The effect of inoculated azotobacteria and basidiomycetes white-rot fungi on the population dynamics of bacteria and eumycetes during the co-composting of olive mill pomace and wheat straw was evaluated by Polymerase Chain Reaction-Denaturing Gradient Gel Electrophoresis (PCR-DGGE) analysis combined with sequencing of rRNA gene amplicons from selected DGGE bands. The evolution of pH, temperature, phytotoxicity and water-soluble phenol content during co-composting was also monitored. In general, a similar evolution of microbial biodiversity was seen in both the inoculated and uninoculated (control) piles, which was in keeping with a similar evolution of phytotoxicity and water-soluble phenol content. Overall, under the conditions applied, data suggest a marginal influence of the inoculated starters on the physical, chemical and microbiological properties of compost piles, with the resident microbiota playing a major role. Olive pomace is potentially harmful for the environment due to numerous intrinsic properties, including its acidic pH, relatively high content of salts and organic compounds, phytotoxicity, antimicrobial activity, and phenolic and lipid components2. The organic matter within this agro-industrial waste consists mainly of nitrogenous compounds, organic acids, sugars, tannins, pectins, carotenoids, oil residues, and phenolic substances2. Over the last decade, the composting of olive pomace has been increasingly attracting the attention of the scientific community due to the beneficial effects of the resulting compost on horticultural and short-term crops3. Composting substantially consists in the aerobic stabilization of organic matter4. During composting, the endogenous microbiota colonizing the solid matrix being composted transforms the organic matter into CO2, biomass, heat and humic compounds5.Olive pomace is an olive mill solid waste that is produced during the discontinuous (press-based) olive oil extraction process6 and even fixing atmospheric nitrogen in olive mill wastes8. Select strains of azotobacteria have been found to remove phytotoxic compounds9 and produce both fertility-promoting metabolites10 and exopolysaccharides11 during aerobic treatment of olive mill wastewater.To date, several microorganisms, including azotobacteria and ligninolytic microfungi, have been assayed, either alone or in consortia, as accelerating agents for the composting of olive mill byproducts. Azotobacteria are free-living nitrogen-fixing bacteria capable of growingPhanerochaete chrysosporium  is a white-rot fungus belonging the Basidiomycotina subdivision, which has been recognized as comprising some of the most effective degraders of lignin5. So far, P. chrysosporium has been extensively exploited in composting trials with numerous agricultural wastes, including olive-mill waste water12 and olive pomace14.Concerning ligninolytic microfungi, 16. Though both studies investigated the physical and chemical traits of the compost piles, neither identified the bacterial and fungal species that predominated during the composting process.By contrast, only scarce research is available regarding microbial community dynamics and polyphenol evolution during composting of olive mill pomace, and to the best of the authors’ knowledge, only two studies have examined the effect of microbial accelerating agents on the composting of this agro-industrial wasteGiven this knowledge gap, this study aimed to investigate the microbial population dynamics and the evolution of polyphenols during the co-composting of olive pomace and wheat straw inoculated with azotobacteria and ligninolytic microfungi, in comparison with uninoculated control compost. To this end, culture-dependent (viable cell counting) and culture-independent (PCR-DGGE) analyses were carried out to monitor the bacterial and eumycete diversity in piles during the composting process; in parallel, physical  and chemical  properties of the piles were also monitored.et al.17. At the beginning of the maturation phase (44th day of composting), piles 1A and 1B were also inoculated with a strain of P. chrysosporium (see paragraph “Reference strains” for more details) that was previously assayed in co-composting trials of agricultural wastes mixed with olive mill wastewater13. Piles were turned manually three times a week to provide aeration and improve pile homogeneity throughout the composting trial. The average moisture content of the initial mixtures was kept at 48 ± 5% by irrigating with water when necessary.Wet olive pomace (WOP) derived from olive oil production during the 2015–2016 season was provided by the “Azienda del Carmine” oil mill . The WOP was produced by the two-phase system of oil extraction from olives of the “Leccino” cultivar. The composting of WOP was carried out in piles placed in open, plastic 65-L containers to avoid the loss of percolate. The composting trial was carried out in a greenhouse. Four composting piles were prepared, labeled as 1A, 1B, 2A and 2B. For each pile, 20 kg of WOP, 15 kg of wheat straw and 5 kg of wood chips were mixed. At the end of the thermal phase (day 25 of composting) and again after 94 days of composting, experimental piles 1A and 1B were inoculated with a suspension of three azotobacteria strains (see paragraph “Reference strains” for more details). The bacterial inoculants were selected based on their ability to abate water-soluble phenols in olive mill wastewater, as previously assessed by Aquilanti Samples of approximately 0.3 kg were randomly collected from each pile at three different depths for physical, chemical, and microbiological (culture-dependent and culture-independent) analyses. Samples were collected at regular intervals during the composting process and were vigorously mixed before analysis.Azotobacter chroococcum 208, A. chroococcum 220 and A. chroococcum 225) and one fungal strain (P. chrysosporium DSMZ 6909) were used to inoculate experimental piles 1A and 1B and to prepare the two DGGE ladders. The three bacterial strains had previously been isolated from soils that were regularly treated with olive mill wastewater; they were molecularly identified as A. chroococcum and were assayed for their ability to abate water-soluble polyphenols in sterile CaO-treated olive mill wastewater17. The fungal strain was purchased from the Deutsche Sammlung von Microorganismen und Zelkulturen (DSMZ)  and reconstituted according to DSMZ recommendations.Three bacterial reference strains  were cultured separately in tryptic soy broth (TSB) for biomass production. The cultures were incubated on a rotary shaker at 150 rpm. After 48 h incubation at 30 °C, the biomass was harvested by centrifugation, the supernatant was discarded, and the pellet was resuspended in sterile physiological solution 0.85% (w/v) of NaCl. Concentration of the bacterial suspensions was determined using a Thoma Zeiss counting chamber, whereas the cell viability was checked by the plate count method using tryptic soy agar (TSA). Equal parts (150 mL) of the three bacterial suspensions were mixed and used to inoculate the composting piles by spraying with a dispenser. The bacterial suspension of the three A. chroococcum strains was inoculated twice during composting, specifically, on the 25th and the 94th day of composting, to achieve a final concentration of 6 and 8 Log CFU g−1 compost at the two respective timepoints. The inoculation of P. chrysosporium spores was performed on the 44th day of composting to achieve a final concentration of 6 Log CFU g−1 compost. The inoculum of fungal spores was prepared as previously described by Taccari et al.13.The three et al.13. All measurements of moisture, pH, and water-soluble phenols were carried out in duplicate. The results were expressed as mean values ± SDs.The temperature of each compost pile was measured daily at three depths  using a temperature probe , and the mean value of three measurements was calculated. The ambient air temperature was also measured using a Wet and Dry Bulb Hygrometer . The moisture content, pH and concentration of water-soluble phenols in the WOP and compost material collected during composting were determined following the procedures described by Taccari Lepidium sativum) seeds in contact with compost extracts to that of seeds in contact with deionized water (control) after incubating for 72 h at 25 °C. The test was performed in triplicate following the procedure previously described by Zucconi et al.18 with some modifications, as reported by Mari et al.19.WOP and aliquots of the inoculated and control piles were assayed for their phytotoxicity during composting. The phytotoxicity, expressed as germination index (G.I.), was estimated by comparing the root development of cress  of each sample were homogenized in 90 mL sterile peptone water (0.1% peptone) at 260 rpm for 3 min using a Stomacher apparatus 400 Circulator . Serial dilutions of the suspensions were plated on Plate Count Agar for enumeration of mesophilic (incubated for 24–48 h at 30 °C) and thermophilic (incubated for 24–48 h at 50 °C) bacteria. Rose-Bengal chloramphenicol agar was used to enumerate fungi after incubating for 48–72 h at 25 °C. All samples were analyzed in duplicate, and the mean values were calculated; the results are expressed as Log CFU get al.20 and Makimura et al.21, respectively. An E.Z.N.A. soil DNA kit  was used to extract microbial DNA directly from the samples collected at regular intervals during composting. A 1-mL aliquot of sample homogenate that had been diluted 10−1 for viable-cell counting was centrifuged to produce a pellet that was then processed according to the kit manufacturer’s instructions. The quantity and purity of the extracted DNA were assessed by absorbance at 260, 280 and 234 nm using a UV-Vis Shimadzu UV-1800 spectrophotometer .DNA from the bacterial and fungal