Biology Of Organisms Research Articles

Life and Death without Telomerase: The Saccharomyces cerevisiae Model.

Saccharomyces cerevisiae, a model organism in telomere biology, has been instrumental in pioneering a comprehensive understanding of the molecular processes that occur in the absence of telomerase across eukaryotes. This exploration spans investigations into telomere dynamics, intracellular signaling cascades, and organelle-mediated responses, elucidating their impact on proliferative capacity, genome stability, and cellular variability. Through the lens of budding yeast, numerous sources of cellular heterogeneity have been identified, dissected, and modeled, shedding light on the risks associated with telomeric state transitions, including the evasion of senescence. Moreover, the unraveling of the intricate interplay between the nucleus and other organelles upon telomerase inactivation has provided insights into eukaryotic evolution and cellular communication networks. These contributions, akin to milestones achieved using budding yeast, such as the discovery of the cell cycle, DNA damage checkpoint mechanisms, and DNA replication and repair processes, have been of paramount significance for the telomere field. Particularly, these insights extend to understanding replicative senescence as an anticancer mechanism in humans and enhancing our understanding of eukaryotes' evolution.

KTED: a comprehensive Web-Based database for transposable elements in the korean genome

Abstract Summary Transposable Elements (TEs), commonly referred to as 'mobile elements,' constitute DNA segments capable of relocating within a genome. Initially disregarded as 'junk DNA' devoid of specific functionality, it has become evident that TEs have diverse influences on an organism's biology and health. The impact of these elements varies according to their location, classification, and their effects on specific genes or regulatory components. Despite their significant roles, a paucity of resources concerning TEs in population-scale genome sequencing remains. Herein, we analyze whole-genome sequencing data sourced from the Korean Genome and Epidemiology Study, encompassing 2,500 Korean individuals. To facilitate convenient data access and observation, we developed a web-based database, KTED. Additionally, we scrutinized the differential distributions of TEs across five distinct common disease groups: dyslipidemia, hypertension, diabetes, thyroid disease, and cancer. Availability https://snubh.shinyapps.io/KTED Supplementary information Supplementary data are available at Bioinformatics online.

Staring into a crystall ball: understanding evolution and development of in vivo aquatic organismal transparency

Organismal transparency is an ecologically important trait that can provide camouflage advantages to diverse organisms. Transparent organisms are quite common—especially in oceans. Organismal transparency requires low absorption and scattering of light in the body across multi-scale levels. However, it is still not fully understood how such organisms achieve these requirements. Understanding this process requires multiple approaches from various fields and methods. Here, we offer recent insights on this topic from the viewpoints of evolution, developmental biology, and evaluation methodologies of organismal transparency. We also propose “organismal transparency biology” as a new interdisciplinary field of study. Furthermore, we suggest that tunicates are an ideal model animal for studying in vivo organismal transparency.

Navigating the ‘Anthropocene’: Trends and opportunities in modern organismal biology

Navigating the ‘Anthropocene’: Trends and opportunities in modern organismal biology

Pervasive fitness trade-offs revealed by rapid adaptation in large experimental populations of Drosophila melanogaster.

Life-history trade-offs are an inherent feature of organismal biology that evolutionary theory posits play a key role in patterns of divergence within and between species. Efforts to quantify trade-offs are largely confined to phenotypic measurements and the identification of negative genetic-correlations among fitness-relevant traits. Here, we use time-series genomic data collected during experimental evolution in large, genetically diverse populations of Drosophila melanogaster to directly measure the manifestation of trade-offs in response to temporally fluctuating selection pressures on ecological timescales. Specifically, we quantify the genome-wide signal of antagonistic pleiotropy suggestive of trade-offs between reproduction and stress tolerance. We further identify a putative role of two cosmopolitan inversions in these trade-offs, and show that loci responding to selection during lab-based, reproduction selection exhibit signals of fluctuating selection in an outdoor mesocosm exposed to natural environmental conditions. Our results demonstrate the utility of time-series genomic data in revealing the presence and genomic architecture underlying fitness trade-offs, and add credence to models positing a role of generic life history trade-offs in the maintenance of variation in natural populations.

Paleoinspired robotics as an experimental approach to the history of life.

