Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), is a major global health threat. During infection, bacteria are believed to encounter adverse conditions such as iron depletion. Mycobacteria synthesize iron-sequestering mycobactins, which are essential for survival in the host, via the intermediate salicylate. Salicylate is a ubiquitous compound which is known to induce a mild antibiotic resistance phenotype. In M. tuberculosis salicylate highly induces the expression of Rv0560c, a putative methyltransferase. We identified and characterized the promoter and regulatory elements of Rv0560c. PRv0560c activity was highly inducible by salicylate in a dose-dependent manner. The induction kinetics of PRv0560c were slow, taking several days to reach maximal activity, which was sustained over several weeks. Promoter activity could also be induced by compounds structurally related to salicylate, such as aspirin or para-aminosalicylic acid, but not by benzoate, indicating that induction is specific to a structural motif. The −10 and −35 promoter elements were identified and residues involved in regulation of promoter activity were identified in close proximity to an inverted repeat spanning the −35 promoter element. We conclude that Rv0560c expression is controlled by a yet unknown repressor via a highly-inducible promoter. Mycobacterium tuberculosis complex, however, M. tuberculosis is the major causative agent of TB in humans M. tuberculosis physiology and pathogenesis are still poorly understood. M. tuberculosis is an intracellular pathogen, and during infection the mycobacteria are believed to be exposed to adverse conditions such as hypoxia, nitric oxide and iron starvation Tuberculosis (TB) is a major global health threat. According to the WHO, TB causes nearly 2 million deaths each year, and one third of the world's population is believed to be latently infected M. tuberculosis produces two types of siderophores (mycobactins), whose production is essential for infection and survival in macrophages Iron is an indispensable component of many prokaryotic and eukaryotic enzymes. When bacteria encounter conditions of low iron, for example during macrophage infection, they produce iron-sequestering siderophores in order to maintain cellular functions M. tuberculosisEscherichia coli or CmeR in Campylobacter jejuniGiven the natural accumulation of salicylate under conditions encountered by the bacteria during an infection, it is interesting to note exogenous salicylate is able to induce a multiple antibiotic resistant (“mar”) phenotype in M. tuberculosis is poorly understood. Salicylate exposure affects the expression of 58 genes, none of which are known efflux pumps, and results in a general reduction of transcriptional and translational activities, as well as changes in energy metabolism The mechanism of the salicylate-induced mar phenotype in Rv0560c is a non-essential gene encoding a putative benzoquinone methyltransferase. There have been suggestions that Rv0560c plays a role related to the biosynthesis of the isoprenoid lipid menaquinone Rv0560c) which is highly active. We investigated the induction kinetics of this promoter, which took several days to reach maximal activity and remained highly induced for several weeks. We show that PRv0560c is also induced by structural analogues of salicylate as well as fenofibrates and is mildly induced under conditions of low iron. The −10 and −35 promoter elements, as well as residues involved in its regulation were identified. Our results suggest that this regulatory control is likely to be mediated via a repressor. The data presented here reveal PRv0560c to be a promoter with a high level of induction after salicylate treatment.The range of conditions under which Rv0560c is induced and the huge extent of its induction in response to salicylate are intriguing. The aim of this study was to identify and characterise the promoter of Rv0560c to gain further insight into its expression. Here, we demonstrate for the first time that Rv0560c is expressed from a salicylate-inducible promoter  although lower than that of PRv0561c  and continued to increase over 4 hours  . Salicyly at all . These rbenzoate .Rv0560c activity 4-fold. These results show that other compounds that are not direct structural analogues of salicylate, are able to modulate PRv0560c activity.Amongst the fibrates tested, fenofibrate evoked a 17-fold induction 2524 MU; , and gemRv0560c activity was induced to maximal level by growing M. tuberculosis in the presence of salicylate and promoter activity was monitored after removal of salicylate from the growth medium by washing in salicylate-free medium.We determined the off kinetics of the promoter. PRv0560c activity remained high immediately after the wash in salicylate-free medium . Therefore, residual activity of PRv0560c could be due to high intracellular levels of salicylate which would not be removed merely by washing cells. To test this possibility, PRv0560c off kinetics were monitored during growth in salicylate-free medium during several passages; a salicylate-exposed culture was used to inoculate salicylate-free medium and cultured to late log phase before further passaging in salicylate-free medium. Promoter activity decreased with each passage , PRv0560c activity increased by 3-fold to 620 MU  further, an attempt was made to map its promoter elements. According to the current annotation on TubercuList (http://tuberculist.epfl.ch/), there is a short intergenic region of 24 bp between the stop codon of Rv0561c and the start codon of Rv0560c. A search for putative −10 elements within the upstream region of Rv0560c was carried out. Three putative −10 elements  were found, all located downstream of the annotated translational start site of Rv0560c, but immediately upstream of a putative alternative translational start site (To characterise Part site . To estaMutation of PM3 abolished promoter activity to a level seen in the empty vector control (11 MU) confirming that it is the most probable −10 element of the Rv0560c promoter. Interestingly, mutations in PM1 and PM2 both resulted in constitutive expression, albeit to different levels . MutatioRv0560c is highly likely to be a SigA–dependent promoter. The SigA consensus sequence is TTGACW-N16–21-TATAMT Rv0560c looks to be an extended promoter due to the presence of a TGN motif (in this case TGA) directly in front of the −10 element The sequence of the promoter elements suggests that PWe decided to mutate some of the residues in the −10 element to test their effect on promoter strength and regulation . MutatioSince mutation in the −35 region resulted in loss of induction, we predicted that there is a regulatory element in this region; such operator regions are often located between the −35 and 10 elements. We carried out further mutations to identify other residues involved in regulation of promoter activity located between the −10 and −35 region. Mutation of the two residues immediately downstream of the −35 element (PM6) resulted in a much higher basal level of activity (1232 MU). Interestingly, mutation of two bases further downstream (PM7) increased the basal activity even further (5959 MU). In both cases, induction was retained, with promoter activity of over 10000 MU in the presence of salicylate . This coM. tuberculosis gene Rv0560c due to its strikingly high induction in response to salicylate, and its upregulation under conditions mimicking the in vivo environment the bacteria encounter during an infection Rv0560c, but not PRv0561c is inducible by salicylate. This is in accordance with a previous transcriptome study showing that Rv0560c, but not Rv0561c is upregulated after salicylate treatment We were interested in the Rv0560c to be a strong promoter as compared to other M. tuberculosis promoters and with slow induction kinetics, taking several days to reach peak activity and remaining stably induced over a course of several weeks. The majority of M. tuberculosis promoters measured using LacZ as a reporter have activity in the range of 100–1000 MU; examples include the promoters of recA, pknH, embA, mbtB and higBArpfA, which is reported as one of the strongest constitutive promoters in M. tuberculosis has an activity of 4500 MU whiB1 has comparable activity to PRv0560c at 800–15,000 MU We found PwhiB1 promoter with comparable activity The high level of promoter activity after induction could be due to presence of a perfect match to the canonical −35 element TTGACA , the extended promoter motif, and the high sequence similarity of the −10 element to the consensus sequence TATAAT M. tuberculosis systems, for example the ATc and pristinamcyin systems Rv0560c appear to be particularly slow, since the ATc-inducible systems are fully induced with 24 h M. tuberculosis took 18–36 h, rather than 72 h The slow induction kinetics could be due to a tight interaction of the repressor with its binding motif, taking a long time to alleviate and allow full access to the polymerase. Alternatively the mechanism leading to alleviation of repression  might be slow. It is interesting to note that there are other inducible promoters with slow kinetics, although most of these are not native The fact that some structural analogues of salicylate (PAS and aspirin), but not others (benzoate) induce promoter activity confirms that induction is specific to a certain chemical structure present in salicylate, PAS and aspirin, but not benzoate. These findings are in accordance with a previous study on Rv0560crotein expression, except for aspirin  which was reported not to induce Rv0560c Rv0560c activity. In our study, menadione did not induce PRv0560c, but actually repressed it. Both results are in accordance with previous findings of a protein study Compounds that can interfere with isoprenoid quinone action and are structurally related to salicylate (such as fenofibrate or gemfibrozil) also induced PE. coliM. tuberculosis does contain homologs of some of the genes present in the E. coli ubiquinone pathway The function of Rv0560c is unknown, but it has homology with a benzoquinone methyltransferase (UbiG) involved in ubiquinone biosynthesis in menH (Rv0558), menD (Rv0555) and menC (Rv0553) Rv0560c has also been suggested to be involved in menaquinone biosynthesis, due to its genomic proximity to in vitro growth) could be involved in the synthesis of novel menaquinones such as the recently identified sulphated menaquinone Rv0560c to be induced during iron starvation, when intracellular levels of salicylate are naturally elevated. The salicylate-dependent induction of PRv0560c accounts for the upregulation of Rv0560c during iron depletion, despite the absence of binding motifs for the main regulator of iron responsive genes (IdeR) upstream of Rv0560c Alternatively, Rv0560c  was grown in Middlebrook 7H9 medium supplemented with 10% v/v oleic acid-albumin-dextrose-catalase (OADC) supplement and 0.05% w/v Tween 80, or on 7H10 agar supplemented with 10% v/v OADC. Cultures were grown without agitation in 50 mL conical tubes unless otherwise stated. Streptomycin was used at 20 mg L−1 and X-gal at 50 mg L−1 when required. Low iron minimal medium (MMT) was prepared as follows: 6 g L−1 Na2HPO4, 3 g L−1 KH2PO4, 0.5 g L−1 NaCl, 1 g L−1 NH4Cl and 0.0147 g L−1 CaCl2 supplemented with 0.05% w/v Tween 80 and 2% v/v glycerol and treated overnight with 5 g L−1 Chelex 100; 2 mM MgSO4 was added and the medium was filter-sterilised.M. tuberculosis genomic DNA using primer pairs UR561F CCCGGGGGATC- GCGACGTTGTTACCCC