Gotowa bibliografia na temat „Host - microbial interaction”

The vertebrate gut has been continuously populated with complex and dynamic microbial and eukaryotic communities, that over millions of years have coevolved both spatially and temporally (Kreisinger et al., 2015). Due to the prolonged coexistence, intestinal parasites (protozoa and helminths) and resident microbiota have developed the ability to influence one another by several mechanisms: 1) produce changes at the level of intestinal mucus and epithelial barrier, 2) alter the host immune response or 3) direct interaction (Leung et al., 2018). The uncontrolled use of anthelmintics can lead to the elimination of commensal organisms and alteration of host immunity and intestinal microbial community composition. Thus, the aim of this research is to highlight the complexity of interactions between intestinal bacteria and parasites and their importance for the host. The “parasitome”- microbiota relationship is a complex phenomenon that plays an essential role in host intestinal homeostasis, the absence or alteration of either of these organisms being able to cause a severe disruption of host immune system (Leung et al., 2018). Is therefore essential to acquire a deeper understanding of the molecular mechanisms of interaction between these two communities.

A good understanding of how microbes interact with hosts has a direct bearing on our capability of fighting infectious microbial pathogens and making good use of beneficial ones. Among the model organisms used to study reciprocal actions among microbes and hosts, C. elegans may be the most advantageous in the context of its unique attributes such as the short life cycle, easiness of laboratory maintenance, and the availability of different genetic mutants. This review summarizes the recent advances in understanding host-microbe interactions in C. elegans. Although these investigations have greatly enhanced our understanding of C. elegans-microbe relationships, all but one of them involve only one or few microbial species. We argue here that more research is needed for exploring the evolution and establishment of a complex microbial community in the worm’s intestine and its interaction with the host.

Type 2 diabetes mellitus (T2DM) is an established risk factor for periodontitis, yet its contribution to creating host-bacterial disequilibrium in the subgingival crevice is poorly understood. The present investigation aimed to quantify the impact of hyperglycemia on host-bacterial interactions in established periodontitis and to map shifts in these dynamics following mechanical nonsurgical therapy. Seventeen T2DM and 17 non-T2DM subjects with generalized severe chronic periodontitis were recruited along with 20 periodontally healthy individuals. Subjects with periodontitis were treated with scaling and root planing (SRP). Samples of subgingival biofilm and gingival crevicular fluid were collected at baseline and at 1-, 3-, and 6 mo postoperatively. Correlations were generated between 13.7 million 16S ribosomal DNA sequences and 8 immune mediators. Intermicrobial and host-microbial interactions were modeled using differential network analysis. Periodontal health was characterized by a sparse interbacterial and highly connected cytokine-bacterial network, while both normoglycemics and T2DM subjects with periodontitis demonstrated robust congeneric and intergeneric hubs but significantly fewer cytokine-bacterial connections. Following SRP, the cytokine-bacterial edges demonstrated a 2-fold increase 1 mo postoperatively and a 10-fold increase at 6 mo in normoglycemics. In hyperglycemics, there was a doubling at 1 mo but no further changes thereafter. These shifts accompanied an increasingly sparse interbacterial network. In normoglycemics, the nodes anchored by interleukin (IL)–4, IL-6, and IL-10 demonstrated greatest rewiring, while in hyperglycemics, IL-1β, IL-6, INF-γ, and IL-17 exhibited progressive rewiring. Thus, the present investigation points to a breakdown in host-bacterial mutualism in periodontitis, with interbacterial interactions rather than host-bacterial interactions primarily determining community assembly. Hyperglycemia further exacerbates this uncoupled mutualism. Our data also demonstrate that while nonsurgical therapy might not consistently alter microbial abundances or lower proinflammatory molecules, it “reboots” the interaction between the immunoinflammatory system and the newly colonizing microbiome, restoring a role for the immune system in determining bacterial colonization. However, this outcome is lower and delayed in hyperglycemics.

Animal sociality facilitates the transmission of pathogenic microorganisms among hosts, but the extent to which sociality enables animals’ beneficial microbial associations is poorly understood. The question is critical because microbial communities, particularly those in the gut, are key regulators of host health. We show evidence that chimpanzee social interactions propagate microbial diversity in the gut microbiome both within and between host generations. Frequent social interaction promotes species richness within individual microbiomes as well as homogeneity among the gut community memberships of different chimpanzees. Sampling successive generations across multiple chimpanzee families suggests that infants inherited gut microorganisms primarily through social transmission. These results indicate that social behavior generates a pan-microbiome, preserving microbial diversity across evolutionary time scales and contributing to the evolution of host species–specific gut microbial communities.

Microorganisms are present in nearly every niche on Earth and mainly do not exist solely but form communities of single or mixed species. Within such microbial populations and between the microbes and a eukaryotic host, various microbial interactions take place in an ever-changing environment. Those microbial interactions are crucial for a successful establishment and maintenance of a microbial population. The basic unit of interaction is the gene expression of each organism in this community in response to biotic or abiotic stimuli. Differential gene expression is responsible for producing exchangeable molecules involved in the interactions, ultimately leading to community behavior. Cooperative and competitive interactions within bacterial communities and between the associated bacteria and the host are the focus of this review, emphasizing microbial cell–cell communication (quorum sensing). Further, metagenomics is discussed as a helpful tool to analyze the complex genomic information of microbial communities and the functional role of different microbes within a community and to identify novel biomolecules for biotechnological applications.

ABSTRACTThe microbial community in which a pathogen evolves is fundamental to disease outcome. Species interacting with a pathogen on the host surface shape the distribution, density, and genetic diversity of the inoculum, but the role of these species is rarely determined. The screening method developed here can be used to characterize pathogen-associated species affecting disease. This strategy involves three steps: (i) constitution of the microbial community, using the pathogen as a trap; (ii) community selection, using extracts from the pathogen as the sole nutrient source; and (iii) molecular identification and the screening of isolates focusing on their effects on the growth of the pathogenin vitroand host disease. This approach was applied to a soilborne plant pathogen,Phytophthora parasitica, structured in a biofilm, for screening the microbial community from the rhizosphere ofNicotiana tabacum(the host). Two of the characterized eukaryotes interfered with the oomycete cycle and may affect the host disease. AVorticellaspecies acted through a mutualistic interaction withP. parasitica, disseminating pathogenic material by leaving the biofilm. APhomaspecies established an amensal interaction withP. parasitica, strongly suppressing disease by inhibitingP. parasiticagermination. This screening method is appropriate for all nonobligate pathogens. It allows the definition of microbial species as promoters or suppressors of a disease for a given biotope. It should also help to identify important microbial relationships for ecology and evolution of pathogens.