The growth factor brain-derived neurotrophic factor (BDNF) has been implicated in alcohol use disorder. Val66Met is a common variant of the BDNF gene which reduces BDNF release in the brain. Val66Met has been suggested as a risk factor for psychiatric disorders and substance use. Using an operant self-administration paradigm, we investigated ethanol preference and ethanol seeking in a genetically modified rat model of the BDNF Val66Met variant, Val68Met rats. There was no effect of Val68Met genotype  on acquisition of stable lever pressing for a 10% ethanol solution or extinction of this behaviour. Met/Met rats of both sexes had slightly, but significantly lower motivation to lever press for ethanol. Following extinction of responding, females with the Met/Met genotype demonstrated a lower propensity for reinstatement of responding to cues. There were no changes in anxiety-like behaviour or locomotor activity. In conclusion, Met/Met rats showed lower motivation to press for a reward, and also a decreased propensity to relapse, suggesting a possible protective effect of the Met/Met genotype against alcohol use disorder, at least in females.Brain-derived neurotrophic factor (BDNF) has been implicated in alcohol use disorder. The Val66Met polymorphism is a common variant of the BDNF gene (rs6265) which reduces activity-dependent BDNF release, and has been suggested as a risk factor for psychiatric disorders and substance use. Using an operant self-administration paradigm, this study aimed to investigate ethanol preference and ethanol seeking in a novel rat model of the BDNF Val66Met polymorphism, Val68Met rats. Male and female BDNF Val68Met rats of three genotypes  were trained to lever press for a 10% ethanol solution. There was no effect of Val68Met genotype on acquisition of stable response to ethanol or its extinction. Met/Met rats of both sexes had a slight, but significantly lower breakpoint during progressive ratio sessions while female rats with the Met/Met genotype demonstrated a lower propensity for reinstatement of responding to cues. There were no effects of Val68Met genotype on anxiety-like behaviour or locomotor activity. In conclusion, Met/Met rats showed lower motivation to continue to press for a reward, and also a decreased propensity to relapse, suggesting a possible protective effect of the Met/Met genotype against alcohol use disorder, at least in females. Alcohol use disorder (AUD) is characterised by uncontrollable consumption of alcohol for a long period of time, to the degree that daily living is impacted . LifetimBrain-derived neurotrophic factor (BDNF) has a demonstrated role in the body’s response to alcohol ,9. For eGiven these results, BDNF mimetics would be predicted to be useful in treating alcohol seeking and relapse. Indeed, in a model of intermittent access, two-bottle choice (IA2BC) ethanol consumption in rats, systemic administration of the flavonoid, 7,8-dihydroxyflavone (DHF), which mimics the physiological functions of BDNF, reduced excessive ethanol consumption and preference . On the These preclinical studies predict differences in human subpopulations depending on genetic changes in BDNF signalling . The BDNUsing an operant lever press paradigm, this study aims to investigate different aspects of ethanol preference and voluntary alcohol seeking in a novel rat model of the BDNF Val66Met polymorphism, Val68Met rats, which show the expected reduction of activity-dependent BDNF release . We compA total of 91 BDNF Val68Met rats on a Sprague–Dawley genetic background  were helAll rats were housed in standard individually ventilated cages  for the duration of the experiment (4/cage). The animals had ad libitum access to food and water and were housed under standard laboratory conditions  under a 12:12 h reverse light–dark cycle (lights off 7 a.m.). All behavioural testing was conducted during the dark phase of the light cycle between 9 a.m. and 3 p.m. under red light conditions.All procedures were compliant with the Australia Code of Practice for the Care and Use of Animals for Scientific Purposes  and were approved by the La Trobe University Animal Experimentation Ethics Committee (AEC:21002).Self-administration sessions were carried out as per previous studies ,31 in opv/v ethanol and 5% v/v sucrose or a water reward upon 2 lever presses (FR2). Rats were also familiarised with cues to signal reward availability. This included a stimulus light upon reward delivery and an olfactory cue of vanilla essence placed underneath the active lever. Animals had sufficient access to food throughout the night with standard rat chow available ad libitum for the entirety of the overnight training.Overnight Training: When approximately six weeks old, the rats were introduced to the operant chambers in a single overnight training session which lasted approximately 16 h, where rats were able to investigate the chamber and learn how to lever press for a single 100 μL reward of 5% v/v ethanol. Rats were placed in the operant chambers for daily 20 min sessions (Monday–Friday) for 8 days. A solution of 10% v/v ethanol and 5% v/v sucrose was administered on days 1–5, and 10% v/v ethanol, 2.5% sucrose from day 6–8. Ethanol and water levers were alternated on day 4 to avoid place preference. A drop of solution was placed in each receptacle and vanilla essence was placed before the active lever to signal the orientation of the solutions. A fixed ratio of FR2 was used on day 1, then increased to FR3 where it stayed for the duration of the sucrose fade.Sucrose Fade: Following overnight training, animals progressed to the sucrose fade protocol, where the concentration of sucrose was gradually reduced so that rats were eventually only responding for a solution of 10% v/v ethanol, which was considered the reward for the continuation of the study. For the following 4 weeks, a fixed ratio of FR3 was set for the 20 min daily sessions. The olfactory cue of vanilla essence and the stimulus light was again paired with the presence of alcohol.FR3 Acquisition—Stable Responding: After 8 days of decreasing the sucrose concentration, rats progressed to a solution of 10% Progressive Ratio: Following normal responding, rats entered progressive ratio (PR), where the number of lever presses required for a single reward of either solution increased following each reward dispensed; for example, first reward following one lever press, second reward after three presses, third reward delivered after six presses. This was the case for both active and inactive levers. A total of three PR sessions were conducted for a duration of 90 min every second day for five days  and a single drop of each solution in their respective receptacles were re-introduced. Importantly, during this session ethanol and water rewards were withheld upon lever presses. Rats were expected to revert to a preference for pressing the lever associated with ethanol reward over the lever associated with water. The number of lever presses during the reinstatement session were compared with those of the last 5 days of extinction.The elevated plus maze (EPM) test was conducted on two occasions throughout the operant protocol on a day when no operant responding was assessed. The first session, 5 min for each rat, was conducted approximately halfway through the FR3 phase, with the second session conducted several days following completion of the reinstatement session. The maze was raised approximately 50 cm above the floor and consisted of a plus shape with two 50 cm long open arms and two 50 cm long closed arms . An infrLocomotor activity was assessed in a 30 min session conducted immediately after each of the two elevated plus maze sessions and examined whether factors such as sedation or hyperactivity influenced lever pressing. Rats were tested in locomotor photocells  that detected all movements across infrared beam arrays. Data were recorded using MED-PC IV software. Greater distance covered (cm) was a potential indicator of hyperactivity, while significantly lower locomotion suggested lethargy .p ≤ 0.05 regarded statistically significant.Data analysis was carried out using SPSS version 27  and GraphPad Prism version 9 . Mixed between-within ANOVAs with sex and genotype as between-subject factors and lever and session as the repeated measures, followed by appropriate post hoc testing, was used to analyse all data. Data are expressed as the mean ± standard error of the mean (SEM), with p < 0.05. A Bonferroni adjustment was used for all post hoc analyses where appropriate. Magnitude of effect sizes  was defined using guidelines from Cohen [Data were first checked for outliers in each stage of testing using z-scores, and scores falling outside z = ±3.29 were removed. Two additional values were excluded from the reinstatement session based on rats activating <2 rewards (five or fewer presses) over the 20 min period . If the om Cohen .p < 0.001, ηp2 = 0.87); however, there were no significant weight differences between genotypes  = 1.13, p > 0.05, ηp2 = 0.026)  = 544.5, p < 0.001, ηp2 = 0.13), with lever pressing increasing over time. There were no significant interactions between session and either sex or genotype, suggesting that all groups acquired stable responses at the same rate. There was a main effect of sex  = 40.7, p < 0.001, ηp2 = 0.33), with males pressing more than females, but no significant effects of genotype  = 0.46, p > 0.05, ηp2 = 0.011, sex × genotype F = 0.25, p > 0.05, ηp2 = 0.006).All rats successfully learned to operate the levers within the chamber and showed preference for the ethanol and sucrose-paired lever during the overnight training and sucrose fade sessions see . An analp > 0.05, ηp2 = 0.005), and again no significant effects of genotype  = 1.59, p > 0.05, ηp2 = 0.037, sex × genotype F = 0.19, p > 0.05, ηp2 = 0.005), suggesting that, despite the significant interactions with session, there were no significant differences between groups on average stable ethanol responding as a ratio of body weight. There was again a main effect of session  = 4.87, p < 0.001, ηp2 = 0.056) with the amount of ethanol ingested by body weight increasing over time; however, there were now also significant session × sex  = 2.28, p = 0.005, ηp2 = 0.027) and session × genotype interactions  = 1.51, p = 0.047, ηp2 = 0.036). Inspection of the data , with males pressing more than females, but no significant effects of genotypes  = 2.13, p > 0.05, ηp2 = 0.048, sex × genotype F = 0.15, p > 0.05, ηp2 = 0.004). However, when accounting for body weight  and there was also a significant main effect of genotype  = 5.48, p = 0.006, ηp2 = 0.11), although no interaction between sex and genotype  = 1.29, p > 0.05, ηp2 = 0.029). Bonferroni post hoc test showed that Met/Met rats had a significantly lower breakpoint than Val/Val rats when expressed as weight-adjusted ethanol responding (p = 0.001).Analysis of the progressive ratio sessions showed that there was no significant main effect of session  = 0.1.19, y weight D, femalep < 0.001, ηp2 = 0.60) as pressing of the previously active lever decreased over time. There was a significant session × sex interaction  = 3.07, p = 0.004, ηp2 = 0.035), with females starting with lower lever pressing  = 6.15, p = 0.015, ηp2 = 0.068).Analysis of extinction sessions following removal of ethanol rewards and cues A showed p > 0.05, ηp2 = 0.008) and no differences between genotypes  = 1.13, p > 0.05, ηp2 = 0.026, sex × genotype F = 1.00, p > 0.05, ηp2 = 0.023). It should be noted that during this period, there was still a significant main effect of lever  = 81.2, p < 0.001, ηp2 = 0.50), with lever pressing for the previously active lever being higher than the previously inactive lever  = 0.66, ve lever ; howeverp < 0.001, ηp2 = 0.76), with rats overall showing higher active lever pressing during the reinstatement session