Paleontologists must confront the challenge of studying the forms and functions of extinct species for which data from preserved fossils are extremely limited, yielding only a fragmented picture of life in deep time. In response to this hurdle, we describe the nascent field of paleoinspired robotics, an innovative method that builds upon established techniques in bioinspired robotics, enabling the exploration of the biology of ancient organisms and their evolutionary trajectories. This Review presents ways in which robotic platforms can fill gaps in existing research using the exemplars of notable transitions in vertebrate locomotion. We examine recent case studies in experimental paleontology, highlighting substantial contributions made by engineering and robotics techniques, and further assess how the efficient application of robotic technologies in close collaboration with paleontologists and biologists can offer additional insights into the study of evolution that were previously unattainable.

Deep Dive Into Noninvasive Biometrics: A Pilot Journey Using Stereo-Video in a Public Aquarium.

Accurate collection of biometric data is important for understanding the biology and conservation of marine organisms, including elasmobranch and teleost fish, both in nature and controlled environments where monitoring marine specimens' health is mandatory. Traditional methods involving specimen capture and handling are invasive, stressful, and disruptive. Some techniques like underwater visual census or laser photogrammetry have been used for noninvasive data collection, but they have limitations and biases. The application of stereo-video photogrammetry through the use of diver-operated stereo-video systems (stereo-DOV) is a noninvasive method that overcomes these challenges, providing highly accurate measurements. It has become popular for species monitoring, studying anthropogenic impacts, and assessing length distributions. However, this technique is still uncommon and barely reported in aquarium settings. This study describes an innovative pilot study targeting multiple species carried out in a Public Aquarium, using a low-cost house-made device. The results revealed that measuring more than 100 individuals in approximately 1 day's work is possible. Total and fork lengths were estimated using specific software for 31 teleost and 16 elasmobranch species and compared with real measurements for the available species. Despite technical limitations that must be reviewed for application in future studies that resulted in high root mean square (RMS) values (> 20 mm), differences between methodological approaches revealed a minimal discrepancy (1.37%-5% in large sharks and rays and 1.8%-5.5% in teleost fish). This technique has time and cost requirements, but might represent a major advance in husbandry and in the contribution to conservation that ex situ studies can provide.

A Comparative Study of the Chemical Composition and Skincare Activities of Red and Yellow Ginseng Berries.

This study was conducted to investigate the differences in chemical composition between red (RGBs) and yellow ginseng berries (YGBs) and their whitening and anti-aging skincare effects. The differences in the chemical composition between RGB and YGB were analyzed by ultra-high-performance liquid chromatography tandem quadrupole electrostatic field orbit trap mass spectrometry (UHPLC-Q-Exactive-MS/MS) combined with multivariate statistics. An aging model was established using UVB radiation induction, and the whitening and anti-aging effects of the two ginseng berries were verified in vitro and in vivo using cell biology (HaCaT and B16-F10 cells) and zebrafish model organisms. A total of 31 differential compounds, including saponins, flavonoids, phenolic acids, and other chemical constituents, were identified between the two groups. Superoxide dismutase (SOD) activity was more significantly increased (p < 0.05) and malondialdehyde (MDA) content was more significantly decreased (p < 0.01) in RGB more than YGB induced by UVB ultraviolet radiation. In terms of whitening effects, YGB was more effective in inhibiting the melanin content of B16-F10 cells (p < 0.01). The results of zebrafish experiments were consistent with those of in vitro experiments and cell biology experiments. The DCFH fluorescence staining results revealed that both ginseng berries were able to significantly reduce the level of reactive oxygen species (ROS) in zebrafish (p < 0.01). Comparison of chemical composition and skin care activities based on RGB and YGB can provide a theoretical basis for the deep development and utilization of ginseng berry resources.

Adapting to change: insights from new organisms in cell and developmental biology.

We are living in an era of environmental change with undeniable parallels with past mass extinctions. To improve our understanding of planetary health and resilience, we must expand our research beyond traditional lab models. Forecasting the future of biological diversity relies on extrapolation of past trends, which necessitates the study of a wider range of biological systems. The 'Unconventional and Emerging Experimental Organisms for Cell and Developmental Biology' meeting, which took place in Dorking, UK, in September 2023, emphasized the importance of this broader approach. Discussions centered on evolutionary innovation, robustness and diversity, underscoring the need for broader taxon sampling and novel experimental models to address current and future challenges.

