Interview with: Dr Laura Indolfi from PanTher Therapeutics about localized chemotherapy.
Dr Laura Indolfi speaks to Materials Today about her recent paper published in the journal Biomaterials. Follow the link below, to listen to the interview, or right click to download. Click here to read the article, A tunable delivery platform to provide local chemotherapy for pancreatic ductal adenocarcinoma.
Stewart Bland: I’d like to ask if you can start by introducing yourself, PanTher, and telling us about your background?
Laura Indolfi: Yes, so I am Laura Indolfi. I’m the founder and CEO of PanTher Therapeutics, which is a northerly state biotech start up based in Boston, Massachusetts, and we have revolutionised the way we deliver chemotherapeutic agents directly at the tumour site. I am a biomedical engineer. My training was in Italy, and then I moved to Boston to do my post doc at the Massachusetts Institute of Technology, and during my tenure there, we started this project in collaboration with oncologists at the Massachusetts General Hospital, to find a new way to treat cancer, and pancreatic cancer was one of our leading indications.
Stewart Bland: In your study published in the journal, Biomaterials, you reported on a new platform to provide local chemotherapy for pancreatic ductal adenocarcinoma. Before we discuss the development, can you tell us more about this condition?
Laura Indolfi: Yes, sure, so pancreatic cancer is a raising type of cancer. It has been established as the third leading cause of cancer deaths worldwide, just after lung cancer and colon cancer, and unfortunately, in the last 40 years, the survival rates of those patients hasn’t changed, so the diagnosis and the survival numbers for those tumour types are almost equal. Every year the same number of patients get diagnosed than the ones that died, so the treatments that there is right now on the table are definitely not effective. Because of the anatomical position of the pancreas, the tumour can spread, so it can enter into many vital organs that surround the pancreas, like the stomach, the liver, the coeliac nerves, and make the life of the patient very painful. So not only is it a tumour that’s spread very easily, but it also spreads in very vital organs, making the quality of life and prognosis very poor for those patients, so that’s a little bit of the general description of pancreatic cancer. Also it’s a very silent disease, so it gets diagnosed when it’s usually too big to be removed, leaving very few alternatives for those patients, other than the standard treatment, which is the injection of drugs into the bloodstream, with the aim that, in some magical way, going around throughout all of the body, they will find their avenue to go into the tumour mass, and be effective.
Stewart Bland: I think you touched on this in that answer, but could you say a little bit more about why it’s important to develop a new treatment for this particular condition?
Laura Indolfi: Yes, I touched a little bit, saying that it’s spread into other organs, but also I also said that the only treatment currently available is the systemic injection, so being able to deliver the drug into the bloodstream to reach the tumour mass. Unfortunately, for this particular condition, the tumours don’t have a lot of vessels within it, so if we think of the bloodstream as a highway that carries the drug to the tumour, we have no access to this highway into the tumour itself, so the drug goes everywhere else in the body, but very little will actually reach the tumour site. So we need a new treatment that can provide a better delivery of the weapon (the tumour therapeutic agent) directly at the tumour site to be effective. A lot of drugs have been designed and developed by a pharma company that can be very useful for pancreatic cancer, and also for many other types of solid tumours, but the inability of the drug itself to reach the tumour mass is what has been hindering the success of those drugs, so that’s where we kind of came along, and why we need this; it is important to deliver new localised treatment for pancreatic cancer, and many other solid tumours as well.
Stewart Bland: Now, can you tell us about the delivery device that you’ve developed, and what does it do, and how does it work?
