Levels Of Biological Organization Research Articles

Predicting population-level impacts of projected climate heating on a temperate freshwater fish.

Climate heating has the potential to drive changes in ecosystems at multiple levels of biological organization. Temperature directly affects the inherent physiology of plants and animals, resulting in changes in rates of photosynthesis and respiration, and trophic interactions. Predicting temperature-dependent changes in physiological and trophic processes, however, is challenging because environmental conditions and ecosystem structure vary across biogeographical regions of the globe. To realistically predict the effects of projected climate heating on wildlife populations, mechanistic tools are required to incorporate the inherent physiological effects of temperature changes, as well as the associated effects on food availability within and across comparable ecosystems. Here we applied an agent-based bioenergetics model to explore the combined effects of projected temperature increases for 2100 (1.4, 2.7, and 4.4°C), and associated changes in prey availability, on three-spined stickleback (Gasterosteus aculeatus) populations representing latitudes 50, 55, and 60°N. Our results showed a decline in population density after a simulated 1.4°C temperature increase at 50°N. In all other modeled scenarios there was an increase (inflation) in population density and biomass (per unit area) with climate heating, and this inflation increased with increasing latitude. We conclude that agent-based bioenergetics models are valuable tools in discerning the impacts of climate change on wild fish populations, which play important roles in aquatic food webs.

Stable isotopes reveal sex- and context-dependent amino acid routing in green anole lizards (Anolis carolinensis).

Allocation of acquired resources to phenotypic traits is affected by resource availability and current selective context. While differential investment in traits is well documented, the mechanisms driving investment at lower levels of biological organization, which are not directly related to fitness, remain poorly understood. We supplemented adult male and female Anolis carolinensis lizards with an isotopically labelled essential amino acid (13C-leucine) to track routing in four tissues (muscle, liver, gonads, and spleen) under different combinations of resource availability (high and low-calorie diets) and exercise training (sprint training and endurance capacity). We predicted sprint training should drive routing to muscle, and endurance training to liver and spleen, and that investment in gonads should be of lower priority in each of the cases of energetic stress. We found complex interactions between training regime, diet, and tissue type in females, and between tissue type and training and tissue type and diet in males, suggesting that males and females adjust their 13C-leucine routing strategies differently in response to similar environmental challenges. Importantly, our data show evidence of increased 13C-leucine routing in training contexts not to muscle as we expected, but to the spleen, which turns over blood cells, and to the liver, which supports metabolism under differing energetic scenarios. Our results reveal the context-specific nature of long-term tradeoffs associated with increased chronic activity. They also illustrate the importance of considering the costs of locomotion in studies of life history strategies.

An integrative understanding of evolutionary convergence across organisms and biological scales.

The extent to which evolution is predictable is a long-standing question in biology, with implications for urgent biological issues such as viral evolution, the emergence of antibiotic resistance in bacteria, and organismal responses to climate change. Convergent evolution, the phylogenetically independent evolution of similar phenotypes, provides biological replicates useful for exploring patterns of predictability in evolution. Understanding evolutionary convergence requires synthesizing findings across biological scales and organisms. To this end, we organized a SICB-wide symposium entitled "Integrating research on convergent evolution across levels of biological organization, organisms, and time". Our symposium showcased interdisciplinary research on evolutionary convergence across diverse study systems and levels of biological organization, while highlighting new techniques and comparative methods for identifying patterns of predictability in convergently evolved traits. Here, we introduce findings from papers included in this symposium issue and identify common themes, highlight emerging questions, and discuss how we can integrate new techniques, tools, and systems to expand our understanding of evolutionary convergence.

A brief review on models for birds exposed to chemicals.

