Staphylococcus aureus is a major causative pathogen of osteomyelitis. Intracellular infections of resident bone cells including osteocytes can persist despite gold-standard clinical intervention. The mechanisms by which intracellular S. aureus evades antibiotic therapy are unknown. In this study, we utilised an in vitro S. aureus infection model of human osteocytes to investigate whether antibiotic-mediated dysregulation of autophagy contributes to this phenomenon. Infected or non-infected osteocyte-like cells were exposed to combinations of rifampicin, vancomycin, and modulators of autophagy. Intracellular bacterial growth characteristics were assessed using colony-forming unit (CFU) analysis, viable bacterial DNA abundance, and the rate of escape into antibiotic-free medium, together with measures of autophagic flux. Rifampicin, alone or in combination with vancomycin, caused a rapid decrease in the culturability of intracellular bacteria, concomitant with stable or increased absolute bacterial DNA levels. Both antibiotics significantly inhibited autophagic flux. However, modulation of autophagic flux did not affect viable bacterial DNA levels. In summary, autophagy was shown to be a factor in the host-pathogen relationship in this model, as its modulation affected the growth state of intracellular S. aureus with respect to both their culturability and propensity to escape the intracellular niche. While rifampicin and vancomycin treatments moderately suppressed autophagic flux acutely, this did not explain the paradoxical response of antibiotic treatment in decreasing S. aureus culturability whilst failing to clear bacterial DNA and hence intracellular bacterial load. Thus, off-target effects of rifampicin and vancomycin on autophagic flux in osteocyte-like cells could not explain the persistent S. aureus infection in these cells.

Due to their ability to replicate the in vivo microenvironment through cell interaction and induce cells to stimulate cell function, three-dimensional cell culture models can overcome the limitations of two-dimensional models. Organoids are 3D models that demonstrate the ability to replicate the natural structure of an organ. In most organoid tissue cultures, matrigel made of a mouse tumor extracellular matrix protein mixture is an essential ingredient. However, its tumor-derived origin, batch-to-batch variation, high cost, and safety concerns have limited the usefulness of organoid drug development and regenerative medicine. Its clinical application has also been hindered by the fact that organoid generation is dependent on the use of poorly defined matrices. Therefore, matrix optimization is a crucial step in developing organoid culture that introduces alternatives as different materials. Recently, a variety of substitute materials has reportedly replaced matrigel. The purpose of this study is to review the significance of the latest advances in materials for cell culture applications and how they enhance build network systems by generating proper cell behavior. Excellence in cell behavior is evaluated from their cell characteristics, cell proliferation, cell differentiation, and even gene expression. As a result, graphene oxide as a matrix optimization demonstrated high potency in developing organoid models. Graphene oxide can promote good cell behavior and is well known for having good biocompatibility. Hence, advances in matrix optimization of graphene oxide provide opportunities for the future development of advanced organoid models.

Evolutionary models of quantitative traits often assume trade-offs between beneficial and detrimental traits, requiring modelers to specify a function linking costs to benefits. The choice of trade-off function is often consequential; functions that assume diminishing returns (accelerating costs) typically lead to single equilibrium genotypes, while decelerating costs often lead to evolutionary branching. Despite their importance, we still lack a strong theoretical foundation to base the choice of trade-off function. To address this gap, we explore how trade-off functions can emerge from the genetic architecture of a quantitative trait. We developed a multi-locus model of disease resistance, assuming each locus had random antagonistic pleiotropic effects on resistance and fecundity. We used this model to generate genotype landscapes and explored how additive versus epistatic genetic architectures influenced the shape of the trade-off function. Regardless of epistasis, our model consistently led to accelerating costs. We then used our genotype landscapes to build an evolutionary model of disease resistance. Unlike other models with accelerating costs, our approach often led to genetic polymorphisms at equilibrium. Our results suggest that accelerating costs are a strong null model for evolutionary trade-offs and that the eco-evolutionary conditions required for polymorphism may be more nuanced than previously believed.

Mononuclear phagocytes facilitate the dissemination of the obligate intracellular parasite Toxoplasma gondii. Here, we report how a set of secreted parasite effector proteins from dense granule organelles (GRA) orchestrates dendritic cell-like chemotactic and pro-inflammatory activation of parasitized macrophages. These effects enabled efficient dissemination of the type II T. gondii lineage, a highly prevalent genotype in humans. We identify novel functions for effectors GRA15 and GRA24 in promoting CCR7-mediated macrophage chemotaxis by acting on NF-κB and p38 MAPK signaling pathways, respectively, with contributions of GRA16/18 and counter-regulation by effector TEEGR. Further, GRA28 boosted chromatin accessibility and GRA15/24/NF-κB-dependent transcription at the Ccr7 gene locus in primary macrophages. In vivo, adoptively transferred macrophages infected with wild-type T. gondii outcompeted macrophages infected with a GRA15/24 double mutant in migrating to secondary organs in mice. The data show that T. gondii, rather than being passively shuttled, actively promotes its dissemination by inducing a finely regulated pro-migratory state in parasitized human and murine phagocytes via co-operating polymorphic GRA effectors.