Laura Indolfi: The interesting thing in our approach is that we have combined an engineer like myself, with the oncologists that treat those patients, and we have been very creative in trying to combine the two different knowledge bases to provide a solution for these patients, and what we have come up with is; we designed a platform that can be placed in direct contact with the tumour, and so is some sort of Trojan horse – so it’s a material which is very inert with the body, that can be placed in direct contact with the tumour, and over time the material itself will dissolve, and the drug will be released directly into the tumour mass, to increase therapeutic efficacy, and to decrease the systemic exposure, so the exposure of other parts of the body to the drug, that it’s usually the source of complications and side-effects. We designed our first product to be like a Band-Aid, as a patch, that can be placed, minimally invasive, in direct contact with the tumour, so the patients don’t need to undergo surgery. They can just have a laparoscopic procedure, where this patch can be folded in a cigar shape, and can then be unfolded on the other side of the catheter, to be wrapped like a blanket on top of the tumour, and this will serve as a two-fold weapon, on one side being able to place a solid blanket on top of the tumour, will help in preventing the continuous spreading of the tumour into other organs, so in case, where the tumour, it’s very confined, and has not yet invaded other organs, the ability to place this blanket will prevent the metastasis into the nearby organs, like the liver, the stomach, and at the same time, as the blanket will dissolve, the drug will be delivered in direct contact with the tumour, allowing for a better response to treatment that can shrink the tumour to a side where the surgeon feels confident that it can be removed.
Stewart Bland: So can you tell us a little bit about the testing of the device, and the success?
Laura Indolfi: So we have created these animal models, where we have implanted human tumours, human pancreatic tumours, into the pancreas of mice, and then once the microenvironment was recapitulated, so we have tumours into these mice in the pancreas, we either treated those animals with the standard of care of injecting the drug into the bloodstream for four weeks, or we placed it on top of the tumour, our mouse-sized prototype of the device, that was providing for a sustained release over the same time period of four weeks of the same drugs at the same concentration, so basically we wanted to test if the delivery method of the same amount of drugs, of the same drug, was going to have any effect of treatment, and in very good news and very surprisingly, we found that we were able to improve the response of treatment of twelve times, so the same amount of drugs, of the same drug, in the same animal model, but just delivered differently, allowed us to have a huge increase in the response to treatment, where the tumour has shrunk in dimension. They become very necrotic, so they were dead cells that could be easily removed in case of surgery, and we were also able to extend the survival rate of those animals, so the group that received the drug ivs, so into the bloodstream, they became sick very fast, and they died over a very short period of time, while the group that received our localised implant were able to live longer. Actually we had 100% to zero survival rate, so when all of the animals into the control group died, we had still all the animals alive in the localised delivery, that it’s a huge response for that tumour type, because the patients in the clinic, they have a very short life expectancy, so if we had the localised delivery, we can improve and prolong their survival rate, we will be affecting the life of thousands of patients worldwide, and another thing that we were not really expecting, but it’s going to be a very huge benefit for patients, is that we also showed that the ability of giving the drug locally at the primary tumour site affected the ability of the tumour to spread and metastasize also in a very distant part of the body, so when the animal group was treated with the drug injected in the bloodstream, they develop lung metastasis, while when we used our device for doing a localised delivery of the drug, because we were able to kill the primary source of the tumour, so the primary mass, there was no lung metastasis at the end of the study, and that’s because we are basically killing the primary source of the cells, and then they go around in the body and find another place, where to create their home, so this is something that will have a huge impact into the clinic, if we think of patients, that they can get diagnosed before the tumour has spread into other organs, they can have this blanket placed on top, shrunk to a size where the primary tumour can be removed, and also allow for prevention of the spreading into other organs, that then can cause a recurrence of the disease, or some more complication of the treatment, so all in all we had very good data that allowed us to be very enthusiastic about the possibility of bringing this treatment into the clinic for a disease that currently has a very poor outcome and no alternatives whatsoever.
Stewart Bland: So what’s next for the project?
Laura Indolfi: So since then, we have spin out the company, PanTher Therapeutics, into our time at the MIT and MGH, because we want to bring this technology into the clinic. We are working very closely with the FDA to obtain all of the approval and the certification to start testing this treatment into the humans, so we are finalising a large animal model testing to be sure that the procedure of implantation in clinical settings, it’s safe and it’s reproducible, and if everything goes as we are planning in the next twelve months, we may be able to obtain FDA approval to start first-in-man clinical trials, and we can begin the testing into the patients. At the same time, we are also expanding the pipeline, so as I was mentioning at the beginning, all of this limitation of treating cancer, they are not only confined with pancreatic cancer, but most of the major solid tumours, colon, any type of gastrointestinal, solid tumour, they are very difficult to be reached by a surgeon, differently from what happens with breast cancer, for example, for all of this type of disease, an approach like ours, using our blanket to cover the tumour, and deliver the drug locally, can be very beneficial, so we are expanding beyond pancreatic cancer to make this treatment available for other types of disease as well, of the tumour site as well, and in parallel we are preparing a platform of agents that we can embed into this blanket, so we have chosen one drug that we have tested until now, but the beauty of this approach is that it’s a very versatile one, where we can put inside the blanket different types of drugs, even multiple drugs that can be released in a different way at different times, to provide a more comprehensive line of treatment for killing cancer, and making a new treatment solution for this disease, so we have a lot of work to go ahead, but we are very thrilled, and we are very galvanised by the early data that we have provided, so there is a lot of work to do, but we are very hopeful that we can bring a new solution for the treatment of cancer to the patients very soon.