compared to the end of extinction. There was also a significant session × sex interaction  = 7.04, p = 0.010, ηp2 = 0.079) although no session × genotype  = 1.38, p > 0.05, ηp2 = 0.032) or session × sex × genotype interaction  = 1.97, p > 0.05, ηp2 = 0.046). However, when taking body weight into account  and a significant session × sex interaction  = 7.87, p = 0.006, ηp2 = 0.088), there was also a significant session × sex × genotype interaction  = 3.31, p = 0.041, ηp2 = 0.075). Based on these interactions, body weight-adjusted data were then analysed further with males and females separated. Males showed no significant session × genotype interaction  = 0.20, p > 0.05, ηp2 = 0.009), suggesting that all groups showed the same level of reinstatement. In contrast, there was a large and significant session × genotype interaction in females  = 1.97, p = 0.049, ηp2 = 0.14). Bonferroni post hoc test comparing active lever pressing during extinction and reinstatement showed that Val/Val (p < 0.001), Val/Met (p < 0.001) as well as Met/Met (p = 0.016) rats all showed reinstatement of ethanol responding. However, while there were no genotype differences during extinction sessions, Met/Met females had significantly lower active lever pressing during the reinstatement session compared to both Val/Val (p < 0.001) and Val/Met (p = 0.012) females  analysis. First, a grand mean value was calculated for all female or male rats, and the number of rats of each genotype that were either higher or lower than this grand mean was expressed as percentage , with females first pressing later than males. Female Met/Met rats had the longest latencies, but there was no significant main effect of, or interactions with, genotype  with longer latencies in females than males, particularly in female Met/Met rats, but no significant main effect of, or interactions with, genotype  = 16.9, genotype . Similargenotype .p < 0.001, ηp2 = 0.24), with females spending more time in the open arms than males. There was no main effect of session  = 0.60, p > 0.05, ηp2 = 0.007), suggesting rats explored the open arms of the maze similarly when tested during the middle of the operant protocol and again at the end; however, there was a session × sex interaction  = 6.84, p = 0.011, ηp2 = 0.074). Analysis of males and females separately showed there was no difference in time spent in the open arm across the two testing sessions in males  = 2.25, p > 0.05, ηp2 = 0.049); however, females spent more time in the open arm when tested following completion of operant testing compared to midway through  = 4.47, p = 0.041, ηp2 = 0.098).Behavioural testing to assess any genotype differences between anxiety-like behaviour or locomotor activity which could affect operant responding was conducted at two time points throughout the testing period. Time spent in the open arm of the elevated plus maze was used as a measure of anxiety-like behaviour A. There p = 0.012, ηp2 = 0.079), with rats less active in the second session, most likely due to habituation to the testing chamber. There were no interactions with sessions, suggesting this effect was consistent across groups. There was a main effect of sex  = 31.4, p < 0.001, ηp2 = 0.29), as females were more active than males, and there was also a main effect of genotype  = 3.67, p = 0.030, ηp2 = 0.086), although no sex × genotype interaction  = 0.48, p = 0.62, ηp2 = 0.012). Bonferroni post hoc test of the genotype effect showed that Val/Met rats were more active than both Val/Val (p = 0.014) and Met/Met rats (p = 0.016) in the photocell chambers used to measure distance travelled  = 6.65, ravelled B.This study showed that, despite no effect of Val68Met genotype in acquisition of stable responding to ethanol or extinction of this response upon removal of reward paired cues, female rats with the Met/Met genotype demonstrate a decreased reinstatement of responding to cues compared to other genotypes, while Met/Met rats of both sexes have a subtly, but significantly lower breakpoint during progressive ratio sessions than Val/Val wildtype rats. These differences were seen primarily when actual or potential amount of alcohol consumed by body weight was taken into account, despite no significant effects of genotype on body weight at any age. There were also no effects of Val68Met genotype on anxiety-like behaviour or locomotor activity which could have affected the way rats behave and respond to lever presentation in the operant self-administration chambers.The results of this study are consistent with previous work in our laboratory where we have shown sex differences in various animal models of the role of BDNF in operant alcohol self-administration ,20,31. IIn addition to a difference in breakpoint, we also showed that, after adjusting for body weight, females with the Met/Met genotype selectively showed decreased reinstatement of lever responding following re-presentation of alcohol paired cues. We previously demonstrated that treatment with the TrkB receptor agonist, DHF, increased reinstatement selectively in females, again after adjusting for body weight . As the That Met/Met rats appear to have lower motivation to continue to press for a reward when the number of presses becomes too high in the progressive ratio sessions, and also show decreased response to return of alcohol-paired cues in the reinstatement session, suggests a possible protective effect of the Met/Met genotype against the likelihood of relapse, at least in females. This is consistent with clinical studies showing higher relapse rates in Val/Val carriers compared to Met allele carriers  and thatThe contradictory results between clinical and pre-clinical studies may also reflect limitations in the translatability of findings in some of the rodent models used so far. Two meta analyses have cast doubt on genetic linkage of the Val66Met (rs6265) polymorphism and risk for alcohol dependence ,25. ThisThe effect of genotype on reinstatement was seen in females only. Female rodents have been extensively shown to have enhanced addiction vulnerability compared to males . Sex difAlthough Val/Met rats were more active than other genotypes, and there were some changes in behaviour as the rats aged and completed more of the operant self-administration protocol, there were no differences in anxiety-like or locomotor activity behaviours between Val/Val wildtype and Met/Met rats. This confirms that the differences in lever pressing between these groups cannot be attributed to baseline differences in anxiety or hyperactivity which could alter the way rats press the lever. These results are mostly consistent with our previous work in this rat model during early adulthood, where we saw no effect of genotype on any measures of anxiety-like behaviour or locomotor activity and only showed decreased fear memory in Met/Met rats compared to other genotypes ,55.The subtle increase in exploratory locomotor activity in Val/Met rats compared to both Val/Val and Met/Met genotypes may hint at why Val/Met rats did not differ from Val/Val in any aspect of operant alcohol self-administration. Chen et al.  found thA limitation of this study is that Met/Met rats may metabolise or excrete alcohol faster than other genotypes, which could have led to lower motivation and reinstatement of alcohol responding. Previously, we found no difference in methamphetamine metabolism between mouse Val66Met genotypes , but simThis study showed that in an operant alcohol self-administration paradigm, rats with the Met/Met genotype of the Val66Met polymorphism had a lower breakpoint than Val/Val wildtype rats when the demands to obtain alcohol increase, and that female Met/Met rats had lower propensity for reinstatement to alcohol-paired cues when they were reintroduced following a period of extinction. This suggests that the Met/Met genotype is associated with reduced perseverance and cue-induced relapse of ethanol intake, which is consistent with clinical studies showing increased relapse and susceptibility to dependence in the Val/Val genotype . Despite


Surface morphology and physiochemical properties of the prepared adsorbent are characterized by scanning electron microscopy-energy dispersive spectrometer, X-ray diffraction, and N2 adsorption–desorption. The effect of pH, contact time, adsorbent dosage, and initial concentration on Cu2+ and F− adsorption is also investigated. In addition, adsorption kinetics and isotherms are fitted to pseudo-second-order kinetics and Langmuir model, respectively. Thermodynamic parameters suggest that the adsorption process is spontaneous and endothermic. The adsorption mechanism is further characterized by Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy. The Cu2+ absorption mainly occurs through ion exchange, coordination reactions, and surface precipitation, while the F− adsorption mainly occurs via ion exchange and hydrogen bonding. The selective adsorption experiments reveal that FKBC has good selectivity for Cu2+ and F−. The adsorption–desorption experimental results indicate that FKBC can be reused for Cu2+ and F− adsorption after regeneration. Results indicate that FKBC can be a promising adsorbent for Cu2+ and F− removal from aqueous solutions.In this work, bamboo charcoal (BC) is prepared by pyrolysis of bamboo. Then, KOH modification and surface deposition of Goethite (α-FeOOH) are performed to obtain a new KOH-modified BC loaded with α-FeOOH (FKBC) adsorbent for copper  was successfully synthesized and used for highly efficient Cu A large amount of wastewater containing copper  is widely present in nature and can be easily synthesized in the laboratory. It has been increasingly used as an adsorption material due to its strong affinity, special structure, number of binding sites, environmental friendliness, and low cost.35,36 Literature has confirmed that α-FeOOH can effectively adsorb Cu2+ and has strong affinity and adsorption ability for F− due to its reactive functional groups.37,38 However, α-FeOOH is prone to aggregation, limiting its practical applications.39,40 Therefore, depositing α-FeOOH onto biochar to improve its dispersion benefits its widespread utilization in environmental applications.In particular, metal hydroxide minerals have been extensively reported as good adsorbents.2+ and F− removal. Therefore, this study prepares a novel KOH-modified BC loaded with α-FeOOH (FKBC). The physicochemical properties of FKBC have been investigated. The effect of pH, contact time, adsorbent dosage, initial concentration on Cu2+ and F− adsorption, adsorption kinetics, isotherms, thermodynamics, and adsorption mechanism are studied. Finally, the adsorption selectivity and reusability of FKBC for Cu2+ and F− are also evaluated. Nevertheless, no investigation has been previously reported on FKBC for simultaneous Cu2+ and F− removal.Based on this information, we anticipate alkali modification of bamboo charcoal (BC) and α-FeOOH surface deposition can produce a potential adsorption material for Cu2.2.13, Cu(NO3)2, KF, Fe(NO3)3, NaCl, K2SO4, KNO3, and NH4Cl were purchased from China National Pharmaceutical Group Chemical Reagents Co., Ltd. NiSO4 and CdSO4 were obtained from Aladdin Reagent Co., Ltd. All chemical reagents used in these experiments were of analytical grade and were used without further pretreatment. Cu2+ and F− working solutions were prepared by dissolving Cu(NO3)2 and KF in deionized water, respectively. pH of Cu2+ and F− working solutions was adjusted by KOH (1 mol L−1) and HNO3 (1 mol L−1).The bamboo used in the experiment was collected from Hubei Polytechnic University, Hubei Province, China. KOH, HNO2.229,41 First, 100 g fresh bamboo was cut into small pieces, washed three times with deionized water, and dried in an oven at 353 K for 6 h. The BC was prepared in a resistance tube by calcinating the bamboo pieces at 923 K for 1.5 