The Interplay of Light and Oxygen in the Reactive Oxygen Stress Response of Chlamydomonas reinhardtii Dissected by Quantitative Mass Spectrometry

Light and oxygen are factors that are very much entangled in the reactive oxygen species (ROS) stress response network in plants, algae and cyanobacteria. The first obligatory step in understanding the ROS network is to separate these responses. In this study, a LC-MS/MS based quantitative proteomic approach was used to dissect the responses of Chlamydomonas reinhardtii to ROS, light and oxygen employing an interlinked experimental setup. Application of novel bioinformatics tools allow high quality retention time alignment to be performed on all LC-MS/MS runs increasing confidence in protein quantification, overall sequence coverage and coverage of all treatments measured. Finally advanced hierarchical clustering yielded 30 communities of co-regulated proteins permitting separation of ROS related effects from pure light effects (induction and repression). A community termed redox^II was identified that shows additive effects of light and oxygen with light as the first obligatory step. Another community termed 4-down was identified that shows repression as an effect of light but only in the absence of oxygen indicating ROS regulation, for example, possibly via product feedback inhibition because no ROS damage is occurring. In summary the data demonstrate the importance of separating light, O₂ and ROS responses to define marker genes for ROS responses. As revealed in this study, an excellent candidate is DHAR with strong ROS dependent induction profiles.Life originated in an environment in which the atmosphere was reducing. More than 2.2 Gyr ago, photosynthetic bacteria managed to extract electrons from water, thereby releasing oxygen (O₂) as a side product (1). Although molecular O₂ is a triplet state (³O₂), and is thus kinetically inhibited, its related reactive oxygen species (ROS)¹, i.e., superoxide (O₂^•−), peroxides (ROOR), singlet oxygen (¹O₂), and hydroxyl radicals (HO^•) are not. Nevertheless, molecular O₂ itself oxidizes biomolecules, for example, thiol groups, albeit at a much slower rate. The fundamental change in environment and the appearance of O₂ and ROS triggered the biggest mass extinction ever seen on Earth (2, 3). Soon after, the much more efficient O₂ based metabolism (compared with fermentation) lead to an evolutionary explosion (4). Today, cells obtain energy from reduced organic molecules through O₂ based respiration.In the past ROS were associated with cellular stress but strong evidence points toward a cellular ROS network that keeps ROS production and ROS scavenging in tight balance to ensure the maintenance of the cellular redox homeostasis and protection against ROS stress (5, 6). An imbalance in this network has been associated with a wide array of human diseases such as cancer (7), neurodegeneration (8), Keshan disease (9), and many others (see also review (6)), although arguments have been brought forward that the origin of some diseases is not directly linked to ROS and that ROS are more likely to be the result of deteriorating cells (10). In any case, the cellular ROS network response to ROS stress is implicated in the progress of these diseases and understanding the network dynamics will have a significant impact in medicine.Equally important, reduced ROS capacity or imbalance in the ROS network results in decreased crop yields and simple attempts to increase production yields by increasing ROS scavenging capacities in plants failed because those plants lost their ability to mount a defense against pathogens efficiently by the hypersensitive reaction (11), which implicates intended localized high yield ROS production. On the other hand Chang et al. could show that the knock-out of glutathione peroxidase 7 (gpx7), i.e., reducing ROS scavenging capacity, leads to an increased pathogen resistance but, unfortunately, to an increased photosensitivity as well (12), thus resulting in reduced crop production. The quintessence is that plants require the ability to produce sufficient amounts of ROS as part of their defense mechanism yet require some ROS scavenging capacity because photosynthetic growth inevitably produces damaging ROS. In order to effectively mount a hypersensitivity defense reaction, the ROS scavenging capacities have to be suppressed. Thus understanding the ROS network is an important global issue in the light of hunger in some parts of the world and the need for biofuels. Elucidating the key players of the ROS network will allow high production crop plants to be designed.It seems clear that the ROS