Stewart Bland: Excellent, well that’s fantastic to hear. So finally, as always, I’d like to ask, in your opinion, what are the hot topics in materials science right now?
Laura Indolfi: I think that there is, I may be biased on that, because it’s the area where we are working on, but I really think that there is an untapped area of really providing a localised solution for delivering drugs, or for allowing regeneration of organs. Until now, medicine has been very focused on a systemic and whole body treatment for many diseases, and as material science progresses, and there is all of this combination of natural and synthetic material, or material that can recapitulate a biological clue, can sense a biological clue when inserted into the body and respond accordingly, this is a new area where materials science has a lot to bring on the table, to improve treatment in medicine, and I think that like us, many others are working in the field, we are really excited and intrigued to be at the forefront of engineering and medical science, to combine new material and old material reformulated, to have a huge impact in the development of new medical treatment in cancer and beyond.
Structures of the glucocorticoid-bound adhesion receptor GPR97–Go complex
No statistical methods were used to predetermine sample size. The experiments were not randomized, and investigators were not blinded to allocation during experiments and outcome assessment.
HEK293 cells were obtained from the Cell Resource Center of Shanghai Institute for Biological Sciences (Chinese Academy of Sciences). Spodoptera frugiperda (Sf9) cells were purchased from Expression Systems (cat. 94-001S). Y-1 cells were originally obtained from the American Type Culture Collection (ATCC). The cells were grown in monolayer culture in RPMI 1640 with 10% FBS (Gibco) at 37 °C in a humidified atmosphere consisting of 5% CO2 and 95% air.
Constructs of GPR97 and miniGo heterotrimer
For protein production in insect cells, the human GPR97 (residues 21–549) with the autoproteolysis motif mutation (H248/A and T250/A) was sub-cloned into the pFastBac1 vector. The native signal peptide was replaced with the haemagglutinin signal peptide (HA) to enhance receptor expression, followed by a Flag tag DYKDDDK (China peptide) to facilitate complex purification. An engineered human Gαo1 with Gαo1 H domain deletion, named miniGαo1 was cloned into pFastBac1 according to published literature29. Human Gβ1 with the C-terminal hexa-histidine tag and human Gγ2 were subcloned into the pFastBacDual vector. scFv16 was cloned into pfastBac1 with the C-terminal hexa-histidine tag and the N-terminal GP67 signal peptide. To examine the activities of GPR97, the GPR97-FL-WT (wild-type full-length GPR97), GPR97-FL-AA (GPR97 GPS site mutation, H248/A and T250/A), GPR97β (GPR97 with the NTF removed, residues 250–549) and GPR97-β-T (GPR97β with the N-terminal tethered Stachel sequence removed, residues 265–549) were sub-cloned into the pcDNA3.1 plasmid. The GPR97 mutations E298A, R299A, F345A, F353A, H362A, L363A, Y364A, V370A, F371A, Y406A, W421A, W490A, A493G, I494A, L498A and N510A were generated using the Quikchange mutagenesis kit (Stratagene). The G protein BRET probes were constructed according to previous publications42,43. Human G protein subunits (Gαq, Gβ1 and Gγ2) were sub-cloned into the pcDNA3.1 expression vectors. The Gαq-RlucII subunit was generated by amplifying and inserting the coding sequence of RlucII into Gαq between residue L97 and K98. The Gqo probe, in which the six amino acids of the C-terminal of Gαq-RlucII were substituted with those from Gαo1, was constructed by PCR amplification using synthesized oligonucleotides encoding swapped C-terminal sequences. The GFP10–Gγ2 plasmid was generated by fusing the GFP10 coding sequence in frame at the N terminus to Gγ2. All of the constructs and mutations were verified by DNA sequencing.