h under an N2 atmosphere of 100 mL min−1 flow rate. The obtained BC was then ground and sieved at 100 microns.BC adsorbent was prepared according to previous work.31,40 20 g BC powder was added to a 200 mL KOH solution (2 mol L−1) and impregnated at 333 K for 12 h in a water bath shaker at 120 rpm. Then, 100 mL Fe(NO3)3 solution (1 mol L−1) was slowly added to the BC-KOH mixture to form a precipitate, aged in an oscillating water bath at 333 K for 48 h before natural precipitation. The precipitate was washed with deionized water until the pH was neutral. The product was dried at 333 K for 6 h, ground, and sieved at 100 microns.The preparation procedure of FKBC was referred to in the previous paper.2.32 adsorption–desorption method at 77 K . The surface potential of the adsorbent was measured by the pH drift method. Fourier transform infrared spectroscopy (FTIR) was used to characterize the surface functionalities of the adsorbent before and after adsorption . X-ray photoelectron spectroscopy (XPS) was used to study the surface chemical state of the adsorbent before and after adsorption .The surface and elemental composition of FKBC were analyzed by scanning electron microscopy  combined with an energy dispersive spectrometer , respectively. The mineral composition was determined by X-ray diffraction analysis . The adsorbent's specific surface area and pore volume were obtained by the N2.42+ and F− concentrations in the filtrate were determined by atomic absorption spectroscopy (AAS) and ion chromatography (IC), respectively.Batch adsorption experiments were conducted in a 200 mL conical flask at a shaking speed of 120 rpm. At the end of each experiment, a 2 mL solution sample was filtered with a 0.22 μm membrane. The residual Cu2+, F− initial concentration, kinetics, isotherms, and thermodynamics, are provided in ESI (Table S1R%), adsorption capacity  at time t, and equilibrium adsorption capacity  of FKBC for Cu2+ or F− was calculated by the following equations:42C0 is the Cu2+ or F− initial concentration (mg L−1), Ce is the Cu2+ or F− concentration at adsorption equilibrium (mg L−1), Ct is Cu2+ or F− concentration over time (mg L−1), V is the solution volume (L), and m is the amount of FKBC (g) used in the experiments.Detailed experimental conditions for batch adsorption, such as pH, contact time, adsorbent dosage, Cu Table S1. Paramet Table S1. The ads2.52+ or F−-loaded FKBC was filtered with 0.22 μm membrane and regenerated with 100 mL HNO3 (1 mol L−1) and KOH (1 mol L−1) for 1 h, respectively. Then, the desorbed adsorbent was washed with deionized water several times and dried for the next adsorption experiments.Several adsorption–desorption cycle experiments were conducted under 120 rpm to examine the reusability of the adsorbent. Detailed experimental conditions are shown in Table S3.2.6post hoc test comparisons using the IBM SPSS Statistics 21.0 software. The statistical significance is set at a level of p < 0.05. The kinetic, isotherm, and thermodynamic data fitting are performed using the Origin 2021 software.In this study, all adsorption experiments are conducted in triplicate to ensure consistency. The experiment results are calculated as mean ± standard error. Data are analyzed by one-way analysis of variance (ANOVA) and Student–Newman–Keuls (SNK) 3.3.12+ and F− adsorption, the surface is rough with a large amount of sediment, suggesting that the morphology of FKBC does not change after reuse. EDS element analysis also confirms the successful adsorption of Cu2+ and F−.θ = 23°, attributed to aromatization and graphitization of carbonaceous organic matter.43 Peaks at 28.40° and 40.48° are assigned to (111) and (210) planes of SiO2 (PDF 76-0935). These SiO2 impurities are present in biochar pores and are unfavorable for active adsorption site exposure.44 The XRD spectrum of FKBC shows that the SiO2 characteristic peaks disappear, suggesting that the biochar surface impurities are eliminated after alkali modification, promoting the surface pores formation.45 The characteristic peaks at 21.24°, 33.24°, 36.66°, 53.24°, and 59.00° belong to (110), (130), (111), (221), and (151) of α-FeOOH (PDF81-0464), suggesting that α-FeOOH is successfully loaded on biochar surface.38XRD patterns of BC  show tha2 adsorption–desorption isotherms of BC and FKBC. The N2 adsorption–desorption curve of FKBC indicates obvious hysteresis loops at high pressure and features of the type-IV model, demonstrating the formation of mesoporous structures.462 g−1, and the total pore volume is 0.126 cc g−1, 14.8 times and 2.7 times higher than BC, respectively. The FKBC pore diameter is 3.54 nm, smaller than that of BC. Therefore, FKBC has a larger specific surface area, pore volume, and smaller pore size, offering more adsorption sites and playing a vital role in Cu2+ and F− adsorption from the aqueous phase.3.23.2.12+ and F−.47 Cu2+ mainly exists in the solution when the pH is between 1 and 5. However, light blue copper hydroxide precipitation appears when the pH exceeds 6.4 When the pH of the F− solution is less than 2, they are mainly in the form of HF; when the pH is higher than 5, they are in the form of F−.48 Therefore, determining the optimum pH is necessary at the beginning of the Cu2+ and F− adsorption study.The solution pH always dominates adsorption, influencing the chemical structure and adsorption sites and affecting the existing forms of Cu2+ adsorption capacity and efficiency rapidly increase between pH 2 to 5 and slightly increase from pH 5 to 6. For F− adsorption, the capacity and efficiency improve significantly between pH 2 to 7 and decrease from pH 7 to 10  of FKBC is 6.56. The FKBC surface is positively charged when the pH of the solution is less than pHzpc, resulting in electrostatic repulsion, hindering the Cu2+ diffusion to the adsorbent surface.49 In addition, H+ in the solution combines with F− to form HF, limiting F− adsorption by FKBC. The surface is negatively charged when the pH > pHzpc. With the OH− on the FKBC surface increasing, the competitive adsorption between F− and OH− strengthens. Also, the electrostatic repulsion for F− increases, which is not conducive to F-adsorption. However, the precipitated flocs appear in Cu2+ solution at pH > 5, indicating that the enhanced removal is mainly attributed to precipitation, distinguished from adsorption and avoided.6 Therefore, for subsequent adsorption experiments, the pH of the Cu2+ and F− working solution is set at 5 and 7, respectively. 7 to 10 . The res3.2.22+ and F− adsorption. During the first 30 minutes, the Cu2+ and F− adsorption by FKBC is rapid. However, the adsorption rate decreases when the contact time exceeds 30 minutes. At the beginning of the adsorption process, Cu2+, and F− are quickly adsorbed onto the adsorbent surface through mass transfer; as the reaction proceeds, most of the surface sites of FKBC are occupied; therefore, other Cu2+ and F− diffuse into the porous structure, which is a relatively slow process compared to surface adsorption. Also, the Cu2+ and F− adsorption approaches equilibrium at 90 and 120 minutes, respectively. However, the contribution of extended contact time to the adsorption effect is insignificant. Finally, when the contact time reaches 180–240 minutes, the adsorption efficiency and capacity for Cu2+ and F− are 90.5%, 90.5 mg g−1 and 88.0%, 35.2 mg g−1, respectively, indicating that almost all adsorption sites and pores are occupied, bringing the adsorption reaction to an equilibrium state. Based on the results, the contact time of 240 minutes is appropriate.3.2.32+ and F− adsorption. With the increase in FKBC dosage at constant Cu2+ and F− content, the adsorption capacity gradually decreases while the adsorption efficiency gradually increases. This is due to an increase in FKBC content increases the total number of adsorption sites, thereby improving the adsorption efficiency. However, when the FKBC dosage reaches 0.2 g, the adsorption efficiency tends to stabilize. With further increased adsorbent amount, the ion concentration per unit surface area of FKBC decreases, making it difficult to improve adsorption efficiency. Moreover, as adsorbent dosage increases, the amount of adsorbed ions per unit surface area decreases,50 thus decreasing FKBC adsorption capacity for Cu2+ and F−.3.2.42+ and F− initial concentrations. For a fixed FKBC dosage, when the Cu2+ and F− initial concentrations are from 50 to 200 mg L−1 and 20 to 80 mg L−1, respectively, their adsorption efficiency decreases; however, the adsorption capacity increases rapidly. The main reason is that the Cu2+ and F− initial concentrations are in lower range, many surface sites are available for ions' adsorption, increasing the adsorption capacity. Subsequently, with the same number of adsorption sites, the adsorption efficiency rapidly decreases as the initial concentration increases due to the saturation of adsorption capacity. Thus, the adsorption efficiency can be improved with an increasing adsorbent dosage for higher Cu2+ and F− initial concentrations.503.32+ and F− adsorption rate and the mechanism by FKBC. This study simulated the experimental adsorption data related to Cu2+ and F− using pseudo-first-order, pseudo-second-order, and intraparticle-diffusion models.The adsorption kinetics are analyzed to investigate the Cuk1 (min−1), k2 (g mg−1 min−1), and kip (mg g−1 min−0.5) are the rate constants related to pseudo-first-order, pseudo-second-order, and intraparticle-diffusion models, respectively, c (mg g−1) is the intercept of the intraparticle-diffusion model.Pseudo-first-order , pseudo-2+ and F− adsorption at 288 K, 298 K, and 308 K, respectively. The adsorption rates for Cu2+ and F− increase at higher temperatures, suggesting that temperature reinforces Cu2+ and F− adsorption by FKBC. In addition, the statistical parameters of kinetic models are demonstrated in 2+ (R2 = 0.989–0.997) and F− (R2 = 0.988–0.998) adsorption rate at each temperature. The Cu2+ and F− adsorption capacity calculated  by pseudo-second-order kinetics is closer to the experimental data , indicating that the adsorption behavior of Cu2+ and F− is more suitable to Pseudo-second-order kinetics and mainly controlled by chemisorption.4,382+ and F− adsorption on FKBC, respectively. Both curves display two linear portions at each temperature, indicating that the adsorption process is divided into two diffusion stages.51 The intraparticle-diffusion rate constant of the two stages is shown in 2+ and F− may have first diffused on the FKBC surface at a high rate and then diffused into micropores at a lower rate.37 The linear curves do not traverse the origin, revealing that the adsorption rate is determined by intraparticle-dispersion and physical and chemical processes.523.42+ and F− by FKBC, the experimental data are fitted using the Langmuir, Freundlich, and Temkin isotherm models. Langmuir isotherm model indicates that the adsorption process is monolayer chemisorption on a homogeneous surface.19,21 At the same time, the Freundlich isotherm model describes the multi-layer physisorption on heterogeneous surfaces.19 The Temkin isotherm model is appropriate for chemisorption and assumes that adsorption energy decreases linearly with the surface coverage.14To evaluate the adsorption capacity of CuKL (L mg−1) is the Langmuir constant related to the adsorption sites, Qm (mg g−1) is the maximum adsorption capacity, KF [(mg g−1) (mg L−1)n] and n are Freundlich constants related to adsorption capacity and adsorption density, respectively. B (J mol−1) is the heat of the adsorption constant, and KT (L g−1) is the equilibrium binding constant related to the Temkin model.Langmuir isotherm , Freundl2+ and F− than those of the Freundlich model, respectively ) demonstrates the applicability of the adsorption experiment.55 However, 0 < RL ≤ 1 and RL > 1 indicate that the adsorption