Cutibacterium acnes and Staphylococcus epidermis. These bacteria are not only associated with inflammatory acne but also with prosthetic-implant-associated infections and wounds. Studies have hypothesised that these bacteria have a mutualistic relationship and act as a multispecies system. It is believed that these bacteria form a multispecies biofilm under various conditions and that these biofilms contribute to increased antibiotic resistance compared to single-species biofilms. This study aimed to investigate the antibacterial and wound healing potential of synthesised gold nanoparticles (AuNPs) from an endemic South African plant, Plectranthus aliciae (AuNPPAE), its major compound rosmarinic acid (AuNPRA) and a widely used antibiotic, tetracycline (AuNPTET). Synthesised gold nanoparticles were successfully formed and characterised using ultraviolet–visible spectroscopy (UV–vis), dynamic light scattering (DLS), Fourier transform infrared spectroscopy (FTIR), zeta potential , high-resolution transmission electron microscopy (HRTEM), and selected area electron diffraction (SAED), and they were investigated for stability under various biological conditions. Stable nanoparticles were formed with ζ-potentials of −18.07 ± 0.95 mV (AuNPPAE), −21.5 ± 2.66 mV (AuNPRA), and −39.83 ± 1.6 mV (AuNPTET). The average diameter of the AuNPs was 71.26 ± 0.44 nm, 29.88 ± 3.30 nm, and 132.6 ± 99.5 nm for AuNPPAE, AuNPRA, and AuNPTET, respectively. In vitro, biological studies confirmed that although no antibacterial activity or biofilm inhibition was observed for the nanoparticles tested on the multispecies C. acnes and S. epidermis systems, these samples had potential wound closure activity. Gold nanoparticles formed with rosmarinic acid significantly increased wound closure by 21.4% at 25% v/v (≈29.2 µg/mL) compared to the negative cell control and the rosmarinic acid compound at the highest concentration tested of 500 µg/mL. This study concluded that green synthesised gold nanoparticles of rosmarinic acid could potentially be used for treating wounds.Gold nanoparticles from plant extracts and their bioactive compounds to treat various maladies have become an area of interest to many researchers. Acne vulgaris is an inflammatory disease of the pilosebaceous unit caused by the opportunistic bacteria  Acne vulgaris is a disease of the pilosebaceous unit. Patients with acne vulgaris have confirmed that the disease affects their quality of life both socially and psychologically. Acne vulgaris develops when an abnormal shedding of the skin blocks the pilosebaceous unit. Overproduction of sebum in the pilosebaceous unit results in skin distention and acts as a carbon and nutrient source for acne-causing bacteria. Acne-causing bacteria proliferate in the sebum releasing various pathogenic enzymes that trigger an inflammatory response resulting in scarring and postinflammatory hyperpigmentation .Cutibacterium acnes  and Staphylococcus epidermis (aerobic) are Gram-positive bacteria that form part of the skin′s normal microbiota. These commensal bacteria are found abundantly in the skin and protect the host from pathogens. However, shifts in the external and skin environment result in dysbiosis of these opportunistic commensal bacteria. This shift allows these opportunistic bacteria to flourish, causing skin-related maladies such as acne vulgaris. Cutibacterium acnes and S. epidermidis are opportunistic bacteria that have been associated with maladies such as acne vulgaris, prosthetic-implant-associated infections, and wounds. Both C. acnes and S. epidermidis have been isolated from acne lesions either alone or in combination. It is hypothesised that these bacteria may exist in a mutually beneficial relationship and could have a combined bacterial effect that results in the formation of a multispecies biofilm under certain conditions. Biofilm formation of C. acnes and S. epidermidis contributes to antibiotic resistance observed in acne vulgaris, prosthetic-implant-associated infections, and wounds [The skin microbiome consists of various bacterial species protecting the skin and the host from the external environment and other pathogenic bacteria. d wounds ,4,5,6,7.C. acnes and S. epidermidis results from the bacteria forming a protective biofilm. The biofilm protects these bacterial communities from their external environment, making them less susceptible to antibiotics treatments than planktonic bacteria, which are much more susceptible without this protective layer. The thick polymetric extracellular matrix of the biofilm structure prevents antibiotics from inhibiting the bacteria within [The antibiotic resistance of a within ,4,8. Anta within ,9. The Wa within ,11,12,13Plectranthus aliciae (Codd) Van Jaarsv. & T.J.Edwards previously classified as Plectranthus madagascariensis (Pers.) Benth. var. aliciae Codd is an endemic South African plant. Traditionally, the Zulu and Xhosa communities use this species to treat respiratory ailments such as coughs and asthma, colds and flu, and skin-related maladies such as wounds and scabies. A study on the acetonic extract of P. aliciae confirmed that the species have antibacterial activity. Plectranthus madagascariensis displayed antibacterial activity against S. epidermidis, known to be associated with inflammatory acne and wounds. Several compounds have been isolated from Plectranthus madagascariensis and its varieties, such as P. aliciae, with antibacterial and potentially wound healing properties. One of these isolated compounds is rosmarinic acid. Rosmarinic acid has shown analgesic and anti-inflammatory activity and could potentially contribute to wound healing [ healing ,15,16,17Nanotechnology has become an area of interest as a potential solution to overcome bacterial resistance. Due to the small size of nanoparticles compared to proteins and their large surface-to-volume ratio, nanoparticles can accommodate many functional groups, making them ideal candidates for targeting resistant bacteria. Studies have shown that nanoparticles capped with various compounds can pass through the bacterial envelope and inhibit bacteria due to their size. The biologically inert nature of gold and the increased biological activity of gold nanoparticles (AuNPs) makes this metal ideal for targeting antibiotic-resistant bacteria. AuNPs capped with various antibiotics and compounds for their antibacterial activity have undergone extensive research. Various factors play a role in the antibacterial activity of AuNPs. Research studies have revealed AuNPs with diameter sizes ranging between 2 and 52 nm to have noteworthy antibacterial activity. The surface charge of the AuNPs also plays a role in antibacterial activity, with positive surface charged AuNPs interacting with the negative electrostatic charges of the bacterial cell surface, inferring antibacterial activity. Furthermore, AuNPs capped with negatively charged functional groups have shown no antibacterial activity ,18. NanoPlectranthus aliciae, rosmarinic acid, and tetracycline show similar antimicrobial inhibition of biofilm development and wound healing activity compared to that of the extract and compounds alone. The present study aimed to determine whether the gold nanoparticles synthesised using UV–vis spectroscopy is widely used to characterise AuNPs based on their surface plasmon resonance (SPR). SPR is defined as the absorption band measured through UV–vis spectroscopy due to free conduction electrons associated with AuNPs, that oscillate when exposed to light. UV–vis spectroscopy is a nondestructive method to measure the aggregation of nanoparticles in a suspension and is widely used to determine the stability of nanoparticles. Therefore, UV–vis detects changes in transmitted light brought on by light scattering because of the turbidity of a suspension. Turbidimetry is a technique widely used by researchers to measure the aggregation of nanoparticles. UV–vis is used to determine the stability of the AuNPs in various biological solutions and, depending on the UV spectra, give information on the stability, diameter, and size distribution of the nanoparticles. The stability of AuNPs in biological systems is vital to ensure optimal activity under various physiological test conditions ,20,21.Plectranthus aliciae ethanolic extract gold nanoparticles (AuNPPAE), rosmarinic acid gold nanoparticles (AuNPRA), and tetracycline gold nanoparticles (AuNPTET) in various biological solutions. The absorbance intensity of the distilled water (Aq. dest.) UV–vis spectra for AuNPPAE were around 539 nm and for AuNPRA and AuNPTET around 523 nm. Absorption peaks at low wavelengths indicate small spherical AuNP [RA could explain the small particle size observed using a dynamic light scattering (DLS) analysis  broth. BHI broth has an overall pH of 7.4 ± 0.2 at room temperature; however, AuNPPAE was stable at a pH of 7 in NaCl, an ingredient in BHI broth. The reduction in stability in BHI broth could be due to various factors that could neutralise the surface charge of the gold nanoparticles, causing aggregation. Studies have shown that glucose, an ingredient of BHI broth, could contribute to AuNP aggregation. AuNPs oxidise glucose to hydrogen peroxide and gluconic acid, causing a change in pH [RA and AuNPTET , and Dulbecco′s Modified Eagle Medium (DMEM), although an absorbance maxima shift was observed after 48 h. However, AuNPRA was unstable in various pH solutions and displayed minimal stability at a pH of 10 for up to 24 h before a shift in the absorbance maxima was observed. AuNPTET was stable for up to 72 h, whereafter the stability of the AuNPs slightly decreased. AuNPAll AuNP samples were highly stable in DMEM, which is used to maintain cell cultures for cytotoxicity and wound healing in in vitro assays . The sta−1 in all figures are due to CO2 in the atmosphere  and AuNPPAE. Strong absorption bands were observed at 3361 cm−1 and 3272 cm−1 that could be attributed to N-H stretching, 2075 cm−1 assigned to N = C = S stretching, and 1635 cm−1 and 1636 cm−1 attributed to C = C or N-H bending for PAE and AuNPPAE, respectively. Rosmarinic acid was not a major capping agent during the formation of AuNPPAE due to the nature of the functional groups of PAE that capped the AuNPs [he AuNPs ,31.RA were observed at 3302 cm−1, which could be assigned to O-H stretching and 1647 cm−1 and 1636 cm−1 assigned to C=C stretching for RA and AuNPRA, respectively. Minor peaks were observed at 1348 cm−1 and 1356 cm−1 assigned to O-H bending, 1259 cm−1 and 1253 cm−1 assigned to C-O stretching, 1152 cm−1 and 1150 cm−1 assigned to C-O stretching, and 669 cm−1 and 668 cm−1 assigned to C=C bending for RA and AuNPRA, respectively (Major absorption bands for rosmarinic acid (RA) and AuNPectively . These iTET with the FTIR spectra at 3301 cm−1 and 3304 cm−1 that could be assigned to N-H stretching 1641 cm−1 and 1635 cm−1 assigned to C = C or N-H bending. Minor peaks were observed at 1393 cm−1 and 1409 cm−1 assigned to O-H bending, 1252 cm−1 and 1255 cm−1 assigned to C-O