EutR promotes recognition and adaptation to the intracellular environment.

<p>(<b>A-C</b>) Competition assays between Δ<i>eutR</i>::Cm^R (CJA007) and Δ<i>eutB</i> (CJA020) strains collected from (<b>A</b>) harvested spleens, (<b>B</b>) the peritoneal cavity, or (<b>C</b>) phagocytized cells at 6 h pi. Mice were intraperitoneally infected with 1:1 mixtures of the Δ<i>eutR</i> and Δ<i>eutB</i> strains. Each column represents a CI. Each column shows the geometric mean value ± SE for each group (n = 2 litters (6–8 animals)). *, <i>P</i> ≤ 0.05; **, <i>P</i> ≤ 0.005; ***, <i>P</i> ≤ 0.0005; <i>P</i> > 0.05 = ns.</p

Ethanolamine Signaling Promotes <i>Salmonella</i> Niche Recognition and Adaptation during Infection

<div><p>Chemical and nutrient signaling are fundamental for all cellular processes, including interactions between the mammalian host and the microbiota, which have a significant impact on health and disease. Ethanolamine is an essential component of cell membranes and has profound signaling activity within mammalian cells by modulating inflammatory responses and intestinal physiology. Here, we describe a virulence-regulating pathway in which the foodborne pathogen <i>Salmonella enterica</i> serovar Typhimurium (<i>S</i>. Typhimurium) exploits ethanolamine signaling to recognize and adapt to distinct niches within the host. The bacterial transcription factor EutR promotes ethanolamine metabolism in the intestine, which enables <i>S</i>. Typhimurium to establish infection. Subsequently, EutR directly activates expression of the <i>Salmonella</i> pathogenicity island 2 in the intramacrophage environment, and thus augments intramacrophage survival. Moreover, EutR is critical for robust dissemination during mammalian infection. Our findings reveal that <i>S</i>. Typhimurium co-opts ethanolamine as a signal to coordinate metabolism and then virulence. Because the ability to sense ethanolamine is a conserved trait among pathogenic and commensal bacteria, our work indicates that ethanolamine signaling may be a key step in the localized adaptation of bacteria within their mammalian hosts.</p></div

Percent difference in (A) annual precipitation; (B) PET averaged by land use categories in switchgrass altered regions in Kansas and Oklahoma as shown in <b>Figure 1</b>.

<p>Box top and bottom edges are the interquartile range of percent difference for each year, and whiskers are maximum and minimum annual values. X-axis labels are land use categories: No Change (NC), Switchgrass/Grassland (S/G), Switchgrass/Cropland (S/C), Grassland/Switchgrass (G/S), Cropland/Switchgrass (C/S), and average over all categories (Avg).</p

Change in mean annual precipitation and potential evapotranspiration for 1981–2004 expressed in A) percentage change in mean annual precipitation; B) change in mean annual precipitation (millimeters); C) percentage change in mean annual PET; and D) change in PET (millimeters) under the biofuel scenario.

<p>Percent change under the biofuel scenario relative to the baseline scenario for a given location is estimated as the mean of: where x is either P or PET and i is year between 1981 and 2004.</p

Default land use categories in the WRF model (A); new land use categories defined for the biofuel scenario (B); and fraction of land use that is switchgrass in the biofuel scenario (C).

<p>Default land use categories in the WRF model (A); new land use categories defined for the biofuel scenario (B); and fraction of land use that is switchgrass in the biofuel scenario (C).</p

Effect of ethanolamine and EutR on SPI-1.

<p>(<b>A</b>) qRT-PCR of <i>sipC</i> from WT <i>S</i>. Typhimurium (SL1344) grown in LB or LB supplemented with 5 mM ethanolamine (EA). (<b>B</b>) qRT-PCR of <i>sipC</i> from WT <i>S</i>. Typhimurium (SL1344) grown in DMEM or DMEM supplemented with ethanolamine (EA) as indicated. For (<b>A</b>) and (<b>B</b>), n = 3; error bars represent the geometric mean ± SD. Statistical significance is shown relative to cells grown without EA supplementation; <i>strB</i> was used as the endogenous control. (<b>C</b>) Invasion of HeLa cells by WT (SL1344) and the Δ<i>eutR</i> (CJA009) strains. Mean ± SE of nine independent experiments. (<b>D</b>) Invasion of HeLa cells by WT (SL1344) and the Δ<i>eutR</i> (CJA009) strains. Mean ± SE of six independent experiments with supplementation of 5 mM EA. **, <i>P</i> ≤ 0.005; <i>P</i> > 0.05 = ns.</p

EutR in pathogen-microbiota-host interactions.

