Cross-Modal Imaging Reveals Nanoparticle Uptake Dynamics in Hematopoietic Bone Marrow during Inflammation.

Nanoparticles have been employed to elucidate the innate immune cell biology and trace cells accumulating at inflammation sites. Inflammation prompts innate immune cells, the initial responders, to undergo rapid turnover and replenishment within the hematopoietic bone marrow. Yet, we currently lack a precise understanding of how inflammation affects cellular nanoparticle uptake at the level of progenitors of innate immune cells in the hematopoietic marrow. To bridge this gap, we aimed to develop imaging tools to explore the uptake dynamics of fluorescently labeled cross-linked iron oxide nanoparticles in the bone marrow niche under varying degrees of inflammation. The inflammatory models included mice that received intramuscular lipopolysaccharide injections to induce moderate inflammation and streptozotocin-induced diabetic mice with additional intramuscular lipopolysaccharide injections to intensify inflammation. In vivo magnetic resonance imaging (MRI) and fluorescence imaging revealed an elevated level of nanoparticle uptake at the bone marrow as the levels of inflammation increased. The heightened uptake of nanoparticles within the inflamed marrow was attributed to enhanced permeability and retention with increased nanoparticle intake by hematopoietic progenitor cells. Moreover, intravital microscopy showed increased colocalization of nanoparticles within slowly patrolling monocytes in these inflamed hematopoietic marrow niches. Our discoveries unveil a previously unknown role of the inflamed hematopoietic marrow in enhanced storage and rapid deployment of nanoparticles, which can specifically target innate immune cells at their production site during inflammation. These insights underscore the critical function of the hematopoietic bone marrow in distributing iron nanoparticles to innate immune cells during inflammation. Our findings offer diagnostic and prognostic value, identifying the hematopoietic bone marrow as an imaging biomarker for early detection in inflammation imaging, advancing personalized clinical care.

Functional analysis of the apple fruit microbiome based on shotgun metagenomic sequencing of conventional and organic orchard samples.

Fruits harbour abundant and diverse microbial communities that protect them from post-harvest pathogens. Identification of functional traits associated with a given microbiota can provide a better understanding of their potential influence. Here, we focused on the epiphytic microbiome of apple fruit. We suggest that shotgun metagenomic data can indicate specific functions carried out by different groups and provide information on their potential impact. Samples were collected from the surface of 'Golden Delicious' apples from four orchards that differ in their geographic location and management practice. Approximately 1 million metagenes were predicted based on a high-quality assembly. Functional profiling of the microbiome of fruits from orchards differing in their management practice revealed a functional shift in the microbiota. The organic orchard microbiome was enriched in pathways involved in plant defence activities; the conventional orchard microbiome was enriched in pathways related to the synthesis of antibiotics. The functional significance of the variations was explored using microbial network modelling algorithms to reveal the metabolic role of specific phylogenetic groups. The analysis identified several associations supported by other published studies. For example, the analysis revealed the nutritional dependencies of the Capnodiales group, including the Alternaria pathogen, on aromatic compounds.

A framework for the targeted recruitment of crop-beneficial soil taxa based on network analysis of metagenomics data.

BACKGROUND: The design of ecologically sustainable and plant-beneficial soil systems is a key goal in actively manipulating root-associated microbiomes. Community engineering efforts commonly seek to harness the potential of the indigenous microbiome through substrate-mediated recruitment of beneficial members. In most sustainable practices, microbial recruitment mechanisms rely on the application of complex organic mixtures where the resources/metabolites that act as direct stimulants of beneficial groups are not characterized. Outcomes of such indirect amendments are unpredictable regarding engineering the microbiome and achieving a plant-beneficial environment. RESULTS: This study applied network analysis of metagenomics data to explore amendment-derived transformations in the soil microbiome, which lead to the suppression of pathogens affecting apple root systems. Shotgun metagenomic analysis was conducted with data from 'sick' vs 'healthy/recovered' rhizosphere soil microbiomes. The data was then converted into community-level metabolic networks. Simulations examined the functional contribution of treatment-associated taxonomic groups and linked them with specific amendment-induced metabolites. This analysis enabled the selection of specific metabolites that were predicted to amplify or diminish the abundance of targeted microbes functional in the healthy soil system. Many of these predictions were corroborated by experimental evidence from the literature. The potential of two of these metabolites (dopamine and vitamin B12) to either stimulate or suppress targeted microbial groups was evaluated in a follow-up set of soil microcosm experiments. The results corroborated the stimulant's potential (but not the suppressor) to act as a modulator of plant beneficial bacteria, paving the way for future development of knowledge-based (rather than trial and error) metabolic-defined amendments. Our pipeline for generating predictions for the selective targeting of microbial groups based on processing assembled and annotated metagenomics data is available at https://github.com/ot483/NetCom2 . CONCLUSIONS: This research demonstrates how genomic-based algorithms can be used to formulate testable hypotheses for strategically engineering the rhizosphere microbiome by identifying specific compounds, which may act as selective modulators of microbial communities. Applying this framework to reduce unpredictable elements in amendment-based solutions promotes the development of ecologically-sound methods for re-establishing a functional microbiome in agro and other ecosystems. Video Abstract.