Saccharomyces cerevisiae. Thirteen phosphorylation sites were mutated, and a combination of three site mutations in Acc1p, S686A, S659A, and S1157A, was found to increase malonyl-CoA availability. S686AS659AS1157AACC1 expression also improved the production of 3-hydroxypropionic acid, a malonyl-CoA-derived chemical, compared to both wild type and the previously reported S659AS1157AACC1 mutation. This mutation will also be beneficial for other malonyl-CoA-derived products.Malonyl-coenzyme A  is a critical precursor for the biosynthesis of a variety of biochemicals. It is synthesized by the catalysis of acetyl-CoA carboxylase (Acc1p), which was demonstrated to be deactivated by the phosphorylation of Snf1 protein kinase in yeast. In this study, we designed a synthetic malonyl-CoA biosensor and used it to screen phosphorylation site mutations of Acc1p in  Saccharomyces cerevisiae is a very potential microbial cell factory for production of a wide range of fuels and chemicals due to its robustness and high tolerance to environmental stresses. When engineering the cell factory to produce these products, the precursor availability is one of key limiting factors that affects the product titer. Malonyl-coenzyme A  is a major precursor for the production of many important biochemicals and biofuels, such as polyketides, flavonoids, and fatty acid-derived chemicals  and it is subsequently used for fatty acid synthesis. Acc1p is crucial for fatty acids biosynthesis and the maintenance of the nuclear envelope. Acetyl-CoA carboxylases are large, multidomain enzymes and contain a biotin carboxylase (BC) domain, a carboxyltransferase (CT) domain and a biotin carboxyl carrier protein (BCCP) domain. Eukaryotic ACCs also contain two non-catalytic regions, the large central domain (CD) and the BC–CT interaction domain (BT)  . As the or Opi1p . The enzrevisiae . It is rrevisiae , then thn by 50% . Asides response . Thus, SRattus norvegicus (rat) Acc1p with yeast Acc1p and identified an amino acid (Ser1157) that is critical for phosphorylation and causing deactivation of the enzyme. The introduction of a S1157A mutation in Acc1p increased its activity and enhanced polyketide 6-methylsalicylic acid and native fatty acid production  and its DNA binding site (fapO operator) .The Acc catalytic activity determination is complicated, therefore limited the high-throughput screening the mutation libraries of the enzyme. Intracellular malonyl-CoA concentration is another way to reflect the Acc activity. The malonyl-CoA biosensor has been designed in perator) . Li et aoduction . David ioduction . HoweverS. cerevisiae that has higher sensitivity and low leaky transcription which is very important for library screening. The sensor we designed showed better response to malonyl-CoA concentrations than previously reported sensors. Then we used the sensor to detect the effect of mutating all possible phosphorylation sites of Acc1p. A mutation, Acc1p (S686AS659AS1157A), that could increase the concentration of malonyl-CoA and the production of 3-HP  , was isolated.In this study, we aimed to construct a malonyl-CoA sensor in Saccharomyces cerevisiae strain CEN.PK102-5B  was used as the background strain. Synthetic complete (SC) dropout medium was used for recombinant yeast strain selection. The SC medium contained 1.7 g/L yeast nitrogen base , 5 g/L ammonium sulfate, complete supplement mixture  , and 20 g/L glucose. In total, 800 μg/mL G418  was used for selecting strains with the rKan marker. For routine cloning procedures, Escherichia coli Trans2-Blue  was used and grown in Luria–Bertani (LB) medium with 100 μg/L ampicillin.All the plasmids and strains used in this study are listed in Supplementary Tables MCR from Chloroflexus aurantiacus was codon optimized, digested with NotI and SacI, and ligated into the 2 μ plasmid pIYC04 under the control of the TEF1 promoter and ADH1 terminator. T4 DNA ligase  was used for plasmid construction.The malonyl-CoA reductase encoding gene fapR expression, the codon-optimized fapR was digested with SacI and SalI and then ligated into the pre-digested 2 μ plasmid pYX242WS, resulting in the plasmid pYX242WS-fapR. A synthetic promoter was constructed by combining 203 bp of the TEF1 promoter upstream activation sequence and 147 bp of the GAL1 core promoter (with an identified TATA box). The FapR binding site, 17 bp of the fapO operator (TTAGTATCAGGTACTAA), was inserted into the GAL1 core promoter, 7 bp immediately behind the TATA box and replaced the original sequence to obtain the synthetic promoter GAL1p(7)fapO  (yeGFP (yeast-enhanced green fluorescent protein-encoding gene) was fused with the synthetic promoter by fusion PCR, and the fragment was then digested with AatII and EcoRI and inserted into the pre-digested pYX242WS or pYX242WS-fapR plasmid to create pJfapO and pJfapO-fapR. To obtain synthetic promoters GAL1p(61)fapO and fapO(0)GAL1p, the fapO operator was inserted 61 bp behind or immediately upstream the TATA box separately. Each of the synthetic promoters was fused with yeGFP and then was cloned into a 2 μ plasmid to obtain plasmid pIFapO(0) and pIFapO(61) through yeast homologous recombination. The codon-optimized fapR with SV40 NLS sequence at the 3′ end was digested with NotI and SacI and then cloned into plasmids pIFapO(0) and pIFapO(61) separately to create pIFapO(0)-FapR and pIFapO(61)-FapR. To obtain a low level of fapR expression, fapR, which was controlled by the TEF1 promoter, was integrated into the yeast genome using rKan as the selection marker. The plasmid pJFE3-fapO was transformed into the fapR integration strain. The sequence information of fapR and MCR was included in supplemental data.For a high level of gure 2A) . The yeGACC1 sequence with mutated residues was obtained by fusion PCR. ACC1 mutations were inserted into the 2 μ plasmid pJFE3 under the control of the TEF1 promoter and PGK1 terminator through yeast homologous recombination. The constructed plasmids were verified by PCR and sequencing.Site-directed mutagenesis was introduced by designing mutant sites containing primers. A full 3V, PerkinElmer, United States). The excitation and emission wavelengths for GFP were 485 ± 20 and 585 ± 20, respectively. The cell density was measured at 600 nm . The fluorescence intensity (a.u.) was determined relative to cell density. To detect the fluorescence intensity of the mutations, the strains were pre-cultured overnight, inoculated in shake flasks at an initial OD600 of 0.2 in 10 mL of SC medium, and cultivated 30°C at 200 rpm. Samples were taken after 6 h, and fluorescence was measured as described above.Fluorescence intensity was used to evaluate the sensor activity. The sensor-carrying strains were pre-cultured overnight. The overnight culture was collected and inoculated into 3 mL of fresh SC medium at an initial OD600 of 1 at 30°C, 200 rpm, and different concentrations of cerulenin  were added if necessary. For the fluorescence intensity assay, a 1 mL culture was isolated after 2 h of growth and centrifuged at 4°C and 13,000 rpm for 2 min, and the pellets were washed twice with distilled water. A 200 μL cell suspension was used for fluorescence intensity measurement in triplicate. Fluorescence was measured using a 1420 Multilabel Counter  equipped with an Aminex HPX-87H column  at 65°C using 2.5 mM HBacillus subtilis (fapO (the operator region on the fap regulon) in the promoter region, which blocks the access of RNA polymerase II, thus repressing the transcription of downstream fatty acid pathway genes. Malonyl-CoA interacts with FapR and triggers a conformational change in FapR, consequently enabling FapR to disassociate from DNA and relieve the transcription repression. Based on that, we designed a malonyl-CoA sensor in S. cerevisiae and used yeGFP as a reporter to monitor the intracellular malonyl-CoA levels. To obtain a more efficient sensor, the leaking transcription should be low, which means that when fapR binding to fapO, the basic transcription level should be low. In addition, the sensor also needs to response to the change of malonyl-CoA level sensitively, which means that the dynamic change of the fluorescence intensity should be high. Therefore, we chose a synthetic hybrid promoter containing the upstream activated sequence (UAS) of TEF1 promoter and core promoter sequence (begin with TATA box) of GAL1. The UAS from TEF1 allowed the high expression of downstream gene without fapR binding, and TATA box in the core promoter facilitate to decide the locations of fapO operator. The FapR binding site, 17 bp of the fapO operator, was inserted either 7 bp or 61 bp downstream of the TATA box in GAL1 core promoter, or immediately upstream the TATA box, and yeGFP was controlled by these synthetic hybrid promoters in a 2 μ plasmid . The codon-optimized fapR was expressed under the control of the TEF1 promoter in a 2 μ plasmid. When fapO was inserted 7 bp downstream of the TATA box [GAL1p(7)fapO for briefness], the transcription was almost completely shut down. The fluorescence intensity with FapR was only 0.05% relative to that without FapR, demonstrating the efficient repression effect of FapR when binding to this position . However, when fapO was inserted 61 bp downstream of the TATA box [GAL1p(61)fapO for briefness] or immediately upstream of the TATA box [fapO(0)GAL1p for briefness], no transcription repression was observed, demonstrating that the location of fapO on these two sites was not efficient enough for FapR to inhibit transcription initiation.Malonyl-CoA acts as a direct and specific inducer of FapR-regulated promoters in subtilis . FapR bifapO location in promoter, we also detected the expression level of FapR to the behavior of the sensor. The fapR was integrated into the genome to obtain low expression level, and the yeGFP was controlled by the GAL1p(7)fapO synthetic promoter. We found that compared with the FapR expressed in a 2 μ plasmid, a low level of FapR expression resulted in high fluorescence intensity which implicated that low FapR expression caused high leaky transcription .Besides the effect of Figure 2C, as for the sensor containing the GAL1p(7)fapO synthetic promoter, with a gradient supply of cerulenin, the fluorescence intensity also increased gradually, reaching to eightfold with 10 μM cerulenin (saturated concentration) relative to the condition without cerulenin in high FapR expression strain. The fluorescence intensity only increased onefold with cerulenin supply in low FapR expression strain . As expected, the fluorescence intensity of the sensor containing fapO(0)GAL1p or GAL1p(61)fapO synthetic promoter did not increase with increased dose of cerulenin addition, indicating these two designs could not respond the malonyl-CoA concentration. These results demonstrated that high FapR expression combined with GAL1p(7)fapO synthetic promoter showed better response to the change of malonyl-CoA levels.Cerulenin inhibits fatty acid synthesis by specific inhibition of β-ketoacyl-acyl carrier protein synthetase , and inhTable 1), the sensor with GAL1p(7)fapO synthetic promoter and high FapR expression