reference strains was extracted as described by Garofalo 22 and NL1-LS2 for fungi23. A GC clamp was added to the 5’ end of the forward primers, 338 f24 and NL125. For all amplification reactions, 100 ng of DNA was amplified in a total reaction volume of 50 µL containing 1.25 U of Taq DNA polymerase , 1X reaction buffer , 0.2 mM dNTPs, and each primer at 0.2 µM. The PCRs were performed in a My Cycler thermal cycler  using the programs previously described by Osimani et al.26. For each PCR, 5 µL of product was analyzed by electrophoresis in 1.5% agarose gels in 0.5X TBE containing 0.5 mg mL−1 ethidium bromide at 6 V cm−1 for 1 h, using the HyperLadder 100 bp  as a molecular weight standard. Gels were visualized under UV light and photographed using the Complete Photo XT101 system .The DNA extracted directly from the composting samples were amplified by PCR using two primer sets, namely, 338f-518r for bacteriaTM system (Bio-Rad), as previously described by Taccari et al.27. The ladder for the analysis of the bacterial community was prepared by mixing PCR products obtained from the three A. chroococcum reference strains. The NL1GC-LS2 amplicon of P. chrysosporium was used as a ladder in each DGGE gel for the analysis of the fungal community. After electrophoresis, the gels were stained for 20 min in 1X TAE buffer containing 1X SYBR Green I Nucleic Acid Gel Stain  and then visualized under UV light and photographed using the Complete Photo XT101 system (Explera).DGGE analyses of the bacterial and fungal communities were carried out using a DGGE DCodeet al.28.Select DGGE bands were excised from the gels using sterile cutting tips. DNA from each band was eluted in 50 µL deionized water; 5 µL of eluted DNA was reamplified in a PCR reaction under the same conditions as described above but using forward primers 338 f and NL1 without the GC clamp. The obtained amplicons were sent to Genewiz  for purification and sequencing. The analysis of the obtained sequences was performed as previously described by Garofalo Analysis of variance (ANOVA) was applied to assess differences in pH, water-soluble phenol content and phytotoxicity. The means were analyzed using the STATISTICA 7 software (freely available on the internet). Significant differences were determined by the Duncan multiple range test, with P values < 0.05 considered to be significant.−1 dry weight) 13’244.12 ± 45.75 and G.I. (%) 19.66 ± 4.83. Concerning the first two parameters, data collected in the present study were within the range reported by other authors for semisolid olive mill wastes produced with two-phase olive oil extraction systems29. The water-soluble phenol content of olive mill wastes is known to be greatly dependent on several variables, including the geographical area and conditions, soil composition, ripeness of the fruits, olive cultivar, storage conditions prior to processing, and olive oil extraction system applied30.Wet olive pomace (WOP) used for the composting showed the following values for the physical and chemical traits considered: pH 5.05 ± 0.02, concentration of water-soluble phenols  might have affected the phenol metabolism, and hence the humification process, by enhancing the decomposition of lignocellulose compounds and/or polyphenols. A similar hypothesis was recently formulated by Agnolucci et al.16 to explain the contribution of a multi-strain starter culture, which included P. chrysosporium, to the water-soluble phenol content in mature compost from olive mill solid waste.This result seemed to suggest that the inoculation of azotobacteria (at day 25 and 94) and 42.Invariably, the final water-soluble phenol content in compost piles in this study were less than 4%. This content level falls within the recommended limit established by several authors for the direct application of organic matter to annual crops for sustaining crop yields and building soil fertility95 and t142, when a significantly lower concentration of soluble phenols was seen in the inoculated piles compared with the controls. Moreover, in all four piles, a notable increase of soluble phenols was seen during the thermophilic phase (t7–t14), followed by a progressive decrease until t36, a subsequent gradual increase until t65, and a final gradual decrease until the end of the monitoring period. A very similar trend has been reported by Castaldi et al.41 when analyzing the fraction of water-soluble phenols in compost from municipal solid waste. In that study, an increase of water-soluble phenols was seen after the first two weeks of composting, followed by a gradual decrease, which has been ascribed by the authors to the microbial use of these compounds as either an energy source or as precursors for the synthesis of new molecules. In 2012, Gigliotti et al.43 reported that during the maturation phase, phenols tend to increase because of the concentration of these compounds.When the evolution of phytotoxicity and water-soluble phenol content during composting was evaluated Fig. , additioet al.13. In that study, again after 15 days of composting, an enrichment of these phytotoxic compounds was seen in the piles inoculated with P. chrysosporium. The authors13 ascribed this increase in the number of phytotoxic compounds to the previously reported capacity of the inoculated basidiomycetes white-rot fungi to liberate additional water-soluble phenols during lignin degradation44 via a combination of extracellular organic acids, mediators and enzymes, including laccase (phenol oxidase)45. This latter explanation fits well with the overall PCR-DGGE analysis results of the present study, which revealed stable colonization by Aspergillus nidulans and Penicillium chrysogenum of all four piles from the very early phase until the end of the composting trial  or t23  until the end of the monitoring period, or during the late maturation phase, such as L. terricola, N. communis, N. itersonii, P. kocurii, and Q. soli.The viable count data were largely in accordance with the denaturing gradient gel electrophoresis (DGGE) profiles. Indeed, an equally similar trend in the evolution of the microbiota in the four piles was revealed by PCR-DGGE and sequencing of DNAs eluted from selected bands , the thermophilic phase  or at defined time points during the maturation phase .Regarding eumycetes, a quite stable evolution of the population was again seen in the four piles. In more detail, some species were detected during the whole composting process, such as Azotobacter nor Phenerochete could be detected by sequencing of DNA eluted from the excised DGGE bands. This might be explained by the lack of dominance of the inoculated strains in the piles, which in turn might be feasible due to an initially low load or, alternatively, to lower competitive fitness of the starter strains with respect to the autochthonous microorganisms already residing in the matrices to be composted.Interestingly, neither 52. Among those supporting the infectiveness of starter cultures for composting, Golueke53 suggested that inoculants introduced into compost mixtures are already colonized by diverse communities of organisms, each of which rapidly multiplies under the most favorable conditions. Hence, mechanisms such as substrate enzymatic induction and natural selection rapidly lead to the dominance of endemic specialized populations.The lack of DGGE bands ascribable to the inoculated species seems to support what other authors have previously suggested about the still debated use of starters to speed up and guide the composting process16.When compared to the results collected in other published studies relying on culture-independent approaches, the data collected in the present study confirmed the high variation in the microbial diversity characterizing the different phases of the composting process, as well as the progressive stabilization of the microbial population as the compost piles reach maturityThough it is difficult to determine whether the species identified by PCR-DGGE analysis were metabolically active, as extracted genomic DNA could be from resting cells within the samples, the dynamic temporal shifts of DGGE bands suggest that DNA turnover necessarily occurred during the composting. This, in turn, indicates that the microbial species identified through sequencing of the selected DGGE bands were actively growing. Indeed, it is conceivable that if sequenced DGGE bands belonged to vegetative cells, those visualized at the first time points should have been detected throughout the monitoring period. Since this was not the case, the initial hypothesis must be rejected. The same conclusion can be reasonably drawn for eumycetes.Despite the observed microbial succession, the causative factors of the shift in microbial community composition remain unclear, and changes in substrate availability, temperature, or pH might have influenced these community changes.A. variabilis, A. gandensis), acetic acid bacteria , bacteria involved in the nitrogen cycle , human and animal commensal bacteria  and, as expected, bacteria typically associated with soil environments  and even composted agricultural wastes (P. suwonensis). Except for A. radioresistens, all these bacteria are novel species, mostly identified in the last few years and, hence, not yet fully characterized, thus rendering the comprehension of their contribution in the composting process particularly challenging.The bacterial species identified in the present study included microorganisms with very heterogeneous metabolic activities and that originated from various sources. These include obligate aerobes (54.As far as the fungal communities are concerned, again, a very similar evolution was seen in the four composts, with no differences among the enriched and control piles. Overall, a relatively low fungal species richness was seen at any given monitoring