PLoS Biology最新文献

Understanding the developmental basis of phenotypic plasticity is key to unraveling the origins of biodiversity. In coral reef fishes, color pattern changes during ontogeny can serve adaptive functions, yet the mechanisms and ecological contexts shaping these transitions remain largely unknown. Here, we investigated color pattern development in the tomato anemonefish (Amphiprion frenatus), which exhibits transient posterior white barring during early juvenile stages. We demonstrated that the timing of bar loss is plastic and modulated by the social environment, where juveniles cohabiting with adult conspecifics exhibited bar loss ~24 days earlier than those isolated from adults. Through transcriptomic profiling, we identified gene expression changes implicating apoptosis- and autophagy-related pathways, as well as alterations in chromatophore development. Moreover, shifts in the expression of multiple thyroid hormone marker genes highlighted the potential neuroendocrinal integration of social cues that promoted bar loss. Ultrastructural analyses via transmission electron microscopy and in-situ assays indicated massive apoptosis of iridophores and associated dermal remodeling during the white-to-orange transition. The pharmacological inhibition of caspases delayed bar loss, confirming the functional role of programmed cell death. Behavioral trials revealed that adults responded differently to juveniles with/without the posterior bar, suggesting a role of transient barring in conflict avoidance during recruitment. Lastly, our evolutionary reconstruction of this plastic trait suggests that colony size is an important factor promoting this ontogenetic switch throughout anemonefishes. Our results provide compelling evidence for socially mediated plasticity in color pattern ontogeny with ecological and evolutionary implications for communication and species diversification in reef fishes.

Prebiotic, probiotic, and combined (synbiotic) interventions often show variable outcomes across individuals, driven by complex interactions between introduced biotics, the endogenous microbiota, and the host diet. Predicting individual-specific success or failure of probiotic and prebiotic therapies remains a major challenge. Here, we leverage microbial community-scale metabolic models (MCMMs) to predict probiotic engraftment and microbiota-mediated short-chain fatty acid (SCFA) production in response to probiotic and prebiotic interventions. Using data from two human clinical trial cohorts, testing a five-strain probiotic combined with the prebiotic inulin designed to improve metabolic health and an eight-strain probiotic designed to treat recurrent Clostridioides difficile infections, respectively, we show that MCMM-predicted engraftment largely agrees with measurements, achieving 75%-80% accuracy. Engraftment probabilities varied across taxa. MCMMs captured treatment-driven shifts in predicted SCFA production, and higher model-predicted growth rates of Akkermansia muciniphila were negatively associated with glucose area under the curve (AUC) in the first trial, providing clues about the mechanisms underlying treatment efficacy. Extending these models to a third human cohort undergoing a healthy diet and lifestyle intervention revealed substantial inter-individual variability in predicted responses to increasing dietary fiber, which were significantly associated with baseline-to-follow-up changes in cardiometabolic health markers. Finally, our simulation results suggested that personalized prebiotic selection may further enhance probiotic efficacy. Together, these findings demonstrate the potential of metabolic modeling to guide personalized microbiome-mediated interventions.

Blood levels of neurofilament light chain (NfL) increase with age in healthy humans and have been shown to predict all-cause human mortality. To determine whether this relationship is conserved across species, we analyzed NfL in the blood of various animals. We observed age-related increases in NfL levels comparable to those seen in humans in mice, cats, dogs and horses. Longitudinal analysis of NfL trajectories in aged mice demonstrated that a faster rate of NfL increase predicts mortality. When comparing baseline NfL levels across 13 species, we found that those with lower baseline NfL levels tended to have longer lifespans; however, the collinearity between body size and life span complicates the interpretation of this finding. NfL was also robustly detected in blood of 39 additional mammalian species, as well as a few reptiles and birds, consistent with a conserved amino acid sequence of the NfL fragment in blood. Given the growing interest in NfL as a biomarker for neurological health and mortality in humans, our findings suggest that NfL may serve as a cross-species blood biomarker for assessing aging interventions and predicting mortality.

High-quality genome annotations are essential if we are to address central questions in comparative genomics, such as the origin of new genes, the drivers of genome size variation, and the evolutionary forces shaping gene content and structure. Here, we present protein-coding gene annotations for 301 species of the family Drosophilidae, generated using the Comparative Annotation Toolkit (CAT) and BRAKER3, and incorporating available RNA-seq and protein evidence. We take a comparative phylogenetic approach to annotation, with the aim of improving consistency and accuracy, and to generate a robust set of gene annotations and orthology assignments. We analyze our annotations using a phylogenetic mixed-model approach and find that gene number and CDS length exhibit moderate phylogenetic heritability (40% and 9.7%, respectively). For comparison, we also present analyses using a subset of the 215 highest quality genomes, although the findings were not markedly different. Our work suggests that while evolutionary history contributes to variation in these traits, species-specific factors-including assembly error-play a substantial role in shaping observed differences. To illustrate the utility of our annotations for comparative analyses, we investigate codon usage bias and amino acid composition across Drosophilidae. We find that codon usage is correlated with overall GC content and evolves slowly, but that it is also strongly shaped by selection-such that, in general, species with the strongest selection on synonymous codon usage show the lowest GC bias in third codon positions. This comparative annotation dataset forms part of an ongoing collaborative project to sequence and annotate all species of Drosophilidae, with data and annotations being made rapidly and freely available on an ongoing basis. We hope that this effort will serve as a foundation for studies in evolutionary and functional genomics and comparative biology across Drosophilidae.

