s2fieldsofstudy: Biology Medicine Chemistry

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Inhibition of Axitinib on Buspirone Metabolism in vitro and in vivo

Objective To evaluate the effect of axitinib on buspirone metabolism in vitro and in vivo. Methods A microsome incubation assay was performed to study the effect and mechanism of axitinib on buspirone metabolizing. In vivo, buspirone was administered with or without axitinib to Sprague–Dawley rats. Plasma samples were collected and subjected to ultra-performance liquid chromatography–tandem mass spectrometry. Results In both human liver microsomes (HLMs) and rat liver microsomes (RLMs), axitinib (100 μM) decreased buspirone hydroxylation and N-dealkylation by >85%. Axitinib inhibited buspirone hydroxylation and N-dealkylation, with an IC50 of 15.76 and 9.74 for RLMs, and 10.63 and 9.902 for HLMs. Axitinib showed noncompetitive inhibition of both 6′-hydroxylation and N-dealkylation. Moreover, coadministration of axitinib and buspirone led to an increase in the maximum plasma concentration (Cmax) and area under the plasma concentration-time curve (AUC) of buspirone by 4.3- and 5.3-fold, respectively, compared with the control group. Conclusion Axitinib inhibited buspirone metabolism in vivo and in vitro, which increases the risk of the side effects of buspirone in the clinic. When coadministered with axitinib, a lower dosage of buspirone should be defined to avoid a toxic response. Axitinib is suspected to function as an inhibitor of CYP3A4.

Introduction
Anxiety is acknowledged as being one of the most common mental diseases, with an incidence of 15-20% and higher morbidity in China, as estimated by experts. 1 Buspirone, a clinical nonbenzodiazepine anti-anxiety agent, has good efficacy in treating anxiety with a low rate of side effects. 2,3 As a partial agonist of 5-HT 1A , buspirone was first approved to treat generalized anxiety disorder (GAD) in adults. Buspirone shows better compliance due to its decreased side-effect profile compared to other anxiolytic treatments, especially in patients who do not tolerate the side effects of selective serotonin reuptake inhibitors (SSRIs). 2,4 Unlike benzodiazepines or barbiturates, the pharmacological mechanism of buspirone does not depend on gamma-aminobutyric acid (GABA) receptors; thus, addiction or withdrawal symptoms are uncommon. However, some factors can exacerbate the severe toxic effects of buspirone, such as its combination with ritonavir. Indeed, one patient presented with Parkinson-like symptoms after administration of these two drugs. 5 Moreover, a coadministration method improved the AUC (0-inf) of buspirone to 12.8-fold in a rat model compared to the administration of buspirone only. 6 Increasing novel indications for buspirone have been discovered recently, such as dementia with behavioral disturbance, autism spectrum disorder, and chronic schizophrenia, leading to increased use of buspirone. [7][8][9][10] In the clinic, more than 2 weeks of buspirone administration is expected to achieve the desired effect, which increases the probability of long-term medication and the risk of buspirone accumulation. Therefore, further research on buspirone in vivo processes should be advocated.
The progression of chronic physical conditions, such as cancer, is closely related to chronic mental disorders, such as anxiety. [11][12][13] Cancer has significant psychosocial implications that affect an individual's psychological and spiritual state, and often co-occurs with anxiety in patients. [14][15][16] According to previous reviews, approximately 90% of renal tumors are renal cell carcinomas (RCC) with a high metastasis risk factor. 17 Vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR) signaling pathways adjust the function of vessels and play key roles in tumor growth and progression. 18 Axitinib, an inhibitor of VEGFR-1 to 3, is an important drug for advanced RCC. Considering that patients with RCC tend to have a higher rate of psychological disorders, especially anxiety, the use of buspirone combined with axitinib is increased in this patient group. Unfortunately, the risk or benefits of coadministration have never been reported. We studied the effects of axitinib on buspirone metabolism both in vitro and in vivo to provide a useful reference for the clinic.
Buspirone is primarily metabolized by CYP3A, specifically by CYP3A4. The analysis of the main metabolites of buspirone in incubation, including recombinant CYP3A4, demonstrated that 6′-hydroxy buspirone (6′-OH buspirone) and 1-(2-pyrimidyl)-piperazine (1-PP) were the most abundant metabolites, the structures of which are shown in Figure 1. 19 Studies have shown that incubation with microsomes and in vivo pharmacokinetics assays are appropriate methods to evaluate drug-drug interactions (DDIs). 6,20-23 Therefore, we systematically examined the effect of axitinib in human and rat liver microsomes (HLMs and RLMs) in vitro and in Sprague-Dawley (SD) rats in vivo by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS).

Instrumentation
The determination of the concentration of buspirone and its main metabolites was conducted by UPLC-MS/MS, consisting of a Waters Acquity I-Class with BEH C18 column (2.1*50 mm) and a Waters Xevo TQD triplequadrupole mass spectrometer (Waters Corp., Milford, MA, USA) with an electrospray ionization (ESI) source to test and quantify samples. Data were acquired using Masslynx 4.1 software (Waters Corp.).