<p>(<b>A</b>) Schematic of the <i>eut</i> operon. (<b>B</b>) <i>In vitro</i> growth curve of S. Typhimurium WT (SL1344), Δ<i>eutR</i> (CJA009), or Δ<i>eutB</i> (CJA020) strains in LB without or with supplementation of 5 mM ethanolamine (EA). Each data point shows the average of three independent experiments. (<b>C</b>) qRT-PCR of <i>eutR</i> in WT or the Δ<i>eutB</i> (CJA020) <i>S</i>. Typhimurium strains grown in Dulbecco’s Modified Eagle Medium (DMEM) or DMEM supplemented with 5 mM EA. n = 3; error bars represent the geometric mean ± standard deviation (SD); <i>strB</i> was used as the endogenous control. (<b>D-F</b>) Competition assays between (<b>D</b>) Δ<i>eutB</i>::Cm^R (CJA018) and WT strains; (<b>E</b>) Δ<i>eutR</i>::Cm^R (CJA007) and WT strains; or (<b>F</b>) Δ<i>eutR</i>::Cm^R (CJA007) and Δ<i>eutB</i> (CJA020) strains. Mice were orogastrically inoculated with 1:1 mixtures of indicated strains. Colony forming units (cfu) were determined at indicated time points. Each bar represents a competition index (CI). Horizontal lines represent the geometric mean value ± standard error (SE) for each group (n = 2 litters (6–8 animals)). *, <i>P</i> ≤0.05; **, <i>P</i> ≤ 0.005; ***, <i>P</i> ≤0.0005; <i>P</i> > 0.05 = ns.</p

Hydro-climatology of the conterminous US; (A) Precipitation elasticity of streamflow (ε_p) and (B) Evapotranspiration elasticity of streamflow (ε_pet).

<p>Hydro-climatology of the conterminous US; (A) Precipitation elasticity of streamflow (ε_p) and (B) Evapotranspiration elasticity of streamflow (ε_pet).</p

Streamflow Impacts of Biofuel Policy-Driven Landscape Change

<div><p>Likely changes in precipitation (P) and potential evapotranspiration (PET) resulting from policy-driven expansion of bioenergy crops in the United States are shown to create significant changes in streamflow volumes and increase water stress in the High Plains. Regional climate simulations for current and biofuel cropping system scenarios are evaluated using the same atmospheric forcing data over the period 1979–2004 using the Weather Research Forecast (WRF) model coupled to the NOAH land surface model. PET is projected to increase under the biofuel crop production scenario. The magnitude of the mean annual increase in PET is larger than the inter-annual variability of change in PET, indicating that PET increase is a forced response to the biofuel cropping system land use. Across the conterminous U.S., the change in mean streamflow volume under the biofuel scenario is estimated to range from negative 56% to positive 20% relative to a business-as-usual baseline scenario. In Kansas and Oklahoma, annual streamflow volume is reduced by an average of 20%, and this reduction in streamflow volume is due primarily to increased PET. Predicted increase in mean annual P under the biofuel crop production scenario is lower than its inter-annual variability, indicating that additional simulations would be necessary to determine conclusively whether predicted change in P is a response to biofuel crop production. Although estimated changes in streamflow volume include the influence of P change, sensitivity results show that PET change is the significantly dominant factor causing streamflow change. Higher PET and lower streamflow due to biofuel feedstock production are likely to increase water stress in the High Plains. When pursuing sustainable biofuels policy, decision-makers should consider the impacts of feedstock production on water scarcity.</p></div

EutR in <i>S</i>. Typhimurium niche adaptation.

<p>(<b>A</b>) EutR senses ethanolamine to activate transcription. (<b>B</b>) In the intestine, EutR promotes expression of the <i>eut</i> operon that encodes ethanolamine metabolism, thereby enhancing <i>S</i>. Typhimurium growth. (<b>C</b>) EutR expression in macrophages activates expression of genes in SPI-2, which are required for intramacrophage survival and dissemination.</p