The field of microbiome research has evolved rapidly over the past few decades and has become a topic of great scientific and public interest. As a result of this rapid growth in interest covering different fields, we are lacking a clear commonly agreed definition of the term "microbiome." Moreover, a consensus on best practices in microbiome research is missing. Recently, a panel of international experts discussed the current gaps in the frame of the European-funded MicrobiomeSupport project. The meeting brought together about 40 leaders from diverse microbiome areas, while more than a hundred experts from all over the world took part in an online survey accompanying the workshop. This article excerpts the outcomes of the workshop and the corresponding online survey embedded in a short historical introduction and future outlook. We propose a definition of microbiome based on the compact, clear, and comprehensive description of the term provided by Whipps et al. in 1988, amended with a set of novel recommendations considering the latest technological developments and research findings. We clearly separate the terms microbiome and microbiota and provide a comprehensive discussion considering the composition of microbiota, the heterogeneity and dynamics of microbiomes in time and space, the stability and resilience of microbial networks, the definition of core microbiomes, and functionally relevant keystone species as well as co-evolutionary principles of microbe-host and inter-species interactions within the microbiome. These broad definitions together with the suggested unifying concepts will help to improve standardization of microbiome studies in the future, and could be the starting point for an integrated assessment of data resulting in a more rapid transfer of knowledge from basic science into practice. Furthermore, microbiome standards are important for solving new challenges associated with anthropogenic-driven changes in the field of planetary health, for which the understanding of microbiomes might play a key role.
Plant microbiome and its manipulation herald a new era for plant biotechnology with the potential to benefit sustainable crop production. However, studies evaluating the diversity, structure and impact of the microbiota in economic important crops are still rare. Here we describe a comprehensive inventory of the structure and assemblage of the bacterial and fungal communities associated with sugarcane. Our analysis identified 23,811 bacterial OTUs and an unexpected 11,727 fungal OTUs inhabiting the endophytic and exophytic compartments of roots, shoots, and leaves. These communities originate primarily from native soil around plants and colonize plant organs in distinct patterns. The sample type is the primary driver of fungal community assemblage, and the organ compartment plays a major role in bacterial community assemblage. We identified core bacterial and fungal communities composed of less than 20% of the total microbial richness but accounting for over 90% of the total microbial relative abundance. The roots showed 89 core bacterial families, 19 of which accounted for 44% of the total relative abundance. Stalks are dominated by groups of yeasts that represent over 12% of total relative abundance. The core microbiome described here comprise groups whose biological role underlies important traits in plant growth and fermentative processes.
Severe dengue infection in humans causes a disease characterized by thrombocytopenia, increased levels of cytokines, increased vascular permeability, hemorrhage, and shock. Treatment is supportive. Activation of platelet-activating factor (PAF) receptor (PAFR) on endothelial cells and leukocytes induces increase in vascular permeability, hypotension, and production of cytokines. We hypothesized that activation of PAFR could account for the major systemic manifestations of dengue infection. Inoculation of adult mice with an adapted strain of Dengue virus caused a systemic disease, with several features of the infection in humans. In PAFR ؊/؊ mice, there was decreased thrombocytopenia, hemoconcentration, decreased systemic levels of cytokines, and delay of lethality, when compared with WT infected mice. Treatment with UK-74,505, an orally active PAFR antagonist, prevented the above-mentioned manifestations, as well as hypotension and increased vascular permeability, and decreased lethality, even when started 5 days after virus inoculation. Similar results were obtained with a distinct PAFR antagonist, PCA-4246. Despite decreased disease manifestation, viral loads were similar (PAFR ؊/؊ ) or lower (PAFR antagonist) than in WT mice. Thus, activation of PAFR plays a major role in the pathogenesis of experimental dengue infection, and its blockade prevents more severe disease manifestation after infection with no increase in systemic viral titers, suggesting that there is no interference in the ability of the murine host to deal with the infection. PAFR antagonists are diseasemodifying agents in experimental dengue infection.inflammation ͉ cytokines ͉ shock
Plants teem with microorganisms, whose tremendous diversity and role in plant–microbe interactions are being increasingly explored. Microbial communities create a functional bond with their hosts and express beneficial traits capable of enhancing plant performance. Therefore, a significant task of microbiome research has been identifying novel beneficial microbial traits that can contribute to crop productivity, particularly under adverse environmental conditions. However, although knowledge has exponentially accumulated in recent years, few novel methods regarding the process of designing inoculants for agriculture have been presented. A recently introduced approach is the use of synthetic microbial communities (SynComs), which involves applying concepts from both microbial ecology and genetics to design inoculants. Here, we discuss how to translate this rationale for delivering stable and effective inoculants for agriculture by tailoring SynComs with microorganisms possessing traits for robust colonization, prevalence throughout plant development and specific beneficial functions for plants. Computational methods, including machine learning and artificial intelligence, will leverage the approaches of screening and identifying beneficial microbes while improving the process of determining the best combination of microbes for a desired plant phenotype. We focus on recent advances that deepen our knowledge of plant–microbe interactions and critically discuss the prospect of using microbes to create SynComs capable of enhancing crop resiliency against stressful conditions.
The soil-plant ecosystem harbors an immense microbial diversity that challenges investigative approaches to study traits underlying plant-microbe association. Studies solely based on culture-dependent techniques have overlooked most microbial diversity. Here we describe the concomitant use of culture-dependent and -independent techniques to target plant-beneficial microbial groups from the sugarcane microbiome. The community-based culture collection (CBC) approach was used to access microbes from roots and stalks. The CBC recovered 399 unique bacteria representing 15.9% of the rhizosphere core microbiome and 61.6–65.3% of the endophytic core microbiomes of stalks. By cross-referencing the CBC (culture-dependent) with the sugarcane microbiome profile (culture-independent), we designed a synthetic community comprised of naturally occurring highly abundant bacterial groups from roots and stalks, most of which has been poorly explored so far. We then used maize as a model to probe the abundance-based synthetic inoculant. We show that when inoculated in maize plants, members of the synthetic community efficiently colonize plant organs, displace the natural microbiota and dominate at 53.9% of the rhizosphere microbial abundance. As a result, inoculated plants increased biomass by 3.4-fold as compared to uninoculated plants. The results demonstrate that abundance-based synthetic inoculants can be successfully applied to recover beneficial plant microbes from plant microbiota.
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