PLoS Biology最新文献

Shoot stem cells, harbored in the shoot apical meristem (SAM), play key roles during post-embryonic development of Arabidopsis and function as the origin of plant aerial tissues. Multiple transcription factors are involved in the sophisticated transcriptional regulation of stem cell homeostasis, with the WUSCHEL (WUS)/CLAVATA3 (CLV3) negative feedback loop playing a central role. WUS acts as a master regulator in maintaining stem cells through its transcriptional regulatory activity including repressive and activating abilities. Although the interaction between WUS and TOPLESS confers the repressive activity of WUS in transcriptional control, the mechanism by which WUS activates gene expression remains elusive. Here, we showed that DORNRÖSCHEN competitively interacts with WUS and disturbs the WUS homodimer, which recruits BRAHMA to activate CLV3 expression via nucleosome depletion for maintaining the stem cell pool.

Protein lysine methyltransferases (PKMTs) methylate histone and non-histone proteins to regulate biological outcomes such as development and disease including viral infection. While PKMTs have been extensively studied for modulating the antiviral responses via host gene regulation, their role in methylation of proteins encoded by viruses and its impact on host-pathogen interactions remain poorly understood. In this study, we discovered distinct nucleo-cytoplasmic form of euchromatic histone methyltransferase 1 (EHMT1N/C), a PKMT, that phase separates into viral inclusion bodies (IBs) upon cytoplasmic RNA-virus infection (Sendai Virus). EHMT1N/C interacts with cytoplasmic EHMT2 and methylates SeV-Nucleoprotein upon infection. Elevated nucleoprotein methylation during infection correlated with coalescence of small IBs into large mature platforms for efficient replication. Inhibition of EHMT activity by pharmacological inhibitors or genetic depletion of EHMT1N/C reduced the size of IBs with a concomitant reduction in replication. Additionally, we also found that EHMT1 condensation is not restricted to SeV alone but was also seen upon pathogenic RNA viral infections caused by Chandipura and Dengue virus. Collectively, our work elucidates a new mechanism by which cytoplasmic EHMT1 acts as proviral host factor to regulate host-pathogen interaction.

Cellular asymmetry begins with the selection of a discrete point on the cell surface that triggers Rho-GTPases activation and localized assembly of the cytoskeleton to establish new growth zones. The cylindrical shape of fission yeast is organized by microtubules (MT) that deliver the landmark Tea1-Tea4 complex at the cell tips to define the growth poles. However, only a few tea1Δ cells mistaken the direction of growth, indicating that they manage to detect their growth sites. Here, we show that Rgf1 (Rho1-GEF) and Tea4 are components of the same complex and that Rgf1 activity toward Rho1 is required for strengthen Tea4 at the cell tips. Moreover, in cells lacking Tea1, selection of the correct growth site depends on Rgf1 and on a correctly polarized actin cytoskeleton, both necessary for Rho1 activation at the pole. We propose an actin-dependent mechanism driven by Rgf1-Rho1 that marks the poles independently of MTs and the Tea1-Tea4 complex.

Previous work shows that a host's resident microbial community can provide resistance against an invading pathogen. However, this community is continuously changing over time due to adaptive mutations, and how these changes affect the invasion resistance of these communities remains poorly understood. To address this knowledge gap, we used an experimental evolution approach in synthetic communities of Escherichia coli and Salmonella Typhimurium to investigate how the invasion resistance of this community against a bacterium expressing a virulent phenotype, i.e., colicin secretion, changes over time. We show that evolved communities accumulate mutations in genes involved in carbon metabolism and motility, while simultaneously becoming less resistant to invasion. By investigating two-species competitions and generating a three-species competition model, we show that this outcome is dependent on the strength of interspecies interactions. Our study demonstrates how adaptive changes in microbial communities can make them more prone to the detrimental effects of an invading species.

Humans experience many influenza infections over their lives, resulting in complex and varied immunological histories. Although experimental and quantitative analyses have improved our understanding of the immunological processes defining an individual's antibody repertoire, how these within-host processes are linked to population-level influenza epidemiology in humans remains unclear. Here, we used a multilevel mathematical model to jointly infer antibody dynamics and individual-level lifetime influenza A/H3N2 infection histories for 1,130 individuals in Guangzhou, China, using 67,683 haemagglutination inhibition (HI) assay measurements against 20 A/H3N2 strains from repeat serum samples collected between 2009 and 2015. These estimated infection histories allowed us to reconstruct historical seasonal influenza patterns in humans and to investigate how influenza incidence varies over time, space, and age in this population. We estimated median annual influenza infection rates to be approximately 19% from 1968 to 2015, but with substantial variation between years; 88% of individuals were estimated to have been infected at least once during the study period (2009 to 2015), and 20% were estimated to have 3 or more infections in that time. We inferred decreasing infection rates with increasing age, and found that annual attack rates were highly correlated across all locations, regardless of their distance, suggesting that age has a stronger impact than fine-scale spatial effects in determining an individual's antibody profile. Finally, we reconstructed each individual's expected antibody profile over their lifetime and inferred an age-stratified relationship between probability of infection and HI titre. Our analyses show how multi-strain serological panels provide rich information on long-term epidemiological trends, within-host processes, and immunity when analysed using appropriate inference methods, and adds to our understanding of the life course epidemiology of influenza A/H3N2.