stretching, 1161 cm−1 and 1176 cm−1 assigned to C-N stretching, 1060 cm−1 and 1065 cm−1 assigned to C-O stretching, and 669 cm−1 assigned to C = C bending for TET and AuNPTET, respectively (Major peaks were observed for tetracycline (TET) and AuNPectively . These iPAE, AuNPRA, and AuNPTET are shown in PAE with some triangular shapes  was conducted to obtain the selected area electron diffraction (SAED) patterns, measure lattice fringes, and the overall shape of the AuNPs. Due to limited sample availability, the estimated d-spacing values were calculated from the SAED pattern for all the samples compared to the crystalline structure of Au, which represented all frequently occurring d-spacings in the crystal. The HRTEM images and SAED patterns of the gold nanoparticles AuNPr shapes A. These mponents . The HRTents [RA B and AuN[RA  groups contributes to nanoparticle stabilisation through the presence of negatively charged > C = O, which cap the surface of the Au through electrostatic interactions [TET and AuNPRA were formed at high pH values of 11 and 9, respectively, which could explain their highly negative ζ-potential values. Although AuNPPAE was less stable than AuNPTET and AuNPRA, it still displayed monodispersed nanoparticles and is considered stable according to the UV–vis analysis [Zeta potential is a measure of nanoparticle surface charge and indicates the nanoparticles’ long-term stability in a suspension. All the AuNPs in the present study had a negative zeta potential ranging from −18 to −40 mV. The higher the negative value of the AuNPs, the higher the stability of the NPs, and the lesser agglomeration and precipitation can be expected. A ζ-potential in the range of −16 to −30 mV is indicative of the beginning of dispersion, and a ζ-potential between −30 and −40 indicates medium stability . The AuNle AuNPs . Based oractions ,37. The ractions . Both AuPAE, AuNPRA, and AuNPTET was 71.26 ± 0.44 nm, 29.88 ± 3.30 nm, and 132.6 ± 99.5 nm, respectively , S. epidermidis (ATCC® 35984), and a combination of these bacteria (C. acnes + S. epidermidis). Cutibacterium acnes and S. epidermidis have been associated with acne vulgaris, prosthetic-implant-associated infections, and wounds, either alone or in combination. These bacteria can form biofilms that contribute to antibiotic resistance since they act as a protective layer that prevents antibiotics from penetrating the biofilm and inhibiting the growth of the bacteria within [The antibacterial activity of the liquid AuNPs was investigated against is ATCC® 5984, andPAE and AuNPRA at their highest concentrations tested of 25% v/v . This reduction in antibacterial activity could be due to the decrease in stability in BHI broth for these AuNPs, as seen in the stability studies (TET at the highest concentration of 25% v/v (≈172.5 µg/mL) against C. acnes (ATCC® 6919) and C. acnes + S. epidermidis grown aerobically. The antibacterial bacterial activity of AuNPTET was observed at an MIC value of 0.39% v/v (≈0.67 µg/mL) against S. epidermidis (ATCC® 35984) and C. acnes + S. epidermidis grown anaerobically , 500 µg/mL against S. epidermidis (ATCC® 35984), and 500 µg/mL against C. acnes + S. epidermidis grown under anaerobic and aerobic conditions , 231.9 ± 13.2 µg/mL (SI = 2.2), 25.7 ± 5.5 µg/mL (SI = 19.4) and 147.1 ± 7.6 µg/mL (SI = 3.4) against C. acnes, S. epidermidis and C. acnes + S. epidermidis grown anaerobically and aerobically, respectively . AuNPTET prevented the development of C. acnes and S. epidermidis biofilms at IC50 values of 0.50 ± 0.049% v/v (≈0.86 ± 0.1 µg/mL) and 0.83 ± 0.013% v/v (≈1.43 ± 0.02), respectively. The inhibition of biofilm development of AuNPTET was observed for anaerobically and aerobically grown C. acnes + S. epidermidis with IC50 values of 1.98 ± 2.25% v/v (≈3.42 ± 3.9 µg/mL) and 12.47 ± 1.32% v/v (≈21.51 ± 2.3 µg/mL), respectively. A SI larger than one was observed for AuNPTET against C. acnes and aerobically grown C. acnes + S. epidermidis. However, biofilm development was not inhibited at a significantly lower concentration by AuNPTET than the tetracycline control. The HAuCl4.3H2O control (HAuCl4) showed no antibacterial activity or inhibition of biofilm development. No inhibition of biofilm development was observed for RA at the highest concentration tested of 500 µg/mL. PAE inhibited biofilm development at ICectively . Tetracyectively . HoweverPAE, AuNPRA, and AuNPTET displayed no cytotoxicity at the highest concentration tested of 25% v/v . The tetracycline compound and PAE alone displayed IC50 values of 185.4 ± 6.93 µg/mL and 65.16 ± 7.30 µg/mL, respectively. No cytotoxicity was observed for rosmarinic acid on HaCaT cells. Since no cytotoxicity was observed for the AuNPs, the samples were tested for their wound healing potential in vitro using HaCaT cells.The cytotoxicity of the respective AuNPs was tested on the human keratinocyte cell line, HaCaT. The cytotoxicity of the samples was tested to determine whether they could potentially be biocompatible with human keratinocytes considering that they would be topically applied. AuNPv/v Aq. dest. was added to seeded HaCaT cells and served as the 100% closure control since all the nanoparticles were synthesised in Aq. dest. The percentage wound closure of the AuNPs compared to the Aq. dest. control is shown in PAE displayed a significant percentage wound closure of 96.7 ± 1.0% (p < 0.001) at 25% v/v (≈777.5 µg/mL). PAE displayed a significant wound closure of 85.3 ± 7.4% at a 7.8 µg/mL concentration. Comparing the wound closure activity of PAE and AuNPPAE, no significant improvement in wound closure was observed   with a percentage wound closure of 85.9 ± 5.9% at 25% v/v (≈29.2 µg/mL). No wound closure was observed for RA at the highest concentration tested of 500 µg/mL. Therefore, the wound healing activity of rosmarinic acid was significantly increased (p < 0.01) when the AuNP was capped with the compound .P. aliciae were collected, making sure to remove hard wooden twigs. After collection, the plant material was rinsed with Aq. dest. and it was allowed to air dry for 1 h before it was dried at 40 °C in an oven for approximately 48 h or until dry. The dried material was ground with a 0.22 mm sieve using an IKA MF 10 basic grinder to a fine powder. The ground material was extracted using 99% ethanol  for 72 h on a shaker. The extracted material was filtered using vacuum filtration and Whatman® 1.0 filter paper. The extract was subjected to reduced pressure using a Buchi-R200 Rotavapor until dry. To ensure that the PAE was completely dry, it was dried to complete dryness at 40 °C for 24 h in an oven. The extract was stored at room temperature until further use. Leaves and soft twigs of 4 solution was added and allowed to react for 30 min until nanoparticles were formed (solution became red wine colour). The solution was filtered through Whatman No. 1 filter paper, and the AuNPPAE solution was stored at 2 °C until further use. The nano concentration was determined by drying 1 mL of AuNPPAE at 40 °C until dry and recording the weight of the sample (n = 3). In a 250 mL beaker, 100 mL of sterile Aq. dest. and 200 mg of PAE were heated to 90 °C for approximately 5 min. The solution was then transferred to 50 mL falcon tubes and centrifuged for 5 min at 980 rpm to remove any sedimentary particles. The supernatant was removed, and to 50 mL of the solution, 165 mg of gum arabic (GA) was added. The solution was then heated to 60 °C with constant stirring, and 8.25 mL of a 2.2 mM HAuClRA were synthesised by dissolving 7.2 mg of RA in 100 mL sterile Aq. dest. at room temperature (RT). The pH of the solution was adjusted to 9 using a 1 M NaOH solution. To the solution, 15 mL of a 2.5 mM HAuCl4 solution was added and stirred for 30 min until nanoparticles formed, indicated by a red wine colour change. The solution was filtered through Whatman No. 1 filter paper, and the formed nanoparticle solution was stored at 2 °C until further use. The nano concentration was determined by drying 1 mL of AuNPPAE at 40 °C until dry and recording the weight of the sample (n = 3). AuNPTET was synthesised by dissolving 60 mg of TET in 60 mL of sterile Aq. dest. The pH of the solution was adjusted to 11 with 1 M NaOH. With constant stirring, 40 mL of a 1 mM HAuCl4 solution was added, and the solution was left to stir at RT for 24 h. After nanoparticle formation was observed, the solution was filtered through Whatman No. 1 filter paper, and the filtrate was stored at 2 °C until further use. The nano concentration was determined by drying 1 mL of AuNPPAE at 40 °C until dry and recording the weight of the sample (n = 3). AuNPCharacterisation studies were performed as described by De Canha et al. . The forThe stability studies were conducted in brain heart infusion broth , Dulbecco’s Modified Eagle Medium , 0.5% cysteine, 0.5% BSA, 5% sodium chloride (NaCl), and sterile Aq. dest. The nanoparticles were tested in a 1:2 ratio of AuNP to the tested solution. The ultraviolet absorbance of the nanoparticles was measured at 0 h, 2 h, 24 h (1 day), 48 h (2 days), 72 h (3 days), and 168 h (7 days) at a wavelength range of 450–800 nm using a Perkin Elmer VICTOR Nivo microplate reader. The samples were stored at 37 °C between analyses to mimic physiological conditions. C. acnes (ATCC® 6919), S. epidermidis (ATCC® 35984), and a combination of C. acnes (ATCC® 6919) and S. epidermidis (ATCC® 35984) (C. acnes + S. epidermidis) under anaerobic and aerobic growth conditions. The microdilution method was followed with slight modifications [C. acnes, S. epidermidis, or C. acnes + S. epidermidis to a final concentration of 1 × 106 CFU/mL. In a 96-well plate, 100 µL of the synthesised AuNPs was serially diluted in brain heart infusion (BHI) broth with a concentration range of 0.20–25% v/v. Based on the weight determined during nanoparticle synthesis, the starting concentration of 25% v/v for each sample was ≈777.5 ± 4.3 µg/mL for AuNPPAE, ≈29.2 ± 3.8 µg/mL for AuNPRA, and ≈172.5 ± 3.5 µg/mL for AuNPTET, respectively. The sample controls PAE, and the RA concentration ranged between 3.91 and 500 µg/mL. To each well of the test samples, 100 µL of the inoculated bacteria was added. The controls included tetracycline, which served as the positive control (0.39–50 µg/mL), Aq. dest., which served as the negative control (25% v/v), BHI broth, which served as the media control, a bacterial control of each tested bacterial species alone, and a 0.4 mM HAuCl4 solution control that served as a maximum gold effect to equate for potential unreactive gold in the AuNPs. The plates were incubated for 72 h at 37 °C under anaerobic conditions for C. acnes, aerobic conditions for S. epidermidis, and both anaerobic and aerobic conditions for C. acnes + S. epidermidis. After 72 h, 20 µL of PrestoBlue® reagent  was added to all the wells and incubated for 60 min at 37 °C. The viability of the bacteria was determined visually through a colour change from blue to pink in the presence of metabolically active bacteria, and the minimum inhibitory