Erythropoietin (EPO) is a hormone known to stimulate hematopoiesis. However, recent research suggests additional properties of EPO, such as protection against ischemia/reperfusion (I/R) injury in various tissues. We studied the effect of timing of EPO administration on cardioprotection during I/R in the heart. Male Sprague-Dawley rats were subjected to 45 minutes of coronary occlusion, followed by 24 hours of reperfusion. Animals were randomized to receive saline or single dose of EPO (5,000 IU/kg) either 2 hours before I/R, at the start of ischemia, or after the onset of reperfusion. The ratio of infarct area/area at risk (planimetry), left ventricular (LV) function (pressure development), and apoptosis (number of active caspase-3 positive cells) were determined after 24-hour reperfusion. Administration of EPO during different time points resulted in a 19 to 23% (P < 0.05) reduction in the infarct area/area at risk, which was accompanied by a trend toward better LV hemodynamic parameters. Apoptosis was significantly attenuated in groups treated with EPO at the start of ischemia (29% reduction) and after the onset of reperfusion (38%), and to a lesser extent (16%) in the group pre-treated with EPO. Thus, in vivo administration of EPO at different time points protects the myocardial structure and preserves cardiac function during I/R. Cardioprotective effect of EPO is associated with inhibition of apoptosis.

In chronic HF, treatment with ESPs is not associated with a higher mortality rate or more adverse events, whereas a beneficial effect on HF hospitalisation is seen. These outcomes are in contrast with studies in cancer and kidney disease, and support a large phase III morbidity and mortality trial of anaemia correction in patients with chronic HF.

Prokaryotes in natural environments respond rapidly to high concentrations of chemicals and physical stresses. Exposure to anthropogenic toxic substances-such as oil, chlorinated solvents, or antibiotics-favors the evolution of resistant phenotypes, some of which can use contaminants as an exclusive carbon source or as electron donors and acceptors. Microorganisms similarly adapt to extreme pH, metal, or osmotic stress. The metabolic plasticity of prokaryotes can thus be harnessed for bioremediation and can be exploited in a variety of ways, ranging from stimulated natural attenuation to bioaugmentation and from wastewater treatment to habitat restoration.

Bacteria that engage in long-standing associations with particular hosts are expected to evolve host-specific adaptations that limit their capacity to thrive in other environments. Consistent with this, many gut symbionts seem to have a limited host range, based on community profiling and phylogenomics. However, few studies have experimentally investigated host specialization of gut symbionts and the underlying mechanisms have largely remained elusive. Here, we studied host specialization of a dominant gut symbiont of social bees, Lactobacillus Firm5. We show that Firm5 strains isolated from honey bees and bumble bees separate into deep-branching host-specific phylogenetic lineages. Despite their divergent evolution, colonization experiments show that bumble bee strains are capable of colonizing the honey bee gut. However, they were less successful than honey bee strains, and competition with honey bee strains completely abolished their colonization. In contrast, honey bee strains of divergent phylogenetic lineages were able to coexist within individual bees. This suggests that both host selection and interbacterial competition play important roles in host specialization. Using comparative genomics of 27 Firm5 isolates, we found that the genomes of honey bee strains harbour more carbohydrate-related functions than bumble bee strains, possibly providing a competitive advantage in the honey bee gut. Remarkably, most of the genes encoding carbohydrate-related functions were not conserved among the honey bee strains, which suggests that honey bees can support a metabolically more diverse community of Firm5 strains than bumble bees. These findings advance our understanding of the genomic changes underlying host specialization.

The study of complex microbial communities typically entails high-throughput sequencing and downstream bioinformatics analyses. Here we expand and accelerate microbiota analysis by enabling cell type diversity quantification from multidimensional flow cytometry data using a supervised machine learning algorithm of standard cell type recognition (CellCognize). As a proof-of-concept, we trained neural networks with 32 microbial cell and bead standards. The resulting classifiers were extensively validated in silico on known microbiota, showing on average 80% prediction accuracy. Furthermore, the classifiers could detect shifts in microbial communities of unknown composition upon chemical amendment, comparable to results from 16S-rRNA-amplicon analysis. CellCognize was also able to quantify population growth and estimate total community biomass productivity, providing estimates similar to those from 14 C-substrate incorporation. CellCognize complements current sequencing-based methods by enabling rapid routine cell diversity analysis. The pipeline is suitable to optimize cell recognition for recurring microbiota types, such as in human health or engineered systems.