High titre recombinant baculoviruses were generated using Bac-to-Bac Baculovirus Expression System. In brief, 2 μg of recombinant bacmid and 2 μl X-tremGENE HP transfection reagent (Roche) in 100 μl Opti-MEM medium (Gibco) were mixed and incubated for 20 min at room temperature. The transfection solution was added to 2.5 ml Sf9 cells with a density of 1 × 106 per ml in a 24-well plate. The infected cells were cultured in a shaker at 27 °C for 4 days. P0 virus was collected and then amplified to generate P1 virus. The viral titres were determined by flow cytometric analysis of cells stained with gp64-PE antibody (1:200 dilution; 12-6991-82, Thermo Fisher). Then, Sf9 cells were infected with viruses encoding GPR97-FL-AA, miniGαo, Gβγ, and with or without scFv16, respectively, at equal multiplicity of infection. The infected cells were cultured at 27 °C, 110 rpm for 48 h before collection. Cells were finally collected by centrifugation and the cell pellets were stored at −80 °C.
GPR97–Go complex formation and purification
Cell pellets transfected with virus encompassing the GPR97-FL-AA, miniGo trimer and scFv16 (only existed in cell pellets for purifying the cortisol–GPR97-FL-AA–Go–scFv16 complex) were resuspended in 20 mM HEPES, pH 7.4, 100 mM NaCl, 10% glycerol, 10 mM MgCl2 and 5 mM CaCl2 supplemented with Protease Inhibitor Cocktail (B14001, Bimake) and 100 μM TCEP (Thermo Fisher Scientific). The complex was formed for 2 h at room temperature by adding 10 μM BCM (HY-B1540, MedChemExpress) or cortisol (HY-N0583, MedChemExpress), 25 mU/ml apyrase (Sigma), and then solubilized by 0.5% (w/v) lauryl maltose neopentylglycol (LMNG; Anatrace) and 0.1% (w/v) cholesteryl hemisuccinate TRIS salt (CHS; Anatrace) for 2 h at 4 °C. Supernatant was collected by centrifugation at 30,000 rpm for 40 min, and the solubilized complex was incubated with nickel resin for 2 h at 4 °C. The resin was collected and washed with 20 column volumes of 20 mM HEPES, pH 7.4, 100 mM NaCl, 10% glycerol, 2 mM MgCl2, 25 mM imidazole, 0.01% (w/v) LMNG, 0.01% GDN (Anatrace), 0.004% (w/v) CHS, 10 μM BCM (or cortisol) and 100 μM TCEP. The complex was eluted with 20 mM HEPES, pH 7.4, 100 mM NaCl, 10% glycerol, 2 mM MgCl2, 200 mM imidazole, 0.01% (w/v) LMNG, 0.01% GDN, 0.004% (w/v) CHS, 10 μM BCM (or cortisol) and 100 μM TCEP. The elution of nickel resin was applied to M1 anti-Flag resin (Sigma) for 2 h and washed with 20 mM HEPES, pH 7.4, 100 mM NaCl, 10% glycerol, 2 mM MgCl2, 5 mM CaCl2, 0.01% (w/v) LMNG, 0.01% GDN, 0.004% (w/v) CHS, 10 μM BCM (or cortisol) and 100 μM TCEP. The GPR97–Go complex was eluted in buffer containing 20 mM HEPES, pH 7.4, 100 mM NaCl, 10% glycerol, 2 mM MgCl2, 0.01% (w/v) LMNG, 0.01% GDN, 0.004% (w/v) CHS, 10 μM BCM (or cortisol), 100 μM TCEP, 5 mM EGTA and 0.2 mg/ml Flag peptide. The complex was concentrated and then injected onto Superdex 200 increase 10/300 GL column equilibrated in the buffer containing 20 mM HEPES, pH 7.4, 100 mM NaCl, 2 mM MgCl2, 0.00075% (w/v) LMNG, 0.00025% GDN, 0.0002% (w/v) CHS, 10 μM BCM (or cortisol) and 100 μM TCEP. The complex fractions were collected and concentrated individually for EM experiments.
