Multiple Biological Scales Research Articles

Unveiling tryptophan dynamics and functions across model organisms via quantitative imaging.

Tryptophan is an essential amino acid involved in critical cellular processes in vertebrates, serving as a precursor for serotonin and kynurenine, which are key neuromodulators to influence neural and immune functions. Systematic and quantitative measurement of tryptophan is vital to understanding these processes. Here, we utilized a robust and highly responsive green ratiometric indicator for tryptophan (GRIT) to quantitatively measure tryptophan dynamics in bacteria, mitochondria of mammalian cell cultures, human serum, and intact zebrafish. At the cellular scale, these quantitative analyses uncovered differences in tryptophan dynamics across cell types and organelles. At the whole-organism scale, we revealed that inflammation-induced tryptophan concentration increases in zebrafish brain led to elevated serotonin and kynurenine levels, prolonged sleep duration, suggesting a novel metabolic connection between immune response and behavior. Moreover, GRIT's application in detecting reduced serum tryptophan levels in patients with inflammation symptoms suggests its potential as a high-throughput diagnostic tool. In summary, this study introduces GRIT as a powerful method for studying tryptophan metabolism and its broader physiological implications, paving the way for new insights into the metabolic regulation of health and disease across multiple biological scales.

Rhythms in insect olfactory systems: underlying mechanisms and outstanding questions.

Olfaction is a critical sensory modality for invertebrates, and it mediates a wide range of behaviors and physiological processes. Like most living organisms, insects live in rhythmic environments: the succession of nights and days is accompanied by cyclic variations in light intensity and temperature, as well as in the availability of resources and the activity of predators. Responding to olfactory cues in the proper temporal context is thus highly adaptive and allows for the efficient allocation of energy resources. Given the agricultural or epidemiological importance of some insect species, understanding olfactory rhythms is critical for the development of effective control strategies. Although the vinegar fly Drosophila melanogaster has been a classical model for the study of olfaction and circadian rhythms, recent studies focusing on non-model species have expanded our understanding of insect olfactory rhythms. Additionally, recent evidence revealing receptor co-expression by sensory neurons has brought about an ongoing paradigm shift in our understanding of insect olfaction, making it timely to review the state of our knowledge on olfactory rhythms and identify critical future directions for the field. In this Review, we discuss the multiple biological scales at which insect olfactory rhythms are being analyzed, and identify outstanding questions.

Integrating the Study of Polyploidy Across Organisms, Tissues, and Disease.

Polyploidy is a cellular state containing more than two complete chromosome sets. It has largely been studied as a discrete phenomenon in either organismal, tissue, or disease contexts. Increasingly, however, investigation of polyploidy across disciplines is coalescing around common principles. For example, the recent Polyploidy Across the Tree of Life meeting considered the contribution of polyploidy both in organismal evolution over millions of years and in tumorigenesis across much shorter timescales. Here, we build on this newfound integration with a unified discussion of polyploidy in organisms, cells, and disease. We highlight how common polyploidy is at multiple biological scales, thus eliminating the outdated mindset of its specialization. Additionally, we discuss rules that are likely common to all instances of polyploidy. With increasing appreciation that polyploidy is pervasive in nature and displays fascinating commonalities across diverse contexts, inquiry related to this important topic is rapidly becoming unified.

Characterize molecular signatures and establish a prognostic signature of gastric cancer by integrating single-cell RNA sequencing and bulk RNA sequencing