designed in this study showed a low leaky transcription and a better sensitivity to the change of malonyl-CoA levels, which are very important properties for library screening.Comparing with the previously reported malonyl-CoA sensor , which confirmed 15 phosphorylation sites of Acc1p via MIDAS. The other two predicted phosphorylation residues are not existed in the Acc1p from CEN.PK background strain used in this work. The phosphorylation residues were mutated to alanine. The sensor plasmid was then transformed into the Acc1p mutation-containing strains to screen the malonyl-CoA-overproducing mutants. We found that the fluorescence intensity of strains containing Acc1p(S686A) and Acc1p(T1823A) was increased relative to the wild type, even though the increased range was still lower than strain with the previously reported Acc1p(S659AS1157A) double mutation. The remaining phosphorylation site mutations did not show a positive effect on malonyl-CoA levels . We further combined S686A and T1823A single mutations with the S659AS1157A double mutation to see if the combination mutations can achieve further increase in malonyl-CoA generation. As shown in Figure 3C, the introduction of the S686A mutation further improved the fluorescence intensity of the S659AS1157AACC1-expressing strain, whereas T1823A did not further enhance the fluorescence intensity, although the fluorescence intensity of the Acc1p(T1823A) mutant was higher than wild-type Acc1p. These results indicated that Acc1p(S686AS659AS1157A) can produce more malonyl-CoA and should have higher enzyme activity.Although mutations of Ser659 and Ser1157 phosphorylation sites have been shown to improve the synthesis of malonyl-CoA-derived products, it remains unclear whether other phosphorylation sites may have a positive impact. In this work, we mutated 13 predicted phosphorylation sites of Acc1p according to Figure 1). The heterogeneous gene MCR, which encodes a bifunctional enzyme that includes malonyl-CoA reductase and 3-hydroxypropionate dehydrogenase, was overexpressed in Acc1p mutation strains . This finding confirmed that the S686AS659AS1157A mutation of Acc1p contributed to an increase in malonyl-CoA availability. However, the S686A single mutation of Acc1p did not improve 3-HP production. This result indicated that S686A could benefit 3-HP production only when integrated with the S659AS1157A mutation. Additionally, although the fluorescence intensity of T1823AACC1- and T1823AS659AS1157AACC1-expressing strains was higher than the wild type, 3-HP production did not increase, excluding the positive role of T1823A for 3-HP generation. Cell growth of the engineered strains was not obviously changed by ACC1 mutation expression . Although these malonyl-CoA sensors used operators from the same origin (fapO from B. subtilis), the behavior is very different when inserting the operator to different promoters. As for the TEF1-GAL1 synthetic promoter in this work, the transcription was not repressed when fapO was located immediately upstream TATA box, while the same position in GPM1 promoter worked well. When the distance between fapO and the TATA box in TEF1-GAL1 synthetic promoter extended to 61 bp, the transcription repression effect was disappeared. It seems that inserting one operator 7 bp downstream of TATA box in TATA-containing promoter is enough for FapR to repress the transcription initiation, whereas it is not the case when the operators were inserted to the TATA-less promoter TEF1 where three operators were needed to repress the transcription effectively. In fact, the promoter property and operator locations are important to decide the performance of the biosensors.To facilitate the screening of phosphorylation site mutations, a malonyl-CoA sensor was constructed. Compared with the other two previously reported malonyl-CoA sensors , the senAmong the phosphorylation site mutations, the S659AS1157A double mutation increased 3-HP production, which confirmed the role of these phosphorylation sites. Combining the S686A mutation with the S659AS1157A double mutation further increased 3-HP production, suggesting that the phosphorylation site mutation of Ser686 further improved the enzyme activity of Acc1p. Ser1157 phosphorylation triggers a conformational change that disables the formation of the BC dimer domain, thus eliminating the catalysis activity . HoweverWe found that the fluorescence intensity was not completely consistent with 3-HP production. Only the strains with much higher fluorescence intensity showed a beneficial effect on 3-HP production. It is probably because malonyl-CoA is an intermediate metabolite and can be consumed easily. Synthetic malonyl-CoA sensor can show the transient malonyl-CoA concentration. However, the production of 3-HP revealed the amount of malonyl-CoA flux to the downstream products. Therefore, when using a malonyl-CoA sensor to do high-throughput screening, it is essential to set up a fluorescence intensity threshold to obtain the mutations with higher products titer.In this work, we studied the impact of phosphorylation regulation on the activity of acetyl-CoA carboxylase. We discovered that a combination mutation with S686A, S659A, and S1157A could benefit 3-HP production better than the previously reported S659S1157A mutation. Moreover, the malonyl-CoA sensor designed in this work was demonstrated to be a useful tool to screen mutations with improved malonyl-CoA pools.XB and JH designed the experiments. XC and XY carried out the experiments. YS analyzed the experimental results.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.


Greenland's bed topography is a primary control on ice flow, grounding line migration, calving dynamics, and subglacial drainage. Moreover, fjord bathymetry regulates the penetration of warm Atlantic water (AW) that rapidly melts and undercuts Greenland's marine‐terminating glaciers. Here we present a new compilation of Greenland bed topography that assimilates seafloor bathymetry and ice thickness data through a mass conservation approach. A new 150 m horizontal resolution bed topography/bathymetric map of Greenland is constructed with seamless transitions at the ice/ocean interface, yielding major improvements over previous data sets, particularly in the marine‐terminating sectors of northwest and southeast Greenland. Our map reveals that the total sea level potential of the Greenland ice sheet is 7.42 ± 0.05 m, which is 7 cm greater than previous estimates. Furthermore, it explains recent calving front response of numerous outlet glaciers and reveals new pathways by which AW can access glaciers with marine‐based basins, thereby highlighting sectors of Greenland that are most vulnerable to future oceanic forcing. We present a comprehensive, seamless bed topography across the ice‐ocean margin around GreenlandTwo to 4 times more glaciers have calving fronts grounded below 200 m compared to previous mappings6 km3, yielding a potential sea level rise of 7.42 m, 7 cm greater than previous estimatesTotal ice volume of Greenland is 2.99 ± 0.02 times 10 The presence of sills in some fjords, for example, can block warm (>2.5°C) subsurface Atlantic water (AW) from interacting with glacier calving fronts, whereas other fjords are too shallow to host AW, or some glacier fronts are grounded above AW levels  the high density of surface crevasses that reflect off‐nadir radar signal (surface clutter); (2) the ice is warmer, which potentially prevents the radar signal from reaching the bed due to the presence of water pockets; and (3) the deep valleys make the interpretation of radar echograms difficult due to sidewall reflectors  at a horizontal spatial resolution of up to 150 m. In poorly charted fjords, we rely on synthetic fjord bathymetries  as well as crowd‐sourced data from fishing and recreational vessels (MaxSea). While less reliable than MBES data, these data cover an extensive area that significantly improved our mapping in many fjords, where other data were lacking. In the regions of Zachariae‐Isstrøm and Nioghalvfjerdsfjorden, we relied on bathymetry data from Arndt et al.  was within 100 m of bathymetry measurements, which was less than our error estimate  , but the true horizontal resolution of the bed topography depends on the source data used to create the maps in that region. It is about 1,000 m in regions where kriging, RTopo‐2, and gravity inversions are used, 400 m in the regions mapped with MC, and 150 m for the regions of ice‐free land or the regions for which we have MBES bathymetry data  except in coastal regions that experience strong thinning.36 km3 . The volume above floatation, which would directly contribute to sea level rise if the Greenland ice sheet were to melt entirely, is 2.93 ± 0.02 106 km3 (or 2.69 ± 0.02 106 Gt). Assuming that the density of the ice is 916.7 kg m−3, for an average density of sea water of 1,027 kg m−3, and assuming that 361.8 Gt of ice contributes to 1 mm of global eustatic sea level rise, this new map suggests that the Greenland ice sheet has a total sea level rise potential of 7.42 ± 0.05 m, which is 7 cm larger than stated by Stocker et al. , this new bed topography yields a total ice volume of 2.99 ± 0.02 10r et al. .Figure In the region of Savissuaq Gletscher, in northwest Greenland, the new bathymetry data from OMG reveal fine‐scale (<1 km) details, such as moraines that may originate from the Little Ice Age Figure a and mayIn the vicinity of Hayes Gletscher, in northwest Greenland Figures b and 4b,Illullip Sermia Figures c and 4c In the three following examples in southeast Greenland Figures d–3f, we In the region of Mogens Heinesen Figures d and 4d,Heimdal Gletscher and Skinfaxe glacier Figures e, and 4fThese narrow and deep fjords have important implications for the current and future state of the Greenland ice sheet as they can provide pathways for AW to interact with glacier termini. To investigate the regions that are in contact with the ocean, we determine locations that are continuously below sea level from the continental shelf to the ice sheet bed .4We present a new high‐resolution bed map of the Greenland ice sheet and ocean bathymetry, with a seamless transition across glacier termini. The map combines mass conservation and newly collected ocean bathymetry data from OMG and includes bathymetric data from previous marine surveys. Our new estimate for Greenland's sea level rise potential is 7 cm higher than the previously published value, and we find that between 30 and 100% more glaciers are potentially exposed to AW than suggested by RTopo‐2 or B2013. We also find that our new map is consistent with the pattern of ice front retreat along the coast, where the glaciers that have been retreating the most were resting on retrograde beds. This map is a self‐consistent data set that opens the door to high‐resolution coupled ice sheet and ocean numerical modeling, which should ultimately improve our ability to model the evolution of the Greenland ice sheet in a changing climate.Supporting Information S1Click here for additional data file.Table S1Click here for additional data file.


