The impact of whey protein consumption and exercise on the composition and diversity of the gut microbiota: a high through-put DNA sequencing approach

Advances in culture independent technologies over the last decade have highlighted the pivotal role which the gut microbiota plays in maintaining human health. Conversely, perturbations to the composition or actions of the ‘normal/functioning’ microbiota have been frequently associated with the pathogenesis of several disease states. Therefore the selective modulation of enteric microbial communities represents a viable target for the development of novel treatments for such diseases. Notably, while bovine whey proteins and exercise have been shown to positively influence several physiological processes, such as energy balance, their effect on the composition or functionality of the gut microbiota remains largely unknown. In this thesis, a variety of ex vivo, murine and human models are used in conjunction with high-throughput DNA sequencing-based analysis to provide valuable and novel insights into the impact of both whey proteins and exercise on enteric microbial communities. Overall the results presented in this thesis highlight that the consumption both whey protein isolate (WPI), and individual component proteins of whey such as bovine serum albumin (BSA) and lactoferrin, reduce high fat diet associated body weight gain and are associated with beneficial alterations within the murine gut microbiota. Although the impact of exercise on enteric microbial communities remains less clear, it may be that longer term investigations are required for the true effect of exercise on the gut microbiota to be fully elucidated.

Single particle diversity and mixing state measurements

A newly developed framework for quantifying aerosol particle diversity and mixing state based on information-theoretic entropy is applied for the first time to single particle mass spectrometry field data. Single particle mass fraction estimates for black carbon, organic aerosol, ammonium, nitrate and sulfate, derived using single particle mass spectrometer, aerosol mass spectrometer and multi-angle absorption photometer measurements are used to calculate single particle species diversity (Di). The average single particle species diversity (Dα) is then related to the species diversity of the bulk population (Dγ) to derive a mixing state index value (χ) at hourly resolution. The mixing state index is a single parameter representation of how internally/externally mixed a particle population is at a given time. The index describes a continuum, with values of 0 and 100% representing fully external and internal mixing, respectively. This framework was applied to data collected as part of the MEGAPOLI winter campaign in Paris, France, 2010. Di values are low (∼ 2) for fresh traffic and wood-burning particles that contain high mass fractions of black carbon and organic aerosol but low mass fractions of inorganic ions. Conversely, Di values are higher (∼ 4) for aged carbonaceous particles containing similar mass fractions of black carbon, organic aerosol, ammonium, nitrate and sulfate. Aerosol in Paris is estimated to be 59% internally mixed in the size range 150-1067 nm, and mixing state is dependent both upon time of day and air mass origin. Daytime primary emissions associated with vehicular traffic and wood-burning result in low χ values, while enhanced condensation of ammonium nitrate on existing particles at night leads to higher χ values. Advection of particles from continental Europe containing ammonium, nitrate and sulfate leads to increases in Dα, Dγ and χ. The mixing state index represents a useful metric by which to compare and contrast ambient particle mixing state at other locations globally.