is favorable and unfavorable, respectively.5 The RL values are all within the range of 0–1 at each temperature, indicating the favorable nature of the Cu2+ and F− adsorption using FKBC (ectively . The aboing FKBC .B) of the Temkin model increases with increasing temperature, indicating the endothermic adsorption process.56 The investigated parameters also reveal that the maximum adsorption capacities (Qm) for Cu2+ and F− based on the Langmuir model increase by 30.4% and 26.2% when the temperature increases from 288 K to 308 K, respectively. These results suggest that increasing temperature is conducive to reaction progression in Cu2+ and F− adsorption by FKBC, consistent with the Temkin model's investigation.2+ and F− adsorption capabilities are compared with FKBC , enthalpy (ΔH0), and entropy (ΔS0) are calculated to examine the spontaneity and feasibility of Cu2+ and F− adsorption using the following equations:59R [8.314 (J mol−1 K−1)] is the universal gas constant, T (K) is the temperature in Kelvin, KC is an equilibrium coefficient related to Langmuir constant KL (L mg−1), M (g mol−1) is the adsorbate molar mass, and 55.5 corresponds to the solvent molar concentration (mol L−1).3Thermodynamic parameters of the adsorption process involving changes in Gibbs free energy  and substituting H in these groups.5,50 During F− adsorption, the –OH is replaced by F−, or hydrogen bonding occurs between F−.60 In addition, the peak at 613 cm−1 is attributed to Fe–O bending vibrations.52 After Cu2+ adsorption, the peak weakens, preliminarily indicating that Cu may replace some Fe in α-FeOOH. Moreover, after the F− adsorption, the peak at 613 cm−1 changes slightly, and a new absorption peak appears at 467 cm−1, possibly due to Fe–F formation. Overall, preliminary FTIR analysis shows that the oxygen-containing functional groups on the FKBC surface are mainly consumed during Cu2+ and F− adsorption, leading to the movement of characteristic O–H bands.5Functional group changes in FKBC before and after Cuspectrum . The pea2+ and F−, the high-resolution XPS spectra obtained are shown in 2+ and F− adsorption  scale" fill="currentColor" stroke="none"><path d="M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z"/></g></svg>O bond, C–OH bond, and C–C bond, respectively.57 After Cu2+ and F− adsorption, the C–OH bonds and O–CO bonds relative content decreased; however, the reduction is insignificant. This indicates that the oxygen-containing functional groups connected to the C are not the main Cu2+ and F− adsorption participants.2OH (adsorbed water molecules), Oad , and Olatt (lattice oxygen), generated by H–O–H, Fe–OH and Fe–O bonds, respectively.31,35 Before adsorption, the relative Fe–OH content is 50.33%, significantly higher than Fe–O (24.89%), confirming that FKBC contains abundant hydroxyl radicals due to the existence of α-FeOOH.38 After Cu2+ adsorption, the relative contents of Fe–OH and Fe–O decreased significantly, confirming that Cu2+ replaces the hydrogen in hydroxyl groups to form a complex structure with oxygen and exchanges some Fe in α-FeOOH and then forms the O–Cu bond. This conclusion is consistent with FTIR analysis and is confirmed by Cu2p spectroscopy. After F− adsorption, there is a significant decrease in Fe–OH, and the relative content of Fe–O remained unchanged, indicating that the hydroxyl groups in α-FeOOH are exchanged by F−, while Fe is not involved in the adsorption process.The O1s spectrum in 3/2 and Cu2p1/2 characteristic peaks at 935 and 955 eV and shake-up satellite peaks at 963.4 and 943.8 eV, suggesting that Cu2+ is adsorbed in a bivalent state and O–Cu bonds are formed 2 or Cu(OH)+, implying the existence of micro-precipitation on the adsorbent surface,61 confirming the influence of pH on Cu2+ adsorption. After the F− adsorption, the spectrum shows a typical F1s characteristic peak, and the binding energy is between 684–685 eV, indicating that the adsorbed F− mainly existed as inorganic fluoride , S2(d–g)The Cu2p spectrum shows that the binding energy exhibits typical Cu2pe formed .57 In adfluoride . EDS map2+ adsorption mechanism mainly relies on ion exchange, complexation, and micro-precipitation, while F− mainly relies on ion exchange and hydrogen bonding  > Cu2+ (0.073 nm) > Ni2+ (0.069 nm)),62 exhibiting a competitive effect on Cu2+ adsorption process. However, comparing the adsorption capacities and efficiencies of Ni2+ and Cd2+ with that of Cu2+  is smaller than that of Cd2+ (0.426 nm) and Ni2+ (0.419 nm),62 thus, their contact is easy with the FKBC surface and enters the internal pores.To evaluate the FKBC selective adsorption performance, the effect of coexisting ions at different concentrations on Cu2− ≈ Cl− . Additio Table S4, FKBC sh−, NO3−, SO42−, Na+, and NH4+ have little effect on F− adsorption. The adsorption capacities and efficiencies of coexisting ions are far below that of F− by FKBC  are substantially higher after desorption with KOH (43.5–20.2 mg g−1). Based on the effect of pH, some adsorption sites on the adsorbent surface are inevitably occupied by precipitated flocs when using KOH to desorb Cu2+. Overall, the FKBC is a potentially promising adsorbent for Cu2+ and F− due to its high reusability, while using alkali for Cu2+ desorption should be avoided.Adsorption–desorption cycle experiment results are presented in 4.2+ and F− adsorption. The characterization results indicate that FKBC has a mesoporous structure after KOH modification, and the surface loading α-FeOOH has also been successful. Compared with raw BC, FKBC exhibits a larger specific surface area, pore volume, and smaller pore size, providing more adsorption sites and favorable conditions for Cu2+ and F− adsorption. Its adsorption effect for Cu2+ and F− heavily depends on the solution pH, contact time, dosage, Cu2+, and F− initial concentration. The FKBC adsorption kinetics shows that the pseudo-second-order kinetics model better fits the adsorption rate at each temperature. Based on the well-fitted Langmuir isotherm model, the maximum monolayer adsorption capacity of FKBC for Cu2+ and F− at 308 K is estimated at 117.4 mg g−1 and 42.4 mg g−1, respectively. Thermodynamic equations prove that increasing temperature can promote Cu2+ and F− adsorption by FKBC. The adsorption mechanism suggests that the process mainly involves chemical adsorption, and the α-FeOOH on the FKBC surface mainly contributes to Cu2+ and F− adsorption. In addition, the selective adsorption results indicate that FKBC is a selective adsorbent for Cu2+ and F−. The adsorption–desorption results also prove that FKBC has high recycling value. Overall, FKBC can potentially adsorb both Cu2+ and F− effectively.A novel adsorbent, FKBC, is successfully prepared for CuThe data used and analyzed during the current study are available from the corresponding author upon reasonable request.Conceptualization, investigation, writing-original draft, funding acquisition, Wei Yang; investigation, Lei Zhang; conceptualization, methodology, Meng Li; data curation, Ting Zhang; project administration, Yue Liu; resources, Juan Liu.The authors declare no competing interests.RA-013-D3RA05315F-s001


Pediococcus acidilactici GLP06 isolated from feces of beagles. In this study, candidate probiotic bacteria P. acidilactici GLP02 and GLP06 were morphologically characterized and tested for their antimicrobial capacity, tolerance to different conditions , antibiotic sensitivity, hemolytic activity, cell surface hydrophobicity, autoaggregation activity, and adhesion to Caco-2 cells. P. acidilactici GLP06 showed better probiotic potential. Therefore, P. acidilactici GLP06 was evaluated for in vivo safety in mice and whole-genome sequencing. The results showed, that the supplemented MG06 group (1010 cfu/mL), GLP06 was not only nontoxic to mice, but also promoted the development of the immune system, improved resistance to oxidative stress, and increased the diversity of intestinal microorganisms and the abundance of Lactobacillus. Whole-genome sequencing showed that P. acidilactici GLP06 was 2,014,515 bp and contained 1,976 coding sequences, accounting for 86.12% of the genome, with no drug resistance genes and eight CRISPR sequences. In conclusion, the newly isolated canine-derived P. acidilactici GLP06 had good probiotic potential, was nontoxic to mice and promoted the development of immune organs, improved the biodiversity of the intestinal flora, and had no risk of drug-resistant gene transfer, indicating that P. acidilactici GLP06 can be used as a potential probiotic for the prevention and treatment of gastrointestinal diseases in companion animals.The beneficial effects of lactic acid bacteria are well known and recognized as functional foods that are health benefits for companion animals. This study, for the first time, reports the probiotic properties, safety, and whole-genome sequence of  It has been reported to have good probiotic effects, such as reducing constipation and regulating the intestinal flora in mice  microbiota. Therefore, screening and evaluating strains with more beneficial biochemical potential is still needed. However, the canine and feline GIT are rich in microorganisms with probiotic potential.Therefore, this study aimed to isolate and identify strains with probiotic potential from beagle feces and to evaluate the probiotic properties of the strains. At the same time, whole-genome sequencing of the strains and mouse dosing tests were conducted to evaluate the safety of the strains. The results of this study will help in the evaluation of microorganisms that could be used as potential strains in the treatment of gastrointestinal disease syndromes to improve companion animal health and welfare.2.2.1.Fecal samples were obtained from three healthy adult female beagles from the Jimo Livestock Experimental Farm in Qingdao, China; the test animals had not received antibiotics or probiotics for 2 months prior to sample collection. Samples were collected from the rectum using sterile swabs, quickly placed in sterile test tubes containing 10 mL of Man, Rogosa and Sharpe (MRS)  and transported under refrigeration to the Animal Nutrition Laboratory of Qingdao Agricultural University.2.2.−1 to 10−9), and 0.1 mL of each of the 10−3 to 10−7 dilutions was applied to MRS agar containing calcium carbonate. Individual colonies with soluble calcium circles were selected for passaging on MRS agar and incubated for 48 h at 37°C. After three passages, the isolates were stored frozen in 50% (w/v) sterile glycerol at −80°C. The collected samples were mixed with a vortex mixer  for 5 min, serially diluted . Polymerase chain reaction (PCR) amplification was performed using the primers 16S-27F (5’-AGAGTTTGATCCTGGCTCAG-3′) and 16S-1492R (5’-TACGGCTACCTTGTTACGACTT-3′) under the following conditions: pre-denaturation at 94°C for 5 min, denaturation at 94°C for 45 s, annealing at 55°C for 30 s, and extension at 72°C for 45 s for 30 cycles, then extension at 72°C for 10 min. The PCR products were identified by 1.0% agarose gel electrophoresis, and the target bands were recovered with a gel recovery kit  and sent to Tsingke Biological Technology for sequencing. A phylogenetic tree was constructed using Mega 11.0 software to determine the evolutionary relationships of the isolated strains.2.3.2.3.1.Selected pure isolates of LAB were inoculated into MRS broth (2% v/v), incubated for 18 h at 37°C, centrifuged at 10,000 rpm for 10 min at 4°C, and the cell-free supernatant (CFS) was collected.7.0) and adjusted to approximately 1 × 109 CFU/mL to obtain a bacterial suspension (BS).The harvested cells were washed three times with PBS (pH2.3.2.7.0). Furthermore, indicator bacteria  were inoculated into Lysogeny broth , incubated at 37°C for 18 h, and the cellular density adjusted to approximately 1 × 108 CFU/mL.GLP02 and GLP06 were inoculated into MRS broth and incubated at 37°C for 18 h. The cells were removed by centrifugation at 10,000 rpm for 10 min at 4°C, and the bacterial precipitate (BP) resuspended in PBS   with 6 mm holes punched with Oxford cups: 100 μL of BS, CFS, BP, CFS pHer (IZD) . Each te2.3.3.600 and pH of the MRS were measured and used to plot the growth and acid-production curves.An inoculum of 2.0% (v/v) of each strain was cultured in MRS broth, incubated at 37°C for 48 h. At 1, 2, 3, 5, 7, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36, and 48 h, the absorbance OD2.3.4.600 absorbance was measured at 3, 6, 9, 12, 18, 24, 30, 36, and 42 h, respectively, and the growth curves were plotted.The isolated strains were added at 2% (v/v) inoculum to MRS liquid at initial pH 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, and 7.0 and incubated at 37°C. The OD2.3.5.2.3.5.1.7.0), and resuspended in PBS (pH2.5) at 37°C for 3 h. Samples were collected at 0 and 3 h after incubation and analyzed for cell counts , and resuspended in 0.3 and 0.5% bile salts  at 37°C for 4 h. At 0 and 4 h after incubation, samples were collected and CFU counts were determined.The cultures were inoculated into MRS broth, incubated at 37°C for 18 h, washed twice with PBS (pH2.3.5.2.7.0), resuspended in gastric juice, and incubated at 37°C for 1.5 h. Following this, they were centrifuged again, washed twice with PBS (pH7.0), and resuspended in intestinal fluid at 37°C for 2 h  before and after treatment, respectively.