Japanese encephalitis (JE) is inflammation and swelling of the brain caused by the JE virus (JEV), a mosquito-borne member of the Flavivirus family. There are around 68,000 JE cases worldwide each year, many of which result in permanent brain damage and death. There is no specific treatment for JE. Here we present the crystal structure of the JEV capsid protein, a potential drug target, at 1.98 Å, and compare it to other flavivirus capsid proteins. The JEV capsid has a helical secondary structure (α helixes 1–4) and a similar protein fold to the dengue virus (DENV), the West Nile virus (WNV), and the Zika virus (ZIKV) capsid proteins. It forms a homodimer by antiparallel pairing with another subunit (‘) through α-helix 1-1’, 2-2’, and 4-4’ interactions. This dimeric form is believed to be the building block of the nucleocapsid. The flexibility of the N-terminal α helix-1 allows the formation of closed and open conformations with possible functional importance. The basic C-terminal pairing of α4-4’ forms a coiled-coil-like structure, indicating possible nucleic acid binding functionality. However, a comparison with other nucleic acid interacting domains indicates that homodimerization would preclude binding. This is the first JEV capsid protein to be described and is an addition to the structural biology of the Flavivirus. The Japanese encephalitis virus is a flavivirus transmitted by Culex mosquitoes and is closely related to other serious emerging viruses, including the dengue virus (DENV), the West Nile virus (WNV), and the Zika virus (ZIKV). In severe cases, the Japanese encephalitis virus (JEV) causes inflammation and swelling of the brain, with 10–20% of patients dying and over half the survivors left with brain damage ,4,5. RecC proteins have roles, including, but not limited to, nucleocapsid dissociation and assembly. Many studies have revealed the crucial functions of the C protein in the flavivirus life cycle ,8. MutatJEV E ,20,21, NThe JEV capsid DNA (nucleotide residue 1–315) lacking the coding sequence for the hydrophobic C-terminal, which ends at the natural NS3 protease cleavage site (102 QNKR↓GGNE 109) , was cloE. coli BL21(DE3). Cells were lysed in a high salt buffer ). Protein was purified from the soluble fraction by immobilized nickel ion affinity (Ni-NTA) chromatography and dialyzed against a 25 mM Tris pH 7.6, 50 mM NaCl, 2 mM CaCl2 buffer overnight. The protein remained in this buffer throughout the following purification processes. The sample was then centrifuged at 16,000× g for 20 min at 4 °C to separate precipitation. The S-tag was cleaved by enterokinase  at 1:100 ratio enzyme to capsid protein at 4 °C overnight. Fusion tags were removed by filtration through Ni-NTA. Concentrated flow-through was subjected to gel filtration on a Superdex 75 10 × 300 mm size-exclusion chromatography column . The peak at a retention volume of 13.5 mL was concentrated and used for crystallization.The JEV capsid protein was expressed by autoinduction in terrific broth media without trace elements (Formedium) at 30 °C overnight in Purified capsid protein bands were excised from an SDS-PAGE gel and preserved in 20% ethanol. They were washed for 30 min twice with 50% acetonitrile and 0.2 M ammonium bicarbonate pH 8.9 and then dried in a rotary evaporator. The gel pieces were rehydrated in 2 M urea and 0.2 M ammonium bicarbonate pH 7.8 (Rehydration buffer RHB), containing 0.1 µg trypsin and incubated at 37 °C overnight. Excess RHB was then removed to a new 1.5 mL microfuge tube and peptides were extracted from the gel pieces with 60% acetonitrile and 0.1% trifluoroacetic acid (TFA). The total peptide extract was then concentrated to 10 µL in a rotary evaporator and then desalted using C18 (200 Å pore size silica resin) ZipTips (Milipore), according to the manufacturer’s instructions. Mass spectrometry (MS) analysis was performed using a MALDI-ToF instrument (Waters–Micromass), using a saturated solution of alpha-cyano-4 hydroxycinnaminic acid (CHCA) in 50% acetonitrile/0.1% trifluoroacetic acid. Samples were selected in the mass range of 850–2500 Da.v/v 2-propanol, 0.1 M sodium citrate tribasic dihydrate pH 4.6–6.2, 16–18% w/v polyethylene glycol (PEG) 4000 reservoir solution. The crystals were flash frozen in a reservoir solution pH 5.6, containing 25% ethylene glycol.Capsid protein at a concentration of ~6 mg/mL produced needle crystals in a 18% X-ray data were collected at a cryogenic temperature at beamline I04 at Diamond Light Source, UK. Data was processed using Xia2 . Crystalwww.pdb.org with PDB ID 5OW2.The atomic coordinates and structure factors for the JEV capsid have been deposited in the Protein Data Bank, E. coli cysteine proteases may act in a fashion similar to human Cathepsin L, which is known to cleave the C protein between the highly conserved residues Lys18 and Arg19 [Multiple JEV capsid protein species were observed on the purification of the recombinant protein indicating protein degradation. Mass spectrometry confirmed that two different size bands observed by SDS-PAGE were both N-terminally truncated the JEV capsid protein . Three fnd Arg19 .The purified JEV capsid protein, whose size was reduced to less than 15 kDa, was crystallized, and the solved structure has a visible electron density for residues 26–98. Each monomer of the JEV capsid protein is composed of four helices: α1 (amino acid 29–38), α2 (44–57), α3 (63–70), and the longest α4 (74–96), connected by short loops a–d. The As is the case for the DENV, WNV, and ZIKV capsid proteins, the JEV capsid protein is a dimer, created by anti-parallel pairing of the α1-α1’, α2-α2’, and α4-α4’ helices, connected by extensive hydrophobic interactions, hydrogen bonds, and salt bridges . The dimIt is worth noting that the capsid dimer has a coiled-coil-like structure formed by α4-α4’ helices, similar to a leucine zipper type DNA-binding protein (ZIP) a,c,d 4242. The ZThe capsid protein is known to form a spherical core enclosing the viral genome . While tThe JEV capsid gene is the least conserved flavivirus capsid encoding gene . DespiteBoth of the α2 hydrophobic regions (Leu50 and Leu54) d and theArg68, a conserved residue among the DENV, WNV, ZIKV, and JEV , locatedIn this study, we crystallized the JEV capsid at pH 4.6, 5.6, and 6.2, each in similar crystal form with identical protein conformation. The DENV capsid protein, showing a distinct open conformation, was dissolved in buffer pH 6 , while WN-terminus flexibility may relate to the RNA binding capacity observed in the WNV capsid, where the first 32 residues bind to both the 5’ and 3’ untranslated region (UTR) of the WNV mRNA . ST-148,A structural homolog search was performed by Dalilite v.3 . Beyond In addition, a capsid-RNA interaction may occur in the monomeric state because the capsid protein was isolated in a detergent-containing buffer in the study by Khromykh et al. , which mCapsid proteins form an inner shell to enclose a virus genome. They are multifunctional and essential for the virus life cycle. The JEV capsid protein has a helix-rich structure and forms a stable homodimer similar to other flaviviruses. The capsid N-terminus is unstable and the α-helix-1 is flexible, forming a closed conformation in the JEV. The α4-4’ site on the dimeric interface could be a potential viral genome RNA interaction site, due to its coiled-coil-like structure. In contrast, the monomer of the JEV capsid protein shows structural similarity to nucleic acid binding proteins. This suggests that capsid protein is highly dynamic. This is in agreement with rearrangement during virus maturation. Our findings begin to elucidate the mystery of capsid assembly and functional interaction. This understanding may provide an approach to developing treatments for flavivirus infections.