In lichen research, metagenomes are increasingly being used for evaluating symbiont composition and metabolic potential, but the overall content and limitations of these metagenomes have not been assessed. We reassembled over 400 publicly available metagenomes, generated metagenome-assembled genomes (MAGs), constructed phylogenomic trees, and mapped MAG occurrence and frequency across the data set. Ninety-seven percent of the 1,000 recovered MAGs were bacterial or the fungal symbiont that provides most cellular mass. Our mapping of recovered MAGs provides the most detailed survey to date of bacteria in lichens and shows that 4 family-level lineages from 2 phyla accounted for as many bacterial occurrences in lichens as all other 71 families from 16 phyla combined. Annotation of highly complete bacterial, fungal, and algal MAGs reveals functional profiles that suggest interdigitated vitamin prototrophies and auxotrophies, with most lichen fungi auxotrophic for biotin, most bacteria auxotrophic for thiamine and the few annotated algae with partial or complete pathways for both, suggesting a novel dimension of microbial cross-feeding in lichen symbioses. Contrary to longstanding hypotheses, we found no annotations consistent with nitrogen fixation in bacteria other than known cyanobacterial symbionts. Core lichen symbionts such as algae were recovered as MAGs in only a fraction of the lichen symbioses in which they are known to occur. However, the presence of these and other microbes could be detected at high frequency using small subunit rRNA analysis, including in many lichens in which they are not otherwise recognized to occur. The rate of MAG recovery correlates with sequencing depth, but is almost certainly influenced by biological attributes of organisms that affect the likelihood of DNA extraction, sequencing and successful assembly, including cellular abundance, ploidy and strain co-occurrence. Our results suggest that, though metagenomes are a powerful tool for surveying microbial occurrence, they are of limited use in assessing absence, and their interpretation should be guided by an awareness of the interacting effects of microbial community complexity and sequencing depth.

Bottom-up, data-driven, large-scale models provide a mechanistic understanding of neuronal functions. A new study in PLOS Biology builds a biologically realistic model of the rodent CA1 region that aims to become an accessible tool for the whole hippocampal community.

Genomics-based predictions indicate that plants harbor the ability to make a vast array of as yet undiscovered chemistry. Recent advances open up the potential to harness this capability at unprecedented scale for the discovery and development of new therapeutics.

The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, it has been challenging to integrate information obtained from diverse experimental approaches. To address this challenge, we present a community-based, full-scale in silico model of the rat CA1 that integrates a broad range of experimental data, from synapse to network, including the reconstruction of its principal afferents, the Schaffer collaterals, and a model of the effects that acetylcholine has on the system. We tested and validated each model component and the final network model, and made input data, assumptions, and strategies explicit and transparent. The unique flexibility of the model allows scientists to potentially address a range of scientific questions. In this article, we describe the methods used to set up simulations to reproduce in vitro and in vivo experiments. Among several applications in the article, we focus on theta rhythm, a prominent hippocampal oscillation associated with various behavioral correlates and use our computer model to reproduce experimental findings. Finally, we make data, code, and model available through the hippocampushub.eu portal, which also provides an extensive set of analyses of the model and a user-friendly interface to facilitate adoption and usage. This community-based model represents a valuable tool for integrating diverse experimental data and provides a foundation for further research into the complex workings of the hippocampal CA1 region.

A fundamental question in biology, central to our understanding of cancer and other pathologies, is determining how different cell types coordinate to form and maintain tissues. Recognizing the distinct features and capabilities of the cells that compose these tissues is critical. Unfortunately, the complexity of tissues often hinders our ability to distinguish between neighboring cell types and, in turn, scrutinize their transcriptomes and generate reliable and tractable cell models for studying their inherently different biologies. We have recently introduced a novel method that permits the identification and purification of the 12 cell types that compose the human breast-nearly all of which could be reliably propagated in the laboratory. Here, we explore the nature of these cell types. We sequence mRNAs from each purified population and investigate transcriptional patterns that reveal their distinguishing features. We describe the differentially expressed genes and enriched biological pathways that capture the essence of each cell type, and we highlight transcripts that display intriguing expression patterns. These data, analytic tools, and transcriptional analyses form a rich resource whose exploration provides remarkable insights into the inner workings of the cell types composing the breast, thus furthering our understanding of the rules governing normal cell and tissue function.