Linking community composition and ecosystem function via the cultivation-independent analysis of marker genes, e.g., the 16S rRNA gene, is a staple of microbial ecology and dependent disciplines. The certainty of results, independent of the bioinformatic handling, is imperative for any advances made within the field. In this work, thermophilic anaerobic co-digestion experimental data, together with primary and waste-activated sludge prokaryotic community data, were analyzed with two pipelines that apply different principles when dealing with technical, sequencing, and PCR biases. One pipeline (VSEARCH) employs clustering methods, generating individual operational taxonomic units (OTUs), while the other (DADA2) is based on sequencing error correction algorithms and generates exact amplicon sequence variants (ASVs). The outcomes of both pipelines were compared within the framework of ecological-driven data analysis. Both pipelines provided comparable results that would generally allow for the same interpretations. Yet, the two approaches also delivered community compositions that differed between 6.75% and 10.81% between pipelines. Inconsistencies were also observed linked to biologically driven variability in the samples, which affected the two pipelines differently. These pipeline-dependent differences in taxonomic assignment could lead to different conclusions and interfere with any downstream analysis made for such mis- or not-identified species, e.g., network analysis or predictions of their respective ecosystem service.

Anaerobic co-digestion (Co-AD) is used to increase the effectiveness of anaerobic digestion (AD) using local “wastes”, adding economic and environmental benefits. Since system stability is of existential importance for the operation of wastewater treatment plants, thorough testing of potential co-substrates and their effects on the respective community and system performance is crucial for understanding and utilizing Co-AD to its best capacity. Food waste (FW) and canola lecithin (CL) were tested in mesophilic, lab-scale, semi-continuous reactors over a duration of 120 days with stepwise increased substrate addition. Key performance indicators (biogas, total/volatile solids, fatty acids) were monitored and combined with 16S-rRNA amplicon sequencing to assess the impact of co-substrate addition on reactor performance and microbial community composition (MCC). Additionally, the latter was then compared with natural shifts occurring in the wastewater treatment plant (WWTP, source) at the same time. An almost linear increase in biogas production with both co-substrates at an approximate 1:1 ratio with the organic loading rate (OLR) was observed. The MCCs in both experiments were mostly stable, but also prone to drift over time. The FW experiment MCC more closely resembled the original WWTP community and the observed shifts indicated high levels of functional redundancy. Exclusive to the CL co-substrate, a clear selection for a few operational taxonomic units (OTUs) was observed. There was little evidence for a persistent invasion and establishment of microorganisms from typical primary substrates into the stable resident community of the reactors, which is in line with earlier findings that suggested that the inoculum and history mostly define the MCC. However, external factors may still tip the scales in favor of a few r-strategists (e.g., Prolixibacter) in an environment that otherwise favors K-strategists, which may in fact also be recruited from the primary substrate (Trichococcus). In our study, specialization and diversity loss were also observed in response to the addition of the highly specialized CL, which in turn, may have adverse effects on the system’s stability and reduced resilience and recovery.

A statistically significant decrease of oxygen enhancement ratio was found in lymphocytes of Down's syndrome (D.S.) patients, compared with

1. Sediments of aquatic ecosystems are hotspots for biological activity. Here, we address the question if, within surface sediments, oxygen consumption is linearly related to cell abundance. In addition, we identify habitat-specific factors influencing underlying microbial processes. 2. Sediment microcosms were established from three sites within oligotrophic Lake Annsj€ on, Sweden, to use microsensors for measuring oxygen profiles and estimate spatially resolved oxygen consumption rates at the water-sediment interfaces. To evaluate differences between habitats, we measured sediment carbon content and C : N : P as a proxy for diagenetic state and organic matter bioavailability. Epifluorescence microscopy was used to assess the microscale distribution and size of surface-colonising microorganisms.3. There was no linear correlation between oxygen consumption rates and microbial cell abundances. Cell-specific respiration rates were highest in the profundal compared to the littoral-and inflowsediment microcosms, whereas vertical variability in all these parameters was highest at the inflow, intermediate in the littoral and least variable in profundal sediments. 4. Illumina sequencing of spatially resolved 16SrRNA genes was used to test for possible influence of bacterial diversity on spatially resolved oxygen consumption rates. Bacterial a-diversity decreased over depth at each site, but was also lower in sediments from the most active profundal zones of the lake compared to the inflow. 5. We suggest that bacteria in profundal sediments mainly use highly oxidised organic compounds, resulting in overall low growth yield despite high metabolic activity. In the lake inflow and the littoral, more reduced organic substrates of terrestrial origin are used at lower rates but with higher yield.