Reactive oxygen radical scavengers—Saving the cells?

Abstract

This wet and cold season is the ideal time to develop a cold or influenza and to relieve symptoms with a mucolytic agent. N-acetylcysteine, also known as acetylcysteine or N-acetyl-L-cysteine (NAC), is a pharmaceutical drug used mainly as a mucolytic agent. Its chemical name is (R)-2-acetamido-3-sulfanylpropanoic acid. NAC is widely used as a mucolytic agent although its efficacy is highly disputed. Several other potential fields of therapeutic application such as chronic obstructive pulmonary disease, AIDS, and influenza are under discussion. NAC was also suggested as an antidote in cases of metallic intoxication and radioactive irradiation. The multitude of potentially beneficial effects are possibly related to the apoptosis alternating activities of this reactive oxygen species scavenger. However, the management of paracetamol (acetaminophen) overdose is among the most prominent therapeutical applications. Now, Löhrke and colleagues (this issue) report that NAC affects the survival of luteal cells. The authors found that cell survival markedly decreases following NAC treatment in mature corpus luteum-derived luteal cells but not in luteal cells from the developing gland. Phagocytosis and pinocytosis are microscopically the most obvious surface activities of amoebae and are morphologically and functionally similar to that in human macrophages. Antibody cross-recognition with highly conserved leukocyte cluster of differentiation (CD) marker proteins is a common finding between closely related vertebrate species. Studies on the mechanisms of phagocytosis (Ravine et al.; this issue) show similarly recognized protein epitopes on the cell surface. For example, the human panleukocytic marker, CD45 or the protein tyrosine phosphatase receptor type C are important regulators of human leukocyte activity being highly expressed in all nucleated hematopoietic cell lines at all maturation stages. Phagocytosis in the phylogenesis is judged to be a highly conservative mechanism due to the cross-reactivity of different antibodies against the human CD45 antigen with antigen epitopes of amoebae. Proximity of molecules is of substantial relevance in understanding molecular interactions and signal transduction pathways. Typical fields of application are T-cell receptor analysis or Her2 hetero- or homo-dimerization in cancer (Vollmann-Zwerenz and colleagues; this issue). Förster resonance energy transfer is nowadays a convenient method for flow and image cytometry to quantitate molecule proximity. An elegant new alternative is the recently developed method of fluorescence proximity ligation (1). Bridgeman and collaborators (this issue) present a completely new approach to determine molecular interactions in making use of the old co-precipitation technology used for decades in protein chemistry for flow cytometry. This bead-based assay can be multiplexed and renders high detection sensitivity. Determining changes in enzyme activity and protein modification on a single cell basis is of substantial importance for identifying heterogeneity of cell systems. However, present technology lacks the sensitivity to identify several single peptide fragments. The only single cell protein technology is single cell capillary electrophoresis but it lacks the ability to definitely identify protein fragments and other reaction products. In this issue, Brown and colleagues elegantly combined single cell capillary electrophoresis with liquid chromatography and mass spectrometry in a workflow. Using this stream of technologies, the authors were able to identify peaks measured by single cell capillary electrophoresis. This approach may lead to unraveling metabolic pathways and enzyme activities that are of extreme relevance in several diseases. Development of assays for the automated and unbiased quantitation of microscopic images is an ongoing process of software and algorithm research (2). The major challenges are: How can cells or cell organelles be unequivocally recognized and how can these objects then be objectively categorized? Yu et al. (this issue) propose an upgrade of their previously presented maximum common boundary (MCB) algorithm (3) that they applied to measure neurite outgrowth. The new upgrade of their algorithm is based on Voronoi diagrams. This approach improves and speeds up image segmentation of images from a neuroblastoma cell line cultured at different cell densities. Forero and colleagues (this issue) propose a highly interesting approach to automatically count neurons from Drosophila embryos. Their program (DeadEasy Neurons) will be of interest to researchers from neurobiology and developmental biology. DeadEasy Neurons is an image processing and object recognition method that identifies neuronal nuclei labeled with HB9 over background (nonspecific antibody staining) from a stack of confocal images that make up the complete embryonic ventral nerve cord, and it automatically counts the neurons in 3D. The method (written in Java) will become freely available through ImageJ with this publication, and the parameters indicated and the algorithm can be modified by the user to count cells of choice. Dr. Jozsef Bocsi, Heart Center Leipzig, is acknowledged for his help with this editorial.