Gastric cancer is a significant global health concern with complex molecular underpinnings influencing disease progression and patient outcomes. Various molecular drivers were reported, and these studies offered potential avenues for targeted therapies, biomarker discovery, and the development of precision medicine strategies. However, it was posed that the heterogeneity of the disease and the complexity of the molecular interactions are still challenging. By seamlessly integrating data from single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq), we embarked on characterizing molecular signatures and establishing a prognostic signature for this complex malignancy. We offered a holistic view of gene expression landscapes in gastric cancer, identified 226 candidate marker genes from 3 different dimensions, and unraveled key players’ risk stratification and treatment decision-making. The convergence of molecular insights in gastric cancer progression occurs at multiple biological scales simultaneously. The focal point of this study lies in developing a prognostic model, and we amalgamated four molecular signatures (COL4A1, FKBP10, RNASE1, SNCG) and three clinical parameters using advanced machine-learning techniques. The model showed high predictive accuracy, with the potential to revolutionize patient care by using clinical variables. This will strengthen the reliability of the model and enable personalized therapeutic strategies based on each patient’s unique molecular profile. In summary, our research sheds light on the molecular underpinnings of gastric cancer, culminating in a powerful prognostic tool for gastric cancer. With a firm foundation in biological insights and clinical implications, our study paves the way for future validations and underscores the potential of integrated molecular analysis in advancing precision oncology.

Systems-level computational modeling in ischemic stroke: from cells to patients.

Ischemic stroke, a significant threat to human life and health, refers to a class of conditions where brain tissue damage is induced following decreased cerebral blood flow. The incidence of ischemic stroke has been steadily increasing globally, and its disease mechanisms are highly complex and involve a multitude of biological mechanisms at various scales from genes all the way to the human body system that can affect the stroke onset, progression, treatment, and prognosis. To complement conventional experimental research methods, computational systems biology modeling can integrate and describe the pathogenic mechanisms of ischemic stroke across multiple biological scales and help identify emergent modulatory principles that drive disease progression and recovery. In addition, by running virtual experiments and trials in computers, these models can efficiently predict and evaluate outcomes of different treatment methods and thereby assist clinical decision-making. In this review, we summarize the current research and application of systems-level computational modeling in the field of ischemic stroke from the multiscale mechanism-based, physics-based and omics-based perspectives and discuss how modeling-driven research frameworks can deliver insights for future stroke research and drug development.

Advances in understanding bat infection dynamics across biological scales.

Over the past two decades, research on bat-associated microbes such as viruses, bacteria and fungi has dramatically increased. Here, we synthesize themes from a conference symposium focused on advances in the research of bats and their microbes, including physiological, immunological, ecological and epidemiological research that has improved our understanding of bat infection dynamics at multiple biological scales. We first present metrics for measuring individual bat responses to infection and challenges associated with using these metrics. We next discuss infection dynamics within bat populations of the same species, before introducing complexities that arise in multi-species communities of bats, humans and/or livestock. Finally, we outline critical gaps and opportunities for future interdisciplinary work on topics involving bats and their microbes.

How do stochastic processes and genetic threshold effects explain incomplete penetrance and inform causal disease mechanisms?

Incomplete penetrance is the rule rather than the exception in Mendelian disease. In syndromic monogenic disorders, phenotypic variability can be viewed as the combination of incomplete penetrance for each of multiple independent clinical features. Within genetically identical individuals, such as isogenic model organisms, stochastic variation at molecular and cellular levels is the primary cause of incomplete penetrance according to a genetic threshold model. By defining specific probability distributions of causal biological readouts and genetic liability values, stochasticity and incomplete penetrance provide information about threshold values in biological systems. Ascertainment of threshold values has been achieved by simultaneous scoring of relatively simple phenotypes and quantitation of molecular readouts at the level of single cells. However, this is much more challenging for complex morphological phenotypes using experimental and reductionist approaches alone, where cause and effect are separated temporally and across multiple biological modes and scales. Here I consider how causal inference, which integrates observational data with high confidence causal models, might be used to quantify the relative contribution of different sources of stochastic variation to phenotypic diversity. Collectively, these approaches could inform disease mechanisms, improve predictions of clinical outcomes and prioritize gene therapy targets across modes and scales of gene function. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

The effect of tenotomy, neurotomy, and dual injury on mouse rotator cuff muscles: Consequences for the mouse as a preclinical model.

