Sigitas Šulčius

Increased risk of exposure to microcystins in the scum of the filamentous cyanobacterium Aphanizomenon flos-aquae accumulated on the western shoreline of the Curonian Lagoon.

Concentration of toxic cyanobacteria blooms on the downwind shore of high recreational amenity water bodies with largely increases the risk of exposure to cyanotoxins. In this study analysis of phytoplankton structure, cyanotoxin composition and concentration was performed on cyanobacteria scum material, high- and low-density bloom samples in the Curonian Lagoon. We found that the concentration of cyanotoxins in the scum material increased from ∼30 to ∼300-fold compared to bloom samples. In Microcystis aeruginosa dominated samples microcystin-LR was present at the highest concentration, while the dominance of Planktothrix agardhii was associated with the occurrence of dmMC-RR as the major microcystin variant. The toxicological potential of cyanobacterial scums in the Curonian Lagoon is emphasized, and management by removal of these scums is proposed.

Draft Genome Sequence of the Cyanobacterium Aphanizomenon flos-aquae Strain 2012/KM1/D3, Isolated from the Curonian Lagoon (Baltic Sea)

ABSTRACT We report here the de novo genome assembly of a cyanobacterium, Aphanizomenon flos-aquae strain 2012/KM1/D3, a harmful bloom-forming species in temperate aquatic ecosystems. The genome is 5.7 Mb with a G+C content of 38.2%, and it is enriched mostly with genes involved in amino acid and carbohydrate metabolism.

Characterization of a lytic cyanophage that infects the bloom-forming cyanobacterium Aphanizomenon flos-aquae

Vb-AphaS-CL131 is a novel cyanosiphovirus that infects harmful Aphanizomenon flos-aquae. This cyanophage has an isometric head, 97 nm in diameter and a long, flexible non-contractile tail, 361 nm long. With a genome size of ~120 kb, it is the second largest cyanosiphovirus isolated to date. The latent period was estimated to be ~36 h and a single infected cell produces, on average, 218 infectious cyanophages. Cyanophage infection significantly suppresses host biomass production and alters population phenotype.

Automatic detection and morphological delineation of bacteriophages in electron microscopy images

Automatic detection, recognition and geometric characterization of bacteriophages in electron microscopy images was the main objective of this work. A novel technique, combining phase congruency-based image enhancement, Hough transform-, Radon transform- and open active contours with free boundary conditions-based object detection was developed to detect and recognize the bacteriophages associated with infection and lysis of cyanobacteria Aphanizomenon flos-aquae. A random forest classifier designed to recognize phage capsids provided higher than 99% accuracy, while measurable phage tails were detected and associated with a correct capsid with 81.35% accuracy. Automatically derived morphometric measurements of phage capsids and tails exhibited lower variability than the ones obtained manually. The technique allows performing precise and accurate quantitative (e.g. abundance estimation) and qualitative (e.g. diversity and capsid size) measurements for studying the interactions between host population and different phages that infect the same host.

Boosting performance of the edge-based active contour model applied to phytoplankton images

Automated contour detection for objects representing the Prorocentrum minimum (P. minimum) species in phytoplankton images is the core goal of this study. The species is known to cause harmful blooms in many estuarine and coastal environments. Active contour model (ACM)-based image segmentation is the approach adopted here as a potential solution. Currently, the main research in ACM area is highly focused on development of various energy functions having some physical intuition. This work, by contrast, advocates the idea of rich and diverse image preprocessing before segmentation. Advantage of the proposed preprocessing is demonstrated experimentally by comparing it to the six well known active contour techniques applied to the cell segmentation in microscopy imagery task.