The synergistic properties of the combined admixture of benzenecarbonitrile and 5-bromovanillin (BNV) on the corrosion resistance of 1018 carbon steel in 1 M HCl was analysed with potentiodynamic polarization technique, weight loss method, micro-analytical studies and ATF-FTIR spectroscopy. Results obtained show the admixed organic compound was effective with optimal corrosion inhibition values of 99.33% and 90.34% at 1.25% BNV concentration from both electrochemical methods due to the effective inhibition action and passivation characteristics of the protonated inhibitor molecules in the acid solution. Primary amines, stretch alkyl halides and C-H triple bond functional groups of the molecules were observed to actively adsorb during the corrosion inhibition reaction from ATF-FTIR spectroscopic analysis. Calculations from thermodynamic evaluation confirmed cationic adsorption mechanism to be chemisorption obeying the Langmuir and Frumkin adsorption isotherm. Micro-analytical observations of the inhibited carbon steel morphology significantly contrast the unprotected steel due to visible surface deterioration and presence of micro/macro-pits. The organic derivatives showed mixed type inhibition reactions. Under a variety of conditions they are used for handling alkaline, acidic and salt solutions. Solutions containing as low as trace amounts of chlorides, sulphates and nitrate ions in aqueous media are notably aggressive and accelerate corrosion of carbon steel. Acid solutions are utilized in the removal of impurities, rust and scales in mining and extraction processes such as in oil-well acidizing, industrial acid cleaning, acid-descaling and acid pickling; however in the presence of chemical compounds known as inhibitors, corrosion of carbon steel is effectively controlled. Most well-known compounds for corrosion inhibition have been recently discovered to be carcinogenic and environmentally unfriendly6. Recently in industrial plants it has become a common practice to use chemical inhibitors based environmental sustainability and cost in addition to their inhibition efficiency7. A number of organic chemical compounds have been known to be environmentally friendly and effective corrosion inhibitors. Generally, these compounds adsorb on the metal surface and form a passive film which suppresses the redox electrochemical processes responsible for the propagation of corrosion11. These compounds contain heteroatoms  which protonates in solution, donating unshared electron pairs, unsaturated bonds , and plane conjugated systems including all kinds of aromatic cycles in their structures14. Synergistic effect of chemical compounds is one of the most important methods in corrosion inhibition process which serves as the basis for most of the modern corrosion inhibiting admixtures16. In furtherance of the drive for cost effective and environmentally benign corrosion inhibitors, this research focuses on the evaluation of the corrosion inhibition effect of the synergistic combination of benzenecarbonitrile and 5-bromovanillin on 1018 carbon steel, a highly applicable metallic alloy in dilute HCl solution.Carbon steel corrosion in aggressive industrial environments is of immense economic importance due to the extensive application of the alloy. They are employed as a construction material, storage containers, reservoirs and equipment parts in chemical processing plants, mining industry, power generation and petrochemical industries. In oil and gas they are applied for pipe work in down hole tubular, flow lines and transmission pipelines17. Benzenecarbonitrile and 5-bromovanillin purchased from BOC Sciences, USA were the organic compounds evaluated. Benzenecarbonitrile is an aromatic, translucent organic compound with a sweet almond odour. It used mainly as an antecedent to the resin benzoguanamine. They have a chemical formula of C7H5N and molar mass of 103.12 g/mol. 5-bromovanillin is a carbolic aldehyde organic compound with the chemical formula of C8H8O3 and molar mass of 152.15 g/mol. It is one of the constituents of vanilla bean extract and is used as a flavouring agent in foods, beverages, and pharmaceuticals. The molecular structures benzenecarbonitrile and 5-bromovanillin are shown in Fig. −3, 1.96 × 10–2, 2.94 × 10−2, 3.92 × 10−2, 4.90 × 10−2, 5.88 × 10−2, in 200 mL of 1 M HCl solution, prepared from standard grade of HCl acid (37%) with deionized water.1018 carbon steel (1018CS) obtained from the tie rod linkage of an automobile has a basic composition (wt. %) depicted in Table 2. Polarization curves were plotted at scan rates of 0.0015 V/s at potentials of −1.25 V to +0.5 V19. Corrosion current density Jcr, (A/cm2) and corrosion potential, Ecr (V) values were determined by Tafel extrapolation. Corrosion current, Icr (A) was calculated from the intercept of the cathodic and anodic polarization plots21. Corrosion rate, CR (mm/y) was determined from the formula below;Eqv is the equivalent weight (g) of metal, 0.00327 is a constant22, and D is the density (g/cm3) Inhibition efficiency values, η (%) were calculated from corrosion rate results  within a glass cell containing 200 mL of HCl/BNV inhibitor formulation were connected to Digi-Ivy 2311 potentiostat to monitor the test. The working electrodes were encased in resin mounts with limited surface area of 0.79 cmRp, (Ω) was determined from equation Ba is the anodic Tafel slope (V/dec) and Bc is the cathodic Tafel slope (V/dec).Polarization resistance, −1 wavelength and 0.9 cm−1 resolution. The resulting ATF-FTIR absorption plot consisting of spectra peaks were assessed and correlated with the theoretical ATF-FTIR absorption Table to determine the functional groups responsible for corrosion inhibition of 1018CS. Optical micrographs of BNV inhibited and non-inhibited 1018CS morphology were analysed after corrosion test with Omax trinocular using ToupCam software for analysis.HCl solutions with BNV compound at predetermined concentration, before and after the electrochemical tests were exposed to infrared ray beams with Bruker Alpha FTIR spectrometer at 375 to 7500 cm23. Corrosion rate, CR (mm/y) was calculated as follows24;ω is the weight loss (g), D is the density (g/cm3), A is the total exposed surface area of 1018CS sample (cm2) and 87.6 is a constant. t is the time (h). Inhibition efficiency values (η) were calculated from the formula below;1018CS steel samples individual hanged within 200 mL of 1 M HCl solution for 240 h were weighed at 24 h intervalω1 and ω2 are the weight loss at specific BNV concentrations. Surface coverage values were calculated from equation 26:θ is the extent of BNV coverage on 1018CS. ω1 and ω2 are the weight loss of each 1018CS at predetermined BNV concentration in 1 M HCl solution.−5 Acm−2 due to anodic inhibition, however observation of the cathodic and anodic Tafel slope values shows mixed inhibition reaction on the steel surface. The anodic Tafel slope is greater than the respective cathodic Tafel slopes due to the anodic exchange-current density value being lower than the cathodic value. Increase in concentration of BNV (0.5–1.5% BNV) caused a significant increase in passivation of the polarization plot  which is attached to one carbon atom with the general formula RC≡N. They are polar with high dipole moments which creates strong electrostatic attraction with the 1018CS surface. 5-bromovanillin component of BNV is a phenolic aldehyde with the aldehyde, hydroxyl, and ether functional group. Considering the structure of BNV different points where it can interact with 1018CS can be established. The free electron pairs on N and O, and the π-electrons from the aromatic rings are capable of forming covalent bonds with Fe substrate metal of 1018CS. The N atom of the amino group attached to the aromatic ring enhances the BNV molecule to strongly adsorb onto the steel41 for identification. The IR spectra of 1 M HCl/BNV solutions before and after the corrosion test are shown in Fig. −1 and 3573.48 cm−1 consisting of alkenes, aromatics, alkynes , carboxylic acids, primary and secondary amines, amides, alcohols and phenols functional groups C–H: C–H stretch, O–H stretch, N–H stretch, O–H stretch and H–bonded bonds) within BNV compound due to limited or negligible adsorption. At wavelengths between 1592.27 cm−1 and 3067.46 cm−1, slight decrease in transmittance intensities of the spectra peak was observed due to adsorption of aromatics, primary amines, alkenes, alpha, beta–unsaturated aldehydes and ketones, saturated aliphatic, alpha, beta–unsaturated esters, aldehydes, esters, carboxylic acids, carbonyls , nitriles, alkynes, alkanes, alkenes, aromatics, alkynes , primary, secondary amines, amides, alcohols and phenols functional groups present. These consists of C=O stretch, –C=C– stretch, N–H bend, C–H stretch, H–C=O: C–H stretch, C(triple bond)N stretch, C(triple bond)C stretch and C–C stretch (in–ring) bonds.Designation of the functional groups of atoms or bonds within molecules involved in BNV (combined admixture) inhibition on 1018CS after hydrolysis in HCl, was done through IR spectroscopy and correlated with the theoretical IR Table−1 and 1592.27 cm−1. The functional groups at these wavelengths consists of most of the earlier mentioned functional groups, in addition to nitro compounds, aromatic amines, ethers, alkyl halides, aliphatic amines, alkenes, carboxylic acids, primary, secondary amines. Previous research has shown that compounds with amines, carboxylic acids and alcohols functional groups are effective corrosion inhibitors43. The C–Cl  resulting from replacement one of the H atom of alkyne molecule with Cl atom is due to the electrostatic attraction between the protonated BNV molecules and Cl− anions on the steel surface. BNV replaces the Cl− ions due to competitive