ISSN / EISSN : 15449173 / 15457885
Current Publisher: Public Library of Science (PLoS) (10.1371)
Total articles ≅ 5,499
Google Scholar h5-index: 87
Latest articles in this journal
PLOS Biology, Volume 17; doi:10.1371/journal.pbio.3000530
Abstract:Type I interferon (IFN-I) is a family of multifunctional cytokines that modulate the innate and adaptive immunity and are used to treat mastocytosis. Although IFN-I is known to suppress mast cell function, including histamine release, the mechanisms behind its effects on mast cells have been poorly understood. We here investigated IFN-I’s action on mast cells using interferon-α/β receptor subunit 1 (Ifnar1)-deficient mice, which lack a functional IFN-I receptor complex, and revealed that IFN-I in the steady state is critical for mast cell homeostasis, the disruption of which is centrally involved in systemic anaphylaxis. Ifnar1-deficient mice showed exacerbated systemic anaphylaxis after sensitization, which was associated with increased histamine in the circulation, even though the mast cell numbers and high affinity immunoglobulin E receptor (FcεRI) expression levels were similar between Ifnar1-deficient and wild-type (WT) mice. Ifnar1-deficient mast cells showed increased secretory granule synthesis and exocytosis, which probably involved the increased transcription of Tfeb. Signal transducer and activator of transcription 1(Stat1) and Stat2 were unexpectedly insufficient to mediate these IFN-I functions, and instead, Stat3 played a critical role in a redundant manner with Stat1. Our findings revealed a novel regulation mechanism of mast cell homeostasis, in which IFN-I controls lysosome-related organelle biogenesis.
PLOS Biology, Volume 17; doi:10.1371/journal.pbio.3000526
Abstract:The Amazon is Brazil’s greatest natural resource and invaluable to the rest of the world as a buffer against climate change. The recent election of Brazil’s president brought disputes over development plans for the region back into the spotlight. Historically, the development model for the Amazon has focused on exploitation of natural resources, resulting in environmental degradation, particularly deforestation. Although considerable attention has focused on the long-term global cost of “losing the Amazon,” too little attention has focused on the emergence and reemergence of vector-borne diseases that directly impact the local population, with spillover effects to other neighboring areas. We discuss the impact of Amazon development models on human health, with a focus on vector-borne disease risk. We outline policy actions that could mitigate these negative impacts while creating opportunities for environmentally sensitive economic activities.
PLOS Biology, Volume 17; doi:10.1371/journal.pbio.3000497
Abstract:Predicting individual mental traits and behavioral dispositions from brain imaging data through machine-learning approaches is becoming a rapidly evolving field in neuroscience. Beyond scientific and clinical applications, such approaches also hold the potential to gain substantial influence in fields such as human resource management, education, or criminal law. Although several challenges render real-life applications of such tools difficult, future conflicts of individual, economic, and public interests are preprogrammed, given the prospect of improved personalized predictions across many domains. In this Perspective paper, we thus argue for the need to engage in a discussion on the ethical, legal, and societal implications of the emergent possibilities for brain-based predictions and outline some of the aspects for this discourse.
PLOS Biology, Volume 17; doi:10.1371/journal.pbio.3000534
Abstract:Phosphate starvation response (PSR) in nonmycorrhizal plants comprises transcriptional reprogramming resulting in severe physiological changes to the roots and shoots and repression of plant immunity. Thus, plant-colonizing microorganisms—the plant microbiota—are exposed to direct influence by the soil’s phosphorus (P) content itself as well as to the indirect effects of soil P on the microbial niches shaped by the plant. The individual contribution of these factors to plant microbiota assembly remains unknown. To disentangle these direct and indirect effects, we planted PSR-deficient Arabidopsis mutants in a long-term managed soil P gradient and compared the composition of their shoot and root microbiota to wild-type plants across different P concentrations. PSR-deficiency had a larger effect on the composition of both bacterial and fungal plant-associated microbiota than soil P concentrations in both roots and shoots. To dissect plant–microbe interactions under variable P conditions, we conducted a microbiota reconstitution experiment. Using a 185-member bacterial synthetic community (SynCom) across a wide P concentration gradient in an agar matrix, we demonstrated a shift in the effect of bacteria on the plant from a neutral or positive interaction to a negative one, as measured by rosette size. This phenotypic shift was accompanied by changes in microbiota composition: the genus Burkholderia was specifically enriched in plant tissue under P starvation. Through a community drop-out experiment, we demonstrated that in the absence of Burkholderia from the SynCom, plant shoots accumulated higher ortophosphate (Pi) levels than shoots colonized with the full SynCom but only under Pi starvation conditions. Therefore, Pi-stressed plants are susceptible to colonization by latent opportunistic competitors found within their microbiome, thus exacerbating the plant’s Pi starvation.
