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Algal blooms have seriously affected the production and life of people and real-time detection of algae in water samples is a powerful measure to prevent algal blooms. The traditional manual detection of algae with a microscope is extremely time-consuming. In recent years, although there have been many studies using deep learning to classify and detect algae, most of them have focused on the relatively simple task of algal classification. In addition, some existing algal detection studies not only use small datasets containing limited algal species, but also only prove that object detection algorithms can be applied to algal detection tasks. These studies cannot implement the real-time detection of algae and timely warning of algal blooms. Therefore, this paper proposes an efficient self-organized detection system for algae. Benefiting from this system, we propose an interactive method to generate the algal detection dataset containing 28,329 images, 562,512 bounding boxes and 54 genera. Then, based on this dataset, we not only explore and compare the performance of 10 different versions of state-of-the-art object detection algorithms for algal detection, but also tune the detection system we built to its optimum state. In practical application, the system not only has good algal detection results, but also can complete the scanning, photographing and detection of a 2 cm × 2 cm, 0.1 mL algal slide specimen within five minutes (the resolution is 0.25886 μ m/pixel); such a task requires a well-trained algal expert to work continuously for more than three hours. The efficient algal self-organized detection system we built makes it possible to detect algae in real time. In the future, with the help of IoT, we can use various smart sensors, actuators and intelligent controllers to achieve real-time collection and wireless transmission of algal data, use the efficient algal self-organized detection system we built to implement real-time algal detection and upload the detection results to the cloud to realize timely warning of algal blooms. [ABSTRACT FROM AUTHOR]

• Analyzed the taxonomic and functional dynamics of microbial community to algal blooms. • Constructed 161 high-quality metagenome-assembled genomes by binning analysis. • Cyanobacterial strains showed diverse energy pathways, transporters and prokaryotic defense systems. • Nitrogen and phosphorus influence the microbial structure by affecting co-pathways. Freshwater lakes are threatened by harmful cyanobacterial blooms, whose basic unit is Cyanobacterial Aggregate (CA). CA-attached bacteria play a significant role through different blooming stages with substantial variation of their taxonomic structure. However, little is known about their functional variations and functional links with cyanobacteria due to the lack of reference genomes. In this longitudinal study, we collected 16 CA samples from Lake Taihu, one of China's largest freshwater lakes, from April 2015 to February 2016, and sequenced their V4 region of 16S rRNA genes, full metagenomes (MG), and metatranscriptomes (MT). The analysis of these data revealed the dynamics of microbial taxonomic and functional structure in CAs, influenced by both external environmental factors and internal metabolism. 55 OTUs, 456 genes, and 37 transcripts showed significantly differential abundance across the early, middle, and late blooming stages (ANOVA test, P < 0.05). Total nitrogen and total phosphorus were proved to be the most important environmental drivers of microbial taxonomic and functional variations in CAs (Mantel's r > 0.25, P < 0.05). We constructed 161 high-quality metagenome-assembled genomes (MAGs), out of which 22 were cyanobacterial strains with diverse energy pathways, transporters and prokaryotic defense systems. Based on these MAGs, we constructed a cyanobacteria-bacteria co-nitrogen-pathway and a cyanobacteria-bacteria co-phosphorus-pathway, by which we demonstrated how nitrogen and phosphorus influence the dynamics of the microbial structure to a certain extent by affecting these co-pathways. Overall, these results characterized the taxonomic, functional, and transcriptional variations of microbes in CAs through different blooming stages. Genome assembly and metabolic analysis of cyanobacteria and their attached bacteria suggested that the material exchange and signal transduction do, indeed, exist among them. Our understanding of the underlying molecular pathways for cyanobacterial blooms could lead to the control of blooms by interventional strategies to disrupt critical microbes' expression. [Display omitted] [ABSTRACT FROM AUTHOR]

The cause of phytoplankton blooms has been extensively discussed and largely attributed to favorable external conditions such as nitrogen/phosphorus resources, pH and temperature. Here from the standpoint of hormesis response, we propose that phytoplankton blooms are initiated by stimulatory effects of low concentrations of herbicides as environmental contaminants spread over estuaries and lakes. The experimental results revealed general stimulations by herbicides on Microcystis aeruginosa and Selenastrum capricornutum , with the maximum stimulation in the 30–60% range, depending on the agent and experiment. In parallel with enhancing stimulation, the ratio of HP (high-potential) form to LP (low-potential) form of cytochrome b 559 (RHL) was observed decreasing, while intracellular reactive oxygen species (ROS) were observed increasing. We propose that the ROS originated from the thermodynamic transformation of cytochrome b 559 , enhancing the stimulatory response. Furthermore, the results also proved that thermodynamic states of cytochrome b 559 could be modulated by nitric oxide, thus affecting cellular equilibrium of oxidative stress (OS) and correspondingly causing the inhibitory effect of higher concentrations of herbicides on phytoplankton. This suggests that hormesis substantially derives from equilibrium shifting of OS. Moreover, it is reasonable to infer that phytoplankton blooms would be motivated by herbicides or other environmental pollutants. This study provides a new thought into global phytoplankton blooms from a contaminant perspective. Image 1 • The experimental results revealed hormesis effects by herbicides on Microcystis aeruginosa and Selenastrum capricornutum. • Cytochrome b 559 played a vital role in alleviating photoinhibition caused by herbicides. • Hormesis response substantially derived from equilibrium shifting of oxidative stress. • It is proposed that low concentrations of water pollutants are supportive factors in the formation of phytoplankton blooms. [ABSTRACT FROM AUTHOR]