time; however, the community structure of eumycetes was dynamic and paralleled changes in the bacterial community structureAspergillus, Mucor, Penicillium, Humicola, Caetomium and Thermomyces. Overall, the dominant species identified in this study have previously been detected in compost. A. nidulans and P. chrysogenum have been isolated from spent mushroom compost45. Selected cultures of the latter species, isolated from different composting processes, were found to tolerate heavy metals in multipolluted aqueous systems, as well as to remove these metals with high detoxification ratios50. Analogously, isolates of C. boidinii collected from two-phase decanter system olive oil waste were proven to degrade toxic substances, such as phenols, in a fed-batch microcosm system55. More intriguingly, both A. nidulans and P. chrysogenum are known to produce laccase46, a key enzyme in the ligninolytic process, thus suggesting a key role for these microorganisms in the transformations of organic matter during the composting of WOP.Eumycetes play a key role in compost, being prevalent in this ecosystem, thanks to their strong ability to degrade lignocellulose compounds, which are particularly abundant in agricultural wastes. A few genera are dominant in this compost, namely, P. chrysosporium inoculation on the composting of piles added with WOP. Overall, only a modest impact of the starter strains on the physical, chemical and microbiological properties of the mature composts was seen, except for a significantly lower content of water-soluble phenols in the inoculated piles after 142 days. However, an intense evolution of these compounds was seen in all piles, thus suggesting an active role of the heterogeneous resident microbiota.To date, the composting of WOP has not been thoroughly elucidated, and most aspects regarding microbial population dynamics remain largely unknown. In this study, new information was attained by exploring the effects of azotobacteria and Supplementary Figure 1Supplementary Figure 2


Antibodies to brewer’s yeast or anti-Saccharomyces cerevisiae antibodies (ASCA) have been detected in 70% of patients with Crohn’s disease and have become a part of the evaluation of a patient for Crohn’s disease. Prior evaluation of these antibodies in rheumatoid arthritis have been inconsistent. In an initial small study, the levels of antibodies were elevated but not statistically significant. In a second large study from China, 40% of rheumatoid arthritis patients were positive for immunoglobulin A (IgA) ASCA and 20% positive for immunoglobulin G (IgG) ASCA.Our study was inspired by the observation that several seronegative patients with rheumatoid arthritis were positive for ASCA antibodies. Between January 1, 2016 and January 1, 2018, a total of 241 patients with clinical rheumatoid arthritis were evaluated for antibodies to IGA and IGG ASCA, rheumatoid factor, cyclic citrullinated peptide (CCP), and antinuclear antibody (ANA). Our results indicate that 158 (66%) of these patients were positive for ASCA; 70 (29%) of these patients were positive for ASCA but negative for other serologies; 62% of the patients were positive for rheumatoid factor. Our results also indicate that the percentage of rheumatoid factor (95%) and CCP positive (78%) patients in the ASCA negative group was higher than the percentage of rheumatoid factor positive (49%) and CCP positive (37%) patients in the ASCA positive group, suggesting serologic differences between the two groups. Only 4% of the rheumatoid patients were negative for all the evaluated serologies.The possible role of mannan, a mucopolysaccharide from the cell wall of Saccharomyces cerevisiae (S. cerevisiae) in producing rheumatoid arthritis is discussed. Antibodies to brewer’s yeast or anti-Saccharomyces cerevisiae antibodies (ASCA) have been found to be present in 70% of patients with Crohn’s disease , 11% of The impetus for this case series came from a clinical observation by one of the authors several years ago - patients presenting with classic clinical and radiographic findings of rheumatoid arthritis, who were seronegative for rheumatoid factor and anti-cyclic citrullinated peptide (CCP) antibodies, could be positive for ASCA.This study was conducted entirely at a single rheumatology center in Annapolis, Maryland without any outside funding. Between January 1, 2016 and January 1, 2018, all patients (n=241) with a diagnosis of rheumatoid arthritis were evaluated once for ASCA titer, rheumatoid factor, anti-CCP antibody, and antinuclear antibody (ANA) along with their routine laboratory studies. Specimens were sent to Quest Laboratories where the tests were performed using routine commercial assays. The ASCA assay was done using an enzyme-linked immunosorbent assay (ELISA) ) which can test for IgG and IgA antibodies to Saccharomyces cerevisiae (S. cerevisiae). This assay uses mannan, a beta-glucan or complex polysaccharide specifically found in the S. cerevisiae yeast cell wall. The patients were informed that the specimens were being drawn to address a specific research question and they provided their consent. All patients fulfilled the American College of Rheumatology (ACR) criteria for rheumatoid arthritis. No systematic attempt was made to test for celiac disease.Two hundred and forty-one patients with rheumatoid arthritis from a single rheumatology center in Annapolis, Maryland were included in the study. They were divided into three groups:1. ASCA +: Patients who were ASCA positive and could have either a positive rheumatoid factor, positive anti-CCP antibody, or positive ANA. At least one of these serologies was positive, but in many instances two of the serologies or all three serologies were positive.2. ASCA -: Patients who were ASCA negative, but had a positive rheumatoid factor, positive anti-CCP antibody, or positive ANA.3. Seronegative: Patients who were negative for ASCA, rheumatoid factor, anti-CCP antibody, and ANA.The ages of both ASCA positive and negative groups were similar as seen in Tables A higher percentage of ASCA negative patients were female (76%) as compared to the ASCA positive group (68%). In this study, 66% (158/241) of rheumatoid arthritis patients were positive for ASCA antibodies; 62% (148/241) were positive for rheumatoid factor, 48% (116/241) were positive for anti-CCP antibodies, 29% (70/241) were positive for ANA and 3.7% were negative for all serologies. Of note, 70 patients (29%) were positive for ASCA, but negative for rheumatoid factor and anti-CCP antibodies. Thus, 29% of these patients (70 of 241) would previously have been considered to have seronegative rheumatoid arthritis. This indicates that there is a distinct group of patients with clinical features of rheumatoid arthritis who are rheumatoid factor and anti-CCP negative, but who are ASCA positive. Notably, only 49% (78/158) of the ASCA positive patients with rheumatoid arthritis were positive for rheumatoid factor, whereas 95% (70/74) of the ASCA negative patients were positive for rheumatoid factor.The expected percentage of rheumatoid arthritis patients positive for rheumatoid factor is 80%. Our figure of 62% in the total group of 241 rheumatoid arthritis patients is lower. We believe that this is representative of our referral patient population with rheumatoid arthritis. It should be noted that in the group of patients who were ASCA positive, the percentage of patients who were rheumatoid factor positive (49.3%) and CCP positive (36.7%) were reduced compared to the group of patients who were ASCA negative who had elevated rheumatoid factor (94.5%) and CCP (78.3%) positivity. This suggests there were serologic differences between the two groups. Also, one would expect about 20% of patients with rheumatoid arthritis to be seronegative, but when we excluded ASCA positive patients from the seronegative group, only 3.7% of the population was seronegative. Only three of the patients who were ASCA positive were known to have colitis.Brewer's yeast is ubiquitous, being critical for the fermentation of beer, wine, and cheese; for baking bread and cakes; and for many other home and industrial processes. It is also present in several brands of probiotics. It occurs as a part of the gingival and gut microbiome. It is rare for S. cerevisiae to be a pathogen.Our current paradigm is that autoimmune diseases, such as rheumatoid arthritis, are triggered by environmental factors in a genetically predisposed host. SKG mice spontaneously develop a T-cell mediated chronic autoimmune arthritis that is clinically and pathologically like rheumatoid arthritis. SKG mice fail to develop such an arthritis in a microbially clean environment, despite the presence of arthritogenic autoimmune T cells. Zymosan, a crude yeast cell wall extract, has been shown to trigger the development of severe arthritis in these SKG mice under sterile conditions . In a reIn our study, we found that patients with rheumatoid arthritis have a high incidence of antibodies to mannan, a component of the S. cerevisiae cell wall. This suggests that in certain patients, as in the SKG mice, mannan might be important in inducing chronic arthritis.In this prospective study of 241 patients with rheumatoid arthritis, 66% were positive for antibodies to S. cerevisiae. The majority of patient with seronegative rheumatoid arthritis were found to be ASCA positive. In addition, 70 of 241 (29%) rheumatoid patients were negative for RF, CCP, and ANA but were found to be positive for either IGA or IGG ASCA. These results indicate ASCA may be a valuable test in assessing patients with rheumatoid arthritis, particularly if they were believed to be seronegative for rheumatoid factor and CCP. Hopefully, other investigators will find these results intriguing and pursue these findings in more scientifically rigorous studies.