adsorption onto the steel surface.Significant variation in transmittance signifying strong molecular interaction and adsorption was observed between wavelengths of 526.23 cmῶ) and corrosion rate (CR), and BNV percentage inhibition efficiency (ɲ) in HCl acid solution at 504 h are depicted in Table − ions in the acid solution. Dilute HCl acid completely ionizes in H2O releasing one proton (equation − and H3O+ (hydronium ion). The Cl− ion strongly reacts with the steel surface  proportional to BNV inhibition efficiency of 76.18–90.34%. The presence of BNV stifled the redox reactions responsible for surface deterioration. This inhibits the release of oxidized Fe2+ resulting from the electrochemical action of Cl− ions, into the acid solution. In the acid media, BNV protonates strongly with respect to concentration allowing more of its molecules to donate unshared electrons, hence increasing the functionality of the inhibitor and enabling strong adsorption onto the steel surface. Increase in BNV concentration to 1.5% at 90.06% BNV inhibition efficiency had no further influence on the corrosion rate values signifying that the optimum BNV concentration for effective corrosion inhibition is 1.25% BNV in 1 M HCl.Addition of 0.25% BNV concentration drastically reduced the corrosion of 1018CS to 7.444 mm/y (43.91% BNV inhibition efficiency) at 504 h; however the rate of corrosion is still relatively high due to the presence of insufficient BNV molecules to counteract the action of Cl47. The adsorption mechanism of BNV inhibitor was determined and studied to achieve a further in-depth understanding of the molecular interaction between the compound and 1018CS. BNV adsorption strongly aligns with the Langmuir and Frumkin isotherm models as shown in Figs θ is the extent of BNV molecular coverage on 1018CS, CBNV is BNV concentration in HCl solution, and Kads is the equilibrium constant of the adsorption mechanism. The graphical illustration of CBNV showed linearity in agreement with Langmuir adsorption isotherm  dislodge by BNV. Data of Gibbs free energy (49.R is the universal gas constant, T is the absolute temperature and Kads is the equilibrium constant of adsorption. Kads is related to surface coverage (The thermodynamics of the inhibition mechanism discusses the adsorption strength of BNV compound on 1018CS. The adsorption strength is proportional to the extent of H50. Organic molecular adsorption being a substitutional reaction involving the removal of H2O molecules from metal surface through hydrophobic part of functional groups is proportional to the degree of metal cations diffused into the acid solution. The amount of cations released to the acid solution is proportional to the degree of BNV coverage due to changes in interaction energy with water molecules as BNV cations adsorb on the steel51. The negative values of −1 at 1.25% BNV while the lowest value is −37.93 KJmol−1 at 0.25% BNV. This observation is consistent with chemisorption adsorption mechanism53. After 1.25% BNV the Flaws, discontinuities and impurities on stainless steels significantly influence − ions in the acid solution severely degraded the total surface and morphology of 1018CS during the exposure hours. General corrosion best explains the topographic damage on the steel as corrosion has significantly eaten inwards on the steel. The steel contrast the images of the steel sample before corrosion test [Figs The macro-images of 1018CS samples before corrosion, and after corrosion in and without the presence of BNV compound are shown from Fig. est Figs  as it beBNV effectively improved the corrosion resistance of 1018 carbon steel in dilute HCl acid solution. The admixed organic compound adsorbed strongly onto the carbon steel, passivating it through electrostatic attraction and covalent bonding, resulting from chemisorption mechanism onto the steel surface. The inhibition efficiency values remained sufficiently high from the onset of the exposure hours till the end due to the inhibition reaction of the molecular functional groups and heteroatoms of the compounds which strongly altered the mechanism of the electrochemical process and protecting the steel from corrosion. The inhibition property of the compound was determined to be anodic type inhibitor.


All organisms have evolved pathways to respond to different forms of cellular stress. The Gcn2 kinase is best known as a regulator of translation initiation in response to starvation for amino acids. Work in budding yeast has showed that the molecular mechanism of GCN2 activation involves the binding of uncharged tRNAs, which results in a conformational change and GCN2 activation. This pathway requires GCN1, which ensures delivery of the uncharged tRNA onto GCN2. However, Gcn2 is activated by a number of other stresses which do not obviously involve accumulation of uncharged tRNAs, raising the question how Gcn2 is activated under these conditions. Here we investigate the requirement for ongoing translation and tRNA binding for Gcn2 activation after different stresses in fission yeast. We find that mutating the tRNA-binding site on Gcn2 or deleting Gcn1 abolishes Gcn2 activation under all the investigated conditions. These results suggest that tRNA binding to Gcn2 is required for Gcn2 activation not only in response to starvation but also after UV irradiation and oxidative stress. S. pombe) of the eukaryotic translation initiation factor 2α (eIF2α) [All cells and organisms are surrounded by a changing and often stressful environment and have developed various signaling pathways to adapt to these changes. An important requirement for maintaining cell homeostasis during stress conditions is the correct regulation of translation. Translational regulation in response to different types of stress involves phosphorylation of serine51 (Ser 52 in  (eIF2α) . One of  (eIF2α) –9.The mechanism of GCN2 activation in response to amino-acid starvation has been extensively studied through the years, mainly in budding yeast. Under starvation conditions, uncharged tRNAs accumulate and bind a histidyl-tRNA synthetase-like domain (HisRS) in Gcn2. This, in turn, leads to a conformational change and activates the kinase. This model is supported by the findings that (i) mutations leading to amino-acid substitutions close to the predicted active site of the HisRS domain affect Gcn2 activation, either by leading to constitutive activation or abolishing kinase activation –12; (ii)In budding yeast, the association of GCN2 with the ribosome depends on its interaction with GCN1, a cofactor required for Gcn2 activation upon amino-acid starvation. GCN1 binds the ribosome at or near the A site and is thus perfectly placed to ensure the transfer of the uncharged tRNA onto GCN2 –19.2O2, proteasome inhibition, viral infections and serum starvation [2O2 is very fast. Therefore we reasoned that Gcn2 might be activated by other mechanisms.In addition to amino-acid starvation various other types of stress can activate Gcn2, including ultraviolet light (UVC), MMS, Harvation ,21. HoweHere we investigated the mechanism of Gcn2 activation in response to different types of stress. We found that Gcn1 is required for Gcn2 activation after amino-acid starvation also in fission yeast. We show that ongoing translation is not required for UVC-induced activation of Gcn2. However, mutating the tRNA-binding site on Gcn2 or deleting Gcn1 abolishes Gcn2 activation not only in response to starvation but also after UVC irradiation and oxidative stress. These results strongly suggest that tRNA binding is required for Gcn2 activation in response to all these types of stress.Schizosaccharomyces pombe L972h- strain, and are listed in 6 cells/ml .All strains used are derived from the Leucine-auxotroph cells were grown in the presence of leucine in EMM medium and washed by filtering with three volumes of EMM lacking leucine. The cells were then resuspended in EMM lacking leucine and samples were collected at different timepoints after leucine removal.6/ml were treated with H2O2 at the indicated concentrations, and samples were collected at different timepoints after addition of the oxidative agent.Cells grown in EMM to a density of 4X 102 was given at an incident dose rate of approximately 250 J/m2/min [Cells were grown in EMM medium to early log phase (OD = 0.15 Fission yeast cells suspended in a thin layer (3 mm) of rapidly stirred liquid EMM medium were irradiated with 254-nm UVC light. The dose was measured with a radiometer , and a dose of 1100 J/mJ/m2/min . This doIn situ chromatin binding assay was performed as described previously ,24.Samples for immunoblotting were made by the trichloroacetic acid (TCA) protein extraction method . A totalCells were pulse-labelled with the methionine analogue L-Homopropargylglycine  at a concentration of 50 μM for 10 minutes. Samples were taken at the indicated timepoints after treatment and fixed in ice-cold 70% ethanol. Newly synthesized proteins were detected by chemoselective fluorescence tagging by means of “click chemistry”  using thgcn2Δ cells. After 30 min incubation EDTA was added to 20 mM, Laemmli sample buffer to 1X and the reaction mix was boiled for 5 min before loading on a gel and immunoblotting for eIF2α-P.Gcn2 was immunoprecipitated from exponentially growing unirradiated (“C”) and UV-irradiated “UV” cells, using IP buffer . The immunoprecipiates were resuspended in kinase buffer Tris-HCl pH 7,5; 5 mMMgCl2; 75 mM NaCl DTT 1mM; 0,5% Triton; Protease inhibitor from Roche; 0,1 mM PMSF; 100 μM Na3VO4; 100 μM ATP and mixed with extracts made from an unirradiated culture of Under starvation conditions uncharged tRNAs accumulate as the existing pool of charged tRNAs is gradually exhausted during protein synthesis. If Gcn2 activation occurs through a