A metatranscriptomics‐based assessment of small‐scale mixing of sulfidic and oxic waters on redoxcline prokaryotic communities

Abstract

Summary Lateral intrusions of oxygen caused by small‐scale mixing are thought to shape microbial activity in marine redoxclines. To examine the response of prokaryotes to such mixing events we employed a shipboard mixing experiment in the euxinic central Baltic Sea: oxic, nitrate containing and sulfidic water samples without detectable oxygenized substances were incubated directly or after mixing. While nitrate, nitrite and ammonium concentrations stayed approximately constant in all incubations, we observed a decrease of sulfide after the contact with oxygen in the sulfide containing incubations. The transcription of marker genes from chemolithoauthotrophic key players including archaeal nitrifiers as well as gammaproteobacterial and campylobacterial autotrophic organisms that couple denitrification with sulfur‐oxidation were followed at four time points within 8.5 h. The temporally contrasting transcriptional profiles of gammaproteobacterial and campylobacterial denitrifiers that depend on the same inorganic substrates pointed to a niche separation. Particular archaeal and campylobacterial marker genes involved in nitrification, denitrification and sulfur oxidation, which depend on oxidized substrates, were highly upregulated in the anaerobic sulfidic samples. We suggest that, despite the absence of measurable oxygenated compounds in the sulfidic water, frequent intermittent small‐scale intrusions stimulate the permanent upregulation of genes involved in nitrification, denitrification and sulfur oxidation.

Interleaving of oxygenized intrusions into the Baltic Sea redoxcline

“…In this view, the enhanced turbidities are interpreted as the optical signature of colloidal sulfur particles generated during the mixing of oxic and sulfidic waters (Schmale et al ; Holtermann et al ), similar to the classical redoxcline turbidity peak found in the Baltic Sea and other euxinic systems (Blumenberg et al ; Wakeham et al ; Jakobs et al ). This is consistent with a recent study of Beier et al (), who investigated the microbiological consequences of permanent small‐scale intrusions into the anoxic deep layers of the Gotland Basin. These authors describe an unexpected upregulation of oxygen‐dependent genes in regions where neither oxygen nor oxygenated compounds such as nitrate and nitrite could be detected.…”

“…These authors describe an unexpected upregulation of oxygen‐dependent genes in regions where neither oxygen nor oxygenated compounds such as nitrate and nitrite could be detected. Beier et al () argue that the most likely explanation for the puzzling transcription of denitrifying and sulfur oxidizing genes in the anoxic/sulfidic region below the HTZ is a permanent stimulation by intrusions.…”

Bacteroidetal cold-active and promiscuous esterases play a significant role in global polyethylene terephthalate (PET) degradation

“…Bioinformatic analyses followed previously published protocols 67 except that metatranscriptome reads were mapped onto the BARM metagenome 41 with very sensitive settings. The recovery rate of the internal standard molecules in the sequencing data reads was used to calculate the absolute number of transcripts that were in the respective water samples 68,69 . The above described HMM search was used to identify potential bacteroidetal PETase genes in the BARM metagenome and compared to those which showed expression in the Baltic Sea metatranscriptome data set.…”

Resource Partitioning Between Phytoplankton and Bacteria in the Coastal Baltic Sea

“…Differential expression analyses were made for both the PE and BAC metatranscriptome data using the DESeq2 (Love et al, 2014) package in R (version 3.4.4), with the internal standards (controlGenes) in the estimateSizeFactors function to normalize counts between samples ( Supplementary Table 3) (Beier et al, 2018). Transcriptional changes of enzymes refer to relative log2 fold changes between contrasted timepoints (including triplicates), at an adjusted p < 0.01, unless otherwise stated ( Supplementary Tables 5, 7).…”

“…Bacterial absolute transcript counts per mL (grouped by SEED Rank3), calculated according to formula in Satinsky et al (2013) can be found in Supplementary Table 6. To account for transcript length, counts were normalized to one mRNA standard at a time: pTZ19R (546nt), pFN19R (970nt) from which the mean was calculated (Beier et al, 2018), and then log2 transformed. Bacterial absolute transcript counts per mL (grouped by SEED Rank3), with standard errors (SE), calculated according to formula in Satinsky et al (2013) can be found in Supplementary Table 6.…”