Cryo-EM grid preparation and data collection
For the preparation of cryo-EM grids, 3 μl of purified BCM-bound and cortisol-bound GPR97–Go complex at approximately 20 mg/ml was applied onto a glow-discharged holey carbon grid (Quantifoil R1.2/1.3). Grids were plunge-frozen in liquid ethane cooled by liquid nitrogen using Vitrobot Mark IV (Thermo Fisher Scientific). Cryo-EM imaging was performed on a Titan Krios at 300 kV accelerating voltage in the Center of Cryo-Electron Microscopy, Zhejiang University. Micrographs were recorded using a Gatan K2 Summit direct electron detector in counting mode with a nominal magnification of ×29,000, which corresponds to a pixel size of 1.014 Å. Movies were obtained using serialEM at a dose rate of about 7.8 electrons per Å2 per second with a defocus ranging from −0.5 to −2.5 μm. The total exposure time was 8 s and intermediate frames were recorded in 0.2-s intervals, resulting in an accumulated dose of 62 electrons per Å2 and a total of 40 frames per micrograph. A total of 2,707 and 5,871 movies were collected for the BCM-bound and cortisol-bound GPR97–Go complex, respectively.
Cryo-EM data processing
Dose-fractionated image stacks for the BCM–GPR97–Go complex were subjected to beam-induced motion correction using MotionCor2.144. Contrast transfer function (CTF) parameters for each non-dose-weighted micrograph were determined by Gctf45. Particle selection, 2D and 3D classifications of the BCM–GPR97–Go complex were performed on a binned data set with a pixel size of 2.028 Å using RELION-3.0-beta246.
For the BCM–GPR97–Go complex, semi-automated particle selection yielded 2,026,926 particle projections. The projections were subjected to reference-free 2D classification to discard particles in poorly defined classes, producing 911,519 particle projections for further processing. The map of the 5-HT1BR–miniGo complex (EMDB-4358)47 low-pass filtered to 40 Å was used as a reference model for maximum-likelihood-based 3D classification, resulting in one well-defined subset with 307,700 projections. Further 3D classifications focusing the alignment on the complex produced two good subsets that accounted for 166,116 particles, which were subsequently subjected to 3D refinement, CTF refinement and Bayesian polishing. The final refinement generated a map with an indicated global resolution of 3.1 Å at a Fourier shell correlation of 0.143.
For the cortisol–GPR97–Go complex, particle selection yielded 4,323,518 particle projections for reference-free 2D classification. The well-defined classes with 2,201,933 particle projections were selected for a further two rounds of 3D classification using the map of the BCM-bound complex as reference. One good subset that accounted for 335,552 particle projections was selected for a further two rounds of 3D classifications that focused the alignment on the complex, and produced one high-quality subset with 75,814 particle projections. The final particle projections were subsequently subjected to 3D refinement, CTF refinement and Bayesian polishing, which generates a map with a global resolution of 2.9 Å. Local resolution for both density maps was determined using the Bsoft package with half maps as input maps48.
Model building and refinement
For the structure of the BCM–GPR97–Go complex, the initial template of GPR97 was generated using the module ‘map to model’ in PHENIX44. The coordinate of the 5-HT1BR–Go complex (PDB ID: 6G79) was used to generate the initial models for Go (ref. 44). Models were docked into the EM density map using UCSF Chimera49, followed by iterative manual rebuilding in COOT50 according to side-chain densities. BCM and lipid coordinates and geometry restraints were generated using phenix.elbow. BCM was built to the model using the ‘LigandFit’ module in PHENIX. The placement of BCM shows a correlation coefficient of 0.81, indicating a good ligand fit to the density. The model was further subjected to real-space refinement using Rosetta51 and PHENIX44.