similar mechanism of tRNA accumulation also after UV irradiation, one would expect that ongoing translation is also required for activation. To address this, we inhibited translation prior to UVC-irradiation and measured eIF2α phosphorylation to assess Gcn2 activation. To inhibit translation we treated the cells with 100 μg/ml cycloheximide for 10 minutes, under which conditions no further translation could be detected as measured by incorporation of HPG, a methionine analogue . To verigcn2Δ cells  and a sample was taken to extract proteins and measure eIF2α phosphorylation by immunoblotting . “log” refers to a sample of exponentially growing cells. On the graphs showing translation rates median fluorescence intensity from 10 000 fission yeast cells and standard deviations are shown. α-tubulin levels are shown to check even loading. E GCN2 was immunoprecipitated from from UV-irradiated “UV” and unirradiated control “C” cells, and incubated with extracts prepared from unirradiated gcn2Δ cells in kinase buffer. eIF2α phosphorylation was measured by immunoblotting. α-tubulin levels are shown to demonstrate that equal amounts of extracts from unirradiated gcn2Δ cells were used as substrate in the kinase assays.Cycloheximide was added to 100 μg/ml to inhibit translation for 10 minutes. Half the culture was irradiated with 1100 J/mescribed  and sampgcn2Δ, and gcn2-FARL cells were starved for leucine and samples were collected at different timepoints. Phosphorylation of eIF2α was measured by immunoblotting. As expected, eIF2α was not phosphorylated after leucine starvation  . This doarvation , “-L”. earvation . To testarvation , UV, sugGCN1 homologue and investigated whether Gcn2 can be activated in gcn1Δ cells. Leucine was withdrawn from the medium of leucine-auxotroph wild-type, gcn2Δ, and gcn1Δ cells and samples were collected at different timepoints. Phosphorylation of eIF2α was measured by immunoblotting. In wild-type cells, phosphorylation of eIF2α occurred at 30 min after the withdrawal of leucine and persisted for at least one hour  in a Gcn2-dependent manner  and thusng assay ,24. The 1Δ cells , as prev2Δ cells , suggestThe above data suggest that tRNA binding is necessary for GCN2 activation also after UVC irradiation. One plausible mechanism for the accumulation of uncharged tRNA-s is depletion of one (or a few) specific amino-acyl- tRNA due to, for example, a chemical modification or conversion. To test whether such a mechanism might be responsible for the activation of Gcn2, we supplemented the medium with all amino acids as well as adenine and uracil prior to UV irradiation. A prototroph strain was grown in EMM medium and supplements were added 30 min before irradiation. We used concentrations of supplements that were sufficient to allow growth of auxotrophic mutants. The cells were irradiated with UVC and samples were taken for immunoblotting immediately after irradiation. Providing supplements in excess in the medium did not prevent or reduce eIF2α phosphorylation . These r2O2-induced activation of Gcn2, wild-type, gcn2Δ and gcn1Δ cells were grown in minimal medium, H2O2 was added to the concentrations shown and samples were collected 15 minutes after the addition of H2O2. In agreement with previous reports, phosphorylation of eIF2α was observed in response to H2O2 in wild-type cells. It should be noted that prolonged oxidative stress or high concentration of H2O2 activates another eIF2α kinase, Hri2, but the initial eIF2α phosphorylation is due to Gcn2 [2O2 and cell density were carefully controlled. Interestingly, eIF2α phosphorylation was abolished in the absence of Gcn1. Gcn2 protein levels were not reduced in the gcn1Δ mutant , thus these results suggest that Gcn1 is required for Gcn2 activation also in response to oxidative stress  involving tRNA binding assisted by Gcn1 in response to stresses other than starvation. However, identification of the mechanisms that alter the balance between charged and uncharged tRNAs and the possible involvement of other upstream regulators requires further studies.S1 Figgcn2Δ cells were treated with 100 μg/ml cycloheximide for 10 min as indicated and UV irradiated.Wild-type and (TIF)Click here for additional data file.S2 FigThe same samples as shown in (A) (TIF)Click here for additional data file.


Pusa hispida) reproduction, body condition, recruitment, and stress in Hudson Bay from 2003 to 2013. Aerial surveys suggested a gradual decline in seal density from 1995 to 2013, with the lowest density occurring in 2013. Body condition decreased and stress (cortisol) increased over time in relation to longer open water periods. The 2010 open water period in Hudson Bay coincided with extremes in large-scale atmospheric patterns  resulting in the earliest spring breakup and the latest ice formation on record. The warming event was coincident with high stress level, low ovulation rate, low pregnancy rate, few pups in the Inuit harvest, and observations of sick seals. Results provide evidence of changes in the condition of Arctic marine mammals in relation to climate mediated sea ice dynamics. We conclude that although negative demographic responses of Hudson Bay seals are occurring gradually with diminishing sea ice, a recent episodic environmental event played a significant role in a punctuated population decline.To assess whether demographic declines of Arctic species at the southern limit of their range will be gradual or punctuated, we compared large-scale environmental patterns including sea ice dynamics to ringed seal ( Organisms evolve specific adaptations to their habitats through natural selection  and whenUrsus maritimus) (Pusa hispida) have a circumpolar distribution and show high variability in the relative importance of predation from polar bears  , where tritimus) . Ringed ar bears  and to var bears . Howeverar bears  and a sear bears . Evolvedar bears .High latitude species are characterized by a strong seasonal cycle of feast and fast with both periods critical to reproduction and survival . Ringed 2)  .Here, we compare indices in the productivity and health of the Hudson Bay ringed seal population with environmental covariates over time. Our data sets were annual trends in sea ice breakup and formation, major climatic indices, and biological data from seal collections, 2003–2013: (1) body condition (% fat) from seals harvested by Inuit; (2) reproduction from examination of reproductive tracts; (3) recruitment from hunter harvest statistics; and (4) stress from blubber cortisol levels. We hypothesize that gradual deteriorating change in sea ice characteristics will correlate with a gradual decrease in ringed seal body condition, ovulation rate and pup recruitment , whereashttp://iceweb1.cis.ec.gc.ca/IceGraph/), for eastern Hudson Bay, 1979–2014. The majority of biological data for ringed seals was derived from the Sanikiluaq (southeast Hudson Bay) seal collection whereas Arviat (southwest Hudson Bay) only provided the time-series of cortisol measures. Therefore, we only present annual changes in sea ice coverage (http://www.cpc.ncep.noaa.gov/), including the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), and El Nino-Southern Oscillation (ENSO) for the December to February monthly mean estimates from 1971 to 2014. We included ENSO due to its significant climatic influence in North America and due to its effect on ecological relationships in several ecosystems across the globe (Sea ice breakup and freeze-up dates were determined from weekly data obtained from the Canadian Ice Service using Icegraph 2.0 (coverage  for thiscoverage  and how coverage . Convershe globe . NAO andhe globe . The lonn = 917), NU, Canada  and Arviat (n = 508), NU  from 2003 to 2013. Permits to collect samples as part of the Inuit subsistence hunts were acquired from Fisheries and Oceans Canada. All biological data with the exception of cortisol was derived from seals collected by Sanikiluaq hunters in the eastern region of Hudson Bay. Samples were collected in autumn (October to December) in Arviat. In Sanikiluaq, some samples were collected throughout the year but we used only autumn collections for age/sex composition as the late open-water season provides a representative sample of the population  and biological variables  over time using R v 3.2.3 . ContinuResults support a gradual pattern of earlier spring ice breakup and later autumn freeze-up in Hudson Bay; where from 2003 to 2013, sea ice breakup has varied more widely than freeze-up. No relationship occurred with any climate variability index over 1979–2014, but the NAO and AO have been more positive from 1999 to 2015 . The lont = −8.2, p < 0.001), from 55.4% blubber mass in 2004 to 40.3% in 2012 before increasing to 48.1% in 2013 , ENSO index , and NAO index  from about 40% of the harvest to about 20%  from about 0.1 to 0.6 ng/g over the 2003–2012 period  and sand lance (Ammodytes spp.) and decrease in Arctic cod (Boreogadus saida) abundance in Hudson Bay since 2000 has caused dietary shifts from endemic Arctic cod to sub-Arctic capelin and sand lance in Arctic marine megafauna including sea birds , Ovulated (Yes).Click here for additional data file.10.7717/peerj.2957/supp-2Supplemental Information 2Year, sample size, mean radio-immune assay cortisol (ng/g), standard deviation, standard error.Click here for additional data file.10.7717/peerj.2957/supp-3Supplemental Information 3Year, percent blubber.Click here for additional data file.10.7717/peerj.2957/supp-4Supplemental Information 4North Atlantic Oscillation (NAO), Atlantic Oscillation (AO), El Nino Southern Oscillation (ENSO), breakup and freeze-up dates.Click here for additional data file.10.7717/peerj.2957/supp-5Supplemental Information 5Date, Comment, Reporter.Click here for additional data file.