Using the model constructed by logistic regression analysis and the optimum cutoff value, the localization of PA  was determined with an accuracy of 67.1% (55/82). CT texture analysis may provide a potential avenue for less invasive prediction of the localization of PA.We performed present study to investigate whether the localization of primary aldosteronism (PA) can be predicted using quantitative texture analysis on unenhanced computed tomography (CT). Plain CT data of 82 PA patients , 28 bilateral) were analyzed retrospectively. After semi-automatically setting the region of interest to include the whole adrenal gland, texture analyses were performed with or without a Laplacian of Gaussian filter with various spatial scaling factors (SSFs). Logistic regression analysis was performed using the extracted histogram-based texture features to identify parameters capable of predicting excessive aldosterone production. The result of adrenal venous sampling served as gold standard in present study. As a result, logistic regression analysis indicated that the mean gray level intensity ( PA is recognized as the most frequent cause of secondary hypertension3, and has been reported to account for >5%, and possibly >10%, of hypertension cases in both unselected and referred hypertensive patients6.Primary aldosteronism (PA) is a disorder in which aldosteronesynthesis is disproportionately high given the sodium status, relatively autonomous of the major regulators of secretion loading1. For patients with unilateral PA, unilateral laparoscopic adrenalectomy is recommended, while medical treatment  is recommended for bilateral PA patients. As it is a straightforward diagnostic test, adrenal venous sampling (AVS) is considered as the gold standard in differentiation of these subtypes of PA9. However, as it is both technically challenging and invasive, AVS is not routinely used even in some major referral centers10. Although less invasive approaches, such as computed tomography (CT), magnetic resonance imaging and biochemical tests, are desirable, these alternative methods lack reliability for distinguishing between unilateral and bilateral disease12. Recently the 11C-metomidate PET-CT scanning is reported to show relatively high diagnostic performance13, it is not yet clinically widely available14.Treatment of PA basically depends on the localization of the disease17. Among those analysis, we now can investigate fine to coarse textures of an object by a method involving histogram analyses of images with and without filtration18. These textural features are known to provide information of clinically importance not only for tumor characterization20, but also for the diseased organ itself22.Quantitative texture analysis has recently gained much attention for assessing the internal heterogeneity of the targeted organ or tumorWe performed present study to investigate whether the localization of PA can be predicted using quantitative texture analysis on unenhanced CT.This study was approved by the Research Ethics Committee of University of Tokyo Hospital as a retrospective medical imaging data analysis using texture analysis and deep learning technique. The requirement for informed consent was waived by the Committee . All experiments were performed in accordance with the relevant guidelines and regulations.The study population initially consisted of 94 consecutive patients diagnosed as having PA biochemically, and who underwent AVS to determine the localization of excessive aldosterone production between January 2007 and December 2017. Six patients were excluded due to indeterminate AVS results. A further two patients for whom the interval between CT examination and AVS was more than 1 year were also excluded. Four patients were additionally excluded because a CT protocol without plain CT was performed  lateralization index ([A/C dominant]/A/C non-dominant]) > 3 and; (3) contralateral suppression index ([A/C non-dominant]/[A/C IVC]) < 124. If all three criteria were fulfilled, the patient was judged to have unilateral PA; otherwise, a diagnosis of bilateral PA was made.In all cases, AVS was performed with adrenocorticotropic hormone stimulation. During AVS, both plasma aldosterone concentration (PAC) and cortisol concentration were determined in blood collected from the adrenal veins, and in blood collected simultaneously from the inferior vena cava (IVC). The levels of cortisol were used in the calculation of the aldosterone/cortisol ratio ([A/C]). The diagnostic criteria used in this study were as follows: (1) PAC CT studies were performed using a 64-detector row CT scanner  or a 64-, 80-, or 320-detector row CT scanner . Although CT was performed with various protocols, the scanning parameters of unenhanced CT were constant, as follows: voltage, 120 kVp; tube current controlled by automatic exposure control technique; matrix, 512 × 512; field of view, 350–450 mm; and slice thickness, 5 mm. Iterative reconstruction methods were not used in the present study.CT texture was analyzed using commercial software . The images were evaluated by a single radiologist with 24 years of experience who was blinded to the clinical outcome. The region of interest (ROI) for each adrenal gland was drawn automatically by the software after the observer set a seed on the adrenal gland. If the automatically drawn ROI included adjacent organs or structures, the observer manually amended the ROI to exclude such organs and structures. For each adrenal gland, three consecutive CT slices, including the maximum cross-section of the adrenal gland, were selected for the analysis. Unless the CT slice with the maximum cross-section of the adrenal gland was at the top or bottom of the CT slices including the adrenal gland, the CT slice with the maximum cross-section of the adrenal gland was selected as the center of the three slices.18. Hereafter, these parameters are described by addition of the SSF values after the parameter name. For example, the mean of the positive value pixels of the SSF 2 mm image is referred to as mpp2. A total of 18 parameters were assessed in the present study.Quantitative texture analysis using the software mentioned above was performed using the filtration-histogram technique. First, filtration was performed using a Laplacian of Gaussian band-pass filter to extract features of different sizes with various spatial scaling factors (SSFs). SSFs of 2 and 4 mm were used in this study to reflect medium and coarse textures, respectively . Since the PAC and [A/C] were not normally distributed, spearman rank correlation test was used to assess the correlation of each texture parameters and the result of AVS (PAC and [A/C]). For the estimation of the subtypes of PA, first, we compared the CT texture parameters between the adrenal gland with and without excessive aldosterone production on a per-lesion basis using Student’s t test. Then, to select the best combination of parameters to predict the aldosterone production status of each adrenal gland, logistic regression analysis with a stepwise procedure was performed for 5 parameters with the smallest p value in the first step. This number of parameters was selected due to the number of adrenal glands without excessive aldosterone production (n = 54). Finally, as the purpose of the present study was to determine the localization of excessive aldosterone production on a per-patient basis, we subtracted the results of logistic regression analysis  from the right and left adrenal glands, and sought to determine the optimum cutoff value. In all analyses, p < 0.05 was taken to indicate statistical significance.All statistical analyses were performed using EZR software dominant  and [A/Cdominant]  were very high compared to PACnon-dominant and [A/Cnon-dominant] , respectively. For the bilateral PA patients, median of PAC was 2905 ng/dL (lower - upper quartile: 1753–4275 ng/dL) and median of [A/C] was 2.98 (lower - upper quartile: 2.01–5.14).Among the total population of 82 patients, 54 had unilateral PA (right-sided:left-sided = 24:30) and 28 had bilateral PA. For the unilateral PA patients, PAC2 (lower - upper quartile: 95–163 mm2) for the right adrenal gland and 137 mm2 (lower -upper quartile: 106–185 mm2) for the left adrenal gland. Mean0 , mpp0  and mean2  showed statistically significant but weak negative correlation with PAC, And for [A/C], mean2  showed negative correlation and entropy2  and kurtosis2  showed weak positive correlation.On CT, the median of the maximum cross-sectional area of the adrenal gland was 117 mmp value were mean0, mean2, mpp0, entropy2, and entropy4; logistic regression analysis was performed using these parameters and mpp0 (p = 0.003), mean0 (p = 0.026), and entropy2 (p = 0.027) were found to be significant parameters. The model was determined as follows:individual = Logit right adrenal gland − Logit left adrenal gland), the optimum cutoff value was found to be 0.25 . Using this cutoff value, the accuracy of the testing  was 67.1% (55/82).The results of univariate analysis on a per-lesion basis are shown in Table In the present study, we investigated whether the localization of PA can be predicted using quantitative texture analysis on unenhanced CT. The results indicated that mpp0, mean0, and entropy2 were significant parameters, and the model constructed by logistic regression analysis determined the localization of PA with an accuracy of 67.1%.12. In another study including a larger number of PA patients (203 patients with both CT and AVS), CT correctly identified unilateral or bilateral disease in only 53% of cases7. In the same paper, it was reported that 22% patients would have been incorrectly excluded as candidates for adrenalectomy, and 25% may have had unnecessary or inappropriate surgery based on CT findings. Although the accuracy achieved (67.1%) was not satisfactory, CT texture analysis extracted some informative features from unenhanced CT, resulting in greater accuracy compared to previous reports.The accuracy of adrenal CT for localization of the source of excessive aldosterone secretion was reported to be relatively low. In one study of 41 PA patients with AVS, the concordance rate between CT and AVS was only 54%Of the 18 texture features obtained, mpp of the unfiltered image showed the strongest correlation with the status of aldosterone production by the adrenal gland, and adrenal glands with hypersecretion of aldosterone tended to show lower mpp0 values. We speculated that the lower mpp0 value indicated the presence of aldosterone-producing adenoma regardless of whether a tumor was apparent or not. In addition, the difference between the mean and mpp of the unfiltered image was due only to the inclusion or exclusion of negative value pixels. The observation that mpp0 showed the strongest correlation suggests that elimination of negative value pixels may yield better accuracy when analyzing small structures and those close to the bone. Such structures usually suffer from a partial volume effect and streak artifacts: exclusion of the negative value pixels may filter out the outliers from such artifacts.In the direct comparison of texture features and AVS result, not only the features that were used in final model for estimating PA subtypes but also other features such as mean2 and kurtosis2 showed statistically significant correlation with PAC and [A/C]. On contrast, no features using medium filter (SSF: 4 mm) showed significant correlation with measured value of AVS. We speculate that the medium filter was too large to adequately assess the internal heterogeneity of the adrenal glands, and the fine filter (SSF: 2 mm) is proper in assessing the small structure like adrenal gland. There can be a possibility that smaller size of filter (1–2 mm) is more beneficial in assessing adrenal glands, we could not check the possibility since the used software in the present study does not allow smaller filter than 2 mm.et al. reported that most CT texture features were robust among different scanners, except for skewness and kurtosis in filtered images featuring medium and coarse textures26. Second, due to the variety of CT scanning protocols, we could not include data of enhanced images. Further investigations are required to determine whether these images are useful. In addition, the study population was relatively small, so we could not perform validation testing. Future studies in larger numbers of patients are necessary to validate our results.There were several limitations to the present study. First, due to the long study period, different CT scanners were used. However, Yasaka In conclusion, the present study showed that there were correlations between some of the texture features of plain CT and the aldosterone production state of the adrenal gland in PA patients. CT texture analysis may provide a less invasive means of predicting the localization of PA. By searching more adequate size of filtering and combination with more complicated features (e.g. second order features), CT texture analysis may further accurately assess the internal heterogeneity of the adrenal glands, resulting in better prediction of the localization of PA.