Here we present the crystal structures of GUS enzymes from human gut commensals Lactobacillus rhamnosus, Ruminococcus gnavus, and Faecalibacterium prausnitzii that possess an active site loop  analogous to that found in E. coli GUS, which processes drug substrates. We also resolve the structure of the No Loop GUS from Bacteroides dorei. We then compare the pNPG and diclofenac glucuronide processing abilities of a panel of twelve structurally diverse GUS proteins, and find that the new L1 GUS enzymes presented here process small glucuronide substrates inefficiently compared to previously characterized L1 GUS enzymes like E. coli GUS. We further demonstrate that our GUS inhibitors, which are effective against some L1 enzymes, are not potent towards all. Our findings pinpoint active site structural features necessary for the processing of drug-glucuronide substrates and the inhibition of such processing.Bacterial β-glucuronidase (GUS) enzymes cause drug toxicity by reversing Phase II glucuronidation in the gastrointestinal tract. While many human gut microbial GUS enzymes have been examined with model glucuronide substrates like  The gut microbiota has been termed both a “metabolic organ” and an “essential organ”, and it possesses a metabolic capacity that rivals that of the liver, which is critical to both anabolism and catabolism in the human host6.The gastrointestinal (GI) microbiome harbours incredible metabolic potential and is intimately connected to human physiology. Possessing 150 times more genes than are found in the human genome, the gut microbiome encodes a vast number of enzymes that function in a variety of metabolic pathways, including the biosynthesis of essential vitamins and the breakdown of complex, non-digestible polysaccharides7. However, the types of reactions performed by gut microbial enzymes are distinct from those performed by host liver enzymes. Drug metabolism enzymes in the liver transform relatively non-polar xenobiotics of low-molecular weight into molecules that are more polar and of a higher molecular weight, facilitating their excretion from the body8. Specifically, these reactions are carried out by Phase I enzymes, which introduce hydroxyl, thiol, and amine functional groups to the xenobiotic scaffold, and Phase II enzymes, which transfer glucuronide, sulphate, and glutathione moieties onto the Phase I functional groups or the xenobiotic scaffold9. In contrast, GI microbial enzymes perform hydrolytic and reductive transformations that are capable of reversing the Phase I and Phase II reactions performed by liver enzymes10. For this reason, the transformations carried out by microbial enzymes can drastically alter the pharmacological properties of xenobiotics.Like the liver, the gut microbiota are capable of transforming xenobiotics such as pharmaceuticals, environmental pollutants, and dietary compounds ingested by humans11. This process has been extensively studied in connection with the colorectal and pancreatic cancer drug irinotecan and its active and toxic metabolite, SN-3813. Prior to excretion, SN-38 is sent to the liver where uridine diphosphate glucuronosyltransferase (UGT) enzymes attach a glucuronide group to the SN-38 scaffold, converting it to the inactive metabolite SN-38-glucuronide (SN-38-G), which is non-toxic. However, upon its delivery to the GI tract, gut microbial GUS enzymes hydrolyse SN-38-G and reactivate it back into its toxic form SN-38, which causes dose limiting diarrhoea15. In a similar fashion, NSAIDs have also been shown to cause small intestinal ulcers and inflammation, presumably due to the action of GUS enzymes that convert NSAID glucuronides back into their parent forms following Phase II glucuronidation16. In previous work, we have shown in mice that inhibitors selective for bacterial GUS alleviated SN-38 dose limiting diarrhoea and reduced the number of NSAID-induced small intestinal ulcers, further suggesting that GUS enzymes give rise to undesired GI side effects by reversing Phase II glucuronidation19.Bacterial β-glucuronidase (GUS) proteins comprise one class of gut microbial enzymes that have been shown to reverse Phase II glucuronidation and, in doing so, cause the GI toxicity of several drugs20  faster than non-L1 GUS enzymes20. We also found that two selective microbial GUS inhibitors, Inhibitor 1 and UNC10201652, were potent against the L1 E. coli GUS (EcGUS) but did not inhibit the non-L1 GUS enzyme mL1 Bacteroides fragilis GUS (BfGUS)22. From these data, we hypothesized that GUS enzymes possessing a Loop 1 efficiently process drug glucuronide substrates, such as SN-38-G and NSAID glucuronides, and are susceptible to inhibition by our GUS selective inhibitors.It is apparent that GUS enzymes are capable of hydrolysing a diverse array of glucuronides, but limited information is available on the specific types of GUS enzymes that are most efficient at processing drug glucuronides. In an attempt to gain insight into the structural and functional diversity of GUS enzymes, we recently reported an atlas of 279 unique GUS enzymes identified from the stool sample catalogue in the Human Microbiome Project (HMP) that clustered into six structural groups based on their active site loops, Loop 1 (L1), Mini Loop 1 (mL1), Loop 2 (L2), Mini Loop 2 (mL2), Mini Loop 1,2 , and No Loop (NL)20 Fig. . We furtEcGUS, Eubacterium eligens GUS (EeGUS), Streptococcus agalactiae (SaGUS), Clostridium perfringens GUS (CpGUS), and Faecalibacterium prausnitzii (FpGUS) have exhibited activity with pNPG, and all have been structurally characterized, with the exception of FpGUS21. All four L1 GUS structures exhibited similar tertiary, quaternary, and active site architectures22. To determine whether any structural and functional differences exist among L1 GUS enzymes and to test our hypothesis that GUS enzymes containing a Loop 1 are the most efficient within the GUS family at processing drug glucuronides, we cloned, expressed, and purified two additional L1 GUS enzymes, Lactobacillus rhamnosus GUS (LrGUS) and Ruminococcus gnavus GUS (RgGUS). Lactobacillus rhamnosus was found to be adherent to healthy colon tissue in a patient biopsy obtained at UNC Hospitals ; thus, we chose to study a GUS from this bacterial species. Ruminococcus gnavus GUS was previously identified and examined for general biochemical properties23.To date, five L1 GUS enzymes, FpGUS, LrGUS, and RgGUS, as well as the NL Bacteroides dorei (BdGUS), and show that LrGUS and RgGUS exhibit unique active site features not previously seen in L1 GUS enzymes. We also determined the kinetic parameters kcat and Km for each L1 GUS enzyme and our panel of non-L1 GUS enzymes with the small standard substrate pNPG. Surprisingly, we found that FpGUS, LrGUS, and RgGUS exhibited catalytic efficiencies 10 to 100-fold lower than the those of the L1 GUS enzymes previously characterized. We further demonstrate that while these three L1 GUS enzymes were not inhibited by our selective GUS inhibitors, NL BdGUS was weakly inhibited, despite its lack of a Loop 1. We show that our panel of GUS enzymes differentially processed the NSAID metabolite diclofenac glucuronide (DCF-G) and that the relative cleavage rates were analogous to that observed for pNPG. Finally, we demonstrate that treating mice with diclofenac (DCF) increases GUS activity in faecal samples. These findings advance our understanding of the structure, function and inhibition of GUS enzymes. Furthermore, they suggest that the specific amino acid composition of Loop 1, as well as additional GUS structural features, likely play a role in the ability of GUS enzymes to cleave drug-glucuronides and in the efficacy of bacterial GUS inhibitors.Here we present the crystal structures of the L1 GUS enzymes 20. To gain greater insight into the specific sequence-structure-function relationships among GUS proteins, particularly those belonging to the L1 class, we generated a sequence similarity network (SSN), which groups protein sequences into clusters and facilitates the analysis of functional relationships within protein families24. We utilized the 279 GUS protein sequences identified in the Human Microbiome Project (HMP) database to construct the SSN, as well as the sequences of the L1 GUS enzymes previously characterized , and the new L1 GUS sequences RgGUS and LrGUS21.Human gut microbial GUS enzymes have been previously shown to exhibit unique structures and functionsBfGUS, L2 Bacteroides uniformis (BuGUS), nL BdGUS, mL1,2 Bacteroides ovatus (BoGUS), and L2 Parabacteroides merdae (PmGUS), clustered with GUS enzymes containing their same loop type , SaGUS (PDB: 4JKL), CpGUS (PDB: 4JKM), and EcGUS (PDB: 3LPG) have been previously determined. To further examine the structural variability of L1 GUS enzymes, we determined the crystal structures of FpGUS, LrGUS, and RgGUS , 1.7 Å rmsd, and 2.0 Å rmsd, respectively, over 576 Cα equivalent positions. The three new L1 GUS enzymes also retain the same tetramer organization compared to previously determined L1 structures, in which GUS monomers are in a “C-term-mediated” tetrameric state rather than a “square” tetrameric state, as exhibited by mL1 BfGUS (PDB: 3CMG) and discussed below  over 528 Cα positions . The second C-terminal domain of BdGUS is a member of the carbohydrate binding module (CBM) 57 family, based on malectin25. The presence of these C-terminal domains likely explains the unique quaternary arrangement of BdGUS compared to that of other L1 GUS enzymes.To further advance our understanding of GUS structure and function we also determined the crystal structure of NL GUS Fig. . Like thons Figs  and S1. nus Figs  and S2. BdGUS is highly similar to that exhibited by BuGUS, with a 2.3 Å root-mean-square deviation over 816 Cα positions  and are the most efficient of the twelve GUS enzymes at processing pNPG, with catalytic efficiencies ranging from 540 to 920 s−1 mM−1. The L1 GUS enzymes CpGUS and FpGUS demonstrated moderate pNPG processing rates, exhibiting kcat values of 57 s−1 and 58 s−1, respectively. However, FpGUS exhibited the second highest Km (2.2 mM) of all the GUS enzymes tested, resulting in a lower catalytic efficiency compared to that of EcGUS, EeGUS, SaGUS, and CpGUS. In addition, while FpGUS was previously concluded to process pNPG faster than the non-L1 GUS enzymes BfGUS and BuGUS, determination of kcat and Km values reveal that FpGUS demonstrates a lower catalytic efficiency than these two GUS enzymes20. Interestingly, the L1 GUS enzymes LrGUS and RgGUS exhibited much lower kcat values  than the five other L1 GUS enzymes as well as Km values ~10-fold higher than that of EcGUS. LrGUS and RgGUS also demonstrated lower catalytic efficiencies than those of BfGUS and BuGUS, which are mL1 and L2 GUS enzymes, respectively. These results for LrGUS and RgGUS likely reflect their unique active site features, appearing to be electrostatically and sterically occluded from processing this small molecule glucuronide substrate.The L1 GUS enzymes PmGUS and BoGUS, which are mL2 and mL1,2 GUS enzymes, respectively, are even poorer than LrGUS and RgGUS in utilizing this substrate, exhibiting the lowest pNPG processing efficiencies observed, with kcat/Km values of 3–4 orders of magnitude less than that of EcGUS. The mL2 PmGUS processed pNPG the slowest, with a kcat value of 0.088 s−1 and exhibited the highest Km value (2.40 mM). Thus, gut microbial GUS enzymes offer a range of active site architectures and activities toward a model small glucuronide substrate, likely reflecting the range of variable native substrates they likely evolved to process within the GI tract.22. We sought to assess the inhibition propensities of these inhibitors against both the L1 GUS and non-L1 GUS enzymes within our panel. To date, our inhibitors have only been tested with pNPG at pH 7.421. However, the gut pH increases