Vmax) but short-term drying and waterlogging caused a significant increase of dissolved organic carbon (DOC) and phenolics associated with increases in Vmax (enzyme production) and Km (indicative of competitive inhibition). Inhibition within the drain blocked and pristine sites at depth exhibited non-competitive inhibition (decreased Vmax), whilst uncompetitive inhibition (decreased Vmax and Km) occurred in surface peat explained by variation in humic substances and phenolics. These results suggest that loss of carbon by short-term drought or rewetting may occur from sites with a legacy of drought due to the release of non-inhibitory phenolics that permits enhanced enzyme activity.Peatland ecosystems contain one-third of the world’s soil carbon store and many have been exposed to drought leading to a loss of carbon. Understanding biogeochemical mechanisms affecting decomposition in peatlands is essential for improving resilience of ecosystem function to predicted climate change. We investigated biogeochemical changes along a chronosequence of hydrological restoration , and examined whether hydrological legacy alters the response of β-glucosidase kinetics (i.e. type of inhibition) to short-term drying and waterlogging. In the dry eroded gully at depth, low phenolic concentrations were associated with enhanced β-glucosidase enzyme activities ( Historically, peatlands have been drained for forestry, agriculture and peat harvesting, which has led to degradation and potential loss of a variety of ecosystem services including carbon sequestration and potable water quality2. There are also concerns that at high latitudes, drought frequency and severity is predicted to increase3, and there is evidence that this is already increasing losses of carbon dioxide (CO2) and dissolved organic carbon (DOC)4. Indeed, drought and drainage combined with warming have resulted in degradation of more than 11% of global peatlands switching these carbon sinks to carbon sources5.Peatland ecosystems contain one-third of the world’s soil carbon store and are therefore a significant component of the global carbon cycle7. Key processes in restoration include identifying and understanding the biogeochemical mechanisms that enhance and inhibit the decomposition of organic matter (OM) in ombrotrophic peatlands so that management strategies can be developed to promote the resilience of peatland ecosystem functions to predicted climate change9. Recent contrasting results on the effect of drought and even rewetting on decomposition in peat particularly dissolved organic carbon (DOC) release, raise uncertainty on the conventional theory that anoxia is the key to carbon storage in peat13.Peatland restoration aims to return these ecosystems to a defined pristine or pre-determined less degraded state. Peat quality depends on physical, chemical, and biological properties, especially the activities of hydrolytic enzymes that are frequently measured to evaluate microbial and ecosystem function15, vegetation10, acidity16 and particularly hydrology19 affect decomposition as well as the degree of peat formation (humification) via effects on microbial and enzymic degradation of OM20. The variation of the water table depth is considered as the principle driving factor influencing peatland ecosystems, compared to other environmental conditions22. Decomposition of OM and ultimate CO2 release depend on the combined response of extracellular and intracellular , enzymatically mediated reactions14. Extracellular enzymes such as β-glucosidase catalyze the initial enzymatic hydrolysis of a variety of complex polysaccharides in peat to simple monomers (i.e. glucose) that can be transported actively and passively into microbial cells and catabolized by intracellular enzymes producing CO2. Extracellular enzyme catalytic activities therefore limit the rate of decomposition23 and are markedly affected by site-specific factors such as moisture, nutrient availability, inhibitors and other site parameters25. Freeman et al. and Fenner & Freeman describe in detail the enzyme latch mechanism responsible for decomposition of peat, in which oxygen (O2) constraints on the enzyme phenol oxidase prevent the decomposition of peatland carbon due to phenolic compounds inhibiting hydrolase enzymes18. This enzymic latch sits within a regulatory pathway of process-specific limitations, which are sequentially removed as drought proceeds, constituting a biogeochemical cascade with potent positive feedbacks to carbon loss18. Following drought, the cascade consists of (1) ingress of O2 enabling increased microbial growth rates that results in (2) increased synthesis of phenol oxidase. This increase in activity causes (3) a decline in inhibitory phenolics that (4) stimulates microbial growth and metabolism and edaphic hydrolases. Increased activity (5) stimulates release of carbon and nutrients following re-wetting of peat, further enhancing (6) microbial activity and abundance, that (7) positively feeds-back on the synthesis of hydrolases, phenol oxidases, CO2 emissions and also (8) edaphic enzyme activities18. Therefore severe drought and counterintuitively rewetting can destabilize peatland carbon stocks raising concerns for peatland restoration management under predicted climate change.Long-term environmental conditions such as temperature26. In Michaelis–Menten kinetics, Vmax defines the maximum rate of enzyme activity under saturating substrate concentrations, and Km (the Michaelis constant) defines the substrate concentration at which 50% Vmax is achieved and represents the substrate affinity of the enzyme under non-saturating substrate concentrations27. Soil moisture content will affect the movement of enzymes and their substrate concentrations and the diffusional limitation of the substrates may directly affect soil enzyme kinetics28. Changes to enzyme kinetics may reflect differences in the types of inhibition by OM and/or DOC such as competitive inhibition (where substrate and inhibitor molecules compete for the active site resulting in an increase in Km), uncompetitive inhibition (where an inhibitor binds to the ES complex resulting in both decreased Vmax and Km) or non-competitive inhibition . Humic substances are the dominant fraction in DOC11 and humic acids and phenolic compounds are known to play an important role in the stabilisation or inhibition of extracellular enzymes in soils31 through complexation or covalent binding reactions that impede substrate access to the enzyme active site34. Hydrology affects humification and the self-assembly of humic substances over time  as redox reactions occurring under drought (oxidation) and re-wetting (reduction) events affect the formation and accumulation of humic matter (see Tan for models of humic matter genesis)35. Change in Vmax and Km may also reflect shifts in the microbial community structure37 such as the bacterial-to-fungal ratio that may alter carbon allocation to the extracellular enzyme pool affecting the kinetic characteristics such as more rapid conformational changes14.Extracellular enzymes are usually adsorbed on the surface of organic material in soil, and the heterogeneous nature of soil affects the kinetic diversity of immobilized enzymes39. The phylogenetic and functional response of microbial communities under drought are an emergent property of the ecosystem determined by life history strategies and traits41. Hydrological impacts that modify microbial community structure can also alter intracellular allocation pathways within organisms and populations40. Constraints on substrate diffusion can promote the allocation of carbon to extracellular enzyme production, stimulating the decomposition of polymeric compounds to monomers for intracellular cellular metabolism42. Therefore, historical environmental conditions select for microbial communities that alter the production of extracellular enzymes and the decomposition of carbon19. “Legacy effects” represent the persistent influence of previous ecosystem conditions that reflect the history of a site44. We hypothesize that hydrological legacy of a site  will alter the response of microbial decomposition and Michealis-Menten enzyme kinetics (Vmax and Km) to contemporary (short-term) variation in hydrology potentially affecting the release of DOC. The impact of rewetting by ditch-blocking on DOC export in peat bogs appears dependent on the length of time following rewetting but the mechanisms responsible are not fully understood13. Recent studies show the prominent role of indirect and direct temperature effects on microbial community composition in governing decomposition rates via enzyme expression and intracellular metabolism of the products formed19. As hydrology is arguably of more significance in peatland systems, the formation of distinct humic or phenolic compounds due to differences in hydrological legacy may play an important role in how peatland decomposition processes respond to climate change and restoration management.Understanding the effects of climate on decomposition is complicated by the relationship between direct effects, which dictate the rate responses of enzyme-catalyzed microbial processes, and indirect effects, which alter the structure and composition of microbial communitiesThe aim of this study was to investigate relationships between physical (hydrology), chemical (organic matter) and biological (enzymic) properties of peat across a chronosequence of peatland sites within the Geltsdale National Nature Reserve, UK that differed in long-term legacy of hydrological condition and/or restoration management. The four sites Fig.  were eitP < 0.022) and WP (P < 0.019) sites. Water content was also significantly higher at depth than the surface in the EG site (P < 0.007). Correspondingly, surface SOM content was significantly lower in EG (P < 0.005) and DB2 (P < 0.006) sites compared to the WP site. SOM was also significantly lower at the surface in the EG (P < 0.001), DB2 (P < 0.001) and DB7 (P < 0.009) sites compared to deep peat. In surface peat, the E4/E6 ratio was significantly lower within the DB7 (P < 0.001) site compared to the other sites that may be explained by significantly higher pH (P < 0.012). However, the E4/E6 ratio was significantly lower at depth compared to the surface in the EG (P < 0.001), DB2 (P < 0.002) and WP (P < 0.001) sites. Additionally, humification degree (Abs 540 nm) was significantly higher at depth compared to the surface in the EG (P < 0.017), DB7 (P < 0.022) and WP (P < 0.003) sites.Table P < 0.001) and phenolics  were significantly higher in the WP site relative to all other sites. Within the WP site, DOC was also higher at depth compared to the surface (P < 0.045). The phenolic/DOC ratio (Supplementary Table P < 0.002) whilst SUVA254 (Table P < 0.001) was significantly higher in the WP site in both surface and deep peat. Interestingly, baseline DOC, phenolics and SUVA254 were significantly lower at depth in the EG site (Site*Depth interaction P < 0.01), but significantly higher at depth in the WP site (Site*Depth interaction P < 0.05).There were no significant differences in baseline DOC or biological measurements in surface peat. However, at depth, baseline DOC  whilst net CH4 production was significantly higher at depth overall compared to surface peat (P < 0.05). However, baseline β-glucosidase Vmax (P < 0.014) and Km (P < 0.001) were also significantly higher in the EG site relative to all other sites  whilst Km was significantly higher at depth compared to the surface in the EG (P < 0.001), DB7 (P < 0.004) and WP (P < 0.020) sites.Baseline heterotrophic respiration was significantly higher in the eroded gully (EG) site relative to the drain blocked <2 years (DB2) site  and depth (P < 0.05) whilst waterlogging was not significantly different to baseline water content (Table 4/E6 ratio was increased by drying and waterlogging in the DB7 site in the surface (P < 0.001) and at depth (P < 0.006) due to the low baseline E4/E6 ratio attributed to the high pH.Air drying in the laboratory significantly reduced the water content relative to baseline and waterlogged conditions in all sites at surface (nt Table . The E4/P < 0.001) and in the WP site between baseline and air dried (P < 0.005). In surface peat from the EG site, air drying and waterlogging