PLOS Biology, Volume 17; doi:10.1371/journal.pbio.3000476
Abstract:Learning of most motor skills is constrained in a species-specific manner. However, the proximate mechanisms underlying species-specific learned behaviors remain poorly understood. Songbirds acquire species-specific songs through learning, which is hypothesized to depend on species-specific patterns of gene expression in functionally specialized brain regions for vocal learning and production, called song nuclei. Here, we leveraged two closely related songbird species, zebra finch, owl finch, and their interspecific first-generation (F1) hybrids, to relate transcriptional regulatory divergence between species with the production of species-specific songs. We quantified genome-wide gene expression in both species and compared this with allele-specific expression in F1 hybrids to identify genes whose expression in song nuclei is regulated by species divergence in either cis- or trans-regulation. We found that divergence in transcriptional regulation altered the expression of approximately 10% of total transcribed genes and was linked to differential gene expression between the two species. Furthermore, trans-regulatory changes were more prevalent than cis-regulatory and were associated with synaptic formation and transmission in song nucleus RA, the avian analog of the mammalian laryngeal motor cortex. We identified brain-derived neurotrophic factor (BDNF) as an upstream mediator of trans-regulated genes in RA, with a significant correlation between individual variation in BDNF expression level and species-specific song phenotypes in F1 hybrids. This was supported by the fact that the pharmacological overactivation of BDNF receptors altered the expression of its trans-regulated genes in the RA, thus disrupting the learned song structures of adult zebra finch songs at the acoustic and sequence levels. These results demonstrate functional neurogenetic associations between divergence in region-specific transcriptional regulation and species-specific learned behaviors.
PLOS Biology, Volume 17; doi:10.1371/journal.pbio.3000568
PLOS Biology, Volume 17; doi:10.1371/journal.pbio.3000481
Abstract:Data normalization is a critical step in RNA sequencing (RNA-seq) analysis, aiming to remove systematic effects from the data to ensure that technical biases have minimal impact on the results. Analyzing numerous RNA-seq datasets, we detected a prevalent sample-specific length effect that leads to a strong association between gene length and fold-change estimates between samples. This stochastic sample-specific effect is not corrected by common normalization methods, including reads per kilobase of transcript length per million reads (RPKM), Trimmed Mean of M values (TMM), relative log expression (RLE), and quantile and upper-quartile normalization. Importantly, we demonstrate that this bias causes recurrent false positive calls by gene-set enrichment analysis (GSEA) methods, thereby leading to frequent functional misinterpretation of the data. Gene sets characterized by markedly short genes (e.g., ribosomal protein genes) or long genes (e.g., extracellular matrix genes) are particularly prone to such false calls. This sample-specific length bias is effectively removed by the conditional quantile normalization (cqn) and EDASeq methods, which allow the integration of gene length as a sample-specific covariate. Consequently, using these normalization methods led to substantial reduction in GSEA false results while retaining true ones. In addition, we found that application of gene-set tests that take into account gene–gene correlations attenuates false positive rates caused by the length bias, but statistical power is reduced as well. Our results advocate the inspection and correction of sample-specific length biases as default steps in RNA-seq analysis pipelines and reiterate the need to account for intergene correlations when performing gene-set enrichment tests to lessen false interpretation of transcriptomic data.
PLOS Biology, Volume 17; doi:10.1371/journal.pbio.3000472
Abstract:With the rapid improvement of cryo-electron microscopy (cryo-EM) resolution, new computational tools are needed to assist and improve upon atomic model building and refinement options. This communication demonstrates that microscopists can now collaborate with the players of the computer game Foldit to generate high-quality de novo structural models. This development could greatly speed the generation of excellent cryo-EM structures when used in addition to current methods.
PLOS Biology, Volume 17; doi:10.1371/journal.pbio.3000547
Abstract:The sensitivity of genotype-based diagnostics that predict antimicrobial susceptibility is limited by the extent to which they detect genes and alleles that lead to resistance. As novel resistance variants are expected to emerge, such sensitivity is expected to decline unless the new variants are detected and incorporated into the diagnostic. Here, we present a mathematical framework to define how many diagnostic failures may be expected under varying surveillance regimes and thus quantify the surveillance needed to maintain the sensitivity of genotype-based diagnostics.
PLOS Biology, Volume 17; doi:10.1371/journal.pbio.3000510
Abstract:Despite general and wide-ranging negative effects of coral reef degradation on reef communities, hope might exist for reef-associated predators that use nursery habitats. When reef structural complexity is lost, refuge density declines and prey vulnerability increases. Here, we explore whether the presence of nursery habitats can promote high predator productivity on degraded reefs by mitigating the costs of increased vulnerability in early life, whilst allowing for the benefits of increased food availability in adulthood. We apply size-based ecosystem models of coral reefs with high and low structural complexity to predict fish biomass and productivity in the presence and absence of mangrove nurseries. Our scenarios allow us to elucidate the interacting effects of refuge availability and ontogenetic habitat shifts for fisheries productivity. We find that low complexity, degraded reefs with nurseries can support fisheries productivity that is equal to or greater than that in complex reefs that lack nurseries. We compare and validate model predictions with field data from Belize. Our results should inform reef fisheries management strategies and protected areas now and into the future.