from approximately 5 in the proximal duodenum to about 7.4 in the colon28. Thus, we determined IC50 values for Inhibitor 1 and UNC10201652 against each GUS at pH 6.5 and 7.5 to sample two pH values in the GI tract   the cleavage rates of the novel L1 GUS enzymes FpGUS, LrGUS, RgGUS, as well as the ten additional enzymes in our GUS panel, with the physiologically relevant glucuronide metabolite of the NSAID diclofenac, DCF-G  for pNPG -enzyme catalytic intermediate as a piperazine-linked glucuronide22. The resulting piperazine-linked glucuronide contains a positively charged piperazine amine and is predicted to form an electrostatic interaction with the catalytic acid/base glutamate in the active site  forms pi-pi stacking interactions with the UNC10201652 aromatic scaffold, which may also aid in stabilizing the inhibitor-bound complex  and the UNC10201652-bound CpGUS complex, we observed that F365 present on the Loop 1 of the adjacent EcGUS monomer likely serves as a primarily contact with Inhibitor 1, as previously described  and domains of unknown function (DUFs). These additional domains may also provide additional rationale as to why non-L1 GUS enzymes, in general, process pNPG less efficiently than L1 GUS enzymes, which do not possess CBMs or DUFs . It is also noteworthy that the kcat of the two enzymes also differ by 3-fold, something that we cannot explain using static structures and may involve distinctions in active site motion, as outlined elegantly for other enzyme systems30.As noted above, BdGUS, only GUS enzymes that do not contain a C-terminal domain are inhibited. The previously reported inhibitor-bound structures of EcGUS reveal that the selective GUS inhibitors make contacts with both the Loop 1 of the primary monomer as well as the Loop 1 of the adjacent monomer in its functional “C-term-mediated” tetrameric state  or dimeric states (e.g. BuGUS and BdGUS)  Fig. . These qion Fig. . To evalies Figs .Figure 7In summary, this work provides insight into the structural and functional diversity among GUS enzymes, specifically focusing on those of the L1 class, and advances our knowledge of the specific GUS enzymes that are capable of reactivating drug glucuronides in the gut. We have shown that not all L1 GUS enzymes efficiently process small glucuronide substrates and have provided several structural explanations to support these observations. However, those enzymes that process small substrate glucuronides well are inhibited by UNC10201652.EcGUS (P05804), EeGUS (C4Z6Z2), SaGUS (Q8E0N2), CpGUS (Q8VNV4), LrGUS (C2JTS9), RgGUS (R5TSA0), FpGUS (C7H4D2), BfGUS (Q5LIC7), BdGUS (C3R9X4), BuGUS (A0A078SUX9), BoGUS (A7LZ25), and PmGUS (A7AG62).The Uniprot accession codes for the proteins examined here are: 31. The sequences obtained from the GUS rubric were used in combination with the EFI-EST “fasta” tool to create a sequence with 282 nodes. Each node represents sequences bearing ≥90% sequence identity to each other. A BLAST E-value of 1 × 10−220 was employed.The sequence similarity network diagram of GUS enzyme sequences was generated using the online enzyme function initiative-enzyme similarity tool (EFI-EST)Lactobacillus rhamnosus and Ruminococcus gnavus were purchased from Bio Basic in the pUC57 vector. The genes were amplified by PCR and inserted into the ligation independent cloning vector (LIC) pLIC-His using the primers shown in Table LrGUS and FpGUS crystallisation, an additional 36 amino acids and 33 amino acids were added to the C-termini of the LrGUS and FpGUS proteins, respectively, using the C-term primers (Table The GUS genes from rs Table .EeGUS (−)EeLoop, EcGUS F365A, LrGUS EDD to QNN, and BdGUS (−)CBM Loop mutants were created using site-directed mutagenesis. Primers were synthesized by Integrated DNA Technologies and are shown in Table E. coli BL21 (DE3) Gold as described below.The 31. Enzyme (2.5 µM) in CD buffer containing 10 mM potassium phosphate (pH 7.4) and 100 mM potassium fluoride was loaded into a 1-mm pathlength cuvette. Using a Chirascan-plus instrument (Applied Photophysis Limited), spectra from 185 to 260 nM were recorded at 20 ± 1.0 °C. Measurements were corrected for background signal using a CD buffer sample. The melting profile of the sample (2.5 µM) was monitored at 228, 220, 225, and 218 nm for EcGUS, EeGUS, LrGUS, and BdGUS, respectively, from 20 °C to 94 °C.The protein stabilities of the WT and mutant GUS enzymes described above were determined using the Circular Dichroism method20. Expression and purification of LrGUS and RgGUS was identical to that previously described for EeGUS20. Briefly, LrGUS and RgGUS expression plasmids were transformed into BL21 DE3 Gold cells. Cells were grown in the presence of ampicillin in LB at 37 °C until the OD600 reached 0.5, at which point the temperature was reduced to 18 °C. At OD600 ~0.8, protein expression was induced by the addition of 0.1 mM isopropyl-1-thio-D-galactopyranoside (IPTG), and cells were incubated overnight. Cells were pelleted by centrifugation at 4500 × g for 20 min at 4 °C. Cell pellets were resuspended in Buffer A , DNase, lysozyme, and a Roche complete EDTA free protease inhibitor tablet. Proteins contained 6x histidine tags and were purified by Ni-column affinity chromatography and eluted with Buffer B . After Ni-column chromatography, the proteins were subjected to size-column chromatography using Buffer C . Protein eluents were then concentrated, flash frozen in liquid nitrogen, and stored at −80 °C.All GUS enzymes were expressed and purified as previously describedp-nitrophenyl-β-D-glucuronide (pNPG) was purchased as a solid (Sigma Aldrich) and resuspended in water to a concentration of 100 mM. In vitro assays were conducted in 96-well, clear bottom assay plates  at 37 °C in a 50 µL total volume. Reactions consisted of 10 µL assay buffer , 10 µL enzyme (various concentrations), and 30 µL pNPG (various concentrations) diluted in assay buffer. Product formation was measured at 410 nm using a PHERAstar Plus Microplate reader (BMG Labtech). To determine the optimal pH for SaGUS, CpGUS, LrGUS, and RgGUS, the above assay was conducted at various enzyme concentrations and 800 µM pNPG in the appropriate assay buffer where the pH ranged from 4.0 to 7.4. For assays at pH 6.0 or lower, reactions were quenched with 100 µL of 0.2 M sodium carbonate, and product formation was measured over time via absorbance at 410 nm. For reactions at pH 6.5 or above, reactions were not quenched. For CpGUS and RgGUS, pH 6.5 was selected as the optimal pH due to the ability to monitor product formation continuously at this pH. Upon determining the optimal pH for each enzyme, velocities were determined for multiple substrate and enzyme concentrations at each enzyme’s optimal pH, and the Michaelis-Menten kinetics module in SigmaPlot was used to calculate Km, kcat, and catalytic efficiency.The standard substrate RgGUS and BoGUS displayed complex substrate inhibition kinetics, and we were not able to fit these to established substrate inhibition models, including the uncompetitive substrate inhibition model, as determined in Equation et al. or Yoshino et al.27.cat and Km values for RgGUS and BoGUS were estimated by plotting velocity versus pNPG concentrations at which no inhibition was observed.Therefore, apparent kIn vitro assays were conducted at 37 °C in a 50 µL total volume. Reactions consisted of 10 µL assay buffer , 10 µL enzyme (various concentrations), and 30 µL DCF-G  diluted in assay buffer. The pH of each reaction was chosen based on the optimal pH determined for each GUS with pNPG. Reactions were quenched at 0, 1, 2, 3, 4, and 5 min with 50 µL of 25% trichloroacetic acid (TCA). For PmGUS, reactions were quenched at 0, 10, 20, 30, 40, and 50 min. After centrifugation at 13,000xg for 10 min, the resultant supernatant was subjected to UPLC analysis. The concentration of DCF-G remaining at each time point was quantified on a Waters Acquity H-class liquid chromatograph system. Samples were separated on a Waters Acquity UPLC BEH C18 column  at 40 °C. The flow rate was 0.6 mL/min, and the injection volume was 3 µL. LC conditions were set at 100% water with 0.1% formic acid (A) ramped linearly over 9.8 mins to 95% acetonitrile with 0.1% formic acid (B) and held until 10.2 mins. At 10.21 mins the gradient was switched back to 100% A and allowed to re-equilibrate until 11.25 mins. DCF-G was monitored at 280 nm. The concentration of DCF-G was determined from a standard curve (0–500 µM DCF-G in assay buffer). Control reactions were performed in which enzyme was substituted with buffer. Background hydrolysis was not observed at each pH tested. Reactions were performed in triplicate for each enzyme.Diclofenac acyl β-D-glucuronide (DCF-G) was purchased as a solid  and resuspended in DMSO to a concentration of 25 mM. ad libitum access to chow and water. Prior to treatment, faecal pellets were collected from each mouse shortly by gentle abdominal palpation and snap frozen in sterile microfuge tubes. Animals received a single ulcerogenic dose of DCF (60 mg/kg) by intraperitoneal injection, as previously described18. Twelve hours following DCF exposure, another set of faecal pellets were collected and stored as described above. To perform the assay, frozen faecal samples were rehydrated in 15× assay buffer . Bacterial cells were lysed using a Tissuelyzer II (Qiagen) for 2 min at 30 Hertz. Homogenate was sonicated for 4 min, and then clarified by centrifugation for five minutes at 13,000×g. All experimental manipulation until this point occurred at 4 °C. 5 μL of faecal slurry supernatant was used to initiate the hydrolysis reaction of 1 mM pNPG resuspended in the same buffer. Parallel reactions containing only pNPG or only buffer/faecal slurry were used as negative controls; an aliquot of each sample was heat inactivated at 95 °C and used in the assay for further background establishment. Each sample was assayed using three technical replicates. The initial velocities of the resultant progress curves of the reaction were calculated in MATLAB by linear regression, and then normalized to the total faecal protein content calculated using a standard Bradford assay.All animal studies were approved by the University of North Carolina Institutional Animal Care and Use Committee (IACUC), in accordance with the Care and Use of Laboratory Animals guidelines set by the National Institutes of Health. Twelve-week old female C57/BL6J mice were individually housed in specific pathogen-free conditions with sterile ventilator cages containing corn bedding, with In vitro inhibition of bacterial GUS enzymes by UNC10201652 was assessed as previously described22. Reactions consisted of 5 µL of GUS , 5 µL of inhibitor (various concentrations), 30 µL of pNPG , and 10 µL of assay buffer . Reactions were initiated by addition of pNPG and then incubated for 1 hour, after which the end point absorbance was determined. Due to the slow-binding nature of UNC10201652, the IC50 was determined as the inhibitor concentration that yielded a 50% reduction in the maximum absorbance of the uninhibited reaction, where percent inhibition was calculated as:Aexp is the end point absorbance at a particular inhibitor concentration, Amax is the absorbance of the uninhibited reaction, and Abg is the background absorbance the assay. Percent inhibition values were subsequently plotted against the log of inhibitor concentration and fit with a four-parameter logistic function in SigmaPlot 13.0 to determine the IC50.where In vitro inhibition of bacterial GUS enzymes by Inhibitor 1 was determined using the reaction conditions described above, but the IC50 was determined as the inhibitor concentration that yielded 50% reduction in the maximum initial velocity of the uninhibited reaction.LrGUS, RgGUS, BdGUS and FpGUS were produced via the hanging-drop vapor diffusion method. LrGUS