significantly increased SUVA254 (P < 0.001), phenolics . Air drying (P < 0.053) and waterlogging (P < 0.001) also increased Km significantly .In surface peat, although air dried heterotrophic respiration appears lower compared to baseline levels  and net CH4 (P < 0.05) production were consistently and significantly reduced by air drying relative to baseline conditions in all sites  corresponding with a significant decrease in pH (P < 0.001), and an increase in glucosidase Vmax . There were no significant differences in phenol oxidase although results show potential for increase in short-drying and waterlogging within the EG site  differed between each site, peat extracts were incubated with 1U of pure β-glucosidase enzyme relative to a deionised water control . Surface peat inhibited pure β-glucosidase activity (Vmax) to between 4 and 10% of the control across all sites  that were together all significantly lower than inhibition in the EG site (P < 0.007). There was no significant effect of hydrological treatment within sites although there was a significant interaction between site and hydrological treatment (P < 0.001). Km was increased by deep peat from all sites although EG deep peat increased Km significantly between 4 to 12 times (1326%) the other sites in the dry treatment  due to significantly higher Km in the air dried compared to the waterlogged peat from the EG site (P < 0.028). Non-linear regression modelling  as were potential and in vitro Km  across all sites.To evaluate whether the degree and type of β-glucosidase inhibition  with physical, chemical and biological parameters using all, surface or deep datasets. As can be seen in Table in vitro Km variation in surface peat could not be modelled significantly using the measured parameters, and in addition, all modelled kinetics in surface peat had low adjusted R2 values suggesting limited explained variation (approximately 22–36%). Models using only deep peat replicates explained more variation than models using data from both depths. In particular, the H+ ion and phenolic concentration had a positive effect on potential Vmax and Km at depth together explaining greater than 69% of the variation. In vitro Vmax and Km at depth were also related to the H+ ion concentration but this only explained between 33 and 46% of the variation respectively. Comparing the effect of other factors between each dataset suggests that the OM fractions may mediate effects on β-glucosidase kinetics via the type of inhibition.Multiple stepwise regression analyses were used to determine the relationship between either potential or 4/E6 ratio (0.699) and third by dissolved phenolic concentration (0.307) according to the standardized canonical discriminant function coefficients in brackets  with function 1 explaining most of the variance. However, Box’s M test was significant (P < 0.001) suggesting that the assumption of homogeneity of covariance matrices was not met. Comparison of log determinants showed that the competitive inhibition group (−35.4) differed to the uncompetitive (−21.47) and non-competitive (−22.4) groups suggesting uncertainty in the attribution of factors explaining the competitive group. Figure 4/E6 ratio. It can be seen that DOC and the other organic fractions appear perpendicular to the enzyme inhibition functional groups that relates to the effect of laboratory hydrological manipulation, particularly in the competitive inhibition group that exhibit significant increase in phenolic compounds.Discriminant Function Analysis revealed that the three types of enzyme inhibition  were best explained first by SOM (−0.731), second by the Eets Fig.  with 92.18. Other studies have shown increasing activities of enzymes with restoration suggesting enhanced oxidative microbial capacity6. However, the decreasing trend in extracellular β-glucosidase at depth shown here suggests that restoration has relatively rapid effects (i.e. the DB < 2 years) on carbon decomposition. As β-glucosidase activity was low in the DB sites despite low concentrations of phenolics, we did not observe a transient gradient of change in the enzyme latch mechanism across the chronosequence and therefore step changes may have occurred following rewetting related to change in the form or molecular weight of phenolics produced (i.e. inhibitory vs non-inhibitory)45. Indeed, these results and those discussed below regarding short-term hydrological responses, suggest that restored sites show distinct characteristics to degraded and pristine systems possibly reflecting legacy effects on the microbial community structure and function that requires further investigation.Our study shows that hydrological legacy alters how the functional microbial community responds to contemporary hydrological change. Physical, chemical and biological parameters varied across the chronosequence consistent with recovery from drought. The baseline results showed that decomposition of OM within surface peat had been enhanced over the long-term in the ‘drier’ EG site compared to the ‘wetter’ WP sites with the DB sites intermediate. However, in deep peat, elevated DOC, phenolics and other aromatic fractions resembled the enzymic latch mechanism with phenolic inhibition of β-glucosidase in the WP site relative to the EG site46. Indeed, Moore et al. found that fluvial DOC loss in tropical peatlands disturbed by drainage, deforestation and fire was primarily old (centuries to millennia) carbon from deep within the peat profile47. Under anoxic conditions, fermentative metabolisms are dominant, promoting the production of DOC48, as seen in the WP site and at depth, even though decomposition might be slowed13. Schiff et al. suggested that, above the maximum depth of the water table, the water flow is rapid enough to flush out DOC produced in surface layers but at depth, as the groundwater flow is much slower, DOC can still accumulate49. As DOC was lower at depth in the EG site, this suggests substantial drainage and DOC loss in the EG site over time. Kalbitz et al. also found greater peat decomposition in degraded peatlands resulting in lower DOC concentrations in soil solution with a higher proportion of aromatic compounds50. Also, Braggaza et al. measured enzyme activities and DOC in ombrotrophic peatlands along an altitudinal gradient of decreasing temperature and increasing water content and found enhanced β-glucosidase activity at the relatively dry low altitude peatland and phenol oxidase inhibition at the wet high altitude peatland with a decreasing gradient of DOC with altitude51.The significant differences in decomposition pools and processes at depth was counter-intuitive as we expected sites to be similar at depth due to the constant water table (i.e. the catotelm) with hydrological legacies primarily causing differences between sites in surface peat where the water table fluctuates (i.e. the acrotelm). It is possible that the depth of the acrotelm-catotelm border differed between each site and this should be considered in future field investigations. However, deep peat is generally characterized by anaerobic conditions and older more humified carbon with slower exchange of energy and matter2 and CH4 results show that the drying treatments caused osmotic disruption of microbial biomass and likely lysis of cellular components particularly at depth that may have contributed to the DOC pool. Therefore these effects reflect extreme drought and therefore do not necessarily reflect moderate drought effects likely under field or predicted climate change conditions. However, the response of enzyme kinetics and DOC to extreme drought were clearly dependent on hydrological legacy as shown by the increase in Vmax and Km at the EG site associated with a positive increase in DOC and phenolics. Bouskill et al. found a significant increase in compounds related to metabolic and carbohydrate biosynthesis in a tropical forest soil drought experiment that suggested a metabolic response in the microbial community caused by elevated enzyme production rather than stabilization of sorbed enzymes19. The increase in β-glucosidase activity (Vmax) within the EG site, reflects a stimulation of microbial de novo synthesis that is as expected via the enzyme latch mechanism despite the drop in heterotrophic respiration18. Newly released enzymes will be considerably more active, despite the release of phenolic inhibitors18. The change in β-glucosidase kinetics might also reflect the decrease in pH and increased substrate availability (affecting Vmax). Interestingly, whilst the dry EG site exhibited an increase in potential Vmax and Km, our in vitro study showed evidence of competitive inhibition (increased Km only) in which the inhibitor binds to the active site, reducing the affinity of the enzyme for substrate. A number of studies have linked SOM and humic complexes containing phenols to competitive inhibition of β-glucosidase55. We suggest that competitive inhibition within the ‘open latch’ EG peat may relate to humic (phenolic) substances (i.e. increase in Km) but also edaphic enzymes (i.e. increase in Vmax) that are less sensitive to phenolics due to stimulation of microbial enzyme expression18 and/or a hydrological legacy effect of less inhibitive phenolic material (<1000 AMW) due to enhanced phenol oxidase activity over the longer term57. Although no significant change in phenol oxidase activity was observed, there was evidence of elevated phenol oxidase under extreme drought in the EG site (P < 0.064). It is likely that the effect of oxygen on edaphic enzymes and de novo synthesis by the microbial community may have occurred within 5–24 hours of drought18. The lower sensitivity of extracellular enzymes compared with microbial metabolism to phenolics would disproportionately favor DOC release, rather than complete mineralization18. The increase of DOC in the EG site due to waterlogging may also be caused by the mobilization of released DOC from the peat matrix and persistence of β-glucosidase enzymes due to competitive inhibition. Indeed, there also appeared to be a declining gradient of DOC release by air drying due to drought legacy from the EG, DB2 and DB7 sites. Short-term flushing of DOC by drought and rewetting in the field has been observed in a number of studies58 and these results may explain some of the inconsistencies. Laine et al. observed higher DOC concentrations in drained than in pristine peat mesocosms in line with previous results that a deep aerobic layer promotes DOC release60. Laine et al. also observed a lower pH and higher DOC in drained peat that was attributed to humic substances61 and carboxyl acids62 in accordance with our observations in the EG site at depth.The second objective was to examine whether hydrological legacy alters the response of β-glucosidase kinetics and the type of inhibition to short-term variation in hydrology. Importantly, the CO63. Phenolics exist as either (1) a dissolved form moving freely in the soil solution, (2) a sorbed form that reversibly binds to the soil particle or proteins, or (3) a polymerized form of phenolics consisting of humic substances each involving reversible sorption to soil through hydrophobic, hydrogen and ionic bonds63. Our study supports recent studies that suggest that the form of phenolics, not their chemical structure, can influence their fate in peat, as they cannot all be easily characterized into the slow recalcitrant pool in C dynamics63 or all be considered as potent inhibitors of hydrolase enzymes as according to the enzyme latch mechanism. Fierer found that low molecular phenolic compounds could serve as a labile substrate, promoting microbial biomass64. Müller et al. showed that lignin-drived phenolic compounds induced cellulase production, suggesting their potential to enhance decomposition65. Apparently the effect of phenolics on microbial extracellular enzyme activities depends on the source and composition rather than the absolute quantities66. In peatland ecosystems with a large amount of phenolics, higher phenol oxidase results in higher phenolic content in pore water as a product of enzyme action63. Bouskill et al. found evidence of an increase in the abundance of genes related to the oxidative enzymes targeting aromatic moieties in a forest soil drought experiment19. Wang et al. also observed