Genome-Scale Metabolic Models in Fungal Pathogens: Past, Present, and Future.

Fungi are diverse organisms with various characteristics and functions. Some play a role in recycling essential elements, such as nitrogen and carbon, while others are utilized in the food and drink production industry. Some others are known to cause diseases in various organisms, including humans. Fungal pathogens cause superficial, subcutaneous, and systemic infections. Consequently, many scientists have focused on studying the factors contributing to the development of human diseases. Therefore, multiple approaches have been assessed to examine the biology of these intriguing organisms. The genome-scale metabolic models (GEMs) have demonstrated many advantages to microbial metabolism studies and the ability to propose novel therapeutic alternatives. Despite significant advancements, much remains to be elucidated regarding the use of this tool for investigating fungal metabolism. This review aims to compile the data provided by the published GEMs of human fungal pathogens. It gives specific examples of the most significant contributions made by these models, examines the advantages and difficulties associated with using such models, and explores the novel approaches suggested to enhance and refine their development.

Reproductive response of the predator Tenuisvalvae notata (Mulsant) (Coleoptera: Coccinellidae) to temperatures outside their ideal thermal range.

Global warming has driven changes in the biology and fitness of organisms that need to adapt to temperatures outside of their optimal range to survive. This study investigated aspects of reproduction and survival of the lady beetle Tenuisvalvae notata (Mulsant) (Coleoptera: Coccinellidae) subjected to temperatures that varied from its optimal (28°C) to a gradual decrease (12, 14, 16, and 18°C) and increase (32, 34, 35, and 36°C) over time at a rate of 1°C/day. Fertility, fecundity, oviposition period, and survival were determined. There was a significant reduction in fertility and fecundity at temperatures below 18°C and above 34°C, whereas survival was reduced only above 34°C. Additionally, we evaluated that fecundity was the lowest when females were kept at low temperature, and when males were kept under high temperature. Therefore, if the T. notata remained for a long period under exposure to temperatures outside the ideal range, then the species could present different reproductive responses for each sex to high and low temperatures. This factor must be considered when releasing natural enemies into an area to understand the effect of temperature on the decline of a local population a few generations after release.

Hot and cold exposure triggers distinct transcriptional and behavioral responses in laboratory-inbred pond snails

Animals exhibit remarkable behavioral and molecular adaptations to cope with thermal stressors, which are crucial for survival in variable environments that are exacerbated by climate change. Aquatic poikilotherms like our model organism—the pond snail Lymnaea stagnalis—face significant challenges due to their dependence on external temperatures. Our study provides valuable insights into the different behavioral and molecular responses of lab-inbred snails to cold and heat shock stressors (i.e., 4 ​°C and 30 ​°C), particularly in the context of learning and memory formation. We found that while short-term (1 ​h) cold exposure transiently upregulated the expression levels of HSP70 and HSP40 in the snail's central ring ganglia, prolonged cold exposure (24 ​h) resulted in a significant downregulation of LymMIPII and an upregulation of LymMIPR. These data suggest, albeit at the transcriptional level, the existence of a negative feedback loop necessary for sustaining cellular functions when metabolic demands might shift towards conserving energy during prolonged cold exposure. At the behavioral level, we found that, compared to heat shock, cold exposure did not result in a Garcia effect (i.e., a “special form” of conditioned taste aversion). The difference in memory outcomes was associated with changes in the expression levels of selected targets involved in neuronal plasticity and the stress response. While both cold and heat shock upregulated the HSP levels in the snail's central ring ganglia, cold exposure did not affect the expression levels of the neuroplasticity genes LymGRIN1 and LymCREB1, contrasting with heat shock's neurogenic effects. Overall, this study provides insights into L. stagnalis's adaptive responses to thermal stressors, emphasizing different molecular strategies for coping with heat versus cold challenges in aquatic environments. These findings contribute to our understanding of thermal biology and stress physiology in aquatic organisms, underscoring the importance of molecular mechanisms in shaping species' resilience in dynamic environments.

Preparing the Next Generation of Integrative Organismal Biologists.