crystals were formed by incubation of 5 mg/mL LrGUS in 17% PEG3350, 0.4 M NaCl, and 0.1 Tris HCl pH 7.4 at 20 °C. RgGUS crystals were formed by incubation of 16 mg/mL RgGUS in 1 M diammonium hydrogen citrate and 0.05 M sodium acetate pH 4.5 at room temperature. BdGUS crystals were formed by incubation of 11.2 mg/mL BdGUS in 16% PEG3350 and 0.35 M sodium citrate at 20 °C. FpGUS crystals were formed by incubation of 13 mg/mL FpGUS in 0.1 M bis-tris propane: HCl, pH 7.0 and 0.4 M magnesium formate at 20 °C. For all crystals, 15% glycerol was used as the cryoprotectant. Diffraction data for all crystals were collected at APS beamline 23-ID-D and ID-B, and data were collected at 100 K. LrGUS, RgGUS, and FpGUS were solved via molecular replacement with E. coli GUS (PDB: 3LPG) in the software Phenix. BdGUS was solved via molecular replacement with Bacteroides uniformis GUS (PDB: 5UJ6). Refinement was also performed in Phenix, with initial rounds of simulated annealing. Final coordinates and structure factors have been submitted to the RCSB and assigned accession codes 6ECA, 6EC6, 6ED2, and 6ED1 for the LrGUS, RgGUS, FpGUS, and BdGUS structures, respectively.Crystals of RgGUS, LrGUS, FpGUS, and BdGUS were analysed on a Superdex 200 size exclusion column connected to an Agilent FPLC system, Wyatt DAWN HELEOS II multi-angle light scattering instrument and a Trex refractometer. The injection volume was 50 μL. RgGUS, LrGUS, and FpGUS were assessed at 3 mg/mL, and BdGUS was assessed at 10 mg/mL in 50 mM HEPES and 150 mM NaCl pH 7.4 buffer. A flow rate of 0.5 mL/min was used. Light scattering and refractive index data were collected and analysed using Wyatt ASTRA (Ver. 6.1) software. A dn/dc value of 0.185 was used for calculations, and a band-broadening correction was applied. Almost 100% of RgGUS, LrGUS, and FpGUS eluted in single peaks with weight-average molar masses of 291.5 kDa, 284.2 kDa, and 293.0 kDa, respectively, indicating that they form stable tetramers in solution. In contrast, BdGUS eluted in a single peak with a small trailing edge with a weight-average molar mass of 206.3 kDa, indicating that it is in dimer-tetramer equilibrium with dimer being the predominant species.Supplementary Info


R1, but evidence for between-site reproducibility of R1 in small-animal MRI is lacking.Many translational MR biomarkers derive from measurements of the water proton longitudinal relaxation rate R1 repeatability and multi-site reproducibility in phantoms for preclinical MRI.To assess R1 was measured by saturation recovery in 2% agarose phantoms with five nickel chloride concentrations in 12 magnets at 5 field strengths in 11 centres on two different occasions within 1–13 days. R1 was analysed in three different regions of interest, giving 360 measurements in total. Root-mean-square repeatability and reproducibility coefficients of variation (CoV) were calculated. Propagation of reproducibility errors into 21 translational MR measurements and biomarkers was estimated. Relaxivities were calculated. Dynamic signal stability was also measured.N = 180 regions of interest) was 2.34% and for between-centre reproducibility (N = 9 centres) was 1.43%. Mostly, these do not propagate to biologically significant between-centre error, although a few R1-based MR biomarkers were found to be quite sensitive even to such small errors in R1, notably in myocardial fibrosis, in white matter, and in oxygen-enhanced MRI. The relaxivity of aqueous Ni2+ in 2% agarose varied between 0.66 s−1 mM−1 at 3 T and 0.94 s−1 mM−1 at 11.7T.CoV for day-to-day repeatability (R1-based MR biomarkers measured preclinically, between-centre propagation of errors arising from intrinsic equipment irreproducibility should in most cases be small. However, in a few specific cases exceptional efforts might be required to ensure R1-reproducibility.While several factors affect the reproducibility of  Errors in R1  measure the temperature of the cucumber flesh in several places and verify thermal equilibrium has been reached.” The temperature of the cucumber flesh around the phantom was measured before and after each acquisition. The entire protocol was run in each centre on two separate days, mean 2.7 days apart (range 1–13).Centres were asked to measure T1 saturation-recovery measurement method “T1map_RARE protocol” (Rat/Head/Relaxometry) was invoked. All images were coronal with 58 × 58 mm field of view, 128 × 128 matrix, with a π/2 for 1.16 mm slice selection followed by a π train with RARE factor 8, effective echo time 30 ms, echo spacing 7.5 ms. Signal averaging was not employed and 5 dummy scans were used. Saturation recovery experiments used repetition times TR of 5500, 2000, 1200, 750, 500, 300, 200 and 100 ms giving a scan time of 169 s, not including the dummy scans. Next, a “dynamic-no-enhancement” (DNE) stability series to simulate dynamic contrast-enhanced MRI was run for 5 min (approximately 34 images) with repeated acquisition using the same parameters but with TR fixed at 500 ms.In ParaVision, the standard RARE 2.3T1 values were obtained using a 2-parameter fit in ParaVision from circular 25 mm2 RoIs, i.e. 29 μl volumes, approximately 120 voxels, at three RoI positions. These were: at the isocentre; radially at the edge of the phantom 10 mm from isocentre; and axially at the end of the phantom 12–20 mm from isocentre, denoted respectively by  = ,  and  mm. The 2-parameter fit assumed zero longitudinal magnetisation at the mid-point of the eighth echo. The resulting T1 values and standard deviation of the fit for each RoI, together with the mean and standard deviation DNE signal for  = , were submitted to the core lab in Manchester for further analysis.Each centre conducted measurements independently and was blinded to findings from the other centres until their own results had been submitted. At each centre, R1 repeatabilities and between-centre reproducibilities were calculated using Microsoft Excel. Each calculation was performed both using absolute units (i.e. standard deviations with units s−1), and using coefficients of variation . This was done because absolute R1 units (s−1) propagate to absolute concentration of relaxive substance and in some instances to absolute biomarker value, while coefficients of variation may be more relevant when biomarker change is considered. Post-hoc tests of significance were made for “effect of day” using Student's t-test, and for “effect of RoI position” by analysis of variance. No correction for multiple comparisons was made but p < 0.01 was considered significant. For each centre, weighted mean R1 values were calculated for each of the five phantoms:Rd,RoI1, are the R1 values for each of the two days in each of the three RoIs, and wd,RoI are the corresponding weights, derived from the T1 fit in ParaVision:At the core lab, root-mean-square (rms) within-centre R1 values were then used to obtain relaxivities by linear regression:r01, B/s−1 ∙ mM−1 is the longitudinal relaxivity of aqueous Ni2+ in 2% agarose at field B0, R01, [Ni]=0, B/s−1 is the longitudinal relaxation rate of 2% agarose at field B0, and ε is a normally-distributed error term assumed to subsume inter alia any temperature effects.These weighted mean 2.4T1 values. Since centres elected to use the proprietary ParaVision software, a small supplementary study was also performed using an alternative analysis to verify values. Data from one centre were reanalysed. Centre A's data were considered a good test set because they submitted data with both high and low fit errors. For each of the 10 RARE data sets (5 phantoms × 2 days), and for the same three RoIs used in the primary analysis, signal mean and standard deviation were retrieved for each TR value. R1 was calculated using “R” [Our “institution-led” study design required each centre to derive its own sing “R”  using foR1 from “R”, R1R, was compared with the reciprocal T1 from Paravision, R1PV. In each of the four cases:For three-parameter fits, Minf, M0 and R1 were fitted, while for two-parameter fits M0 was set to zero. For weighted fits, each RoI value y was weighted by w, the inverse of the variance in y, while for unweighted fits w was set to unity. For each of the 30 data sets, each of the four estimates of 2.5R1 reproducibility was estimated for a range of derived measurements and biomarkers, using representative relaxivities and other parameters from the literature. This is conservative as it does not fully eliminate repeatability error. Three general cases were considered: firstly, native R1 (or T1) used as a biomarker; secondly, concentration of endogenous or exogenous paramagnetic substance used as biomarker; and thirdly, biomarkers derived from compartmental models. For Dynamic Contrast-Enhanced (DCE) MRI, the error in precontrast R1 was propagated into the biomarkers for four preclinical case-studies. Representative ‘true’ values of kinetic parameters, pre-contrast R1 values, and appropriate tracer kinetic models were chosen from literature to estimate contrast agent concentration uptake in each tissue type. Simulation parameters are provided in Supplementary Material.Error propagation associated with two standard deviations of 3R1 measurements (5 phantoms × 3 locations × 2 days), the results of 10 DNE runs (5 phantoms × 2 days), and the 10 associated temperature measurements (5 phantoms × 2 days). The quality of the exponential fits for the 8 TR values was generally good, although in 15/360 cases the fit error was worse than 5%  (see Each centre was requested to submit 30 e L) see . All the3.1R1 data, and r1 from this work, with additional data points added from the literature [terature ,9,15,16.3.2−1 (centre D) to 0.097 s−1 (centre A): day-to-day repeatability CoV ranged from 0.76% (centre F) to 5.48% (centre L). In exploratory analysis, the day-to-day repeatability of 2.34% was not markedly improved either if measurements were restricted to the isocentre (2.22%), or if measurements with >1 °C difference in temperature between day 1 and day 2 were excluded (2.05%). No evidence was seen for field dependence of repeatability. For day-to-day repeatability, 2 centres  showed a statistically significant effect of day, and 4 centres  showed a statistically significant effect of RoI position. Dynamic (DNE) signal stability CoV varied between 0.30% (centre C) and 2.1% (centre L), and in exploratory analyses was not found to be associated with B0, nor with repeatability, nor with the T1 fit error. Between-centre reproducibility of R1 was measured for the 5 phantoms at both 4.7 T and 7 T. Least reproducible, on a CoV basis, was the 0.5 mM phantom at 4.7 T  or, on an absolute units basis, the 8 mM phantom at 7 T . In exploratory analysis, reproducibility was not improved if measurements were restricted to the isocentre .R1 as a biomarker over the range 0.8–8 s−1 was obtained from the relaxivity Eq. r01,B was 0.6% .A measure of the linearity of 3.3R1 values for centre A derived from two-parameter fits performed in “R” and in Paravision were close: mean differences were 0.024% for an unweighted fit and 0.26% for a weighted fit. When three-parameter fits performed in “R” were compared with two-parameter fits performed Paravision, disagreement was greater: 1.67% for an unweighted fit and 1.74% for a weighted fit. Bland-Altman style plots are provided in Supplementary Fig. S5.3.4R1 reproducibility for a range of derived measurements and biomarkers are given in Illustrative between-centre irreproducibility expected from two standard deviations of the observed For measurements of concentration of substance, the propagated irreproducibility naturally varies with relaxivity, while for “derived” biomarkers the propagated irreproducibilities were generally ≤10%.4R1 in MR systems designed and employed for translational in vivo research. We prefer to work with R1 rather than T1, since from a