concentration (MIC) was recorded. The antibacterial activity of the synthesised AuNPs were tested against ications ,48,49. BThe inhibitory effect of the synthesised AuNPs on biofilm development was conducted with slight modifications . The micA SI was used to determine if the samples were more selective towards inhibiting the bacteria  or bacterial development. A SI larger than one is an indication that the sample is more selective as an inhibitor of bacterial development . The SI was calculated using the following equation :Selectiv2 until a confluent monolayer formed. Trypsin-EDTA was used to detach the cells for no longer than 2 min and deactivated with fresh DMEM. The detached cells were seeded  in the centre wells of a sterile 96-well plate and incubated for 24 h at 37 °C, 5% CO2. Stock solutions of the samples were prepared in 24-well plates in DMEM, and 100 µL of the sample dilutions were transferred to the 96-well plates containing the cells. The final concentrations of the liquid AuNP samples ranged between 0.20 and 25% v/v and between 3.12 and 400 µg/mL for PAE, RA, and TET. Actinomycin D was included in the study as a positive control with a final concentration range of 0.05–3.91 × 10−4 µg/mL. A 0.4 mM HAuCl4 solution was included in the study as a maximum gold effect to equate for potential unreactive gold in the AuNPs. A 25% v/v sterile Aq. dest. to DMEM with cells control and media control without cells were also included in the experiment and served as the negative control. The plates were incubated for 72 h at 37 °C with 5% CO2. After incubation, 20 µL of PrestoBlue® reagent was added, and the plates were incubated for 2 h. The fluorescence was measured at excitation (560 nm) and emission (590 nm) wavelengths using a Perkin Elmer VICTOR Nivo microplate reader. Human keratinocytes (HaCaT) were obtained from Dr. Lester Davids from the Department of Human Biology, the University of Cape Town . The cel4 cells per well in DMEM supplemented with 100 µg/mL penicillin, 100 µg/mL streptomycin, 250 µg/mL fungizone, and 10% FBS. The plates were incubated for 24 h at 37 °C with 5% CO2 until a confluent monolayer formed. A cross was made from top to bottom and left to right using a sterile 1000 µL tip in each well. The media was carefully removed, the wells were washed once with sterile phosphate buffered saline (PBS), and 1125 µL of fresh DMEM was added. Pictures of the untreated scratched wells containing the cells were taken under a ZEISS Primovert microscope at a four-time magnification (phase 0) that served as the pre-treatment control (0 h). The samples were added to the wells of the 48-well plate to a final volume of 1500 µL and a final sample starting concentration of 25% v/v for the AuNPs and 0.5MIC for PAE, RA, and TET . The percentage wound closure was calculated using ImageJ and GraphPad Prism 4 software. The viability of the cells for each sample was determined by first removing 1300 µL of the sample from the wells and adding 20 µL of PrestoBlue® reagent to each of the wells. The fluorescence was measured using a Perkin Elmer VICTOR Nivo microplate reader (excitation: 560 nm and emission: 590 nm wavelengths).The scratch assay was conducted with slight modifications . To the  and TET . A 0.4 mThe following formula was used to determine the percentage wound closure from 0 h to 18 h where “A” is the area of the scratch : % Woundn = 3) and in three independent experiments to ensure reproducible results. The 50% inhibitory concentration (IC50) and statistical analyses were conducted using GraphPad Prism 4 software. The statistical significance of the results was determined with a one-way analysis of variance (ANOVA) and Tukey′s multiple comparison test with * p < 0.05, ** p < 0.01, and *** p < 0.001 results regarded as statistically significant.All in vitro biological experiments were performed in triplicate (P. aliciae, rosmarinic acid, and tetracycline as potential treatments for acne vulgaris, prosthetic-implant-associated infections and wounds. The study aimed to investigate the antibacterial and wound healing potential of biosynthesised AuNP of P. aliciae, rosmarinic acid, and tetracycline were successfully formed. Although the biosynthesised AuNPs had no improved antibacterial or inhibition of biofilm development, significant wound healing activity was observed for AuNPRA. The AuNPRA is potentially a safe and effective nano treatment for wounds due to its low cytotoxicity and significantly increased wound healing activity. Further studies could investigate the in vivo wound healing activity and the permeability of AuNPRA. This is the first-time report of the wound healing potential of AuNPRA, which contributes to the novelty of the study. Based on the results obtained in this study, in vivo wound healing studies will be the next step toward developing a wound healing technology of rosmarinic acid formed gold nanoparticles.Gold nanoparticles could hold the key to improved activity of plant extracts and their compounds. Gold nanoparticles from


However, the complex structure and components of corn fiber, especially hemicellulose, make it difficult to be effectively hydrolyzed into fermentable sugars through enzymatic hydrolysis. This study developed a simple and easy industrialized process without detoxification treatment for high-yield ethanol produced from corn fiber. Corn fiber was pretreated by dilute acid under the conditions optimized by Box-Behnken design (0.5% H Bioethanol, being a kind of fuel made from organic matter resulting from agriculture or forestry, is a sustainable resource with the advantages, such as cleanliness, renewable, and reduced dependence on petroleum imports . In addi2, and using the pretreated corn fiber as substrate, the ethanol concentration reached 6.9 g/L by enzymatic hydrolysis and fermentation at 2% solid content, but the conversion of hemicellulose sugar is lower than 60%. Unlike other lignocellulose, such as corn stover, hemicellulose is the most abundant component of corn fiber (about 40% of dry corn fiber weight), mainly composed of glucuronoarabinoxylan substituted by various side chains . It covein situ pretreat whole stillage containing corn fiber and recycled it to the liquefaction step, which improved the ethanol yield by 6.3% compared to the traditional process, and the cellulose conversion was 77.5%, but similarly, many inhibitors were also produced, which led to incomplete fermentation. Many literature showed that dilute acid pretreatment could effectively degrade hemicellulose of lignocellulose materials , thus thPenicillium oxalicum, which has more abundant hemicellulase activities than the cellulase from Trichoderma reesei . It was ground using an MF 10 basic Microfine grinder  with a 2.0-mm-hole diameter sieve, then stored in a sealed polyethylene bag at −20°C before use.The liquid chromatography standards, including glucose, galactose, arabinose, xylose, mannose, galacturonic acid, glucuronic acid, furfural, HMF, and acetic acid, were purchased from Sigma-Aldrich Co. LLC . Reagent grade sulfuric acid (98%), anhydrous sodium acetate, sodium hydroxide, and ethanol were obtained from Sinopharm Chemical Reagent Co. Ltd. .Penicillium oxalicum MCAX, an engineered strain in our laboratory  and 4% (w/w), respectively, according to the analytical method NREL/TP-510-42618  protocols. The extractives were quantified according to the analytical method NREL/TP-510-42619 , and the10-42618 . The sta10-42618 . The pro10-42618 . The samP. oxalicum MCAX according to the method suggested by 4)2SO4: 2, KH2PO4: 3, and MgSO4: 0.5] in 300 ml Erlenmeyer flasks for 24 h at 30°C and 200 rpm on a rotary shaker. Then, the culture was inoculated into a fermentation medium  with an inoculation ratio of 10% (v/v) and incubated at 30°C and 200 rpm for 6 days. After fermentation, the supernatant was obtained by centrifugation at 10,000 rpm for 10 min and used as crude cellulase. The hydrolytic activities of the crude cellulase were as follows: filter paper activity (FPA) 6 stocktickerFPU/ml, xylanase 783 IU/ml, arabinofuranosidase 5 IU/ml, and β-xylosidase 1 IU/ml.The cellulase used in this study was produced by 2SO4 concentration of 0.2–0.5% (w/v), and time of 10–60 min. The experiments were designed by a Box-Behnken RSM using Design-Expert version 8.0.6.1 software and are shown in Pretreatment of corn fiber with dilute sulfuric acid was performed in a laboratory-scale vertical pressure steam sterilizer . A total of 4 g of corn fiber and dilute acid solution was thoroughly mixed in 50 ml flasks with 12 ml of reaction volume. Based on preliminary experiments, the following experimental conditions were tested: temperature of 105–125°C, Hp-value was obtained by ANOVA and used for determining statistically significant. p > 0.05 indicates that the factor is not significant; p ≤ 0.05 indicates that it is significant; and p ≤ 0.01 indicates that it is very significant.For the significance analysis of different factors in the pretreatment, After pretreatment, the flasks were cooled down to room temperature. A part of the pretreated corn fiber slurries was collected to analyze the contents of furfural, HMF, formic acid, and acetic acid.The saccharification was performed at 5% (w/v) substrate concentration in 50 ml flasks with a reaction volume of 20 ml. The pretreated corn fiber slurries were first adjusted to pH 5.0 with 10 M NaOH solution, mixed well with crude cellulase solution and acetate buffer of pH 4.8 in flasks, and incubated at 48°C in a thermostat air bath shaker set at 150 rpm. The samples were taken at reaction times of 0, 12, 24, and 48 h, respectively, and 72 h to analyze the concentrations of monomeric sugars in the enzymatic hydrolysates.All experiments were performed in triplicate, and the average values are given in this study.4)2SO4, and 1.00 g/L yeast extract were added. S. cerevisiae LF2 was first inoculated into YPD medium for activation of 24 h at 30°C, then take 2 ml of inoculum, centrifuge, and transfer the yeast cells to a 50 ml Erlenmeyer flask containing 20 ml of the acclimation medium with the lowest inhibitors concentration and incubated at 30°C to the glucose content in the medium less than 90% of the initial glucose content. After that, the strain was further transferred to the next acclimation medium with a higher inhibitors’ concentration and cultured according to the procedure above until the highest inhibitors concentration. To make the yeast better adapt to the change of inhibitor concentration, the acclimation of yeast in each inhibitor concentration was repeated more than four times.The hydrolysate of corn fiber was treated with dilute acid under the optimum pretreatment conditions, which contains 4.60 g/L glucose, 3.92 g/L xylose, 0.44 g/L furfural, 1.04 g/L formic acid, and 1.62 g/L acetic acid. For acclimation of the yeast, four different acclimation media were used. One of the media consisted of hydrolysate that was not diluted. The three other media were prepared by diluting hydrolysate to a concentration of 25, 50, and 