Michaelis-Menten Curve
The incubation system was designed as buspirone in a 200-μL reaction solution, containing buspirone solubilized in methanol and serially diluted to 5, 10, 20, 50, 100, and 200 μM in PBS buffer (n = 3). RLMs (40 μg) or HLMs (60 μg) were added to take part in this in vitro reaction. After incubation for 5 min at 37°C, the reactions were initiated by the addition of 10 μL of 20 mM NADPH to the samples, which were then incubated at 37°C for 40 min. Next, 400-μL acetonitrile was added to denature the proteins and terminate the incubation. Following addition of 20 μL of 20 ng/mL CBZ as an IS, the tubes were vortexed vigorously for 2 min and centrifuged at 13,000 rpm for 10 min. The supernatant was transferred to a 1.5-mL clean tube and evaluated by UPLC-MS/MS.

DovePress
Drug Design, Development and Therapy 2022:16 min and centrifuging at 13,000 rpm for 10 min, the samples were subjected to UPLC-MS/MS analysis to quantify buspirone 6′-hydroxylation and N-dealkylation.

Effects of Axitinib on the Metabolism of Buspirone in Rats in vivo
We purchased 12 male SD rats (approximately 250-300 g) from the Laboratory Animal Centre of Wenzhou Medical University (Wenzhou, China; animal number: 2020-078). The animals were allowed to adapt to laboratory conditions and were provided with sufficient food and water for more than 2 weeks. All procedures conformed to the Guide for the Care and Use of Laboratory Animals and were conducted with the approval of the Animal Care and Use Committee of Wenzhou Medical University (wydw2020-3022).
The animals were randomly placed into two groups: the control group (A) and the experimental group (B). The animals in both groups were fasted for 12 h before administration (with sufficient water); the B group was administered axitinib distributed in 0.5% carboxymethyl cellulose (CMC) (1 mg/kg) by gavage, and the A group was treated with 0.5% CMC using the same administration approach. After 30 min, the rats in both groups were administered buspirone dissolved in ultrapure water (20 mg/kg) by gavage. Blood samples were collected from the caudal vein at 0, 0.083, 0.167, 0.25, 0.5, 1, 2, 3, 4, 6, 8, 12, and 24 h postdosing. After centrifuging at 13,000 rpm for 10 min, 100-μL plasma samples were extracted from the blood and mixed with a 300-μL aliquot of acetonitrile and a 20-μL aliquot of 200 ng/mL MDZL (IS). After 2 min of vortex mixing and 15 min of centrifugation at 13,000 rpm, the supernatants were collected and diluted with ultrapure water at a ratio of 1:10. The mixtures were subjected to UPLC-MS/MS analysis.

Enzymatic Kinetics of Axitinib Inhibition of Buspirone in RLMs
The incubation was established with buspirone (5-50 μM, which includes the K m value) as the substrate, axitinib (0-30 μM, which includes the IC 50 value), and RLMs (40 μg) in 1× PBS buffer. After a 5-min-preincubation at 37°C, the samples were incubated with the addition of 10 μL of 20 mM NADPH at 37°C for 40 min. The method of sample processing was the same as that outlined for the method in Effects of Axitinib on the Metabolism of Buspirone in Rats in vivo.

UPLC-MS/MS
Compounds were separated using a gradient elution method, operating at a flow rate of 0.4 mL/min. The mobile phase consisted of 0.1% formic acid diluted in ultrapure water (as solvent A) and acetonitrile (as solvent B); the solution was held at 10% B for 0.5 min, followed by a linear increase to 98% B at 0.6 min, held at 98% B until 1.1 min, and then ramped back to 10% B at 2.1 min and maintained at 10% B for 0.9 min.
These analytes were detected with an ESI source in multiple reaction monitoring (MRM) mode using the following method: as the desolvation gas, nitrogen was selected to deionize samples at 1000 L h-1, with a desolvation temperature of 600°C. MRM modes were employed for quantification as follows: m/z 386.

Data Analysis
All results are expressed as the mean ± SD. Michaelis-Menten curves of buspirone, dose response-inhibition curves, drug concentration-time profiles, and enzyme kinetics were constructed and analyzed by GraphPad Prism 5.0 software. We performed the statistical analysis with SPSS 20.0 software using an independent sample t-test. P-values <0.05 (in twotailed test) indicate significant differences between the two groups.