"A Who's Who of pesticides is therefore of concern to us all. If we are going to live so intimately with these chemicals eating and drinking them, taking them into the very marrow of our bones - we had better know something about their nature and their power."-Rachel Carson, Silent Spring. In her day, Rachel Carson was right: plant protection products (PPP), like all the other chemical substances that humans increasingly release into the environment without further precaution, are among our worst enemies today (Bruhl and Zaller, 2019; Naidu etal., 2021; Tang etal., 2021; Topping etal., 2020). All compartments of the biosphere, air, soil and water, are potential reservoirs within which all species that live there are impaired. Birds are particularly concerned: PPP are recognized as a factor in the decline of their abundance and diversity predominantly in agricultural landscapes. Due to the restrictions on vertebrates testing, in silico-based approaches are an ideal choice alternative given input data are available. This is where the problem lies as we will illustrate in this paper. We performed an extensive literature search covering a long period of time, a wide diversity of bird species, a large range of chemical substances, and as many model types as possible to encompass all our future need to improve environmental risk assessment of chemicals for birds. In the end, we show that poultry species exposed to pesticides are the most studied at the individual level with physiologically based toxicokinetic models. To go beyond, with more species, more chemical types, over several levels of biological organization, we show that observed data are crucially missing (Gilbert, 2011). As a consequence, improving existing models or developing new ones could be like climbing Everest if no additional data can be gathered, especially on chemical effects and toxicodynamic aspects.

Integrated Multi-Biomarker Responses of Juvenile Zebra Seabream (Diplodus cervinus) to Warming and Acidification Conditions

The impacts of climate change-related stressors are becoming more noticeable in the ocean, particularly in coastal marine ecosystems. Yet limited information still exists on the physiological state and ecological resilience of marine fish species, especially during their early life stages (i.e., larvae and juveniles). The present study investigated the effects of chronic exposure to seawater warming (OW; ΔT = +4 °C) and acidification (OA; ΔpH = −0.3 pH units, equivalent to pCO2~1000 µatm), acting alone or combined (OWA), on juvenile zebra seabream (Diplodus cervinus) physiological resilience, considering distinct levels of biological organization (i.e., biochemical, cell, organ and individual levels). After 60 days of exposure, both stressors, in isolation or combination, significantly decreased specific growth rate (−11% in OW, −42% in OA and −49% in OWA) and leukocyte counts (from −29% in OA and OWA up to −37% in OW) in relation to the control treatment. In addition, a decreased Fulton’s condition index (K) was observed under warming and acidification in combination (−35% in OWA). At the cell level, OW, OA and OWA triggered different biomarker responses in D. cervinus (i.e., up-regulation, down-regulation, or absence of significant effect). In general, the results are suggestive of an antagonistic effect when warming and acidification are combined. OWA yielded the highest integrated biomarker response (IBR) index value in the whole organism, muscle, brain and gills of D. cervinus juveniles, therefore suggesting that the effects of these stressors are more severe when they act together. The distinct patterns observed in each stress scenario highlight the importance of carrying out further studies adjusted to the specificities of different regions, i.e., accounting not only for the type and degree of severity of environmental stressors already felt and/or projected for that specific area, but also the physiological plasticity of species that inhabit a particular ecosystem. The gathered knowledge will allow one to determine the vulnerability of particular marine species and geographic areas and, most importantly, to draw up effective and tailor-made conservation strategies to overcome climate change impacts.

Resources modulate developmental shifts but not infection tolerance upon coinfection in an insect system.

Energetic resources fuel immune responses and parasite growth within organisms, but it is unclear whether energy allocation is sufficient to explain changes in infection outcomes under the threat of multiple parasites. We manipulated diet in flour beetles ( Tribolium confusum ) infected with two natural parasites to investigate the role of resources in shifting metabolic and immune responses after single and co-infection. Our results suggest that gregarine parasites alter the within-host energetic environment, and by extension juvenile development time, in a diet- dependent manner. Gregarines do not affect host resistance to acute bacterial infection but do stimulate the expression of an alternative set of immune genes and promote damage to the gut, ultimately contributing to reduced survival regardless of diet. Thus, energy allocation is not sufficient to explain the immunological contribution to coinfection outcomes, emphasizing the importance of mechanistic insight for predicting the impact of coinfection across levels of biological organization.