75% (v/v), respectively. In each acclimation medium, 15.0 g/L glucose, 0.40 g/L .The inoculum was prepared by growing The semi-SSF experiment was performed in a 50 ml sealed Erlenmeyer flask by a rubber plug with a needle. First, the pretreated corn fiber slurries were adjusted to pH 5.0 with 10 M NaOH, and the pre-hydrolysis was conducted at 20% (w/v) solid consistency, 48°C, pH 5.0 for 12 h using cellulase of 10 FPU/g (DM). After pre-hydrolysis, the reaction system temperature was adjusted to 30°C, and 5% (v/v) of seed was inoculated to the reaction system. Fermentation was carried out in a thermostat air bath shaker with a rotation rate of 200 rpm. The samples were taken periodically to determine the concentrations of glucose, xylose, and ethanol.pNPXase), and α-arabinofuranosidase (pNPAase) of culture supernatants were measured using a Whatman No.1 filter paper, insoluble xylan (beech), p-nitrophenyl-β-D-xylopyranoside, and p-nitrophenyl-α-L-arabinofuranoside as the substrates, respectively, according to the methods presented by p-nitrophenol (for pNPAase and pNPXase) per minute under the assay conditions.The FPA and the activities of xylanase, β-xylosidase  With an Aminex HPX-87H column  at 60°C using a mobile phase of 5 mM H5 ml/min . For theCHPLC is the concentration of sugar as determined by HPLC, mg/ml; V is the volume of the reaction system, ml; CF (conversion factor) is 0.9 for C-6 sugars and 0.88 for C-5 sugars; W is the weight of the substrate in the reaction system, g; and ContentSugar is the percentage of the polymeric sugar in corn fiber.where From batch kinetics studies, it was found that the factors affecting acid pretreatment included the type of biomass, the type of acid, acid concentration, reaction time, and reaction temperature . Among tGlucose = + 334.95 – 0.49 × Temp. + 4.69 × Time + 8.45 × Acid conc. – 9.53 × Temp. × Time – 6.38 × Temp. × Acid conc. – 2.60 × Time × Acid conc.Xylose = + 132.21 + 19.61 × Temp. + 14.86 × Time + 19.06 × Acid conc. – 0.64 × Temp. × Time + 1.19 × Temp. × Acid conc. – 0.66 × Time × Acid conc. + 1.56 × Temp.2 – 7.19 × Time 2 – 3.91 × Acid conc.2Arabinose = + 110.82 + 5.20 × Temp. + 4.97 × Time + 6.71 × Acid conc. – 4.23 × Temp. × Time −3.00 × Temp. × Acid conc. – 2.97 × Time × Acid conc. – 0.62 × Temp.2 – 4.26 × Time 2 – 2.29 × Acid conc.2Furfural = + 3.07 + 0.57 × Temp. + 0.19 × Time – 0.14 × Acid conc. – 0.24 × Temp. × Time – 7.500E-003 × Temp. × Acid conc. + 0.018 × Time × Acid conc. + 0.061 × Temp.2 – 0.014 × Time 2 – 0.39 × Acid conc.2Formic acid = + 5.30 + 0.33 × Temp. + 0.14 × Time + 0.23 × Acid conc. + 0.16 × Temp. × Time + 0.17 × Temp. × Acid conc. + 0.047 × Time × Acid conc.Acetic acid = + 8.25 + 2.90 × Temp. + 1.69 × Time + 2.65 × Acid conc. + 0.73 × Temp. × Time + 0.93 × Temp. × Acid conc. + 1.10 × Time × Acid conc.where sugars and inhibitors appear as yield (mg/g) and the variables are Temp. , Time (in min), and Acid conc. .p-values in ANOVA that the yield of glucose obtained from the enzymatic hydrolysis of pretreated corn fiber was sensitive to acid concentration (p = 0.0372 ≤ 0.05) but not to pretreatment time (p = 0.2119 > 0.05) and temperature (p = 0.8922 > 0.05), but the yield of xylose was significantly very sensitive to reaction time (p < 0.0001), temperature (p < 0.0001), and acid concentration (p < 0.0001). Initially, the increase in pretreatment temperature is in favor of the conversion of xylan to xylose in subsequent enzymatic hydrolysis, but a high pretreatment temperature led to the dehydration reaction of xylose accelerated, thus decreased xylose production but increased furfural content , time (p = 0.0014), and acid concentration (p = 0.0002).In contrast, it was found that the yields of glucose and xylose  were 10.5 and 38.3%, respectively, in the pretreatment stage, and the yields of glucose and xylose were 95.5 and 72.4% after enzymatic hydrolysis, indicating that xylan was more dissolved out in the pretreatment stage. 2SO4 and enzyme hydrolysis, including glucose of 340 mg, xylose of 171 mg, and arabinose of 117 mg, respectively, on the basis of per gram corn fiber. This amount was approximately 85.4% of the three sugars present in the corn fiber.Overall, for three main sugars in corn fiber , the highest yield of total sugars was produced by pretreatment at 125°C for 35 min using 0.5% (w/v) Hp < 0.0001), but not to acid concentration (p = 0.949 > 0.05), maybe because sulfuric acid only acts as a catalyst to provide an acidic environment. The highest furfural content of 3.93 mg/g corn fiber was found after pretreatment at 125°C for 10 min with 0.35% sulfuric acid (p < 0.0001), temperature (p < 0.0001), and acid concentration (p < 0.0001). Longer reaction time, higher reaction temperature, and acid concentration can promote acetic acid formation.Furfural and HMF were generated from xylose and glucose in the pretreatment process through a further dehydration reaction, respectively . It was ric acid . Extendiric acid , increasric acid . In addiric acid , which cric acid , and its2SO4, there was also the higher production of formic acid (5.97 mg/g corn fiber), acetic acid (14.5 mg/g corn fiber), and furfural (3.11 mg/g corn fiber), which may result in the inhibitory effect on microbial growth in subsequent ethanol fermentation. To obtain the maximum sugars while minimizing the formation of inhibitory compounds as much as possible, based on the RSM analysis  and the conditions for obtaining the highest total sugars yields , respectively, we first assessed the inhibition effect of hydrolysates on the growth of S. cerevisiae LF2 by investigating the effect on ethanol fermentation. The hydrolysates were preadjusted to pH 5.0 with 10 M NaOH solution, and S. cerevisiae LF2 was inoculated into the hydrolysates. It was shown in S. cerevisiae LF2 was obviously inhibited in the hydrolysates, in which the growth of S. cerevisiae LF2 was strongly inhibited in the hydrolysate from pretreated corn fiber at 125°C using 0.5% (w/v) H2SO4 for 35 min, and almost no ethanol was produced in the whole fermentation period. For the hydrolysate from corn fiber pretreated in optimum conditions, ethanol was just produced after about 60 h of fermentation.According to the reports from the literature, furfural concentration greater than 0.2 mg/ml or acetic acid concentration greater than 5 mg/ml could be severely toxic to the growth of revisiae . In the revisiae . To highS. cerevisiae LF2 during semi-SSF of hydrolysate, strain domestication was conducted by continuously and gradually increasing hydrolysate concentration in acclimation medium for making the S. cerevisiae LF2 adapt to this environment with inhibitors. After multiple habituated cultures, the tolerance of S. cerevisiae LF2 to inhibitors was greatly improved. The performances of the domesticated strain and parent strain were compared by cultivation in the acclimation media with the highest concentration of inhibitors, in which glucose was supplemented to 50.0 g/L in the media. As shown in vs. 18.8 g/L), and the lag period decreased from 60 to 12 h, which could meet the requirements of semi-SSF, thus, in the following experiments, the domesticated strain was directly applied to ethanol fermentation of pretreated corn fiber without pre-detoxification treatment.To shorten the lag growth period of S. cerevisiae LF2 will be further improved to decrease the lag period of strain, and the enzyme system will be modified to improve the rate of xylose conversion.Semi-simultaneous saccharification and fermentation was used to evaluate ethanol production potential using corn fiber as substrate under the best pretreatment conditions. Compared to the SSF process, a pre-hydrolysis step was first carried out prior to SSF under the optimal conditions of enzymatic hydrolysis, which help to promote enzymatic hydrolysis and liquefaction of cellulosic substrate. The pretreated corn fiber was pre-hydrolyzed with the cellulase preparation for 12 h at 48°C and pH 5.0 before yeast was inoculated. Paecilomyces variotii to remove inhibitors produced by citric acid pretreatment, and the ethanol concentration reached 70.2 g/L using semi-SSF at 25% of solid content, and ethanol production reached 0.280 g/g initial corn fiber. Although less wastewater is produced due to biological detoxification rather than water washing and overliming, high citric acid dosage (4%) and reaction temperature (165°C) during pretreatment and too-long biodetoxification as strain growth and inactivation after detoxification influenced the economy of the process. in situ pretreat whole stillage containing corn fiber. The pretreated stillage was recycled to the liquefaction step with the addition of cellulase, or hydrolyzed using cellulase and then recycled to the liquefaction step, or hydrolyzed using cellulase followed by C6/C5 sugar co-fermentation. Compared with the traditional dry milling process, the highest ethanol yield increased by 6.3%, and the conversion of cellulose reached 77.5%. However, a large number of inhibitors in the pretreatment liquid resulted in incomplete fermentation. Some results from literature about cellulosic ethanol production using corn fiber as feedstock through different pretreatment and saccharification-fermentation process are summarized in Overall, this study proposed a simple and low-cost process used to produce ethanol from corn fiber. In this process, mild pretreatment with dilute acid can enable the saccharification and fermentation process to directly be conducted without detoxification while ensuring the low loss of sugars during pretreatment, which was conducive to ensure the high ethanol yield, high final ethanol concentration (as high solid content after pretreatment), and no wastewater problem in pretreatment stage. These advantages show that this process has a good prospect of industrial application.This study developed a simple production process for cellulosic ethanol using corn fiber. In this process, an optimized mild dilute acid pretreatment process ensured the high sugar recovery and fewer inhibitor production while high enzymatic digestibility of substrate, and the mixtures of solid and hydrolysates from pretreatment were directly transported into subsequent enzymatic hydrolysis and fermentation process without detoxification treatment for achieving high-efficiency conversion of sugar to ethanol and obtaining high ethanol yield at 20% of solid content through the semi-SSF process using acclimated yeast. This process could be easily industrialized with low equipment investment, fewer process steps, and no pretreatment wastewater problem.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.YG and JZ designed the study. YG performed the experiment, analyzed the data, and wrote the manuscript. JH, NX, and HJ participated in part of the experiments. YQ revised the manuscript. JZ and XL conceived the study and edits for the manuscript. All authors contributed to the creation of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.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.