Regulation of neural cell morphology remains a fundamental question in neuroscience. Photoreceptor cells, a specialized class of neurons capable of initiating the phototransduction cascade, exhibit distinct structural and morphological characteristics. While the structural and morphological differences between rod and cone photoreceptors have been extensively studied, the variability in the morphology of cone outer segments (OS) remains largely unexplored. Zebrafish possess four distinct cone types, each displaying unique OS morphologies. By modulating opsin expression across cone types, we reveal that the morphology of the cone OS correlates directly with the wavelength sensitivity of the expressed opsins, with cones expressing longer wavelength-sensitive opsins exhibiting elongated OS. This regulatory mechanism is conserved across various vertebrates. Furthermore, we show that alterations in light intensity-induced by ectopic lipid droplet formation in the light path or by changing the environment light intensity-can also modulate OS morphology. Notably, this morphological plasticity is not transient, but rather dependent on long-term neural activity. Based on these findings, we propose a model for the regulation of cone OS length. Our data suggest that both opsin sensitivity and light intensity shape cone OS morphology through long-term neural activity, providing critical insights into neural plasticity in these light-sensitive neurons.

RNA structures are essential for understanding their biological functions and developing RNA-targeted therapeutics. However, accurate RNA structure prediction from sequence remains a crucial challenge. We introduce DRfold2, a deep learning framework that integrates a novel pre-trained RNA Composite Language Model (RCLM) with a denoising structure module for end-to-end RNA structure prediction. Based solely on single sequence, DRfold2 achieves superior performance in both global topology and secondary structure predictions over other state-of-the-art approaches across multiple benchmark tests from diverse species. Detailed analyses reveal that the improvements primarily stem from the RCLM's ability to capture co-evolutionary pattern and the effective denoising process, with a more than 100% increase in contact prediction precision compared to existing methods. Furthermore, DRfold2 demonstrates high complementarity with AlphaFold3, achieving statistically significant accuracy gains when integrated into our optimization framework. By uniquely combining composite language modeling, denoising-based end-to-end learning, and deep learning-guided post-optimization, DRfold2 establishes a distinct direction for advancing ab initio RNA structure prediction.

Despite decades of intensive research, our current approaches to treating neurodegenerative diseases only slow down the seemingly inevitable. Could recent data associating vaccinations with reduced risk of dementia offer an unexpected beacon of hope?

Epilepsy is thought to develop through pathological connections involving various and widespread brain regions. A new study in PLOS Biology shows how some of these connections are formed across network sites, and how this interconnectivity can serve as a treatment target in epilepsy.

Biological differences between males and females are pervasive. Researchers often focus on sex differences in the mean or, occasionally, in variation, albeit other measures can be useful for biomedical and biological research. For instance, differences in skewness (asymmetry of a distribution), kurtosis (heaviness of a distribution's tails), and correlation (relationship between two variables) might be crucial to improve medical diagnosis and to understand natural processes. Yet, there are currently no meta-analytic ways to measure differences in these metrics between two groups. We propose three effect size statistics to fill this gap: Δsk, Δku, and ΔZr, which measure differences in skewness, kurtosis, and correlation, respectively. Besides presenting the rationale for the calculation of these effect size statistics, we conducted a simulation to explore their properties and used a large dataset of mice traits to illustrate their potential. For example, in our case study, we found that females show, on average, a greater correlation between fat mass and heart weight than males. Although calculating Δsk, Δku, and ΔZr will require large sample sizes of individual data, technological advancements in data collection create increased opportunities to use these effect size statistics. Importantly, Δsk, Δku, and ΔZr can be used to compare any two groups, allowing a new generation of meta-analyses that explore such differences and potentially leading to new insights in multiple fields of study.

Cdc42, a small GTPase essential for cell polarity, often becomes hyperactive with age and promotes senescence in yeast and animal cells. Yet, the mechanisms driving its age-related upregulation remain unclear. Here, we show that in budding yeast, Cdc42 accumulates over successive cell divisions and that reducing its levels extends life span. Using microfluidics-assisted live-cell imaging and genetic analysis, we found that Cdc42 is distributed unevenly between mother and daughter cells during division. Daughter cells inherit lower Cdc42 levels, which likely help them remain young. This asymmetric distribution depends on Cdc42's association with and/or release from endomembranes and likely involves Ydj1, a farnesylated Hsp40/DnaJ chaperone anchored to the endoplasmic reticulum. Ydj1 interacts with Cdc42, promoting its stability and proper partitioning during cell division. We propose that ER-bound Ydj1 facilitates the asymmetric distribution of Cdc42, thereby restricting aging to mother cells.