(1) 2.3.6.The strains were incubated overnight and placed in water baths at temperatures of 50°C, 60°C, 70°C, 80°C, and 90°C for 5 min . SurvivaTinitial2 and Ttreatment2 are the numbers of viable bacteria at 0 min and 5 min, respectively (log CFU/mL).(2) 2.3.7.2.3.7.1.Staphylococcus aureus (ATCC25923) served as a positive control.The cultures were incubated overnight (18 h), streaked onto blood agar containing 5% (v/v) sheep blood  and incubated for 48 h at 37°C . Staphyl2.3.7.2.Based on recommendations for evaluating the safety of probiotics, 21 antibiotics were selected for testing in the form of 6 mm paper tablets : penicillin, oxacillin, ampicillin, piperacillin, imipenem, vancomycin, streptomycin, gentamicin, amikacin, kanamycin, tetracycline, chloramphenicol, minocycline, doxycycline, cotrimoxazole, azithromycin, erythromycin, clindamycin, norfloxacin, ciprofloxacin, and levofloxacin.7.0) to obtain 0.5 McFarland turbid cultures. Antibiotic-containing paper sheets were dispensed onto MRS agar medium coated with 0.5 McFarland and cultivated for 48 h at 37°C (Colonies of the isolates were inoculated into PBS (pH at 37°C . The IZD at 37°C .2.3.8.7.0), and resuspended in PBS (pH7.0) to an OD600 of about 0.25 ± 0.05 (A1) in order to standardize. Subsequently, an equal volume of xylene and chloroform was added and mixed by vortexing for 90 s (2). The cell surface hydrophobicity was calculated using the formula:The strains were collected during the stable growth period, centrifuged at 10,000 rpm for 10 min at 4°C, washed three times with PBS  2.3.9.7.0), the OD600 was measured (A3) and the sample mixed for 15 s by vortexing (4). The autoaggregation activity was calculated using the formula:An overnight culture was washed three times with PBS  2.3.10.The adhesion ability of LAB strains was evaluated using Caco-2 cells. Caco-2 cells were cultured using minimal essential medium (MEM) supplemented with 20% (v/v) fetal bovine serum , 100 μg penicillin, and 100 μg streptomycin .7.0), and 1 mL of MEM complete culture solution without double antibiotics and serum added. The bacterial solution was washed three times with PBS (pH 7.0). The bacterial solution was resuspended in PBS (pH 7.0) and adjusted to 1 × 107 CFU/mL, and 1 mL of the bacterial suspension added to each well, followed by incubation for 1.5 h at 37°C in the presence of 5% CO2. Following this, 1.0% Triton X-100 solution  was added to the bacterial cells for 15 min (7.0), and wells without Caco-2 cells to which only bacterial solution was added served as blank controls (A5), and the number of bacteria adhering to Caco-2 cells (A6) was assessed by serially dilution of the bacterial cytosol and incubating at 37°C for 24–48 h.Caco-2 cells with good growth and 90% wall adherence were digested with 0.25% trypsin–EDTA, incubated in 24-well plates at 37°C until the cells grew to a monolayer, washed the cultured cells three times with PBS  and after treatment (log CFU/mL), respectively.(5) A2.3.11.2.3.11.1.A DPPH reagent test kit  was used to measure the DPPH radical scavenging ability of the isolated strains. The absorbance of the resulting solution was measured at 517 nm. Ascorbic acid was used as a positive control. The DPPH radical scavenging rate was calculated as follows:assay1 is the absorbance of the sample to be tested; Acontrol1 is the absorbance of a mixture of the supernatant of the isolate treatment and anhydrous ethanol; Ablank1 is the absorbance of a mixture of the extract and working solution.(6) A2.3.11.2.The ABTS radical scavenging ability of the isolated strains was measured by an ABTS reagent test kit . The absorbance of the resulting solution was measured at 405 nm. Ascorbic acid was used as a positive control. The ABTS radical scavenging rate was also calculated using Formula (6).2.4.2.4.1.9 CFU/mL), MG06 group (1010 CFU/mL), and HG06 group (1011 CFU/mL) mice were orally administered 0.2 mL of different concentrations of bacterial solution, while CK group mice were given an equal volume of saline. Every 3 days, body weight and food intake were measured, and the health status of the mice was recorded. After 27 days, the mice were fasted for 12 h and anesthetized with 1% sodium pentobarbital (50 mg/kg). Blood was collected from the abdominal aorta, and serum was collected by centrifugation  for analysis. After execution, the mice in each group were dissected and the viscera observed, and organs were collected and weighed. The organ coefficient was calculated as organ weight/body weight ×100 (Eighty Kunming mice (4-weeks-old) were randomly divided into four groups, half males and half females. LG06 group  kits . The data were measured by an enzyme marker or biochemical autoanalyzer .2.4.3.3–V4 region of the bacterial 16S rRNA gene was sequenced using the Illumina NovaSeq platform. The sequences were clustered into Operational Taxonomic Units (OTUs) with 97% similarity. All analyzes from clustering to determining α and β diversity were performed using QIIME. The data visualization web address is https://www.chiplot.online/.Before the end of the experiment, feces were randomly collected from 10 mice in each group and stored at −80°C. DNA was extracted from the feces samples, and the V2.5.The genome was sequenced on the PacBio and Nanopore platforms at Allwegene Technology Co.  and reads were assembled using Unicycler  and analyzed using the 3.3.1.E. coli, S. aureus and P. aeruginosa was significantly higher than that of CFS GLP02 (p < 0.05), but its inhibition of L. monocytogenes was significantly lower than that of CFS GLP02 (p < 0.05). BS GLP02 showed significantly more inhibitory ability on Salmonella than GLP06 (p < 0.05), while the inhibition results for other pathogenic bacteria were not significantly different (p > 0.05). Overall, the inhibitory ability of BS was significantly higher than that of CFS (p < 0.05). The results indicated that GLP02 and GLP06 had better inhibition of pathogenic bacteria. From all the strains isolated, the two most effective strains, GLP02 and GLP06, were selected for further study. 3.2.P. acidilactici . The graph shows that there was a slight fall in the survival rates of GLP02 and GLP06 at 0.3% bile salt, although GLP02 (98.84%) showed significantly higher resistance than GLP06 . However, GLP06 (90.22%) showed significantly higher resistance to 0.5% bile salt than GLP02 . The study demonstrated the good viability of GLP02 and GLP06 under both gastric and intestinal conditions, with mean viability rates of 55.32 and 54.83%, respectively. Treatment of P. acidilactici GLP06 at 50, 60, and 70°C for 5 min had little effect on its survival, but after 5 min at 80 and 90°C, the % survival of GLP02 and GLP06 decreased significantly. The higher the temperature above 70°C, the greater the damage to the bacteria, although GLP06 had better resistance than GLP02, as shown in 3.3.3.3.3.3.1.γ-hemolysis) and can be generally accepted as safe; the data are shown GLP02 and GLP06 did not present any hemolysis . The autoaggregation of GLP02 (63.97%) was significantly lower than that of GLP06 .3.3.5.p < 0.001).The two strains showed a high level of adhesion ability to Caco-2 cells . GLP06 (3.3.6.p < 0.0001) and ABTS (p < 0.05) than GLP02. The two strains showed high antioxidant ability.3.4.3.4.1.p < 0.01 or p < 0.05; We evaluated the effects of GLP06 supplementation on body weight and food intake in mice. The body weights of mice supplemented with different concentrations of GLP06 were not significantly different from those of the CK group, and the body weight of mice gradually increased during the trial ,B. In adp < 0.01; Next, we investigated how GLP06 affected organ coefficients in mice. The organ weights of the heart, liver, spleen, and kidneys were not significantly different from those of the CK group –D. It is3.4.2.p < 0.05 or p < 0.01; We also investigated how GLP06 affected blood markers in mice. The serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin (T-BIL), indirect bilirubin (I-BIL), and direct bilirubin (D-BIL) concentrations of mice supplemented with GLP06 were not statistically significantly different from those of the CK group –E. At thp < 0.01; p < 0.05; The superoxide dismutase (SOD) levels of mice in the HG06 and MG06 groups were significantly higher than those of the LG06 and CK groups  abundance between groups was not significant, but the Firmicutes/Bacteroidota in the LG06 group were significantly higher than those of the MG06 (p < 0.01) and HG06 groups , implying that the inhibitory effect of the strain may be due to the organic acids produced , and other conditions . Many stnditions . In thisnditions . Therefonditions . In thisnditions . In thisnditions . We alsoin vitro  of the probiotic improved growth performance. The thymus coefficient, a marker of immune system development  of the GLP06 strain showed the same results.Through a series of cibility . The evaelopment , was sigelopment . This exelopment . MDA canFirmicutes in the probiotic-added group and an increase in the combined abundance of Firmicutes and Bacteroidota in the MG06 group, but the differences between the groups were not significant. Interestingly, Firmicutes abundance seemed to be inversely proportional to Bacteroidota abundance, which may indicate that they occupy the same ecological niche , and increased levels of IL-10 and abundance of Muribaculaceae and Lactobacillus; the authors concluded that P. pentosaceus CECT 8330 could be a promising probiotic to reduce intestinal inflammation , γ-hemolysis, high cell surface hydrophobicity, strong self-aggregation, and good adhesion to Caco-2 cells, indicating that P. acidilactici GLP06 had excellent probiotic properties and an ideal safety profile. In vivo experiments showed that P. acidilactici GLP06 supplementation not only had no toxic effects on mice but also promoted the development of the immune system, improved resistance to oxidative stress, and increased the diversity of intestinal flora and the abundance of Lactobacillus at suitable concentrations (MG06 group). Whole-genome sequencing showed that P. acidilactici GLP06 had one chromosome and one plasmid containing 1,976 coding sequences, representing 86.12% of the genes, with no resistance genes and eight CRISPR sequences, indicating that the strain’s genome was stable and free from the risk of resistance gene transfer. However, it is necessary to further reveal