Pursuing cutting edge questions in organismal biology in the future will require novel approaches for training the next generation of organismal biologists, including knowledge and use of systems-type modeling combined with integrative organismal biology. We link agendas recommending changes in science education and practice across three levels: Broadening the concept of organismal biology to promote modeling organisms as systems interacting with higher and lower organizational levels; enhancing undergraduate science education to improve applications of quantitative reasoning and modeling in the scientific process; and K-12 curricula based on Next Generation Science Standards emphasizing development and use of models in the context of explanatory science, solution design, and evaluating and communicating information. Out of each of these initiatives emerges an emphasis on routine use of models as tools for hypothesis testing and prediction. The question remains, however, what is the best approach for training the next generation of organismal biology students to facilitate their understanding and use of models? We address this question by proposing new ways of teaching and learning, including the development of interactive web-based modeling modules that lower barriers for scientists approaching this new way of imagining and conducting integrative organismal biology.

PSVII-1 Widespread allele-specific expression across tissues and cells of the chicken genome

Abstract Chickens are a valuable livestock species, providing an affordable and nutritious food source worldwide through eggs and meat. Additionally, chickens are extensively used in scientific research as model organisms in virology, immunology, epigenetics, development, and conservation biology. Considering this, there are increasing efforts to deepen our understanding of their genome complexity, such as efforts by the Functional Annotation of Animal Genomes (FAANG) Consortium. Toward this goal, we are working to contribute to the annotation of the chicken transcriptome. Allele-specific expression (ASE) is an imbalance of allelic gene expression often driven by genetic and epigenetic changes in cis-regulatory regions. We, therefore, aimed to determine allelic imbalances in gene expression across 20 tissues and cells to shed light on mechanisms regulating gene expression. Using replicate paired-end (PE) RNA-seq samples, we identified around 7 million variants across 20 tissues and cells (e.g., reproductive tissues, intestine tissues, muscle, and immune tissues and cells). We applied quality control measures and filtered out monoallelic and homozygous variants. After that, we calculated read counts per allele to determine allelic expression. We found 365,894 significant ASE SNPs and 11,530 ASE genes in at least one tissue or cell type (FDR ≤ 0.05). We discovered that ASE SNPs are widely distributed throughout the chicken genome, and ASE SNPs and ASE genes showed a varied distribution across tissues and cells. Primary macrophage exhibited the most abundant, while the pectoralis major (breast muscle) had the lowest ASE genes and ASE SNPs, ranging from 7,592 to 32,505 ASE SNPs and 773 to 2,387 ASE genes. Our findings reveal several important pathways affected by allelic imbalance of expression. These pathways included fatty acid biosynthesis and regulation, cell proliferation and differentiation, cell metabolism, adipocytokine signaling, proteolysis and autophagy, and focal adhesion. In summary, our study provides insight into relevant biological processes critical to chickens and can contribute to improving genome annotation, helping to expand the transcriptomic reference source.

Editorial: Model organisms in plant developmental biology—their effectiveness and limitations

Editorial: Model organisms in plant developmental biology—their effectiveness and limitations

Drosophila are hosts to the first described parasitoid wasp of adult flies

Parasitoid wasps are exceptionally diverse and use specialized adaptations capable of manipulating the physiology and behaviour of host organisms1. In more than two centuries since the first records of Drosophila-parasitizing wasps, nearly 200 described and provisional parasitoid species of drosophilids have been identified2. These include endoparasitoids and ectoparasitoids, as well as species attacking larval and pupal hosts3. Despite a deep history of research attention and remarkable biodiversity, a wasp species that attacks and develops inside the adult stage of a fly host has not been described previously. Here we report the discovery of a wasp species that infects the adult stage of fruit flies in the genus Drosophila, including one of the most deeply studied model organisms in biology, Drosophila melanogaster. Notably, this wasp can be easily collected from backyard fly baits and has a broad geographic distribution throughout the eastern USA. We document its life history and unique host interactions, including egg-laying into and larval emergence from adult flies, and provide protocols to raise wasps from wild-caught host flies. Our results emphasize the need for ongoing research investment in insect biodiversity and systematics. As parasitoid research continues to uncover unusual biology and supports fundamental mechanistic insights into immunity4, metabolism5, ecology6, evolution7–9 and behaviour10–12, we anticipate that this wasp’s association with the laboratory model organism, D. melanogaster, will provide new research opportunities across the life sciences.

