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Biology subjects

Lilleskov, E.

Publications and source records attributed to Lilleskov, E..

2 recordsLinked to original sources

Spatiotemporal differences in salmon nutrient inputs restructure functional and taxonomic fungal communities in riparian system

O_LISpawning salmon transport marine-derived nutrients (MDN) into riparian forests, influencing soil, plant, and animal communities, yet their effects on fungal communities remain poorly understood. C_LIO_LIWe used DNA metabarcoding to examine fungal responses to three spatial patterns of salmon-derived nitrogen (N) in southwest Alaska: (i) patchy inputs from wildlife-deposited carcasses, (ii) a 21-year carcass relocation experiment, and (iii) natural N gradients with distance from streams. C_LIO_LIDecomposing carcasses increased saprotrophic fungal diversity, identifying taxa responsible for salmon carcass decomposition. Long-term carcass relocation reduced diversity of medium-distance fringe ectomycorrhizal fungi (EMF), whereas recent, patchy carcass inputs increased diversity of both medium-distance fringe and long-distance EMF--guilds often associated with low-nutrient environments. Along natural stream N gradients, EMF responses varied markedly within functional guilds and genera, revealing unexpected variation in N sensitivity among closely related taxa. C_LIO_LIPulsed, spatially heterogeneous nutrient inputs enhanced diversity of typically nitrophobic EMF, likely reflecting their capacity to maintain extensive mycelial networks, exploit nutrient hotspots, and mobilize organic N and phosphorus. The diversity of responses along natural N gradients suggests that mechanisms linking EMF traits to nutrient acquisition and tolerance remain unresolved. Our findings emphasize the importance of linking fungal community composition with functional attributes and nutrient dynamics. C_LI

ecology↗

Benchmarking solutions to the T-cell receptor epitope prediction problem: IMMREP22 workshop report

Many different solutions to predicting the cognate epitope target of a T-cell receptor (TCR) have been proposed. However several questions on the advantages and disadvantages of these different approaches remain unresolved, as most methods have only been evaluated within the context of their initial publications and data sets. Here, we report the findings of the first public TCR-epitope prediction benchmark performed on 23 prediction models in the context of the ImmRep 2022 TCR-epitope specificity workshop. This benchmark revealed that the use of paired-chain alpha-beta, as well as CDR1/2 or V/J information, when available, improves classification obtained with CDR3 data, independent of the underlying approach. In addition, we found that straight-forward distance-based approaches can achieve a respectable performance when compared to more complex machine-learning models. Finally, we highlight the need for a truly independent follow-up benchmark and provide recommendations for the design of such a next benchmark.

bioinformatics↗