A common animal model of muscle pathology following rotator cuff tear (RCT) is a tenotomy of the supraspinatus and infraspinatus, often combined with neurotomy of the suprascapular nerve, which induces a more robust atrophy response than tenotomy alone. However, the utility of this model depends on its similarity to human muscle pathology post-RCT, both in terms of the disease phenotype and mechanisms of muscle atrophy and fatty infiltration. Given the clinical prevalence of nerve injury is low and the muscular response to denervation is distinct from mechanical unloading in other models, an understanding of the biological influence of the nerve injury is critical for interpreting data from this RCT model. We evaluated the individual and combined effect of tenotomy and neurotomy across multiple biological scales, in a robust time-series in the mouse supraspinatus. Muscle composition, histological, and gene expression data related to muscle atrophy, degeneration-regeneration, fatty infiltration, and fibrosis were evaluated. Broadly, we found tenotomy alone caused small, transient changes in these pathological features, which resolved over the course of the study, while neurotomy alone caused a significant fatty atrophy phenotype. The dual injury group had a similar fatty atrophy phenotype to the neurotomy group, though the addition of tenotomy did marginally enhance the fat and connective tissue. Overall, these results suggest the most clinically relevant injury model, tenotomy alone, does not produce a clinically relevant phenotype. The dual injury model partially recapitulates the human condition, but it does so through a nerve injury, which is not well justified clinically.

Mathematical bounds on Shannon entropy given the abundance of the ith most abundant taxon

The measurement of diversity is a central component of studies in ecology and evolution, with broad uses spanning multiple biological scales. Studies of diversity conducted in population genetics and ecology make use of analogous concepts and even employ equivalent mathematical formulas. For the Shannon entropy statistic, recent developments in the mathematics of diversity in population genetics have produced mathematical constraints on the statistic in relation to the frequency of the most frequent allele. These results have characterized the ways in which standard measures depend on the highest-frequency class in a discrete probability distribution. Here, we extend mathematical constraints on the Shannon entropy in relation to entries in specific positions in a vector of species abundances, listed in decreasing order. We illustrate the new mathematical results using abundance data from examples involving coral reefs and sponge microbiomes. The new results update the understanding of the relationship of a standard measure to the abundance vectors from which it is calculated, potentially contributing to improved interpretation of numerical measurements of biodiversity.

The Antibiocene – towards an eco-social analysis of humanity’s antimicrobial footprint

Over eight decades of mass antimicrobial exposures have changed microbial populations and genes at a global level. This thought piece argues that adequately responding to the anthropogenic transformation of the microbial commons requires reframing antimicrobial resistance (AMR) as the pheno- and genotypic signal of a new geological era – an Antibiocene. Thinking through the multiple spatiotemporal, biological, and social scales of this Antibiocene opens important perspectives on the long-term goals of (anti)microbial stewardship, the injustices connected with unequal antimicrobial exposures, and the scale of necessary changes to health, food production, and waste disposal systems. Conceptualising AMR within an Antibiocene also necessitates shifting the political gaze from the clinic and sites of food production to the hitherto neglected environmental domain of One Health, whose terrestrial and aquatic milieus act as crucial reservoirs for antimicrobial substances, antimicrobial resistance genes, and resistant organisms. Finally, disentangling the human and non-human dimensions of the Antibiocene requires working across the humanities, social-, environmental, and biomedical sciences. The thought piece ends by proposing comparative research on particularly contaminated sites as a promising way of reconstructing the microbial, biochemical, and societal fallouts of chronic antimicrobial exposures as well as already existing societal adaptations. Resulting findings will provide orientation for emerging debates on the preservation of our microbial commons and the development of new forms of ‘eubiotic governance’.

Host functional traits as the nexus for multilevel infection patterns

Understanding pathogen transmission and infection patterns at multiple biological scales is a central issue in disease ecology and evolution. Here, we suggest that functional traits of host species readily affect infection patterns of species, communities, and landscapes, and thus serve as a linkage for multilevel studies of infectious disease.

