From hydrothermal vents, to glaciers, to deserts, research in extreme environments has reshaped our understanding of how and where life can persist. Contained within the genomes of extremophilic organisms are the blueprints for a toolkit to tackle the multitude of challenges of survival in inhospitable environments. As new sequencing technologies have rapidly developed, so too has our understanding of the molecular and genomic mechanisms that have facilitated the success of extremophiles. Although eukaryotic extremophiles remain relatively understudied compared to bacteria and archaea, an increasing number of studies have begun to leverage 'omics tools to shed light on eukaryotic life in harsh conditions. In this perspective paper, we highlight a diverse breadth of research on extremophilic lineages across the eukaryotic tree of life, from microbes to macrobes, that are collectively reshaping our understanding of molecular innovations at life's extremes. These studies are not only advancing our understanding of evolution and biological processes but are also offering a valuable roadmap on how emerging technologies can be applied to identify cellular mechanisms of adaptation to cope with life in stressful conditions, including high and low temperatures, limited water availability, and heavy metal habitats. We shed light on patterns of molecular and organismal adaptation across the eukaryotic tree of life and discuss a few promising research directions, including investigations into the role of horizontal gene transfer in eukaryotic extremophiles and the importance of increasing phylogenetic diversity of model systems.
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http://dx.doi.org/10.1093/gbe/evae160 | DOI Listing |
JCO Clin Cancer Inform
January 2025
Machine Learning Department, H. Lee Moffit Cancer Center and Research Institute, Tampa, FL.
Purpose: Adaptive radiotherapy accounts for interfractional anatomic changes. We hypothesize that changes in the gross tumor volumes identified during daily scans could be analyzed using delta-radiomics to predict disease progression events. We evaluated whether an auxiliary data set could improve prediction performance.
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January 2025
Faculty of Science and Engineering, School of Computer Science, University of Hull, Hull, United Kingdom.
Mold defects pose a significant risk to the preservation of valuable fine art paintings, typically arising from fungal growth in humid environments. This paper presents a novel approach for detecting and categorizing mold defects in fine art paintings. The technique leverages a feature extraction method called Derivative Level Thresholding to pinpoint suspicious regions within an image.
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January 2025
Instituto de Investigaciones en Ecosistemas y Sustentabilidad, Universidad Nacional Autónoma de México, Morelia, Michoacán, México.
Land use change from wildlands to urban and productive environments can dramatically transform ecosystem structure and processes. Despite their structural and functional differences from wildlands, human-modified environments offer unique habitat elements for wildlife. In this study, we examined how migratory birds use urban, productive, and wildland environments of a highly anthropized region of Western Mexico known as "El Bajío".
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January 2025
Departamento de Ciências Biológicas, Laboratório de Ecologia Aplicada à Conservação, Universidade Estadual de Santa Cruz (UESC), Ilhéus, Bahia, Brazil.
Knowledge of the potential distribution and locations of poorly known threatened species is crucial for guiding conservation strategies and new field surveys. The painted tree-rat (Callistomys pictus) is a monospecific, rare, and endangered echimyid rodent endemic to the southern Bahia Atlantic Forest in Brazil. There have been no records of the species published in the last 20 years, and the region has experienced significant forest loss and degradation.
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January 2025
Department of Entomology and Plant Pathology, NC State University, Raleigh, North Carolina, United States of America.
We examined the evolutionary history of Phytophthora infestans and its close relatives in the 1c clade. We used whole genome sequence data from 69 isolates of Phytophthora species in the 1c clade and conducted a range of genomic analyses including nucleotide diversity evaluation, maximum likelihood trees, network assessment, time to most recent common ancestor and migration analysis. We consistently identified distinct and later divergence of the two Mexican Phytophthora species, P.
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