and UR561R CCCGGGCCGCCAGCCACTTACCCC for Rv0561c, and UR560F CCCGGGGCGCCGGCTAGCGTTGTTACCCC and UR560R CCCGGGCCTG- CCGTCATAGCCGGTAAACGCCC for Rv0560c. Products were cloned as SmaI fragments (underlined) into the SacI site of pSM128 lacZ reporter gene. Protein tags were added to lacZ in pSM128 using SDM primer pairs TailLAAf GGTCTGGTGTCAAAAAGCAGCAAACGACGAAAACTACGCTTTAGC AGCTTAATAATAAC, TailLAAr GTTATTATTAAGCTGCTAAAGCGTAGTTTTCG TCGTTTGCTGCTTTTTGACACCAGAC or TailASVf GGTCTGGTGTCAAAAAGC AGCAAACGACGAAAACTACGCTGCATCAGTTTAATAATAAC, TailASVr GTTA TTATTAAACTGATGCAGCGTAGTTTTCGTCGTTTGCTGCTTTTTGACACCAGACC.Primers were designed to amplify the upstream regions of Rv0561c and Rv0560c from PfuUltra Hot Start high fidelity DNA polymerase (Stratagene), 1× buffer, 0.5 mM dNTPs, 10 pmol of each primer, 5 µL DMSO, and 10 ng template. The thermocycling programme used was: 94°C for 2 min, followed by 18 cycles of 94°C for 30 s, 56°C for 1 min and 68°C for 9 min, followed by 68°C for 10 min. Template was degraded using 10 units DpnI (Promega) at 37° for 2 h. 10 µL of each reaction were used to transform competent E. coli. Recombinant plasmids were isolated and sequence-verified.Amplification reactions were carried out in 50 µL total volume containing 2.5 units M. tuberculosis transformants were cultured to mid-log phase and exposed to compounds. Cells were harvested, washed and resuspended in 1 mL 10 mM Tris-Cl (pH 8) and added to 2 mL lysing matrix B tubes  on ice. Cells were disrupted using a 30 s cycle at speed 6.0 using a FastPrep™ FP120 . Extracts were centrifuged at 16000× g for 4 min and the supernatants recovered filter-sterilised through a 0.2 µm filter unit and recovered. Total protein concentration of the samples was determined using the BCA protein assay kit.Electrocompetent mycobacteria were prepared as described previously 2HPO4, 40 mM Na2PO4, 10 mM KCl, 1 mM MgSO4, pH 7) was added. Samples were pre-warmed to 37°C for 5 min and 200 µL of 4 mg mL−1 ONPG was added. Reaction mixtures were incubated at 37°C and reactions were stopped with 500 µL of 1 M NaHCO3 after 30–90 min. The OD420 was measured and ß-galactosidase activity was calculated as Miller units (MU) = amount of O-nitrophenol produced (nmol) per min per mg of total protein, using the following formula: Units = (OD420×1.7)/(time (min)×volume of cell-free extract (mL)×total protein concentration (mg mL−1)×0.0045).Assays of ß-galactosidase activity were carried out as previously described


In Parl−/− cells accumulation of IMS-OPA1 is blunted and conditioning fails to protect from cytochrome c release and apoptosis. Thus, the OPA1/PARL dependent pathway of cristae remodeling is implicated in heat shock. This article is part of a Special Issue entitled: 17th European Bioenergetics Conference (EBEC 2012).The mitochondria-shaping protein optic atrophy 1 (OPA1) has genetically distinguishable roles in mitochondrial morphology and apoptosis. The latter depends on the presenilin associated rhomboid like (PARL) protease, essential for the accumulation of a soluble intermembrane space form of OPA1 (IMS-OPA1). Here we show that OPA1 and PARL participate in the heat shock response, a stereotypical cellular process of adaptation to thermal stress. Upon heat shock, long forms of OPA1 are lost and mitochondria fragment. However, mitochondrial fusion is dispensable to maintain viability, whereas IMS-OPA1 is required. Upon conditioning—a process of mild heat shock and recovery—IMS-OPA1 accumulates, OPA1 oligomers increase and mitochondria release less cytochrome  ► Heat shock causes cleavage of the cristae regulator OPA1. ► Heat shock causes PARL-dependent accumulation of soluble antiapoptotic OPA1. ► Soluble OPA1 confers secondary resistance to apoptosis to heat shocked cells. ► OPA1 is essential also for heat shock conditioning. Mitochondrial shapes vary depending on the organism, the cellular type, the metabolic state and the environmental conditions c during apoptosis Drosophila melanogaster cleaves the orthologs of OPA1 Morphological and ultrastructural alterations accompany the recruitment of mitochondria by the cell death pathway, including fragmentation of the network When cells are exposed to stressful stimuli that results in the inhibition of protein synthesis, such as mRNA translation inhibitors and UV irradiation, mitochondria undergo hyperfusion c and with the other released cofactor AIF in the cytosol In addition to nutrient availability, cells can respond efficiently also to changes in temperature by activating the so called heat shock response. In response to thermal stress, cells synthesize and accumulate heat shock proteins (HSPs), chaperones or proteases that protect the cell in response to potentially damaging conditions c and AIF cofactor released in the cytosol One of the most remarkable aspects of the heat shock response is that upon transient exposure of cells to mild heat stress, it renders cells resistant to further cellular insults. This might be linked to the ability of overexpressed HSPs to block apoptosis. HSP27 and HSP70, two main heat shock response proteins, prevent apoptosis at a post-mitochondrial level, by interacting with cytochrome Here we analyzed whether OPA1 participates in the heat shock response. We show that upon heat shock the antiapoptotic soluble form of OPA1 accumulates in mitochondria and that this accumulation favors heat stress-induced tolerance against subsequent apoptotic cell death. A genetic analysis proved that the rhomboid protease PARL participates in cellular adaptation to heat shock by impinging on soluble OPA1. Thus, our data suggest a role for OPA1 in heat stress-induced cytoprotection against apoptotic stimuli.22.12 as previously described 2 incubator at 42 °C (for mild heat stress) or at 45 °C (for severe heat stress) for the time indicated. For conditioning, cells were exposed to mild heat shock followed by recovery at 37 °C.Mouse embryonic fibroblasts (MEFs) of the indicated genotype were cultured at 37 °C in 5% CO2.24 MEFs were seeded in plastic dishes containing a glass coverslip. After 24 h cells were transfected with mitochondrial yellow fluorescent protein (mtYFP) for imaging of live cells or immunostained with a FITC-conjugated anti TOM20 antibody. Heat shock treatment of cells started 20 h post-transfection. Images of mtYFP or FITC were acquired using a Leica TCS SP5 inverted confocal microscope equipped with a 63 ×, 1.3 NA PLANApo objective (Leica) using the appropriate excitation lasers and emission filters, as previously described 8 × 102.35 MEF cells were seeded in 12 well plastic plates, after 24 h cells were exposed to heat shock treatment for the indicated time points  and cell viability was determined by flow cytometry. For co-transfection experiments, 7 × 104 MEFs were seeded on plastic 12-well plates, after 18 h of growth cells were co-transfected with Transfectin (Biorad) and 24 h post transfection cell viability was determined by flow cytometry. Cells were harvested and stained with propidium iodide (PI) and Annexin-V-FITC (Bender) according to manufacturer's protocol. Flow cytometry analyses were performed using a FACS Calibur cytometer (Becton-Dickinson). Viability was measured as the percentage Annexin-V, PI negative cells.1.2 × 102.4g and the pellet fraction was washed with 150 mM KCl, 10 mM KPi (pH 7.4). Proteins in the pooled supernatant fractions were precipitated with 10% TCA. Soluble and membrane associated mitochondrial proteins were contained in the supernatant fraction and the pellet fraction contained membrane integrated proteins. Samples were solubilized in loading buffer, resolved by SDS-PAGE and analyzed by Western blot.Mitochondria were isolated from MEFs by differential centrifugation as described previously c release and BAK crosslinking in response to recombinant cBid were measured as described previously Cytochrome 33.1Opa1 gene, and of proteolytic processing of the OPA1 protein, two long and three short forms of OPA1 can be retrieved upon immunoblotting of MEFs lysates In order to address if changes in mitochondrial shape participate in the cellular response to heat shock we first decided to inspect the morphology of the mitochondrial network after exposure of cells to heat stress. Following exposure of wild type MEFs to mild heat shock (42 °C), confocal microscopy of the outer mitochondrial membrane protein TOM20 in fixed cells and of mitochondrial YFP in live cells (not shown) showed consistent mitochondrial network fragmentation whose extent was dependent on the time of heat treatment A and B. 3.2c release depends on PARL Opa1−/− MEFs exposed to mild heat shock (42 °C), we could not detect any death for up to 8 h (not shown). We therefore decided to turn to severe heat shock (45 °C), upon which we could also observe an increase in the levels of HSP27, cleavage of OPA1 and at later time points cleavage of the caspase substrate PARP Parl−/− MEFs (Parl−/− MEFs (not shown). These changes were accompanied by mitochondrial fragmentation and aggregation, as testified by the confocal imaging of the mitochondrial network labeled with a mitochondrially targeted YFP  Parl−/− MEFs  the lack of PARL did not affect the heat shock response, as judged by the efficient accumulation of HSP27. In addition, cleavage to lower molecular weight forms of OPA1 was as efficient as in wild type cells A. We thechondria A. The re3.4c release Parl−/− MEFs where we could observe that upon heat shock and thermal conditioning, accumulation of lower molecular weight forms of OPA1 was delayed in Parl−/− MEFs (Parl−/− MEFs (c release during apoptosis c release in response to recombinant caspase 8 cleaved BID (cBID) in mitochondria purified from conditioned wild type and Parl−/− MEFs. Thermal conditioning of cells leads to a reduced release of cytochrome c from wild type but not from Parl−/− mitochondria  Parl−/− cells do not accumulate soluble OPA1 during heat shock and a soluble OPA1 can complement their death defect; (iv) upon conditioning by mild heat shock, the accumulation of soluble OPA1 results in increased OPA1 oligomerization, resistance to cytochrome c release and to secondary apoptosis that are all abolished in cells lacking Parl. Thus, our data extend the role of mitochondrial morphology to the regulation of heat shock response and indicate that this depends on the antiapoptotic function of the OPA1–PARL couple.In this study we show a role for OPA1 and PARL in the regulation of the response of the cells to heat shock. Several lines of evidence indicate that production of soluble OPA1 by PARL is required to protect cells from severe thermal stress and to render them resistant to a secondary apoptotic insult: (i) during thermal stress mitochondria fragment as a consequence of OPA1 cleavage; (ii) cells lacking Saccharomyces cerevisiae depends on the rhomboid protease Pcp1p Parl−/− MEFs . It is therefore unlikely that OPA1 is a heat shock protein in a classic way, i.e. whose levels are regulated by heat shock response elements Parl−/− cells can be complemented by soluble OPA1 c release and apoptosis.The mitochondrial function of PARL has been a matter of intense debate. While mice lacking this protease are affected by multisystemic apoptosis and In summary, our data identify a role for the antiapoptotic OPA1/PARL couple in the regulation of the response to thermal stress, broadening our knowledge of the processes regulated by mitochondria-shaping proteins.LKSS and LS conceived the research, analyzed the data and wrote the manuscript; LKSS performed the experiments.


