Biology subjects

Wechsler, T.

Publications and source records attributed to Wechsler, T..

9 recordsLinked to original sources

bioRxiv2026

Assessing the impact of renewable energy installations on biodiversity and identifying sustainable trade-offs

Renewable energy is crucial to achieve climate neutrality, but its rapid expansion can threaten biodiversity through habitat loss or fragmentation and ecological disruption. We present a spatially explicit assessment framework that quantifies biodiversity impacts from land use change associated with renewable energy infrastructure across a broad range of species groups, and identifies siting configurations that balance energy provision and conservation goals. Drawing on metrics from life cycle assessment, combined with species distribution models and siting strategies, we evaluate alternative deployment strategies. Using Switzerland as a case study, we compare three siting strategies (maximizing energy output, minimizing biodiversity impact, and a trade-off approach) for photovoltaic systems, run-of-river hydropower, and wind turbines. For solar and hydropower installations, prioritizing energy efficiency yields the highest cumulative biodiversity losses. However, these impacts can be substantially reduced with only a slight increase in land use by favouring biodiversity protection. For wind installations, strict avoidance of sensitive ecosystems may increase total impacts, as less efficient and therefore additional sites are required to achieve the same annual energy yield. Overall, our results show that trade-off-based siting strategies can effectively balance performance and biodiversity protection, highlighting that renewable energy can be provided without sacrificing sensitive ecosystems.

ecology↗

bioRxiv2024

Interactions between Pseudomonas aeruginosa and six opportunistic pathogens cover a broad spectrum from mutualism to antagonism

Bacterial infections often involve more than one pathogen. While it is known that polymicrobial infections can impact disease outcomes, we have a poor understanding about how pathogens affect each others behaviour and fitness. Here, we used a microscopy approach to explore interactions between Pseudomonas aeruginosa and six opportunistic human pathogens that often co-occur in polymicrobial infections: Acinetobacter baumannii, Burkholderia cenocepacia, Escherichia coli, Enterococcus faecium, Klebsiella pneumoniae, and Staphylococcus aureus. When following growing micro-colonies on agarose pads over time, we observed a broad spectrum of species-specific ecological interactions, ranging from mutualism to antagonism. For example, P. aeruginosa engaged in a mutually beneficial interaction with E. faecium but suffered from antagonism by E. coli and K. pneumoniae. While we found little evidence for active directional growth towards or away from cohabitants, we observed that certain species increased growth in double layers in co-cultures and that physical forces due to fast colony expansion had a major impact on fitness and interaction patterns. Overall, our work provides an atlas of pathogen interactions, potentially useful to understand species dynamics in polymicrobial infections. We discuss possible mechanisms driving pathogen interactions and offer predictions of how the different ecological interactions could affect virulence.

microbiology↗

bioRxiv2024

Olive Flowering dependence on winter temperatures - linking empirical results to a dynamic model

Increasing winter temperatures jeopardize the yield of fruit trees requiring a prolonged and sufficiently cold winter to flower. Assessing the exact risk to different crop varieties is the first step in mitigating the harmful effect of climate change. Since empirically testing the impacts of many temperature scenarios is very time-consuming, quantitative predictive models could be extremely helpful in reducing the number of experiments needed. Here, we focus on olive (Olea europaea) - a traditional crop in the Mediterranean basin, a region expected to be severely affected by climatic change. Olive flowering and consequently yield depend on the sufficiency of cold periods and the lack of warm ones during the preceding winter. Yet, a satisfactory quantitative model forecasting its expected flowering under natural temperature conditions is still lacking. Previous models simply summed the number of cold hours during winter, as a proxy for flowering, but exhibited only mediocre agreement with empirical flowering values, possibly because they overlooked the order of occurrence of different temperatures. We empirically tested the effect of different temperature regimes on olive flowering intensity and flowering-gene expression. To predict flowering based on winter temperatures, we constructed a dynamic model, describing the response of a putative flowering factor to the temperature signal. The crucial ingredient in the model is an unstable intermediate, produced and degraded at temperature-dependent rates. Our model accounts not only for the number of cold and warm hours but also for their order. We used sets of empirical flowering and temperature data to fit the model parameters, applying numerical constrained optimization techniques, and successfully validated the model outcomes. Our model more accurately predicts flowering under winters with warm periods yielding low-to-moderate flowering and is more robust compared to previous models. This model is the first step toward a practical predictive tool, applicable under various temperature conditions.

