Large scale exploration reveals rare taxa crucially shape microbial assembly in alkaline lake sediments.

Alkaline lakes are extreme environments inhabited by diverse microbial extremophiles. However, large-scale distribution patterns, environmental adaptations, community assembly, and evolutionary dynamics of microbial communities remain largely underexplored. This study investigated the characteristics of microbial communities on rare and abundant taxa in alkaline lake sediments in west and northwest China. We observed that abundant taxa varied significantly with geographical distance, while rare taxa remained unaffected by regional differences. The assembly process of abundant taxa was influenced by dispersal limitation, whilst rare taxa were predominantly driven by heterogeneous selection. Network analysis indicated that rare taxa as core species for community interactions and community stability. Rare taxa exhibited higher speciation and transition rate than abundant taxa, serving as a genetic reservoir and potential candidates to become abundance taxa, highlighting their crucial role in maintaining microbial diversity. These insights underscore the significant influence of rare taxa on ecosystem biodiversity and stability in alkaline lakes.

Bidirectional Enhancement of Nitrogen Removal by Indigenous Synergetic Microalgal-Bacterial Consortia in Harsh Low-C/N Wastewater.

Conventional microalgal-bacterial consortia have limited capacity to treat low-C/N wastewater due to carbon limitation and single nitrogen (N) removal mode. In this work, indigenous synergetic microalgal-bacterial consortia with high N removal performance and bidirectional interaction were successful in treating rare earth tailing wastewaters with low-C/N. Ammonia removal reached 0.89 mg N L-1 h-1, 1.84-fold more efficient than a common microalgal-bacterial system. Metagenomics-based metabolic reconstruction revealed bidirectional microalgal-bacterial interactions. The presence of microalgae increased the abundance of bacterial N-related genes by 1.5- to 57-fold. Similarly, the presence of bacteria increased the abundance of microalgal N assimilation by 2.5- to 15.8-fold. Furthermore, nine bacterial species were isolated, and the bidirectional promotion of N removal by the microalgal-bacterial system was verified. The mechanism of microalgal N assimilation enhanced by indole-3-acetic acid was revealed. In addition, the bidirectional mode of the system ensured the scavenging of toxic byproducts from nitrate metabolism to maintain the stability of the system. Collectively, the bidirectional enhancement system of synergetic microalgae-bacteria was established as an effective N removal strategy to broaden the stable application of this system for the effective treatment of low C/N ratio wastewater.

BASALT refines binning from metagenomic data and increases resolution of genome-resolved metagenomic analysis.

Metagenomic binning is an essential technique for genome-resolved characterization of uncultured microorganisms in various ecosystems but hampered by the low efficiency of binning tools in adequately recovering metagenome-assembled genomes (MAGs). Here, we introduce BASALT (Binning Across a Series of Assemblies Toolkit) for binning and refinement of short- and long-read sequencing data. BASALT employs multiple binners with multiple thresholds to produce initial bins, then utilizes neural networks to identify core sequences to remove redundant bins and refine non-redundant bins. Using the same assemblies generated from Critical Assessment of Metagenome Interpretation (CAMI) datasets, BASALT produces up to twice as many MAGs as VAMB, DASTool, or metaWRAP. Processing assemblies from a lake sediment dataset, BASALT produces ~30% more MAGs than metaWRAP, including 21 unique class-level prokaryotic lineages. Functional annotations reveal that BASALT can retrieve 47.6% more non-redundant opening-reading frames than metaWRAP. These results highlight the robust handling of metagenomic sequencing data of BASALT.

Resourceful application and mechanism of oyster shell-microalgae synergistic system：Sustainable treatment of harsh low carbon nitrogen ratio actual wastewater.

Microalgal technology holds great promise for both low C/N wastewater treatment and resource recovery simultaneously. Nevertheless, the advancement of microalgal technology is hindered by its reduced nitrogen removal efficiency in low C/N ratio wastewater. In this work, microalgae and waste oyster shells were combined to achieve a total inorganic nitrogen removal efficiency of 93.85% at a rate of 2.05 mg L-1 h-1 in low C/N wastewater. Notably, over four cycles of oyster shell reuse, the reactor achieved an average 85% ammonia nitrogen removal extent, with a wastewater treatment cost of only $0.092/ton. Moreover, microbial community analysis during the reuse of oyster shells revealed the critical importance of timely replacement in inhibiting the growth of non-functional bacteria (Poterioochromonas_malhamensi). The work demonstrated that the oyster shell - microalgae system provides a time- and cost-saving, environmental approach for the resourceful treatment of harsh low C/N wastewater.

A mixed blessing of influent leachate microbes in downstream biotreatment systems of a full-scale landfill leachate treatment plant.

In landfill leachate treatment plants (LLTPs), the microbiome plays a pivotal role in the decomposition of organic compounds, reduction in nutrient levels, and elimination of toxins. However, the effects of microbes in landfill leachate influents on downstream treatment systems remain poorly understood. To address this knowledge gap, we collected 23 metagenomic and 12 metatranscriptomic samples from landfill leachate and activated sludge from various treatment units in a full-scale LLTP. We successfully recovered 1,152 non-redundant metagenome-assembled genomes (MAGs), encompassing a wide taxonomic range, including 48 phyla, 95 classes, 166 orders, 247 families, 238 genera, and 1,152 species. More diverse microbes were observed in the influent leachate than in the downstream biotreatment systems, among which, an unprecedented ∼30 % of microbes with transcriptional expression migrated from the influent to the biological treatment units. Network analysis revealed that 399 shared MAGs across the four units exhibited high node centrality and degree, thus supporting enhanced interactions and increased stability of microbial communities. Functional reconstruction and genome characterization of MAGs indicated that these shared MAGs possessed greater capabilities for carbon, nitrogen, sulfur, and arsenic metabolism compared to non-shared MAGs. We further identified a novel species of Zixibacteria in the leachate influent with discrete lineages from those in other environments that accounted for up to 17 % of the abundance of the shared microbial community and exhibited notable metabolic versatility. Meanwhile, we presented groundbreaking evidence of the involvement of Zixibacteria-encoded genes in the production of harmful gas emissions, such as N2O and H2S, at the transcriptional level, thus suggesting that influent microbes may pose safety risks to downstream treatment systems. In summary, this study revealed the complex impact of the influent microbiome on LLTP and emphasizes the need to consider these microbial characteristics when designing treatment technologies and strategies for landfill leachate management.