Soil bacteria are largely missing from future biodiversity assessments hindering comprehensive forecasts of ecosystem changes. Soil bacterial communities are expected to be more strongly driven by pH and less by other edaphic and climatic factors. Thus, alkalinisation or acidification along with climate change may influence soil bacteria, with subsequent influences for example on nutrient cycling and vegetation. Future forecasts of soil bacteria are therefore needed. We applied species distribution modelling (SDM) to quantify the roles of environmental factors in governing spatial abundance distribution of soil bacterial OTUs and to predict how future changes in these factors may change bacterial communities in a temperate mountain area. Models indicated that factors related to soil (especially pH), climate and/or topography explain and predict part of the abundance distribution of most OTUs. This supports the expectations that microorganisms have specific environmental requirements (i.e., niches/envelopes) and that they should accordingly respond to environmental changes. Our predictions indicate a stronger role of pH over other predictors (e.g. climate) in governing distributions of bacteria, yet the predicted future changes in bacteria communities are smaller than their current variation across space. The extent of bacterial community change predictions varies as a function of elevation, but in general, deviations from neutral soil pH are expected to decrease abundances and diversity of bacteria. Our findings highlight the need to account for edaphic changes, along with climate changes, in future forecasts of soil bacteria.

Interactions between plants and bacteria in the non-rhizosphere soil are rarely assessed, because they are less direct and easily masked by confounding environmental factors. By studying plant vegetation alliances and soil bacterial community co-patterning in grassland soils in 100 sites across a heterogeneous mountain landscape in the western Swiss Alps, we obtained sufficient statistical power to disentangle common co-occurrences and weaker specific interactions. Plant alliances and soil bacterial communities tended to be synchronized in community turnover across the landscape, largely driven by common underlying environmental factors, such as soil pH or elevation. Certain alliances occurring in distinct, local, environmental conditions were characterized by co-occurring specialist plant and bacterial species, such as the Nardus stricta and Thermogemmatisporaceae. In contrast, some generalist taxa, like Anthoxanthum odoratum and 19 Acidobacteria species, spanned across multiple vegetation alliances. Meta-scale analyses of soil bacterial community composition and vegetation surveys, complemented with local edaphic measurements, can thus prove useful to identify the various types of plant-bacteria interactions and the environments in which they occur.

23Bacteria that engage in longstanding associations with particular hosts are expected 24 to evolve host-specific adaptations that limit their capacity to thrive in other 25 environments. Consistent with this, many gut symbionts seem to have a limited host 26 range, based on community profiling and phylogenomics. However, few studies have 27 experimentally investigated host specialization of gut symbionts and underlying 28 mechanisms have largely remained elusive. Here, we studied host specialization of a 29 dominant gut symbiont of social bees, Lactobacillus Firm5. We show that Firm5 30 strains isolated from honey bees and bumble bees separate into deep-branching host-31 specific phylogenetic lineages. Despite their divergent evolution, colonization 32 experiments show that bumble bee strains are capable of colonizing the honey bee 33 gut. However, they were less successful than honey bee strains, and competition with 34 honey bee strains completely abolished their colonization. In contrast honey bee 35 strains of divergent phylogenetic lineages were able to coexist within individual bees. 36This suggests that both host selection and interbacterial competition play important 37 roles for host specialization. Using comparative genomics of 27 Firm5 isolates, we 38 found that the genomes of honey bee strains harbor more carbohydrate-related 39 functions than bumble bee strains, possibly providing a competitive advantage in the 40 honey bee gut. Remarkably, most of the genes encoding carbohydrate-related 41 functions were not conserved among the honey bee strains, which suggests that 42 honey bees can support a metabolically more diverse community of Firm5 strains 43 than bumble bees. These findings advance our understanding of genomic changes 44 underlying host specialization. 45