Microbial translocation and its clinical significance

This research article investigates the clinical significance of MT in humans in relation to its significance in contribution to several disease states.The literature was searched in PubMed Medline National Library of Medicine from 1990 to 2016 were used. The following words were used: ‘microbial translocation’ and ‘clinical significance,’ or ‘biomarkers,’ or ‘toll-like receptor,’ or ‘pathogen-associated molecular pattern.’ We found 3,300 published manuscripts using the above search. Of 3,300 manuscripts, we dropped 2087 and 723 manuscripts either they did not suit this review or were not in English; 490 manuscripts were selected for this review. From the literature, there is evidence that microbial translocation occurs in both animals and humans, but unlike in animals, its clinical significance remains questionable in humans. This could partly be explained by the current lack of a single acceptable sensitive and accurate biomarker to detect microbial translocation. Additionally, the extent to which microbial translocation in animals can be demonstrated cannot apply to humans for the sake of research without an underlying disease. In humans microbial translocation is associated with many conditions and microbial products may lead to systemic inflammation and immune activation. Although some of the microbial products or Pathogen-Associated Molecular Patterns (PAMPs) have been studied, their clinical importance is not well established, and the assays developed to measure PAMPs in blood have not been developed or validated for clinical use. However, a few molecules of microbial origin have been used as biomarkers of microbial translocation in many disease conditions. The innate immune system detects all PAMPs through cells such as macrophages, dendritic cells, and monocytes. Detection of PAMPs through pathogen recognition receptors such as Toll like receptors which result in the activation of the transcription factors, NK-κB, resulting in the production of pro-inflammatory cytokines. We provide a synthesis of the current understanding of the nature of microbial translocation, PAMP-receptor interaction and the health significance of microbial translocation in humans.Office of Global AIDS/US Department of Sat

Biogeographical survey of soil microbiomes across sub-Saharan Africa:structure, drivers, and predicted climate-driven changes

BACKGROUND: Top-soil microbiomes make a vital contribution to the Earth’s ecology and harbor an extraordinarily high biodiversity. They are also key players in many ecosystem services, particularly in arid regions of the globe such as the African continent. While several recent studies have documented patterns in global soil microbial ecology, these are largely biased towards widely studied regions and rely on models to interpolate the microbial diversity of other regions where there is low data coverage. This is the case for sub-Saharan Africa, where the number of regional microbial studies is very low in comparison to other continents. RESULTS: The aim of this study was to conduct an extensive biogeographical survey of sub-Saharan Africa’s top-soil microbiomes, with a specific focus on investigating the environmental drivers of microbial ecology across the region. In this study, we sampled 810 sample sites across 9 sub-Saharan African countries and used taxonomic barcoding to profile the microbial ecology of these regions. Our results showed that the sub-Saharan nations included in the study harbor qualitatively distinguishable soil microbiomes. In addition, using soil chemistry and climatic data extracted from the same sites, we demonstrated that the top-soil microbiome is shaped by a broad range of environmental factors, most notably pH, precipitation, and temperature. Through the use of structural equation modeling, we also developed a model to predict how soil microbial biodiversity in sub-Saharan Africa might be affected by future climate change scenarios. This model predicted that the soil microbial biodiversity of countries such as Kenya will be negatively affected by increased temperatures and decreased precipitation, while the fungal biodiversity of Benin will benefit from the increase in annual precipitation. CONCLUSION: This study represents the most extensive biogeographical survey of sub-Saharan top-soil microbiomes to date. Importantly, this study has allowed us to identify countries in sub-Saharan Africa that might be particularly vulnerable to losses in soil microbial ecology and productivity due to climate change. Considering the reliance of many economies in the region on rain-fed agriculture, this study provides crucial information to support conservation efforts in the countries that will be most heavily impacted by climate change. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-022-01297-w

Additional file 7 of Biogeographical survey of soil microbiomes across sub-Saharan Africa: structure, drivers, and predicted climate-driven changes

Additional file 7. Figure S7. MIROC6 model predictions for mean annual temperature (oC) (A) and mean annual precipitation (mm) (B) under too different GH emission scenarios (SSP126 and SSP585), predicted for 2040-2060 and 2080-2100 temporal windows. The predicted datasets are grouped according to country, as indicated by the vertical dashed lines

Additional file 7 of Biogeographical survey of soil microbiomes across sub-Saharan Africa: structure, drivers, and predicted climate-driven changes

Additional file 7. Figure S7. MIROC6 model predictions for mean annual temperature (oC) (A) and mean annual precipitation (mm) (B) under too different GH emission scenarios (SSP126 and SSP585), predicted for 2040-2060 and 2080-2100 temporal windows. The predicted datasets are grouped according to country, as indicated by the vertical dashed lines

Additional file 8 of Biogeographical survey of soil microbiomes across sub-Saharan Africa: structure, drivers, and predicted climate-driven changes

Additional file 8. Figure S8-A. Predicted prokaryotic Shannon biodiversity index values (expressed as natural log scale) in soils of the 9 sub-Saharan Africa countries used in this study, for 2040-2060 and 2080-2100 under two distinct GH emission scenarios (SSP126 and SSP585), and comparison with current predicted Shannon biodiversity as estimated by SEM. Pairwise significance values of differences in biodiversity means between the different years and scenarios are represented by the brackets with the following nomenclature: * - p-value \u3c 0.05; ** - p-value \u3c 0.01; *** - p-value \u3c 0.001

Additional file 18 of Biogeographical survey of soil microbiomes across sub-Saharan Africa: structure, drivers, and predicted climate-driven changes

Additional file 18. Table S7. Number of samples allocated for each country, and number of samples collected

Additional file 19 of Biogeographical survey of soil microbiomes across sub-Saharan Africa: structure, drivers, and predicted climate-driven changes

Additional file 19. Table S8. Variable codes, meaning and units for the environmental variables used in this study

Additional file 17 of Biogeographical survey of soil microbiomes across sub-Saharan Africa: structure, drivers, and predicted climate-driven changes

Additional file 17. Table S6. Net estimates and corresponding significance values for the environmental variables associated with soil health in the SEM model

Additional file 18 of Biogeographical survey of soil microbiomes across sub-Saharan Africa: structure, drivers, and predicted climate-driven changes

Additional file 18. Table S7. Number of samples allocated for each country, and number of samples collected