For the structure of the cortisol–GPR97–Go complex, the coordinates of GPR97 and Go from the BCM-bound complex and scFv16 from the human NTSR1–Gi1 complex (PDB ID: 6OS9) were used as initial model. Models were docked into the density map and then were manual rebuilt in COOT. The agonist cortisol was built to the model using the ‘LigandFit’ module as described, showing a good density fit with a correlation coefficient of 0.80. The model was further refined using Rosetta51 and PHENIX44. The final refinement statistics for both structures were validated using the module ‘comprehensive validation (cryo-EM)’ in PHENIX44. The goodness of the fit of the model to the map was performed for both structures using a global model-versus-map FSC (Extended Data Fig. 2). The refinement statistics are provided in Extended Data Table 1. Figures of the structures were generated using UCSF Chimera, UCSF ChimeraX52 and PyMOL53.
Molecular dynamics simulation of the BCM–GPR97 and cortisol–GPR97 complexes
On the basis of the favour binding poses of BCM and cortisol with the receptor GPR97, which was calculated by the LigandFit program of PHENIX, the GPR97–agonist complexes were substrate from the two GPR97–agonist–mGo complexes for molecular dynamics simulation. The orientations of receptors were calculated by the Orientations of Proteins in Membranes (OPM) database. Following this, the whole systems were prepared by the CHARM-GUI and embedded in a bilayer that consisted of 200 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipids by replacement methods. The membrane systems were then solvated into a periodic TIP3P water box supplemented with 0.15 M NaCl. The CHARMM36m Force Filed was used to model protein molecules, CHARMM36 Force Filed for lipids and salt with CHARMM General Force Field (CGenFF) for the agonist molecules BCM and cortisol.
Then, the system was subjected to minimization for 10,000 steps using the conjugated gradient algorithm and then heated and equilibrated at 310.13 K and 1 atm for 200 ps with 10.0 kcal mol−1 Å−2 harmonic restraints in the NAMD 2.13 software. Next followed five cycles of equilibration for 2 ns each at 310.13 K and 1 atm, for which the harmonic restraints were 5.0, 2.5, 1.0, 0.5 and 0.1 kcal mol−1 Å−2 in sequence.
Production simulations were run at 310.13 K and 1 atm in the NPT ensemble using the Langevin thermostat and Nose–Hoover method for 200 ns. Electrostatic interactions were calculated using the particle mesh Ewald (PME) method with a cut-off of 12 Å. Throughout the final stages of equilibration and production, 5.0 kcal mol−1 Å−2 harmonic restraints were placed on the residues of GPR97 that were within 5 Å of Go in the BCM (or cortisol)–GPR97–Go complex to ensure that the receptor remained in the active state in the absence of the G protein. Trajectories were visualized and analysed using Visual Molecular Dynamics (VMD, version 1.9.3)
cAMP ELISA detection in Y-1 cells
Y-1 cells were transfected with Gpr97 siRNA (si-97, GUGCAGGGAAUGUCUUUAA) or control siRNA (si-Con) for 48 h. After starvation for 12 h in serum-free medium, the cells were further stimulated with cortisone (8 nM), forskolin (5 μM) (Sigma-Aldrich) or control vehicle for 10 min. Then, cells were washed three times with pre-cooled PBS and resuspended in pre-cooled 0.1 N HCl containing 500 μM IBMX at a 1:5 ratio (w/v). The samples were neutralized with 1 N NaOH at a 1:10 ratio (v/v) after 10 min. The supernatants were collected after centrifugation of the samples at 600g for 10 min. The supernatants were then prepared for cAMP determination using the cAMP Parameter Assay Kit (R&D Systems) according to the manufacturer’s instruction. The Gpr97 expression level under various conditions were further confirmed using quantitative real-time PCR.
Mouse adrenocorticotoma cell line Y-1 cells were transfected with Gpr97 siRNA (si-97) or control siRNA (si-Con) for 48 h. Then, the cells were treated with serum-free medium for 12 h. After that, cortisone (16 nM) or ACTH (0.5 μM) were added to cells for 30 min. The supernatants of the cell culture medium were collected for measurements of corticosterone by ELISA according to the manufacturer’s instructions.
