.3 in young and old controls, and 37.3 and 33.3 in CAD and PAOD patients. In the healthy younger subjects the mutant allele was 1.4 times more frequent compared to the older subjects (P = 0.01). No difference in either MTHFR genotype distribution (P = 0.33) or allele frequencies (P = 0.48) between patients and controls was found. Except for the PAOD group with elevated tHcy levels for the +/+ carriers compared to the other genotypes, no statistically significant difference was found comparing homocysteine levels with genotype.This study shows no link between the mutation and the occurrence of vascular disease but we found evidence pointing to a correlation between the mutation and longevity in our population.

Despite their extensive sequence identities at the amino acid level (approximately 55%), NGF and brain-derived neurotrophic factor (BDNF) display distinct neuronal specificity toward neurons of both the PNS and CNS. To explore which region(s) within these neurotrophic factors might determine their differential actions on various subpopulations of peripheral neurons, a systematic series (homolog-scanning mutagenesis) of chimeric NGF/BDNF molecules was prepared using PCR overlap-extension techniques. After expression in COS-7 cells, the chimeric proteins were tested for their biological activities in neurite outgrowth and neuronal survival assays. This approach led to the functional expression of 12 NGF/BDNF chimeras. Surprisingly, despite replacing successive amino acid segments throughout the entire length of NGF with the corresponding parts of BDNF, all chimeras displayed full NGF-like activity in bioassays carried out with PC12 cells, embryonic chick dorsal root ganglion explants, sympathetic ganglion explants, and dissociated cultures of dorsal root ganglion neurons. Most of the chimeras additionally showed BDNF-like activity as defined by neurite outgrowth on chick nodose ganglion explants. However, none of the chimeras supported the survival of dissociated nodose ganglion neurons. Our results suggest that NGF and BDNF must share very similar higher- order protein structures, and we propose that the overall structure or conformation of NGF, in contrast to short amino acid –active-site” segments, may determine its exact neuronal specificity.