Solitary terminal cells of Aphanizomenon gracile (Cyanobacteria,Nostocales) can divide and renew trichomes

An attempt was made to find evidence that morphologically distinct terminal cells of filamentous cyanobacterium Aphanizomenon gracile strain CCALA 8 are capable of dividing and forming trichomes. Based on our current knowledge, the division of morphologically diversified terminal cells is possible in nostocalean cyanobacteria. However, this process has been observed only in a few species. Terminal cells of A. gracile differ morphologically from other vegetative cells of a trichome, as they are not hyaline and can sometimes be found as solitary cells in cultures. Hence, it was reasonable for us to suspect that these cells are capable of dividing and forming trichomes. We observed terminal cells under a light and transmission electron microscope. Microscopic observations revealed that the septum formed in both solitary terminal cells and in terminal cells attached to trichomes. Our study is the first to demonstrate division and renewal of trichomes in terminal cells of A. gracile. Previously, such mode of reproduction was described only for another nostocalean cyanobacterium Raphidiopsis mediterranea. Moreover, our findings further emphasize the variability among members that belong to the genus Aphanizomenon , in which a type species (A. flos‐aquae) has hyaline cells incapable of dividing and renewing trichomes, while A. gracile can additionally propagate by solitary terminal cells division. This additional feature distinguishing A. gracile from typical species of Aphanizomenon, such as A. flos‐aquae, might be valuable for resolving taxonomic position of the species considering ambiguous genetic relationship between A. gracile and A. flos‐aquae.     

Setae thickening in <Emphasis Type="Italic">Daphnia magna</Emphasis> alleviates the food stress caused by the filamentous cyanobacteria

It is assumed that daphnids adjust the filter screen morphology in order to minimize the interference with cyanobacterial filaments. The aim of this study was to investigate the impact of filamentous cyanobacteria (Aphanizomenon gracile Lemmermann, Cylindrospermopsis raciborskii Woloszynska Seenaya et Subba Raju) on the thickness and length of setae of the third pair of thoracic limbs of Daphnia magna. The second objective was to assess whether the setae modifications could improve the performance of daphnids in the presence of cyanobacteria. Three clones of Daphnia magna Straus were cultured with: green algae; green algae with filaments of Cylindrospermopsis; and green algae with filaments of Aphanizomenon. The size and age of animals in the first reproduction cycle as well as the number of offspring were recorded. Setae thickness and length were measured in the central part of each endopodite. Additionally, we analyzed how the changes in setae morphology affect the fitness of experimental animals using the intrinsic rate of population increase calculated with the Euler–Lotka equation. The results showed that the thickness and length of setae increased in the presence of filamentous cyanobacteria. Moreover, cyanobacteria-induced setae thickening was positively correlated to the fitness of daphnids, which may indicate setae thickening as a phenotypic adaptation to cope with food stress caused by filamentous cyanobacteria.     

Biophotonic markers of malignancy: Discriminating cancers using wavelength-specific biophotons

Early detection is a critically important factor when successfully diagnosing and treating cancer. Whereas contemporary molecular techniques are capable of identifying biomarkers associated with cancer, surgical interventions are required to biopsy tissue. The common imaging alternative, positron-emission tomography (PET), involves the use of nuclear material which poses some risks. Novel, non-invasive techniques to assess the degree to which tissues express malignant properties are now needed. Recent developments in biophoton research have made it possible to discriminate cancerous cells from normal cells both in vitro and in vivo. The current study expands upon a growing body of literature where we classified and characterized malignant and non-malignant cell types according to their biophotonic activity. Using wavelength-exclusion filters, we demonstrate that ratios between infrared and ultraviolet photon emissions differentiate cancer and non-cancer cell types. Further, we identified photon sources associated with three filters (420-nm, 620-nm., and 950-nm) which classified cancer and non-cancer cell types. The temporal increases in biophoton emission within these wavelength bandwidths is shown to be coupled with intrisitic biomolecular events using Cosic's resonant recognition model. Together, the findings suggest that the use of wavelength-exclusion filters in biophotonic measurement can be employed to detect cancer in vitro.     

Human platelets release alpha-6-L-fucosyltransferase upon activation

Previously we have shown that human platelets release alpha-6-L-fucosyltransferase (EC 2.4.1.68) during coagulation of blood [(1987) Glycoconjugate J. 4, 43-49]. Here we report that agonists which induce platelet aggregation bring about release of the enzyme. In quantitative terms the release of alpha-6-L-fucosyltransferase by washed, aggregated platelets was very similar to that occurring during blood coagulation.     

qNABpredict: Quick,accurate, and taxonomy-aware sequence-based prediction of content of nucleic acid binding amino acids

Protein sequence-based predictors of nucleic acid (NA)-binding include methods that predict NA-binding proteins and NA-binding residues. The residue-level tools produce more details but suffer high computational cost since they must predict every amino acid in the input sequence and rely on multiple sequence alignments. We propose an alternative approach that predicts content (fraction) of the NA-binding residues, offering more information than the protein-level prediction and much shorter runtime than the residue-level tools. Our first-of-its-kind content predictor, qNABpredict, relies on a small, rationally designed and fast-to-compute feature set that represents relevant characteristics extracted from the input sequence and a well-parametrized support vector regression model. We provide two versions of qNABpredict, a taxonomy-agnostic model that can be used for proteins of unknown taxonomic origin and more accurate taxonomy-aware models that are tailored to specific taxonomic kingdoms: archaea, bacteria, eukaryota, and viruses. Empirical tests on a low-similarity test dataset show that qNABpredict is 100 times faster and generates statistically more accurate content predictions when compared to the content extracted from results produced by the residue-level predictors. We also show that qNABpredict's content predictions can be used to improve results generated by the residue-level predictors. We release qNABpredict as a convenient webserver and source code at http://biomine.cs.vcu.edu/servers/qNABpredict/ . This new tool should be particularly useful to predict details of protein–NA interactions for large protein families and proteomes.