High-resolution metagenomic reconstruction of the freshwater spring bloom

BackgroundThe phytoplankton spring bloom in freshwater habitats is a complex, recurring, and dynamic ecological spectacle that unfolds at multiple biological scales. Although enormous taxonomic shifts in microbial assemblages during and after the bloom have been reported, genomic information on the microbial community of the spring bloom remains scarce.ResultsWe performed a high-resolution spatio-temporal sampling of the spring bloom in a freshwater reservoir and describe a multitude of previously unknown taxa using metagenome-assembled genomes of eukaryotes, prokaryotes, and viruses in combination with a broad array of methodologies. The recovered genomes reveal multiple distributional dynamics for several bacterial groups with progressively increasing stratification. Analyses of abundances of metagenome-assembled genomes in concert with CARD-FISH revealed remarkably similar in situ doubling time estimates for dominant genome-streamlined microbial lineages. Discordance between quantitations of cryptophytes arising from sequence data and microscopic identification suggested the presence of hidden, yet extremely abundant aplastidic cryptophytes that were confirmed by CARD-FISH analyses. Aplastidic cryptophytes are prevalent throughout the water column but have never been considered in prior models of plankton dynamics. We also recovered the first metagenomic-assembled genomes of freshwater protists (a diatom and a haptophyte) along with thousands of giant viral genomic contigs, some of which appeared similar to viruses infecting haptophytes but owing to lack of known representatives, most remained without any indication of their hosts. The contrasting distribution of giant viruses that are present in the entire water column to that of parasitic perkinsids residing largely in deeper waters allows us to propose giant viruses as the biological agents of top-down control and bloom collapse, likely in combination with bottom-up factors like a nutrient limitation.ConclusionWe reconstructed thousands of genomes of microbes and viruses from a freshwater spring bloom and show that such large-scale genome recovery allows tracking of planktonic succession in great detail. However, integration of metagenomic information with other methodologies (e.g., microscopy, CARD-FISH) remains critical to reveal diverse phenomena (e.g., distributional patterns, in situ doubling times) and novel participants (e.g., aplastidic cryptophytes) and to further refine existing ecological models (e.g., factors affecting bloom collapse). This work provides a genomic foundation for future approaches towards a fine-scale characterization of the organisms in relation to the rapidly changing environment during the course of the freshwater spring bloom.B2NzroPNjWa1JSkBbq3YLpVideo

SEX DIMORPHISM IN AGING

Abstract In this symposium, the speakers will discuss how sex can influence aging trajectories using complementary perspectives and approaches across multiple biological scales and systems. Indeed, accumulating evidence across species has revealed that aging is a highly sex-dimorphic process. On the one hand, women outlive men consistently across populations, and most supercentanarians are women. On the other hand, especially after the onset of menopause, women are at increased risk for most age-related diseases (e.g. Alzheimer’s disease, osteoporosis, etc.). However, the molecular pathways underlying such sex-differences in aging and longevity are still largely unexplored and poorly understood. Dr. Austad will discuss how compatibility between the mitochondrial and nuclear genomes during aging is influenced as a function of sex. Dr. Dubal will discuss the impact of sex chromosome complement on cognition with aging in mouse models, and how sex chromosomes may underlie sex-differences in brain aging. Dr. Ucar will discuss work from her lab revealing that the genomic signatures of immune aging in humans are specific to sex. Finally, Dr. Benayoun will discuss how aging of innate immune cells (e.g. macrophages or neutrophils) is regulated by the female vs. male milieu, with sex-specific age-related trajectories remodeling the immune compartment in mice.

Exploring the response of a key Mediterranean gorgonian to heat stress across biological and spatial scales

Understanding the factors and processes that shape intra-specific sensitivity to heat stress is fundamental to better predicting the vulnerability of benthic species to climate change. Here, we investigate the response of a habitat-forming Mediterranean octocoral, the red gorgonian Paramuricea clavata (Risso, 1826) to thermal stress at multiple biological and geographical scales. Samples from eleven P. clavata populations inhabiting four localities separated by hundreds to more than 1500 km of coast and with contrasting thermal histories were exposed to a critical temperature threshold (25 °C) in a common garden experiment in aquaria. Ten of the 11 populations lacked thermotolerance to the experimental conditions provided (25 days at 25 °C), with 100% or almost 100% colony mortality by the end of the experiment. Furthermore, we found no significant association between local average thermal regimes nor recent thermal history (i.e., local water temperatures in the 3 months prior to the experiment) and population thermotolerance. Overall, our results suggest that local adaptation and/or acclimation to warmer conditions have a limited role in the response of P. clavata to thermal stress. The study also confirms the sensitivity of this species to warm temperatures across its distributional range and questions its adaptive capacity under ocean warming conditions. However, important inter-individual variation in thermotolerance was found within populations, particularly those exposed to the most severe prior marine heatwaves. These observations suggest that P. clavata could harbor adaptive potential to future warming acting on standing genetic variation (i.e., divergent selection) and/or environmentally-induced phenotypic variation (i.e., intra- and/or intergenerational plasticity).