network, its dynamics and homeostasis are poorly understood. Understanding how to evaluate the ROS balance and how to restore ROS balance within a cell would have a strong impact on a medical and agricultural level. To put it in the words of Barry Halliwell: “the likely clinical value of ‘antioxidant therapy’ will depend on how well the exact role of reactive oxygen species,” i.e., the ROS network, “is known” (13).ROS can be divided into two classes, i.e., H₂O₂ and ¹O₂ based ones. Especially in plants, algae, and cyanobacteria, it is now widely accepted that the signaling pathways of H₂O₂ (14) and ¹O₂ (15) are complex and entangled (16, 17) simply through the nature of their production, i.e., via an active photosynthetic electron transport chain. However, there have been reports that clearly show the independence of H₂O₂ and ¹O₂ mediated responses (see e.g. (18, 19)). In Arabidopsis thaliana the ROS network, in particular the ¹O₂ aspect has been widely studied, but comprehensive proteomic studies are still required. The A. thaliana flu mutant was used to reveal ¹O₂ related retrograde signaling. The flu mutant accumulates protochlorophyllide when grown in the dark, and seedlings bleach and die whereas mature plants stop growing when transferred into light (20). ¹O₂ production yielded an induction of distinct genes and these differed significantly from genes induced by H₂O₂ (15). Apel and co-workers identified the chloroplast localized EXECUTER1/2 proteins as key players in ¹O₂ retrograde signaling (18, 21), highlighting that specific ¹O₂ induced signals trigger programmed cell death (PCD) rather than ROS induced damage. A flu-like gene (flp) was identified in Chlamydomonas reinhardtii, and its gene product FLP in its two splicing variants was shown to be involved in the chlorophyll biosynthesis (22). Regulation of FLPs were suggested to occur via light and retrograde plastid signals (22). The specific ¹O₂ signaling mechanism in A. thaliana was further extended by Ramel et al. (23). The authors could show that ¹O₂ induced damage to β-carotene, a major component in a ROS defense strategy, yields β-cyclocitral, which when produced and applied exogenously triggers a selective ¹O₂ response, similar to the one reported by Apel and co-workers when describing the effects of the flu mutant (15, 18, 21). However, the signaling pathways involving EXECUTER and β-cyclocitral show more and more independent features (see e.g. Lundquist et al. (24)).ROS production is an inevitable part of the oxygenic photosynthesis and thus can be controlled noninvasively by light intensities. This is why plants, algae, and cyanobacteria offer a unique opportunity to investigate the ROS network. However, in plants the majority of ROS is produced in the chloroplast requiring O₂ as educt and the presence of light. Therefore, careful separation of the light, O₂, and ROS responses is required. As a consequence, simple high light/low light comparisons are overshadowed by additional ROS production, and vice versa. A classical example is HSP70A in C. reinhardtii, which was originally reported to be light regulated (25) and later proven to be regulated by ROS (19), via two promoters that react specifically on H₂O₂ and ¹O₂, to be precise.We have devised an experimental setup, which allows the ROS, high light/low light (HL/LL) and aerobic/anaerobic (AR/AN) responses to be dissected on a proteome level using metabolic labeling and quantitative proteomics. We used an interlinked experimental setup that connects all four possible treatments in such a way that each treatment is compared with two other treatments. This offers a strong internal control because the changes in protein levels comparing two not directly connected treatments can be measured by two independent estimates. MS data was analyzed employing high quality retention time alignment to increase overall confidence in protein quantification, increase protein sequence coverage and increase coverage of all conditions. PyGCluster, a novel hierarchical clustering approach (26) was used to identify communities of proteins that are coregulated. Five communities/expression profiles are discussed: a) light and O₂ dependent induction, i.e., potential ROS related regulations, b) a novel regulation type, which shows induction of protein expression influenced additively by light and O₂, but with light as the obligatory first step, c) light related induction (O₂ independent), d) light dependent repression (O₂ independent), and e) light dependent repression in the absence of O₂, which might be a regulation linked to feedback inhibition by for example, molecules that are normally damaged by ROS.