Vertical ground reaction force (vGRF), contact time and kinematics of the lower extremities were captured. The results showed that boys jumped significantly lower than adults in DJs, and both age groups presented jumping gain with increasing drop height, up to DJ125. Boys demonstrated longer total contact time, lower angular velocity and vGRF during the propulsive phase, as well as smaller knee flexion at touchdown and lower reactive strength index. vGRF in DJ75 and DJ100 was lower than in DJ125 and DJ150. The highest value for maximum knee flexion was also presented at DJ150. It is concluded that in prepubescent boys, the appropriate drop height for an effective DJ is linked to their performance in SJ and might be between 75% and 125% of their maximum SJ performance.Drop jump (DJ) performance gain with increasing drop height is well documented in adults, but there is still no clear evidence of such gain in children. This study aimed to examine the differences in DJ performance gain in male adults and prepubescent boys by comparing drop heights tailored to each individual’s performance and expressed as a percentage of their squat jump (SJ) performance. Fifteen boys (9–11 y) and 15 men (19–27 y) executed DJs from drop heights that were set at 75%, 100%, 125%, and 150% of their best performance in SJ (DJ Squat jump (SJ), countermovement jump (CMJ), and drop jump (DJ) are commonly used as tests to evaluate the power output capabilities of the lower limbs . CompariThe external load exerted on the body during a DJ is determined to a great extent by the drop height, and this defines the intensity of a DJ ,8,9. TheThe effect of fixed  drop heights on DJ performance has received much attention during the last decade in both children ,17 and aEven fewer studies are available concerning the effect of drop height on children’s jumping performance. Although the ability of children to use the SSC effectively has been confirmed in boys and girls during low impact jumps by demonstrating gain in CMJ performance compared with SJ , this waUsing common drop heights for individuals of different age groups may seem rational for extracting conclusions regarding matters of everyday life . However, the conclusion about the lack of DJ gain in children might be misleading, considering the inherent differences in body size  and, consequently, strength capacity . TherefoIndividualization is a key training principle, since adjusting the intensity to each individual’s requirements may lead to more optimal adaptations . In maleThirty males  volunteered to participate in this study. Prepubescent boys were 9–11 years old , and men were 19–27 years old . According to Tanner’s criteria, children were classified as prepubertal (Stage 1) by the same physician . Both boInitially, the anthropometric characteristics were measured . Body ma75, DJ100, DJ125, and DJ150, respectively). Individualized drop heights were attained with a precision of 1 cm by using combinations of custom-made wooden boxes  and plates (height of 1 and 3 cm).After the placement of the markers, the participants performed 3 maximal SJs by flexing slowly their knees at 90°, as measured with a manual goniometer, and maintaining this position for approximately 2 s before jumping as high as possible. The highest jump height was used for the calculation of the drop heights. The DJ test included DJs from 75%, 100%, 125%, and 150% of each participant’s maximum SJ height (DJThe DJ was initiated by stepping forward from the drop platform (without pushing or hopping) with the leg of preference . Any lanKinematic data were captured using a six-camera 3D motion analysis system , with a sampling frequency set at 100 Hz. To obtain the kinematics, 16 reflective spherical markers (14 mm diameter) were placed at anatomical bony landmarks of the lower body according to the Helen Hayes model . Vicon sData were processed offline using Matlab R2021 scripts . Jump height was estimated from the vGRF–time curve, as described in a previous study . Only thThe performance gain was calculated as presented in Equation (1) :(1)Gain Furthermore, the reactive strength index (RSI) of the lower limbs during the DJs was estimated according to Flanagan et al. , namely δθ is the joint angular displacement from touch-down to maximal knee flexion.The knee joint angle was calculated at the following time-instances: at 100 ms and 50 ms before landing and at touchdown and at maximal knee flexion during the DJs. The duration of the braking phase  and the propulsive phase  were evaluated, as well as the total contact time (instance of contact with the ground until take-off). The peak angular velocity of the knee joint during the braking and propulsion phase was evaluated. The peak vGRF was normalized to the body weight. Finally, the knee joint stiffness (k) was calculated as follows (Equation (2)) :(2)k=ΜδθSD was assessed for all dependent variables. Linear mixed-effects model analyses were conducted to determine the main effects of age group  and drop height  as well as their interaction. AGE and HEIGHT were set as fixed factors and participants as a random factor. To explore significant differences between sub-groups, pairwise Bonferroni-adjusted comparisons were performed. Effect sizes were estimated by calculating partial eta squared (η2p), classified as small (0.01–0.05), medium (0.06–0.13), and large (≥0.14). All statistical analyses were performed using the R v.4.2.1 software , and the significance level was set at α = 0.05.Mean and 75, DJ100, DJ125, and DJ150.The height of the SJ was 30.00 ± 1.89 cm and 15.85 ± 2.37 cm for men and boys, respectively. Squat jump performance provided the basis for the definition of the dropping heights for DJF = 19.2, p < 0.001, η2p = 0.41; 100 and DJ125 jump performance was significantly higher than DJ75 (p < 0.05), while DJ150 was significantly lower than DJ100 and DJ125 (p < 0.05). Drop Jump height was significantly higher in men than in boys  = 387.6, p < 0.001, η2p = 0.97). No significant interaction was detected (p > 0.05).ANOVA revealed an effect of drop height on DJ performance  = 19.6, p < 0.001, η2p = 0.41) with increasing gain values up to DJ125 (75 compared with DJ100 and DJ125 (p < 0.001), while DJ150 was significantly lower than DJ100 and DJ125 (p < 0.001). No significant difference between groups (p > 0.05) nor interaction was revealed (p > 0.05).For the gain in DJ performance compared with SJ, a significant effect of drop height was found  = 13.5, p < 0.001, η2p = 0.29) was found (75 and DJ100 differed significantly from DJ150 (p < 0.001). Boys’ vGRF values, although lower, were not statistically different (p > 0.05) from those of men. No interaction for height × age was found (p > 0.05). During the propulsion phase, a significant effect of drop height was found in vGRF  = 2.8, p < 0.05, η2p = 0.09), and boys generated lower vGRF than men  = 13.4, p < 0.005, η2p = 0.49). No interaction of height × age was found (p > 0.05).During the braking phase, a significant effect of drop height on vGRF  = 2.9, p < 0.05, η2p = 0.09). Boys presented statistically significant longer contact time than adults  = 19.3, p < 0.001, η2p = 0.58). No significant interaction was detected (p > 0.05). During the propulsion phase, a significant effect of drop height was found in contact time  = 12.9, p < 0.001, η2p = 0.31), as contact time increased significantly at DJ150 (p < 0.001). No difference between groups nor interaction of drop height × group was found (p > 0.05). The total contact time changed at different drop heights  = 3.7, p < 0.05, η2p = 0.12), and boys presented longer total contact time than men  = 8.4, p < 0.05, η2p = 0.37). No interaction of drop height × age was found for total time (p > 0.05).During the braking phase, a significant effect of drop height on contact time was revealed (p > 0.05). Neither group difference nor significant interaction was found (p > 0.05). During the propulsion phase, a significant effect of drop height was found in knee angular velocity  = 3.5, p < 0.05, η2p = 0.11), as both groups decreased their angular velocity at DJ125 compared with their angular velocity at DJ100 (p < 0.05). Boys generated lower angular velocity  = 7.9, p < 0.05, η2p = 0.36) than men at DJ100, DJ125, and DJ150 (p < 0.05). No interaction was found (p > 0.05).F = 0.8, p = 0.507, η2p = 0.03 and F = 1.3, p = 0.288, η2p = 0.04, respectively). Boys’ knee flexion values at both time instances were not different from those of men  = 0.5, p = 0.491, η2p = 0.03 and F = 1.1, p = 0.319, η2p = 0.07, respectively). No drop height × age interaction was found  = 2.1, p = 0.111, η2p = 0.07 and F = 0.9, p = 0.442, η2p = 0.03 for 100 ms and 50 ms prior the touchdown, respectively).No drop height effect was found for knee flexion at 100 ms and 50 ms before touchdown (p > 0.05). A significant interaction of drop height × age was found  = 5.4, p < 0.005, η2p = 0.16), as boys did not alter their knee flexion at touchdown in different drop heights, whilst men altered their knee flexion when dropping from DJ150. A significant age effect was revealed, as boys presented lower flexion at touchdown than adults  = 17.8, p < 0.001, η2p = 0.56) in drop heights DJ75, DJ100, and DJ125 (p < 0.001) but not in drop height DJ150 (p > 0.05).Regarding the knee flexion angle at touchdown , no effeF = 6.7, p < 0.001, η2p = 0.19; F = 60.5, p < 0.001, η2p = 0.81). A significant interaction of drop height × age was also found  = 3.4, p < 0.05, η2p = 0.11), as RSI scores at DJ150 were significantly lower than DJ75, DJ100, and DJ125 (p < 0.001) in adults but remained unchanged in boys (p > 0.05).A significant effect of drop height on RSI was found  = 2.8, p = 0.048, η2p = 0.09; p > 0.05).A significant effect of drop height on knee joint stiffness was found , lower angular velocity and vGRF during the propulsive phase, as well as less knee flexion at touchdown.In the present study, we showed that prepubescent boys jumped lower than men from all individualized drop heights, but both age groups presented DJ gain with increasing drop height, up to DJIn previous studies concerning children, no effect of drop height on jumping performance has been reported for prepubescent children ,24,30 orThe lower jumping performance of boys compared with adults is in accordance with previous studies in both prepubescent ,24 and aIn adults, we observed an increase