Systemic Onset Juvenile Idiopathic Arthritis (SoJIA) is characterized by systemic inflammation besides arthritis. SoJIA has a broad differential diagnosis. In a minority of SoJIA patients, it takes time (weeks to months) before arthritis develops. These cases are challenging for clinicians, as is the question how and when to treat these patients.to identify SoJIA patients before the onset of arthritis and to evaluate treatment with recombinant IL-1RA (Anakinra) in these ‘suspected SoJIA’ patients.We characterized the systemic inflammation in 5 Â´suspected SoJIAÂ´ patients and compared them to our cohort of known SoJIA patients. These 5 patients were thoroughly checked for alternative diagnoses by extensive microbial analysis , radiological evaluation (including CT and/or PET scans) and genetic testing where appropriate. Moreover, bonemarrow aspirates were performed to rule out leukemia and haemophagocytosis.Biochemical and immunological parameters of disease activity  as well as newly developed biomarkers for SoJIA (cytokine profiles (IL-18), MRPÂ´s, NK cell numbers, phenotype and lytic function) were assessed at onset of disease and during treatment with Anakinra.The 5 ‘suspected SoJIA’ patients were clinically and immunologically very similar to our cohort of SoJIA patients table  at time Here we show that, making use of recently developed biomarkers, `suspected SoJIAÂ´ patients can be identified very early in their disease-course, before the development of arthritis. These patients show a similar beneficial clinical response to treatment with recombinant IL-1RA as our cohort of newly diagnosed SoJIA patients. Our data support the idea of early treatment with recombinant IL-1RA in (suspected) SoJIA patients.


Our hypothesis was that human activities alter the energy budget of the reef system, specifically by altering the allocation of metabolic energy between microbes and macrobes. To determine if this is occurring on a regional scale, we calculated the basal metabolic rates for the fish and microbial communities at 99 sites on twenty-nine coral islands throughout the Pacific Ocean using previously established scaling relationships. From these metabolic rate predictions, we derived a new metric for assessing and comparing reef health called the microbialization score. The microbialization score represents the percentage of the combined fish and microbial predicted metabolic rate that is microbial. Our results demonstrate a strong positive correlation between reef microbialization scores and human impact. In contrast, microbialization scores did not significantly correlate with ocean net primary production, local chla concentrations, or the combined metabolic rate of the fish and microbial communities. These findings support the hypothesis that human activities are shifting energy to the microbes, at the expense of the macrobes. Regardless of oceanographic context, the microbialization score is a powerful metric for assessing the level of human impact a reef system is experiencing.The majority of the world's coral reefs are in various stages of decline. While a suite of disturbances  have been identified, the mechanism(s) of reef system decline remain elusive. Increased microbial and viral loading with higher percentages of opportunistic and specific microbial pathogens have been identified as potentially unifying features of coral reefs in decline. Due to their relative size and high per cell activity, a small change in microbial biomass may signal a large reallocation of available energy in an ecosystem; that is the  The relationship between increasing human activity and decreasing fish biomass is well-established in coral reef systems Despite the epidemiological evidence linking the microbial ecology of coral reef systems to human activity, the largest study of coral reef microbial communities included only four coral atolls in the Line Islands, all clustered within one oceanographic region I), defined as the amount of energy per unit time that an individual organism requires, is calculated using E is the activation energy, k is Boltzmann's constant (8.62×10−5 eV K−1), and T is the water temperature at the site at the time of collection (in Kelvin). Distinct scaling exponents have been derived for different physiological states and evolutionary groups Ecosystems exhibit higher-level properties resulting from lower-level phenomena microbialization3 volume of reef water. Microbialization refers to an increase in the percentage of the combined fish and microbial predicted metabolic rate that is microbial. Island-level microbialization scores were derived for 29 islands (99 sites) within four oceanographic regions of the Pacific Ocean. Our data show a strong significant positive correlation between microbialization scores and the NCEAS cumulative human impact scores at each island. In comparison, microbialization scores did not correlate with the net primary production values. These findings support the hypothesis that human activities rather than variation in oceanographic conditions are causing microbialization of coral reefs and that the microbialization score is a powerful metric for assessing and comparing reef health.The process of replacing macroorganisms with microbes has been termed The twenty-nine islands included in this study were surveyed following the National Oceanic and Atmospheric Association (NOAA) 's Rapid Ecological Assessment (REA) protocol as part of the Coral Reef Ecosystem Division (CRED) and Pacific Reef Assessment and Monitoring Program (Pacific RAMP) −1 DAPI  within 2 hours of collection V) was calculated by considering all cells to be cylinders with hemispherical caps using l is length and w is width 3) were converted to mass in wet weight (g) using previously established size-dependent relationships for marine microbial communities V was next converted to dry weight using the linear relationship derived from data reported in Simon and Azam (1989) and shown in x is cell dry weight and y is cell volume (r2 = 0.99). Then cell wet weight (z) was calculated using the linear relation shown in 2 = 0.99):At each site, 4 replicate 2 l seawater samples were collected ∼1 m above the benthos using polycarbonate Niskin bottles. Microscopy grade glutaraldehyde was added to a final concentration of 0.3% v/v. Microbial cells were collected from each sample by filtration using a 0.2 µm Anodisc filter (Whatman) and then stained with 5 µg ml−2) and mean abundance , from which the mean mass per individual (g) was calculated. Because surveys were carried out at an average water depth of 10 m and surveyors counted all fish in the water column up to the surface, the mean abundances  represented the total number present in a 10 m3 water column.This study includes fish data from all surveys performed at REA sites during the years 2001–2009. The number of REA sites surveyed over this time period is provided for each island in I) for all fish or microbes present in a standard volume of water (10 m3). Individual metabolic rates (I) in watts were calculated using At each REA site, community-level metabolic rates were calculated by summing the individual metabolic rates  was extracted from the plots in Brown et al. 16 and 1.08×1021, respectively) were calculated from previously reported individual prokaryote metabolic rate values E) used were 0.61 eV for microbes The mass independent normalization constant for fish, ihttp://www.nceas.ucsb.edu/globalmarine/impacts). Using ArcGIS 9.3, “NoData” pixels corresponding to the land mass of each island were identified and converted into polygon format. A 10 km zone was then calculated for each of these polygons, representing the immediate 10 km of sea surface around the border of each island in the study. Using these zones, statistics were then performed on the NCEAS human impact raster in order to calculate the mean impact score. These scores incorporate data related to: artisanal fishing; demersal destructive fishing; demersal non-destructive, high-bycatch fishing; demersal non-destructive low-bycatch fishing; inorganic pollution; invasive species; nutrient input; ocean acidification; benthic structures ; organic pollution; pelagic high-bycatch fishing; pelagic low-bycatch fishing; population pressure; commercial activity ; and anomalies in sea surface temperature and ultraviolet insolation.The level of human impact was assessed from the cumulative global human impact map generated by the National Center for Ecological Analysis and Synthesis ; the dissimilarity matrix was calculated using Gower's standardization Other indicators of reef system health were also considered in this study using benthic survey data collected at the same time as the microbial data. Benthic surveys were performed using the survey methodology described in Vargas-Angel −2 day−1) were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data using the Vertically Generalized Production Model . This model, based on an algorithm by Behrenfeld and Falkowski (1997) calculates net primary production from satellite-based measurements of surface chla concentrations, while also taking into account sea surface temperature, daily photosynthetically active radiation, and a temperature-dependent photosynthetic efficiency factor a concentrations (µg l−1) used in this study were obtained using fluorometric analysis a samples were collected in conjunction with the microbial samples at each site.Productivity estimations for net primary productivity (NPP) (mg C m3) and basal metabolic rate (W per 10 m3) for both the water column-associated microbial and fish communities (3) and Wake Atoll (0.12 g per 10 m3), respectively. This difference in microbial biomass equates to a 76-fold increase in the rate of energy flux (W per 10 m3 or J sec−1 10 m−3) on Oahu (0.076 W per 10 m3) relative to Wake Atoll (0.001 W per 10 m3). The highest fish biomass was found on Kingman (514.84 g per 10 m3) and the lowest on Guam (17.98 g per 10 m3). The metabolic requirements predicted for the fish communities on Kingman and Guam were 0.015 and 0.002 W per 10 m3, respectively. This difference equates to a 7.5-fold reduction in the metabolic requirements of the fish community. The largest differences in the predicted metabolic rates between each island represent a 100-fold change