| 1. |
- Murphy, Eileen F., et al.
(författare)
-
Divergent metabolic outcomes arising from targeted manipulation of the gut microbiota in diet-induced obesity
- 2013
-
Ingår i: Gut. - : BMJ Publishing Group Ltd. - 0017-5749 .- 1468-3288. ; 62:2, s. 220-226
-
Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: The gut microbiota is an environmental regulator of fat storage and adiposity. Whether the microbiota represents a realistic therapeutic target for improving metabolic health is unclear. This study explored two antimicrobial strategies for their impact on metabolic abnormalities in murine diet-induced obesity: oral vancomycin and a bacteriocin-producing probiotic (Lactobacillus salivarius UCC118 Bac(+)).DESIGN: Male (7-week-old) C57BL/J6 mice (9-10/group) were fed a low-fat (lean) or a high-fat diet for 20 weeks with/without vancomycin by gavage at 2 mg/day, or with L. salivarius UCC118Bac(+) or the bacteriocin-negative derivative L. salivarius UCC118Bac(-) (each at a dose of 1×10(9) cfu/day by gavage). Compositional analysis of the microbiota was by 16S rDNA amplicon pyrosequencing.RESULTS: Analysis of the gut microbiota showed that vancomycin treatment led to significant reductions in the proportions of Firmicutes and Bacteroidetes and a dramatic increase in Proteobacteria, with no change in Actinobacteria. Vancomycin-treated high-fat-fed mice gained less weight over the intervention period despite similar caloric intake, and had lower fasting blood glucose, plasma TNFα and triglyceride levels compared with diet-induced obese controls. The bacteriocin-producing probiotic had no significant impact on the proportions of Firmicutes but resulted in a relative increase in Bacteroidetes and Proteobacteria and a decrease in Actinobacteria compared with the non-bacteriocin-producing control. No improvement in metabolic profiles was observed in probiotic-fed diet-induced obese mice.CONCLUSION: Both vancomycin and the bacteriocin-producing probiotic altered the gut microbiota in diet-induced obese mice, but in distinct ways. Only vancomycin treatment resulted in an improvement in the metabolic abnormalities associated with obesity thereby establishing that while the gut microbiota is a realistic therapeutic target, the specificity of the antimicrobial agent employed is critical.
|
|
| 2. |
- Saunois, Marielle, et al.
(författare)
-
The Global Methane Budget 2000–2017
- 2020
-
Ingår i: Earth System Science Data. - : Copernicus GmbH. - 1866-3516 .- 1866-3508. ; 12:3, s. 1561-1623
-
Tidskriftsartikel (refereegranskat)abstract
- Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations).For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters.Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning.The data presented here can be downloaded from https://doi.org/10.18160/GCP-CH4-2019 (Saunois et al., 2020) and from the Global Carbon Project.
|
|
| 3. |
- Murphy, Eileen F., et al.
(författare)
-
Antimicrobials : Strategies for targeting obesity and metabolic health?
- 2013
-
Ingår i: Gut microbes. - : Landes Bioscience. - 1949-0976 .- 1949-0984. ; 4:1, s. 48-53
-
Tidskriftsartikel (refereegranskat)abstract
- Obesity is associated with a number of serious health consequences, including type 2 diabetes, cardiovascular disease and a variety of cancers among others and has been repeatedly shown to be associated with a higher risk of mortality. The relatively recent discovery that the composition and metabolic activity of the gut microbiota may affect the risk of developing obesity and related disorders has led to an explosion of interest in this distinct research field. A corollary of these findings would suggest that modulation of gut microbial populations can have beneficial effects with respect to controlling obesity. In this addendum, we summarize our recent data, showing that therapeutic manipulation of the microbiota using different antimicrobial strategies may be a useful approach for the management of obesity and metabolic conditions. In addition, we will explore some of the mechanisms that may contribute to microbiota-induced susceptibility to obesity and metabolic diseases.
|
|