in jumping performance when increasing drop height from 75% to 125% of SJ performance. This is in contrast to studies showing no gain in DJ performance when using drop heights from 50% to 150% of maximum CMJ height ,11. This125 and DJ150 but jump performance increased up to DJ125, it could be suggested to use 125% of SJ drop height as a safety limit for drop height in children and adults, provided the appropriate DJ technique has been adopted.Vertical ground reaction force is an important biomechanical feature during DJ  that det150. The current decreased RSI in DJ150 may be explained by the significant decrease of DJ height and the decreasing trend for total contact time during DJ150. On the other hand, in adult volleyball players, no significant effect of relative drop height on RSI was reported, although a decreasing trend for RSI was noted above the drop height of 100% CMJ [The RSI has been previously considered a crucial marker for identifying the optimal drop height, and it has been used in plyometric training as an index to control the intensity and as feedback to the participants . Further100% CMJ .150. As the dropping height increases, vertical downward velocity increases and, thus, the neuromuscular system is required to compensate for the additional load during the absorption phase by altering the power output and stiffness regulation [RSI is also highly correlated with musculotendinous stiffness . In the gulation ,55. A kegulation . Thus, tgulation  and neurgulation . Howevergulation . This sugulation . This wagulation . Howevergulation . The facThere are some limitations in the study. Although all participants were not athletes, and children followed only their typical physical education lesson, the level of physical activity that may influence performance has not been documented with a specialized questionnaire. Therefore, we cannot rule out possible variations either in jump performance or in biomechanical parameters among subjects regarding this issue. Moreover, as the participants were untrained adult and prepubescent males with no previous training experience in DJ exercises, our findings may not apply to females, athletes, or children of other maturation statuses, as they may behave differently during DJs of different—even individualized—drop heights, as previous research indicates . FurtherAs far as we know, this is the first time that DJ performance is evaluated in prepubescent boys using individualized drop heights. In our view, the results of this study support our hypothesis that individual approach in jumping tests may reveal each participant’s ability to optimally use stretch-shortening cycle, regardless the age. Additionally, this study provides new evidence of DJ performance gain with increasing height in male adults and prepubescent boys, provided that drop heights are tailored to each individual’s SJ performance. These findings offer insights with regard to more optimal and individualized drop height settings in prepubescent boys and have the potential to inform coaches and practitioners when designing plyometric programs for training, injury prevention, or rehabilitation. According to our findings, individualized drop heights based on SJ performance are suggested to be used for testing and possibly during plyometric training of prepubescent boys, as they seem to be safer than fixed drop heights. Furthermore, drop height loadings within the range from 75 to 125% of SJ performance might be more effective during plyometric training, although more research is required to elucidate this issue regarding the optimal loading and its effectiveness in children of different maturation status, training level, or sex. However, biomechanical differences between the age groups should also be considered to tackle the age-related differences in DJ performance.


LRRK2) gene harbors both rare highly damaging missense variants  and common noncoding variants  with lower effect sizes that are associated with Parkinson's disease (PD) risk.The leucine‐rich repeat kinase 2 (LRRK2 Genome‐Wide Association Study (GWAS) signal represented by rs76904798 is independently associated with PD risk from LRRK2 coding variation and whether complex linkage disequilibrium structures with p.G2019S and the 5′ noncoding haplotype account for the association of LRRK2 coding variants.This study aimed to investigate in a large meta‐analysis whether the LRRK2 coding variation in mediating disease risk and excluded carriers of relatively rare LRRK2 coding variants to assess the independence of rs76904798. We also investigated the co‐inheritance of LRRK2 coding variants with p.G2019S, rs76904798, and p.N2081D.We performed a meta‐analysis using imputed genotypes from 17,838 patients, 13,404 proxy patients, and 173,639 healthy controls of European ancestry. We excluded carriers of p.G2019S and/or rs76904798 to clarify the role of LRRK2 rs76904798 remained significantly associated with PD after excluding the carriers of relatively rare LRRK2 coding variants. LRRK2 p.R1514Q and p.N2081D were frequently co‐inherited with rs76904798, and the allele distribution of p.S1647T significantly changed among patients after removing rs76904798 carriers.LRRK2 coding variants previously related to PD  do not drive the 5′ noncoding GWAS signal. These data, however, do not preclude the independent association of the haplotype p.N551K‐p.R1398H and p.M1646T with altered disease risk. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society. This article has been contributed to by US Government employees and their work is in the public domain in the USA.These data suggest that the  LRRK2) gene has been a focus of Parkinson's disease (PD) research since the discovery that pathogenic mutations in the gene are related to autosomal‐dominant PD.LRRK2 have been shown to impact lysosomal and endocytic regulation by increasing LRRK2 recruitment to lysosomes.The leucine‐rich repeat kinase 2 , Arab‐Berber , and European ancestries .P = 1.52e‐28) upstream of LRRK2 is associated with increased PD risk, an effect that is independent of the p.G2019S mutation.Several studies have nominated LRRK2 is unknown,LRRK2 coding variation suggests that changes in the expression or splicing of LRRK2 could mediate PD risk. There is evidence that the GWAS‐nominated noncoding variation tagged by rs76904798 could affect LRRK2 expression. The allele rs76904798‐T has been associated with increased LRRK2 expression in monocytes,LRRK2 locus and determine in a significantly larger data set whether rs76904798 is independently associated with PD from LRRK2 coding variation, we performed a conditional association analysis using individual‐level genotype data from 17,838 PD patients, 13,404 proxy patients , and 173,639 healthy controls of European ancestry.Although the exact causal variant at the 5′ GWAS signal of 2 > 0.8) for p.G2019S and the 5′ noncoding variant rs76904798 were included. Quality control parameters can be found in the Supplementary Information. In total, 13 data sets were included from the International Parkinson's Disease Genomics Consortium (IPDGC), with individual‐level genotypes from 16,309 PD patients and 17,705 healthy controls of European ancestry  that was included as an independent signal on chromosome 12 (located ~82 mb upstream of LRRK2) despite slightly lower imputation quality in the Myers‐Foroud (MF)Genotype data were obtained as previously described.ry Table . Followi2 > 0.8. Quality control parameters are available in the Supplementary Information. After quality control, the case–control data set consisted of individual‐level genotypes from 1529 patients and 15,279 healthy controls, with the controls selected randomly from the pool of nonaffected, nonproxy individuals in the biobank. The proxy–control data set consisted of 13,404 proxy patients and 140,655 healthy controls , identified in a previous PD meta‐analysis,Summary statistics were generated for each study using a logistic regression model on imputed genotypes from chromosome 12, followed by Firth regression when logistic regression failed to converge. IPDGC data were adjusted for biological sex, age, and the first five PCs representing population substructure. Age at onset was used for PD cases and age at study for healthy controls, except in the Vance (dbGap phs000394) and MFWe used two methods to compare the allelic distributions of the single nucleotide polymorphisms (SNPs) provided in Table https://github.com/neurogenetics/LRRK2_conditional_v3.All codes used in this study are available at We included 15 data sets, with 13 case–control cohorts , case–control data from the UK Biobank , and proxy‐control data from the UK Biobank . Together, these sample sets comprised 17,838 PD patients, 13,404 proxy patients, and 173,639 healthy controls of European ancestry. The mean age of onset for PD in the IPDGC cohorts, age at recruitment for the UK Biobank, and percentage of female participants for each data set are reported in Table LRRK2 coding variants with a minor allele frequency (MAF) > 0.001 in all three data sets, as presented in Table In the examination of the IPDGC, UK Biobank case–control, and proxy–control data sets, we identified 10 nonsynonymous Four of these variants  have been previously associated with either decreased or increased PD risk in Europeans,LRRK2, we first verified the associations of the known pathogenic variant p.G2019S  and the 5′ noncoding variant rs76904798  in a meta‐analysis of all 15 data sets (Table P = 1.40e−07) , and all of the relatively rare LRRK2 coding variants examined in this study   (To confirm the effect of the previously identified PD GWAS loci in ts Table . We then7) Table , the PD‐.90e‐07) .LRRK2 region that reached genome‐wide significance (P < 5e‐8). The association of the 3′ intergenic variant rs190807041 disappears after conditioning on p.G2019S, and the 5′ signal driven by noncoding LRRK2 variation explains the associations of both rs76904798 and the proximal intronic variant rs1491942 with PD risk , 9679 proxy patients , and 127,254 controls  in the conditional analysis. After removing carriers of p.G2019S and rs76904798, there were no LRRK2 variants that reached genome‐wide significance. The results of the association analyses for the LRRK2 variants examined in this study are presented in Table LRRK2 p.K1423K, which is in high LD with p.N551K‐p.R1398H, and