a significant build-up of phenolics during short-term drought but suggested that reduced phenol oxidase activity as an explanation as supported by studies that show an optimal soil water content for phenol oxidase67. Indeed, Wang et al. also found evidence of changes in phenolic quality and quantity in shrub/tree relative to Sphagnum/herb10. Therefore, long-term differences in vegetation succession from Sphagnum to shrub domination may also affect the characteristics of the peat and its decomposability by increasing inhibitory phenolics.Phenolics consist of one aromatic ring and hydroxyl group and encompass low molecular compounds to complex highly polymerized compoundsin vitro β-glucosidase activity in surface peat by uncompetitive inhibition would have involved the inhibitor binding to the enzyme-substrate (ES) complex, resulting in the reduction in both Vmax and Km. Kim et al. found that pine bark extract (containing phenols) caused a combination of non-competitive (decreased Vmax) and uncompetitive inhibition of α-glucosidase68. In the DB and WP sites at depth, inhibition was non-competitive, where the inhibitor reduces the activity (Vmax) of the enzyme and binds equally well to the enzyme whether or not it has already bound the substrate. Malcolm and Vaughan explained non-competitive inhibition of phosphomonoesterases by SOM in terms of conformational change in the enzyme structure when bound to humic material69. Our multivariate results suggest that uncompetitive (surface) and non-competitive (deep) inhibition were likely attributable to differences in H+ ions and SOM quantity and quality (phenolic content of humic substances) between depths. Humification was higher at depth suggesting a sustained microbial activity despite anoxic conditions resulting in higher concentrations of larger humic acids relative to smaller fulvic acids that represents the age of the deep peat layer. Indeed, the final stage of decomposition of humic matter is the breakdown of the more resistant lignoid or phenol part of the humic molecule and many carboxylic and phenolic acids are produced35. Wallage et al. also found that the surface peat layer consists predominately of fulvic acids (high E4/E6 ratio) from enhanced microbial decomposition and the lower depth of humic acids (lowE4/E6)11. Enzymes can be entrapped by humic molecules and can maintain their activity, being protected against proteolysis, thermal and pH denaturation, remaining active under conditions unfavorable for the activity of soil microorganisms34.The observed reduction of in vitro enzyme kinetic and inhibition assays using specific fractionated or filtered humic/phenolic peat extracts. Phylogenetic and microbial functional diversity molecular approaches are required to establish how hydrological legacy impacts on the microbial community structure and function and in situ enzyme production using genomic, proteomic and metabolomic techniques to link these changes to extracellular enzyme kinetics.Further research is required on enzyme kinetics using more realistic and dynamic laboratory experiments on moisture manipulations in a variety of peatlands exposed to varying hydrological legacy. The results presented here represent more extreme effects and there is a requirement to determine how enzyme inhibition may change in response to predicted climate change particularly moderate dry-rewetting cycles. In particular, analysis of the forms of phenolic compounds as well as In conclusion, enzyme kinetics and different types of enzyme inhibition were related to three-dimensional hydrological legacy suggesting that shifts in the microbial community structure and function over time alters the composition of humic compounds and their interaction with extracellular enzyme function. Importantly, the drought legacy site at depth following short-term drying and rewetting exhibited (1) a flush of DOC and phenolics that were (2) associated with increased β-glucosidase activity and (3) competitive inhibition. These results suggest that loss of carbon by short-term drought or rewetting may occur from sites with a legacy of drought due to the release of non-inhibitory phenolics that permit enhanced enzyme activity.Calluna vulgaris L.), cotton grass (Eriophorum spp.), and bryophytes , and is described within the National Vegetation Classification70 as C. vulgaris-Eriophorum vaginatum blanket mire with Empetrum nigrum sub-community (M19b). Four sites were chosen with known historical hydrological legacies and flat slopes, all within the Geltsdale NNR (50 km2 catchment but sites were within 4 km2 of each other) as this reduced variation in climatic conditions . Site 1 (eroded gully - EG) was located at Blackburn Head  which was within a historically unmanaged area that had suffered from drainage due to gully erosion (i.e. unmanaged dry site). Site 2 (ditch-blocked <2 years - DB2) was located at Glendue Fell  which had been drained historically but recently ditch-blocked within the last two years (i.e. short-term grip-blocked). Site 3 (ditch-blocked <7 years – DB7) was located at Halton Lea Fell  which had also been drained historically but was known to have been ditch-blocked approximately seven years ago (i.e. long-term grip-blocked). Site 4 (wet pristine - WP) was located at Midgeholme Fell  that had not been managed (except for burning in adjacent downslope locations) with potentially pristine mire hydrological conditions (i.e. unmanaged surface wet site with Sphagnum cover).The study was conducted at Geltsdale RSPB National Nature Reserve, North Pennines, UK Fig.  because All peat cores were collected in spring 2010 between April and May. Samples were collected from the DB2 site at Coldfell on the 14/4/2010; at the DB7 site at Haltonlea Fell on the 21/4/2010; at the EG site at Blackburn Head on the 12/5/ 2010; and at the WP at Midgeholme Fell on the 18/5/2010. Four replicate sampling plots within each of the four sites were randomly selected for collecting peat cores, within areas that were visually representative of the site. At each replicate sampling plot, 3 peat cores were collected from the peat surface (0–10 cm) and 3 from depth (50–60 cm) – one for destructive baseline determinations, and two for incubating peat under either dry or waterlogged conditions in the laboratory. The 50–60 cm sampling depth was chosen to ensure samples were from the anaerobic, water saturated zone. A grab sample was also collected at each depth from the four plots for additional baseline determinations described below .2 and CH4 production by headspace incubation with gas analysis by gas chromatography, bulk density and gravimetric water content . The 8 grab samples were used for determination of baseline pH, enzyme kinetics, and DOC as described in the sections below. The remaining 16 cores (8 from each depth) were all incubated at 8 °C in a temperature controlled incubator for 14 days in air (n = 4 per depth), or saturated with artificial rainwater in 1 litre Kilner jars (n = 4 per depth). Information on the artificial rainwater solution and storage of treatments is in Supplementary Materials and Methods.Peat cores and grab samples were returned to the laboratory on the same day as collection and stored at field temperature (8 °C) for 24 hours prior to analyses. Wet weights of all cores were determined. Eight cores were used for baseline determinations under the immediate site hydrological and thermal conditions for surface (n = 4) and deep (n = 4) peat including CO2 and CH4 production were determined as described in Supplementary Materials and Methods. Peat pH, glucosidase and phenol oxidase enzyme kinetics, spectroscopy of water extracts and dissolved phenolics were determined as described in the sections below using a peat solution of 5 cm3 peat in 50 ml deionized water .After two weeks incubation, the dry cores were weighed. The water in the Kilner jars with the saturated cores was carefully removed along with the PVC tubes and the cores weighed. Bulk density determinations from the baseline replicates were used to estimate the gravimetric water content of the cores. COAir and peat temperature were determined at each site on the day of collection using a hand-held meter with probe. Peat pH was determined using the peat solution with a standard pH electrode. The bulk density, gravimetric and volumetric water content of cores were determined by drying the cores of known volume in an oven at 105 °C for 24 hours.3 of peat was incubated in 50 ml of 0.1 M NaOH solution for 24 hours, filtered through 0.45 µm filter papers and stored at 4 °C before analysis. Samples were scanned between 400 and 700 nm using a scanning spectrophotometer. The E4/E6 ratio (humic/fulvic acids) was determined as the ratio of 465 to 665 nm71. The absorbance at 540 nm was also used as a measure of humification degree.A known weight of dried peat was placed in a crucible and ignited at 550 °C for 24 hours to determine soil organic matter (SOM) content (% dry weight) by loss on ignition (LOI). 5 cm72. Specific UV absorbance (SUVA254) was determined as the ratio of absorbance at 254 nm to DOC concentration and expressed as m−1 Abs254 mg−1 DOC L−1.Dissolved organic carbon was extracted from the peat solution by centrifugation of subsamples at 10 000 rpm for 10 minutes, filtering through 0.45 µm filter papers and storing at 4 °C before analysis. Dissolved Organic Carbon (DOC) was determined on a TOC analyzer. Dissolved phenolic concentrations were determined using the Folin-Ciocalteau reagent microplate methodVmax) and Michaelis constant (Km) were determined using fluorogenic methylumbelliferyl (MUF)-β glucoside substrate according to the methods of Freeman et al.73 and Bonnett et al.74. Phenol oxidase activity (Vmax) was determined by the method of Pind et al.75 but not Km as the rate of L-DOPA oxidation in soils may not vary linearly with time, substrate concentration or soil dilution59 .The maximal rate of β-glucosidase enzyme reaction  in 1 mlVmax and Km) and inhibition constants (Ki) were determined using Michaelis-Menten and Substrate Inhibition non-linear regression models in GraphPad Prism 5. An F-test was used to accept the null hypothesis of Michaelis-Menten fit to the data or reject in favor of Substrate Inhibition. Identification of the inhibition mechanism for peat incubation with pure enzyme  was achieved using plots of Ki. NR versus substrate [S] concentration according to Geng76. Based on the inhibition degree, [R = [v(+inhibitor)/v(−inhibitor)] = 1/], the apparent inhibition constant regardless of the inhibition mechanisms  could be calculated from R by rearranging this equation as Ki, NR = [I] R/(1 − R). Uncompetitive competition was identified by its unique decrease of Ki. NR with increase of [S] when [S] < Km. Competitive and non-competitive models were selected using Akaike’s Information Criterion (AIC). Prism calculates the difference in AICc values and the probability that each model is correct, with probabilities summing to 100%. Relationships between variables were tested using Spearman Rank correlation analysis and multiple stepwise regression analysis. Discriminant Function Analysis (DFA) was used to predict categorical groups of enzyme inhibition  with continuous, independent decomposition variables. Principal Components Analysis (PCA) was used to determine relationships between decomposition pools and processes. All data from both depths and hydrological manipulations were included (n = 96).All statistical analyses were carried out using Minitab 13.20  or IBM SPSS Statistics Version 23.0.0.2. Data were tested for normality using the Kolmogorov-Smirnov normality test and homogeneity of variances using Bartlett’s test for normal data and Levene’s test for non-normal data. Data that failed the equal variance assumption were log transformed. The minimum value + 1 for negative datasets was added to each individual data point to shift the distribution from negative to positive values above 1 prior to transformation. Two-way General Linear Model ANOVA with Tukey multiple comparisons were used to compare Site x Depth factor interactions for each level of moisture under baseline conditions, and Site x Moisture factor interactions for each depth level (surface and deep). For enzyme kinetics, Michaelis-Menten coefficients (Supplementary Inofrmation