Terrestrial cyanobacteria are very diverse and widely distributed in Antarctica, where they can form macroscopically visible biofilms on the surfaces of soils and rocks, and on benthic surfaces in fresh waters. We recently isolated several terrestrial cyanobacteria from soils collected on Signy Island, South Orkney Islands, Antarctica. Among them, we found a novel species of Nodosilinea, named here as Nodosilinea signiensis sp. nov. This new species is morphologically and genetically distinct from other described species. Morphological examination indicated that the new species is differentiated from others in the genus by cell size, cell shape, filament attenuation, sheath morphology and granulation. 16S rDNA phylogenetic analyses clearly confirmed that N. signiensis belongs to the genus Nodosilinea, but that it is genetically distinct from other known species of Nodosilinea. The D1-D1´ helix of the 16S-23S ITS region of the new species was also different from previously described Nodosilinea species. This is the first detailed characterization of a member of the genus Nodosilinea from Antarctica as well as being a newly described species.
Freshwater algae can be used as indicators to monitor freshwater ecosystem condition. Algae react quickly and predictably to a broad range of pollutants. Thus they provide early signals of worsening environment. This study was carried out to develop a computer-based image processing technique to automatically detect, recognize, and identify algae genera from the divisions Bacillariophyta, Chlorophyta and Cyanobacteria in Putrajaya Lake. Literature shows that most automated analyses and identification of algae images were limited to only one type of algae. Automated identification system for tropical freshwater algae is even non-existent and this study is partly to fill this gap.
Toxic cyanobacteria blooms are increasing in magnitude and frequency worldwide. However, this issue has not been adequately addressed in Malaysia. Therefore, this study aims to better understand eutrophication levels, cyanobacteria diversity, and microcystin concentrations in ten Malaysian freshwater lakes. The results revealed that most lakes were eutrophic, with total phosphorus and total chlorophyll-a concentrations ranging from 15 to 4270 µg L(-1) and 1.1 to 903.1 µg L(-1), respectively. Cyanobacteria were detected in all lakes, and identified as Microcystis spp., Planktothrix spp., Phormidium spp., Oscillatoria spp., and Lyngbya spp. Microcystis spp. was the most commonly observed and most abundant cyanobacteria recorded. Semi-quantitative microcystin analysis indicated the presence of microcystin in all lakes. These findings illustrate the potential health risk of cyanobacteria in Malaysia freshwater lakes, thus magnifying the importance of cyanobacteria monitoring and management in Malaysian waterways.
Five cyanobacterial strains with Nostoc-like morphology from different localities of the Mazandaran province of Iran were characterized using a polyphasic approach. Three strains clustered within the Aliinostoc clade whereas one each of the remaining two strains clustered within the genera Desmonostoc and Desikacharya. The phylogenetic positioning of all the strains by the bayesian inference, neighbour joining and maximum parsimony methods inferred using 16S rRNA gene indicated them to represent novel species of the genera Aliinostoc, Desmonostoc and Desikacharya. The 16S-23S ITS secondary structure analysis revealed that all five strains under study represented novel species unknown to science. In accordance with the International Code of Nomenclature for algae, fungi and plants we describe three novel species of the genus Aliinostoc and one species each of the genera Desmonostoc and Desikacharya.
Banana is one of the most important fruits cultivated in Malaysia, and it provides many health benefits. However, bacterial wilt disease, which attacks bananas, inflicts major losses on the banana industry in Malaysia. To understand the complex interactions of the microbiota of bacterial wilt-diseased banana plants, we first determined the bacterial communities residing in the pseudostems of infected (symptomatic) and diseased-free (non-symptomatic) banana plants. We characterized the associated microorganisms using the targeted 16S rRNA metagenomics sequencing on the Illumina MiSeq platform. Taxonomic classifications revealed 17 and nine known bacterial phyla in the tissues of non-symptomatic and symptomatic plants, respectively. Cyanobacteria and Proteobacteria (accounted for more than 99% of the 16S rRNA gene fragments) were the two most abundant phyla in both plants. The five major genera found in both plant samples were Ralstonia, Sphingomonas, Methylobacterium, Flavobacterium, and Pseudomonas. Ralstonia was more abundant in symptomatic plant (59% out of the entire genera) as compared to those in the non-symptomatic plant (only 36%). Our data revealed that 102 bacterial genera were only assigned to the non-symptomatic plant. Overall, this study indicated that more diverse and abundant microbiota were associated with the non-symptomatic bacterial wilt-diseased banana plant as compared to the symptomatic plant. The higher diversity of endophytic microbiota in the non-symptomatic banana plant could be an indication of pathogen suppression which delayed or prevented the disease expression. This comparative study of the microbiota in the two plant conditions might provide caveats for potential biological control strategies.