plant biology↗

bioRxiv2024

A new protocol for multispecies bacterial infections in zebrafish and their monitoring through automated image analysis

The zebrafish Danio rerio has become a popular model host to explore disease pathology caused by infectious agents. A main advantage is its transparency at an early age, which enables live imaging of infection dynamics. While multispecies infections are common in patients, the zebrafish model is rarely used to study them, although the model would be ideal for investigating pathogen-pathogen and pathogen-host interactions. This may be due to the absence of an established multispecies infection protocol for a defined organ and the lack of suitable image analysis pipelines for automated image processing. To address these issues, we developed a protocol for establishing and tracking single and multispecies bacterial infections in the inner ear structure (otic vesicle) of the zebrafish by imaging. Subsequently, we generated an image analysis pipeline that involved deep learning for the automated segmentation of the otic vesicle, and scripts for quantifying pathogen frequencies through fluorescence intensity measures. We used Pseudomonas aeruginosa, Acinetobacter baumannii, and Klebsiella pneumoniae, three of the difficult-to-treat ESKAPE pathogens, to show that our infection protocol and image analysis pipeline work both for single pathogens and pairwise pathogen combinations. Thus, our protocols provide a comprehensive toolbox for studying single and multispecies infections in real-time in zebrafish.

microbiology↗

bioRxiv2023

Space and epigenetic inheritance determine inter-individual differences in siderophore gene expression in bacterial colonies

Heterogeneity in gene expression among cells in clonal groups is common in bacteria. Albeit ubiquitous, it often remains unclear what the sources of variation are and whether variation has functional significance. Here, we tracked the expression of genes involved in the synthesis of iron-chelating siderophores (pyoverdine and pyochelin) in individual cells of the bacterium Pseudomonas aeruginosa during colony growth on surfaces using time-lapse fluorescence microscopy, to explore potential sources and functions of cellular heterogeneity. Regarding sources, we found that the physical position of cells within the colony and epigenetic gene expression inheritance from mother to daughter cells significantly contributed to cellular heterogeneity. In contrast, cell pole age and cellular lifespan had no effect. Regarding functions, our results indicate that cells optimize their siderophore investment strategies (pyoverdine vs. pyochelin) along a gradient from the centre to the edge of the colony. Moreover, we found evidence that cell lineages with above-average siderophore investment increase the fitness of cell lineages with below-average investment through cooperative sharing of secreted siderophores. Altogether, our study highlights that single-cell experiments combined with automated image and cell-tracking analyses can identify sources of heterogeneity and yield adaptive explanations for gene expression variation among clonal bacterial cells.

microbiology↗

bioRxiv2023

Predicting bacterial interaction outcomes from monoculture growth and supernatant assays

How to derive principles of community dynamics and stability is a central question in microbial ecology. Bottom-up experiments, in which a small number of bacterial species are mixed, have become popular to address it. However, experimental setups are typically limited because co-culture experiments are labor-intensive and species are difficult to distinguish. Here, we use a 4-species bacterial community to show that information from monoculture growth and inhibitory effects induced by secreted compounds can be combined to predict the competitive rank order in the community. Specifically, integrative monoculture growth parameters allow building a preliminary competitive rank order, which is then adjusted using inhibitory effects from supernatant assays. While our procedure worked for two different media, we observed differences in species rank orders between media. We then parameterized computer simulations with our empirical data to show that higher-order species interactions largely follow the dynamics predicted from pairwise interactions with one important exception. The impact of inhibitory compounds was reduced in higher-order communities because their negative effects were spread across multiple target species. Altogether, we formulated three simple rules of how monoculture growth and supernatant assay data can be combined to establish a competitive species rank order in an experimental 4-species community.

microbiology↗

bioRxiv2021

Single-cell imaging reveals that Staphylococcus aureus is highly competitive against Pseudomonas aeruginosa on surfaces