Bio-hybrid electronic and photonic devices.

Bio-hybrid devices, combining electronic and photonic components with cells, tissues, and organs, hold potential for advancing our understanding of biology, physiology, and pathologies and for treating a wide range of conditions and diseases. In this review, I describe the devices, materials, and technologies that enable bio-hybrid devices and provide examples of their utilization at multiple biological scales ranging from the subcellular to whole organs. Finally, I describe the outcomes of a National Science Foundation (NSF)-funded workshop envisioning potential applications of these technologies to improve health outcomes and quality of life.

Body size responses to the combined effects of climate and land use changes within an urban framework.

Alterations in body size can have profound impacts on an organism's life history and ecology with long-lasting effects that span multiple biological scales. Animal body size is influenced by environmental drivers, including climate change and land use change, the two largest current threats to biodiversity. Climate warming has led to smaller body sizes of many species due to impacts on growth (i.e., Bergmann's rule and temperature-size rule). Conversely, urbanization, which serves as a model for investigating the effects of land use changes, has largely been demonstrated to cause size increases, but few studies have examined the combined influences of climate and land use changes on organism size. We present here the background theory on how each of these factors is expected to influence body size, summarize existing evidence of how size has recently been impacted by climate and land use changes, and make several recommendations to guide future research uniting these areas of focus. Given the rapid pace of climate change and urbanization, understanding the combined effects of climate and land use changes on body size is imperative for biodiversity preservation.

Bridging the muscle genome to phenome across multiple biological scales.

Muscle is highly hierarchically organized, with functions shaped by genetically controlled expression of protein ensembles with different isoform profiles at the sarcomere scale. However, it remains unclear how isoform profiles shape whole-muscle performance. We compared two mouse hindlimb muscles, the slow, relatively parallel-fibered soleus and the faster, more pennate-fibered tibialis anterior (TA), across scales: from gene regulation, isoform expression and translation speed, to force-length-velocity-power for intact muscles. Expression of myosin heavy-chain (MHC) isoforms directly corresponded with contraction velocity. The fast-twitch TA with fast MHC isoforms had faster unloaded velocities (actin sliding velocity, Vactin; peak fiber velocity, Vmax) than the slow-twitch soleus. For the soleus, Vactin was biased towards Vactin for purely slow MHC I, despite this muscle's even fast and slow MHC isoform composition. Our multi-scale results clearly identified a consistent and significant dampening in fiber shortening velocities for both muscles, underscoring an indirect correlation between Vactin and fiber Vmax that may be influenced by differences in fiber architecture, along with internal loading due to both passive and active effects. These influences correlate with the increased peak force and power in the slightly more pennate TA, leading to a broader length range of near-optimal force production. Conversely, a greater force-velocity curvature in the near-parallel fibered soleus highlights the fine-tuning by molecular-scale influences including myosin heavy and light chain expression along with whole-muscle characteristics. Our results demonstrate that the individual gene, protein and whole-fiber characteristics do not directly reflect overall muscle performance but that intricate fine-tuning across scales shapes specialized muscle function.

TMNP: a transcriptome-based multi-scale network pharmacology platform for herbal medicine.