The model was informed with the latest available European datasets of domestic and industrial emissions, population and livestock densities. Model parameters were calibrated using 2008–2012 mean annual BOD concentrations measured in 2157 European monitoring stations, and validated with other 1134 stations. The most sensitive model parameters were abatement of BOD by secondary treatment and the BOD decay exponent of travel time. The mean BOD concentrations measured in monitored stations was 2.10 mg O2/L and predicted concentrations were 2.54 mg O2/L; the 90th percentile of monitored BOD concentration was 3.51 mg O2/L while the predicted one was 4.76 mg O2/L. The model could correctly classify reaches for BOD concentrations classes, from high to poor quality, in 69% of cases. High overestimations (incorrect classification by 2 or more classes) were 2% and large underestimations were 5% of cases. Across Europe about 12% of freshwater network was estimated to be failing good quality due to excessive BOD concentrations (>5 mg O2/L). Dominant sources of BOD to freshwaters and seas were point sources and emissions from intensive livestock systems. Comparison with previous assessments confirms a decline of BOD pollution since the introduction of EU legislation regulating water pollution.Biochemical Oxygen Demand (BOD) is an indicator of organic pollution in freshwater bodies correlated to microbiological contamination. High BOD concentrations reduce oxygen availability, degrade aquatic habitats and biodiversity, and impair water use. High BOD loadings to freshwater systems are mainly coming from anthropogenic sources, comprising domestic and livestock waste, industrial emissions, and combined sewer overflows. We developed a conceptual model  still affects about 14% of European surface waters.•In North Europe, livestock waste contributed 38–49% of BOD loads to the sea.•Domestic waste was the major source of BOD to the Mediterranean and Black seas. BOD is 2/L) will amount to 2.5 billion people by year 2050. For Europe, the study projected an increase in organic pollution especially in the Southern Countries due to loss of dilution capacity for rivers in water scarce areas. This projection partly contrasts with the European-wide assessment of Projections of demographic growth coupled with increased demand and consumption of meat and dairy products prompted concerns for worsening of global ‘sanitation crisis’ , especiaAcross Europe BOD is monitored systematically as an indicator of river water quality. An important decreasing trend in BOD concentrations has been detected in the last decade , largely+BOD because it shares the general conceptual structure and extent of the GREEN model (2/L) in freshwater reaches. It was calibrated against BOD concentrations monitored in Europe in 2008–2012. The model conceptualization addresses all potential sources of anthropogenic BOD, including BOD loadings from natural and urban areas, and adopts effective parameters that are suitable for the European conditions. Parameter sensitivity analysis, model calibration and validation are carried out to assess potential sources of uncertainty in the parameterization before presenting an assessment of current organic pollution across Europe. Finally current knowledge gaps and potential use of the model for management scenarios are discussed.The aim of this study was to develop a pan European model to assess current BOD fluxes in freshwater systems. The conceptual model was inspired by previous large-scale models , but infEN model  to track22.12/L). The spatial structure of the model is semi-distributed, based on subbasins that comprise a main reach and the land that drains into it. The main reaches are linked topologically from upstream to the river outlet. The extent and topological structure corresponds to the River and Catchment dataset for Europe . Several sources of BOD are considered. Point sources of BOD loadings comprise urban waste water (UWWTPs discharges) and industrial discharges, and are considered to be discharged directly in the subbasin reach. Diffuse sources encompass organic waste from livestock, scattered dwellings, urban wash off, and organic matter originated from natural areas, like forests and inland waters. Abatement of BOD in waters was based on travel time. Diffuse sources are considered to be reduced in the subbasin before reaching the main stream network. Travel times from diffuse sources from basin release to the main reach are set separately for each source, allowing for different preferential pathways. BOD load in the stream network is degraded during transport as a function of the travel time in the reach  and concentrations  occurring in a subbasin:U = urban wash off BOD (t/y); RU = annual urban runoff (m3/s); and EMCU is the effective mean annual BOD concentration in urban wash off  can act as sinks or sources of BOD to downstream waters. Their role depends on several factors, among which trophic status, hydrology and retention time, type and amount of incoming organic matter, and location within the freshwater network . AutochtAreaNAT (km2). Natural areas were defined as subbasin area not covered by agriculture or urban land according to CORINE Land Cover 2012  was adopted:Emissions of BOD due to organic material either washed off from natural areas or released from lakes were pooled together and assumed to be proportional to the extent of natural land ver 2012 . A simpl2; 2. NAT was set in model calibration , and TTj is the mean travel time in the subbasin (TTB) or reach ; kT,j is the BOD decay in the jth subbasin; and BODOUT = BOD outflux (t/y). As in kT,j was derived from the decay rate at 20 °C k20 and adjusted with Arrhenius equation to account for water temperature:kT,j is the degradation rate [/day] in the jth subbasin, k20 is the degradation rate at 20 °C and Tj is the water temperature [°C] in the subbasin. Water temperature across Europe was assessed with a log-linear function of mean annual air temperature . Before reaching the main stream network, diffuse BOD sources are however attenuated by degradation occurring during the time necessary to arrive to the main reach and in transport through the main freshwater network. BOD attenuation in freshwater was modelled with an exponential decay as a function of travel time , both duperature .k20 of 0.35/day, whereas k20 has been measured in laboratory (0.3–0.5/day) or in rivers , and AB = area of the subbasin (km2); TB was transformed in days for application in Eq. Travel time in the subbasin was based on time lag estimated as a simple empirical function of subbasin area :(5)TB=0.TB is an approximation of travel time in the subbasin via surface flow. However, diffuse sources may follow other pathways, e.g. via interflow, with longer travel time. To adapt travel time by different pathways, source specific delays [days] were added to TB to obtain the source travel time in the subbasin. Domestic waste from disconnected dwellings (SD and IAS) was assumed to leach in the underground and reach the stream network through groundwater or interflow. To account for delay through this pathway an additional time  was added to the time lag , assumed equal to 4 h .l to 4 h . Convers2.1.8TTR (days) was calculated on the basis of reach length and water velocity. Water velocity was estimated from mean annual discharge, assuming hydraulic relationships suitable for the European continent , and sample size. Only mean annual values of sample sizes larger than six measurements/year were used in this study as smaller sample size was considered unreliable. After taking out data entries flagged in the database as outliers or as failing quality assurance checks, 11,115 data in 3252 stations were retained for model calibration and validation. The modal reported detection limit of BOD in the retained database was 0.5 mg O2/L, and about 50% of data entries had detection limits below 1 mg O2/L. Furthermore, BOD7 loads (t/y) for 29 stations in 2008–2015 were provided by BOD monitored in rivers across Europe was retrieved from Waterbase Rivers . Since B2/L with median of 2.11 and interquartile range 1.17–2.33 mg O2/L. Importantly, the spatial distribution of monitored data varied largely across countries, with the densest set located in France but no data from Greece or Hungary (2/y) were higher than mean European values in Bosnia and Herzegovina and lower in Cyprus , on which 2157 (65%) BOD monitoring stations fell , and with decreasing urban wash-off (EMCU). R2 increased with Eff.2, livestock travel time delay (#LVST), and EMCU, but decreased with ENAT. Thus model response to KGE and R2 was opposite for EMCU and ENAT. Few significant correlations were found among model parameters: Eff.1 was positively correlated to industrial bod/toc ratio; effective concentration in urban wash-off (EMCU) was negatively correlated to efficiency in secondary treatment but positively correlated to that of tertiary treatment. Efficiency in septic tanks (Eff.SD) was correlated to efficiencies in secondary or tertiary treatment but was not correlated to model goodness-of fit indices.Within the 1500 simulations, we identified a subset of best parameter sets ; the 90th percentile of predicted BOD concentration was 4.76 mg O2/L, while that of monitored data was 3.51 mg O2/L. In the calibration dataset, the percent bias of BOD concentration was 20% and that of BOD specific loads was 1% , about 12%  of freshwater network for the whole territory,  was mapped to be failing good quality due to excessive BOD concentrations (>5 mg O2/L). Areas of high BOD concentrations were linked to high urban density, especially where untreated domestic waste is still sizable, in zones of high livestock densities, and/or where dilution is limited by low streamflow, like in the Mediterranean region.BOD concentrations were mapped in Europe adopting the same class thresholds of BOD loadings discharged to the sea were estimated at 2.4 M t/y annually . Anthrop4The conceptual model developed in this study builds on literature research , but exp4.1Errors in location of monitoring stations, and by consequence attribution of draining area, can cause considerable deviation in deriving specific loads from the modelled outputs, i.e. mean annual loads. In consideration of the size of spatial units, which are relatively small, this error is likely to play an important role in the evaluation of model results. Location errors would also affect the attribution of mean annual streamflow which is used