BioSense: An automated sensing node for organismal and environmental biology

Automated remote sensing has revolutionized the fields of wildlife ecology and environmental science. Yet, a cost-effective and flexible approach for large scale monitoring has not been fully developed, resulting in a limited collection of high-resolution data. Here, we describe BioSense, a low-cost and fully programmable automated sensing platform for applications in bioacoustics and environmental studies. Our design offers customization and flexibility to address a broad array of research goals and field conditions. Each BioSense is programmed through an integrated Raspberry Pi computer board and designed to collect and analyze avian vocalizations while simultaneously collecting temperature, humidity, and soil moisture data. We illustrate the different steps involved in manufacturing this sensor including hardware and software design and present the results of our laboratory and field testing in southwestern United States.

Swimming performance, but not metabolism, is related to a boldness-activity syndrome in schoolmaster snapper (Lutjanus apodus).

Commercial overexploitation and climate change can alter the physiology and behavior of marine organisms, although intraspecific phenotypic responses to such changes can vary greatly depending on the environment, species, and severity of the stressor. Under the pace-of-life syndrome (POLS) hypothesis, behavior, physiology, and life-history traits are linked, and thus, affected by selection targeting any aspect of organismal biology. However, these links are understudied in tropical marine fishes, and further work is needed to better understand the impacts of fisheries and climate change on wild stocks. Moreover, tropical regions have a greater reliance on fisheries; thus investigations should focus on species with substantial socioeconomic value to ensure benefits at the local level. This study aimed to address this need by measuring the behavior (boldness and activity), metabolism, and swimming performance (using a critical swim speed [Ucrit] test) of schoolmaster snapper Lutjanus apodus in Eleuthera, the Bahamas. We report a strong positive correlation between boldness and activity, high repeatability of these behavioral metrics, and two groupings that were consistent with "proactive" and "reactive" behavioral types. These behavioral types differed significantly in their swimming performance, with reactive individuals having a 13.1% higher mean Ucrit. In contrast, no significant differences were found in the measured metabolic parameters between behavioral types. This study is the first to investigate the intraspecific links between behavior and physiology in a snapper species, using the novel and ecologically relevant comparison of Ucrit with behavioral syndrome types. These data suggest that additional research is needed to better predict the success of proactive/reactive tropical fish if overexploited and as influenced by climate change.

Stem Life: A Framework for Understanding the Prebiotic-Biotic Transition

Abiogenesis is frequently envisioned as a linear, ladder-like progression of increasingly complex chemical systems, eventually leading to the ancestors of extant cellular life. This “pre-cladistics” view is in stark contrast to the well-accepted principles of organismal evolutionary biology, as informed by paleontology and phylogenetics. Applying this perspective to origins, I explore the paradigm of “Stem Life,” which embeds abiogenesis within a broader continuity of diversification and extinction of both hereditary lineages and chemical systems. In this new paradigm, extant life’s ancestral lineage emerged alongside and was dependent upon many other complex prebiotic chemical systems, as part of a diverse and fecund prebiosphere. Drawing from several natural history analogies, I show how this shift in perspective enriches our understanding of Origins and directly informs debates on defining Life, the emergence of the Last Universal Common Ancestor (LUCA), and the implications of prebiotic chemical experiments.

KegAlign: Optimizing pairwise alignments with diagonal partitioning.

Our ability to generate sequencing data and assemble it into high quality complete genomes has rapidly advanced in recent years. These data promise to advance our understanding of organismal biology and answer longstanding evolutionary questions. Multiple genome alignment is a key tool in this quest. It is also the area which is lagging: today we can generate genomes faster than we can construct and update multiple alignments containing them. The bottleneck is in considerable computational time required to generate accurate pairwise alignments between divergent genomes, an unavoidable precursor to multiple alignments. This step is typically performed with lastZ, a very sensitive and yet equally slow tool. Here we describe an optimized GPU-enabled pairwise aligner KegAlign. It incorporates a new parallelization strategy, diagonal partitioning, with the latest features of modern GPUs. With KegAlign a typical human/mouse alignment can be computed in under 6 hours on a machine containing a single NVidia A100 GPU and 80 CPU cores without the need for any pre-partitioning of input sequences: a ~150× improvement over lastZ. While other pairwise aligners can complete this task in a fraction of that time, none achieves the sensitivity of KegAlign's main alignment engine, lastZ, and thus may not be suitable for comparing divergent genomes. In addition to providing the source code and a Conda package for KegAlign we also provide a Galaxy workflow that can be readily used by anyone.