Evaluation of denitrification performance and bacterial community of a sequencing batch reactor under intermittent aeration

Identifying local associations in biological time series: algorithms, statistical significance, and applications

Local associations refer to spatial-temporal correlations that emerge from the biological realm, such as time-dependent gene co-expression or seasonal interactions between microbes. One can reveal the intricate dynamics and inherent interactions of biological systems by examining the biological time series data for these associations. To accomplish this goal, local similarity analysis algorithms and statistical methods that facilitate the local alignment of time series and assess the significance of the resulting alignments have been developed. Although these algorithms were initially devised for gene expression analysis from microarrays, they have been adapted and accelerated for multi-omics next generation sequencing datasets, achieving high scientific impact. In this review, we present an overview of the historical developments and recent advances for local similarity analysis algorithms, their statistical properties, and real applications in analyzing biological time series data. The benchmark data and analysis scripts used in this review are freely available at http://github.com/labxscut/lsareview.

Heterogeneous selection dominated the temporal variation of the planktonic prokaryotic community during different seasons in the coastal waters of Bohai Bay

To explore temporal and spatial effects on the planktonic prokaryotic community composition (PCC) in the coastal region of the Bohai Sea, surface water samples were collected from 12  to  28 regularly distributed sites in Bohai Bay across 3 months from different seasons to characterize the PCC using high-throughput sequencing of the 16S rRNA V4 region. Prokaryotic α- and β-diversity showed significant temporal variation during the three sampling months. VPA analysis based on both weighted and unweighted UniFrac distances exhibited a shift of environmental and spatial effects on PCC variation with temporal variation. Quantification analysis of assembly processes on community turn over showed that "heterogeneous selection" dominated for PCC temporal variation, with basic abiotic parameters such as temperature, pH, ammonia nitrogen as the driving factors. Analysis of seasonal features showed that seasonal specific OTUs (ssOTUs) exhibited different seasonal attributions under the same phylum; meanwhile, the ssOTUs showed significant correlations with the driving environmental factors, which suggested that finer-level analysis was needed to more strictly reflect the temporal variation. Moreover, predicted nitrogen and sulfur metabolism were significantly shifted during the temporal variation. Our results clearly showed that seasonally varied environmental factors drive the "heterogeneous selection" process for PCC assembly in seawaters of Bohai Bay during different sampling seasons.

Dynamics of bacterial functional genes and community structures during rhizoremediation of diesel-contaminated compost-amended soil

The objective of this study was to characterize the effects of organic soil amendment (compost) on bacterial populations associated with petroleum hydrocarbon (PH) degradation and nitrous oxide (N₂O) dynamics via pot experiments. Soil was artificially contaminated with diesel oil at total petroleum hydrocarbon (TPH) concentration of 30,000 mg·kg-soil^-1 and compost was mixed with the contaminated soil at a 1:9 ratio (w/w). Maize seedlings were planted in each pot and a total of ten pots with two treatments (compost-amended and unamended) were prepared. The pot experiment was conducted for 85 days. The compost-amended soil had a significantly higher TPH removal efficiency (51.1%) than unamended soil (21.4%). Additionally, the relative abundance of the alkB gene, which is associated with PH degradation, was higher in the compost-amended soil than in the unamended soil. Similarly, cnorB and nosZ (which are associated with nitric oxide (NO) and N₂O reduction, respectively) were also highly upregulated in the compost-amended soil. Moreover, the compost-amended soil exhibited higher richness and evenness indices, indicating that bacterial diversity was higher in the amended soil than in the unamended soil. Therefore, our findings may contribute to the development of strategies to enhance remediation efficiency and greenhouse gas mitigation during the rhizoremediation of diesel-contaminated soils.