Climate change impacts on a sedimentary coast—a regional synthesis from genes to ecosystems

Climate change effects on coastal ecosystems vary on large spatial scales, but can also be highly site dependent at the regional level. The Wadden Sea in the south-eastern North Sea is warming faster than many other temperate coastal areas, with surface seawater temperature increasing by almost 2 °C over the last 60 years, nearly double the global ocean mean increase. Climate warming is accompanied by rising sea levels, which have increased by approximately 2 mm yr−1 over the last 120 years. For this sedimentary coast, the predicted acceleration of sea-level rise will have profound effects on tidal dynamics and bathymetry in the area. This paper synthesises studies of the effects of ocean warming and sea level rise in the northern Wadden Sea, largely based on research conducted at the Wadden Sea Station Sylt of the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research. An increasing rate of sea level rise above a critical threshold will lead to coastal erosion and changes in sediment composition, and may cause the transition from a tidal to lagoon-like environment as tidal flats submerge. This involves changes to coastal morphology, and the decline of important habitats such as muddy tidal flats, salt marshes and seagrass meadows, as well as their ecological services (e.g. carbon sequestration). Ocean warming affects plankton dynamics and phenology, as well as benthic community structure by hampering cold-adapted but facilitating warm-adapted species. The latter consist mostly of introduced non-native species originating from warmer coasts, with some epibenthic species acting as ecosystem engineers that create novel habitats on the tidal flats. Warming also changes interactions between species by decoupling existing predator–prey dynamics, as well as forming new interactions in which mass mortalities caused by parasites and pathogens can play an understudied but essential role. However, Wadden Sea organisms can adapt to changing abiotic and biotic parameters via genetic adaptation and phenotypic plasticity, which can also be inherited across generations (transgenerational plasticity), enabling faster plastic responses to future conditions. Important research advances have been made using next-generation molecular tools (-omics), mesocosm experiments simulating future climate scenarios, modelling approaches (ecological network analysis), and internet-based technologies for data collection and archiving. By synthesising these climate change impacts on multiple levels of physical and biological organisation in the northern Wadden Sea, we reveal knowledge gaps that need to be addressed by future investigations and comparative studies in other regions in order to implement management, mitigation and restoration strategies to preserve the uniqueness of this ecosystem of global importance.

Ecological consequences of body size reduction under warming.

Body size reduction is a universal response to warming, but its ecological consequences across biological levels, from individuals to ecosystems, remain poorly understood. Most biological processes scale with body size, and warming-induced changes in body size can therefore have important ecological consequences. To understand these consequences, we propose a unifying, hierarchical framework for the ecological impacts of intraspecific body size reductions due to thermal plasticity that explicitly builds on three key pathways: morphological constraints, bioenergetic constraints and surface-to-volume ratio. Using this framework, we synthesize key consequences of warming-induced body size reductions at multiple levels of biological organization. We outline how this trait-based framework can improve our understanding, detection and generalization of the ecological impacts of warming.

Critical thermal maxima in neotropical ants at colony, population, and community levels.

Global warming is exposing many organisms to severe thermal conditions and is having impacts at multiple levels of biological organisation, from individuals to species and beyond. Biotic and abiotic factors can influence organismal thermal tolerance, shaping responses to climate change. In eusocial ants, thermal tolerance can be measured at the colony level (among workers within colonies), the population level (among colonies within species), and the community level (among species). We analysed critical thermal maxima (CTmax) across these three levels for ants in a semiarid region of northeastern Brazil. We examined the individual and combined effects of phylogeny, body size (BS), and nesting microhabitat on community-level CTmax and the individual effects of BS on population- and colony-level CTmax. We sampled 1864 workers from 99 ant colonies across 47 species, for which we characterised CTmax, nesting microhabitat, BS, and phylogenetic history. Among species, CTmax ranged from 39.3 to 49.7°C, and community-level differences were best explained by phylogeny and BS. For more than half of the species, CTmax differed significantly among colonies in a way that was not explained by BS. Notably, there was almost as much variability in CTmax within colonies as within the entire community. Monomorphic and polymorphic species exhibited similar levels of CTmax variability within colonies, a pattern not always explained by BS. This vital intra- and inter-colony variability in thermal tolerance is likely allows tropical ant species to better cope with climate change. Our results underscore why ecological research must examine multiple levels of biological organisation.