Although intrinsic postzygotic reproductive barriers can play a fundamental role in speciation, their underlying evolutionary causes are widely debated. One hypothesis is that incompatibilities result from genomic conflicts. Here, I synthesize the evidence that conflict generates incompatibilities in plants, thus playing a creative role in plant biodiversity. While much evidence supports a role for conflict in several classes of incompatibility, integrating knowledge of incompatibility alleles with natural history can provide further essential tests. Moreover, comparative work can shed light on the relative importance of conflict in causing incompatibilities, including the extent to which their evolution is repeatable. Together, these approaches can provide independent lines of evidence that conflict causes incompatibilities, cementing its role in plant speciation.

We have developed a machine learning (ML) approach using Gaussian process (GP)-based spatial covariance (SCV) to track the impact of spatial-temporal mutational events driving host-pathogen balance in biology. We show how SCV can be applied to understanding the response of evolving covariant relationships linking the variant pattern of virus spread to pathology for the entire SARS-CoV-2 genome on a daily basis. We show that GP-based SCV relationships in conjunction with genome-wide co-occurrence analysis provides an early warning anomaly detection (EWAD) system for the emergence of variants of concern (VOCs). EWAD can anticipate changes in the pattern of performance of spread and pathology weeks in advance, identifying signatures destined to become VOCs. GP-based analyses of variation across entire viral genomes can be used to monitor micro and macro features responsible for host-pathogen balance. The versatility of GP-based SCV defines starting point for understanding nature\'s evolutionary path to complexity through natural selection.

Genetic variation for disease resistance within host populations can strongly impact the spread of endemic pathogens. In plants, recent work has shown that within-population variation in resistance can also affect the transmission of foreign spillover pathogens if that resistance is general. However, most hosts also possess specific resistance mechanisms that provide strong defenses against coevolved endemic pathogens. Here we use a modeling approach to ask how antagonistic coevolution between hosts and their endemic pathogen at the specific resistance locus can affect the frequency of general resistance, and therefore a host\'s vulnerability to foreign pathogens. We develop a two-locus model with variable recombination that incorporates both general (resistance to all pathogens) and specific (resistance to endemic pathogens only). We find that introducing coevolution into our model greatly expands the regions where general resistance can evolve, decreasing the risk of foreign pathogen invasion. Furthermore, coevolution greatly expands which conditions maintain polymorphisms at both resistance loci, thereby driving greater genetic diversity within host populations. This genetic diversity often leads to positive correlations between host resistance to foreign and endemic pathogens, similar to those observed in natural populations. However, if resistance loci become linked, the resistance correlations can shift to negative. If we include a third, linkage modifying locus into our model, we find that selection often favors complete linkage. Our model demonstrates how coevolutionary dynamics with an endemic pathogen can mold the resistance structure of host populations in ways that affect its susceptibility to foreign pathogen spillovers, and that the nature of these outcomes depends on resistance costs, as well as the degree of linkage between resistance genes.

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Upon pathogen detection, macrophages normally stay sessile in tissues while dendritic cells (DCs) migrate to secondary lymphoid tissues. The obligate intracellular protozoan Toxoplasma gondii exploits the trafficking of mononuclear phagocytes for dissemination via unclear mechanisms. We report that, upon T. gondii infection, macrophages initiate the expression of transcription factors normally attributed to DCs, upregulate CCR7 expression with a chemotactic response, and perform systemic migration when adoptively transferred into mice. We show that parasite effector GRA28, released by the MYR1 secretory pathway, cooperates with host chromatin remodelers in the host cell nucleus to drive the chemotactic migration of parasitized macrophages. During in vivo challenge studies, bone marrow-derived macrophages infected with wild-type T. gondii outcompeted those challenged with MYR1- or GRA28-deficient strains in migrating and reaching secondary organs. This work reveals how an intracellular parasite hijacks chemotaxis in phagocytes and highlights a remarkable migratory plasticity in differentiated cells of the mononuclear phagocyte system.

When bacteria sense cues from the host environment, stress responses are activated. Two component systems, sigma factors, small RNAs, ppGpp stringent response, and chaperones start coordinate the expression of virulence factors or immunomodulators to allow bacteria to respond. Although, some of these are well studied, such as the two-component systems, the contribution of other regulators, such as sigma factors or ppGpp, is increasingly gaining attention. Pseudomonas aeruginosa is the gold standard pathogen for studying the molecular mechanisms to sense and respond to environmental cues. Bordetella spp., on the other hand, is a microbial model for studying host-pathogen interactions at the molecular level. These two pathogens have the ability to colonize the lungs of patients with chronic diseases, suggesting that they have the potential to share a niche and interact. However, the molecular networks that facilitate adaptation of Bordetella spp. to cues are unclear. Here, we offer a side-by-side comparison of what is known about these diverse molecular mechanisms that bacteria utilize to counteract host immune responses, while highlighting the relatively unexplored interactions between them.