Quantitative real-time PCR
Total RNA of cells was extracted using a standard TRIzol RNA isolation method. The reverse transcription and PCR experiments were performed with the Revertra Ace qPCR RT Kit (TOYOBO FSQ-101) using 1.0 μg of each sample, according to the manufacturer’s protocols. The quantitative real-time PCR was conducted in the Light Cycler apparatus (Bio-Rad) using the FastStart Universal SYBR Green Master (Roche). The mRNA level was normalized to GAPDH in the same sample and then compared with the control. The forward and reverse primers for GPR97 used in the experiments were CAGTTTGGGACTGAGGGACC and GCCCACACTTGGTGAAACAC. The mRNA level of GAPDH was used as an internal control. The forward and reverse primers for GAPDH were GCCTTCCGTGTTCCTACC and GCCTGCTTCACCACCTTC.
cAMP inhibition assay
To measure the inhibitory effects on forskolin-induced cAMP accumulation of different GPR97 constructs or mutants in response to different ligands or constitutive activity, the GloSensor cAMP assay (Promega) was performed according to previous publications12,13. HEK293 cells were transiently co-transfected with the GloSensor and various versions of GPR97 or vehicle (pcDNA3.1) plasmids using PEI in six-well plates. After incubation at 37 °C for 24 h, transfected cells were seeded into 96-well plates with serum-free DMEM medium (Gibco) and incubated for another 24 h at 37 °C in a 5% CO2 atmosphere. Different ligands were dissolved in DMSO (Sigma) to a stock concentration of 10 mM and followed by serial dilution using PBS solution immediately before the ligand stimulation. The transfected cells were pre-incubated with 50 μl of serum-free DMEM medium containing GloSensor cAMP reagent (Promega). After incubation at 37 °C for 2 h, varying concentrations of ligands were added into each well and followed by the addition of forskolin to 1 μM. The luminescence intensity was examined on an EnVision multi-label microplate detector (Perkin Elmer).
The Gqo protein activation BRET assay
According to previous publications, the BCM dipropionate-induced GPR97 activity could be measured by chimeric Gqo protein assays25. The Gqo BRET probes were generated by replacing the six amino acids of the C-terminal of Gq-RlucII with those from GoA1, creating a chimeric Gqo-RlucII subunit47. GFP10 was connected to Gγ. The Gqo protein activation BRET assay was performed as previously described54. In brief, HEK293 cells were transiently co-transfected with control D2R and various GPR97 constructs, plasmids encoding the Gqo BRET probes, incubated at 37 °C in a 5% CO2 atmosphere for 48 h. Cells were washed twice with PBS, collected and resuspended in buffer containing 25 mM HEPES, pH 7.4, 140 mM NaCl, 2.7 mM KCl, 1 mM CaCl2, 12 mM NaHCO3, 5.6 mM d-glucose, 0.5 mM MgCl2 and 0.37 mM NaH2PO4. Cells that were dispensed into a 96-well microplate at a density of 5–8 × 104 cells per well were stimulated with different concentrations of ligands. BRET2 between RLucII and GFP10 was measured after the addition of the substrate coelenterazine 400a (5 μM, Interchim) (Cayman) using a Mithras LB940 multimode reader (Berthold Technologies). The BRET2 signal was calculated as the ratio of emission of GFP10 (510 nm) to RLucII (400 nm).
Measurement of receptor cell-surface expression by ELISA
To evaluate the expression level of wild-type GPR97 and its mutants, HEK293 cells were transiently transfected with wild-type and mutant GPR97 or vehicle (pcDNA3.1) using PEI regent at in six-well plates. After incubation at 37 °C for 18 h, transfected cells were plated into 24-well plates at a density of 105 cells per well and further incubated at 37 °C in a 5% CO2 atmosphere for 18 h. Cells were then fixed in 4% (w/v) paraformaldehyde and blocked with 5% (w/v) BSA at room temperature. Each well was incubated with 200 μl of monoclonal anti-FLAG (F1804, Sigma-Aldrich) primary antibody overnight at 4 °C and followed by incubation of a secondary goat anti-mouse antibody (A-21235, Thermo Fisher) conjugated to horseradish peroxide for 1 h at room temperature. After washing, 200 μl of 3,3′,5,5′-tetramethylbenzidine (TMB) solution was added. Reactions were quenched by adding an equal volume of 0.25 M HCl solution and the optical density at 450 nm was measured using the TECAN (Infinite M200 Pro NanoQuant) luminescence counter. For determination of the constitutive activities of different GPR97 constructs or mutants, varying concentrations of desired plasmids were transiently transfected into HEK293 cells and the absorbance at 450 nm was measured.