The Prisoner’s Dilemma game as a tool to investigate cooperation and undergraduate education in evolution

Evolutionary theory is based on the conflict that arises when certain heritable variants out-compete others. Given this foundational conflict, a central question for evolutionary biologists concerns the presence of cooperation found throughout all levels of biological organization; from biochemical pathways to complex animal societies. Human behavior is often distinguished from other animal behavior by the presence of acts of cooperative behavior called altruism. Altruism is a cooperative act that penalizes the actor for actions that benefit the recipient. Any other form of cooperation, one that does not penalize the actor, is formally not considered altruistic. How can costly altruistic behavior evolve? This question was the basis for development of a web application tool incorporating a game theory model to investigate conditions affecting cooperative behavior. The game theory model described as Prisoner’s Dilemma incorporates acts of cooperation and non-cooperation (defection). Computer simulations of Prisoner’s Dilemma were developed and online applications were administered for five semesters at Georgia Gwinnett College, using two simulation environments referred to as Random and Non-random. Data collected from simulation runs were used to evaluate the effect of environment on student cooperative behavior and actively engage students in concepts associated with the evolution of cooperation and game theory. Results from student game play suggest group simulation environment played a significant role in the likelihood of observing cooperative behavior. Educational content and attitudinal surveys suggested that PD game play in the undergraduate evolution class at Georgia Gwinnett College improved student knowledge and self-confidence.

Connected interactions: enriching food web research by spatial and social interactions.

This theme issue features 18 papers exploring ecological interactions, encompassing metabolic, social, and spatial connections alongside traditional trophic networks. This integration enriches food web research, offering insights into ecological dynamics. By examining links across organisms, populations, and ecosystems, a hierarchical approach emerges, connecting horizontal effects within organizational levels vertically across biological organization levels. The inclusion of interactions involving humans is a key focus, highlighting the need for their integration into ecology given the complex interactions between human activities and ecological systems in the Anthropocene. The comprehensive exploration in this theme issue sheds light on the interconnectedness of ecological systems and the importance of considering diverse interactions in understanding ecosystem dynamics. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Use of woody species in the Caatinga dry forest may lead to higher vulnerability to extirpation: An assessment based on ethnobiological, reproductive and conservation criteria

Tropical forests play an important role in maintaining, replenishing and conserving a large portion of the planet's biodiversity. However, these forests have been converted into anthropic landscapes, threatening the persistence of wildlife. The exploitation of forest products can result in different ecological impacts at different levels of biological organization. In this study, we propose a vulnerability index to examine the susceptibility of woody plants used by locals in a human-modified landscape of the Caatinga dry forest (i.e., the Catimbau National Park). We contrasted patterns of (1) plant use by local people (risk of use, collection risk, local importance, and diversity of use), (2) plant reproductive strategies (pollination, sexual and reproductive systems, dispersal mode, flowering and fruiting phenology), and (3) the conservation status of the plant species. We combined this information to propose a vulnerability index expressing species sensitivity to human disturbances in 14 regenerating and 14 old-growth forest stands. We tested the hypothesis that regenerating forest stands will harbor more vulnerable plant species compared to old-growth forest stands. Among the 119 plant species registered in regenerating and old-growth forest stands, 80 species (67.2 %) were recorded as useful for local people in Caatinga. Specifically, about 71.8 % and 70.5 % are exploited by the rural population for some type of use in regenerating and old-growth forest stands, respectively. The most frequent type of use was medicinal, followed by construction and fuel in both regenerating and old-growth forest stands. Regarding the potentially collected plant parts, the total removal of the individual and collection of leaves exhibited similar and higher relevance in regenerating, while leaves were the most collected part in old-growth forest stands. Of the 80 plant species analyzed, 62 % and 58.5 %, respectively, were classified as exhibiting moderate and high vulnerability to extirpation in regenerating and old-growth forest stands; thus not supporting our hypothesis. Our results suggest that in the Caatinga dry forest, (1) woody plant species responsible for forest regeneration in the context of slash-and-burn agriculture are exploited for multiple uses, (2) medicinal use is the main type of use of woody plants occurring in regenerating and old-growth forest stands, (3) total removal of the individual and collection of leaves were the most collected plant parts, and (4) both regenerating and old-growth forest stands showed a high vulnerability to human disturbances in the study area. In the long term, the exploitation of vulnerable plant species may negatively affect the composition and structure of the community and, consequently, the rate and trajectory of succession. It can be expected that as populations of vulnerable plant species are reduced or extirpated from the community, ecological interactions such as pollination and dispersal, which are key to ecosystem maintenance, will change along with the services provided.