One of the most difficult problems that hinder the development and application of herbal medicine is how to illuminate the global effects of herbs on the human body. Currently, the chemo-centric network pharmacology methodology regards herbs as a mixture of chemical ingredients and constructs the 'herb-compound-target-disease' connections based on bioinformatics methods, to explore the pharmacological effects of herbal medicine. However, this approach is severely affected by the complexity of the herbal composition. Alternatively, gene-expression profiles induced by herbal treatment reflect the overall biological effects of herbs and are suitable for studying the global effects of herbal medicine. Here, we develop an online transcriptome-based multi-scale network pharmacology platform (TMNP) for exploring the global effects of herbal medicine. Firstly, we build specific functional gene signatures for different biological scales from molecular to higher tissue levels. Then, specific algorithms are designed to measure the correlations of transcriptional profiles and types of gene signatures. Finally, TMNP uses pharmacotranscriptomics of herbal medicine as input and builds associations between herbs and different biological scales to explore the multi-scale effects of herb medicine. We applied TMNP to a single herb Astragalus membranaceus and Xuesaitong injection to demonstrate the power to reveal the multi-scale effects of herbal medicine. TMNP integrating herbal medicine and multiple biological scales into the same framework, will greatly extend the conventional network pharmacology model centering on the chemical components, and provide a window for systematically observing the complex interactions between herbal medicine and the human body. TMNP is available at http://www.bcxnfz.top/TMNP.

Reintegrating Biology Through the Nexus of Energy, Information, and Matter.

Information, energy, and matter are fundamental properties of all levels of biological organization, and life emerges from the continuous flux of matter, energy, and information. This perspective piece defines and explains each of the three pillars of this nexus. We propose that a quantitative characterization of the complex interconversions between matter, energy, and information that comprise this nexus will help us derive biological insights that connect phenomena across different levels of biological organization. We articulate examples from multiple biological scales that highlight how this nexus approach leads to a more complete understanding of the biological system. Metrics of energy, information, and matter can provide a common currency that helps link phenomena across levels of biological organization. The propagation of energy and information through levels of biological organization can result in emergent properties and system-wide changes that impact other hierarchical levels. Deeper consideration of measured imbalances in energy, information, and matter can help researchers identify key factors that influence system function at one scale, highlighting avenues to link phenomena across levels of biological organization and develop predictive models of biological systems.

Surface Engineering of FLT4-Targeted Nanocarriers Enhances Cell-Softening Glaucoma Therapy.

Primary open-angle glaucoma is associated with elevated intraocular pressure (IOP) that damages the optic nerve and leads to gradual vision loss. Several agents that reduce the stiffness of pressure-regulating Schlemm's canal (SC) endothelial cells, in the conventional outflow pathway of the eye, lower IOP in glaucoma patients and are approved for clinical use. However, poor drug penetration and uncontrolled biodistribution limit their efficacy and produce local adverse effects. Compared to other ocular endothelia, FLT4/VEGFR3 is expressed at elevated levels by SC endothelial cells and can be exploited for targeted drug delivery. Here, we validate FLT4 receptors as clinically relevant targets on SC cells from glaucomatous human donors and engineer polymeric self-assembled nanocarriers displaying lipid-anchored targeting ligands that optimally engage this receptor. Targeting constructs were synthesized as lipid-PEGx-peptide, differing in the number of PEG spacer units (x), and were embedded in micelles. We present a novel proteolysis assay for quantifying ligand accessibility that we employ to design and optimize our FLT4-targeting strategy for glaucoma nanotherapy. Peptide accessibility to proteases correlated with receptor-mediated targeting enhancements. Increasing the accessibility of FLT4-binding peptides enhanced nanocarrier uptake by SC cells while simultaneously decreasing the uptake by off-target vascular endothelial cells. Using a paired longitudinal IOP study in vivo, we show that this enhanced targeting of SC cells translates to IOP reductions that are sustained for a significantly longer time as compared to controls. Confocal microscopy of murine anterior segment tissue confirmed nanocarrier localization to SC within 1 h after intracameral administration. This work demonstrates that steric effects between surface-displayed ligands and PEG coronas significantly impact the targeting performance of synthetic nanocarriers across multiple biological scales. Minimizing the obstruction of modular targeting ligands by PEG measurably improved the efficacy of glaucoma nanotherapy and is an important consideration for engineering PEGylated nanocarriers for targeted drug delivery.