The FlAsH-BRET assay
HEK293 cells were seeded in six-well plates after transfection with GPR97-FlAsH with Nluc inserted in a specific N-terminal site. Before the BRET assay, HEK293 cells were starved with serum for 1 h. Then cells were digested, centrifuged and resuspended in 500 μl BRET buffer (25 mM HEPES, 1 mM CaCl2, 140 mM NaCl, 2.7 mM KCl, 0.9 mM MgCl2, 0.37 mM NaH2PO4, 5.5 mM d-glucose and 12 mM NaHCO3). The FlAsH-EDT2 was added at a final concentration of 2.5 μM and incubated at 37 °C for 60 min. Subsequently, HEK293 cells were washed with BRET buffer and then distributed into black-wall clear-bottom 96-well plates, with approximately 100,000 cells per well. The cells were treated with a final concentration of BCM and cortisol at 10−5 to 10−11 and then coelenterazinc H was added at a final concentration of 5 μM, followed by checking the luciferase (440–480 nm) and FlAsH (525–585 nm) emissions immediately. The BRET ratio (emission enhanced yellow fluorescent protein/emission Nluc) was calculated using a Berthold Technologies Tristar 3 LB 941 spectrofluorimeter. The procedure was modified from those described previously34,55,56.
A one-way ANOVA test was performed to evaluate the statistical significance between various versions of GPR97 and their mutant in terms of expression level, potency or efficacy using GraphPad Prism. For all experiments, the standard error of the mean of the values calculated based on the data sets from three independent experiments is shown in respective figure legends.
Further information on research design is available in the Nature Research Reporting Summary linked to this paper.
A ‘Build and Retrieve’ methodology to simultaneously solve cryo-EM structures of membrane proteins
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Glycoproteomics is coming of age, thanks to advances in instrumentation, experimental methodologies and computational search algorithms.
Glycosylation is one of the most common post-translational modifications, and glycoproteins play crucial roles in important biological processes like cell signaling, host–pathogen interaction, immune response and disease, including cancer and even the ongoing COVID-19 pandemic (Science 369, 330–333, 2020). Glycoproteomics aims to determine the positions and identities of the complete repertoire of glycans and glycosylated proteins in a given cell or tissue.
Glycans are everywhere. High-throughput glycoproteomics approaches offer insights. Credit: Katherine Vicari, Springer Nature
Mass spectrometry (MS)-based approaches allow large-scale global analysis; however, the structural diversity of glycans and the heterogeneous nature of glycosylation sites make comprehensive analysis particularly challenging. Glycans obstruct complete fragmentation of the protein backbone, and they were traditionally removed for simplicity at the cost of losing glycan information. The MS spectra tend to be complicated due to the presence of isomers, often requiring manual interpretation. Furthermore, database searching for spectral matches can quickly become a combinatorial problem and requires innovative bioinformatics solutions.
Recent developments in MS instrumentation, fragmentation strategies (J. Proteome Res. 19, 3286–3301, 2020) and high-throughput workflows have made analyzing intact glycoproteins a possibility. Several specific enrichment strategies have made even low-abundance glycans and glycopeptides detectable (Mol. Cell. Proteomics https://doi.org/10.1074/mcp.R120.002277, 2020). A variety of experimental workflows tailored for either N-linked glycans, which are found at consensus sites on the proteins, or O-linked glycans, which have no recognizable consensus sequence, have been developed (Nature 549, 538–542, 2017; Nat. Commun. 11, 5268, 2020; Nat. Methods 16, 902–910, 2019). New software packages based on fragment-ion indexing strategies offer substantial increases in speed for glycopeptide and site assignments (Nat. Methods 17, 1125–1132, 2020; Nat. Methods 17, 1133–1138, 2020).
With other -omics fields taking the lion’s share of attention in recent years, it is now time for glycoproteomics to shine. Comprehensive understanding of glycosylation at different levels of granularity is bound to serve both basic and translational research.
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Cite this article
Singh, A. Glycoproteomics. Nat Methods 18, 28 (2021). https://doi.org/10.1038/s41592-020-01028-9
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