Synthetic and biological surfactant effects on freshwater biofilm community composition and metabolic activity

Publication history: Accepted - 8 September 2022; Published - 19 September 2022.Surfactants are used to control microbial biofilms in industrial and medical settings. Their known toxicity on aquatic biota, and their longevity in the environment, has encouraged research on biodegradable alternatives such as rhamnolipids. While previous research has investigated the effects of biological surfactants on single species biofilms, there remains a lack of information regarding the effects of synthetic and biological surfactants in freshwater ecosystems. We conducted a mesocosm experiment to test how the surfactant sodium dodecyl sulfate (SDS) and the biological surfactant rhamnolipid altered community composition and metabolic activity of freshwater biofilms. Biofilms were cultured in the flumes using lake water from Lake Lunz in Austria, under high (300 ppm) and low (150 ppm) concentrations of either surfactant over a four-week period. Our results show that both surfactants significantly affected microbial diversity. Up to 36% of microbial operational taxonomic units were lost after surfactant exposure. Rhamnolipid exposure also increased the production of the extracellular enzymes, leucine aminopeptidase, and glucosidase, while SDS exposure reduced leucine aminopeptidase and glucosidase. This study demonstrates that exposure of freshwater biofilms to chemical and biological surfactants caused a reduction of microbial diversity and changes in biofilm metabolism, exemplified by shifts in extracellular enzyme activities.SG is funded by an Ulster University Vice Chancellors Doctoral Research Fellowship, and received additional support through an Ulster University Broadening Horizons Travel Bursary. Analytical costs were partly supported by the HYDRO-DIVERSITY project funded by the Environmental Systems Sciences Program of the Austrian Academy of Sciences (ÖAW) to JS, and core funding of the AFBI Aquatic Chemistry Laboratory (WH)

Benchmarking of cell type deconvolution pipelines for transcriptomics data

Many computational methods have been developed to infer cell type proportions from bulk transcriptomics data. However, an evaluation of the impact of data transformation, pre-processing, marker selection, cell type composition and choice of methodology on the deconvolution results is still lacking. Using five single-cell RNA-sequencing (scRNA-seq) datasets, we generate pseudo-bulk mixtures to evaluate the combined impact of these factors. Both bulk deconvolution methodologies and those that use scRNA-seq data as reference perform best when applied to data in linear scale and the choice of normalization has a dramatic impact on some, but not all methods. Overall, methods that use scRNA-seq data have comparable performance to the best performing bulk methods whereas semi-supervised approaches show higher error values. Moreover, failure to include cell types in the reference that are present in a mixture leads to substantially worse results, regardless of the previous choices. Altogether, we evaluate the combined impact of factors affecting the deconvolution task across different datasets and propose general guidelines to maximize its performance. Inferring cell type proportions from transcriptomics data is affected by data transformation, normalization, choice of method and the markers used. Here, the authors use single-cell RNAseq datasets to evaluate the impact of these factors and propose guidelines to maximise deconvolution performance

Unexpected large evasion fluxes of carbon dioxide from turbulent streams draining the world’s mountains

Inland waters, including streams and rivers, are active components of the global carbon cycle. Despite the large areal extent of the world’s mountains, the role of mountain streams for global carbon fluxes remains elusive. Using recent insights from gas exchange in turbulent streams, we found that areal CO2 evasion fluxes from mountain streams equal or exceed those reported from tropical and boreal streams, typically regarded as hotspots of aquatic carbon fluxes. At the regional scale of the Swiss Alps, we present evidence that emitted CO2 derives from lithogenic and biogenic sources within the catchment and delivered by the groundwater to the streams. At a global scale, we estimate the CO2 evasion from mountain streams to 167 ± 1.5 Tg C yr−1, which is high given their relatively low areal contribution to the global stream and river networks. Our findings shed new light on mountain streams for global carbon fluxes

Did Corporate Governance Compliance Have an Impact on Auditor Selection and Quality? Evidence From FTSE 350

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This paper examines the possible effects of corporate governance (GC) on audit quality (AQ) among the FTSE 350 companies. Using a sample of 180 companies from 2012 to 2017 (i.e., 1080 firm-year observations) a binary logistic model has been employed to investigate the CG-AQ nexus. This analysis was supported by conducting a probit logistic model as a sensitivity analysis. Our findings are associative of a heterogeneous impact of CG on AQ post the implementation of the 2012 CG reforms in the UK. For example, although institutional ownership and management ownership are positively associated with auditor selection and AQ, board independence, non-executive directors and audit committee are not attributed to AQ in the UK. This implies that corporate compliance with good CG practices has a limited impact on the decision to select a Big4 auditor in the UK. Despite the limitations of our study, we hope it can motivate further investigations in this area