for the microbes, as compared to a 14-fold change for the fish  but a relatively low NCEAS score (8.48). In actuality, Johnston is heavily impacted by factors not reflected in the NCEAS scores including the addition of two artificial islands with paved runways formed by coral dredging, usage for both above-ground and underground nuclear tests in the 1950s and 1960s, and service as a chemical weapons depot until 2000. The microbialization score appears to be a better indicator of these stressors than the NCEAS index of human impact.n data points in d dimensions, into k clusters, so that the within clusters sun-of-squares is minimized k) indicated k = 3 to be the optimal number (for k = 2–8). The 11 islands contained in cluster two (within-cluster sum of squares = 1.47) were negative for PC1 (k-means cluster were Lanai (LAN) and Guam (GUA) (within cluster sum-of-squares = 0.32).A principal components analysis was carried out with the goal of visualizing how the microbialization score related to other indicators of reef health, including coral disease prevalence, prevalence of coral colonies with other signs of compromised health, percent crustose corraline algae cover, and percent coral cover . The fir for PC1 , while t3 on Rota Island (MARIANA) to a high of 0.077 W per 10 m3 on Oahu (MHI)  , x-axis.hu (MHI) , y-axis.Net primary production (NPP) might be expected to be a significant factor driving variation in community metabolic rates. Previous small-scale inter-island studies that correlated differences in microbial communities with varying local human impacts could not conclusively rule out inter-island variations in oceanographic conditions as a possible driving factor −2 day−1) derived from satellite data is shown in −2 day−1 at Aguijan to 445 mg C m−2 day−1 at Jarvis  explained even less of the inter-island variation in combined predicted metabolic rate  or nearshore chla concentrations (2 = 0.22). However, higher nearshore chla concentrations associated with microbialization scores above a certain threshold (∼70%) are suggestive of eutrophication processes linked to human impact , y = β0+β1(NCEAS)+β2(chla), y = β0+β1(NCEAS)+β2(NPP), y = β0+β1(NCEAS)+β2(chla)+β3(NPP). Given that the NCEAS score was in the model, the p-values for chla and NPP were not significant by the t-test in the second and third models . The only variable that was significant was the NCEAS score, having a highly significant p-value in all of the models . The model which included both chla and NPP as variables (y = β0+β1(NCEAS)+β2(chla)+β3(NPP)) gave a multiple R2 value of 0.706, which was not a significant improvement over the simplest model (y = β0+β1(NCEAS)) which explained 68.4% of the variability of the microbialization score.To further examine whether or not accounting for oceanographic context would improve our ability to predict reef microbialization, multiple linear regression analysis was performed. In addition to the NCEAS score, satellite-based estimates of net primary production (NPP) and nearshore [chl0+β1(NCEAS)). Although the exact mechanism(s) underlying the process of microbialization remain unclear, these analyses support the hypothesis that human activities alter the energy budget of the reef system, specifically by altering the allocation of metabolic energy between microbes and macrobes.Next, Akaike's Information Criterion (AIC) was used for model selection between the 4 different statistical models. AIC is the most widely known and used model selection criterion which consists of a “goodness-of-fit” term and a “penalty” term for increased number of model parameters a concentrations, or the combined metabolic rate of the fish and microbial communities suggests that the microbialization score may be a powerful metric for comparing and assessing reef degredation, particularly at large spatial scales. Other measures of reef degredation which are more heavily influenced by oceanographic context  may be more easily confounded by non-human factors and are subsequently harder to interpret across large spatial scales.The finding that microbialization scores did not significantly correlate with ocean net primary production, local chlIn this study, surveys of microbial and fish sizes were used to predict whole organism metabolic rates. Ideally, the energetic requirements per unit time for fish and microbial communities would be measured empirically. However, this is not practical over this large region. To evaluate whether or not the MTE-based approach is a reasonable alternative to quantifying energy flux, the mean predicted metabolic rates for microbial communities were compared against experimental values reported from other studies . The mea2 value for the regression analysis of community-level metabolic rate as a function of biomass by only 0.01% and 0.05% for fish and microbes, respectively. Therefore, inter-island variation in temperature does not account for our observed trends.Similarly, differences in temperature at the time of sampling explained a small proportion of the variation in metabolic rate between islands. Water temperature at the time of sampling ranged from 25–30°C. For the microbial community-level metabolic rates, the standard deviation in the 29 island data set was 0.16 at the actual temperatures and 0.01 when all locations were corrected to the same temperature (20°C); for the fish community-level metabolic rates, the standard deviations were 0.006 and 0.003, respectively. Temperature correction increased the rmicrobialization. The data presented here supports this hypothesis over a wide swath of Pacific coral reefs and suggests that microbialization is a general process of reef decline. Although the exact mechanism(s) driving the process of microbialization remain unclear, the microbialization score provides a way to diagnose the degree of microbialization that has occurred on reefs. Fish were the primary movers of energy in the most pristine locations  and Kingman (PRIA), respectively) but made up only 3% of the total predicted metabolic rate on Oahu (MHI). Microbialization scores reflect both increased microbial biomass and decreased fish biomass; however microbial biomass has a proportionately greater impact on metabolic rate. This means that even a minor increase in the microbial load results in a substantial shift in community energy use; up to a 100-fold increase in the metabolic requirements of the microbes in the most heavily impacted reef systems. This study has significant implications for the protection of coral reefs. The degree of microbialization a reef is experiencing may be important for predicting its response to perturbation. On Pacific coral reefs, microbialization may be set in motion by an increase in the percent cover of turf algae resulting from the loss of herbivorous fish. Turf algae release large amounts of dissolved organic carbon (DOC) into the water column, a source of energy almost exclusively available to the microbes Overfishing, eutrophication, and global climate change are important drivers of the global loss of coral reefs. However, the precise mechanism(s) by which these perturbations lead to coral decline have remained elusive. We and others have previously argued that human activities are favoring the coral reef-associated microbes at the expense of the macrobes, a process called Figure S1Principal components analysis of reef system properties related to reef health. The first two principal components account for 66% of the variability in the dataset . Arrow length reflects the relative contribution of a variable to a PC axis. MS = microbialization score; CCA = % crustose coralline algae cover; DZ = % coral disease prevalence; CO = % coral cover; CH = % coral with other indications of compromised health. Symbol denotes oceanographic region: Guam and the Mariana Islands (*), the Main Hawaiian Islands (∧), Pacific Remote Islands and Atolls (#), and the Samoa region (+). Two groups of islands identified from k-means cluster analysis are divided along PC1 by the dotted line; the third group is circled (Lanai and Guam). For island abbreviations, see (TIF)Click here for additional data file.Figure S2Mean microbial and fish biomass. (a) Mean microbial biomass with standard error. Total number of sites where microbial data was collected = 99. (b) Mean fish biomass with standard error. Total number of sites where fish data was collected = 791. The number of REA sites included is given in parentheses next to three-letter island code.(TIF)Click here for additional data file.Table S11–5.Comparison of mean MTE-based microbial metabolic rate predictions from this study with experimental measurements from marine systems Rates of photosynthesis were converted from units of gross carbon production (Pg) to units of power (W) using 39,444 J g−1 C, the standard free energy change from the synthesis of glucose from CO2 and H2O during photosynthesis at STP6. For conversion between rates of oxygen consumption or production in volume or mass units, we assumed that 1 ml O2 per second = 1.43 mg O2 per second24. To convert between units of power (W) and rates of respiration we assumed that 1W = 0.05 ml O2 per second24. Metabolic rates in W per 10 m3 were derived after calculating total daily energy use: Pg (from sunrise to sunset) + Respiration (over a 24 hour period). In studies where only dark incubation experiments were performed, total daily energy use was calculated assuming Pg/R24 hrs = 1. When two measurements are listed for the same sample and conditions, they indicate high and low values. B = predicted basal metabolic rate; A = predicted active metabolic rate.(XLSX)Click here for additional data file.Table S2Summary table showing the number of REA sites where microbial or fish data (belt transect method only) was collected, time period of sampling, and standard error for biomass and abundance of the fish and microbial communities at each island.(XLS)Click here for additional data file.Table S3Summary table for  The importance of each component and the contribution (loadings) of each variable is shown. MS = microbialization score; CCA = % crustose coralline algae cover; DZ = % coral disease prevalence; CO = % coral cover; CH = % coral with other indications of compromised health.(XLS)Click here for additional data file.