to transform loads into concentrations and vice versa. Where ancillary information about monitoring stations, like drainage area and streamflow, were reported, these data were used to countercheck location of monitoring stations. However this was rarely possible and location errors could not be excluded.Monitored BOD data is subject to large uncertainty. First of all, BOD measurements in rivers are subject to a relatively large error, about 15–28% . Plus, sErrors in the estimation of mean annual streamflow may play an important role. The Waterbase Rivers database does not report streamflow associated to the water quality data entries, which represents a large limitation in the usefulness of these data for model evaluation, as the impact of streamflow on concentration cannot be quantified. In the model, we relied on long-term mean annual streamflow to derive modelled concentrations (and loads from monitored concentrations), and inter annual streamflow variation could not be taken into account. Further, water abstractions may not be fully considered, thus mean annual streamflow might be overestimated where abstractions are high. For example, in Cyprus BOD concentrations were generally overestimated in the model, whereas specific loads were not . It may 4.22) in which there is no point source emission. It is unlikely that such high BOD specific loads could be generated in the absence of point sources, thus this example points to either an error in the location of monitoring station or a missing BOD point source.Missing model inputs and errors of input location, for example of BOD point source emissions, may also contribute to large local errors. For example, while BOD specific loads in eight out of the ten stations depicted in In terms of uncertainty in input data, domestic waste was assessed to generate 2.3 M t/y, 70% of which discharged as point sources. In EU28, Switzerland and Norway domestic waste was based on the Waterbase-UWWTD database. The database provides unprecedented detailed information of population equivalent generation and discharge. While reporting inconsistencies in the database were noticed and dealt with , the maiE-PRTR totaled 0.8 M t/y, and were largely variable, both as total per country and amounts per inhabitant  or basin retention for extensive systems (87–97%) were equally large, thus BOD to freshwater system was estimated at 1.8 M t/y, second source after point sources direct discharges (2.4 M t/y), confirming previous assessments of the importance of livestock for organic pollution in Europe . LivestoEmissions from urban wash-off was estimated at 1 M t/y, whereas from natural land at 0.6 M t/y. These were thus minor sources of BOD compared to point sources or livestock, however they were still important. Uncertainty in spatial data used to assess them are relatively minor, as both sources were based on a well-established spatial layer , with ur4.3While potential uncertainties in monitored data are to be acknowledged, the sheer number of data entries allowed for a balanced calibration of model parameters , Fig. 5,20 at 0.56 the final distribution of BOD exponential decay rate after correction for water temperature kT ranged from 0.29 to 0.49 across Europe, with mean value of 0.35/day. These values are very much in line with literature . It is hard to assess how reliable this estimation is, as little is known about frequency and volumes of combined sewer overflows (CSO) or of BOD emissions in urban land net of WWTP discharges.EMCficiency , howeveriency . Large reductions (>100 kt/y) in BOD emissions occurred in Great Britain, France, Italy, Spain, Germany, Poland, Belgium, Ireland, the Netherlands and Greece. Conversely, BOD fluxes of this study for a few Nordic countries  were larger than in BOD emissions appear to have significantly declined in Europe since the 2000s . FittingCurrent BOD fluxes have thus declined in time, especially thanks to improvements in wastewater treatments . Decline2/L) in about 12% of freshwater systems (14% of EU28 freshwaters). While reaching full compliance of UWWTD directive will certainly further improve freshwater quality, other management strategies should also be considered. In this assessment, industrial emissions were an important source of BOD loads to European freshwater and the seas. Regulation or reduction of intensive livestock production systems will allow tackling the major source of BOD emissions in agricultural areas. In urban catchments, management of urban wash off may probably reduce BOD effectively. Last but not least, the reduction of streamflow, and thus of BOD dilution capacity, due to increasing water demands or climate change, may exacerbate poor habitat conditions, particularly in water scarce areas. The current model may help exploring the likely impact of these scenarios at the European scale.Water quality due organic pollution was assessed to be in moderate to poor conditions  were 2% and large underestimations were 5% of cases. The model was thus judged fit to assess current mean conditions across Europe, albeit errors in detecting high BOD concentrations remained high. Potential improvement in the model could be achieved by (i) improving input datasets, for example industrial BOD emissions; (ii) enlarging the BOD monitoring dataset, especially in regions currently under or not represented; and (iii) coupling the model to a more dynamic hydrological model to take into consideration the impact of annual streamflow changes on BOD concentrations. Importantly, given uncertainty in inputs and outputs highlighted by the analysis, further research should aim at assessing model uncertainty in BOD fluxes spatially.Acknowledging uncertainty in sources and hydrological pathways, ten model parameters were calibrated at 2157 BOD monitoring stations. This allowed for robust characterization of the model, yielding a final parameter set that mostly confirmed literature values. Model mean absolute errors were 1.2 mg O2/L). Dominant sources of BOD emissions were point sources and intensive livestock systems. Improving wastewater treatment may reduce BOD loads effectively, especially in Eastern Europe. Compliance of regulative efforts set by the UWWTD Directive are however close to reach their maximum impact. Regulation and reduction of industrial emissions may abate BOD loadings to the seas effectively, especially if targeting emissions in coastal areas. Thus while current legislative regulations may still improve conditions further, other management strategies should also be considered to reach or maintain the good ecological status of freshwater systems as required by the WFD. The conceptual model can help exploring the effectiveness of potential alternative management at the European scale.About 262,000 km (12%) of freshwater network  were assessed as being in moderate to poor conditions due to organic pollution (BOD concentrations > 5 mg O


Ophiorrhiza japonica and designated as OjCHI. Multiple sequence alignments and phylogenetic analysis revealed that OjCHI had the conserved CHI active site residues and was classified into type I CHI group. In order to better understand the mechanisms of anthocyanin synthesis in O. japonica, integrative analysis between metabolites and OjCHI expression was conducted. The results showed OjCHI expression matched the accumulation patterns of anthocyanins not only in different tissues but also during the flower developmental stages, suggesting the potential roles of OjCHI in the biosynthesis of anthocyanin. Then biochemical analysis indicated that recombinant OjCHI protein exhibited a typical type I CHI activity which catalyzed the production of naringenin from naringenin chalcone. Moreover, expressing OjCHI in Arabidopsis tt5 mutant restored the anthocyanins and flavonols phenotype of hypocotyl, cotyledon and seed coat, indicating its function as a chalcone isomerase in vivo. In summary, our findings reveal the in vitro as well as in vivo functions of OjCHI and provide a resource to understand the mechanism of anthocyanin biosynthesis in O. japonica.Anthocyanins are distributed ubiquitously to terrestrial plants and chalcone isomerase (CHI) catalyzes the stereospecific isomerization of chalcones – a committed step in the anthocyanin biosynthesis pathway. In this study, one gene encoding CHI was isolated from  Anthocyanins, a kind of natural pigment, are widespread in plants and predominantly found in flowers, fruits, vegetables, cereals as well as teas . Among mS)-flavanones  obtained from the Arabidopsis Biological Resource Center were in the Columbia ecotype background and grown under the conditions as described before  for 12 h in darkness at 4°C. Then the extracts attained were centrifuged at 12,000 rpm for 10 min, and the supernatant was passed through a 0.22 μm reinforced nylon membrane filter before subjecting to HPLC identification. The Shimadzu HPLC system with API 2000 mass spectrometer was used for qualitative analysis according to the protocol as described by O-glucoside and quercetin-3-O-glucoside standards  (The composition and contents of anthocyanin and flavonol were determined by high-performance liquid chromatography (HPLC). For extraction, 0.1 g flour of each sample was homogenized in 1 ml extraction solvent (H States) . Each saO. japonica measured before, a total of five sequences of the CHI gene from O. japonica were identified through blastn alignment with reference genes of proximal species and Arabidopsis CHI protein sequence. Then comparative analysis was conducted by using the following database: national center for biotechnology information (NCBI) and the results indicated that the sequence of unigene (OjCHI) (Unigene35425_All) showed the highest similarity to CHI genes from other plants. Therefore, the specific primers (OjCHIF1 and OjCHIR1) were designed from sequence information of OjCHI gene. To isolate the total RNA, flowers of O. japonica at stage 4 were ground into powder and extracted by RNA pure Plant Kit . Then the cDNA was synthesized from 1.0 μg total RNA using EasyScript One-Step gDNA Removal and cDNA Synthesis SuperMix . Subsequently, for obtaining the full-length sequence of OjCHI, its complete open reading frame (ORF) generated by RT-PCR was cloned into pMD18-T vector and sequenced by Sangon Biotech . All the primers used in this work are listed in Based on the transcriptome data of different tissues of OjCHI and actin were designed by using IDT1 and listed in TransStart® Green qPCR SuperMix . Each PCR reaction in 20 μl