AOP-Anchored Transcriptome Analysis Catalogue Accelerates the Discovery of Environmental Toxicants in Zebrafish.

Current toxicity screening approaches to evaluate the vast number of environmental chemicals that require assessment are hampered due to their significant costs, time requirements, and reliance on live animal testing. The aim of the present study was to develop an adverse outcome pathway (AOP)-anchored transcriptome analysis (AATA) catalogue to expedite the discovery of environmental toxicants. 437 AOPs from the AOPwiki (https://aopwiki.org/) and 2280 transcriptomics data sets from NCBI Gene Expression Omnibus (GEO) and EMBL-EBI ArrayExpress (AE) repositories were comprehensively reviewed and analyzed. By using the differentially expressed molecular key event (mKE) genes as connection nodes, we created a large-scale environmental substance─target gene (mKE)─predicted adverse outcomes (SGAs) network that included 78 substances, 1099 genes, and 354 adverse outcomes (AOs). To validate the reliability of the network, comprehensive literature verification was conducted. We demonstrated that 164 of the 354 AOs identified have been previously characterized in the literature. The results for 136 of these AOs were consistent with the predictions of the AATA catalogue, representing an accuracy rate of 82.9%. Besides, distinct patterns in molecular KEs and AOs among categories of substances, such as biocides and metals, were demonstrated. Some representative substances, including atrazine and copper, pose significant risks to fish at various levels of biological organization. Moreover, experimental verification of the AATA predictions was conducted, including exposures of zebrafish to perfluorooctanesulfonate, cresyl diphenyl phosphate, and lanthanum. Results demonstrated consistency with predictions of the AATA catalogue, with an accuracy rate of 92.3%. Collectively, the present findings support the AATA catalogue as an efficient and promising platform for identifying environmental toxicants to fish and thereby provide novel insights into the understanding of potential risks of environmental contaminants.

Multi-biomarker approach reveals the effects of heavy metal bioaccumulation in the foundation species Prosopis laevigata (Fabaceae).

Mining is a major economic activity in many developing countries. However, it disturbs the environment, producing enormous quantities of waste, known as mine tailings, which can have deleterious environmental impact, due to their high heavy metals (HM) content. Often, foundation species that establish on mine tailings are good candidates to study the effects of HM bioaccumulation at different levels of biological organization. Prosopis laevigata is considered a HM hyperaccumulator which presents attributes of a foundation species (FS) and establishes naturally on mine tailings. We evaluated the bioaccumulation of Cu, Pb, and Zn in P. laevigata foliar tissue, the leaf micro- and macro-morphological characters, DNA damage, and population genetic effects. In total, 80 P. laevigata individuals (20/site) belonging to four populations: The individuals from both sites (exposed and reference) bioaccumulated HMs (Pb > Cu > Zn). However, in the exposed individuals, Pb and Cu bioaccumulation was significantly higher. Also, a significant effect of macro- and micro-morphological characters was registered, showing significantly lower values in individuals from the exposed sites. In addition, we found significant differences in genotoxic damage in P. laevigata individuals, between the exposed and reference sites. In contrast, for the micro-morphological characters, none of the analyzed metals had any influence. P. laevigata did not show significant differences in the genetic structure and diversity between exposed and reference populations. However, four haplotypes and four private alleles were found in the exposed populations. Since P. laevigata is a species that establishes naturally in polluted sites and bioaccumulates HM in its foliar tissues, the resulting genetic, individual and population effects have not been severe enough to show detrimental effects; hence, P. laevigata can be a useful tool in phytoremediation strategies for soils polluted with Pb and Cu, maintaining its important ecological functions.

