Response of particle-attached and free-living bacterial communities to Microcystis blooms.

The massive proliferation of Microcystis threatens freshwater ecosystems and degrades water quality globally. Understanding the mechanisms that contribute to Microcystis growth is crucial for managing Microcystis blooms. The lifestyles of bacteria can be classified generally into two groups: particle-attached (PA; > 3 µm) and free-living (FL; 0.2-3.0 µm). However, little is known about the response of PA and FL bacteria to Microcystis blooms. Using 16S rRNA gene high-throughput sequencing, we investigated the stability, assembly process, and co-occurrence patterns of PA and FL bacterial communities during distinct bloom stages. PA bacteria were phylogenetically different from their FL counterparts. Microcystis blooms substantially influenced bacterial communities. The time decay relationship model revealed that Microcystis blooms might increase the stability of both PA and FL bacterial communities. A contrasting community assembly mechanism was observed between the PA and FL bacterial communities. Throughout Microcystis blooms, homogeneous selection was the major assembly process that impacted the PA bacterial community, whereas drift explained much of the turnover of the FL bacterial community. Both PA and FL bacterial communities could be separated into modules related to different phases of Microcystis blooms. Microcystis blooms altered the assembly process of PA and FL bacterial communities. PA bacterial community appeared to be more responsive to Microcystis blooms than FL bacteria. Decomposition of Microcystis blooms may enhance cooperation among bacteria. Our findings highlight the importance of studying bacterial lifestyles to understand their functions in regulating Microcystis blooms. KEY POINTS: • Microcystis blooms alter the assembly process of PA and FL bacterial communities • Microcystis blooms increase the stability of both PA and FL bacterial communities • PA bacteria seem to be more responsive to Microcystis blooms than FL bacteria.

Dynamic response of bacterial communities to Microcystis blooms: A three-year study.

Although nutrient availability is widely recognized as the driving force behind Microcystis blooms, identifying the microorganisms that play a pivotal role in their formation is a challenging task. Our understanding of the contribution of bacterial communities to the development of Microcystis blooms remains incomplete, despite the fact that the relationship between Microcystis and bacterial communities has been extensively investigated. Most studies have focused on their interaction for a single year rather than for multiple years. To determine key bacteria crucial for the formation of Microcystis blooms, we collected samples from three sites in the Daechung Reservoir (Chuso, Hoenam, and Janggye) over three years (2017, 2019, and 2020). Our results indicated that Microcystis bloom-associated bacterial communities were more conserved across stations than across years. Bacterial communities could be separated into modules corresponding to the different phases of Microcystis blooms. Dolichospermum and Aphanizomenon belonged to the same module, whereas the module of Microcystis was distinct. The microbial recurrent association network (MRAN) showed that amplicon sequence variants (ASVs) directly linked to Microcystis belonged to Pseudanabaena, Microscillaceae, Sutterellaceae, Flavobacterium, Candidatus Aquiluna, Bryobacter, and DSSD61. These ASVs were also identified as key indicators of the bloom stage, indicating that they were fundamental biological elements in the development of Microcystis blooms. Overall, our study highlights that, although bacterial communities change annually, they continue to share core ASVs that may be crucial for the formation and maintenance of Microcystis blooms.

A multi-commodity network model for optimal quantum reversible circuit synthesis.

Quantum computing is a newly emerging computing environment that has recently attracted intense research interest in improving the output fidelity, fully utilizing its high computing power from both hardware and software perspectives. In particular, several attempts have been made to reduce the errors in quantum computing algorithms through the efficient synthesis of quantum circuits. In this study, we present an application of an optimization model for synthesizing quantum circuits with minimum implementation costs to lower the error rates by forming a simpler circuit. Our model has a unique structure that combines the arc-subset selection problem with a conventional multi-commodity network flow model. The model targets the circuit synthesis with multiple control Toffoli gates to implement Boolean reversible functions that are often used as a key component in many quantum algorithms. Compared to previous studies, the proposed model has a unifying yet straightforward structure for exploiting the operational characteristics of quantum gates. Our computational experiment shows the potential of the proposed model, obtaining quantum circuits with significantly lower quantum costs compared to prior studies. The proposed model is also applicable to various other fields where reversible logic is utilized, such as low-power computing, fault-tolerant designs, and DNA computing. In addition, our model can be applied to network-based problems, such as logistics distribution and time-stage network problems.

Network analysis reveals succession of Microcystis genotypes accompanying distinctive microbial modules with recurrent patterns.

Every member of the ecological community is connected via a network of vital and complex relationships, called the web of life. To elucidate the ecological network and interactions among producers, consumers, and decomposers in the Daechung Reservoir, Korea, during cyanobacterial harmful algal blooms (cyanoHAB), especially those involving Microcystis, we investigated the diversity and compositions of the cyanobacterial (16S rRNA gene), including the genotypes of Microcystis (cpcBA-IGS gene), non-cyanobacterial (16S), and eukaryotic (18S) communities through high-throughput sequencing. Microcystis blooms were divided into the Summer Major Bloom and Autumn Minor Bloom with different dominant genotypes of Microcystis. Network analysis demonstrated that the modules involved in the different phases of the Microcystis blooms were categorized into the Pre-Bloom, Bloom, Post-Bloom, and Non-Bloom Groups at all sampling stations. In addition, the non-cyanobacterial components of each Group were classified, while the same Group showed similarity across all stations, suggesting that Microcystis and other microbes were highly interdependent and organized into cyanoHAB-related module units. Importantly, the Microcystis genotype-based sub-network uncovered that Pirellula, Pseudanabaena, and Vampirovibrionales preferred to interact with specific Microcystis genotypes in the Summer Major Bloom than with other genotypes in the Autumn Minor Bloom, while the copepod Skistodiaptomus exhibited the opposite pattern. In conclusion, the transition patterns of cyanoHAB-related modules and their key components could be crucial in the succession of Microcystis genotypes and to enhance the understanding of microbial ecology in an aquatic environment.

Stage-Wise Identification and Analysis of miRNA from Root-Knot Nematode Meloidogyne incognita.

In this study, we investigated global changes in miRNAs of Meloidogyne incognita throughout its life cycle. Small RNA sequencing resulted in approximately 62, 38, 38, 35, and 39 Mb reads in the egg, J2, J3, J4, and female stages, respectively. Overall, we identified 2724 known and 383 novel miRNAs (read count > 10) from all stages, of which 169 known and 13 novel miRNA were common to all the five stages. Among the stage-specific miRNAs, miR-286 was highly expressed in eggs, miR-2401 in J2, miR-8 and miR-187 in J3, miR-6736 in J4, and miR-17 in the female stages. These miRNAs are reported to be involved in embryo and neural development, muscular function, and control of apoptosis. Cluster analysis indicated the presence of 91 miRNA clusters, of which 36 clusters were novel and identified in this study. Comparison of miRNA families with other nematodes showed 17 families to be commonly absent in animal parasitic nematodes and M. incognita. Validation of 43 predicted common and stage-specific miRNA by quantitative PCR (qPCR) indicated their expression in the nematode. Stage-wise exploration of M. incognita miRNAs has not been carried out before and this work presents information on common and stage-specific miRNAs of the root-knot nematode.