metrology perspective [R1 is a ratio variable while T1 is merely an interval variable. No single method for measuring R1 is optimal for all in vivo studies. The most accurate methods (e.g. inversion recovery with long TR and short TE readout) are neither fast nor efficient. In vivo studies involve complex tradeoffs between accuracy, speed, spatial resolution, field of view, need for fat suppression, sensitivity to inflow, sensitivity to motion artefact, biexponential decay, and other confounding behaviours of tissue magnetisation such as T2 and magnetisation transfer. Moreover, even after a specific method is chosen, errors can be very sensitive to pulse sequence parameters such as choice of delays and nutation angles, spoiling and refocussing strategies, mis-set pulses and so on. In this study we elected to use a RARE saturation recovery technique covering the entire field of view, as this is fairly robust and efficient: our findings may not be directly translatable to other commonly used techniques such as Variable Flip Angle [In this work we addressed the repeatability and reproducibility of spective , R1 is aip Angle ,19 or Loip Angle ,21 which4.1Previous work in preclinical MR systems has addressed the between-centre reproducibility of apparent diffusion coefficients  and voluin vivo studies. Reproducibility [R1 reproducibility and repeatability were small, and there was no obvious factor  that made any one set of measurements worse. Indeed, the error in the exponential fit of signal intensity against TR was numerically the largest error. Several between-centre studies of T1 or R1 reproducibility have been published for clinical equipment [Repeatability ,25 62+ arises because two of the 3d nickel orbitals are half-filled, creating a high-spin triplet state with two unpaired electrons. At lower fields, below 1 T, populations of the three electron spin states are almost independent of B0, as the Zeeman splittings are dominated by spin-orbit coupling (zero field splitting) and not by the applied field B0. Above 2 T, the Zeeman splittings increase linearly with B0. The relaxivity occurs through proton-electron dipolar mechanisms, with the relevant spectral density being the longitudinal relaxation rate R1,e of the nickel electrons [0, R1,e depends on fluctuations of the zero field splitting which are independent of B0, and previous investigators, working at relatively low fields, reported little field dependence for nickel agarose water proton T1 values [The relaxivity of Ni are much less studied, but are critically important in translating from single-centre to multi-centre use. Since physiologic variability is largely absorbed in the repeatability error, phantoms can be very informative about reproducibility.Repeatability errors  have previously been extensively studied. Good repeatability in phantoms is a necessary, but not sufficient, condition for good repeatability T1 was arguably the first MR biomarker [T1 has been reported as a biomarker inter alia in cardiac diseases [R1 differences , and in vivo effects . Nevertheless, R1-based MR biomarkers would be quite sensitive even to such small errors in R1 unless additional acquisition and analysis methods are designed to reduce the impact of error propagation. An example of this is the use of dynamic time series in OE-MRI that determine ∆R1(t) by referencing the time-varying signal to a baseline R1 measurement, thereby reducing the degrees of freedom in the measurement and subsequent error propagation [A realistic assessment of propagation of errors is complex and beyond the scope of this work. In particular, in compartmental models, reproducibility errors and repeatability errors are not completely independent. We omitted from consideration terms which primarily affect repeatability, such as error cancellation with post-contrast pagation . Similar4.3(1)This study was performed using only one vendor's equipment, Bruker Avance I, II or III systems running Paravision 5 or 6, representing a typical range of equipment for preclinical MR biomarker research at the time when the study was performed (2017–18). The findings may not be translatable to other vendors' equipment.(2)1 is imperfect, and the findings may not be translatable to other sequences with different B1 sensitivity.Only one pulse sequence (saturation recovery with RARE readout) was employed. This was chosen  in a com(3)The accuracy of our data was not verified using an external standard, such as spectroscopic inversion-recovery.(4)R1 temperature dependencies in the range −1.3%/°C to +0.7%/°C; data at 0. 08 T [r1 temperature dependence of 0.006 s−1 mM−1/°C. Although temperatures were measured in this study, no direct measurement was made of the agarose temperature itself during MR data acquisition, and exploratory analyses did not reveal temperature as a confound.A common problem for MR phantoms is temperature dependence. In addition to ambient room temperature, heat is imparted to the phantom from the shims during the working day, from the pulsed gradients, and directly from radiofrequency power deposited by the pulse. Data at 1.5 T  and 2.35 0. 08 T  show an (5)0 or coil design. RoIs and T1 calculations were performed locally. Possibly, “centrally-led” standardisation rigorously imposed by a core lab might further improve reproducibility.In order to address the question of reproducibility in normal academic practice, our study modelled “institution-led” standardisation. No site training was performed, no quality control was imposed, nor were sites permitted to repeat their measurements to eliminate apparent outliers. We did not verify that all scanners were performing optimally, and indeed SNR estimated from the DNE runs did not show the anticipated variation with B(6)in vivo measurement. Nevertheless, a well-designed phantom study sets a lower limit on the error to be expected from measurements in living animals.No phantom study can fully model the 4.4R1 exhibited adequate reproducibility for most purposes. Reproducibility (and repeatability) of <0.06 s−1 and < 2.4% was readily achieved. These small technical (instrumentation-derived) errors in R1 measurement mostly do not contribute biologically significant errors into R1-based MR biomarkers. However, in a small number of very demanding applications, such as myocardial fibrosis, white mater, or oxygen-enhanced MRI, the accuracy of R1-based MR biomarkers would be quite sensitive even to such small errors in R1, therefore in these cases further work may be needed to adequately standardise R1 data acquisition and analysis.Using nickel agarose phantoms in typical preclinical MR systems, CG, GS and SZ are employees of Bayer AG, a for-profit company providing MR contrast agents. PDH is an employee at Antaros Medical, a for-profit company providing MR biomarker services. SK and KS are employees of Bruker BioSpin MRI GmbH, a for-profit company which is the manufacturer of the MR systems used in the study. JCW receives compensation from Bioxydyn Ltd., a for-profit company providing MR biomarker services.


Periosteal colonies were more homogenous in size (range 2-30 mm2 vs. 2-54 mm2) and on average 2500-fold more frequent  relative to total viable cells. When expanded in vitro, similar growth rates up to passage 0 (P0) were seen (1.8 population doublings (PDs) per day (periosteum), 1.6 PDs per day (BM)); however, subsequently BM MSCs proliferated significantly slower by P4 (4.3 PDs per day (periosteum) vs. 9.3 PDs per day (BM), n = 9, P = 0.02). In early culture, periosteum cells were less migratory at slower speeds than BM cells. Both MSC types exhibited MSC phenotype and trilineage differentiation capacity; however, periosteum MSCs showed significantly lower (2.7-fold) adipogenic potential based on Nile red : DAPI ratios with reduced expression of adipogenesis-related transcripts PPAR-γ. Altogether, these data revealed that “clinically accessible” periosteal samples represent a consistently rich source of highly proliferative MSCs compared to donor-matched BM, which importantly show similar osteochondral capacity and lower adipogenic potential. Live cell tracking allowed determination of unique morphological and migration characteristics of periosteal MSCs that can be used for the development of novel bone graft substitutes to be preferentially repopulated by these cells.Periosteum is vital for fracture healing, as a highly vascular and multipotential stromal cell- (MSC-) rich tissue. During surgical bone reconstruction, small fragments of periosteum can be “clinically accessible,” yet periosteum is currently not ultilised, unlike autologous bone marrow (BM) aspirate. This study is aimed at comparing human periosteum and donor-matched iliac crest BM MSC content and characterising MSCs in terms of colony formation, growth kinetics, phenotype, cell migration patterns, and trilineage differentiation capacity. “Clinically accessible” periosteum had an intact outer fibrous layer, containing CD271+ candidate MSCs located perivasculary; the inner cambium was rarely present. Following enzymatic release of cells, periosteum formed significantly smaller fibroblastic colonies compared to BM (6.1 mm Fracture nonunion represents a significant clinical challenge. The rate of fracture nonunion is reported to be between 2 and 10% of all fractures, dependent on fracture type, location, and patient demographics , but impThe critically important role of periosteum during bone fracture healing is well established. Following fracture periosteum reacts by thickening and entering into a proliferative state –13. PeriPeriosteum lines the outer aspect of most bones, contributing to appositional growth during childhood and adolescence as well as providing the vascular supply to bone . This tiThe purpose of this study was to investigate “clinically accessible” samples of human periosteum for the presence of osteogenic progenitor multipotential stromal cells (MSCs) and to compare their functional capacities with iliac crest BMA samples from the same donors.2, 0.3 g) was harvested from near to the site of fracture using a scalpel, and BMA (volume range 16-60 mL) was aspirated from the anterior iliac crest. Iliac crest trabecular bone (approximately 1 cm3) was collected from three patients, undergoing autograft procurement. Ethical approval was granted by the National Research Ethics Committee–Leeds East, with ethical approval number 06/Q1206/127 and informed written consent given by all patients.Donor-matched samples of periosteum and BMA were obtained from 12 patients treated for fracture nonunion  at the Trauma Orthopaedic Unit at Leeds General Infirmary, Leeds, UK. Periosteum . Cells were used directly for in vitro assays, as described in the subsequent sections.For extraction of periosteum- and BMA-resident nucleated cells, BMA underwent processing with ammonium chloride (Stem Cell Technologies) to lyse red blood cells. Briefly, 4 mL of ammonium chloride solution was added per 1 mL of BMA and incubated for 10 mins on ice. Cells were concentrated via centrifugation . Periosteum samples were digested in collagenase  at a ratio of 0.1 g of tissue to 0.5 mL of collagenase, for 4 h, incubated at 37°C, 5% COμm thick slides were produced (SuperFrost Plus slides). Slides were dewaxed and hydrated using standard methods, followed by staining for haematoxylin and eosin and picro sirius red. Samples were also stained for CD271 , the well-recognised marker of bone-resident MSCs [Human periosteum and iliac crest bone samples were fixed in 3.75% formaldehyde for a week, and iliac crest bone was next decalcified using 0.1 M EDTA. Subsequently, samples were embedded in paraffin wax, and 5 ent MSCs . AntigenCFU-F assays were used to quantify colony-forming cells in BMA and periosteum digest samples and performed as previously described , 21. Aft5 per cm2 and 1 × 104 per cm2, respectively, and incubated at 37°C, 5% CO2 in StemMACS media. After 48 hours, media were replaced and cells were cultured until 60-80% confluence with biweekly half medium changes; flasks were trypsinised and reseeded at cell densities of 1.25 × 105 for periosteum [5 for BM [2(cell count at passage 0/seeded number of CFU − F) and PD (>P0) = log2(cell count at passage/seeded cell count) as per Churchman et al. [Following initial processing, nucleated cells from BMA and periosteum were plated at a density of 4 × 10riosteum  and 2.5 n et al. .