The majority of animal associated microorganisms are present in digestive tract communities. These intestinal communities arise from selective pressures of the gut habitats as well as host's genotype are regarded as an extra ‘organ’ regulate functions that have not evolved wholly on the host. They are functionally essential in providing nourishment, regulating epithelial development, and influencing immunity in the vertebrate host. As vertebrates are born free of microorganisms, what is poorly understood is how intestinal bacterial communities assemble and develop in conjunction with the development of the host.Set within an ecological framework, we investigated the bacterial community assembly and turnover within the intestinal habitats of developing zebrafish . Spatial and temporal species-richness relationships and Mantel and partial Mantel tests revealed that turnover was low and that richness and composition was best predicted by time and not intestinal volume (habitat size) or changes in food diet. We also observed that bacterial communities within the zebrafish intestines were deterministically assembled (reflected by the observed low turnover) switching to stochastic assembly in the later stages of zebrafish development.This study is of importance as it provides a novel insight into how intestinal bacterial communities assemble in tandem with the host's development (from early to adult stages). It is our hope that by studying intestinal microbiota of this vertebrate model with such or some more refined approaches in the future could well provide ecological insights for clinical benefit. In addition, this study also adds to our still fledgling knowledge of how spatial and temporal species-richness relationships are shaped and provides further mounting evidence that bacterial community assembly and dynamics are shaped by both deterministic and stochastic considerations. Animal species have evolved through time in microbial-rich environments where they exist in intimate associations with microorganisms and their communities; which play key roles in the vertebrate host's development Danio rerio) as they possess several unique features that make them an attractive model vertebrate organism to address this question. First, the transparent zebrafish larvae (from time of fertilization through to early adulthood) are a convenient model to perform in vivo observations of intestinal bacteria Within the current study we used zebrafish  which has been used to prioritize conservation efforts particularly in the SLOSS  debate Initially, microbial based studies of SARs and STRs were performed to assess the form of those relationships and how they compared to studies of animal and plant species see  and moreWithin the present study we investigated patterns of diversity of the intestinal microbiota from individuals of developing zebrafish   using 16r2 = 0.46; F1,28 = 23.91; P<0.0001), although there were occasional outliers to this relationship. These anomalies could be attributed to random sampling and the individual variability may partly arise from developmental differences between individuals. The difference between male and female animals in later stages is another important factor, as female zebrafish are typically larger than males in the adult stages of development  gene fragments was used to evaluate the composition of bacteria colonizing the intestines of zebrafish at different stages of development . For eacelopment .S = zcV. Where S is the number of bacterial taxa (DG-DGGE bands) inhabiting an intestine of volume V, c (the intercept) is an empirically derived taxon- and location-specific constant, and z is the slope of the line  Tz was changed to w, so that the STR power law becomes S = wcTz = 0.029 and w = 0.075, t-distribution method t = 1.66; d.f. = 1,56; P = 0.102). Using this test allowed us to statistically determine that the SVR and STR did indeed have similar scaling exponents as predicted by Preston r2 = 0.63; F8,29 = 4.41; P<0.003) and not volume, diet, or any combination of the three potential predictors  best predicted community turnover . AlthougSimilarities and differences in the composition of the bacterial communities within and between adjacent stages of development were assayed using the Sørensen index of similarity . Within SRC), the stochasticity and determinism in the data was investigated by recording within and between adjacent developmental stage samples taken pair-wise, whose compositional similarities were not more or less expected by chance (0.95>SRC>0.05) or significantly similar (SRC>0.95) or dissimilar (SRC<0.05). From 6 to 75 dpf within developmental stage SRC values remained constant at 1.00±0.00, decreasing to 0.95±0.07 and still significantly similar at 90 dpf, and then less than 0.95 to 0.61±0.43 at 105 dpf  or deterministic (niche) considerations, bacterial community profiles were compared using a Monte Carlo procedure to determine whether any two samples were more or less similar than would be expected by chance. Using the Raup and Crick probability-based similarity index  has been shown to be consistent across animal and plant species, but differs between islands (0.2 – 0.39) and non-isolated sample areas of contiguous habitat (0.1 – 0.2) w) ranged from 0.1 – 0.51 z and w. These analyses indicated that turnover of bacterial taxa within the zebrafish intestines was low. In addition, time was found to be the main predictor of both bacterial richness , where w decreased as selective pressure  increased  Two previous independent microbial studies have demonstrated that temporal scaling exponent values reflect the degree to which a community is influenced by both deterministic and stochastic considerations where low turnover is indicative of deterministic (niche driven) processes at work. For example, van der Gast and colleagues w = 0.31±0.05) formed from more diverse metacommunities when compared to local communities formed from less diverse source communities (w = 0.16±0.02) In a recent study, Ayarza and Erijman In the current study, we observed that bacterial communities within the zebrafish intestines were deterministically assembled (reflected in the low STR exponent) switching to stochastic/random assembly in the later stages of zebrafish development . What isIn conclusion, as humans and other vertebrates are essentially born free of microorganisms All experiments involving zebrafish were performed under protocols approved by the Institutional Animal Care and Use Committee of Institute of Hydrobiology, Chinese Academy of Sciences .Paramecium, from 12 to 15 dpf with 20 µm mesh filtrated boiled egg yolk, and subsequently feeding with brine shrimp. The faeces and leftover food were removed timely to keep a clean environment.Wild-type zebrafish (AB strain) were reared using universal glass aquarium systems under standard laboratory conditions. In brief, fully aerated tap water was used during the experiment, and a stable water temperature (28±0.5°C) as well as 14/10 hours light/dark cycle were strictly controlled to decrease possible effects from environmental perturbation. Zebrafish embryos were obtained from spawning adults as previously described As zebrafish larvae only resorb the yolk until the gut is fully functional by the 5 dpf Intestinal volume was used as being indicative of ‘whole-habitat’ size in the present study. Volume was calculated using standard volumetric equation for cylinder as previously described 2), 2 mM MgCl2, 0.05 unit/µl Taq DNA polymerase (MBI Fermentas), 80 µM of each deoxynucleotide triphosphate (MBI Fermentas), approximately 1 ng/µl DNA template, and 0.3 µM of each bacterial target primer 357F-GC (Escherichia coli 16S rDNA positions 341 to 357) and 518R (E. coli 16S rDNA positions 518 to 534) Each collected intestinal sample was initially incubated in buffer ASL (provided with Qiagen DNA extraction Kit) at 70°C water bath for 1 minute, and then homogenized by repeated passage through a 20-gauge needle as previously described Approximately equal amounts of PCR product from each sample were separated on a double gradient polyacrylamide gel. DG-DGGE analysis was performed with a DCode™ system (Bio-Rad) using 7.5–9.0% polyacrylamide gel (acrylamide: bisacrylamide = 37.5: 1) with a 40–50% denaturing gradient. Electrophoresis was performed at 60°C with 100 V for 12 h according to the method described previously The number of bands present in a sample  was usedSSOR) using the PAST program available from the University of Oslo website link (http://folk.uio.no/ohammer/past) run by Øyvind Hammer. In the current study we used both differences in habitat size (volume) and temporal difference between samples taken pair-wise instead of geographical difference. In addition, using Mantel and partial Mantel tests allowed us to determine how patterns of beta diversity are influenced by environmental factors To examine differences in bacterial beta diversity, similarities and differences in community composition were determined using the Sørensen index of similarity (SRC) SRC was chosen as this measure has advantages over non-probability based similarity indexes, such as the Jaccard or Sørensen coefficients, when comparing the diversities of binary data such as DGGE bands SRC provides a measure of statistically significant similarity and dissimilarity at the 95% confidence level, and is less affected by sampling bias SRC values above 0.95 or below 0.05 signify differences, which are not random assortments of the same species (bands) SRC was calculated using the PAST program.Band matching data were stored as a binary matrix and analyzed using the Raup and Crick probability-based index of similarity (r2), residuals and significance (P) were calculated using software of Minitab 15 . The t-distribution method was used to compare the regression line slopes as described in Fowler and colleagues GLMs, regression analyses, coefficients of determination  comparison of the adult individuals. Asterisks indicate significant difference between female (♀) and male (♂) zebrafish within stage (two-tailed Student's t-test).(TIF)Click here for additional data file.Figure S2DG-DGGE patterns of the amplified 16S ribosomal RNA (rRNA) gene fragments, each band was considered as an operational taxonomic unit (OTU). For each sample code, the number represents days post-fertilisation (dpf) and the letter refers to a different zebrafish individual sampled at that dpf (to be continued).(TIF)Click here for additional data file.Table S1DG-DGGE presence-absence profiles for bacterial communities sampled from the intestines of different zebrafish individuals over development time.(DOC)Click here for additional data file.Table S2General linear models and summary statistics.(DOC)Click here for additional data file.Text S1Intestine removal methods.(DOC)Click here for additional data file.