volume included 10 μl 2× TransStart® Green qPCR SuperMix, 0.8 μl forward and reverse primers, 1 μl template cDNA and 9.2 μl Nuclease-free water. To confirm purity of the PCR products, melting curve analysis and sequencing was employed. The 2-ΔΔCT method was used for OjCHI expression analysis through normalizing to the actin gene from O. japonica  in Escherichia coli strain BL21, respectively. The overnight bacterial cultures obtained from a single transgenic colony were diluted into LB medium and grown to OD600 = 0.6, at which point 0.35 mM isopropyl β-d-thiogalactoside was added to induce recombinant protein expression at 30°C for 10 h. Then the cells were harvested through centrifugation at 6,000 rpm for 10 min and disrupted by sonication on ice. The His6-tagged recombinant proteins were purified using Ni-NTA pre-packed column  following the manufacturer’s recommendations and its purity was finally tested by SDS-PAGE.The open reading frame of Chalcone isomerase activity for production of naringenin from naringenin chalcone was performed in a total volume of 50 μL containing 50 mM potassium phosphate (pH 7.5), 50 μM substrate and 10 μg purified recombinant OjCHI protein. Soluble protein extract from induced BL21 containing empty pET-32a vector was used as a control. After incubating at 30°C for 5 min, the reaction mixtures were terminated and extracted twice with 100 μL ethyl acetate, and centrifuged at 12,000 rpm for 10 min. Subsequently, the supernatant was subjected to high-performance liquid chromatography analysis using a Shimadzu HPLC system. The mobile phases were composed of 50% methanol, 48% water, and 2% acetic acid at a flow rate of 0.8 ml per minute. The enzymatic products were detected at 304 nm with a column temperature of 40°C.OjCHI was amplified by PCR with primers OjCHIF4 and OjCHIR4 -naringenin are conserved in OjCHI. Importantly, the residues proposed to determine substrate preference in type I CHIs  are also presented in OjCHI  and flowers at different developmental stages were identified and quantified  and type II (MsCHI) CHI, we found OjCHI had all conserved amino acid residues and contained Ser and Ile at position 190 and 191, respectively  on the basis of their substrate specificity and catalytic activity, moreover, the type II CHI proteins are regarded as “legume-specific” CHIs  was catalyzed into a product with its retention time identical to that of naringenin . This rehocyanin . To bestic” CHIs . But rec II CHIs . TherefoO. japonica but lacked pelargonidin derivatives – based on this, the proposed anthocyanin pathway was listed in Petunia hybrida and Angelonia angustifolia found, due to the DFR substrate specificities, both plants unable to synthesize pelargonidin-based anthocyanins (Anthocyanin qualitative analysis indicated that four kinds of anthocyanins had been detected in ocyanins . On the ocyanins .CHIs have been investigated in various plants, and their transcripts sometimes are congruent with the accumulation of anthocyanins in target tissues (CHI gene in O. japonica have not been reported yet. Therefore, transcript analyses of OjCHI in different tissues were conducted. As shown in OjCHI was actively transcribed in all organs examined, and showed relatively low expression in the root, which is similar to that of CHI in herbaceous peony (CHI genes were always strong in root, because they would act as signaling molecules to play crucial roles during root-nodule development (OjCHI in root suggests that OjCHI is not a leguminous CHI and probably responsible for the formation of anthocyanin and proanthocyanidin. Correspondingly, we did note OjCHI transcripts in different tissues were strongly consistent with the accumulation of anthocyanin, which further verified its function in anthocyanin biosynthesis (OjCHI gene during flower developmental stages were also performed (OjCHI showed higher expression in the earlier bud than the fully opened flowers which matched the accumulation pattern of anthocyanin (Gentiana triflora (CHIs in flowers has already been reported in tulips, Chrysanthemum, as well as petunia, and the studies demonstrate that different expression patterns of CHIs are a determinant for petal color variations (CHI gene conferred red petals in petunia, while inhibiting its expression made tobacco petal coloration turn to yellow (OjCHI may regulate the accumulation of pigment during O. japonica flower development.Expression levels of  tissues . Howeverus peony . Previouelopment . So, theynthesis . Furthererformed . At diffhocyanin , consisttriflora . Transcrriations . For inso yellow . Thus, tOjCHI was further investigated through its over-expression in Arabidopsis tt5 mutant. The results present in OjCHI could recover the color phenotypes of seed, cotyledons and hypocotyls of tt5 mutant and rescue the deficiency of flavonoid accumulation, which demonstrated the capacity of OjCHI in catalyzing the cyclization of endogenous chalcone to produce flavonols, proanthocyanidins and anthocyanins. Likewise, such in vivo activity of CHI gene from alfalfa and Ipomoea batatas also obtained the same results, suggesting that CHI proteins involved in flavonoid metabolism are functionally exchangeable among distantly related plants (tt5 mutant, and this raise the possibility that CHI may have functions other than catalyzing naringenin chalcone, perhaps serving as transporters and/or chaperons during flavonoid biosynthesis, or functioning as a structural scaffold for enzymes in flavonoid pathway (Functionality of d plants . Meanwhi pathway .CHI gene, OjCHI, which plays a significant role in anthocyanin biosynthesis in O. japonica. Integrative expression analysis indicated that OjCHI had tissue-specific expression and its transcription pattern coincided with the change of anthocyanin accumulation not only in different tissues but also in developing flowers. In vitro enzyme assays of recombinant OjCHI confirmed its predicted function in the biosynthesis of anthocyanin. Moreover, the in vivo genetic analysis of OjCHI in Arabidopsis tt5 mutant further proved its role in proanthocyanidin and anthocyanin biosynthesis. Therefore, the findings from this article will advance our understanding of the molecular mechanisms of anthocyanin biosynthesis in O. japonica, and also provide a basis for flavonoid manipulation studies through using molecular approaches in the future.In conclusion, in this study we have functionally identified one All datasets for this study are included in the manuscript and the ZJ and YY conceived and designed the study. WS, HS, HX, and XT conducted the experiments, analyzed and interpreted the data, and wrote the manuscript. WS, MT, ZJ, and YY revised the manuscript critically. All authors read and approved the final manuscript.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.


Cyprinella lutrensis) were exposed to four water turbidity treatments and their opsin genes were cloned to elucidate how opsin gene expression could be modulated by ambient light conditions. Opsin gene cloning revealed that these fish have single RH1, SWS1, SWS2 and LWS genes and two RH2 genes. Phylogenetic analysis also indicated that these two RH2 opsin genes–RH2A and RH2B –are in-paralogous. Using quantitative PCR, we found evidence that opsin expression is plastic in adults. Elevated proportional expression of LWS in the cone under ambient light and turbid treatment indicated that the red shiner’s visual spectrum displays a red shift in response to increased turbidity.Vision is very important to fish as it is required for foraging food, fighting competitors, fleeing from predators, and finding potential mates. Vertebrates express opsin genes in photoreceptor cells to receive visual signals, and the variety of light levels in aquatic habits has driven fish to evolve multiple opsin genes with expression profiles that are highly plastic. In this study, red shiners ( Fish make up the largest and most diverse group of vertebrates; some species have successfully adapted to a variety of physiologically challenging habitats that range from freshwater to seawater, cold polar regions to hot desert climates, and the Mariana Trench to high mountain lakes. With rare exceptions, such as eyeless cave-dwelling species, vision is necessary for fish to forage for food, fight competitors, flee from predators, and find potential mates .The lighting environment is characterized by the spectral composition of light (intensity at each wavelength), the total intensity of light, the transmission properties of the medium (such as air or water), the locations exposed to light, and the surrounding visual background . Comparemax) of visual pigments [RH1). The cone cell is used for photopic vision and expresses the other four families of opsins: short-wavelength sensitive 1 , short-wavelength sensitive 2 , medium-wavelength sensitive , and long-wavelength sensitive  [In order to receive visual signals, vertebrates rely on visual pigments located in light-accessible outer segments of photoreceptor cells. These pigments contain vitamin A-derived choromophores, including vitamin A1  or A2 , that are linked to opsin proteins, which are G protein-coupled receptors. Compositional differences in either the type of choromophore or opsin gene product may alter the maximal absorbance wavelength (λpigments . Vertebrmax red) .max values. For example, zebrafish (Danio rerio) were shown to have two LWS and four RH2 paralogs; the λmax values of LWS-1 and LWS-2 were 558 and 548 nm, while those of RH2-1 to RH2-4 were 467, 476, 488 and 505 nm, respectively [Oryzias latipes) also has two LWS paralogs, plus three RH2 and two SWS2 paralogs. The λmax values of medaka LWS-A and LWS-B were reported to be 561 and 562 nm; RH2-A, RH2-B and RH2-C were 452, 516 and 492 nm; and SWS2-A and SWS-2B were 439 and 405 nm, respectively [Living in aquatic habitats and facing variable lighting environments, fishes have evolved three genetic features for perceiving color in ambient light conditions: opsin gene duplication, mutations in opsin genes, and plasticity in opsin expression –9. Some ectively . Medaka ectively .max value of the visual pigment [RH1 was highly correlated with the preference for shallow or deep water [Pomatoschistus minutus) exhibited significant diversifying selection on the RH1 gene, but the North Sea ones exhibited stabilizing selection on the same locus [LWS gene of Lake Victoria cichlids and guppies (Poecilia reticulata) not only helped the species adapt to the environment but also