its specific health benefits through in vivo experiments in dogs. In conclusion, P. acidilactici GLP06 is a promising candidate probiotic with potential future use in the companion animal health and food industries.In conclusion, in this study, a strain of The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/The animal study was reviewed and approved by Qingdao Agricultural University, Animal Science and Technology College (protocol code DKY2022003 and 2022.06.10).GL: conceptualization, writing review and editing, supervision, project administration, and funding acquisition. MZ, KL, YZ, and YL: methodology. MZ, YL, and YZ: software and formal analysis. MZ and KL: data curation. MZ: writing–original draft preparation. All authors have read and agreed to the published version of the manuscript.This study was funded by the Start-up Fund for Scientific Research of High-level Talents of Qingdao Agricultural University (1121021) and the Functional pet food research and development project (20220122) of Shandong Chongzhiyoupin Pet Food Co., Ltd. to GL the funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication.NZ was employed by Shandong Chongzhiyoupin Pet Food Co., Ltd.The remaining 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Enterobacterales in many regions. We evaluated the rapid colorimetric polymyxin B elution (RCPE) and developed its miniaturized version, RCPE microelution (RCPEm), aiming to detect polymyxins resistance among Enterobacterales.Fast and accurate detection of polymyxins resistance is necessary as they remain the last resources to treat infections caused by Carbapenem-resistant The methodologies consist of exposing the bacterial population in a solution (NP solution) where polymyxin B disks were previously eluted to obtain a concentration of 2 µg/mL for RCPE and 3 µg/mL for RCPEm.Enterobacterales were evaluated, 90 (33.7%) resistant to polymyxin B by broth microdilution. It was observed 0.6% of major error (ME) by RCPE, with a specificity of 99.4%. The miniaturized version (RCPEm) presented the same ME and specificity values, but slightly higher sensitivity (97.8% vs. 95.6%) with 2.2% of very major error (VME).Two hundred sixty-seven RCPE and RCPEm proved to be useful alternatives to determine polymyxin B susceptibility in clinical microbiology laboratories, presenting low cost, being easy to perform, and demanding short incubation time.The online version contains supplementary material available at 10.1186/s12941-023-00618-7. Enterobacterales (CRE) is recognized, by the World Health Organization (WHO), as “priority 1: critical” for the research and development of new antimicrobials [Antimicrobial resistance is a subject of major concern to public health worldwide. Carbapenem-resistant crobials –4.In these cases, polymyxins (colistin and polymyxin B) and the new combinations of β-lactams/β-lactamase inhibitors are important choices . HoweverAlthough polymyxins resistance rates remain low in some countries, there is a steady increase in others, coinciding with the increase in the frequency of CRE –13. In tThus, new methodologies better adapted to current needs have been developed. In 2016, Nordmann, Jayol & Poirel  describeIn 2021, Ngudsuntia et al.  proposedHere, we evaluated the rapid colorimetric polymyxin B elution (RCPE), which is based on Ngudsuntia and coworkers . Also, wEnterobacterales recovered from clinical specimens of patients attended in four different hospitals of Porto Alegre city, Southern Brazil, from 2015 to 2022 (supplementary table) were included. In two of these hospitals, isolates were recovered consecutively, and, in the other two, isolates were selected by convenience, being resistance to carbapenem the inclusion criteria. The study was approved by the local research ethics committee. E. coli ATCC 25922 and Morganella morganii  were used as negative (susceptible) and positive (resistant) controls, respectively. To determine polymyxin B MIC, BMD was performed and results were interpreted according to CLSI [Two hundred sixty-seven carbapenem-resistant All isolates were submitted to PBDE and RPNP. PBDE was performed as described by Cielo et al. (2020) . The pre8 CFU/mL. Results were read by visual inspections after each 1 h of incubation (35-37 °C), for up to 4 h. Isolates were considered resistant to polymyxin B when color change (orange to yellow) was evidenced in both tubes  , with so , with s8 CFU/mL. After adding bacterial suspension, the well-containing antibiotic had a final concentration of 3 µg/mL of polymyxin B. Plates were incubated and read visually each 1 h, for up to 4 h. Color change of both wells (growth control and test) from orange to yellow indicated resistance to polymyxin B  were added in 15 mL of NP solution, kept at room temperature for 30 min, and at 35–37 °C for another 4 h, in order to complete the antibiotic elution from the disk to the broth, reproducing the full incubation period of PBDE . IsolateEnterobacterales were resistant to polymyxin B, including 18 isolates intrinsically resistant  of isolates presenting borderline MICs (2 or 4 µg/mL), as shown in Fig. According to BMD, 33.7% 90/267) of 67 of EntMIC, minimum inhibitory concentration; n, number of isolates tested; PBDE, polymyxin B broth disk elution; RPNP, rapid polymyxin NP test; RCPE, rapid colorimetric polymyxin B elution; RCPEm, rapid colorimetric polymyxin B microelution; POS, positive; NEG, negative. Red numbers: false negative (very major error); Blue numbers: false positive (major error). Highlighted Lines (pink): Borderline MICs.K. pneumoniae MIC 16 µg/mL).Table S. marcescens (MIC > 64 µg/mL). On the other hand, only 13.3% of truly resistant isolates were positive after 2 h of incubation in RCPE. Indeed, most isolates (72.2%) demanded 3 h for color change. Overall, 91.0% (80/88) of true positive results in RCPEm were observed within 2 h, and only 4 isolates demanded 4 h for positive results  (supplementary table).Noteworthy, RPNP identified 98.8% (85/86) of the truly positive (resistant) isolates within 2 h of incubation. Surprisingly, 3 h was requested for one Enterobacterales, which included a considerable percentage of isolates with borderline MICs.We observed good accuracy of the alternative methodologies  in defining polymyxin B resistance in a diverse population of Enterobacterales were evaluated and our results are in accordance with these results.CBDE/PBDE had proved to be simple, easy to perform, and cheap and was endorsed by CLSI . AlthougEnterobacter spp., reaching only 25% of sensitivity. Belda-Orlowski et al. (2019) [Enterobacterales overall was reduced to 30% when evaluating only Enterobacter spp. It is well recognized that heteroresistance to polymyxins, frequently expressed by Enterobacter spp., may justify, at least partially, these findings. Our population included 15.7% (42/267) of E. cloacae complex, mostly  susceptible to polymyxin B. Of note, both E. cloacae complex resistant to polymyxin B (MIC 32 µg/mL) presented false negative results in RPNP. Therefore, it seems very clear that our number of Enterobacter spp. resistant to polymyxins was not large enough to influence the performance of the test, which could be mentioned as a limitation of our study.Since its first publication, RPNP has been extensively evaluated in several locations, exhibiting sensitivity from 91.0 to 100% and specificity from 70.0 to 100% –31. Our . (2019)  also obs8 CFU/mL). On the other hand, we performed RCPE using 300 IU polymyxin B disks to obtain a concentration of 2 µg/ml (1 disk in 15 mL of NP solution), in order to maintain the same antibiotic concentration of the methodology approved by CLSI (CBDE). Besides, instead of using 1µL loop, we chose 1 mL of an adjusted bacterial suspension (5.0 McFarland) as bacterial inoculum , aiming to improve standardization.Considering RCPE, we introduced some modifications. The version proposed elsewhere  assessedK. pneumoniae and 1 E. cloacae complex with false negative results, all with borderline MICs (4 µg/mL). Among our population, 4 isolates had false negative results, with a consequent sensitivity of 97.8% and VME of 4.4%. On the other hand, the authors of the aforementioned study found a false positive result , reaching a specificity of 99.4% and ME of 0.6%, identical to our results. Furthermore, the miniaturized version we proposed (RCPEm) had better performance with greater sensitivity (97.8% vs. 95.6%), lower VME (2.2 vs. 4.4%), and higher CA (98.9 vs. 98.1%). The reduced volume needed for miniaturized version would demand less bacterial growth to color change, which could explain the superior performance.Ngudsuntia et al. (2021)  found a Noteworthy, compared to BMD (18-24 h) and PBDE (16-20 h), RCPE and RCPEm were faster , which is an advantage that must be highlighted. Negative results were defined after 4 h of incubation, enabling a fast and efficient therapy adjustment.It should be noted that the percentage of VME observed by us is above the accepted value published by the FDA  . HoweverOne could expect that the RCPE and RCPEm would have better sensitivity than PBDE, as a color change would improve the reading of positive results. However, it was not observed by us, indicating that the major advantages of RCPE and RCPEm over PBDE are the higher specificity and the considerably reduced incubation time.RCPE and RCPEm had different final concentrations of polymyxin B, 2 and 3 µg/mL, respectively. It could be a limitation when comparing the performance of both tests, especially in a population with a high percentage of borderline MICs. However, as the false-positive result we observed with both methodologies had MIC 0.25 µg/mL, we did not consider it as an issue. Interestingly, both methodologies had excellent performance considering those isolates with borderline MICs (100% CA among this population of 27 isolates).The qualitative nature of RCPE and RCPEm could be considered a limitation of these methodologies. However, as the therapeutic window of polymyxins is very narrow, dose management is not a routine conduct in clinical practice. For this reason, results obtained by these methodologies, as well as PBDE, do not require, overall, confirmation by BMD .One could mention that a disadvantage of RCPEm would be the need of preparing NP solution with the antibiotic eluted when performing the test. To simplify the methodology, we evaluated it using a solution previously prepared and stored (4–8 °C) for up to 30 days. The pre-eluted stored and the freshly prepared solution were evaluated at the same time, in the same plate with the same bacterial inoculum, with a subset of 7 clinical isolates. The results were fully concordant (supplementary table).K. pneumoniae over other species evaluated must be recognized as a limitation of our study. However, the different origins  of isolates and the prolonged period of recovery (2017–2022) reduces, at least partially, the probability of clonal relationship among these K. pneumoniae. Besides, although in less frequency, we included 10 other species trying to evaluate some eventual species-specific interference on the performance of methodologies. Moreover, it should be noted that this distribution of species represents the epidemiology of our region.The predominance of The RCPE and RCPEm proved to be excellent alternatives for determining susceptibility to polymyxin B. Indeed, they demonstrated to be at least as accurate as those methodologies they are derived (RPNP and PBDE). Due to their lower cost, easier execution, and faster release of results compared to BMD, both methodologies could be routinely implemented in clinical laboratories. Storing the antibiotic-eluted solution may be an option, although this issue should be better evaluated. Because of the reduced volumes and lower incubation time for most isolates, RCPEm seems to adapt better to the routine of microbiology laboratories.Below is the link to the electronic supplementary material.Supplementary Material 1