μL 4′,6-diamidino-2-phenylindole (DAPI) buffer ready to be analysed by an LSRII flow cytometer (BD Pharmingen). Data was analysed using FACS DIVA software.To confirm the MSC nature of expanded cells, flow cytometry of donor-matched BM and periosteum cultures was carried out using antibodies chosen in line with the International Society for Cellular Therapies (ISCT) approved panel (Supplementary n = 7 donors), 2600 cells/cm2 were plated onto 7 replicate flat bottom wells and incubated at 37°C, 5% CO2 in OsteoDIFF for 2 or 3 weeks, with biweekly, half medium changes. At two weeks, alkaline phosphatase (ALP) activity was detected using fast blue. At three weeks, calcium deposition was stained with alizarin red [μL of 0.1% Triton-X 100, and DNA content was quantified using a PicoGreen Assay (Thermo Scientific) [Cultured cells (passage 1-3) from donor-matched periosteum and BM underwent trilineage differentiation assessment; OsteoDIFF, AdipoDIFF, and ChondroDIFF media (Miltenyi Biotec) were used to induce differentiation. For osteogenesis  .2 into 5 replicate flat bottomed well plates, incubated at 37°C, 5% CO2, and half medium (AdipoDIFF) changes were carried out biweekly for 3 weeks. After 3 weeks, plates were fixed with 3.75% formaldehyde and stained with either oil red (n = 6 donors) or Nile red and DAPI (n = 3 donors) [Adipogenesis assays were seeded at 4200 cells/cm donors) , the lat donors) .n = 5 donors) were carried out in 5 replicate 1.5 mL screw cap Eppendorf tubes; 2.5 × 105 cells were added to each tube and centrifuged  to create a pellet culture and was resuspended in ChondroDIFF media. Tubes were placed in an incubator at 37°C, 5% CO2 for 3 weeks, where half medium changes were made three times a week. After 3 weeks, 2 pellets were snap frozen in OCT, cut using a cryostat (Leica Biosystems), and dried onto histology slides where toluidine blue was used to stain GAGs. The remaining three pellets were digested in papain digest buffer at 65°C overnight, and the GAG content was quantified using a sulphated GAG assay kit (Blyscan), as previously described [Chondrogenic assays (escribed .COL2A1) and SRY- (sex-determining region Y-) box 9 (Sox9); and adipogenesis markers—fatty acid-binding protein 4 (FABP4) and peroxisome proliferator-activated receptor-gamma (PPAR-γ). The real time-PCR (RT-PCR) reaction was run using a QuantStudio™ 7 Flex Real-Time PCR System and SDS software, recording the fluorescence in real time. Analysis was carried out using the 2Δ(Ct)- method, to calculate normalised gene expression  expression) [Extra wells or pellets were set up for each trilineage differentiation assay for 3 donors to allow quantification of change expression of key lineage markers following differentiation induction. Cells were lysed and RNA isolated using a Single Cell RNA Purification Kit (Norgen) and on-column DNase (Applied Biosystems) treatment. cDNA was produced using a High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems) for use with TaqMan assays: osteogenesis markers—runt-related transcription factor 2 (RUNX2) and bone gamma-carboxyglutamate (gla) protein (BGLAP); chondrogenesis markers—collagen, type 2, alpha 1 (ression) .2 in StemMACS media. On day 3, following a half medium change, the plate lid was replaced with PHI HoloLids™ imaging covers  . The plate was placed onto the xy motorised stage of a HoloMonitor M4 Microscope, set up inside an incubator. Using the Hstudio software, three coordinates in each well were manually focused and set to automatically image every hour for 2 days.P0 vials of donor-matched  BM and periosteum MSCs were seeded in duplicate (250 cells per well) onto a Lumox® multiwell 24-well cell culture plate (Sarstedt). The cultures were grown for 3 days at 37°C, 5% COPost acquisition, the Hstudio software applied a “mask” to the images, where a threshold was set to distinguish cells from the bottom of the well, allowing for automatic cell identification. Automatic cell number assignment allowed for individual cell tracking over time, which was checked manually. All outputs were exported into Excel files and plotted using Prism.t test depending on data distributions), where P < 0.05 was considered significant. Phase holographic imaging data sets were compared using an unpaired Student's t-test. The exact tests are specified in the figure legends, and the data is presented mean ± standard deviation.To compare donor-matched periosteum and BM samples, statistical analysis was carried out using appropriate paired tests (Wilcoxon signed-rank test or paired n = 5), taken from the femur and humerus (n = 1), approximately 5 cm from a nonunion fracture site  was assessed. The mean donor age was 51.8 ± 24.6 years , and periosteum samples were harvested 50 ± 37 weeks following initial injury, with each patient having undergone 0-2 previous orthopaedic surgeries  , but also the tibia (n = 2) and humerus (n = 1), all from nonunion cases, 70 ± 47 weeks following initial injury, and patients had undergone 0-2 previous orthopaedic surgeries.CFU-F assays were carried out to quantify colony formation as a measure of MSC frequency in donor-matched iliac crest BM and periosteum samples  higher (2500-fold) (2.0 ± 0.6%)  .n = 4). Periosteum colonies were more homogenous, with a smaller size distribution compared to BM colonies  compared to BM colonies at 15.5 ± 0.8 mm2    . Of partr2 values, 0.87 (BM) and 0.91 (periosteum)) (P = 0.02).Growth kinetics of donor-matched BM and periosteum cultures was next investigated, and two clear growth patterns were noticeable Figures  and thusosteum)) . Howeverosteum))  and therFollowing the first passage, the PD rate significantly slowed (P1-P4) for both culture types Figures , by P4 pOverall, these data revealed high CFU-F content and a more homogenous nature of colony-forming cells in “clinically accessible” periosteal samples, compared to donor-matched BM samples. Additionally, in our chosen experimental conditions, periosteum MSC cultures had achieved lower cumulative PDs than their BM counterparts at the same passage.To explore if the observed differences seen in colony size between periosteum and BM MSCs could be due to different cell migration patterns, live cell imaging and tracking of cell movement over time was carried out using holographic imaging. Thawed P0 cell cultures  and 13 PD (BM)) were tracked from one donor . Thawed freshly digested periosteum cultures were grown and shown to be not significant to their P0 counterparts (data not shown); therefore, P0 cultures were taken as surrogate to represent MSC migration for up to 2 weeks in culture (the end time point of a CFU-F assay).μm) but a small cell surface area (<1100 μm2), reflecting a spherical shape just prior to cell division, which made up 2.05% (periosteum) and 2.12% (BM) of all cells  was significantly higher  than BM cells (3.4 ± 0.6 μm); however, cell surface area was similar  compared to BM cells. Overall, these data indicated that periosteal cells MSCs appear to have a larger cell volume than their BM counterparts.With respect to the “dividing” cells, the average thickness of periosteum cells (6.1 ± 2.5  similar . In addiμm cell migration) or the nonmigratory (<100 μm cell migration) cells  cells .t-test, P < 0.0001 (5 hours), P = 0.001 (20 hours)) at 5 hours (102.6 ± 54.6 μm (BM), 53.5 ± 32.6 μm (periosteum)) and 20 hours (209.1 ± 129.2 μm (BM) and 123.6 ± 67.6 μm (periosteum)) . At 5 hours, total cell motility (distance travelled) was 151.4 ± 53.6 μm (BM) compared to 95.6 ± 35.0 μm (periosteum), and by 20 hours, this difference had increased to 594 ± 136.0 μm (BM) and 384.2 ± 81.5 μm (periosteum) ) . A similiosteum) .n = 45) and 63% (n = 94), respectively, suggestive that there is a slightly lower proportion of cells classified as nonmigratory within periosteum cultures  (μm) and 5 hours (<100 μm) for BM cultures, this was extended to about 15 hours (<100 μm) or not well defined for >100 μm within periosteum cultures (The proportion of nonmigratory to migratory MSCs within the periosteum and BM cultures was 42% (cultures . When co < 0.05) . Similarcultures .μm (BM) vs. 150 μm (periosteum)) ) , indicatμm), compared to the nonmigratory cells (<100 μm) from 5 hours onwards , irrespective of culture type  was calculated from the gradient of the cell motility graphs (μm/h (<100 μm) or 32.0 μm/h (>100 μm), confirming that BM MSCs move with greater speed than periosteum MSCs (17.5 μm/h (<100 μm), 20.4 μm/h (>100 μm)) (Significant increases in cell motility or distance (rather than displacement) migrated over time were seen with the migratory cells ) .t-test, P < 0.05); however, after this, differences were not seen, suggestive that with time both MSC types migrated in a more random fashion.Migration directness is a ratio of migration (displacement) to motility (distance), where 1 refers to movement in a straight line and 0 to a cell moving completely randomly. This parameter can be used to calculate whether cells migrate randomly or with apparent “purpose.” In contrast to the previous parameters, no significant differences were seen between the MSC culture types over time . Cell miOverall, these data provided new insights into BM and periosteum MSC behaviour in culture. Smaller volumes of BM MSCs could facilitate their faster migration capacities, which in turn could in part explain their ability to form larger colonies, compared to periosteal MSCs, in standard CFU-F assays.n = 7) at three weeks and was found to be slightly higher  in periosteum than BM cultures. Of note, there was high donor variation that was not shown to correlate with donor age , 0.22 (periosteum)). qPCR showed reduction in the early osteogenic marker, RUNX2 expression, but increases in the late osteogenic marker BGLAP expression at day 21 (n = 3) for both culture types, as expected.Quantitative trilineage differentiation assays were carried out on donor-matched cultures in addition to qPCR for lineage-specific markers comparing day 0 (before differentiation) and day 21 (following three weeks of differentiation induction). Osteogenic cultures were stained for ALP after two weeks and then for calcium deposition after three weeks, where visually similar staining could be seen for both culture types, with a tendency for visually higher confluency in the periosteum cultures . Calciumn = 5, P = 0.99) (r2 = 0.77), but not periosteum cultures (r2 = 0.22). Chondrogenic differentiation markers, COL2A1 and SOX9, were increased in both periosteum and BM pellets by day 21  was confirmed for both . Followi = 0.99) . As withy day 21 .n = 6) (P < 0.05). FABP4 was seen to increase in both culture types following adipogenic induction  . Quantifnduction ; howeverIn this study, the potential for the utilisation of periosteum-derived MSCs as a source of MSCs during bone defect surgical repair was investigated. Currently, there is a lack of direct comparisons of MSCs derived from human periosteum and BMA, especially when donor matched , 35. HerBoth MSC sources were compared histologically to locate CD271+ candidate MSCs within each tissue , 37–39. CFU-F assays are the gold standard for MSC quantification in BM aspirates or solid connective tissues enzymatically processed to release viable cells . DespiteUntil recently, CFU-F colony size measurements have not been routinely performed