Saccharomyces cerevisiae strains of the ∑1278b background generate biofilms, referred to as mats, on low-density agar (0.3%) plates made with rich media (YPD). Mat formation involves adhesion of yeast cells to the surface of the agar substrate and each other as the biofilm matures, resulting in elaborate water channels that create filigreed patterns of cells. The cell wall adhesion protein Flo11p is required for mat formation; however, genetic data indicate that other unknown effectors are also required. For example, mutations in vacuolar protein sorting genes that affect the multivesicular body pathway, such as vps27∆, cause mat formation defects independently of Flo11p, presumably by affecting an unidentified signaling pathway. A cell wall signaling protein, Wsc1p, found at the plasma membrane is affected for localization and function by vps27∆. We found that a wsc1∆ mutation disrupted mat formation in a Flo11p-independent manner. Wsc1p appears to impact mat formation through the Rom2p-Rho1p signaling module, by which Wsc1p also regulates the cell wall. The Bck1p, Mkk1/Mkk2, Mpk1p MAP kinase signaling cascade is known to regulate the cell wall downstream of Wsc1p-Rom2p-Rho1p but, surprisingly, these kinases do not affect mat formation. In contrast, Wsc1p may impact mat formation by affecting Skn7p instead. Skn7p can also receive signaling inputs from the Sln1p histidine kinase; however, mutational analysis of specific histidine kinase receiver residues in Skn7p indicate that Sln1p does not play an important role in mat formation, suggesting that Skn7p primarily acts downstream of Wsc1p to regulate mat formation. Saccharomyces cerevisiae is an attractive fungal model system to study genes important for biofilm formation because it is capable of forming an elaborate multicellular biofilm (hereafter referred to as a mat) on semi-solid agar (0.3%) and is easily manipulated genetically. The S. cerevisiae mat grows into a wheel-like structure that can be visually differentiated into a central wrinkled hub consisting of water channels, some of which resemble spokes of a wheel, all surrounded by a growing smooth rim   genes affect mat formation through pathways that directly affect Flo11p or act parallel to this pathway. The pathway that acts parallel to the Flo11p-dependent pathway is called the biofilm pathway, and it requires an intact and fully functional multivesicular body (MVB) pathway involving the endosome (The ability to form biofilms in fungi is largely dependent on various GPI-anchored adhesion proteins of the flocculin (FLO) family that are localized to the cell wall. Wsc1p is the main sensor for the wall), a Rho-type GTPase and its guanylate exchange factor (GEF) , a protein kinase C homolog (Pkc1p), and a MAP kinase (MAPK) cascade (Bck1p-Mkk1/Mkk2p-Mpk1p) .There are a number of pathways that affect the cell wall. One that has components affected by the MVB pathway is the cell wall integrity pathway (CWI). The CWI pathway consists of several signaling modules that include a family of single transmembrane domain sensors (p-Mpk1p)   and relaying them downstream, leading to activation of appropriate genes that encode proteins that remodel the cell wall. In addition to Pkc1p and the CWI–MAPK cascade, Rho1p also directly regulates the Fks1p β-1,3-glucan synthase and the Skn7p transcription factor, both of which affect the cell wall. Data are presented revealing that components of the CWI pathway, including the Wsc1p receptor but excluding the CWI–MAPK cascade, are required for mat formation and therefore may comprise a part of, or the entire, biofilm signaling pathway.Activation of the CWI pathway has pleiotropic effects on cell wall repair and biogenesis. The main functions of the CWI pathway are maintenance of the highly dynamic cell wall structure by sensing signals  was placed over the biofilm and removed with both hands. This removed cells that were not agar-adherent.The overlay adhesion assay was performed as described  to detect cell wall damage and activate the pathway . A defect in Wsc1p signaling can lead to increased sensitivity to cell wall–perturbing factors like high temperature, calcofluor white, and caffeine  that can be stained using anti-HA antibody  were used. The mat cells were subjected to subcellular fractionation to separate populations of Flo11p that were shed extracellularly (S), covalently attached to the wall (C), and found in the membrane (M), and these were analyzed by SDS-PAGE and Western blotting using an anti-HA antibody ; thus, its mat formation defects were not a consequence of growth defects.One initial concern was that because the Wsc1p is an important sensor of the CWI pathway , so we wanted to determine what downstream components of the pathway are required for mat formation. Deletion mutants of different components were analyzed for their effects on mat formation. Loss of other sensors of the Wsc family  and Mid2p failed to cause any defect in mat formation, suggesting that Wsc1p is the major sensor of the CWI pathway for mat formation (data not shown). No mutants were generated for PKC1 and RHO1 because these genes are essential . None of these mutations led to a defect in mat formation . This is similar to what was seen in the vps27∆ mutant . The wild-type, vps27∆, and wsc1∆ mutants exhibit very few single cells in comparison .wnstream . When boWsc1p acts through Rom2pvs. some other signaling module to affect mat formation specifically, given the pleotropic effect of a complete rom2∆ disruption, residues in the Wsc1p cytoplasmic tail that are known to interact with Rom2p were mutated to determine if interruption of these protein–protein interactions would compromise mat formation in a specific manner. Wsc1p to identify the residues important for Wsc1p–Rom2p interactions. They determined residues Y303, S319-320, S322-323, L369, V371, N373, and D375 to be crucial. The Y303 and L369-D375 residues were particularly important. The S319-323A mutations could actually suppress some of the other mutations. If mutations that block the Wsc1p–Rom2p interaction also block mat formation, then this will support that Wsc1p–Rom2p interactions are important for mat formation. Because Rom2p is a well-known activator of Rho1p .To better-elucidate whether WSC1 regulated by the WSC1 promoter was subcloned into a vector such that it encoded Wsc1p with a green fluorescent protein (GFP) tag on the C-terminal cytoplasmic tail. Transformation of the wsc1∆ mutant with WSC1-GFP (wsc1∆::WSC1-GFP) led to rescue of mat formation  and temperature sensitivity phenotypes , thus confirming that it is fully functional .The fusion gene of Wsc1p–Rom2p interactions were mutated to alanine. Constructs were generated that carried a single-point mutation (Y303A), double-point mutations (S319A S320A or L369A V371A), and triple-point mutations (Y303A L369A V371A). No transformants could be obtained for point mutations in the C-terminal–most region of the cytoplasmic tail  either by themselves or in combination with any other point mutations, and the reason for this is unknown.The aforementioned amino acids that mediate wsc1∆ mid2∆ double-mutant that exhibited a severe lysis defect at all growth temperatures in absence of osmotic support.None of the point mutants fully complemented the mat formation or temperature-sensitive growth defects ; howeverWsc1p mutations to fully complement the wsc1∆ phenotypes was attributable to poor expression of the mutant proteins. However, the mutated versions of Wsc1-GFP were expressed similarly to the wild-type protein . However, this slower growth rate does not explain the mat formation defect because an itr1∆ itr2∆ mutant, which also has a similar mild growth defect, still generates a mat similar to the wild-type but at a slightly slower rate . In contrast, the Wsc1-GFP mutants that failed to complement or only partially complemented, grew as well in liquid media as itr1∆ itr2∆ but still formed a defective mat. The wsc1∆::WSC1Y303A-L369A-V371A-GFP mutant grew even more slowly than the others, but the wsc1∆::WSC1L369A-V371A-GFP had a mat phenotype similar to this mutant and a growth rate similar to the itr1∆ itr2∆ mutant. Thus, growth rate clearly is not a major factor.One concern was that the failure of the  protein . Some ofWsc1p–Rom2p interaction is needed for mat formation, but the CWI–MAPK cascade is not suggests that the biofilm pathway might be mediated via Rho1p through another downstream effector. One option is the Skn7p transcription factor that acts downstream of Rho1p and parallel to the Pkc1p branch of the CWI pathway . Therefore, a skn7∆ mutant was generated and tested. This mutant is defective in mat formation  diminished its activity (SKN7 genes with point mutations pCLM699 (Skn7D427N) and pCLM700 (Skn7D427E)  should rescue the mat formation defect of skn7∆, whereas the inactive version (D427N) should fail to do so. Complementing the skn7∆ mutation with both the active and inactive mutant forms of Skn7p led to rescue of the mat formation defect of skn7∆ , whose activation has diverse effects on the cell wall , Fks1p-Fks2p , and the CWI–MAPK cascade .A surprising result from these studies is that the CWI–MAPK cascade is not involved in mat formation . This suby Rom2p . Rho1p iynthesis   signaling pathways . The genes activated by Skn7p, as a consequence of its activation through the HOG pathway via Sln1p, are not identical to those activated through the CWI pathway  or inactive (D427N) point mutants of SKN7 that either over-respond or under-respond to the Sln1p branch of the HOG pathway, respectively, were transformed into skn7Δ. Because both point mutants rescued the mat formation phenotype, it was shown that Skn7p does not act downstream of Sln1p to affect mat formation.The Wsc1p regulates mat formation by affecting the activation of the Skn7p transcription factor through the Rom2p-Rho1p module. This model is not completely proven by these data, and it is possible that other factors such as Bni1p or another unknown factor are involved, but our data suggest this model, which will be tested in the future.Taking the data altogether, we propose a model suggesting that Flo11p-independent mat formation pathway, referred to as the biofilm pathway, involves the class E vacuolar protein sorting (vps) components of the MVB pathway. It was hypothesized in our previous work  . A future goal will be to elaborate on this pathway.In addition, we recently showed that one FLO11 expression, and these were different from our findings. In addition to the differences in the way the CWI–MAPK cascade affects mat formation, the PC538 strain also differs from TRY181 in expressing FLO10 (VPS27 and other vps mutants (data not shown).We have found that the CWI pathway affects mat formation in a manner that is independent of the CWI–MAPK cascade and may be affected by endosomal sorting mutations. However, ste4∆ mutation, which could affect other signaling pathways. However, there may be other differences as well. Unraveling the differences between these strains will be valuable in understanding how mat formation is regulated in yeast.These phenotypic inconsistencies between the strains may be attributable to undefined genetic differences in PC538 and TRY181 (derived from L6906). One possible difference that could contribute is the fact that PC538 carries a