R2 of 0.91, and by the use of publicly available information on bacterial richness and diversity, we identified grassland biomes as being particularly promising sites for the discovery of novel polyketides. Furthermore, a focus on acidobacterial taxa is likely to be fruitful, as these were responsible for most of the variation in biosynthetic diversity. Overall, our results highlight the importance of sampling diverse environments with high taxonomic diversity in the pursuit for novel secondary metabolites.In the search for novel drug candidates, diverse environmental microbiomes have been surveyed for their secondary metabolite biosynthesis potential, yet little is known about the biosynthetic diversity encoded by divergent microbiomes from different ecosystems, and the environmental parameters driving this diversity. Here, we used targeted amplicon sequencing of adenylation (AD) and ketosynthase (KS) domains along with 16S sequencing to delineate the unique biosynthetic potential of microbiomes from three separate habitats  exhibiting unique small spatial scale physicochemical gradients. The estimated richness of AD domains was highest in marine sediments with 656 ± 58 operational biosynthetic units (OBUs), while the KS domain richness was highest in soil microbiomes with 388 ± 67 OBUs. Microbiomes with rich and diverse bacterial communities displayed the highest PK potential across all ecosystems, and on a small spatial scale, pH and salinity were significantly, positively correlated to KS domain richness in soil and aquatic systems, respectively. Integrating our findings, we were able to predict the KS domain richness with a RMSE of 31 OBUs and a IMPORTANCE To counteract the antibiotic resistance crisis, novel anti-infective agents need to be discovered and brought to market. Microbial secondary metabolites have been important sources of inspiration for small-molecule therapeutics. However, the isolation of novel antibiotics is difficult, and the risk of rediscovery is high. With the overarching purpose of identifying promising microbiomes for discovery of novel bioactivity, we mapped out the most significant drivers of biosynthetic diversity across divergent microbiomes. We found the biosynthetic potential to be unique to individual ecosystems, and to depend on bacterial taxonomic diversity. Within systems, and on small spatial scales, pH and salinity correlated positively to the biosynthetic richness of the microbiomes, Acidobacteria representing the taxa most highly associated with biosynthetic diversity. Ultimately, understanding the key drivers of the biosynthesis potential of environmental microbiomes will allow us to focus bioprospecting efforts and facilitate the discovery of novel therapeutics. Escherichia coli or Klebsiella pneumonia were reported to be resistant to the first-line antibiotic co-trimoxazole , salinity (aquatic system), and redox potential (marine sediment system) –18. Addi–R = 0.8, −0.68, 0.77, 0.75) (H in the oxygenated surface sediments to -175 mVH in the lower layers (R = 0.61). In the aquatic system, a salinity gradient was observed across the sampling stations ranging from 0 PSU in the Skjern Å river outlet up to almost full salinity (30 PSU) in the North Sea outside the Ringkøbing Fjord estuary (R = 0.995)   . As expe7, 0.75) , verticar layers . The red estuary . Natural= 0.995) . Bacteri = 0.59) .10.1128/msystems.00724-22.1TABLE S1Table S1, XLSX file, 0.03 MB.Measured physicochemical metadata across all systems, and additionally estimated bacterial and fungal diversity measures. Download Copyright © 2023 Geers et al.2023Geers et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the P = 0.001; Bacterial and fungal communities clearly differed across systems  and bacterial (V3V4) Chao1 richness for each ecosystem. Download Copyright © 2023 Geers et al.2023Geers et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the P = 0.001), and simultaneously a strong and significant positive correlation between bacterial richness (Chao1) and pH was observed  . The fungal fraction of the soil microbiomes did not exhibit similar pH-dependent patterns .For the bacterial fraction of the soil microbiomes, the main drivers of community structure were sampling site and pH, collectively explaining 39% of the observed variation  . Other cpatterns , though P = 0.001), while the redox potential could explain an additional 8% (P = 0.005). Fungal communities exhibited similar patterns with 42% of the variation being explained by sampling site. Species richness was not correlated with any of the measured variables for bacteria or fungi    and B, w= 0.001)  and D.Comparing the OBUs from each of the 3 systems with the curated MiBIG database of BGCs encoding characterized NPs showed that the vast majority of OBUs did not represent BGCs for which a known compound has been described in all three systems . The hig10.1128/msystems.00724-22.8FIG S4FIG S4, EPS file, 1.8 MB.Relative abundance of AD OBUs (A) and KS OBUs (B), which matches BGCs with characterized compounds in MiBIG v3.1 in the 3 different systems. Download Copyright © 2023 Geers et al.2023Geers et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the In order to investigate which bacterial strains were associated with changes in biosynthetic richness, we fitted a generalized linear model with lasso regularization using the centered log-transformed 16S zOTU table to either KS or AD domain richness . In the 10.1128/msystems.00724-22.2TABLE S2Table S2, XLSX file, 0.01 MB.List of bacterial or fungal zOTUs that can explain 90% variation of KS or AD domain richness. Download Copyright © 2023 Geers et al.2023Geers et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the P < 0.05 and R > |0.5|. For both the NRP and PK biosynthesis potential, we found a significant correlation to moisture content, though positive for NRPs and negative for PKs , while the potential PK biosynthesis was negatively correlated with pH across systems . Lastly, we found strong correlations between bacterial taxonomic diversity (Chao1 and Shannon) and KS richness , suggesting that a more diverse bacterial community results in a higher PK biosynthesis potential     . Additio 0.0065) . As obse × 10−4) . While t × 10−4) .10.1128/msystems.00724-22.4TABLE S4P < 0.05 & R > |0.5|for all correlations. R and P-values are determined by Pearson correlations. Download Table S4, XLSX file, 0.01 MB.Significant linear correlations of (i) OBU richness to environmental variables and species diversity cross systems, (ii) OBU richness to environmental variables and species diversity system-specific, (iii) pH, redox potential, salinity, and cell abundances to other environmental variables system-specific, and (iv) bacterial and fungal species richness to environmental variables. Significance is determined by: adjusted Copyright © 2023 Geers et al.2023Geers et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the R2 of 0.72. With 280 ± 117 OBUs per sample, the error of the model is smaller than the standard deviation.With the ultimate goal of predicting the capacity of a microbiome using readily available, or easily quantifiable variables, we built a generalized linear model and, after stepwise variable selection, we arrived at a specific model for KS richness estimation drawing upon system type and alpha diversity measures: log(KS) ~ system + log(Chao1_V3V4) + log(Shannon_V3V4). Testing the model on a subset of data, we reached a RMSE of 48.1 and a R2 of 0.91. Additionally, we tested if the model could be further generalized by excluding the system as a variable, and instead relying only on bacterial diversity and cell abundance as predictors for PK biosynthetic richness. However, this reduced the accuracy of the model resulting in a RMSE on the test data of 69.1, and a R2 of 0.561. It was not possible to build a model with an RMSE lower than the standard deviation for AD domains. We further applied our improved PK model on the Earth Microbiome data set  were collected in sterile 50 mL Falcon tubes from 2 sites in, and around, the pristine deer park, Dyrehaven (Site 1 [S1]: 55°47'17.1′'N 12°32'51.1′'E and Site 2 [S2]: 55°48'46.3′'N 12°33'33.4′'E). S1 and S2 were situated in mixed coniferous and deciduous forests separated by 2.85 km . At eachMarine coastal sediment cores were retrieved using a Hydro-Bios 60 cm sediment corer from two sites (S4 and S5), separated by 75 m in the shallow estuarine bay area of Nivå Bay Strandenge bird sanctuary, Nivå Bay   At each 3PO4 solution for the determination of carbon content.Triplicate water samples were collected at 9 different sampling stations within, and around, the temperate estuary of Ringkøbing Fjord . Water wFor the measurement of pH, 2 g of soil from each sample was mixed with 15 mL of water (pH 7.7). The pH was then measured under continuous stirring with an ATAGO DPH-2 digital pH-meter. The pH of the water samples was measured with the same approach on site. The redox potential was measured in the sediment samples using the GR 175-BNC-L01 Greisinger ORP/Redox electrode on site. The salinity, oxygen concentration, and temperature of the water were measured using a YSI Pro 2030 sensor.Concentrations of phosphate and inorganic nitrogen compounds  were determined using segmented flow analysis . For the soil samples, 2 g of soil matrix was leached in 20 mL 2 M KCl solution overnight, shaking at 300 rpm. Subsequently, the leachate was filtered through 45 μm Minisart sterile filters (Sartorius), before the measurement, while the water samples were measured directly on the Skalar.Ion chromatography (IC) was performed using an anion-exchange column equipped with a guard column , and suppressed conductivity detection  was used to measure concentrations of fluoride, bromide, sulfate, and chloride. In order to measure concentrations of aluminum, calcium, iron, potassium, magnesium, sodium, phosphorus, sulfur, and selenium, the samples were analyzed by ICP-MS  with Yttrium and Scandium as internal standards added directly in the samples. The instrument was equipped with Platinum tipped skimmer and sample cones, a double pass Scott spray chamber operated at 2° C, and a Micromist spray chamber. All elements were analyzed in He collision mode, with a Helium flow of 5 mL/min. Surface water and extracted sediment pore water were directly measured, while soil samples were pretreated by drying (60° C for 48 h) and leaching in 5 mL deionized water for 18 h.The organic carbon content was estimated in both sediment and soil after initial drying, and subsequent measurement of loss on ignition (LOI) at 550° C. For the surface water samples, nonvolatile organic carbon (NVOC) content was determined by first bubbling nitrogen gas through the sample to eliminate the inorganic carbon. Then, sodium persulfate was added for oxidation, and the resulting carbon dioxide was measured by an infrared detector according with the Shimadzu Total Organic Carbon Analyzer TOC-Vwp with auto sampler ASI-V instructions.Bacterial abundances were determined in all samples using SYBR Gold staining and fluorescence microscopy (Olympus BX51), as previously described . Surfaceg. Based on the absorbance at 630, 645, 663, and 720 nm, the chlorophyll a (Chl a) content was calculated according to established protocols . The filters were subsequently dissolved in 3 mL aqueous acetone solution, sonicated for 20 s, and incubated at 4° C in the dark overnight. The extract was then clarified by centrifuging for 20 min at 500 × rotocols . All colApproximately 250 mg of thawed soil was transferred to a bead beating tube, and the DNA was extracted and purified using the PowerSoil kit from Qiagen according to the instructions provided by the manufacturer. The DNA was