Search

Mitigation of greenhouse gas emissions is relevant for reducing the environmental impact of ruminant production. In this study, the rumen microbiome from Holstein cows was characterized through a combination of 16S rRNA gene and shotgun metagenomic sequencing. Methane production (CH4) and dry matter intake (DMI) were individually measured over 4–6 weeks to calculate the CH4 yield (CH4y = CH4/DMI) per cow. We implemented a combination of clustering, multivariate and mixed model analyses to identify a set of operational taxonomic unit (OTU) jointly associated with CH4y and the structure of ruminal microbial communities. Three ruminotype clusters (R1, R2 and R3) were identified, and R2 was associated with higher CH4y. The taxonomic composition on R2 had lower abundance of Succinivibrionaceae and Methanosphaera, and higher abundance of Ruminococcaceae, Christensenellaceae and Lachnospiraceae. Metagenomic data confirmed the lower abundance of Succinivibrionaceae and Methanosphaera in R2 and identified genera (Fibrobacter and unclassified Bacteroidales) not highlighted by metataxonomic analysis. In addition, the functional metagenomic analysis revealed that samples classified in cluster R2 were overrepresented by genes coding for KEGG modules associated with methanogenesis, including a significant relative abundance of the methyl‐coenzyme M reductase enzyme. Based on the cluster assignment, we applied a sparse partial least‐squares discriminant analysis at the taxonomic and functional levels. In addition, we implemented a sPLS regression model using the phenotypic variation of CH4y. By combining these two approaches, we identified 86 discriminant bacterial OTUs, notably including families linked to CH4 emission such as Succinivibrionaceae, Ruminococcaceae, Christensenellaceae, Lachnospiraceae and Rikenellaceae. These selected OTUs explained 24% of the CH4y phenotypic variance, whereas the host genome contribution was ~14%. In summary, we identified rumen microbial biomarkers associated with the methane production of dairy cows; these biomarkers could be used for targeted methane‐reduction selection programmes in the dairy cattle industry provided they are heritable. [ABSTRACT FROM AUTHOR]

The mechanism of electron transport across electroactive biofilms (EABs) is of high interest and still a matter of debate. Quantitative assessments of their redox conduction take considerable time and require non-turnover conditions (absence of substrate), which can be detrimental to EABs. Here, we measure the charge-transport parameters of Geobacter spp. dominated EABs with double potential step chronoamperometry (DPSC) with Cottrell analysis. The DPSC measurement is simpler and much faster than usual techniques and allows the determination of the charge-transport parameters even under turnover conditions. The electrochemical responses were well-described by a model of redox conduction driven only by electron diffusion within the EAB. The apparent diffusion coefficient for the electron ( Dapp) was measured as approximately 3.2×10−7 cm2 s−1, a value similar to those recorded for pure Geobacter sulfurreducens EABs, or for some redox polymers with comparable redox center concentrations. This method will be valuable for assessing the impact of EAB characteristics and environmental factors on the charge-transport ability of the biofilm, and for determining the rate-limiting step(s) for current production. [ABSTRACT FROM AUTHOR]

The Back Cover picture illustrates the discharge of an electroactive biofilm recorded by double potential step chronoamperometry, allowing the fast determination of charge‐transfer parameters across the biofilm (Artwork: A. Landi). More information can be found in the Article by A. Prévoteau and co‐workers on page 1026 in Issue 5, 2017 (DOI: 10.1002/celc.201600853). [ABSTRACT FROM AUTHOR]