“Quantifying the Impacts of Multiple Stressors” (QIMS)—a new experimental platform for robust multifactorial experiments in benthic ecosystems

AbstractTo predict the ecological consequences of expected global change, we need to understand the independent and combined effects of multiple stressors. Multiple experimental treatments are required to simultaneously test for effects of multiple stressors at different levels of intensity, independently and combined, and at different levels of biological organization. Most marine multiple stressors studies to date are conducted on assembled communities in mesocosms with a low number of treatments or low replication of treatments or both. These limitations prevent (1) robust data analyses, (2) characterization of single and combined effects of multiple stressors, and (3) identification of mechanisms underpinning biological responses. We present a new mesocosm‐based experimental platform for benthic communities: Quantifying the Impacts of Multiple Stressors (QIMS). Here, 96 independent mesocosms facilitate multifactorial and multilevel experimental designs with the high replication required for robust tests of multiple stressors and biological interactions. For example, three distinct pH levels are achieved by manipulating CO2 concentrations in the air supply, and three water temperature levels are provided by a cooling system in a fully crossed design that is required to identify all potential interactions, from which all combinations can be replicated 10 times (i.e., 90 experimental units). We demonstrate clearly how different levels of temperature and pCO2/pH can be manipulated precisely and maintained for at least 7 weeks. QIMS complements the limited number of permanently installed marine mesocosm facilities worldwide that simulate ocean warming and/or acidification and expedites multiple stressor research by providing an unprecedented level of replication for statistical robustness.

Predicting emergent animal biodiversity patterns across multiple scales.

Restoring biodiversity-based resilience and ecosystem multi-functionality needs to be informed by more accurate predictions of animal biodiversity responses to environmental change. Ecological models make a substantial contribution to this understanding, especially when they encode the biological mechanisms and processes that give rise to emergent patterns (population, community, ecosystem properties and dynamics). Here, a distinction between 'mechanistic' and 'process-based' ecological models is established to review existing approaches. Mechanistic and process-based ecological models have made key advances to understanding the structure, function and dynamics of animal biodiversity, but are typically designed to account for specific levels of biological organisation and spatiotemporal scales. Cross-scale ecological models, which predict emergent co-occurring biodiversity patterns at interacting scales of space, time and biological organisation, is a critical next step in predictive ecology. A way forward is to first capitalise on existing models to systematically evaluate the ability of scale-explicit mechanisms and processes to predict emergent patterns at alternative scales. Such model intercomparisons will reveal mechanism to process transitions across fine to broad scales, overcome approach-specific barriers to model realism or tractability and identify gaps which necessitate the development of new fundamental principles. Key challenges surrounding model complexity and uncertainty would need to be addressed, and while opportunities from big data can streamline the integration of multiple scale-explicit biodiversity patterns, ambitious cross-scale field studies are also needed. Crucially, overcoming cross-scale ecological modelling challenges would unite disparate fields of ecology with the common goal of improving the evidence-base to safeguard biodiversity and ecosystems under novel environmental change.

СОВРЕМЕННОЕ СОСТОЯНИЕ ПРОБЛЕМЫ ЗАГРЯЗНЕНИЯ ОКРУЖАЮЩЕЙ СРЕДЫ СРЕДСТВАМИ ИНДИВИДУАЛЬНОЙ ЗАЩИТЫ МЕДИЦИНСКОГО НАЗНАЧЕНИЯ

A new coronavirus infection (COVID-19) caused by acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has changed the lives of many people around the world. During the pandemic, hundreds of thousands of genomic sequences of the new coronavirus were formed, and its steady transmission from person to person remains. The use of disposable personal protective equipment (PPE) has become necessary to combat the COVID-19 pandemic, which has led to an unprecedented increase in the number of their production. Is of great concern the accumulation of the number of used PPE (medical and household waste), as well as their further disposal. The presence of various fragments of plastic and chemicals in disposable PPE can cause ecotoxicological effects on representatives of aquatic and terrestrial habitats at different levels of biological organization. In addition, PPE is a great danger for the further spread of various viruses, including SARS-CoV-2, since viruses can remain on different surfaces for several days. In the current situation, it is obvious that there is a need to conduct research to assess environmental risks and the impact of used PPE on the environment and human health

