Potential of novel dextran oligosaccharides as prebiotics for obesity management through in vitro experimentation.

The energy-salvaging capacity of the gut microbiota from dietary ingredients has been proposed as a contributing factor for the development of obesity. This knowledge generated interest in the use of non-digestible dietary ingredients such as prebiotics to manipulate host energy homeostasis. In the present study, the in vitro response of obese human faecal microbiota to novel oligosaccharides was investigated. Dextrans of various molecular weights and degrees of branching were fermented with the faecal microbiota of healthy obese adults in pH-controlled batch cultures. Changes in bacterial populations were monitored using fluorescent in situ hybridisation and SCFA concentrations were analysed by HPLC. The rate of gas production and total volume of gas produced were also determined. In general, the novel dextrans and inulin increased the counts of bifidobacteria. Some of the dextrans were able to alter the composition of the obese human microbiota by increasing the counts of Bacteroides–Prevotella and decreasing those of Faecalibacterium prausnitzii and Ruminococcus bromii/R. flavefaciens. Considerable increases in SCFA concentrations were observed in response to all substrates. Gas production rates were similar during the fermentation of all dextrans, but significantly lower than those during the fermentation of inulin. Lower total gas production and shorter time to attain maximal gas production were observed during the fermentation of the linear 1 kDa dextran than during the fermentation of the other dextrans. The efficacy of bifidobacteria to ferment dextrans relied on the molecular weight and not on the degree of branching. In conclusion, there are no differences in the profiles between the obese and lean human faecal fermentations of dextrans.

Effects of agricultural management practices on earthworm populations and crop yield: validation and application of a mechanistic modelling approach

There is little consensus on how agriculture will meet future food demands sustainably. Soils and their biota play a crucial role by mediating ecosystem services that support agricultural productivity. However, a multitude of site-specific environmental factors and management practices interact to affect the ability of soil biota to perform vital functions, confounding the interpretation of results from experimental approaches. Insights can be gained through models, which integrate the physiological, biological and ecological mechanisms underpinning soil functions. We present a powerful modelling approach for predicting how agricultural management practices (pesticide applications and tillage) affect soil functioning through earthworm populations. By combining energy budgets and individual-based simulation models, and integrating key behavioural and ecological drivers, we accurately predict population responses to pesticide applications in different climatic conditions. We use the model to analyse the ecological consequences of different weed management practices. Our results demonstrate that an important link between agricultural management (herbicide applications and zero, reduced and conventional tillage) and earthworms is the maintenance of soil organic matter (SOM). We show how zero and reduced tillage practices can increase crop yields while preserving natural ecosystem functions. This demonstrates how management practices which aim to sustain agricultural productivity should account for their effects on earthworm populations, as their proliferation stimulates agricultural productivity. Synthesis and applications. Our results indicate that conventional tillage practices have longer term effects on soil biota than pesticide control, if the pesticide has a short dissipation time. The risk of earthworm populations becoming exposed to toxic pesticides will be reduced under dry soil conditions. Similarly, an increase in soil organic matter could increase the recovery rate of earthworm populations. However, effects are not necessarily additive and the impact of different management practices on earthworms depends on their timing and the prevailing environmental conditions. Our model can be used to determine which combinations of crop management practices and climatic conditions pose least overall risk to earthworm populations. Linking our model mechanistically to crop yield models would aid the optimization of crop management systems by exploring the trade-off between different ecosystem services.