eluted twice in 50 μL elution buffer. Similarly, DNA was extracted from sediments using the PowerSoil kit, using 1000 mg of starting material, and eluting only once in 50 μL elution buffer. For surface water samples, biomass was collected by filtration of 50–250 mL of water onto 0.2 μm polycarbonate track etched filters (Whatman). The filters were subsequently submerged in 1.8 mL sucrose lysis buffer , and the DNA was extracted and purified using an established phenol-chloroform protocol .To determine the bacterial and fungal taxonomic composition in the microbiomes, we amplified the V3V4 and the ITS region using established primer pairs  , 43 taggTo assess the biosynthesis potential of the sampled microbiomes, we used an amplicon sequencing approach targeting conserved AD and KS regions, using the A3F-A7R and DegKS2F-R primer sets, as these have proven most broadly applicable . The AD The KS region was amplified in a nested PCR. In the first round, amplification was done with the primers DegKS2F –DegKS2R  , applyinAll PCR products were cleaned up using AMPure XP beads with a ratio of 1:1.8 for the ITS amplicons, 1:1.4 for the V3V4 amplicons, and 1:1.2 for the KS and AD amplicons. The DNA concentrations were determined with the Invitrogen Quibit 2.0 fluorometer HS range kit, and the samples were pooled in equimolar ratios. Sequencing was performed by Novogene using PCR free library preparation and the NovaSeq PE250 system.https://github.com/lh3/seqtk). For generating the OBUs, a combination of commands from USEARCH v.11.0.667 and Vsearch v.2.15.1 was used. First, the forward and the reverse reads were merged with an ‘N’. Subsequently, merged reads were error filtered (-fastq_maxee 5.0 accommodating the unmerged amplicons), dereplicated, and, finally, denoised using USEARCH unoise3 , dereplicated, and denoised with unoise3, generating the zOTUs. The merged and clean reads were then mapped to the zOTUs, generating the abundance table. Taxonomy was assigned using usearch –sintax with rdp_16s_v16.fa and rdp_its_v2.fa as reference databases. Chloroplasts and zOTUs consistently present in negative control samples were removed from the V3V4 zOTU table. Average number of mapped reads per sample were 69402 ± 74736 and 90726 ± 100494 for V3V4 and ITS respectively, while they were 60253 ± 63865 and 32189 ± 41163 for AD and KS. Samples with less than 3000 mapped reads for AD, V3V4, and ITS or less than 1000 mapped reads for KS were excluded from the subsequent analysis, resulting in the exclusion of 8,9,3, and 7 samples, respectively. Rarefaction was performed to the same threshold, and the sample coverage estimated at the given threshold using the coverage function from the R package entropart .10.1128/msystems.00724-22.9FIG S5FIG S5, EPS file, 2.3 MB.Rarefaction curves showing the coverage of AD, KS, V3V4, and ITS sequences and estimates of the average sample coverage (± SD) at the given cutoff (dotted line). Download Copyright © 2023 Geers et al.2023Geers et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the P-value computed using R and RStudio. Adjusted P-values were calculated using the p.adjust function in R with the Benjamini & Yekutieli correction for each dependent variable independently . This meant that on average, 49.8% of the reads per sample were retained. Subsequently, the abundances were scaled using a centered log-ratio transformation, as described previously . The modPRJNA828401.Sequencing data are available in the Sequencing Read Archive (SRA) under bioproject


Idiopathic rapid eye movement sleep behavior disorder (iRBD) represents the prodromal stage of α‐synucleinopathies. Reliable biomarkers are needed to predict phenoconversion.The aim was to derive and validate a brain glucose metabolism pattern related to phenoconversion in iRBD (iRBDconvRP) using spatial covariance analysis .18F]FDG‐PET (18F‐fluorodeoxyglucose positron emitting tomography) to investigate brain glucose metabolism at baseline. SSM‐PCA was applied to obtain the iRBDconvRP; nonconverter patients were considered as the reference group. Survival analysis and Cox regression were applied to explore prediction power.Seventy‐six consecutive iRBD patients  were enrolled in two centers and prospectively evaluated to assess phenoconversion . All patients underwent FDG‐PET pattern analysis has potential as a phenoconversion biomarker in iRBD patients. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.We derived and validated an iRBDconvRP to efficiently discriminate converter from nonconverter iRBD patients. [ The study was conducted in two centers, each one used to derive the pattern that was then validated in the other center, thus increasing the stability of the results.Using SSM‐PCA analysis, we studied FP‐CIT SPECT and by at least 2 years of follow‐up.RBD diagnosis was confirmed in both iRBD and de novo PD patients using polysomnography (PSG), according to current criteria.At baseline, all patients underwent the Movement Disorder Society Unified Parkinson's Disease Rating Scale, motor section (MDS‐UPDRS‐III), to investigate the presence of parkinsonism, the Mini Mental State Examination (MMSE), as a measure of global cognitive functioning, as well as a comprehensive neuropsychological assessment, including at least two tests for each of the main cognitive domains All patients provided written consent to the study. The local ethics committee approved the study protocol, and all participants signed an informed consent form in compliance with the Helsinki Declaration of 1975.18F]FDG‐PET to investigate brain glucose metabolism within 12 months from iRBD diagnosis. Brain [18F]FDG‐PET scans were acquired according to the guidelines of the European Association of Nuclear Medicine.All patients underwent [GE and RTV acquisition protocols are described in Supporting Information.18F]FDG‐PET images were acquired in static mode and then subjected to affine and nonlinear spatial normalization into Montreal Neurological Institute (MNI) brain space using SPM12 . All the default settings of SPM were used, and the specific[18F]FDG‐PET brain template was used as reference.All FDG‐PET and the last follow‐up visit in nonconverter patients and between the date of [18F]FDG‐PET and the date of phenoconversion in converter patients. The hazard ratio (HR) was calculated with a Cox regression, using age, sex, and site as covariates. For the iRBDconvRP, the presence of MCI and the MDS‐UPDRS‐III score were subsequently added as covariates to explore their possible influence in predicting the phenoconversion.Next, Kaplan–Meier survival analysis was performed to estimate the risk of phenoconversion from iRBD to an overt α‐synucleinopathy, using pattern expression values, categorized as below or above the threshold previously computed by the Youden index method. The survival time was set as the interval (expressed in months) between the date of : 2.5–21.4).In Cox regression analysis, iRBDconvRP significantly predicted phenoconversion . Besides iRBDconvRP expression, only MDS‐UPDRS‐III score contributed to the prediction with an HR of 1.21 .The model was significant when MCI and MDS‐UPDRS‐III were included as covariates , the result did not change significantly.r: 0.6, P < 0.001).Brain areas involved in the denovoPDRBDRP are presented in Table SP = 0.001, 95% CI: 1.81–8.83). Kaplan–Meier curves are shown in Figure SThe denovoPDRBDRP showed a good power in discriminating iRBD converters and nonconverters, with an AUC of 0.85  and significantly predicted phenoconversion , whereas the former had a HR of 1.81 .When combining the Cox regression and the denovoPDRBDRP and the iRBDconvRP, only the latter maintained a statistical significance  found by applying the SSM‐PCA to 30 iRBD patients, who phenoconverted to an overt α‐synucleinopathy (14 PD and 16 DLB), and 46 nonconverters. The iRBDconvRP significantly predicted phenoconversion from iRBD to PD or DLB over time, with a high HR.18F]FDG‐PET acquisition between the two centers.Initially, because the patients were enrolled by two different centers, two independent iRBDconvRP were derived and cross‐center validated on each other, so as to obtain a more reliable pattern. The resulting patterns were topographically similar and significantly able to predict the conversion in the validation group . It should be noted that the application of RTV‐iRBDconvRP to GE patients showed a lower HR compared with GE‐iRBDconvRP. This finding may be explained by the lower number of patients participating in the derivation of the RTV‐iRBDconvRP. Nevertheless, the RTV‐iRBDconvRP was significantly able to predict conversion in GE patients. This is an intriguing result, considering that no specific harmonization was performed in the FDG‐PET data.It is now recognized that neurodegenerative conditions, such as PD,In particular, it has been shown that the PDRP is more expressed in iRBD patients compared with healthy subjects.However, iRBD patients are highly heterogeneous,Indeed, a recent multicentric study investigated brain metabolism correlates of DLB core features, showing that the presence of RBD is associated with bilateral parieto‐occipital cortex, precuneus, and ventrolateral–frontal metabolism,2 and are likely related to a more advanced stage of the disease. Moreover, the iRBDconvRP showed a higher HR in predicting phenoconversion than the denovoPDRBDRP, as previously described and stated to be a better prediction biomarker than the PDRP.The iRBDconvRP expression was able to significantly predict phenoconversion in our group of patients, with an adjusted HR of 7.42, thus superior to the already‐known risk factors. Indeed, the clinical risk factors showed HRs of 2 to 5,18F]FDG‐PET may be one among the most accurate biomarkers for the assessment of short to medium term phenoconversion in iRBD patients, thus considered as an inclusion criterion for future disease‐modifying clinical trials. Moreover, the iRBDconvRP expression showed an inverse correlation with survival time (expressed in months and defined as the difference between [18F]FDG‐PET acquisition and phenoconversion diagnosis or last outpatient visit), highlighting its possible role as a progression biomarker. However, 90% of iRBD patients will eventually phenoconvert to the overt stage of the disease, when the follow‐up is more than 10 yearsThis result suggests that FDG‐PET longitudinal study of iRBD patients so far. Second, given the lack of a validation group in the whole cohort, we applied the LOOCV procedure to cross‐validate the results, as done in previous studies.18F]FDG‐PET equipment between the two centers. Despite these limitations, finding two similar iRBDconvRP from two different centers, without previous harmonization of the data, may even strengthen our result, suggesting the solidity of the data. Nevertheless, center belonging was used as a nuisance within the analysis. Further longitudinal studies are warranted to confirm these results and eventually to differentiate patterns predicting conversion to different α‐synucleinopathies.This study has some limitations. First, it has a relatively small sample size. However, this work is the largest [(1) Research project: A. Conception, B. Organization, C. Execution; (2) Statistical analysis: A. Design, B. Execution, C. Review and critique; (3) Manuscript preparation: A. Writing of the first draft, B. Review and critique.B.O.: 1A, 1B, 1C, 2A, 2B, 3AP.M.: 1A, 1B, 1C, 2A, 2B, 3AC.L.: 1C, 2C, 3BF.F.: 1C, 2C, 3BL.G.: 1C, 2C, 3BA.D.: 1C, 2C, 3BF.M.: 1C, 2C, 3BA.G.: 1C, 2C, 3BD.V.G.: 2C, 3BS.K.M.: 2C, 3BK.L.L.: 2C, 3BF.P.: 1C, 2C, 3BM.S.: 1C, 2C, 3BA.C.: 1C, 2C, 3BR.C.: 1C, 2C, 3BO.S.: 1C, 2C, 3BF.I.: 1C, 2C, 3BN.B.M.: 1C, 2C, 3BM.P.: 1C, 2C, 3BM.B.: 1C, 2C, 3BS.M.: 1C, 2C, 3BF.N.: 1B, 1C, 2B, 2C, 3A, 3BD.A.: 1A, 1B, 1C, 2A, 2B, 2C, 3A, 3BAPPENDIX S1. Supporting InformationClick here for additional data file.