Mechanisms of visual perception should be robustly fast and provide veridical information about environmental objects in order to facilitate survival and successful coping. Because species-specific brain mechanisms for fast vision must have evolved under heavy pressure for efficiency, it has been held that different human individuals see the physical world in the same way and produce psychophysical functions of visual discrimination that are qualitatively the same. For many years, this assumption has been implicitly accepted in vision research studying extremely fast, basic visual processes, including studies of visual masking. However, in recent studies of metacontrast masking surprisingly robust individual differences in the qualitative aspects of subjects' performance have been found. As the basic species-specific visual functions very likely are based on universal brain mechanisms of vision, these differences probably are the outcome of variability in ontogenetic development . Such developmental differences can be brought about by variants of genes that are differentially expressed in the course of CNS development. The objective of this study was to assess whether visual discrimination in metacontrast masking is related to three widely studied genetic polymorphisms implicated in brain function and used here as independent variables. The findings suggest no main effects of BDNF Val66Met, NRG1/rs6994992, or 5-HTTLPR polymorphisms on metacontrast performance, but several notable interactions of genetic variables with gender, stage of the sequence of experimental trials, perceptual strategies, and target/mask shape congruence were found. Thus, basic behavioral functions of fast vision may be influenced by common genetic variability. Also, when left uncontrolled, genetic factors may seriously confound variables in vision research using masking, obscure clear theoretical interpretation, lead to unexplicable inter-regional differences and create problems of replicability of formerly successful experiments. Visual masking refers to impairment of perception of a target stimulus as a result of presentation of the masking stimulus in close spatiotemporal proximity to a target congruence influences the criterion contents subjects use in evaluating targets vis-à-vis the mask From recent experiments We examined the metacontrast effects in subjects genotyped for three functional polymorphisms known to affect brain structure: (1) serotonin (5-HT) transporter gene ins/del polymorphism (5-HTTLPR) using biallelic classification, (2) brain derived neurotrophic factor (BDNF) Val66Met polymorphism, and (3) neuregulin 1 (NRG1) a promoter polymorphism SNP8NRG243177 (rs6994992).Carriers of the 5-HTTLPR short allele display increased amygdala reactivity to fearful stimuli In the case of BDNF Val66Met polymorphism, Met allele carriers are characterized by deficits in neural plasticity and decrease of the neocortical gray matter volume NRG1 rs6994992 minor (T) allele has been associated with decreases in white matter density in the right anterior internal capsule The opportunistic sample consisted in 57 Estonian subjects  with normal or corrected-to-normal vision. The data from subjects whose correct response rate did not exceed the random correct quessing level in a particular condition were not used in the data analysis. To participate, subjects had to be in good health, having no tiredness and having consumed no alcohol or other substances potentially confounding the experimental results.Experimental procedures were approved by the Research Ethics Committee of the University of Tartu under the general project “Comparative analysis of the effects of different attentional perception paradigms by the methods of transcranial magnetic stimulation and EEG.” Subjects recruited to the study consented to an additional procedure of giving saliva samples for genotyping in a subset of experiments without TMS/EEG provided their written informed consent including the following statements: “... NB! Participation in the study is voluntary and you may at any moment to withdraw from it and/or discontinue the experiment. Data gathered during this research will not be made available to third parties in the format allowing to identify the participating person unless that person gives his/her consent to do so.” All subjects who signed the informed consent form consented to giving samples of saliva for genotyping.  Signed forms of consent are kept by the first author so as to guarantee confidentiality and all data from genotyping and metacontrast results is used in an anonymous format.2). In each trial shapes of a target and a mask were either congruent or incongruent. The spatial separation between targets' outer edges and masks' inner edges was 0.02 degrees of visual angle.Two types of stimuli were used – targets and masks. Targets were solid black squares and diamonds both subtending 1.5 degrees of visual angle in diameter; masks were prepared as black squares or diamonds subtending 2.6 degrees, with inner empty spaces shaped so as to allow the 1.5 degree targets fit in snugly within mask contours , a pseudo-randomly chosen target (23 ms), followed either by a mask or by a fixation field which in turn was followed by a pseudo-randomly chosen mask (105 ms). Thus, SOAs between the target and mask varied between 23, 47, and 70 ms.  was used, handled according to the instructions of the manufacturer. To extract DNA from the sampleQiagen QIAamp Mid set was used. Genotyping of the acquired DNA was performed based on TaqMan® Pre-Designed SNP Genotyping Assays technology . The procedure was carried out in the Institute of Technology of the University of Tartu.As a result of genotyping, the following sizes of subjects' sub-samples were found: with regard to BDNF Val66Met polymorphisms there were 32 Val/Val homozygotes and 20 Met allele carriers; with regard to NRG1/rs6994992 polymorphisms there were 18 C/C homozygotes and 34 T allele carriers; with regard to 5HTTLPR polymorphisms there were 24 L/L carriers and 28 S allele carriers (24 L/S heterozygotes and 4 S/S homozygotes).F  = .234, p = .792). There were several significant interactions involving BDNF endophenotypes. (i) Female Val/Val homozygotes did not have a lower rate of correct discrimination than Met allele carriers, but male Val/Val homozygotes had – an interaction   = 4.678, p<.035) which substantially originates from intermediate SOA conditions where the proportion of correct responses in males was significantly higher   = −4.087, p<.0006, Cohen's d = 1.88). In Val/Val homozygotes no analogous gender difference was found   = −1.330, p = .193) (See We found no main effect of BDNF polymorphisms on correct discrimination of targets in metacontrast (193) See . A similF  = 4.566, p<.013) showed different dynamics of metacontrast discrimination for different genotypes in males and females. In the Val/Met group in the first stage of the experiment, females produced significantly fewer correct answers than males (t(20)  = −3.5, p<.002, Cohen's d = 1.67). After Bonferroni correction the effect remained at a significant level . Differences in the proportion of correct answers between gender groups disappeared in the end sections of the experiment (t(20)  = −0.498, p = .624). (See (ii) A three-way interaction between gender, genotype and stage of the experiment (24). See .  = 3.213, p<.044) (see t(20)  = 2.328, p<.031). Whether this may be related to poorer recognition memory of Met allele carriers (iii) Val/Val homozygotes performed similarly regardless of the perceptual strategy, but Met allele carriers' performance dropped with a longer SOA when they used the strategy of paying attention to local corners/edges of the target situated within the inner mask contours (F044) see . At SOA F  = 4.114, p<.004) suggested a need for separate analysis carried out separately for different gender groups.   = 3.536, p<.013). How the similarity of target and mask shapes relates to target/mask relative timing appears important for male subjects. In the group of T allele carriers when target and mask shapes were incongruent, males' level of metacontrast discrimination was higher than females' level of metacontrast discrimination (M(SD = 0.144)  = 0.817 vs M(SD = 0.124)  = 0.611, respectively; t(27)  = −4.034, p<.0004). Gender of T allele carriers had no significant effect when target and mask shapes were congruent   = 1.373, p = .262). An interaction between gender and polymorphism was also not significant   = .596, p = .555). However, a three-way significant interaction emerged between gender, polymorphism and a SOA   = 3.279, p<.014). With the shortest SOA ( = 23 ms) female L/L homozygotes had higher rate of correct discrimination than S/L heterozygotes (t(24)  = −2.306, p<.030, Cohen's d = 1.19) while in males this pattern of results was reversed, although not at a significant level (t(10)  = 1.475, p = .171) (see There was no main effect of 5-HTTLPR polymorphism on metacontrast masking (171) see . If we cWe found no overall effect of BDNF Val/Met, NRG1-rs6994992 or 5HTTLPR on visual discrimination in metacontrast masking, but a genotype x gender interaction was found with all three common gene variants examined. We should bear in mind that due to the exploratory format of the present study, including many variables and their combinations even the significant effects of interaction should be interpreted cautiously. We have not solved the problem of multiple comparisons and for this, more restricted and targeted future studies are necessary. However, on the other hand, our present results have made it possible to know better where the possible more rigorous effects could be found if specifically studied. It appears that when discrimination of target shapes under metacontrast masking has to be executed and the conditions are relatively more difficult, male subjects carrying alleles that are considered as less advantageous in terms of development of brain tissues seem to cope better with these situations compared to female subjects. The beginning stages of the experiment, intermediate or short SOAs instead of the long SOAs and mutually incongruent target/mask shapes can be considered as the more difficult conditions. Yet we see that male met allele carriers , T allele carriers (NGR1) and S allele carriers (5HTTLPR) perform relatively better. On the other hand, the results we obtained with only three gene polymorphisms as variables in metacontrast already seem to show a high level of complexity and interactivity of different hereditary factors involved in visual masking and possibly other fast-perception phenomena. If we consider that in virtually all studies of masking carried out so far, (i) genetic factors have not been controlled and (ii) relatively small groups of subjects  have been used then – in the light of our present results – it should not be surprising how variable and often mutually inconsistent the results of masking research have been. This calls for further research where progressively more candidate genes as possible factors of gene expression ultimately manifesting in the variability of behavioural phenotypes of visual masking are tested. This also calls for more care in controlling the factors that interact with genetic effects such as gender, nationality, brain morphology, etc. Among the most difficult questions there will be the problem of whether gene polymorphisms are expressed directly in the brain mechanisms of basic vision or there is mainly an indirect influence mediated by higher cognitive and personality related processes that influence the ways subjects deal with perceptual representations formed in itself in an invariant species-specific way.