in MSC tissue comparison studies; however, these data can provide valuable information on MSC heterogeneity within the tissues under investigation. When this was carried out on BM aspirates, MSC subpopulations with different sizes and densities have been found indicating a high degree of MSC heterogeneity, which in one study was linked to donor age  but coulin vitro (2 weeks in culture) MSCs was carried out. Phase holographic imaging was utilised as a noninvasive, unlabeled high throughput method for quantifying cellular morphology and live cell tracking [In order to underpin the differences seen in colony formation between periosteum and BM MSC cultures, live cell imaging of early tracking –48. MSC μm. The speed at which MSCs migrate was also quantified; for the first time, periosteum MSCs were shown to migrate at 17.5 μm/h (nonmigratory) and 20.4 μm/h (migratory), which was slower than their BM MSC counterparts at 22.3 μm/h (nonmigratory) and 30.0 μm/h (migratory). BM MSC migration speed within a collagen type I gel has been quantified previously in one study (15 μm/h), which could reflect that migration speed is influenced by the substrate on which MSCs are in contact with [2), showing favorable cell adhesion and spreading on the TiO2 coating [When individual cells were analysed over a 24-hour period, it was observed that as MSCs proliferate and occupy more surface, their migration plateaus and cell directness becomes more random, for both cell types. Indeed, periosteum MSCs were less migratory and moving at slower speeds than BM MSCs. This was also true when cells were divided into two subpopulations, nonmigratory and migratory, based on chosen arbitrary cut-off point of 100 act with . This waact with , whereby coating , highligWith respect to cell size analysis, periosteum MSC cell area was 20% larger compared to donor-matched BM cells. This confirmed that despite higher cumulative PDs accrued by BM MSCs, they were not approaching senescence (senescent cells are larger) , which iin vitro for the same time period, are potentially interacting with the same substrate (in this case tissue culture plastic) in different ways, thus resulting in changes in cell surface area, migration distance, and velocity. It is known that migration of spindle-shaped cells, like MSCs, is dependent on the formation focal adhesions with actin filaments that mechanically link the extracellular matrix to the cytoskeleton and contractile stress fibres [in vitro express different levels of various integrins, which influence focal adhesion formation. However, little is known about differences in integrin and focal adhesion levels between periosteum and BM MSCs; future developments to this work would involve ascertaining whether there are inherent differences in the cytoskeleton and focal adhesion formation.We have shown that differing tissue sources of MSCs, from the same donor and grown s fibres . Levels s fibres . Goessles fibres  showed tPPAR-γ levels, a molecule critical to initiating adipocyte differentiation [For periosteum to be utilised as a source of MSCs for fracture healing, osteogenic and chondrogenic capacities are of particular importance , 57. Whintiation , in day ntiation , 31. Masntiation . Based o2, are harvested from the medial femoral condyle, to wrap around a defect site [As with harvesting of bone autograft for filling of critical size bone defects, a key point to consider with advocating for the use of periosteum is creating a minimal donor site morbidity. Currently, free vascularised corticoperiosteal bone grafts, where the periosteum and underlying cortical graft bone can be 4 cmect site –63. The ect site , 61. Addect site , 65. Tog“Clinically accessible” samples of long bone periosteum, a vital component of bone fracture repair has been shown to be a rich source of highly proliferative MSCs, compared to the current “gold-standard” BMA, with lower adipogenic but similar osteochondral potential. A novel live cell tracking technique permitted extensive quantification of morphological and migratory characteristics of periosteal MSCs that can be used to inform the development of novel bone graft substitutes to be repopulated by these cells. Further investigation into “minimally manipulated” periosteum samples, for example, periosteal micrografts, is needed for future clinical translation of this tissue source for use during single surgical procedure.


Purpose Preclinical evidence suggests the importance of Janus activating kinase (JAK) and TANK-binding kinase 1 (TBK1) in pancreatic ductal adenocarcinoma (PDAC). We evaluated the safety and efficacy of momelotinib (MMB), a JAK1/2 inhibitor with additional activity against TBK1, plus albumin-bound paclitaxel + gemcitabine (nab-P + G), in patients with previously untreated metastatic PDAC. Experimental Design Patients were enrolled into five cohorts of increasing doses of MMB between 100 and 200 mg administered once or twice daily in combination with nab-P + G in 28-day cycles to determine maximum tolerated dose (MTD). Safety, efficacy, pharmacokinetics, and pharmacodynamics were assessed for all patients. Results Twenty-five patients were enrolled. Dose-limiting toxicities of Grade 3 diarrhea occurred in 1 patient each in the 100 and 200 mg MMB once-daily dose groups. MTD was not reached. The 200 mg MMB twice-daily was the maximum administered dose. Objective response rate was 28% , and 13 (52%) patients had a best response of stable disease. The most common adverse events (AEs) were fatigue (80%), nausea (76%), and anemia (68%). Grade 3 or 4 AEs, most commonly neutropenia (32%), were reported by 88% of patients, of which 44% were considered related to MMB. Pharmacokinetic analyses showed MMB concentrations were too low for TBK1 inhibition. Conclusions MMB was safe and well tolerated in combination with nab-P + G. As no OS or PFS benefit vs nab-P + G was apparent in context of suboptimal engagement of the target TBK1, this study does not support further development of MMB as a first-line therapy in pancreatic cancer. As the third leading cause of cancer-related death in the United States, estimates for 2018 are that more than 55,440 people will be diagnosed and nearly 44,330 will die from pancreatic cancer ), withdrawal of consent (n = 4 [16.0%]), study termination by the sponsor (n = 4 [16.0%]), or loss to follow-up (n = 1 [4.0%]).The study screened 38 patients and enrolled 25 patients with a mean age 60.7 ± 10.2 years and mean body mass index 25.8 ± 5.4 kg/mTwo DLTs occurred. The first DLT was Grade 3 diarrhea with intermittent fever in a 68-year-old male with multiple chronic concomitant illnesses in the 100 mg once-daily dose group. The second patient was a 62-year-old male with multiple chronic concomitant illnesses in the 200 mg once-daily group who experienced Grade 3 diarrhea beginning on Cycle 1 Day 18 and was admitted to the hospital for Grade 3 febrile neutropenia on Cycle 1 Day 21.MTD was not reached. The 200 mg MMB twice-daily dose was the maximum administered dose (MAD).All patients experienced at least one treatment-emergent AE (TEAE). The most common TEAEs were fatigue (80%); nausea (76%); anemia (68%); diarrhea (64%); pyrexia (56%); constipation and vomiting (52% each); peripheral edema (48%); abdominal pain (44%); alopecia, decreased appetite, and dysgeusia (40% each); and hypertension, peripheral neuropathy, and peripheral sensory neuropathy (36% each). Serious AEs (SAEs) were experienced by 72% of patients (24% considered related to MMB). 88% of patients reported Grade 3 or 4 TEAEs, most commonly neutropenia  and anemia and pneumonia . SAEs were considered related to MMB in 24% of patients. Grade 3 MMB-related AEs included diarrhea (12.0%); peripheral sensory motor neuropathy, anemia, thrombocytopenia, and decreased neutrophil count (8.0% each); and fatigue, peripheral edema, malaise, generalized edema, polyneuropathy, tremor, febrile neutropenia, dehydration, cachexia, decreased weight, respiratory distress, hypertension, deep vein thrombosis, and nephrolithiasis (4.0% each). Grade 4 events included embolic stroke, neutropenia, and increased blood uric acid (4.0% each). There were no deaths due to TEAEs.Peripheral neuropathy, a predefined AE of interest, occurred in 15 patients (60%), with a higher incidence at the two highest dose levels, and led to discontinuation of MMB in 2 patients . Investigators attributed peripheral sensory neuropathy and peripheral neuropathy as being related to MMB in 6 (24%) and 4 (16%) patients, respectively; related to nab-paclitaxel in 9 (36%) and 8 (32%) patients, respectively; and related to gemcitabine in 7 (28%) and 5 (20%) patients, respectively.Response rates are shown in Table max) and area under the curve (AUCtau) were less than 2-fold higher after the 200 mg once-daily dose of MMB compared with the 100 mg once-daily dose. Based on the Cmax of approximately 300 ng/mL, we estimate transient maximal TBK1 inhibition in the 70% maximal effective concentration (EC70) range.Twenty subjects were included in the PK analyses. Of the 5 patients not included in the PK analyses, 4 had MMB dosing interrupted or decreased at the time of PK sampling and 1 had discontinued the study before PK samples were taken. PK parameters for MMB and its major metabolite, GS-644603, are shown in Table max and AUCtau, respectively.On Cycle 1 Day 15, plasma concentrations of GS-644603 reached a peak approximately 3–5 h after the first dose of MMB. Across dose levels, the median terminal half-life of GS-644603 was approximately 6–28 h. Mean metabolite-to-parent ratio across dosing groups ranged from 0.9 to 2.7 and 1.2 to 4.6 for CIn this study, MMB in doses of up to 200 mg twice daily (MAD) was safe in combination with nab-P + G. Only 2 DLTs of Grade 3 diarrhea were experienced. These were insufficient to guide determination of the MTD in this patient population.OS and PFS values varied inconsistently with dose, but were generally comparable to those observed with nab-P + G alone in the MPACT trial (median OS = 8.5 months in the nab-P + G group . There wP = 0.25), a subgroup analysis suggested benefit for patients with C-reactive peptide >13 mg/L  , P = 0.942, respectively) [The limited efficacy demonstrated and lack of apparent relationship between dose and efficacy at the inflection point between the dose-finding phase 1 portion of the trial and the randomized phase 3 portion of the trial led to a decision not to initiate the planned phase 3 portion of the trial. Announcement of the results of a trial assessing the combination of ruxolitinib, another JAK1/2 inhibitor, with capecitabine in patients with metastatic pancreatic cancer that was refractory to gemcitabine occurred as the phase 1 portion of this study was concluding, and further supported the decision to not advance to the phase 3 portion. That trial found that although the prespecified primary endpoint of OS was not met in the overall study population  .No unexpected toxicities occurred with MMB. TEAEs were consistent with those reported previously in a myelofibrosis population , 16. AEs70 range are insufficient to achieve clinically meaningful levels of TBK1 inhibition [PK analysis was generally comparable to prior evaluations , 20. Maxhibition . Tonic iMomelotinib is an investigational agent which is well tolerated in combination with gemcitabine and nab-paclitaxel for previously untreated PDAC. This study was stopped prior to entering the planned phase 3 portion of the trial because of limited efficacy in context of suboptimal dose/exposure of momelotinib for meaningful engagement of the target TBK1 and a similar lack of efficacy of JAK inhibition in other trials. The disappointing results in this study do not support further development of MMB as a component of first-line therapy in pancreatic cancer, but TBK1 remains a significant target of interest.