Pseudomonas aeruginosa and Staphylococcus aureus frequently occur together in polymicrobial infections, and their interactions can complicate disease progression as well as treatment options. While interactions between P. aeruginosa and S. aureus have been extensively described using planktonic batch cultures, little is known about whether and how individual cells interact with each other on solid substrates. This is important, because in infections, both species frequently colonize surfaces to form microcolony aggregates and biofilms. Here, we performed single-cell time-lapse fluorescence microscopy combined with automated image analysis to describe interactions between P. aeruginosa PAO1 with three different S. aureus strains (Cowan I, 6850, JE2) during microcolony growth on agarose surfaces. While P. aeruginosa is usually considered the dominant species, we found that the competitive balance tips in favor of S. aureus on surfaces. We observed that all S. aureus strains accelerated the onset of microcolony growth in competition with P. aeruginosa and significantly compromised P. aeruginosa growth prior to physical contact. These results suggest that S. aureus deploys mechanisms of both resource competition and interference competition via diffusible compounds. JE2 was the most competitive S. aureus strain, simply usurping P. aeruginosa microcolonies when coming into direct contact, while 6850 was the weakest competitor itself suppressed by P. aeruginosa. Moreover, P. aeruginosa reacted to the assault of S. aureus by showing increased directional growth and expedited expression of quorum sensing regulators controlling the synthesis of competitive traits. Altogether, our results reveal that quantitative single-cell live imaging has the potential to uncover microbial behaviors that cannot be predicted from batch culture studies, and thereby contribute to our understanding of interactions between pathogens that co-colonize host-associated surfaces during polymicrobial infections.

microbiology↗

bioRxiv2018

Understanding policing as a mechanism of cheater control in cooperating bacteria

Policing occurs in insect, animal and human societies, where it is used as a conditional strategy to prevent cheating and enforce cooperation. Recently, it has been suggested that policing might even be relevant in enforcing cooperation in much simpler organisms such as bacteria. Here, we used individual-based modelling to develop an evolutionary concept for policing in bacteria, and identify the conditions under which it can be adaptive. We modelled interactions between cooperators, producing a beneficial public good, cheaters exploiting the public good without contributing to it, and public good producing policers that secrete a toxin to selectively target cheaters. We found that toxin-mediated policing is favored when (i) toxins are potent and durable, (ii) cheap to produce, (iii) cell and public good diffusion is intermediate, and (iv) toxins diffuse farther than the public good. Overall, we show that toxin-mediated policing can enforce cooperation, but the parameter space where it is beneficial seems quite narrow. Moreover, we found that policing decays when the genetic linkage between public good and toxin production breaks. This is because policing is itself a public good, offering protection to toxin-resistant mutants that still produce public goods, yet no longer invest in toxins. Our work suggests that very specific environmental conditions are required for genetically fixed policing mechanisms to evolve in bacteria, and offers empirically testable predictions for their evolutionary stability.

evolutionary biology↗

bioRxiv2017

Division of labor during biofilm matrix production

Organisms as simple as bacteria can engage in complex collective actions, such as group motility and fruiting body formation. Some of these actions involve a division of labor, where phenotypically specialized clonal subpopulations, or genetically distinct lineages cooperate with each other by performing complementary tasks. Here, we combine experimental and computational approaches to investigate potential benefits arising from division of labor during biofilm matrix production. We show that both phenotypic and genetic strategies for a division of labor can promote collective biofilm formation in the soil bacterium Bacillus subtilis. In this species, biofilm matrix consists of two major components; EPS and TasA. We observed that clonal groups of B. subtilis phenotypically segregate into three subpopulations composed of matrix non-producers, EPS-producers, and generalists, which produce both EPS and TasA. This incomplete phenotypic specialization was outperformed by a genetic division of labor, where two mutants, engineered as specialists, complemented each other by exchanging EPS and TasA. The relative fitness of the two mutants displayed a negative frequency dependence both in vitro and on plant roots, with strain frequency reaching a stable equilibrium at 30% TasA-producers, corresponding exactly to the population composition where group productivity is maximized. Using individual-based modelling, we show that asymmetries in strain ratio can arise due to differences in the relative benefits that matrix compounds generate for the collective; and that genetic division of labor can be favored when it breaks metabolic constraints associated with the simultaneous production of two matrix components.\n\nHighlights- matrix components EPS and TasA are costly public goods in B. subtilis biofilms\n\n- genetic division of labor using {Delta}eps and {Delta}tasA fosters maximal biofilm productivity\n\n- {Delta}eps and {Delta}tasA cooperation is evolutionary stable in laboratory and ecological systems\n\n- costly metabolic coupling of public goods favors genetic division of labor

microbiology↗