Sphingobium cyanobacteriorum sp. nov., isolated from fresh water.

A novel Gram-stain-negative, yellow-pigmented, short rod-shaped bacterial strain, HBC34T, was isolated from a freshwater sample collected from Daechung Reservoir, Republic of Korea. The results of 16S rRNA gene sequence analysis indicated that HBC34T was affiliated with the genus Sphingobium and shared the highest sequence similarity to the type strains of Sphingobium vermicomposti (98.01 %), Sphingobium psychrophilum (97.87 %) and Sphingobium rhizovicinum (97.59 %). The average nucleotide identity (ANI) and digital DNA-DNA hybridisation (dDDH) values between HBC34T and species of the genus Sphingobium with validly published names were below 84.01 and 28.1 %, respectively. These values were lower than the accepted species-delineation thresholds, supporting its recognition as representing a novel species of the genus Sphingobium. The major fatty acids (>10 % of the total fatty acids) were identified as summed feature 8 (C18 : 1ω7c and/or C18 : 1ω6c) and summed feature 3 (C16 : 1ω7c and/or C16 : 1ω6c). The main polar lipids were phosphatidylglycerol, phosphatidylcholine, phosphatidylethanolamine, two phospholipids and two unidentified polar lipids. The respiratory quinone was Q-10. The genomic DNA G+C content of HBC34T was 64.04 %. The polyphasic evidence supports the classification of HBC34T as the type strain of a novel species of the genus Sphingobium, for which the name Sphingobium cyanobacteriorum sp. nov is proposed. The type strain is HBC34T (= KCTC 8002T= LMG 33140T).

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.

Microcystis abundance is predictable through ambient bacterial communities: A data-oriented approach.

The number of cyanobacterial harmful algal blooms (cyanoHABs) has increased, leading to the widespread development of prediction models for cyanoHABs. Although bacteria interact closely with cyanobacteria and directly affect cyanoHABs occurrence, related modeling studies have rarely utilized microbial community data compared to environmental data such as water quality. In this study, we built a machine learning model, the multilayer perceptron (MLP), for the prediction of Microcystis dynamics using both bacterial community and weekly water quality data from the Daechung Reservoir and Nakdong River, South Korea. The modeling performance, indicated by the R2 value, improved to 0.97 in the model combining bacterial community data with environmental factors, compared to 0.78 in the model using only environmental factors. This underscores the importance of microbial communities in cyanoHABs prediction. Through the post-hoc analysis of the MLP models, we revealed that nitrogen sources played a more critical role than phosphorus sources in Microcystis blooms, whereas the bacterial amplicon sequence variants did not have significant differences in their contribution to each other. Similar to the MLP model results, bacterial data also had higher predictability in multiple linear regression (MLR) than environmental data. In both the MLP and MLR models, Microscillaceae showed the strongest association with Microcystis. This modeling approach provides a better understanding of the interactions between bacteria and cyanoHABs, facilitating the development of more accurate and reliable models for cyanoHABs prediction using ambient bacterial data.

Effect of rainfall in shaping microbial community during Microcystis bloom in Nakdong River, Korea.

Various environmental factors play a role in the formation and collapse of Microcystis blooms. This study investigates the impact of heavy rainfall on cyanobacterial abundance, microbial community composition, and functional dynamics in the Nakdong River, South Korea, during typical and exceptionally rainy years. The results reveal distinct responses to rainfall variations, particularly in cyanobacterial dominance and physicochemical characteristics. In 2020, characterized by unprecedented rainfall from mid-July to August, Microcystis blooms were interrupted significantly, exhibiting lower cell densities and decreased water temperature, compared to normal bloom patterns in 2019. Moreover, microbial community composition varied, with increases in Gammaproteobacteria and notably in genera of Limnohabitans and Fluviicola. These alterations in environmental conditions and bacterial community were similar to those of the post-bloom period in late September 2019. It shows that heavy rainfall during summer leads to changes in environmental factors, consequently causing shifts in bacterial communities akin to those observed during the autumn-specific post-bloom period in typical years. These changes also accompany shifts in bacterial functions, primarily involved in the degradation of organic matter such as amino acids, fatty acids, and terpenoids, which are assumed to have been released due to the significant collapse of cyanobacteria. Our results demonstrate that heavy rainfall in early summer induces changes in the environmental factors and subsequently microbial communities and their functions, similar to those of the post-bloom period in autumn, leading to the earlier breakdown of Microcystis blooms.