Chloroplasts of leaves under high light stress initiate signals to the nuclei of both exposed and distal leaves in order to acclimate against the potential threat of oxidative damage: a process known as high light systemic acquired acclimation (HL SAA). This study explores the nature of HL SAA, synergistic interactions with other environmental stresses, and the impact of repeated HL stress on the acclimation response of exposed and distal leaves. This necessitated the development of novel experimental systems to investigate the initiation, perception, and response to HL SAA. These systems were used to investigate the HL SAA response by monitoring the induction of mRNA in distal leaves not exposed to the HL stress. Acclimation to HL is induced within minutes and the response is proportionally dependent on the quality and quantity of light. HL SAA treatments in conjunction with variations in temperature and humidity reveal HL SAA is influenced by fluctuations in humidity. These treatments also result in changes in auxin accumulation and auxin-responsive genes. A key question in retrograde signaling is the extent to which transient changes in light intensity result in a “memory” of the event leading to acclimation responses. Repeated exposure to short term HL resulted in acclimation of the exposed tissue and that of emerging and young leaves (but not older leaves) to HL and oxidative stress. Acclimation to changes in the environment is required for optimal plant performance under adverse conditions. Factors such as light, temperature, drought, mineral concentrations, and biotic infection are all capable of causing extensive damage to plants as well as inducing short and long term acclimation responses , respectively. In contrast, plant pigments such as carotenoids and tocopherols remove ROS via chemical and physical quenching  pathways that allow for the dissipation of excess energy; (2) systems that detoxify the harmful by-products of HL; and (3) mechanisms that reduce the amount of light absorbed by the plant. Plants have also evolved different mechanisms that facilitate the dissipation of accumulated excess energy absorbed under HL conditions, including chlororespiration, cyclic electron flow (CEF), photorespiration, and non-photochemical quenching . Acclimation of metabolism in distal leaves occurs as a result of a 15- to 60-min short term HL exposure, termed high light systemic acquired acclimation (HL SAA), in which HL stressed tissues of individual plants communicate to the distal parts of the plant initiating stress acclimation. Even though research over that last decade has significantly progressed the understanding of HL SAA many unknowns still exist in regards to the identity of the retrograde signal(s) and the acclimation processes which they govern. Also unclear is the exact nature of the synergistic relationships between different stresses, how they affect the initiation of HL SAA and subsequent acclimation processes against multiple stresses . This is a study in two parts, firstly, the investigation of how light and environmental conditions affect HL SAA and secondly, the study of repeated HL treatments on signaling in exposed and distal mature leaves. This was achieved through (1) the development of a novel treatment system to further characterize the short term HL SAA gene activation in existing tissues under varying ambient qualities such as the duration of treatment, light intensity, temperature, and relative humidity (RH), as well as to determine the spatial distribution of oxidative stress tolerance across the rosette; (2) investigation of whether and how repeated, transient, and localized HL treatments can alter acclimation responses within existing mature leaves.Arabidopsis thaliana (Col-0) plants were cultivated in soil under a 12-h photoperiod of 150 ± 25 μmol photons m−2 s−1, 23/22 ± 2°C day/night temperatures, and 70 ± 10% day/night RH. All HL treatments utilized a new light emitting diode (LED)-array system and mature (approximately 4 weeks old) Arabidopsis plants. Arabidopsis leaf position for tissue collection were counted according to Arabidopsis phyllotaxy  or to LL conditions (40 ± 25 μmol photons m−2 s−1). Subsequently, HL, control, and distal tissues from three treated individual plants were pooled to yield three “biological” replicates per tissue, immediately frozen in liquid N2, and stored at −80°C. During analysis of environmental effects on HL SAA, plants were subjected to: HL exposure (1500 ± 50 μmol photons m−2 s−1) for either 5, 30, 60, and 120 min; varied irradiances of 250, 500, 1000, or 1500 ± 50 μmol photons m−2 s−1 for 60 min. Light quality treatments were performed with white, ultra violet A (400 nm), blue (460 nm), green (515 nm), yellow (600 nm), red (680 nm), and far-red (720 nm) specific light. The wavelength and irradiance of the specialized LEDs  was verified by a spectrophotometer  three times a day for 60 min (separated by 120 min), for eight consecutive days, or remained untreated in the same growth environment.The HL SAA LED-array system consisted of nine white Luxeon III star LEDs (Lumileds Lighting)−2s−1) under varied humidity levels  at 21°C or at increasing temperatures  at 55% RH.All variable humidity and temperature specific HL SAA treatments were performed in a controlled environment chamber . Plants were subjected to either HL LED-array exposure (1500 ± 50 μmol photons mCYCLOPHILIN 5(CYP5) and PROTEIN PHOSPHATASE 2A (PP2A). In subsequent experiments target transcript level were normalized to one of the aforementioned reference genes. List of primers are outlined in Table t-tests (between LL controls and other samples) and one-way analyses of variance (ANOVA) on all samples using the scientific statistical analysis program, SigmaPlot12 . Least significant difference (LSD) post hoc tests were used where one-way ANOVAs indicated significant differences between factors.For gene transcript analysis, RNA was extracted from frozen samples using an RNeasy Plant Mini Kit  as instructed by the manufacturer’s instructions. RNA was converted to cDNA using SuperScript III Reverse Transcriptase (Invitrogen), and RT-qPCR performed using a LightCycler 480 (Roche) with either the LightCycler Universal ProbeLibrary or Sybr green specified by the manufacturer’s instructions. The LightCycler 480 software application  was used to determine crossing-point values for each reaction, amplification efficiency of each primer set, validation of each reaction, and relative expression values obtained as described Pfaffl, . For iniin vitro photo-oxidative stress tolerance assay was performed after short term HL SAA treatments and at the end of the 8-day period of the repeated, HL SAA study, using a method adapted from Rossel et al. (2O2 in a clear 200 μL 96-well plate. The leaf disks were then exposed to HL (1500 ± 50 μmol photons m−2 s−1) for 60 min and moved to LL growth conditions for 24 h while remaining in H2O2 solution, during which time photographs were taken periodically every 2 h to determine the extent of bleaching of the leaves. Analysis of the photos was performed using ImageJThe l et al. . Leaf diin vivo HL-stress tolerance assay were exposed to the HL spot treatment (leaf 4 @ 1000 ± 50 μmol photons m−2 s−1) for 60 min or remained untreated under LL growth conditions. Following the initial HL SAA treatment, treated and untreated whole plants were placed in a controlled growth environment chamber  under HL growth conditions for 24 h . Plants remained well watered for the duration of the 24-h treatment. During the 24-h HL treatment photographs were taken periodically to assess the first appearance photobleaching.Plants subjected to the Chlorophyll fluorescence measurements were taken during the repeated, HL SAA study using an IMAGING-PAM chlorophyll fluorometer and analyzed with the ImagingWin software application  as described . Mature DR5:GUS transgenic plants were either treated with LL conditions (40 ± 25 μmol photons m−2 s−1), or with HL spot (1500 ± 50 μmol photons m−2 s−1) for 60 or 120 min. GUS staining and localization was performed using a modified version of the GUS visualization assay  a greater understanding of the genetic regulation of HL retrograde responses governing the initiation and perpetuation of SAA; (2) identification of SAA marker genes that could be used in this study for an efficient quantification of HL SAA activation under different treatment regimes; and (3) identification of genes which are specifically induced in distal leaves, but not exposed leaves, which may give novel insight into the mechanisms or role of HL SAA in Arabidopsis  and ZAT10 were selected as marker genes for HL SAA in subsequent experiments as both transcripts exhibited strong, relatively consistent transcript induction under short term HL spot treatment.For this analysis, genes were selected based on one of two factors: if they were reported to be involved in HL or SAA in previous studies . RRTF1 and ZAT10 were induced at already relatively small changes in light intensity . Under blue light RRTF1 also shows significant induction in comparison to the majority of the other light treatments (P < 0.05). On the other hand the significance of transcriptional changes of ZAT10 between different light qualities becomes less apparent due to small relative fold changes and experimental variance. The results clearly demonstrate that the degree of HL SAA induction of the marker genes is wavelength-dependent.Light quality (wavelength) also plays an important role in HL response, acclimation, and plant developmental processes . Normalizing transcript levels of HL spot exposed plants to LL 90% RH revealed that humidity directly affects the induction of HL SAA. Even though independent samples 2O2-mediated bleaching of leaf disks  tissue than in controls for the younger leaves . Using GO annotation  it became evident that the co-expressed genes in both HL SAA and two or more auxin treatment experiments exhibited a large proportion of genes involved in either auxin-related (29%) or plant stress processes (29%).Our initial analysis of different HL SAA marker transcript levels demonstrated specific distal expression of .3 Table , an impo.3 Table . This ma.3 Table  with dat.3 Table . The ana.3 Table ; Table 2GH3.3, GH3.5, PIN-FORMED3 (PIN3), PIN4, and PIN7). After the LED-spot treatment, independent samples t-tests show that both GH3 transcripts exhibited statistically significant induction in the distal leaves . Whereas PIN4 and PIN7 were down-regulated in HL and distal tissues and PIN3 exhibited no significant changes in transcript levels , the narrow wavelength would result in a lower overall total photosynthetic available radiation (PAR) available for capture by chlorophylls and carotenoids. Interestingly, for both UVA and blue light the lack of systemic response is in despite of an observed strong physiological photobleaching response in the treated tissue (data not shown). This indicates the presence of separate retrograde signaling systems which activate HL SAA independent from those that govern blue light responses and photodamage acclimation responses (Franklin and Whitelam, −2s−1. Such intensities are unlikely to even induce the xanthophyll cycle as zeaxanthin typically accumulates in response to 400 μmol photons m−2s−1 and above (Demmig-Adams et al., −2s−1 indicates that changes in photosynthetic parameters and subsequent retrograde signals initiate HL SAA, not oxidative stress and damage, although the latter may contribute to the intensity of the response at higher light intensities.UVA, blue, yellow and red light-exposed plants exhibited significant systemic induction of  Figures E,F, howe Figures C. This m Figures , but wouRRTF1 and ZAT10 compared to the other wavelengths (Figures APX1 and APX2 exhibit no apparent attenuation and dependency of blue light perception via cryptochrome photoreceptors in double mutants cry1/cry2 (Szechynska-Hebda et al., 2O2 and 1O2, trigger different transcriptional responses including induction of ZAT10 and RRTF1, respectively (op den Camp et al., APX isoforms may be influenced by both H2O2-derived and blue light 1O2-derived signaling and be dependent on how these different ROS signaling pathways interact.Interestingly, blue light treatments resulted in increased transcript induction for both  Figures E,F. This Figures . ContrarRRTF1 and ZAT10 in distal leaves was similar at all analyzed temperatures (Figure RRTF1 transcripts relative to 21°C in all three tissues, including the control.Even though heat exposure is able to cause photoinhibition (Allakhverdiev et al., s Figure , althougZAT10 and APX2, such as SAL1 (Kimura et al., APX2 (Karpinski et al., APX2 and ZAT10 (Rossel et al., alx8, also retains the additive increase in APX2 and ELIP2 gene expression under drought and light stress (Rossel et al., In contrast to increased temperatures lower RH levels proportionally inhibited HL SAA induction in distal leaves (normalized to LL 90% RH; Figure in vitro beyond the transcriptional changes (Figures 2O2 tolerance and NPQ (Karpinski et al., 2O2 and elevated NPQ capacity compared to LL controls (Figures RRTF1 and ZAT10 mRNA accumulation (Figure 2O2 bleaching compared to LL control plants (Figure To date, the study of acclimation processes and function of HL SAA has been restricted to evaluation of the immediate adaptation responses to one or several hours of HL (Rossel et al.,  Figures –6. This  Figures –9. Key tn Figure , and higs Figure . Youngers Figure . The pros Figure .GH3.3 and GH3.5 were exclusively expressed in distal tissue in response to HL SAA (Figure GH3.5 alters the balance between free and conjugated auxin enhancing tolerance to pathogen infection and abiotic stresses such as drought, salinity, and temperature (Park et al., GH3.3 is induced under pathogen infection its role in plant stress is relatively undefined (González-Lamothe et al., S-transferases (Laskowski et al., Auxin is a well-established regulator of many plant processes including organ patterning, root and shoot architecture, vascular development, growth, and tropic responses (Benjamins and Scheres, A Figure  and are A Figure . Over-exIn conclusion localized HL treatments and repeated, localized HL treatments initiate retrograde signals that lead to transcriptional and acclimatory responses in both treated and distal tissue. However, a single 1 h HL spot treatment is not sufficient to alter the acclimation response in distal tissues. HL SAA requires either a 1/3 of the rosette to be treated (Rossel et al., The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.