resulted in the differentiation of mating preference [Opsin gene mutations that cause substitutions in amino acids, especially those that interact with the chromophore, can greatly affect the λ pigment ; therefoep water . Additiome locus . Moreoveeference –18SWS1 to SWS2, which brought about a red-shifted detection profile in cone cells [Chanos chanos) when moving from nursery waters, such as lagoons and estuarine areas, into to the ocean after reaching the juvenile stage [Anguilla japonica) and giant mottled eel (A. marmorata) lead to an ontogenetic blue shift in rod cells [Oreochromis niloticus) has a profound effect on adult opsin expression profile [Lucania goodei) displays plasticity in opsin expression as an adult; it can quickly modify cone opsin expression level in response to exposure to clear spring waters or tannic acid-stained swamp waters within a few days [Although opsin gene duplications and mutations have equipped fish with a variety of opsins, it takes time for a population to acclimate to both through evolutionary events; these evolutionary adjustments cannot immediately enable an individual fish to adjust its visual sensitivity to new surroundings. Many fishes have been found to rely on the plasticity of opsin gene expression to cope with novel or varied lighting environments due to transitory events, such as life history transitions, movement between habitats, or seasonal changes in habitat. The salmonid fishes exhibited a time-dependent opsin expression switch from ne cells  in prepale stage , 21. On od cells , 23. Bes profile , 25. Howfew days , 27. Morfew days –30.Cyprinella lutrensis) are small-bodied cyprinids (> 90 mm) that are widely distributed over the Great Plains of the United States. These fish can tolerate extreme environmental conditions–such as low oxygen, high acidity, varied temperature, and turbidity–better than other North American cyprinids [Cyprinella spp.) have a special crevice spawning behavior. During the breeding season, males express sex-limited nuptial coloration and compete with each other to establish territories. The territorial male expels intruding males through threat displays or ‘mock battles’ to protect spawning substrates (e.g. rocks and twigs), and it courts a female by circling her [Red shiners , ranging from 35 to 50 mm in standard length (SL), were purchased from an aquarium store in Taipei City and transported to the Marine Research Station, Academia Sinica, where they were housed in glass aquaria (90 cm Length x 40cm Width x 40 cm Height) at 25–30°C with a 12L:12D photoperiod for at least one month before being moved to four experimental aquaria (45 cm Length x 43 cm Width x 40 cm Height). Fish were fed ad libitum with artificial fish feed and frozen Artemia twice a day. All experiments were performed and specimens handled with approval (RFiZOOHY20060701) from the Institutional Animal Care and Use Committee (IACUC) of Academia Sinica.Red shiners  and mainly ranges from 400 nm to 700 nm. The ambient light spectra of 0 NTU and 200 NTU experimental aquaria were measured using an AvaSpec Micro . The light in the water was measured upwelling at 8 cm depth. The relative spectral irradiance was smoothed by a factor of 30 using a simple moving average, and then normalized to where 100% indicated the intensity at 550 nm. The red shiners were fed twice a day in the experimental aquaria and were sampled after exposure to this treatment for one month.Kaolin , which consists of clay particles with high surface area that facilitates suspension, was added to tap water to create turbid conditions, 50, 100, and 200 nephelometric turbidity units (NTU); tap water was assumed to be 0 NTU. The absorbance spectra of these four turbid conditions were measured every 30 nm from 400 to 700 nm by a spectrophotometer  with distilled water as the reference. Each turbid sample was measured with three replicates. The four different NTU levels were set up in individual aquaria, each holding 20 red shiners. Air was pumped into each experimental aquarium, not only to provide oxygen, but also to keep the kaolin particles suspended. The light source for each aquarium was a MASTER TL5 HE 28W/865, PHILIPS, which was placed approximately 28 cm above the water’s surface; the photoperiod was set to 12L:12D. The spectrum of the light source is available on the PHILIPS website  solution. After the fish were rendered comatose, body weight and SL of each specimen were measured. An RNeasy mini kit  was used to isolate total RNA according to the manufacturer’s protocol. The two eyes of each specimen were collected and placed in a 2 ml microcentrifuge tube with stainless steel beads, where the tissue was homogenized by a TissueLyser II (QIAGEN). Total RNA contents and quality were measured by NanoDrop 1000 (Thermo Scientific). Two micrograms of total RNA were reverse transcribed with Super-Script III First-Strand Synthesis SuperMix ; Oligo(dT)20  was used as a primer.The primers from Wang et al.  and Chenhttp://www.translator.co.uk), which is designed to align protein-coding nucleotide sequences based on their corresponding amino acid translations [Other cyprinid opsin gene sequences were downloaded from NCBI and two genes, VAL-opsin and tmt-opsin, were selected as outgroups . All opsslations .Phylogenetic analyses were performed using partitioned Maximum Likelihood (ML). RAxML 8  was usedThe specific primers designed for qPCR were based on the sequences identified from our opsin gene cloning experiments. The amplification efficiency and melting curve of each qPCR primer pair was tested by 5-fold serial dilutions of the templates, with three replicates for each gene and sample. Each qPCR primer pair was adopted only when its amplification efficiency fell between 95% and 105%. Expression of opsin genes and the reference gene was determined by qPCR with an Applied Biosystems StepOnePlus system (Applied Biosystems). Each reaction contained Fast SYBR Green Mastermix (Applied Biosystems), 20 ng of cDNA, and 50 nM of each primer  in a fin(hk) expression of each opsin gene with respect to the housekeeping gene, cytochrome c oxidase subunit 1 (CO1), was calculated according to the following equation:Expression of each opsin gene was calculated using two methods. First, the relativeTi/TCO1 is the expression of each opsin gene i relative to the expression of CO1. Ei is the amplification efficiency for each pair of opsin primers, and ECO1 is the amplification efficiency for CO1 pair of primer. Cti is the average critical cycle number for each opsin gene, and CtCO1 is the average critical cycle number for CO1. Relative(hk) expression values represent the level of opsin gene expression relative to that of the housekeeping gene, CO1.Second, the proportional expression of the cone opsin genes with respect to the total cone opsin pool was calculated according to the following equation:Ti/Tall is the proportional expression for a given opsin gene i.MANOVA  was used to determine if the cone opsin expression profiles differed with turbidity treatment. When MANOVA revealed that cone opsin expression indeed differed by turbidity treatments, the expression of each cone opsin was first examined in the distinct turbidity treatments by Levene’s test and then compared using Tukey’s pairwise comparisons (one-way ANOVA). The statistical tests were performed on R version 3.2.3 .RH1)–and five cone opsins–one SWS1 gene, one SWS2 gene, two RH2 (RH2A and RH2B) genes, and one LWS gene. In the ML tree  absorbed relatively more short than long wavelength light , while tF3, 27 = 6.729, P < 0.01) and the proportional expression . The one-way ANOVA test revealed that the relative expression values of each cone opsin were significantly different among different levels of turbidity  , SWS2 , and LWS  were significantly different across turbidity levels  ; howevery levels .post hoc test further demonstrated that the relative expression value of SWS1 in the 0 NTU environment was significantly lower than those in 100 NTU  and 200 NTU . The relative expression of SWS2 in 0 NTU was significantly lower than in 50 NTU , NTU100  and 200 NTU . RH2A in 0 NTU was significantly lower than in 100 NTU . RH2B in 0 NTU was significantly lower than in 50 NTU , 100 NTU  and 200 NTU . LWS in 0 NTU was significantly lower than in 50 NTU , 100 NTU  and 200 NTU . In general, the red shiner expressed more in all five cone opsins in response to increased water turbidity. Moreover, the HSD post hoc test demonstrated that the proportional expression of cone opsin SWS1 in the 0 NTU environment was significantly or marginally higher than those in 50 NTU , 100 NTU , and 200 NTU . The proportional expression of SWS2 in 0 NTU was significantly higher than that in 100 NTU . LWS in 0 NTU was significantly lower than in 50 NTU , 100 NTU , and 200 NTU . Overall, compared to the other opsins, LWS became the dominant cone opsin when the red shiners were exposed to turbid water.Tukey’s honestly significant difference (HSD) RH1, SWS1, SWS2 and LWS genes and two RH2 genes were amplified from the red shiner. In our phylogenetic analysis  was shown to suffer from search inefficiency in humic water, possibly due to limited plasticity in opsin expression [Color vision results from the integration of signals from different stimulated cone cells in the retina . The chaght Figs . The shiid water . Besidesne cells –62. The pression , 64. Henpression  assertedpression –69.C. venusta) was incomplete, the females of these species were more responsive to conspecific mates. Interestingly, both laboratory experiments and field data demonstrated that turbidity weakened the strength of the behavioral isolation between these two shiners and hence made hybridization possible [All shiners are phylogenetically closely related and many are sympatric; moreover, historical and current genetic introgressions have been detected in shiners , 70. Reppossible , 72.According to the model presented by Mitchem et al. , color pFinally, the loss of opsin expression plasticity in adults supports the idea that it is costly to remodel a phenotype once it is developed , 63, 76.S1 TableThe original data of cone opsins relative and proportional expression values for different turbidity treatments.(CSV)Click here for additional data file.S2 TableThe original data of light spectra of the 0 NTU and 200 NTU.(CSV)Click here for additional data file.S3 TableThe original data of absorbance spectra measured by VersaMax ELISA Plate Reader.(CSV)Click here for additional data file.