Computational thinking through the lens of biological evolution learning: enhancing understanding through the levels of biological organization and computational complexity

Research on exploring the relationship between computational thinking and domain specific knowledge gains (i.e. biological evolution) are becoming more common in science education research. The mechanisms behind these relationships are not well understood, particularly between computational practices and biological evolution content knowledge. Increased computational complexity (i.e. simple to complex) may support a greater comprehension of scales or levels of biological organization (i.e. micro to macro) within the context of biological evolution learning. We made use of quantitative methods from qualitative work in the form of coding and relational analysis to identify which biological levels of organization students addressed, how students made connections between these levels and the level of computational complexity displayed during evolution learning with the use of two computational interventions. The aim of this study was not only exploring the biological levels and biological level connections made during the computational thinking interventions, but also analysis of the differences between these two interventions. The results illuminated that use of specific biological levels, biological level connections and differences in computational complexity were distinguishable and there were significant differences between the interventions. These factors may contribute to better understanding of biological evolution knowledge gains.

Multi‐omics analyses reveal the signatures of metabolite transfers across trophic levels in a high‐CO2 ocean

AbstractAlthough the diverse impacts of elevated dissolved CO2 and warming on organisms within various trophic levels in marine food webs are well documented, we have yet to explore the biological links across different levels of biological organization from primary producers to secondary producers on an evolutionary time scale in a high‐CO2 ocean. Here, we cultured a model marine diatom Phaeodactylum tricornutum (primary producer) in predicted future high‐CO2 and/or warming conditions for ~ 1250 d with an experimental evolution approach and then fed them to the clam Coelomactra antiquata (secondary producer). We present an in‐depth multi‐omics analysis along the methylome (primary producer)–transcriptome (primary producer)–metabolome (primary producer)–metabolome (secondary producer) continuum. Our results showed that the downregulated terpenoid backbone biosynthesis in the methylome and transcriptome lead to decreased pyruvate levels and upregulation of some pathways (such as phenylalanine metabolism) in the metabolome of the primary producer in the long‐term warming conditions. These changes in metabolomic profile in the primary producer were then transferred to the secondary producer, resulting in changes in abundance of some metabolites, such as decreases in pyruvate, and in pyruvaldhyde (also known as methylglyoxal), and increases in 2‐hydroxylamino‐4,6‐dinitrotoluene. Our study provides a new insight into the molecular mechanisms underlying the trophic transfer from primary to secondary producers in a future high‐CO2 ocean and may provide more accurate projections of marine ecosystem services and functions over the next century.

GPT-4 as a biomedical simulator

BackgroundComputational simulation of biological processes can be a valuable tool for accelerating biomedical research, but usually requires extensive domain knowledge and manual adaptation. Large language models (LLMs) such as GPT-4 have proven surprisingly successful for a wide range of tasks. This study provides proof-of-concept for the use of GPT-4 as a versatile simulator of biological systems. MethodsWe introduce SimulateGPT, a proof-of-concept for knowledge-driven simulation across levels of biological organization through structured prompting of GPT-4. We benchmarked our approach against direct GPT-4 inference in blinded qualitative evaluations by domain experts in four scenarios and in two quantitative scenarios with experimental ground truth. The qualitative scenarios included mouse experiments with known outcomes and treatment decision support in sepsis. The quantitative scenarios included prediction of gene essentiality in cancer cells and progression-free survival in cancer patients. ResultsIn qualitative experiments, biomedical scientists rated SimulateGPT's predictions favorably over direct GPT-4 inference. In quantitative experiments, SimulateGPT substantially improved classification accuracy for predicting the essentiality of individual genes and increased correlation coefficients and precision in the regression task of predicting progression-free survival. ConclusionThis proof-of-concept study suggests that LLMs may enable a new class of biomedical simulators. Such text-based simulations appear well suited for modeling and understanding complex living systems that are difficult to describe with physics-based first-principles simulations, but for which extensive knowledge is available as written text. Finally, we propose several directions for further development of LLM-based biomedical simulators, including augmentation through web search retrieval, integrated mathematical modeling, and fine-tuning on experimental data.