Biology subjects

Persson, A.

Publications and source records attributed to Persson, A..

6 recordsLinked to original sources

bioRxiv2026

Nationwide citizen science reveals core and rare osmotolerant yeast communities in Swedish honey

Honey represents an extreme microbial habitat, comprising >80% sugar, low pH, oxidative stress, and antimicrobial compounds. Despite these conditions, specialized yeast species persist in nectar and honey microbial communities, where their metabolic activity may contribute to honey maturation and chemistry. To characterize the diversity and functional traits of honey-associated yeasts, we conducted a nationwide citizen science survey with the help of Swedish beekeepers, yielding ~2,400 isolates from 119 honey samples across 103 locations. Sequencing of ITS and LSU barcode regions of cultured isolates identified 85 species across 26 genera, dominated by Entelexis, Starmerella, Zygosaccharomyces, Rhodotorula, Aureobasidium, and Metschnikowia. While a small number of core taxa were consistently detected across geographic and environmental gradients, most species were rare and locally restricted, indicating a highly uneven community structure. Phenotypic assays of representative strains, typically one per isolated species, revealed broad osmotolerance, with several Entelexis, Starmerella and Zygosaccharomyces strains capable of growth at up to 80% glucose. Sugar utilization experiments showed widespread fructophilic metabolism, particularly under high-sugar conditions, and this trait was enriched among the most frequently recovered taxa. Selected isolates also fermented diluted honey, altering both its volatile profile and chemical composition. Together, these results demonstrate that honey hosts a taxonomically diverse but functionally specialized yeast community shaped by strong osmotic selection. This study establishes the largest culture-based collection of honey-associated yeasts to date, underscores the value of citizen science for large-scale microbial ecology, and identifies honey as an important reservoir of osmotolerant and fructophilic yeasts with ecological and biotechnological relevance.

microbiology↗

bioRxiv2026

Small-scale within-drainage spawning behavior causes population differentiation in Atlantic salmon

Understanding the genetic structure of keystone species within river networks is essential for effective conservation and management. While population differentiation of anadromous species often occurs between river systems, less research has been conducted on differentiation within rivers with smaller catchment areas. In this study, we investigated the population genetic structure of wild Atlantic salmon (Salmo salar) across the small-scale river Ronne [a] system in southernmost Sweden using Restriction-site Associated DNA sequencing (RADseq). Although the Admixture analysis did not detect clearly defined genetic clusters, significant pairwise FST values and DAPC revealed emerging population differentiation among the Ronne [a] tributaries. The observed patterns are consistent with a system characterized by connectivity, where genetic flow is present but can be reduced by behavioral and ecological factors such as spawning homing behavior and selective movements. These findings suggest that, despite overall connectivity, Atlantic salmon populations in the Ronne [a] catchment area may function as partially independent sub-populations. This highlights the importance of conservation and management strategies in fragmented river systems to consider population genetic structure to support resilient salmon populations under ongoing anthropogenic pressures.

molecular biology↗

bioRxiv2025

Amino acid restriction sensitizes lung cancer cells toferroptosis via GCN2-dependent activation of the integratedstress response

Lung cancer cells are vulnerable to iron-dependent oxidation of phospholipids leading to ferroptosis, a process countered by glutathione peroxidase-4 that converts lipid hydroperoxides to lipid alcohols using glutathione as reducing agent. Since ferroptosis-inducing agents are in clinical development, identifying modifiers of ferroptosis susceptibility is warranted. Here, we investigate the impact of amino acids on susceptibility to buthionine sulfoximine (BSO), a glutamate-cysteine ligase inhibitor that blocks biosynthesis of glutathione. We found that reduced amounts of amino acids other than cysteine increased the sensitivity to BSO and other ferroptosis-inducing agents, in a panel of mouse and human lung cancer cells, without affecting glutathione production. Activation of the amino acid sensor protein GCN2 and the integrated stress response lowered the threshold for lipid peroxidation by stimulating ATF4-dependent mitochondrial respiration. The finding has implications for lung cancer metabolism and raises the possibility of using protein restricted diets in combination with ferroptosis-inducing agents as cancer therapies.

cancer biology↗

bioRxiv2025

From Archaea to the atmosphere: remotely sensing Arctic methane

Global atmospheric methane concentrations are rapidly rising and becoming isotopically more depleted, implying an unresolved microbial contribution. Rising Arctic temperatures are variably altering soil methane cycling, causing consequential uncertainty in the atmospheric methane budget. We demonstrated in an Arctic wetland that below-ground microbiota and methane-cycling features parallelled above-ground plant communities. To upscale emissions, we applied machine learning to remote sensing data to identify habitats, which were assigned average emissions. To upscale dynamically, we incorporated climate data, remotely-sensed water table variation, and habitat classes into a temporally-resolved biogeochemical model, to predict methane flux and isotope dynamics. This accurately estimated more depleted 13C-methane than previously used for Arctic habitats in global source partitioning. Remote-sensing of these rapidly changing inaccessible landscapes can thus help constrain the role of the Arctic in ongoing changes in global methane emissions.

microbiology↗

bioRxiv2023

Mathematical models disentangle the role of IL-10 feedbacks in human monocytes upon proinflammatory activation

Inflammation is one of the vital mechanisms through which the immune system responds to harmful stimuli. During inflammation, pro and anti-inflammatory cytokines interplay to orchestrate fine-tuned, dynamic immune responses. The cytokine interplay governs switches in the inflammatory response and dictates the propagation of inflammation. Molecular pathways underlying the interplay are complex, and time-resolved monitoring of mediators and cytokines is necessary as a basis to study them in detail. Our understanding can be advanced by in silico models which enable to analyze the system of interactions and their dynamical interplay in detail. We, therefore, used a mathematical modeling approach to study the interplay between prominent pro and anti-inflammatory cytokines with a focus on Tumor Necrosis Factor (TNF) and Interleukin 10 (IL-10) in lipopolysaccharide (LPS)-primed primary human monocytes. Relevant time-resolved data were generated by experimentally adding or blocking IL-10 at different time points. The model was successfully trained and could predict independent validation data and was further used to perform in silico experiments to disentangle the role of IL-10 feedbacks in acute inflammation. We used the insight to obtain a reduced predictive model including only the necessary IL-10-mediated feedbacks. Finally, the validated reduced model was used to predict early IL-10 - TNF switches in the inflammatory response. Overall, we gained detailed insights into fine-tuning of inflammatory responses in human monocytes and present a model for further use in studying the complex and dynamic process of cytokine-regulated acute inflammation.

systems biology↗

bioRxiv2020

Mechanisms of a sustained anti-inflammatory drug response in alveolar macrophages unraveled with mathematical modeling

Both initiation and suppression of inflammation are hallmarks of the immune response. If not balanced, the inflammation may cause extensive tissue damage, which is associated with common diseases, e.g. asthma and atherosclerosis. Anti-inflammatory drugs often come with severe side effects driven by high and fluctuating drug concentrations. To remedy this, drugs with sustained anti-inflammatory responses are desirable. However, we still lack a quantitative mechanistic understanding of such sustained effects. Here, we study the anti-inflammatory response to a common glucocorticoid drug, Dexamethasone. We find a sustained response 22 hours after drug removal. With hypothesis testing using mathematical modeling, we unravel the underlying mechanism - a slow release of Dexamethasone from the receptor-drug complex. The developed model is in agreement with time-resolved training and testing data, and is used to simulate hypothetical treatment schemes. This work opens up for a more knowledge-driven drug development, to find sustained anti-inflammatory responses and fewer side effects.

systems biology↗