rs10847864  are presented in To better understand the role of coding variation at the P = 0.006.With this sample size, we had ~80% power to detect genotype relative risks ≥1.16 and ≥1.44 based on the MAFs of p.M1646T and p.N2081D, respectively, in the conditional analysis , p.R1398H , p.M1646T , and p.N2081D   Table –S4. Locu4) Table . We also4) Table . After orrection .LRRK2 coding variants, we calculated the percentage of carriers that were removed after excluding the carriers of p.G2019S and rs76904798 in our data sets, as shown in To further investigate the effects of excluding rs76904798 carriers on the allele distribution of LRRK2 variants examined in this study are presented in We also found significant differences in the allele distributions of p.R1514Q, p.N2081D, and p.S1647T after removing rs76904798 carriers from the IPDGC case, UK Biobank case, and proxy‐case data sets . AlthougLRRK2 locus can influence PD susceptibility. Several large GWASs and meta‐analyses have pointed to at least two independent association signals, represented by p.G2019S and 5′ noncoding variation, that reach genome‐wide significance.LRRK2 locus. Interestingly, several LRRK2 variants have been associated with other disorders, suggesting that there are shared pathological mechanisms that result from genetic changes in LRRK2. For example, LRRK2 p.N2081D has been implicated as a shared risk variant in Crohn's diseaseLRRK2 5' variation has been shown to be a modifier of progressive supranuclear palsy phenotypes.LRRK2 association with PD, we investigated the PD risk associated with LRRK2 missense variants in a large meta‐analysis of European‐ancestry individuals.It has been established that both rare and common variations at the LRRK2 missense variants , all of which passed multiple test correction. After removing carriers of the common noncoding variant rs76904798, we found that these missense variants do not pass Bonferroni correction, whereas they retained Bonferroni‐corrected significance when rs76904798 was included as a covariate in a logistic regression model. These data therefore do not exclude the possibility that the putative protective haplotype p.N551K‐p.R1398H and proposed risk factor p.M1646T are independently associated with PD from rs76904798. These variants, however, did not meet genome‐wide significance in our study despite including a very large sample size.First, we confirmed the genome‐wide associations of p.G2019S and rs76904798 and identified the potential associations of four other PD‐linked LRRK2 p.R1514Q and p.N2081D.In a recent analysis of whole‐genome sequencing data from the Accelerating Medicines Partnership‐Parkinson's Disease cohort, Bryant and colleagues found that the 5′ variant rs76904798 was associated with LRRK2 variants have been implicated in mechanisms that are relevant to PD pathogenesis. LRRK2 rs76904798 has been previously associated with increased LRRK2 expression in monocytes 19 and in human brain and iPSC‐derived microglia 21. To further investigate the other potential effects of this variant on expression, we queried the Open Targets Platform (v. 21.06) in July 2021 for eQTL data across tissue and cell types. LRRK2 expression linked to this variant was significant across multiple tissues, including artery, skin, and thyroid, as well as monocyte cells, which is concordant with previously cited literature. The most significant expression signal was from whole‐blood eQTL data sourced from eQTLgen . Increased LRRK2 expression in whole blood and monocytes is supportive of previous studies that suggest LRRK2 has a role in immune regulation and inflammation.Several LRRK2 kinase activity, typically estimated to be approximately twofold compared to wild type, has negative effects on neuronal survival.LRRK2,LRRK2 p.M1646T has also been associated with increased glucocerebrosidase activity with a larger effect than p.G2019S.LRRK2 p.R1398H has been shown to affect GTPase and Wnt signaling activity contrary to pathogenic LRRK2 mutations.Drosophila models.Previous studies of the p.G2019S mutation have shown that increased LRRK2 variant p.M2397T in several disorders. Although this variant does not appear to affect kinase activity,LRRK2 p.M2397T with PD and MSA were underpowered due to relatively small sample sizes, and further investigation in larger and diverse cohorts is warranted.Previous studies have also implicated the common LRRK2 coding variants with whole‐genome and whole‐exome sequence data shows that the imputation of these variants was highly accurate. Second, although we included a large amount of data in our meta‐analysis, removing over one‐quarter of the samples in the conditional analysis limited our statistical power to detect less‐common small‐effect (OR ~ 1.2) variants. Therefore, we cannot exclude that relatively common coding variants have a very small effect resulting in increased or decreased risk for PD. Further studies exploring the cumulative effects of common small‐effect variants could enhance our understanding of their genetic burden and should consider the complex linkage disequilibrium structure of the LRRK2 region. Third, our analysis was limited to individuals of European ancestry, so the results of this study may not extend beyond European‐ancestry populations. In‐depth studies of PD‐linked genes in diverse cohorts will help clarify the associations discussed here as well as broader disease mechanisms.We note several limitations of this study. First, our use of imputed genotype data limits the accuracy of some genotypes, though very high concordance of the LRRK2 locus and demonstrate that the 5′ LRRK2 noncoding GWAS signal represented by rs76904798 is independently associated with PD risk from LRRK2 coding variation. These coding variants are therefore unlikely to drive the LRRK2 GWAS signal in individuals of European ancestry and require additional genetic and functional studies to clarify their potential impact on disease state. Characterizing the PD susceptibility associated with LRRK2 genetic variation is critical for anticipating disease progression and response to LRRK2‐targeted therapeutics.In conclusion, here we provide insights into the relationship between coding and noncoding variation at the Concept and design: C.B., H.L.L.Statistical analysis: J.L., M.A.N., C.B., H.L.L.Contributed expertise, data, or DNA samples: X.R., R.L., M.R.C., Z.G.‐O.Drafting of the manuscript: All authorsCritical revision of the manuscript: All authorsAPPENDIX S1 Supporting InformationClick here for additional data file.Figure S1. Meta‐analysis of p.N551K in the included data sets excluding (from left to right) (1) no samples, (2) carriers of rs76904798 and p.G2019S, and (3) carriers of p.N2081D and p.G2019S.Figure S2. Meta‐analysis of p.R1398H in the included data sets excluding (from left to right) (1) no samples, (2) carriers of rs76904798 and p.G2019S, and (3) carriers of p.N2081D and p.G2019S.Figure S3. Meta‐analysis of p.M1646T in the included data sets excluding (from left to right) (1) no samples, (2) carriers of rs76904798 and p.G2019S, and (3) carriers of p.N2081D and p.G2019S.Figure S4. Meta‐analysis of p.N2081D in the included data sets excluding (from left to right) (1) no samples and (2) carriers of rs76904798 and p.G2019S.Figure S5. Meta‐analysis of p.S1647T in the included data sets excluding (from left to right) (1) no samples, (2) carriers of rs76904798 and p.G2019S, and (3) carriers of p.N2081D and p.G2019S.Figure S6. Meta‐analysis of p.M2397T in the included data sets excluding (from left to right) (1) no samples, (2) carriers of rs76904798 and p.G2019S, and (3) carriers of p.N2081D and p.G2019S.Figure S7. Meta‐analysis of (from left to right) (1) p.G2019S and (2) rs76904798 in the included data sets.Figure S8. Meta‐analysis of rs76904798 in the included data sets excluding (from left to right) (1) no samples and (2) carriers of p.N2081D and p.G2019S.Figure S9. Meta‐analysis of p.L119P in the included data sets excluding (from left to right) (1) no samples, (2) carriers of rs76904798 and p.G2019S, and (3) carriers of p.N2081D and p.G2019S.Figure S10. Meta‐analysis of p.I723V in the included data sets excluding (from left to right) (1) no samples, (2) carriers of rs76904798 and p.G2019S, and (3) carriers of p.N2081D and p.G2019S.Figure S11. Meta‐analysis of p.R1514Q in the included data sets excluding (from left to right) (1) no samples, (2) carriers of rs76904798 and p.G2019S, and (3) carriers of p.N2081D and p.G2019S.Figure S12. Meta‐analysis of p.P1542S in the included data sets excluding (from left to right) (1) no samples, (2) carriers of rs76904798 and p.G2019S, and (3) carriers of p.N2081D and p.G2019S.Figure S13. Meta‐analysis of p.K1423K in the included data sets excluding (from left to right) (1) no samples, (2) carriers of rs76904798 and p.G2019S, and (3) carriers of p.N2081D and p.G2019S.Figure S14. Meta‐analysis of rs10847864 in the included data sets excluding (from left to right) (1) no samples, (2) carriers of rs76904798 and p.G2019S, and (3) carriers of p.N2081D and p.G2019S.Figure S15. LocusZoom plot of LRRK2 association with Parkinson's disease risk conditioned on p.N2081D. The left panel shows the association signal at the LRRK2 locus in the IPDGC and UK Biobank meta‐analysis conditioned on p.N2081D, and the right panel conditions on both p.G2019S and p.N2081D. The LRRK2 variants p.N551K, p.R1398H, p.M1646T, p.G2019S, and rs76904798 are indicated by red dots.Click here for additional data file.Table S1. Overview of included data.Table S2. Imputation quality of LRRK2 variants examined in this study.Table S3. Summary statistics of LRRK2 variants after removing carriers of the specified variants.Table S4. Co‐inheritance analysis of LRRK2 variants examined in this study with p.G2019S, rs76904798, and p.N2081D.Table S5. Fisher's exact test comparing the allele distributions of LRRK2 variants among cases in the unconditioned and conditioned data sets.Table S6. Concordance of LRRK2 variants in the imputed data sets with whole‐exome sequencing data (IPDGC) and whole‐genome sequencing data (UKBIO).Table S7. Summary statistics of LRRK2 variants, including the allele counts of the specified variants as covariates.Table S8. Frequencies and allele distributions of LRRK2 variants examined in this study in the unconditioned and conditioned data sets.Click here for additional data file.