Effects of T5 treatment on microstructure and mechanical properties at elevated temperature of hot-ring-rolled (HRRed) AZ80-Ag magnesium alloy were systematically investigated. Results show that, after aging at 175 °C for 36 h, discontinuous and continuous precipitates form inside grains, with the former one taking up a volume fraction of ~64.9%. T5 treatment improves the tensile strength at ambient temperature of the alloy but weakens its tensile strength and creep resistance at elevated temperatures (120–175 °C), indicating opposite effects of T5 on mechanical properties at ambient and elevated temperatures. During creep at 120–175 °C and under 70–90 MPa, the dynamic precipitation process in HRRed specimen is accelerated with increasing temperature. At 150–175 °C massive nucleation and growth of dynamic discontinuous precipitates could result in an atypical primary creep stage, consisting of deceleration and acceleration creep stages, which is reported in wrought Mg-Al-based alloy for the first time. Such primary creep stage can be eliminated by T5 treatment. Besides, diffusion-controlled dislocation creep is the dominant creep mechanism for both HRRed and T5 specimens. Magnesium alloys are promising engineering materials due to their low density, high specific strength, and superior electromagnetic shielding performance ,2,3. Com17Al12 phase. However, studies about the effect of aging treatment on mechanical properties at elevated temperature are rarely reported. As load-bearing parts in aircraft or spacecraft, magnesium alloy components need to work at elevated temperature in some cases, rendering the components subjected to thermal-mechanical coupled loads. Therefore, creep performance is an important parameter to evaluate the long-term reliability.In practical applications, aging treatment is generally conducted to modify comprehensive performance of wrought AZ80-based alloys ,10,11,1217Al12 phase is a major microstructural evolution during creep, which in turn has significant influence on creep behavior. Discontinuous precipitation is believed to have a detrimental effect on creep resistance due to promotion of grain boundary sliding [Extensive researches have been performed on the creep behavior of cast Mg-Al-based alloys ,14,15,16In a recent study by Zeng et al. , aging tIn the present study, a hot-ring-rolled (HRRed) AZ80-Ag alloy  was used, and its fabrication process has been depicted in our previous work . SpecimeMicrostructures were characterized using Leica optical microscope , FEI Nova Nano230 scanning electron microscope  and FEI Tecnai G20 transmission electron microscope . OM and SEM samples were prepared by mechanical polishing and etching. TEM samples were prepared by argon ion-beam thinning. Macro-texture was identified using Bruker D8 Discover X-ray diffractometer . OM, SEM and texture examinations were conducted in the rolling plane, i.e., rolling-axial direction (RD-AD) plane . Volume Tensile tests were carried out at ambient (25 °C) and elevated temperatures (120 °C and 175 °C) using Instron 3369 testing machine  with a cross-head speed of 1 mm/min. The tensile specimens with a gauge dimension of Φ4 mm × 20 mm were machined from the ring along AD. To ensure the reliability of the data, three tensile tests were repeated for each condition and their average results were reported. Tensile creep tests were performed using CRITM RWS50 creep testing machine , at temperatures of 120–175 °C and under constant loads of 70–90 MPa. The creep specimens, with a gauge dimension of Φ10 mm × 50 mm, were cut from the ring along AD. Specimens were crept up to 100 h unless they were fractured within that time. Before loading, the specimens were preheated to target temperature and held for 1 h. The creep displacement was measured using two linear variable differential transformers (LVDT) attached to the high-temperature extensometer, coupled with a data acquisition system.17Al12 precipitates are formed, as shown in 17Al12 precipitates in Mg-Al series alloys are classified into two types, continuous precipitation (CP) and discontinuous precipitation (DP) [Microstructure of HRRed specimen is presented in ion (DP) . In T5 sion (DP) . Meanwhiion (DP) . StatistIn order to capture the texture evolution during T5 treatment, (0002) pole figures are displayed in Tensile curves of specimens tested at ambient and elevated temperatures are shown in Creep curves of specimens tested at 120–175 °C and under 70–90 MPa are displayed in Detailed creep data of HRRed and T5 specimens are summarized in gb ≠ 0) [g = 0002, while all the <c> type dislocations are extinguished when g = ·b ≠ 0) , all theg = 0002  [On the contrary, the YS and UTS at elevated temperatures of the alloy exhibit a downward trend after T5 treatment . Since β~437 °C) , such teT) have significant influence on the steady creep rate  is then converted to Equation (2) as follows:Applied stress (σ) and temperature :At a given temperature, the Q value can be obtained by Equation (4):At a given stress, the n values are calculated by plotting ln σ at 120–175 °C, as shown in Q values are calculated by plotting ln T under 70–90 MPa, as shown in To determine the dominant creep mechanism of HRRed and T5 specimens, the n values of HRRed specimens are 2.97, 4.60, and 4.82 at 120 °C, 150 °C, and 175 °C respectively, while those of T5 specimens are 3.95, 5.52, and 6.23 at corresponding temperatures. For magnesium alloys, three types of creep mechanisms can be activated during creep deformation, grain boundary sliding (GBS), dislocation creep and diffusional creep, which are closely associated with the n value. Generally, n = 3–7 is reported for dislocation creep including dislocation viscous glide (n = ~3) and dislocation climb (n = 4–7) [The n = 4–7) ,26,27,28Q value. For HRRed specimen, the Q values under 70–90 MPa are 129.20–141.99 kJ/mol, close to the activation energy for lattice self-diffusion of magnesium (135 kJ/mol) [Q values of 102.88–117.96 kJ/mol are in the range of 92 to 135 kJ/mol, i.e. between the activation energies for pipe diffusion and lattice self-diffusion of magnesium [n and Q values were 4.2–6.0 and 94.0–122.9 kJ/mol, respectively, for cast AZ91 alloy at 152–297 °C under constant punching stresses of 100–650 MPa, suggesting the activation of two parallel creep mechanisms of lattice and pipe-diffusion-controlled dislocation climb. The similar results are reported by Mahmudi et al. [The information about specific diffusion mode in creep mechanism is revealed by  kJ/mol) ,29. Theragnesium  reportedi et al. . TherefoGenerally, typical primary creep stage of the cast and aged Mg-Al-based alloys is characterized by continuously decelerating creep rate ,17,24,25Dynamic precipitation also occurs in the cast Mg-Al-based alloys during creep at 150–180 °C ,15,16. GAs for T5 specimen, since initial microstructure is already occupied by DP and CP, the growth of DP and resulting GBS are limited during creep process, which is inadequate for significant enhancement of softening effect. Consequently, the atypical primary creep stage is eliminated by aging treatment.It is found that T5 treatment exerts a detrimental effect on the creep resistance. The microstructure of T5 specimen is mainly occupied by lamellar DP, which can provide more interfaces for GBS, making considerable contribution to creep deformation . Besides(1)After T5 treatment, the microstructure is mostly occupied by discontinuous and continuous precipitates, with the former taking up a dominant volume fraction of ~64.9%. Besides, T5 treatment has little influence on the macro-texture.(2)T5 treatment can improve the tensile strength at ambient temperature of the alloy, but deteriorate the tensile strength and creep resistance at elevated temperatures (120–175 °C), indicating opposite effects of T5 treatment on mechanical properties at ambient and elevated temperatures.(3)During creep under conditions of 120–175 °C and 70–90 MPa, HRRed specimens exhibit accelerated dynamic precipitation behavior with increasing temperature. At 150–175 °C, the massive nucleation and growth of dynamic discontinuous precipitates could promote softening effect and lead to an atypical primary creep stage, which is eliminated by T5 treatment.(4)Based on the creep stress exponent (2.97–6.23) and activation energy (102.88–141.99 kJ/mol), diffusion-controlled dislocation creep is the dominant creep mechanism for both HRRed and T5 specimens. Dislocations with <a> and <c> components are activated simultaneously, influencing creep behavior.In the present study, effects of T5 treatment on microstructure and mechanical properties at elevated temperature of HRRed AZ80-Ag alloy were analyzed. The dynamic microstructural evolution and creep mechanism were also discussed. Main conclusions are drawn as follows: