Radiometal-Based PET/MRI Contrast Agents for Sensing Tumor Extracellular pH

Acidosis is a useful biomarker for tumor diagnoses and for evaluating early response to anti-cancer treatments. Despite these useful applications, there are few methods for non-invasively measuring tumor extracellular pH, and none are routinely used in clinics. Responsive MRI contrast agents have been developed, and they undergo a change in MRI signal with pH. However, these signal changes are concentration-dependent, and it is difficult to accurately measure the concentration of an MRI contrast agent in vivo. PET/MRI provides a unique opportunity to overcome this concentration dependence issue by using the PET component to report on the concentration of the pH-responsive MRI agent. Herein, we synthesized PET/MRI co-agents based on the design of a pH-dependent MRI agent, and we have correlated pH with the r1 relaxivity of the MRI co-agent. We have also developed a procedure that uses PET radioactivity measurements and MRI R1 relaxation rate measurements to determine the r1 relaxivity of the MRI co-agent, which can then be used to estimate pH. This simultaneous PET/MRI procedure accurately measured pH in solution, with a precision that depended on the concentration of the MRI co-agent. We used our procedure to measure extracellular pH in a subcutaneous flank model of MIA PaCa-2 pancreatic cancer. Although the PET co-agents were stable in serum, post-imaging studies showed evidence that the PET co-agents were degraded in vivo. These results showed that tumor acidosis can be evaluated with simultaneous PET/MRI, although improvements are needed to more precisely measure MRI R1 relaxation rates, and ensure the in vivo stability of the agents.

Introduction
Cancer cells undergo many biochemical processes that distinguish them from normal cells. One of these processes is upregulated aerobic glycolysis, which has been termed the Warburg effect (Figure 1a) [1]. Due to this effect, cancer cells upregulate the conversion of glucose into lactate through glycolysis, even in the presence of adequate oxygen [1,2]. The Warburg effect is atypical for normal cells because aerobic glycolysis is an inefficient pathway to synthesize adenosine 5'-triphosphate (ATP). While there is still debate regarding the selective pressures for tumors to rely on the Warburg effect, the production of lactate is an effective method to quickly produce carbon building blocks, which aid in rapid cancer cell division [2]. Once lactate is produced, it is then secreted out of the tumor cells, leading to a buildup of extracellular lactic acid, and an acidic extracellular pH (pHe) (<7.0), compared to normal tissues [2,3]. GLUT1 and other glucose transporters shuttle glucose into the cell, which is metabolized into pyruvate. The pyruvate is then converted into lactate by lactate dehydrogenase (LDHA), and this upregulated glycolysis pathway in tumor cells is known as the Warburg effect. The lactate is then secreted out of tumor cells by MCT1 and other monocarboxylate transporters, along with excess intracellular protons secreted via V-ATPase (red H + , left side). Furthermore, carbonic anhydrase IX (CA-IX) produces bicarbonate that is internalized into cells to neutralize intracellular acidosis caused by the Warburg effect, and the bicarbonate production contributes to extracellular acidification (red H + , right side). These processes lead to an acidic extracellular pH (pHe) relative to intracellular pH (pHi). (b) Evaluations of tumor acidosis can have a central role in diagnostic applications (white) and evaluations of anti-cancer treatments (orange).
The evaluation of tumor acidosis has many diagnostic applications (Figure 1b). Tumor acidosis is related to tumor growth rate [4], invasion [5], and metastasis [6], so quantitatively imaging pHe can improve the diagnosis of aggressive vs. benign tumors. Measuring pH can also differentiate acidic tumors with pHe < 7.0 from mild inflammation that typically has pHe 7.1-7.4 [7], and infections that are typically pHe-neutral [8]. Moreover, monitoring changes in pHe can evaluate the early response to certain drug therapies that directly reduce tumor glycolysis, or that more generally reduce tumor metabolism [9,10]. Evaluations of tumor pHe can also be used to predict and monitor the effect of pH-dependent drugs and antibodies [11,12]. Tumor acidosis contributes to immune escape, and therefore, measuring tumor pHe can aid in predicting response to immunotherapies before expensive treatments are started [13].
While many research studies have explored methods to measure in vivo tumor acidosis through molecular imaging, it is currently not a practice adopted in the clinic [14]. In particular, magnetic resonance imaging (MRI) has been investigated for measuring in vivo tumor pHe. T1 agents have an r1 relaxivity that indicates the strength of the agent to increase the R1 relaxation rate of water, and generate T1-weighted MR image contrast (Equations (1) and (2)) [15]. Some T1 contrast agents have been designed to have a pHdependent r1 relaxivity, so that the measured ΔR1 may be used to determine pH [16,17]. However, the change in MR image contrast caused by these agents also depends on the agent's concentration ([CA]) in the tissue (Equation (1) The concentration of an MRI contrast agent is variable between different tissues, and even within the same tissue. For this reason, using a single pH-responsive MRI contrast agent is impractical for measuring in vivo tumor pHe [18]. and other glucose transporters shuttle glucose into the cell, which is metabolized into pyruvate. The pyruvate is then converted into lactate by lactate dehydrogenase (LDHA), and this upregulated glycolysis pathway in tumor cells is known as the Warburg effect. The lactate is then secreted out of tumor cells by MCT1 and other monocarboxylate transporters, along with excess intracellular protons secreted via V-ATPase (red H + , left side). Furthermore, carbonic anhydrase IX (CA-IX) produces bicarbonate that is internalized into cells to neutralize intracellular acidosis caused by the Warburg effect, and the bicarbonate production contributes to extracellular acidification (red H + , right side). These processes lead to an acidic extracellular pH (pHe) relative to intracellular pH (pHi). (b) Evaluations of tumor acidosis can have a central role in diagnostic applications (white) and evaluations of anti-cancer treatments (orange).
The evaluation of tumor acidosis has many diagnostic applications (Figure 1b). Tumor acidosis is related to tumor growth rate [4], invasion [5], and metastasis [6], so quantitatively imaging pHe can improve the diagnosis of aggressive vs. benign tumors. Measuring pH can also differentiate acidic tumors with pHe < 7.0 from mild inflammation that typically has pHe 7.1-7.4 [7], and infections that are typically pHe-neutral [8]. Moreover, monitoring changes in pHe can evaluate the early response to certain drug therapies that directly reduce tumor glycolysis, or that more generally reduce tumor metabolism [9,10]. Evaluations of tumor pHe can also be used to predict and monitor the effect of pH-dependent drugs and antibodies [11,12]. Tumor acidosis contributes to immune escape, and therefore, measuring tumor pHe can aid in predicting response to immunotherapies before expensive treatments are started [13].
While many research studies have explored methods to measure in vivo tumor acidosis through molecular imaging, it is currently not a practice adopted in the clinic [14]. In particular, magnetic resonance imaging (MRI) has been investigated for measuring in vivo tumor pHe. T 1 agents have an r 1 relaxivity that indicates the strength of the agent to increase the R 1 relaxation rate of water, and generate T 1 -weighted MR image contrast (Equations (1) and (2)) [15]. Some T 1 contrast agents have been designed to have a pHdependent r 1 relaxivity, so that the measured ∆R 1 may be used to determine pH [16,17]. However, the change in MR image contrast caused by these agents also depends on the agent's concentration ([CA]) in the tissue (Equation (3)): The concentration of an MRI contrast agent is variable between different tissues, and even within the same tissue. For this reason, using a single pH-responsive MRI contrast agent is impractical for measuring in vivo tumor pHe [18].
Many researchers have devised unique ways to address this concentration dependence, by using ratiometric approaches that involve pH-dependent and pH-independent imaging agents [18]. One solution is to harness the power of simultaneous PET/MRI [19], where the radioactivity measured by positron emission tomography (PET) corresponds to the concentration of the agent, and is also independent of pH [20]. This PET-based concentration measurement can then be used in a ratiometric approach with the pH-and concentration-dependent MR image contrast that is affected by the MRI agent, resulting in an estimated pH value.
In this work, a pair of contrast agents have been synthesized and consist of a pHresponsive MRI co-agent and a pH-independent PET co-agent. These two agents were designed to have identical pharmacokinetics, so that a dual injection of the two agents at a known ratio can quantitatively measure pH. The r 1 relaxivity of the MRI co-agent has been reported to relate to pH, because the protonation of the sulfonamide leads to the dissociation of the arm from the gadolinium (Gd) core, increasing the R 1 relaxation rate of the surrounding water [21]. With a known ratio of MRI co-agent to PET co-agent, the radioactivity detected by the PET detector can be translated into the concentration of the MRI co-agent. Therefore, with this known concentration and the R 1 relaxation rate, the r 1 relaxivity can be calculated, and pH can be determined using a calibration curve of pH versus r 1 relaxivity for the MRI co-agent. This approach has been explored previously with a different pair of PET/MRI co-agents than the agents used in our study, but was not tested with a clinically relevant magnetic field strength, and in vivo studies were not performed [20].

General Chemistry and Radiochemistry Methods
All solvents and reagents were purchased from commercial sources and used as received. Water was deionized using a Milli-Q integral water purification system (Milli-poreSigma, Burlington, MA, USA). The pH values of the samples were recorded using a SevenCompact S221 benchtop pH/ion meter (Mettler Toledo, Columbus, OH, USA). All reactions were performed with oven-dried glassware under nitrogen, unless otherwise noted. Thin layer chromatography (TLC) was performed using aluminum-backed plates pre-coated with silica gel 60 matrix with fluorescent indicator F 254 and 0.2 mm layer thickness. Flash column chromatography was performed using an Isolera One automated flash chromatography system (Biotage, Uppsala, Sweden). 1 H NMR spectra were performed using a 500 or 600 MHz Bruker NMR spectrometer (Bruker, Billerica, MA, USA). Chemical shifts (δ) are reported in ppm. Ultra-performance liquid chromatography-mass spectrometry/mass spectrometry (UPLC-MS/MS) was performed using a Waters Xevo TQD IVD with Acquity UPLC, using an Acquity UPLC BEH C18 1.7 µm column with 2.1 × 50 mm dimensions (Waters, Milford, MA, USA). The concentration of the MRI co-agent was confirmed by measuring Gd concentration using a PerkinElmer NexION 300 inductively coupled plasma-mass spectrometer (ICP-MS) running Syngistix software (PerkinElmer, Waltham, MA, USA). The acquisition mode included three replicates averaged to give 157 Gd concentrations. The dwell time was 50 ms with 18 L/min main argon flow, 1.2 L/min auxiliary argon flow, 0.97 L/min optimized nebulizer argon flow, 1600 W RF power, 0.2 mL/min sample flow, and KED cell mode with 1.2 mL/min helium flow.
Preparative HPLC (prep HPLC) was performed on an Agilent 1260 Infinity II (Agilent Technologies, Santa Clara, CA, USA) with a Luna ® C18 5 µm column, with 21.2 × 250 mm dimensions (Phenomenex, Torrance, CA, USA). RadioHPLC was performed on an analytical Agilent 1260 Infinity II Series (Agilent Technologies, Santa Clara, CA, USA) with a XBridge C18 3.5 µm column with 4.6 × 250 mm dimensions using a Flow-RAM radioHPLC detector (LabLogic Systems Ltd., Brandon, FL, USA), for compound identification and quality control. For metabolism studies, a more sensitive system was warranted, so an analytical Agilent 1100 Series system (Agilent Technologies, Santa Clara, CA, USA) was used with an Econosil 10 µm column with 4.6 × 250 mm dimensions (Alltech, Nicholasville, KY, USA). Counts were detected using a Bioscan Model 106 detector (Bioscan, Inc., Poway, CA, USA) interfaced with the HPLC using an Agilent Interface 35900E (Agilent Technologies, Santa Clara, CA, USA). Purification with a C18 cartridge was performed using a light C18 Sep Pak ® cartridge (Waters, Milford, MA, USA) prewashed with ethanol (3 mL), and then water (6 mL). HPLC was performed using one of the following solvent systems: 0.1% TFA in water (solvent A) and 0.1% TFA in acetonitrile (solvent B); or 0.05% formic acid in water (solvent C) and 0.05% formic acid in acetonitrile (solvent D). For prep HPLC, the following method was used: 5% solvent B (in solvent A) to 95% solvent B (in solvent A) over 34 min, then hold at 95% solvent B (in solvent A) for 3 min with a 20 mL/min flow rate. For analytical HPLC, the following method was used: 5% solvent D (in solvent C) to 95% solvent D (in solvent C) over 15 min with a 1 mL/min flow rate.

Synthesis of MRI Co-Agent
Compound 1: Cyclen (300 mg, 1.74 mmol) was dissolved in DMA (3.6 mL) and cooled to −20 • C and NaOAc (471 mg, 5.74 mmol) was added. Tert-butylbromoacetate (0.85 mL, 5.74 mmol) was dissolved in DMA (1.2 mL) and added dropwise to the cyclen solution over 30 min while maintaining the temperature. The reaction was then returned to room temperature and stirred for 24 h. The reaction mixture was then poured into water to give a clear solution, and KHCO 3 was added portionwise until a precipitate formed. The precipitate was filtered, washed adequately with water, and lyophilized to dryness to give a white solid (838 mg, 81% yield). 1  Compound 2: 4-Methoxybenzenesulfonyl chloride (200 mg, 0.968 mmol) and 2bromoethylamine hydrobromide (228 mg, 1.11 mmol) were suspended in DCM (3.3 mL) and cooled to 0 • C. Triethylamine (0.32 mL, 2.32 mmol) was added dropwise over 10 min, and the reaction mixture was stirred for 1 h. The reaction was diluted with DCM and washed with 1 M HCl two times followed by brine. The organic layer was dried over MgSO 4 and evaporated under reduced pressure. The resulting oil was purified by column chromatography over silica gel eluting with a gradient of 12% ethyl acetate to 100% ethyl acetate in hexanes over 10 column volumes to afford the title compound as a white solid (220 mg, 77% yield). 1  Compound 3: Compound 1 (118 mg, 0.198 mmol) was dissolved in ACN (2.3 mL), and K 2 CO 3 (82 mg, 0.594 mmol) was added. Compound 2 (70 mg, 0.238 mmol) was dissolved in ACN (0.59 mL). The reaction was cooled to 0 • C, and the solution of compound 2 was added dropwise. The reaction mixture was stirred overnight at room temperature, then K 2 CO 3 was removed via vacuum filtration. The filtrate was evaporated under reduced pressure, and the resulting oil was purified by prep HPLC and lyophilized to afford the title compound as a white solid (141 mg, 98% yield). 1  Compound 4: Compound 3 (1.447 g, 1.988 mmol) was dissolved in concentrated HCl (10 mL) and stirred for 3 h at room temperature. The solution was then evaporated under reduced pressure, redissolved in water, and filtered via a 0.2 µm syringe filter. The filtrate was lyophilized and used without further purification to afford the title compound as white solid (1.078 g, 97% yield). 1  Compound 5: Compound 4 (400 mg, 0.715 mmol) and GdCl 3 (226 mg, 0.858 mmol) were dissolved in 2 mL H 2 O, and the pH was raised to 5-6 with the addition of 1 M NaOH. The reaction mixture was heated to 90 • C and stirred for 12 h. The pH was then raised to 11-12, and the solution was centrifuged for 8 min at 4000 rpm. The supernatant was removed, and the pellet was washed with water two more times, centrifuging and removing the supernatant between each wash. The supernatants were combined and checked for free gadolinium using arsenazo III dye [22]. The solution was then neutralized with 1 M HCl and lyophilized. The resulting solid was dissolved in 95% DCM in MeOH and filtered via vacuum filtration to remove salt byproducts. The filtrate was evaporated under reduced pressure, redissolved in water, filtered via a 0.2 µm syringe filter, and lyophilized to afford the title compound as a white solid (510 mg, quant.

Radiosynthesis of PET Co-Agents
Compound 6: 1.51 mCi (about 700 µL) of [ 68 Ga]GaCl 3 in 0.05 M HCl was added to 300 µL of 1 M HEPES buffer, pH = 4.8. Then 20 µL of compound 4 (2 mg/mL solution in water) was added, and the reaction was heated to 85 • C for 10 min. Reaction completion was confirmed with radioHPLC. The reaction mixture was loaded onto a pre-conditioned C18 cartridge and eluted with 1 mL of a 1:1 PBS:ethanol mixture in 100 µL fractions to concentrate the solution. A non-decay-corrected radiochemical yield of 51% was obtained (n = 9) with a radiochemical purity of 98%.
Compound 7: 4.74 mCi (about 3 µL) of cyclotron produced [ 64 Cu]CuCl 2 in 0.1 M HCl was added to 100 µL of 0.1 M NaOAc buffer, pH = 5.6. 20 µL of compound 4 (2 mg/mL solution in water) was added, and the reaction was heated to 37 • C for 30 min. Reaction completion was confirmed with radioHPLC. The reaction mixture was loaded onto a preconditioned C18 cartridge and with 1 mL of a 1:1 PBS:ethanol mixture in 100 µL fractions to concentrate the solution. A non-decay-corrected radiochemical yield of 81% (n = 1) was obtained with a radiochemical purity of 99%.

pH-Relaxivity Calibration in Solution
A matrix of samples containing the MRI co-agent in 10 mM HEPES were made at concentrations of 0, 0.1, 0.5, 1.2, and 2 mM, and pH values from 4-9.8, with approximately 0.12 pH unit steps, for a total of 235 samples. Each sample was prepared in a PCR tube of 200 µL volume. Concentrations were confirmed using ICP-MS, and pH values were confirmed using a calibrated pH meter. Samples were arranged in a small box filled with 2% agarose designed to hold 30 samples and fit into a Bruker 72 mm MRI coil. The temperature of the samples was maintained at 37 • C with warm air, as validated with the NMR spectroscopy of ethylene glycol samples in an identical agarose-filled box and instrument setup [23].
The samples were imaged using a 7T MR scanner with a 30 cm horizontal bore equipped with 20 cm fixed gradients and Avance HD architecture, using a 72 mm transceiver volume coil (Bruker Biospin, Billerica, MA, USA). The following two MRI acquisition methods were used for the imaging experiment: (1) 2D coronal rapid acquisition with relaxation enhancement with variable repetition time (RAREVTR) (TE = 21.68 ms, 12  .524, 5000 ms, RARE factor = 8, echo spacing = 5.420 ms, 16 dummy scans, 1 average, 1 repetition, 1 coronal slice, slice thickness = 1 mm, 100 × 100 mm FOV, 128 × 128 matrix, 0.781 × 0.781 mm resolution). MR images were reconstructed, and T 1 times were calculated using ParaVision 6.0.1 (Bruker Biospin, Billerica, MA, USA). T 1 times from the first acquisition method were used for samples with 0, 0.1, and 0.5 mM concentrations, and T 1 times from the second acquisition method were used for the samples with 1.2 and 2 mM concentrations. T 1 times were then converted to R 1 relaxation rates. These rates were plotted versus concentration, and the slope of the line was used to determine r 1 relaxivity for each pH value. The r 1 relaxivity was then plotted versus pH values to produce a pH-relaxivity calibration curve. These data were fit to a modified Henderson-Hasselbach equation (Equation (4)) using Matlab R2021b (MathWorks, Natick, MA, USA). This equation was used to convert relaxivity to pH in subsequent PET/MRI experiments: where pKa is the pKa of the sulfonamide arm on the MRI co-agent, r 1 is the relaxivity of the measured sample, a is the relaxivity when the compound is completely protonated, and b is the relaxivity when the compound is completely deprotonated.

Imaging pH in Solution with PET/MRI
Samples were prepared in a 3 mL volume of 10 mM HEPES containing concentrations of 0.05, 0.1, 0.25, 0.5, and 0.8 mM of the MRI co-agent at 7 pH values ranging from 6.2-7.4 pH units. The concentrations of the MRI co-agent were confirmed using ICP-MS. Each sample was spiked with 10-45 µCi of the 68 Ga PET co-agent. The amount of PET co-agent was measured using a CRC-15R dose calibrator (Capintec, Inc., Florham Park, NJ, USA), and decay-corrected to the start of the PET/MRI scan. The samples were placed inside a 15 mL conical tube filled with 2% agarose.
All simultaneous PET/MRI scans were performed on the same 7T MRI instrument with a NuPET™ insert (Cubresa, Inc., Winnipeg, MB, USA) and a 35 mm MRI transceiver volume coil (Bruker Biospin, Billerica, MA, USA). For PET/MRI studies in solution, a simultaneous 30-min PET scan was obtained while also performing the two MRI acquisitions described in Section 2.4, except that an FOV of 38.4 × 38.4 mm was used for a resolution of 0.300 × 0.300 mm. MR image reconstructions and T 1 times were calculated using Par-aVision 6.0.1 (Bruker, Billerica, MA, USA). Random and decay corrections for PET images were applied through the Cubresa software. PET reconstructions were performed using an OSMAPOSL algorithm with 8 iterations and 4 subsets, and PET images were quantified using a Quantification Calibration Factor for 68 Ga or 64 Cu. PET VOIs and representative images were generated and analyzed using VivoQuant (Invicro LLC, Needham, MA, USA).
A VOI was drawn around the tube in the PET image, and the total amount of radioactivity in each sample was determined via the NuPET™ software. This value was converted to the concentration of the MRI co-agent using the known ratio of the PET-to-MRI co-agents in the sample, which simulated the process used to determine the concentration of the MRI co-agent during in vivo studies. The T 1 relaxation times were converted to R 1 relaxation rates. The value of ∆R 1 was calculated for each sample using the R 1 relaxation rate at 0 mM of MRI co-agent during the pH-relaxivity calibration curve experiments (Section 2.4). This value was divided by the calculated concentration of the MRI co-agent, which determined the r 1 relaxivity of the sample. Finally, this value for r 1 relaxivity was converted to a pH value for each sample using the pH-relaxivity calibration curve (Equation (4)). This value was compared to the pH of the sample measured with a calibrated pH meter. Statistical analysis was performed using Microsoft Excel (Microsoft, Corp., Redmond, WA, USA).

Mouse Model
All experiments with mice were approved by the Institutional Animal Care and Use Committee of the University of Texas MD Anderson Cancer Center (MDACC) and Rice University. MIA PaCa-2 pancreatic tumor cells were grown in Dulbecco's modified Eagle media (10-017-CV, Corning, Inc., Corning, NY, USA), with 10% FBS in a T75 flask. Female athymic nude mice were obtained from the MDACC Experimental Radiation Oncology mouse colony. Subcutaneous tumor models were generated by the subcutaneous injection of 50 µL of phosphate buffered saline, containing 1.5 million MIA PaCa-2 cells and 50 µL of Matrigel (Corning, Inc., Corning, NY, USA). The tumors were allowed to grow to 5 mm in diameter within 6 weeks.

Imaging pH In Vivo with PET/MRI
Two mice were used to test the 64 Cu PET co-agent, and one mouse was used to test the 68 Ga PET co-agent during in vivo PET/MRI studies. Each mouse was placed on a sled fitted with a nose cone, allowing the mouse to be anesthetized with 2% isoflurane, using oxygen as a carrier throughout the imaging experiment. A heated water pad under the mouse and temperature-controlled warm air (SA Instruments, Stony Brook, NY, USA) were used to maintain mouse temperature at 37 • C. The breathing rate was monitored throughout the experiment. Each mouse was catheterized via tail vein, and a 125 µL line was used to connect the needle to the syringe located outside of the scanner. This line was filled with a 25 µL lead of saline, followed by a 250 µL injection volume of the PET/MRI co-agents (which completely filled the line and partially filled the syringe). More specifically, 120 µCi (~80 µL) of the PET co-agent and 170 µL of a 30 mM solution of the MRI co-agent were injected in a slow bolus over 1 min, starting 1 min after initiating the DCE MRI scan (to acquire 1 min of baseline images prior to injection; see acquisition method 4 described in the next paragraph). Then, 125 µL of saline was then used to completely flush the co-agents out of the line and into the mouse, so the mice received a total injection volume of 275 µL. The concentration of the injected MRI co-agent was confirmed using ICP-MS. The injected dose of the PET co-agent was calculated by measuring the pre-and post-injection activity in the syringe using a CRC-15R dose calibrator (Capintec, Inc., Florham Park, NJ, USA), and decay-corrected to the start of the scan. It was assumed that the percentage loss of the PET and MRI co-agents in the syringe was equal.
The following MRI acquisitions were obtained for all in vivo imaging sessions: (1) a localizer image to ensure proper placement of the mouse in the PET/MRI system; (2) preinjection 2D coronal RARE (TE = 43.99 ms, TR = 1200 ms, RARE factor = 8, echo spacing = 5.499 ms, 2 dummy scans, 2 averages, 1 repetition, 9 slices, slice thickness = 1 mm, 58.8 × 38.4 mm FOV, 196 × 128 matrix, 0.300 × 0.300 mm in-plane resolution); (3) 2D coronal RAREVTR (TE = 27.12 ms, 6 TR = 500, 650, 1000, 1500, 2500, 5000 ms, RARE factor = 8, echo spacing = 6.78 ms, 2 dummy scans, 2 averages, 1 repetition, 9 slices, slice thickness = 1 mm, 58. 8  The dynamic PET scan was obtained simultaneously with the DCE MRI scan. Random and decay corrections for PET images were applied through the NuPET™ software. For the dynamic PET analysis, data were binned into 2-min time frames over the course of the 16-min dynamic scan. To produce static images, data were binned over the course of the entire 16-min PET scan. PET reconstructions were performed using an Ordered Subset Maximum a Posteriori One Step Late (OMAPOSL) algorithm with 8 iterations and 4 subsets, and PET images were quantified using a Quantification Calibration Factor for 68 Ga or 64 Cu. MRI reconstructions were performed using ParaVision 6.0.1 (Bruker Biospin, Billerica, MA, USA). PET/MR image registration was manually performed using the pre-injection MR image and VivoQuant (Invicro, LLC, Needham, MA, USA). PET VOIs and representative PET/MR images were also generated and analyzed using VivoQuant. Injected doses were used to calculate the percentage of injected dose per cubic centimeter of tissue (%ID/cc). Errors in the averaged %ID/cc were reported as standard deviation. MRI RAREVTR and DCE data were analyzed using Matlab R2021b (MathWorks, Natick, MA, USA).
After the reconstruction and registration of the PET/MR images, a VOI was drawn over the tumor using the anatomical MR image for reference. The total amount of radioactivity in the tumor was determined via the imaging software for each 2-min dynamic PET scan, which was decay-corrected to the start of the scan. This value was converted to the concentration of the MRI co-agent in the tumor for each time frame, using the known ratio of the PET-to-MRI co-agents in the injection volume and the physical tumor volume. The RAREVTR and DCE MR images were analyzed with Matlab to determine the relaxation rate for each 7.6 s MRI frame. The averages of the pre-injection frames of the DCE scan were subtracted from each post-injection frame, to determine ∆R 1 for each time frame. ∆R 1 was divided by the calculated MRI co-agent concentration for each 2-min time frame to determine relaxivity. Once the relaxivity reached a steady value, these relaxivity values were averaged, and the average value was used, with the modified Henderson-Hasselbach equation (Equation (4)), to determine tumor pHe.

Stability and Metabolism Studies of PET Co-Agents
The 68 Ga PET co-agent (~100 µCi,~100 µL) or 64 Cu PET co-agent (~100 µCi,~20 µL) was incubated in 5× volume of human serum or PBS at 37 • C. Aliquots were removed every 20 min and subjected to radioHPLC to determine the stability of the PET co-agent. For the 64 Cu co-agent, an incubation in human serum and a PBS at 37 • C were also performed in the presence of a 100 mM concentration of the MRI co-agent. Aliquots were again removed every 20 min and subjected to radioHPLC to determine the stability of the 64 Cu PET co-agent.
Two tumor-bearing mice (one for testing the 68 Ga PET co-agent, and one for testing the 64 Cu PET co-agent) were anesthetized with 2% isoflurane using oxygen as a carrier and injected i.v., with approximately 120 µCi (~80 µL) of the PET co-agent, and 170 µL of a 30 mM solution of the MRI co-agent. Mice remained anesthetized for twenty min, then urine was extracted, and the mice were sacrificed via cervical dislocation. All urine samples were treated with 2 × their volume of acetonitrile. The samples were mixed thoroughly and subjected to centrifugation for 10 min at 4000 rpm. The acetonitrile layer was removed and injected into the radioHPLC to determine the composition of the PET co-agent.

Synthesis of PET/MRI Co-Agents
The MRI co-agent was synthesized with an overall yield of 59% over 5 steps (Scheme 1). The intermediates and final product were confirmed with NMR spectroscopy (Figures S1-S4) and LRMS (Figures S5-S9). Because free Gd metal could drastically affect relaxivity values, and is also as a known toxin [24], the absence of free Gd was confirmed at the end of each chelation using arsenazo III, which turns blue in the presence of the free metal ion (Scheme 1 inset) [22]. The 68 Ga PET co-agent was synthesized with a radiochemical yield of 51% and a radiochemical purity of 98% (Scheme 2a). The 64 Cu PET co-agent was synthesized with a radiochemical yield of 81% and a radiochemical purity of 99% (Scheme 2b).

pH-Relaxivity Calibration
Two different MRI acquisition methods were used for the creation of the calibration curve, because higher relaxation rates required shorter experimental TR times to obtain accurate T 1 measurements. The pH-relaxivity calibration curve was fit using a modified Henderson-Hasselbach equation (Equation (4)) and the known pKa of 6.7 of the MRI co-agent [21]. The constants a and b were calculated to be 6.07 mM −1 s −1 and 1.77 mM −1 s −1 , respectively ( Figure 2). Residuals demonstrated the good fit of the data.

pH-Relaxivity Calibration
Two different MRI acquisition methods were used for the creation of the calibration curve, because higher relaxation rates required shorter experimental TR times to obtain accurate T1 measurements. The pH-relaxivity calibration curve was fit using a modified

pH-Relaxivity Calibration
Two different MRI acquisition methods were used for the creation of the calibration curve, because higher relaxation rates required shorter experimental TR times to obtain accurate T1 measurements. The pH-relaxivity calibration curve was fit using a modified Henderson-Hasselbach equation (Equation (4)) and the known pKa of 6.7 of the MRI co- agent [21]. The constants a and b were calculated to be 6.07 mM −1 s −1 and 1.77 mM −1 s −1 , respectively ( Figure 2). Residuals demonstrated the good fit of the data. The MRI co-agent displayed pH-dependent relaxivities in a 7T MR scanner. (a) A phantom holder for pH-relaxivity calibration curve studies contained 2% agarose to reduce B0 and B1 inhomogeneities. (b) The pH responsive MRI co-agent undergoes protonation of its sulfonamide arm at low pH values, which allows for an additional water to occupy the inner sphere and interact with the gadolinium core. This leads to an increase in the relaxation rate of bulk water. At high pH values, this arm is deprotonated and bound to gadolinium, which leads to a decrease in the relaxation rate of bulk water. (c) Relaxation rates were calculated from measured T1 times of samples at various pH values and concentrations of the MRI co-agent. Relaxivities were calculated from the relaxation rates and concentrations, and the pH-relaxivity curve was fit to a modified Henderson-Hasselbach equation, where a is the r1 relaxivity at complete agent protonation and b is the r1 relaxivity at complete agent deprotonation. The image insert is a representative MR image of one sample box, where samples with increasingly higher concentrations of MRI co-agent appear increasing brighter towards the right side of the image. (d) The residuals of the fit of the pH-relaxivity curve demonstrated the good fit of the data.

Imaging pH in Solution with PET/MRI
Similar to the samples for the pH-relaxivity calibration curve, the MRI acquisition method with shorter experimental TR times was required for samples of higher MRI coagent concentration (0.8 mM), while samples with lower concentrations could be analyzed with longer experimental TR times. The PET/MRI co-agents were able to accurately measure pH in solution, but the precision was dependent on the concentration of the MRI coagent. At the highest concentration of MRI co-agent (0.8 mM), a standard error of 0.08 pH units was achieved, compared to measurements from a calibrated pH meter (Figure 3a). When lower concentrations of the MRI co-agent were included (0.8, 0.5, and 0.25 mM), the standard error of pH measurements increased to 0.27 pH units (Figure 3b). An analysis using Lin's Concordance Correlation Coefficient showed that the pH measurements from PET/MRI and a calibrated pH meter were highly correlated at higher MRI co-agent concentrations (Figure 3c). This pH measurement methodology used experimental PET results coupled with the known ratio of the co-agents in each sample to estimate the concentration of the MRI contrast agent. This concentration measurement from PET/MRI matched the MRI agent concentration determined by ICP-MS, with high precision (R 2 = 0.997) and high accuracy (LCCC = 0.998; Figure 3d). Therefore, the errors in pH Figure 2. The MRI co-agent displayed pH-dependent relaxivities in a 7T MR scanner. (a) A phantom holder for pH-relaxivity calibration curve studies contained 2% agarose to reduce B0 and B1 inhomogeneities. (b) The pH responsive MRI co-agent undergoes protonation of its sulfonamide arm at low pH values, which allows for an additional water to occupy the inner sphere and interact with the gadolinium core. This leads to an increase in the relaxation rate of bulk water. At high pH values, this arm is deprotonated and bound to gadolinium, which leads to a decrease in the relaxation rate of bulk water. (c) Relaxation rates were calculated from measured T 1 times of samples at various pH values and concentrations of the MRI co-agent. Relaxivities were calculated from the relaxation rates and concentrations, and the pH-relaxivity curve was fit to a modified Henderson-Hasselbach equation, where a is the r 1 relaxivity at complete agent protonation and b is the r 1 relaxivity at complete agent deprotonation. The image insert is a representative MR image of one sample box, where samples with increasingly higher concentrations of MRI co-agent appear increasing brighter towards the right side of the image. (d) The residuals of the fit of the pH-relaxivity curve demonstrated the good fit of the data.

Imaging pH in Solution with PET/MRI
Similar to the samples for the pH-relaxivity calibration curve, the MRI acquisition method with shorter experimental TR times was required for samples of higher MRI coagent concentration (0.8 mM), while samples with lower concentrations could be analyzed with longer experimental TR times. The PET/MRI co-agents were able to accurately measure pH in solution, but the precision was dependent on the concentration of the MRI co-agent. At the highest concentration of MRI co-agent (0.8 mM), a standard error of 0.08 pH units was achieved, compared to measurements from a calibrated pH meter (Figure 3a). When lower concentrations of the MRI co-agent were included (0.8, 0.5, and 0.25 mM), the standard error of pH measurements increased to 0.27 pH units (Figure 3b). An analysis using Lin's Concordance Correlation Coefficient showed that the pH measurements from PET/MRI and a calibrated pH meter were highly correlated at higher MRI co-agent concentrations (Figure 3c). This pH measurement methodology used experimental PET results coupled with the known ratio of the co-agents in each sample to estimate the concentration of the MRI contrast agent. This concentration measurement from PET/MRI matched the MRI agent concentration determined by ICP-MS, with high precision (R 2 = 0.997) and high accuracy (LCCC = 0.998; Figure 3d). Therefore, the errors in pH measurements by PET/MRI (Figure 3a,b) are most likely, due to more inaccurate MRI relaxation rate measurements than inaccurate estimates of MRI agent concentrations.
Biosensors 2021, 11, x 11 of 17 measurements by PET/MRI (Figure 3a,b) are most likely, due to more inaccurate MRI relaxation rate measurements than inaccurate estimates of MRI agent concentrations.

Imaging In Vivo Tumor pHe with PET/MRI
In a proof-of-concept study, a mouse with a subcutaneous tumor of MIA PaCa-2 pancreatic cancer was scanned using simultaneous PET/MRI with the MRI co-agent and the 68 Ga version of the PET co-agent (Figure 4a). PET and MR image registration facilitated the identification of the tumor in the PET images (Figure 4b,d). The dynamic changes in ΔR1 relaxation rate (Figure 4c) and PET-derived MRI co-agent concentration (Figure 4e) were monitored at 7.6-sec and 2-min temporal resolutions, respectively, as averaged for the tumor region in the image. Fortunately, ΔR1 is linearly dependent on the concentration of the MRI co-agent (Equation (3)), so that the fast measurements of ΔR1 could be binned in 2-min intervals without concerns of improper weighting (a non-linear dependence would raise concerns about improper weighting in this binning process). The r1 relaxivity was determined from ΔR1 and concentration from each two-minute interval, and converted to pHe based on the pH-relaxivity calibration (Figure 2c). This pHe value was found to be consistent for the four measurements, made eight min after injection. The average of these four pHe measurements after eight min post-injection was 6.76 ± 0.12 pH units. This pH value agreed with previous studies of the subcutaneous flank model of MIA PaCa-2 pancreatic cancer [25,26], and other small animal models of human cancers that have moderate tumor metabolism [4,8,10,27,28].

Imaging In Vivo Tumor pHe with PET/MRI
In a proof-of-concept study, a mouse with a subcutaneous tumor of MIA PaCa-2 pancreatic cancer was scanned using simultaneous PET/MRI with the MRI co-agent and the 68 Ga version of the PET co-agent (Figure 4a). PET and MR image registration facilitated the identification of the tumor in the PET images (Figure 4b,d). The dynamic changes in ∆R 1 relaxation rate (Figure 4c) and PET-derived MRI co-agent concentration (Figure 4e) were monitored at 7.6-sec and 2-min temporal resolutions, respectively, as averaged for the tumor region in the image. Fortunately, ∆R 1 is linearly dependent on the concentration of the MRI co-agent (Equation (3)), so that the fast measurements of ∆R 1 could be binned in 2-min intervals without concerns of improper weighting (a non-linear dependence would raise concerns about improper weighting in this binning process). The r 1 relaxivity was determined from ∆R 1 and concentration from each two-minute interval, and converted to pHe based on the pH-relaxivity calibration (Figure 2c). This pHe value was found to be consistent for the four measurements, made eight min after injection. The average of these four pHe measurements after eight min post-injection was 6.76 ± 0.12 pH units. This pH value agreed with previous studies of the subcutaneous flank model of MIA PaCa-2 pancreatic cancer [25,26], and other small animal models of human cancers that have moderate tumor metabolism [4,8,10,27,28].  Our simultaneous PET/MRI methodology was used to image two additional mice with a subcutaneous flank MIA PaCa-2 tumor, using the 64 Cu-based PET co-agent along with the MRI co-agent ( Figure S10a). Unfortunately, the PET images showed poor tumor uptake and high liver uptake of the 64 Cu radionuclide. The low PET detection in the tumor was insufficient to estimate tumor pHe. This observation was made with both mice, indicating that this poor tumor uptake 64 Cu radionuclide was reproducible.

Stability and Metabolism Studies of PET Co-Agent
Stability studies of the 68 Ga PET co-agent in PBS and human serum showed complete stability of the agent for up to 1 h (Figure 5a). The 64 Cu PET co-agent also demonstrated complete stability in PBS and human serum for up to 1 h ( Figure S10). In addition, the 64 Cu PET co-agent was challenged in the presence of the MRI co-agent, to determine if the chemical equilibrium of the MRI co-agent led to the dechelation of the Cu ion. The compound was found to be completely stable in the presence of the MRI co-agent ( Figure S10).
The urine of the mice injected with the PET/MRI co-agents showed no presence of the intact PET co-agents (Figure 5b and S11). For the 68 Ga PET co-agent, two species were identified with radioHPLC, and neither species matched the intact agent or free 68 Ga (Figure 5b). For the 64 Cu PET co-agent, the only species present in the urine was free 64 Cu, indicating the de-chelation or transchelation of this 64 Cu-based agent in vivo ( Figure S11b). This result was consistent with our in vivo PET/MRI results with the 64 Cu PET co-agent, which showed low uptake of the 64 Cu radionuclide in the tumor, which is expected if dechelation or transchelation occurs. Our simultaneous PET/MRI methodology was used to image two additional mice with a subcutaneous flank MIA PaCa-2 tumor, using the 64 Cu-based PET co-agent along with the MRI co-agent ( Figure S10a). Unfortunately, the PET images showed poor tumor uptake and high liver uptake of the 64 Cu radionuclide. The low PET detection in the tumor was insufficient to estimate tumor pHe. This observation was made with both mice, indicating that this poor tumor uptake 64 Cu radionuclide was reproducible.

Stability and Metabolism Studies of PET Co-Agent
Stability studies of the 68 Ga PET co-agent in PBS and human serum showed complete stability of the agent for up to 1 h (Figure 5a). The 64 Cu PET co-agent also demonstrated complete stability in PBS and human serum for up to 1 h ( Figure S10). In addition, the 64 Cu PET co-agent was challenged in the presence of the MRI co-agent, to determine if the chemical equilibrium of the MRI co-agent led to the dechelation of the Cu ion. The compound was found to be completely stable in the presence of the MRI co-agent ( Figure S10).
The urine of the mice injected with the PET/MRI co-agents showed no presence of the intact PET co-agents (Figure 5b and Figure S11). For the 68 Ga PET co-agent, two species were identified with radioHPLC, and neither species matched the intact agent or free 68 Ga (Figure 5b). For the 64 Cu PET co-agent, the only species present in the urine was free 64 Cu, indicating the de-chelation or transchelation of this 64 Cu-based agent in vivo ( Figure S11b). This result was consistent with our in vivo PET/MRI results with the 64 Cu PET co-agent, which showed low uptake of the 64 Cu radionuclide in the tumor, which is expected if de-chelation or transchelation occurs. iosensors 2021, 11, x 13 of 17

Discussion
We developed the synthesis of the MRI co-agent, with an overall yield of 59%, which improved on the previously reported synthesis of this agent, which had an overall yield of 17% [21]. All compounds including the DOTA ligand framework required purification by HPLC due to the basicity of the nitrogen atoms in the ligand, and their interaction with acidic normal phase silica. The purification of the final chelated MRI co-agent proved difficult due to high acid sensitivity, preventing the use of TFA in the HPLC solvent system. We found that the use of lower concentrations of formic acid led to the minimal dechelation of the complex during purification. Chelations of the radiometals were performed in high radiochemical yields, with short reaction times and high radiochemical purity. The low concentration of 68 Ga in the eluent from the generator was acceptable for the smallscale reactions in our studies. However, a large-scale production in the future will benefit from the pre-concentration of the 68 Ga eluent [29], or the use of lower volume cyclotronproduced 68 Ga [30].
A large excess of the precursor was used in the radiochemical reactions, and was not removed during C18 cartridge purification. However, only the ratio of PET radioactivity (in units of μCi) to MRI concentration (in units of mM) was necessary for our pH measurements, so that this precursor did not affect our results. Moreover, if our approach with PET/MRI co-agents was used to detect a molecular biomarker such as a cell receptor, the excess precursor, as well as the high concentration of MRI co-agent, would out-compete the radiolabeled PET co-agent for the molecular target, essentially becoming a classic "blocking study" of a targeting PET agent [31]. Fortunately, the pHe of the tumor microenvironment is an environmental biomarker rather than a molecular biomarker, so that the radiolabeled PET co-agent does not compete with excess precursor or MRI co-agent to  Figure 4. The results showed the presence of two new species (blue trace) that were different than intact 68 Ga PET co-agent (green trace) or free 68 Ga (orange trace).

Discussion
We developed the synthesis of the MRI co-agent, with an overall yield of 59%, which improved on the previously reported synthesis of this agent, which had an overall yield of 17% [21]. All compounds including the DOTA ligand framework required purification by HPLC due to the basicity of the nitrogen atoms in the ligand, and their interaction with acidic normal phase silica. The purification of the final chelated MRI co-agent proved difficult due to high acid sensitivity, preventing the use of TFA in the HPLC solvent system. We found that the use of lower concentrations of formic acid led to the minimal dechelation of the complex during purification. Chelations of the radiometals were performed in high radiochemical yields, with short reaction times and high radiochemical purity. The low concentration of 68 Ga in the eluent from the generator was acceptable for the small-scale reactions in our studies. However, a large-scale production in the future will benefit from the pre-concentration of the 68 Ga eluent [29], or the use of lower volume cyclotronproduced 68 Ga [30].
A large excess of the precursor was used in the radiochemical reactions, and was not removed during C18 cartridge purification. However, only the ratio of PET radioactivity (in units of µCi) to MRI concentration (in units of mM) was necessary for our pH measurements, so that this precursor did not affect our results. Moreover, if our approach with PET/MRI co-agents was used to detect a molecular biomarker such as a cell receptor, the excess precursor, as well as the high concentration of MRI co-agent, would out-compete the radiolabeled PET co-agent for the molecular target, essentially becoming a classic "blocking study" of a targeting PET agent [31]. Fortunately, the pHe of the tumor microenvironment is an environmental biomarker rather than a molecular biomarker, so that the radiolabeled PET co-agent does not compete with excess precursor or MRI co-agent to exist in this tumor microenvironment. Therefore, measuring tumor pHe is an outstanding application for our PET/MRI co-agent approach.
A major assumption of our PET/MRI approach is that the PET and MRI co-agents are delivered to the tumor in the same ratio as in the injection volume. Our use of 68 Ga was a logical approach for designing the PET co-agent, because the 68 Ga-based PET co-agent has the same charge as the Gd-based MRI co-agent, and the DOTA derivative is identical for the PET and MRI co-agents. Therefore, the PET and MRI co-agents should have the same pharmacokinetic delivery to tumors [32][33][34]. Our in vitro tests in PBS and human serum showed that both PET co-agents were stable, which supported our assumption. However, each PET co-agent demonstrated instability in vivo, raising concerns that a loss of the metal ion will change the charge of the complex, and invalidate the assumption of identical pharmacokinetics of the PET and MRI co-agents. 64 Cu is known to de-chelate from DOTA, and can be easily transchelated by enzymes in the liver, which often leads to high retention of the metal ion in the liver [35]. This was observed in our in vivo PET/MR images with the 64 Cu PET co-agent (Figure 5a), and was validated by the radioHPLC of extracted urine post-injection ( Figure 5b). Therefore, a 64 Cu-based PET agent was an unsuccessful choice for our PET/MRI co-agent approach.
Interestingly, radioHPLC from urine at 20 min p.i. from mice injected with the 68 Ga PET co-agent showed two polar species that are not free 68 Ga, suggesting in vivo metabolism of the DOTA derivative in this PET co-agent, rather than de-chelation ( Figure 4b). Despite this evidence for degradation, the PET/MRI co-agents using 68 Ga were able to measure tumor pHe during a 16-min dynamic PET/MRI scan. This result suggests that the PET co-agent may be stable within the tumor extracellular microenvironment, and only metabolized during excretion from the body. Therefore, a 68 Ga-based PET agent was a useful choice for our initial in vivo PET/MRI approach.
Similar to the development of other biosensors and pharmaceutical agents, our next phase of development could include the refinement of the PET/MRI co-agents to reduce in vivo metabolism and increase biocompatibility. For example, additional ligands may be introduced to the co-agents to improve their hydrophilicity. These improvements would directly lead to safety and toxicity tests that will be required for eventual approval for clinical use. In addition, our in vivo tests of the 68 Ga PET co-agent used human serum, while our in vivo tests exposed this agent to mouse serum. While this difference in sera may be inconsequential, future in vitro tests to refine the PET/MRI co-agents should use mouse serum to be consistent with in vivo pre-clinical studies.
The PET/MRI co-agents accurately measured pH in solution, although the precision of this pH measurement was dependent on the concentration of the MRI co-agent (Figure 3a,b). Different applications of pHe measurements can accommodate different standard errors in pH measurements (Figure 1b). For example, tumors typically have a pHe that is substantially lower than normal tissue, inflammation, and infection [3,7,8]. A PET/MRI measurement of pHe with a lower co-agent concentration that has a standard error of 0.27 units (Figure 3b) would be acceptable for distinguishing tumor versus these other tissue types. Similarly, malignant tumors can have high glycolytic metabolism relative to benign tumors, which may cause a large difference in pHe that can accommodate lower diagnostic precision [36]. However, tumor pHe changes during early response to therapy are closer to 0.1-0.2 pH units [10,11], so that higher concentrations of the MRI co-agent will be needed to accurately detect early therapeutic effects. Importantly, our results indicated that even moderate errors in 68 Ga radioactivity measurements were still able to precisely measure MRI co-agent concentrations (Figure 3d). Therefore, we attribute the errors in pH measurements to the MRI process of our approach. Higher concentrations of the MRI co-agent and more accurate ways to measure T 1 times will lead to improvements in pH estimates with simultaneous PET/MRI.
Our in vivo studies demonstrated that PET/MRI co-agents can be used to measure pHe in the microenvironment of a subcutaneous flank tumor model of pancreatic cancer following 6 weeks of tumor growth to reach a 5 mm diameter. This demonstration can be expanded in the future to evaluate other tumor models, including models of other cancer types; models with orthotopically implanted tumors or spontaneously forming tumors; and tumors with different stages of growth and volume. For these future studies, a solid tumor must have a patent vascular system that allows for the sufficient uptake of the co-agents for detection with MRI and PET. For example, severely necrotic tumors that have little or no patent vasculature would not be good candidates for evaluation with PET/MRI co-agents. However, measurements of tumor acidosis are more relevant for metabolically active tumors than for severely necrotic tumors, which mitigates this limitation.

Conclusions
Radiometal-based PET/MRI co-agents were synthesized in high yields and purity. The r 1 relaxivity of the MRI co-agent depended on pH, the ∆R 1 increase in relaxation rate caused by the MRI co-agent could be measured with MRI, the PET radioactivity measurements could accurately estimate the concentration of the MRI co-agent, and these results could be combined to accurately measure pH, with a standard error as low as 0.08 pH units. The 64 Cu PET co-agent experienced transchelation in vivo, and was not able to measure tumor pHe using PET/MRI. Despite evidence that the 68 Ga PET co-agent degraded in urine after 20 min, this PET co-agent and the MRI co-agent were used to measure in vivo tumor pHe within 16 min. This initial study demonstrated a feasible workflow for using PET/MRI co-agents to measure tumor pHe, and indicated future improvements for simultaneous PET/MRI.


s2fieldsofstudy: Biology Medicine

text:
Serine protease inhibitor derived from Trichinella spiralis (TsSERP) inhibits neutrophil elastase and impairs human neutrophil functions

During early infection with Trichinella spiralis, host neutrophils destroy newborn larvae migrating in the bloodstream, preventing infection. However, parasites secrete various immunomodulatory molecules to escape the host’s defense mechanisms, allowing them to infect the host and live for long periods. T. spiralis secretes serine protease inhibitors (TsSERPs), which are key inhibitory molecules that regulate serine proteases involved in digestion and inflammation. However, the modulatory roles of TsSERP in the inhibition of neutrophil serine proteases (NSPs) and neutrophil functions are unknown. Therefore, the immunomodulatory properties of recombinant TsSERP1 (rTsSERP1) on NSPs and neutrophil functions were investigated in this study. rTsSERP1 preferentially inhibited human neutrophil elastase (hNE). In addition, incubation of rTsSERP1 with fMLP-induced neutrophils impaired their phagocytic ability. The formation of neutrophil extracellular traps (NETs) was activated with phorbol myristate acetate (PMA), and NETs were dramatically reduced when treated with rTsSERP1. Furthermore, rTsSERP1 suppressed the production of proinflammatory cytokines and chemokines during neutrophil activation, which are essential for neutrophil-mediated local or systemic inflammation regulation. In conclusion, T. spiralis immune evasion mechanisms are promoted by the inhibitory properties of TsSERP1 against neutrophil elastase and neutrophil defense functions, and these might be promising alternative treatment targets for inflammatory disorders.

Introduction
Trichinella spiralis is a harmful food-borne zoonotic nematode that has a detrimental effect on human and animal health worldwide (Murrell and Pozio, 2011). Infection occurs after ingesting raw or inadequately cooked meat carrying encapsulated first-stage larvae (TsL1). The parasite matures to the adult stage in the small intestine and releases newborn larvae (NBL), which infect muscle tissues and remain there as the infective stage (TsL1) for several years (Fröscher et al., 1988). To survive long-term in their hosts, T. spiralis uses various methods to modulate host defenses, including intracellular infection, nurse cell formation, and immunomodulation (Despommier, 1998;Ashour, 2013). Previous studies reported all life stages of T. spiralis released immunomodulatory molecules that modulated host cellular and humoral immune responses, which altered immune cells such as macrophages, dendritic cells, neutrophils, and lymphocytes (Aranzamendi et al., 2012;Bai et al., 2012;Song et al., 2019;Sun et al., 2019).
Serine protease inhibitors or serpins (TsSERPs) have been identified in excretory-secretory products of all developmental stages of T. spiralis. These proteins not only play important roles in larval infectivity (Song et al., 2018;Yi et al., 2020), they also regulate host anti-inflammatory immune responses by mediating alternatively activated macrophages (AAMf), regulatory T cells (Treg), CD8 + CD28 − immunosenescent T cells, and regulatory B cells (Breg) Xu et al., 2021b). Neutrophils are key cells that have critical roles in limiting T. spiralis infection (Bass and Szejda, 1979a;Bass and Szejda, 1979b). However, T. spiralis can evade neutrophil immunity and cause chronic infection. How T. spiralis evades neutrophil immune mechanisms is unknown.
During neutrophil immune responses, the release of neutrophil serine proteases (NSPs) including neutrophil elastase (NE), cathepsin G (CG), and proteinase-3 (PR3) facilitate direct killing by cleavage of pathogen outer membrane, phagocytosis, release of proinflammatory cytokines and chemokines, inflammation, and the formation of neutrophil extracellular traps (NETosis) (Pham, 2008;Cassatella et al., 2019). The NE has been associated with the formation of NETs. Mechanistically, the mitogen phorbol 12-myristate 13acetate (PMA), an in vitro experiment inducer, activates the Raf-Mek-Erk pathway, which activates protein kinase C (PKC) and then produces ROS via NADPH oxidase, releasing NE from granules into the cytoplasm. The NE then translocates to the nucleus and cleaves histones, causing nuclear membrane disintegration, chromatin expansion, and finally cell lysis and NET release (Rosazza et al., 2021). Therefore, the inhibition of NSPs activity most likely necessitates T. spiralis escaping these frontline immune defenses. In a previous study, human serpins a1-PI, serpinB1, and secretory leukocyte inhibitor (SLPI) blocked NSPs, particularly NE, which reduced inflammation-related severity and excessive elastase-induced tissue damage in a mouse model of chronic obstructive pulmonary disease (COPD) (Kelly-Robinson et al., 2021).
Several TsSERP isoforms have been identified and characterized. The first TsSERP isoform (TsSERP1) identified by (Nagano et al., 2001) was studied further because it selectively inhibited neutrophil elastase (found in this study). Subsequently, the inhibitory properties of TsSERP1 on neutrophil functions including phagocytosis, NETosis, and cytokine and chemokine responses were described. The impact of TsSERP1 on neutrophil functions described here will help researchers better understand T. spiralis immunology, and the underlying immunomodulatory mechanisms might be an alternative therapeutic target for inflammatory diseases.

Ethics statement
All human study and data experiment protocols were reviewed and approved by the local Institutional Review Board, The Human Research Ethics Committee of the Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand (MUTM 2021-013-01), with all participants signing informed consent prior to blood collection. All experiments were performed in accordance with relevant guidelines and regulations.
The inhibition constant (K i ) of TsSERP1 for hNE was determined using a Dixon plot according to a previous publication with some modifications (Toubarro et al., 2013). rTsSERP1 (0, 20, 40 and 80 nM) was incubated with 10 nM of hNE for 15 min at 37°C; then, 50, 100 and 200 μM of MeOSuc-AAPV-AMC (Calbiochem) was added to the elastase reactions.

Isolation of human neutrophils
Human neutrophils were isolated from peripheral venous blood of three healthy donors aged between 20-50 years old according to a previous publication with some modifications (Heit et al., 2006). In summary, 20 ml peripheral venous blood was drawn from each donor followed by collection in heparinized tubes to avoid blood clotting. The red blood cells (RBCs) were removed using dextran sedimentation. Subsequently, the leukocyte-rich plasma separated from the top layer was transferred into a 15 ml conical tube followed by centrifugation at 700 ×g for 10 min and the supernatant was discarded. The remaining RBCs were lysed with ice-cold ddH 2 O for 30 s and then mixed with 0.6 M KCl prior to dilution with 1×PBS before centrifugation. The pellet was resuspended in 1×PBS and the polymorphonuclear cells (PMNs) were collected by gradient centrifugation using lymphocyte separating medium (LSM; MP biomedicals, Cat. No:50494, Illkirch, France). The viability and purity of neutrophils were determined using trypan blue and Giemsa staining, respectively, which revealed that they were > 90% viable and 95% neutrophils pure, but with only 2% eosinophil, 1% monocyte and 2% lymphocytes contamination.

Cytotoxicity analysis of rTsSERP1
The cytotoxicity of rTsSERP1 on human neutrophils was evaluated by MTT assay kit (Sigma-Aldrich, Cat. NO:11465007001, Saint Louis, MO, USA) according to manufacturer's protocol. The cells were seed into a 96-well culture plate at a density of 3 × 10 4 cells/ 200 μl/well, followed by treatment with different concentrations of rTsSERP1 (0, 1.25, 2.5, 5, 10, and 20 μg/ml). Media without the cells was used as the blank. After incubation for 4 h, the 0.5 mg/ml of MTT solution was added, followed by additional incubating for 4 h. The supernatant was discarded prior to add 100 μl of DMSO. Subsequently, the optical density (OD) at a wavelength of 570 nm was measured using the Sunrise ™ absorbance reader (Tecan Group Ltd, Männedorf, Switzerland). All assays were performed in triplicate with three donors and the percentage of cell viability was calculated as below.
% cell viability = OD of treatment group − OD of blank control OD of untreated group − OD of blank control Â 100 Inhibitory effect of rTsSERP1 on neutrophil elastase released from human neutrophils Elastase release and inhibition assay were performed according to previous publication with some modifications (Morais et al., 2018). Briefly, human neutrophils were plated into a 96-well culture plate at a density of 2 × 10 5 cells/200 ml/ well. Elastase release and inhibitory effects were induced by stimulation with 100 nM of N-formylmethionyl-leucylphenylalanine (fMLP) (dissolve in DMSO) (Sigma-Aldrich, Cat. No:F3506, Saint Louis, MO, USA) for 10 min prior to the addition of 40 mM of rTsSERP1 or recombinant mouse dihydrofolate reductase (rmDHFR) (irrelevant control protein) at 37°C for 1 h. Treatment with fMLP alone and non-treatment (only media) were used as positive and negative controls, respectively. After incubation, 100 ng/ml of colorimetric neutrophil elastase substrate (elastase substrate I; Calbiochem ® , Cat. No:70967-90-7) was added into each reaction and the colorimetric reaction was immediately monitored at a wavelength of 405 nm every 10 min until 1 h. The percentage of neutrophil elastase activity was calculated at 1 h of kinetic assay. The experiment was performed in triplicate and the results were reported as a change in absorbance per minute. 4-(2-aminoethyl) benzenesulfonyl fluoride hydrochloride (AEBSF) (Sigma-Aldrich, Cat. No:A8456, Saint Louis, MO, USA) at 0.1 mM was used as an inhibitory control for neutrophil elastase. All assays were performed in triplicate with three donors.

Inhibitory effect of rTsSERP1 on neutrophil phagocytosis
The effect of rTsSERP1 on neutrophil phagocytic functions was evaluated by a Vybrant ™ Phagocytosis Assay Kit (Thermo Fisher Scientific Inc., Cat No: V6694, Waltham, USA) according to the manufacturer's protocol. Human neutrophils at a density of 2 × 10 5 cells/well were placed into each well of a 96-well fluorescent microplate. The experiment and control were set up under four different conditions including 1) only fluorescent E. coli BioParticle as a blank control, 2) untreated neutrophils (only media) incubated with fluorescent E. coli BioParticle as mock, 3) fMLP + neutrophils incubated with fluorescent E. coli BioParticle as a positive control, and 4) fMLP + neutrophils treated with rTsSERP1 or rmDHFR and incubated with fluorescent E. coli BioParticle as the test sample. After cell adherence, neutrophils were stimulated by incubation with 100 nM fMLP for 30 min followed by adding 10 μg/ml rTsSERP1 or 10 μg/ml rmDHFR for 1 h. After removing the culture media, 100 μl of the fluorescent E. coli BioParticle suspension was added into each well and incubated further for 2 h. The BioParticle suspension was removed and added 100 μl of trypan blue to quench the fluorescence of the extracellular particles. The ability of phagocytosis was detected after removal of the trypan blue. The intracellular fluorescent signal of the engulfed particles was monitored using a fluorescence plate reader at 480 nm excitation and 520 nm emission. The phagocytotic response to the effector rTsSERP1 was calculated as follows: To determine the fluorescent phagocytotic effect, neutrophils were plated on a 24-well plate with a poly-L-lysine coated 12mm glass coverslip. The cells were treated as for the above experiment. After incubation with the fluorescent E. coli BioParticle, the fresh cells were gently washed with 1×PBS three times, followed by nuclei counterstaining with Hoechst 33342 (Invitrogen, Cat No, H3570, California, USA) for 20 min. The cover slips were washed several times with 1×PBS and then mounted on a glass slide with FluorSave ™ reagent (Calbiochem, Cat No. 345789, Darmstadt, Germany). Cells were analyzed using a laser scanning confocal microscope (LSM700, Zeiss, Jena, Germany). Digital images were captured using the Zeiss microscope software package ZEN 2012 (Zeiss, Jena, Germany).

Inhibitory effect of rTsSERP1 on neutrophil extracellular trap (NETosis)
The formation of NET was performed according to previous publication with some modifications (Barrientos et al., 2013). Neutrophils were prepared at a density of 1 × 10 6 cells/ml in a 1.5 ml microcentrifuge tube. The Sytox green ™ (Thermo Fisher Scientific Inc., Cat No:S7020, Waltham, USA), a DNA binding dye of impermeable cells, at a final concentration of 5 μM was added into the tube. Subsequently, 200 μl of resuspended cells were seeded into each well of a 96-well black polystyrene plate (Corning Incorporated, Corning, NY). After cell attachment, the cells were cultured with 10 μg/ml rTsSERP1 or 10 μg/ml rmDHFR (irrelevant control protein) and then incubated for 30 min at 37°C with 5% CO2. Neutrophil extracellular trapping (Anderson et al., 2019) was stimulated by adding 50 nM PMA (Sigma-Aldrich, Cat. No:P8139, Saint Louis, MO, USA) (dissolved in DMSO) and incubation for 4 h at 37°C with 5% CO2. Fluorescence was measured at excitation/emission wavelengths of 485/527 nm. Non-treatment (only media) was used as a negative control. All assays were performed in triplicate with three donors.
For fluorescent image analysis, the neutrophils from NET induction as above experiment at a density of 2.5 × 10 5 cells were placed on each well of a 24-well plate containing poly-L-lysine coated 12-mm glass coverslips. The fresh cells were gently washed with 1×PBS three times. The coverslips at the bottom of the well were collected prior to being carefully placed on a glass slide containing a drop of FluorSave ™ mounting reagent. Images were analyzed by observing staining patterns with a ×100 oil objective lens on a laser scanning confocal microscope (LSM700, Zeiss, Jena, Germany). Digital images were captured using the microscope software package ZEN 2012 (Zeiss). Nontreatment was used as a negative control.

Inhibitory effect of rTsSERP1 on cytokines and chemokines released from human neutrophils
The effect of rTsSERP1 on the inhibition of cytokines released from human neutrophils was determined by real-time RT-PCR (qRT-PCR) and ELISA. Human neutrophils were seeded into a 24-well culture plate at a density of 5 × 10 5 cells/well followed by treatment with 10 μg/ml rTsSERP1 or 10 μg/ml rmDHFR (irrelevant control protein). After incubation at 37°C for 1 h, cells were stimulated with 100 nM fMLP and incubated for 4 h. Cells treated with fMLP alone and non-treated (only media) were used as positive and negative controls, respectively. After incubation, the cells and supernatants were collected to monitor the cytokine responses using qRT-PCR and ELISA, respectively. Treatment with 0.1 mM AEBSF was used as a positive inhibitory control. All assays were performed in triplicate with three donors.

Real-time RT-PCR
Total RNA was isolated from neutrophils using TRIZOL reagent (Invitrogen) according to the manufacturer's instructions. Genomic DNA contamination was removed by treating total RNA with DNaseI (Thermo Fisher Scientific) prior to conversion to cDNA using a RevertAid First-strand cDNA Synthesis Kit (Thermo Fisher Scientific, Cat. No: K1622, Waltham, MA). SYBR green qRT-PCR (BioRad, California, USA) was performed as mentioned elsewhere with some modifications (Kobpornchai et al., 2020). The reactions were amplified using specific primers for human cytokines and chemokines including IL-1b, IFN-g, TNF-a, IL-6, IL-8 and CCL3 (Supplementary Data 1: Table S1). GAPDH was used as housekeeping gene. The amplification was performed with Eppendorf Realtime PCR (Realplex4, Eppendorf, Hamburg, Germany), consisted of a first denaturation step at 95°C for 5 min, followed by 40 cycles at 95°C for 15 s and 60°C for 60 s, and a melting curve step at 65-95°C. Relative mRNA expression was calculated using the comparative Ct method with the formula 2 -DDCt .

Cytokine ELISA
Supernatants collected from the experiment above were obtained to determine the levels of IL-1b and IFN-g cytokines using commercially available sandwich ELISA kits according to the manufacturer's instructions (BioLegend,Cat. No;, 430104 (IFN-g), San Diego, CA). The cytokine concentrations were performed in triplicate and standard curves were generated with recombinant cytokines.

Statistical analysis
Statistical analyses were performed with GraphPad Prism 6 software (GraphPad Software Inc., La Jolla, CA, USA). Significance of the differences between groups was analyzed using the one-way ANNOVA test. Individual data and mean ± S.D. of the group are presented. p value< 0.05 was considered significant.

Results rTsSERP1 preferentially inhibits neutrophil elastase among NSP
Serpin forms an irreversible covalent complex with its specific protease to inhibit it, resulting in its inactivation and clearance from the circulation (Sanrattana et al., 2019). The inhibitory assay, which used specific peptide substrates, confirmed that rTsSERP1 completely inhibited hNE activity when the molar ratio (E:I) was increased to 1:2 ( Figure 1A) and K i value of approximately 5 nM was determined against hNE ( Figure 1D). While rTsSERP1 only inhibited hCG partially even it did increase the molar ratio (E:I) to 1:10 ( Figure 1C). There was no inhibitory effect of rTsSERP1 on hPR3 at all ratios ( Figure 1B). The 3D structure of TsSERP1 was simulated using conserpin as a template. The molecular docking of TsSERP1 with NE showed that the reactive central loop (RCL) of serpin containing the inhibitory site of target protease specifically interacted with the structure of NE (Supplementary Figure 2).
In addition, the granule content produced by human neutrophils was used to test the inhibitory effect of rTsSERP1 on hNE activity. The findings revealed that the neutrophil granule content released by fMLP activation strongly hydrolyzed the preferential NE substrate, which was set to 100% hNE activity. Pre-treatment of the granule content with rTsSERP1 prior to incubation with the substrate resulted in a reduction of hNE activity of 60%-80% in all three donors, which was comparable to treatment with AEBSF (a positive inhibitor control). Pretreatment of the granule content with rmDHFR had no inhibitory effect on hNE activity. No hNE activity was observed when neutrophils were incubated with media alone (Figure 2). The aforementioned findings indicated that rTsSERP1 is a NE preference inhibitor. Treatment of neutrophils with DMSO alone at the same amount as that used to dissolve fMLP did not increase hNE activity (Supplementary Figure 6A).

rTsSERP1 impaired neutrophil phagocytosis
Prior to evaluating the effect of rTsSERP1 on neutrophil functions, the optimal dose of rTsSERP1 for treating neutrophils was determined using a cell viability assay (MTT assay). rTsSERP1 at a concentration range of 1.25-20 mg/ml did not kill neutrophils (Supplementary Figure 3). Cells incubated with media alone were used as a negative control. All concentrations of rTsSERP1 were nontoxic and a concentration at 10 mg/ml was selected for the subsequent experiments. The impact of rTsSERP1 on neutrophil phagocytosis was analyzed using the fluorescent E. coli BioParticle. The treatment of fMLP-neutrophils with rTsSERP1 significantly reduced the neutrophil phagocytic activity as assessed by a 40%-50% reduction of the fluorescent signal compared with neutrophils induced with fMLP alone (the positive control was set to 100%) ( Figure 3A). Treatment of fMLP-induced neutrophils with rmDHFR did not impair their phagocytotic activity ( Figure 3A). Neutrophil phagocytosis was not increased when neutrophils were treated with DMSO alone at the same concentration as that used to dissolve fMLP (Supplementary Figure 6B).
Images of fluorescent bacterial phagocytosis by neutrophils were consistent with the fluorescent signal mentioned above, which revealed a decrease in the number of bacteria inside fMLPinduced neutrophils when treated with rTsSERP1 but not with rmDHFR ( Figure 3B). Z-stack analysis confirmed bacteria were internalized by neutrophils (Supplementary Figure 4). The same results were obtained for all three donors. These findings imply that rTsSERP1 interferes with neutrophil phagocytic activity.

rTsSERP1 reduced NETosis
NETosis, the process of neutrophil cell death whereby neutrophil extracellular traps (NETs) capture and kill bacteria and other pathogens, is thought to have a key role in the entrapment and eradication of microbes (Majewski et al., 2016). In previous studies, NE inhibitors such as small molecule inhibitors, SLPI, and serpin B1 regulated and decreased NET production (Majewski et al., 2016;Kasperkiewicz et al., 2020). During T. spiralis infection, neutrophils have an important role in frontline defense against larva invasion and migration (Bass and Szejda, 1979b) and NETs may contribute to larva entrapment as seen in Haemonchus contortus (Muñoz-Caro et al., 2015).
To investigate whether the effect of TsSERP1 limited the NETosis of neutrophils, the fluorescent level of Sytox greenstained DNA released from cells and nuclear DNA of dead cells was quantitatively analyzed. The results demonstrated that fluorescent signals were markedly increased in PMA-induced neutrophils from all three donors when compared with untreated controls. Surprisingly, rTsSERP1 treatment of PMA-induced neutrophils prevented NETosis, which resulted in a significant reduction in fluorescent targeted extracellular DNA (doner 1; p<0.001 and donors 2 and 3; p<0.01). Treatment with rmDHFR (an irrelevant control) had no effect on NETosis ( Figure 4A). The fluorescent images were also used to confirm the fluorescent signal described above and both results were found to be in concordance ( Figure 4B). Neutrophils did not form NETs in the absence of PMA stimulation or treatment with rTsSERP1 or rmDHFR alone (Supplementary Figure 5). The same amount of DMSO used to dissolve PMA did not also promote the production of NETs when applied to neutrophils (Supplementary Figure 6C). From the findings of this study, we can conclude that TsSERP1 may decrease NETosis, which could be attributable to NE inhibition.

rTsSERP suppressed neutrophil cytokine and chemokine responses
Inhibiting NE reduced the amount of pro-inflammatory cytokines and chemokines secreted by neutrophils, lowering host resistance to Pseudomonas aeruginosa (Benabid et al., 2012a). TsSERP isoform (Ts-serpin), which was discovered in TsL1's ES product, inhibited NE and demonstrated an antiinflammatory response by alternative activation of macrophages (Xu et al., 2021b). However, no research has been done on the regulatory function of TsSERP on neutrophil inflammation.
of proinflammatory cytokines and chemokines compared with fMLP-induced neutrophils alone (p>0.05) (Figures 5A-F). A positive inhibitor control (AEBSF) significantly downregulated the transcript levels of proinflammatory cytokines and chemokines from fMLP-induced neutrophils obtained from all three donors when compared with fMLP-induced neutrophils alone (p<0.05, p<0.01, and p<0.001, respectively). The level of transcription of neutrophil proinflammatory cytokines was not increased when neutrophils were treated with DMSO alone at the same concentration as that used to dissolve fMLP (Supplementary Figure 6D).
The protein levels of IL-1b and IFN-g released from neutrophils were measured to confirm the qRT-PCR results. IL-1b and IFN-g levels were significantly reduced when fMLPinduced neutrophils from all three donors were treated with rTsSERP1 (p<0.001). The levels of IL-1b and IFN-g were reduced to 15-20 pg/ml ( Figure 6A) and 3-26 pg/ml ( Figure 6B), respectively, after rTsSERP treatment, whereas the levels of fMLP-induced neutrophils alone were higher 30-50 pg/ ml and 20-57 pg/ml, respectively. There were no changes in IL-1b and IFN-g production in fMLP-induced neutrophils treated with rmDHFR (p>0.05) ( Figures 6A, B). AEBSF treatment of fMLP-induced neutrophils resulted in a significant reduction in IL-1b and IFN-g levels (p<0.001). The incubation of neutrophils with rTsSERP1, rmDHFR, or AEBSF in the absence of fMLPinduction failed to increase the production of cytokines and chemokines at the transcript and protein levels (data not shown). According to the findings mentioned above, TsSERP1 reduced the amount of pro-inflammatory cytokines and chemokines produced by neutrophils, which could be mediated by NE inhibition.

Discussion
Neutrophils, an essential component of the innate immune system, can kill T. spiralis NBL when they migrate through the blood (Bass and Szejda, 1979a;Bass and Szejda, 1979b). A high number of neutrophils was observed 3-17 days after T. spiralis infection and these gradually declined, possibly because of The neutrophil-secreted elastase activity inhibited by rTsSERP1. Neutrophils were induced with 100 nM of fMLP prior to treatment with 40 µM of rTsSERP1or an irrelevant control (rmDHFR) followed by detecting NE activity using a neutrophil elastase substrate for 1 h (A) and the percentage of the NE activity was calculated at 1h by setting neutrophils treated with fMLP alone as 100% activity (B). Media alone was used as a negative control and 0.1 mM of 4-(2-aminoethyl) benzenesulfonyl fluoride hydrochloride (AEBSF) was used as a positive control for serine protease inhibition. The bar charts show the data of three different donors, which are presented as the mean ± SD. The experiments were performed in triplicate with three independent experiments. One-way ANOVA followed by a Bonferroni multiple comparison test were used for statistical analysis: **p < 0.01 and ***p < 0.001. The treatment conditions were included media alone (Mock), only fMLP induction (fMLP), fMLP induction and AEBSF treatment (AEBSF+fMLP), fMLP induction and rTsSERP1 treatment (rTsSERP1+fMLP), fMLP induction and irrelevant control (rmDHFR) treatment (rmDHFR+fMLP). rTsSERP1 impairs neutrophil phagocytosis. The phagocytosis of neutrophils was induced by 100 nM of fMLP prior to treatment with 10 µg/ml of rTsSERP1 or an irrelevant control (rmDHFR), followed by incubation with the fluorescent E. coli BioParticle. After incubation, the fluorescent signal was measured and subsequently calculated as the percentage of phagocytosis (A). Neutrophils treated with fMLP alone were set as 100% phagocytotic effect. The bar charts show the data of three different donors, which are presented as the mean ± SD. The experiments were performed in triplicate with three independent experiments. One-way ANOVA followed by a Bonferroni multiple comparison test were used for statistical analysis: **p < 0.01 and ***p < 0.001. Fluorescent images (B) were captured to confirm the above result. The percentage of phagocytosis positive out of the total number of alive neutrophils was indicated in the merge of picture. The E. coli BioParticle was labeled with FITC (green) and the nucleus was counterstained with Hoechst 33342 (blue). Examples of non-phagocytotic neutrophils are indicated by white arrows. The treatment conditions were included media alone (Mock), only fMLP induction (fMLP), fMLP induction and rTsSERP1 treatment (rTsSERP1+fMLP), fMLP induction and irrelevant control (rmDHFR) treatment (rmDHFR+fMLP).
parasite immunomodulation (Wang et al., 2020). A T. spiralis 45 kDa glycoprotein (Tsgp45) was previously shown to suppress neutrophil migration, chemotaxis, and activation, resulting in anti-inflammatory effects (Bruschi et al., 2000). T. spiralis calreticulin (TsCRT) binds to C1q, inhibiting the classical complement pathway as well as C1q-associated neutrophil activation and NET formation (Shao et al., 2020). Apart from these molecules, TsSERPs, which were discovered in the ES of T. spiralis, were shown to inhibit neutrophil elastase and immunological functions of neutrophils, which was confirmed in this study.
Serpins are immunomodulators that mediate the regulatory protective effects of parasites against serine protease hydrolysis as well as being involved in various immune functions including apoptosis (Heutinck et al., 2010), coagulation (Loof et al., 2011), granzyme killing (de Koning et al., 2011;Niehaus et al., 2015), complement activation (Takahashi et al., 2007), and neutrophil functions (Pham, 2006). Several TsSERP isoforms have been rTsSERP1 inhibits neutrophil extracellular traps (NETosis). Neutrophils initially stained with Sytox green (5 µM) were treated with rTsSERP1 or rmDHFR (10 µg/ml) for 30 min followed by induction with PMA (50 nM) for 4 h. NETosis was analyzed by the quantitative fluorescence intensity (A) and fluorescent images (B) with different treatment conditions including media alone (Mock) (a), PMA induction alone (PMA) (b), rTsSERP1 treatment before PMA induction (rTsSERP1+PMA) (c), and treatment with an irrelevant control (rmDHFR) before PMA induction (rmDHFR+PMA) (d). The bar charts show the data of three different donors, which are presented as the mean ± SD. The experiments were performed in triplicate with three independent experiments. One-way ANOVA followed by a Bonferroni multiple comparison test were used for statistical analysis: **p < 0.01 and ***p < 0.001. identified and their potential as immunomodulators and vaccine candidates has been reported (Xu et al., 2021a).
TsSERP1, the first serpin isoform discovered from TsL1, inhibits trypsin (Nagano et al., 2001). We previously used rTsSERP1 for the immunodiagnosis of swine trichinosis and demonstrated that rTsSERP1 could diagnose late infection. In this study, we analyzed the inhibitory function of TsSERP1 against NSPs, which preferentially inhibited hNE and partially inhibited hCG but not hPR3. A serpin of the human hookworm Ancylostoma duodenale (AduTIL-1) suppressed digestive enzymes and NE (Jin et al., 2011). Bmspn-2, a Brugia malayi serpin, suppressed CG and NE specifically (Zang et al., 1999). The impact of helminth serpins on neutrophil functions, which was originally examined using TsSERP1 in this study, has yet to be determined elsewhere.
The specificity and function of serpins that inhibit serine proteases have been intensively studied, and they depend on two regions of the reactive central loop (RCL) at the P1 residue and a highly-conserved hinge region at residues P15-P9 (Marijanovic et al., 2019). TsSERP1 and alpha-1 antitrypsin (A1AT) have relatively similar P1 and P15-P9 regions, except for P10, which is alanine (A) for TsSERP1 and glycine (G) for A1AT (Supplementary Figure 7). A1AT can inhibit a diverse variety of NSPs, especially NE (Marijanovic et al., 2019), whereas TsSERP1 specifically inhibits NE. Differences in substrate specificity between TsSERP1 and A1AT might be related to variances in the P8-P3 or P2'-P3' regions or the insertion of a MYES motif at P4'-P8' in TsSERP1. This should be investigated further via mutagenesis studies.
Neutrophils are a type of innate immune cell that serves as a first line of defense against infections. The secretion of NSPs The experiments were performed in triplicate with three independent experiments. One-way ANOVA followed by a Bonferroni multiple comparison test were used for statistical analysis: *p < 0.05, **p < 0.01, and ***p < 0.001. The treatment conditions were included media alone (Mock), only fMLP induction (fMLP), fMLP induction and AEBSF treatment (AEBSF+fMLP), fMLP induction and rTsSERP1 treatment (rTsSERP1+fMLP), fMLP induction and irrelevant control (rmDHFR) treatment (rmDHFR+fMLP).
such as NE, PR3, and CG is critical in bacterial killing and facilitating neutrophil immune responses (Korkmaz et al., 2010). NE is a major enzyme that has important roles in neutrophil activation as well as host tissue damage (Gramegna et al., 2017).
Silvelestat, a small molecule inhibitor of NE, reduced neutrophil inflammation, NET production, and NET-mediated tissue injury (Hagiwara et al., 2008;Okeke et al., 2020). Mice lacking NE and CG were demonstrated to be more sensitive to bacterial and fungal infection (Tkalcevic et al., 2000). These findings suggest that TsSERP1 secreted from T. spiralis, which inhibits NE preferentially, might be an essential immune evasion mechanism against neutrophils. In this study, rTsSERP1 suppressed NE activity in the culture media of fMLP-induced neutrophils, as well as phagocytosis. Phagocytosis is the ability of neutrophils to ingest and destroy invading microorganisms, particularly bacteria and fungus, which is critical for the health of the host (Kobayashi et al., 2018). Helminths are large pathogens and therefore are difficult for neutrophils to phagocytose. Furthermore, the intracellular infection of T. spiralis in host muscle and nurse cell formation can protect parasites from host immune cells including neutrophils (Wu et al., 2008). NET formation (NETosis) is an important process for defense against parasitic helminths by trapping them in NETs, which restricts parasite mobilization (Dıáz-Godıńez and Carrero, 2019; Hermosilla et al., 2014). Human neutrophils were stimulated to produce NETs by Strongyloides stercoralis larvae in vitro, which aided larval death (Bonne-Anneé et al., 2014). Haemonchus contortas third-stage larvae (L3) activated NET formations, trapping and killing the larvae (Muñoz-Caro et al., 2015). In NETosis, NE is a major protease in NETosis that translocates from azurophilic granules into the nucleus by reactive oxygen species (ROS) and myeloperoxidase (MPO), and which partially cleaves histone to enhance chromatin condensation (Metzler et al., 2014). NET production could be inhibited by NE inhibitors as SLPI and serpin B1 (Majewski et al., 2016). Furthermore, compared with wild-type mice, serpinB1 knockout mice had an increased release of NETs in PMA-activated neutrophils (Farley et al., 2012). These findings support our findings that rTsSERP1 prevents NET formation in PMA-activated neutrophils. However, the exact mechanism by which TsSERP1 modulates NETosis during helminthic infection or unrelated inflammatory disorders is unknown.
Apart from their primary defense against infections, neutrophils also provide an immunomodulatory role, which involves their NSPs processing cytokines and chemokines directly and indirectly to initiate inflammatory responses. The inhibition of NE by NE inhibitors decreased the production of proinflammatory cytokines in inflammation-stimulated neutrophils and monocytes (Haga and Ogawa, 1997). In NEdeficient mice, the transcript and protein levels of the proinflammatory cytokines TNF-a, MIP-2, and IL-6, in the lungs were decreased, which was associated with increased mortality from P. aeruginosa infection. Two recombinant T. spiralis serpins, rTsKaSPI and rTsAdSPI, ameliorated the severity of TNBS-induced colitis, which was related to the decreased expression of IFN-g, a proinflammatory cytokine that interacts with multiple signaling pathways of the innate and adaptive immune responses (Xu et al., 2018). Schistosoma mansoni Kunitz type protease inhibitor (SmKI-1) inhibited NE, which impaired neutrophil function and inflammation. Treatment of various murine models of inflammatory diseases, including acetaminophen (APAP)-mediated liver damage, gout arthritis, and carrageenan-induced plural effusion with SmKI-1 impaired neutrophil migration, NE activity, and IL-1b secretion, which ameliorated clinical manifestations (Morais et al., 2018). In fMLP-primed neutrophils, rTsSERP1 significantly reduced the production of proinflammatory cytokines (IL-1b, IL-6, IFN-A B

FIGURE 6
Inhibitory effect of rTsSERP1 on the production of proinflammatory cytokines released by human neutrophils. In addition to determining the transcription levels of cytokine and chemokine mRNAs in neutrophils, culture media were also collected for ELISA to analyze IL-1b (A) and IFN-g (B) protein levels. ELISA results are reported as pg/ml. The bar charts show the data of three different donors, which are presented as the mean ± SD. The experiments were performed in triplicate with three independent experiments. One-way ANOVA followed by a Bonferroni multiple comparison test were used for statistical analysis: ***p < 0.001. The treatment conditions were included media alone (Mock), only fMLP induction (fMLP), fMLP induction and AEBSF treatment (AEBSF+fMLP), fMLP induction and rTsSERP1 treatment (rTsSERP1+fMLP), fMLP induction and irrelevant control (rmDHFR) treatment (rmDHFR+fMLP).
g, and TNF-a) and chemokines (IL-8 and CCL3). These findings suggest the therapeutic potential of rTsSERP1 for the treatment of inflammatory disorders. Finally, TsSERP1 suppressed NE and impaired neutrophil activities including phagocytosis, NETosis, and the production of proinflammatory cytokines and chemokines (Figure 7). Our future study will focus on providing insights into the mechanism related to the ex vivo and in vivo regulation of neutrophils by TsSERP1. In addition, the therapeutic potential of rTsSERP1 in a mouse model of inflammatory disease must be studied. Understanding the immunomodulatory functions of neutrophils might lead to the development of novel therapeutics for acute and chronic inflammatory disorders.

Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s.

Ethics statement
The studies involving human participants were reviewed and approved by The Human Research Ethics Committee of the Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand (MUTM 2021-013-01). Written informed consent for participation was required for this study in accordance with the national legislation and the institutional requirements.

Author contributions
PK performed all work, designed experiments, analyzed data and drafted the manuscript. OR, OP, and PM provided reagents and designed the experiments. PA conceived and designed the experiments, analyzed data and drafted the manuscript. All authors read the manuscript and approved the submitted version.  A diagram summarizing the main findings of this study. TsSERP1, presented at different developmental stages of T. spiralis and its excretorysecretory (ES) products, inhibited the hNE activity of human neutrophils. The inhibitory effect of TsSERP1 on hNE influences neutrophil functions by impairing phagocytosis, NETosis, and the production of proinflammatory cytokines and chemokines.