The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/d64691d3-b5a9-4270-b545-796a51bb9fb9

Corbera Rubio, Francesc; Laureni, Michele; van Loosdrecht, Mark; van Halem, Doris (2024): Data underlying the publication: Meta-omics profiling of full-scale groundwater rapid sand filters explains stratification of iron, ammonium and manganese removals. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/d64691d3-b5a9-4270-b545-796a51bb9fb9.v1

Dataset

• Civil Engineering
• Ecological Applications
• Engineering
• Environmental Sciences

Ammonia, Groundwater, Iron, Manganese, Metagenomics, Metaproteomics, Sand Filtration

2021

CC BY-NC 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Francesc Corbera Rubio , Michele Laureni , Mark van Loosdrecht , Doris van Halem

We hypothesized that genetically homogeneous RSFs’ microbial communities hold the ability to rapidly modify their pool of expressed proteins to metabolically respond to the environmental conditions encountered at a given filter height. To this end, we quantified the in situ removal of iron, manganese, and ammonium, and resolved the taxonomy and function of the microbial communities along the filter height of two full-scale RSF plants, one dual-media (anthracite and sand) single filter system and one comprising two single-media sand filters in series.

The data here presented comprises the mineral content of the coating as well as the metaproteomics and metagenomics of the microbial communities.

• 2024-06-12 first online, published, posted

4TU.ResearchData

.csv and .zip (which includes fastq files)

Meta-omics profiling of full-scale groundwater rapid sand filters explains stratification of iron, ammonium and manganese removals

TU Delft, Faculty of Applied Sciences, Department of Biotechnology