Escherichia coli associates with humans early in life and can occupy several body niches either as a commensal in the gut and vagina, or as a pathogen in the urinary tract. As such, E. coli has an arsenal of acid response mechanisms that allow it to withstand the different levels of acid stress encountered within and outside the host. Here, we report the discovery of an additional acid response mechanism that involves the deamination of l-serine to pyruvate by the conserved l-serine deaminases SdaA and SdaB. l-serine is the first amino acid to be imported in E. coli during growth in laboratory media. However, there remains a lack in knowledge as to how l-serine is utilized. Using a uropathogenic strain of E. coli, UTI89, we show that in acidified media, l-serine is brought into the cell via the SdaC transporter. We further demonstrate that deletion of the l-serine deaminases SdaA and SdaB renders E. coli susceptible to acid stress, similar to other acid stress deletion mutants. The pyruvate produced by l-serine deamination activates the pyruvate sensor BtsS, which in concert with the noncognate response regulator YpdB upregulates the putative transporter YhjX. Based on these observations, we propose that l-serine deamination constitutes another acid response mechanism in E. coli. Escherichia coli, occupies numerous environmental and host niches and encounters a range of acidic conditions in a niche-dependent manner. For example, all E. coli harbored in the gut are thought to be acquired via ingestion   , 8–10. AE. coli, there is evidence that deamination of amino acids can also serve to increase the intracellular pH. This is evident in AR2, where glutamine deamination not only provides the glutamate that is then decarboxylated (AR2_Q)  , 12 but  (AR2_Q) , 13. Herl-serine is the first amino acid consumed by E. coli when grown in complex media  is an extraintestinal pathotype of E. coli, responsible for over 75% of reported urinary tract infections  was tested via our luminescence reporter assay in acidic and neutral conditions. These experiments showed no induction of yhjX in the ΔbtsSΔypdB strain, regardless of pH in the culture media  and the isogenic ΔbtsSΔypdB (purple) containing the PyhjX luminescence reporter fusion were cultured in LB in the absence (filled shapes) or presence (open shapes) of 10 mM HCl (circles), 10 mM acetic acid (squares), 10 mM lactic acid (upside down triangles), or 1 mM pyruvic acid (diamonds). Luminescence and OD600 were measured every hour and luminescence normalized to OD600 is plotted. Graphs are representative of four biological replicates. Download FIG S2, TIF file, 0.8 MB.Copyright © 2022 Wiebe et al.2022Wiebe 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 l-serine levels in the growth medium , the SdaA or SdaB deaminases  or both deaminases (ΔsdaAΔsdaB). The induction of yhjX in these mutants was tested via luciferase reporter assays either in media in which exogenous l-serine was added  and the isogenic ΔsdaAΔsdaB (brown) strains containing the PyhjX luminescence reporter fusion were cultured in LB in the absence (filled shapes) or presence (open shapes) of 1 mM sodium pyruvate. Luminescence and OD600 were measured every hour and luminescence normalized to OD600 is plotted. Graphs are representative of three biological replicates. Download FIG S3, TIF file, 0.7 MB.Sodium pyruvate induces the Copyright © 2022 Wiebe et al.2022Wiebe 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 l-serine deamination is a component of the E. coli acid response, we reasoned that the mutant lacking the SdaA/B enzymes would display a survival defect in acidic conditions. We first determined the acid tolerance profile of UTI89, given that we have not previously tested this strain for acid sensitivity. To do this, we subcultured UTI89 in fresh, unbuffered LB (pH 7.4) for 3 h then adjusted the culture pH to 7, 6, 5, 4, 3, or 2 using HCl. We then assessed survival of UTI89 after 30 min or 2 h of exposure. As expected, wild-type UPEC survival did not get substantially affected during 30 min incubation at pH 3 but decreased by 2 logs during the 2 h of incubation . b) Graph depicts CFU/mL of UTI89, UTI89 ΔsdaAΔsdaB, and UTI89 ΔgadAΔgadB at t = 0, 30, and 120 minutes after pH of the culture was adjusted to 3 with HCl. c) Graph depicts CFU/mL of UTI89, UTI89 ΔsdaAΔsdaB, and UTI89 ΔgadAΔgadB at t = 0, 30, and 120 minutes after pH of the culture was adjusted to 2 with HCl. Download FIG S4, TIF file, 0.4 MB.a) Graph depicts survival of UTI89 in increasingly acidic conditions. For these assays, cultures were incubated for three hours, at which point an aliquot was collected for CFU enumeration before acid treatment. The remaining culture was adjusted to the indicated pH using HCl. Samples were incubated for 30 minutes and 120 minutes. Percent survival in acid is calculated as the number of CFUs in acid treatment, compared to untreated input control.  or serine importer (sdaC). For these assays, cultures were incubated for three hours, at which point an aliquot was collected for CFU enumeration before acid treatment. The remaining culture was treated with HCl to adjust the pH to three. Samples were incubated for an additional 30 minutes, after which they were plated for CFUs. Percent survival in acid is calculated as the number of CFUs in acid treatment, compared to untreated input control. Statistical analysis was performed by 1-way ANOVA with post hoc Dunnett’s multiple comparisons correction test . Download FIG S5, TIF file, 0.2 MB.Acid tolerance profile of serine deaminase and serine import mutants. Graph depicts survival in acidic conditions, compared to the wild-type strain, of mutants deleted serine deaminases  in E. coli . Each suspension was used to seed black, clear bottomed 96-well plates at 200 μL per well from and grown at 37°C with shaking. OD600 and luciferase readings were taken every hour for 8 h using a Molecular Devices SpectraMax i3 plate reader. At least 3 biological replicates were assayed.Overnight cultures were spun at 3220 × 600 of ~3.0 at 3 h), 1 mL of the culture was centrifuged at 16,000 × g for 5 min, washed in 1× PBS, serially diluted and spot-plated for CFU to determine CFU prior to acid exposure (Input sample). The pH of the remaining 4-mL culture was adjusted to a pH of 3 using 5 M HCl, and acidified cultures were incubated at 37°C, with shaking for 30 min. Following incubation, 1 mL of the acidified sample was centrifuged, washed in PBS, and plated for CFU. Percent survival was calculated by dividing the CFU/mL after acid stress by the CFU/mL of the input sample. Statistical analysis was performed by 1-way ANOVA with post hoc Dunnett’s multiple comparisons correction test.Acid tolerance assays were performed as follows: Bacteria were grown overnight as described above and diluted 1:100 in 5 mL of fresh, unbuffered LB at pH 7.4. Cultures were incubated at 37°C with shaking. When strains reached mid exponential growth phase . A total of 1 μg of DNase-treated RNA was reverse transcribed using Superscript III reverse transcriptase (Invitrogen/Thermo Fisher). cDNA was amplified in an Applied Biosystems StepOne Plus Real-Time instrument using TaqMan MGB chemistry with primers and probes listed in  of >95% . TranscrbtsSΔypdB, and ΔsdaC were grown in LB and incubated at 37°C with shaking, until cultures reached an OD600 = 0.5. Then, 1 M HCl was added to the culture to a final concentration of 10 mM (pH = 5). Cultures were incubated for another 15 min and then 1 mL of culture was collected. Cells were pelleted and supernatant was flash frozen and stored at −80°C until analyzed via Liquid Chromatography-Mass Spectrometry (LC-MS)-based metabolomics in the Vanderbilt Center for Innovative Technology (CIT). Isotopically labeled phenylalanine-D8 and biotin-D2 were added to 200 μL of culture supernatant per sample, and protein was precipitated by addition of 800 μL of ice-cold methanol followed by overnight incubation at −80°C. Precipitated proteins were pelleted by centrifugation , and supernatants were dried down in vacuo and stored at −80°C. Individual samples were reconstituted in 120 μL of reconstitution buffer  containing tryptophan-D3, pyruvate-C13, valine-D8, and inosine-4N15. A quality control (QC) sample was prepared by pooling equal volumes from each individual sample. Quality control samples were used for column conditioning, retention time alignment and to assess mass spectrometry instrument reproducibility throughout the sample set and for individual batch acceptance.UTI89, ΔLC-MS and LC-MS/MS analyses were performed on a high-resolution Q-Exactive HF hybrid quadrupole-Orbitrap mass spectrometer  equipped with a Vanquish UHPLC binary system and autosampler . Metabolite extracts were separated on ACQUITY UPLC BEH Amide HILIC 1.7 μm, 2.1 × 100 mm column  held at 30°C. Liquid chromatography was performed at a 200 μL min using solvent A  and solvent B  with a gradient length of 30 min.m/z) in negative ion mode. Full mass scan was acquired at 120K resolution with a scan rate of 3.5 Hz, automatic gain control (AGC) target of 10e6, and maximum ion injection time of 100 ms. MS/MS spectra were collected at 15K resolution, AGC target of 2e5 ions, and maximum ion injection time of 100 ms.Full MS analyses (6 μL injection volume) were acquired over 70 to 1,050 mass-to-charge ratio (m/z pairs) were deadducted and deisotoped to generate unique “features” (retention time and m/z pairs). Data were normalized to all features using Progenesis QI.The acquired raw data were imported, processed, normalized and reviewed using Progenesis QI v.3.0 . All MS and MS/MS sample runs were aligned against a QC (pooled) reference run. Unique ions (retention time and 2 fragmentation pattern) and pyruvate  was consistent with reference standards.Experimental data for measured serine  were used to quantify pyruvate in the supernatant fraction according to the manufacturer’s protocol. Fold change in pyruvate concentration was calculated by dividing the concentration of pyruvate in cells grown in acidic conditions over the concentration of pyruvate in cells grown in LB alone for each time point. Data were analyzed using 2-way ANOVA with a Dunnett’s post hoc multiple-comparison test to compare the mutants to WT at each time point.To collect samples for extracellular pyruvate quantification, strains were grown aerobically in LB to an ODStatistical analyses were performed in GraphPad Prism, using the most appropriate test as indicated in the sections above and in the results. Details of sample size, test used, error bars, and statistical significance cutoffs are presented in the text or figure legends. All experiments were performed in at least three biological replicates. Representative graphs are shown for the luminescence reporter assays. qPCR data were analyzed using 2-way ANOVA with a Sidak’s multiple-comparison test to compare individual time points. LC-MS abundance values were plotted as ArcSinh normalized values.BioRender.com.All graphical models and drawings were generated using 10.1128/mbio.02963-22.7TABLE S2Table S2, DOCX file, 0.01 MB.Strains and plasmids used in this study. Download Copyright © 2022 Wiebe et al.2022Wiebe 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 10.1128/mbio.02963-22.8DATA SET S1Data Set S1, XLSX file, 0.1 MB.Raw luminescence data associated with Copyright © 2022 Wiebe et al.2022Wiebe 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 10.1128/mbio.02963-22.9DATA SET S2Data Set S2, XLSX file, 18.7 MB.Metabolomics data output associated with Copyright © 2022 Wiebe et al.2022Wiebe 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 10.1128/mbio.02963-22.10DATA SET S3Data Set S3, XLSX file, 0.1 MB.Pyruvate quantification data associated with Copyright © 2022 Wiebe et al.2022Wiebe 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