PCR identification of toxic euglenid species Euglena sanguinea

Ecology of freshwater harmful euglenophytes: A review

A diverse array of aquatic ecosystems are inhabited by the euglenophytes, a group of autotrophic and eukaryotic organisms. In inland waterbodies, the red bloom is caused by a rapid development or accumulation of euglenophytes. Recent studies have designated euglenophytes as bioindicator of organic pollution. The ecology of euglenophytes is influenced by the changes in the intensity of sunlight, temperature, nutrient cycles, and seasons. Most of the species of euglenophytes grow prolifically with the increase of water temperature. Nitrogen and phosphorus are often thought to be the main nutrients that influence the cellular growth of toxic euglenophytes. A high concentration of nutrients is required for the euglenophytes to grow and to form bloom. Heavy bloom of euglenophytes in the summer season is the characteristic of eutrophic ponds. Inland waterbodies in many countries suffer from euglenophyte blooms, which shade submerged vegetation, deplete the dissolved oxygen and disrupt the aquatic food webs. Dense bloom of euglenophytes clog the gills of fishes, cause breathing difficulties and in extreme cases results mortality. Red blooms of the deadly toxin producing Euglena sanguinea negatively affect the water quality resulting massive mortality of fishes. Consequently, aquaculture systems and fisheries are facing a serious threat from the predicted outbreak of toxic red blooms of euglenophytes worldwide. To ensure sustainability in the fisheries and aquaculture industry, it is essential to analyze the ecology of euglenophytes. Again, interesting research on euglenophycin, a Euglena-derived natural product, has shown that it can be utilized as a potential anti-cancer drug. This paper comes up with a thorough review of the latest research in this area, revealing new insights and solutions that can help mitigate the negative impact of the freshwater harmful euglenophytes. By implementing considerable management strategies, the health of the valuable aquatic ecosystems and the future of the aquaculture and fisheries can also be secured.

Reddening of the Unicellular Green Alga Euglena gracilis by Dried Bonito Stock and Intense Red Light Irradiation

This study confirms for the first time that the significant red coloration of Euglena gracilis is induced by bonito stock (BS), a traditional Japanese food, and intense red light exposure (605~660 nm, 1000~1300 µmol photons/m2/s). Under the condition, excessive photosynthetic activity destroyed many chloroplasts, while carotenoids were maintained, resulting in the formation of reddened cells. The HPLC analysis revealed that diadinoxanthin was the primary carotenoid present in reddened cells. Additionally, an undefined xanthophyll, not produced under normal culture conditions, was synthesized and suggested to contain a C=O bond. While it has been reported that strong light stress can increase the total carotenoid content of cells, this study did not verify this claim, and it should be investigated further in future research. Under white light irradiation conditions (90 μmol photons/m2/s) in BS medium, no reddening of cells was observed, and good growth was achieved (over four times the cell density in CM medium on the seventh day). This cell suspension is considered to have a high nutritional value because it is composed of functional food, BS and E. gracilis. The fact that this method does not involve genetic modification suggests the possibility of industrial applications, including food use, even in reddened cells.

Trends in digital image processing of isolated microalgae by incorporating classification algorithm

Identification of microalgae species is of importance due to the uprising of harmful algae blooms affecting both the aquatic habitat and human health. Despite this occurence, microalgae have been identified as a green biomass and alternative source due to its promising bioactive compounds accumulation that play a significant role in many industrial applications. Recently, microalgae species identification has been conducted through DNA analysis and various microscopy techniques such as light, scanning electron, transmission electron, and atomic force -microscopy. The aforementioned procedures have encouraged researchers to consider alternate ways due to limitations such as costly validation, requiring skilled taxonomists, prolonged analysis, and low accuracy. This review highlights the potential innovations in digital microscopy with the incorporation of both hardware and software that can produce a reliable recognition, detection, enumeration, and real-time acquisition of microalgae species. Several steps such as image acquisition, processing, feature extraction, and selection are discussed, for the purpose of generating high image quality by removing unwanted artifacts and noise from the background. These steps of identification of microalgae species is performed by reliable image classification through machine learning as well as deep learning algorithms such as artificial neural networks, support vector machines, and convolutional neural networks. Overall, this review provides comprehensive insights into numerous possibilities of microalgae image identification, image pre-processing, and machine learning techniques to address the challenges in developing a robust digital classification tool for the future.