RESUMO

A multiphase study was proposed to examine microbial communities linked to the nitrogen cycle in the first stage of four full-scale French vertical flow treatment systems. To this end, denaturing gradient gel electrophoresis (DGGE) was performed for structural assessment and quantitative PCR (qPCR) to enumerate the abundance of ammonia-oxidizing (AOB). 16S rRNA sequencing was used to assess the taxonomic profile followed by putative assessment of functional genes. The samples were collected under different conditions, such as operational time (presence/absence of sludge layer on the surface of the filters), season (winter and summer), sampling depth (0, 15 and 30 cm) and operation cycle (rest and feed periods). A structural disparity was noted in the upper layers, whereas higher similarity at 30 cm was observed highlighting the effect of organic matter on bacterial diversity. The 7th rest day was highlighted by an apparent decline in the microbial community abundance. Additionally, qPCR indicated that the largest amount of AOB was found at 30 cm depth and during the feeding period. From the taxonomic profile, Mycobacterium, Acinetobacter, Flavobacterium, and Nitrospira were the most abundant genre found in all systems. The functional prediction results showed predicted genes linked to the denitrification process. The results suggested that operating time and season were responsible for the pattern of the microbial community behavior. This study allowed us to further understand the bacterial dynamics and to advance the idea of design modifications made in the first stage of the classical French system to improve nitrogen removal are promising.

Assuntos

Microbiota , Áreas Alagadas , Amônia , Microbiota/genética , Nitrogênio , RNA Ribossômico 16S/genética , Águas Residuárias

RESUMO

Data generated by metagenomic and metatranscriptomic experiments is both enormous and inherently noisy. When using taxonomy-dependent alignment-based methods to classify and label reads, the first step consists in performing homology searches against sequence databases. To obtain the most information from the samples, nucleotide sequences are usually compared to various databases (nucleotide and protein) using local sequence aligners such as BLASTN and BLASTX. Nevertheless, the analysis and integration of these results can be problematic because the outputs from these searches usually show inconsistencies, which can be notorious when working with RNA-seq. Moreover, and to the best of our knowledge, existing tools do not criss-cross and integrate information from the different homology searches, but provide the results of each analysis separately. We developed the HoSeIn workflow to intersect the information from these homology searches, and then determine the taxonomic and functional profile of the sample using this integrated information. The workflow is based on the assumption that the sequences that correspond to a certain taxon are composed of: sequences that were assigned to the same taxon by both homology searches; sequences that were assigned to that taxon by one of the homology searches but returned no hits in the other one.