Results
According to chromatogram and mass spectrum data, buspirone and its main metabolites could be separated and detected by this method. Referring to the Michaelis-Menten curve in microsomes (Figure 2), buspirone was metabolized with a K m of 22.97 μM for 6′-OH buspirone and a K m of 26.29 μM for 1-PP in RLMs, and with a K m of 29.37 μM for 6′-OH buspirone and a K m of 33.55 μM for 1-PP in HLMs. Based on the enzyme kinetic parameters of buspirone, the proper concentration of buspirone was validated for further study in vitro. As shown in Figure 3 Figure 5 shows the concentration-time curves of groups A and B, which were graphed with the plasma concentration at the designed time points and the main relevant parameters were obtained (Tables 1-3). The data and curves showed significant differences in the AUC (0-t) , T max , and C max , with mild differences in other indicators between groups A and B. Compared with group A, group B increased the AUC (0-t) of buspirone to 530%, the T max to 150%, and the C max to 420%. The AUC (0-t) and AUC (0-∞) values for 6′-OH buspirone were significantly higher in group B (2.4-fold) compared with those in the control. The V z /F and CL z /F values for 6′-OH buspirone were significantly lower (decreased by 82.3% and 57.2%, respectively) in group B. The T max value of 1-PP in group B was slightly higher than that in the control group. We did not observe any significant differences in the other pharmacokinetic parameters of buspirone and its main metabolites between the two groups.
To study the inhibition pattern, we analyzed the enzymatic kinetics of axitinib inhibition on buspirone in RLMs following incubation with RLMs. As shown in Figure 6, axitinib was determined to be a noncompetitive inhibitor that altered the buspirone metabolism, with a K i of 4.462 and an α value of 2.139 in the 6′-hydroxylation, and a K i of 2.606 and an α value of 5.434 in N-dealkylation.

Discussion
It is necessary to study the effects of drugs on buspirone metabolism, although data on buspirone is currently lacking in the literature. Although buspirone is well tolerated in the clinic as an anti-anxiety drug, its accumulation can induce serious reactions to the nervous system. 5 According to a report from Canada, ritonavir is proven to inhibit the metabolism of buspirone in vitro and in vivo. 6 In our pharmacokinetic pre-experiment, the rats were administered ritonavir (the positive inhibitor) before buspirone, and plasma samples were collected at various points postdosing. The results showed that, compared with the control, the rats showed symptoms of inhibition of respiration and near-death with extremely high blood concentrations of buspirone. The result is consistent with the report that ritonavir inhibits buspirone metabolism, 6 and the accumulation of buspirone can induce serious reactions to the nervous system. 5 Therefore, this method may be useful for studying other drugs that may influence buspirone metabolism.
As shown in this experiment (Figures 3 and 4), axitinib is a potent inhibitor that influences the metabolism of buspirone. Given the results of enzymatic parameters and inhibitory effects, no significant differences in the relative activity were shown between HLMs and RLMs in the presence of various concentrations of axitinib, demonstrating that pharmacokinetic experiments and relevant mechanism studies can be used in rats to evaluate possible interactions in humans. Compared with the control (DMSO) and positive groups (ritonavir, a classical inhibitor to buspirone), axitinib inhibited buspirone metabolism to a large extent, with a similar effect to that experienced in the positive group. More common drugs were selected as the perpetrator drugs to evaluate the inhibition intensity of axitinib according to the method in Effects of Axitinib on the Metabolism of Buspirone in HLMs and RLMs. Compared with the relative activity of the common clinical drugs shown in Figure 3, the inhibitory effect of axitinib on buspirone metabolism was much higher than that of most clinical medicines. Indeed, the IC 50 (the concentration of axitinib inhibiting half of the original metabolism rate of buspirone) showed strong inhibition of axitinib, which was consistent with the pharmacokinetic results.
It has been reported that axitinib is mainly metabolized by CYP3A4/5, with minor contributions from CYP2C9 and CYP1A2. 19 A 2013 review indicated that axitinib was not an inhibitor of CYP3A4. 19 Another study, however, revealed that axitinib could decrease loperamide intrinsic clearance with an IC 50 of 1.604 μM in CYP3A4.1 recombinant cell microsomes expressed in Sf-21 cells and showed that axitinib can inhibit loperamide metabolism in CYP3A4. 20 Additionally, previous US studies have reported that after incubation with CYP450 inhibitor, buspirone metabolism decreased significantly only when the CYP3A4 inhibitor was added. 21 Previous reports have indicated that buspirone is primarily metabolized by CYP3A4 in HLMs, which has been acknowledged as the classical enzymatic substrate of CYP3A4. 21 Given the decreased formation rates of 6′-OH buspirone and 1-PP following the increasing concentration of axitinib (Figure 4), we suspected that axitinib inhibited buspirone metabolism by first inhibiting the enzymatic activity of CYP3A4.
Referring to data from our in vivo experiment ( Figure 5), axitinib inhibited buspirone metabolism, significantly increasing the concentrations of buspirone in the plasma and extending the T max in the combined group. As buspirone is rapidly absorbed and has a short half-life value, most time points were designed to be <5 h. Because almost 100% of buspirone was absorbed in the alimentary canal, axitinib could not exert an effect by enhancing absorption; therefore, we focused more on the metabolism. In terms of oral administration, buspirone showed a bioavailability of <5%, which could result from extensive presystemic elimination after absorption. Axitinib can inhibit buspirone metabolism in this process in the liver, meaning that more substrates avoid the first-pass effect and are transferred to the blood. The T max for buspirone was slightly extended in group B, but it unlikely holds any clinical significance because of the small magnitude of the difference. The V z /F of buspirone was also not significantly improved, which may indicate that axitinib cannot  inhibit buspirone absorption and distribution. The AUC (0-∞) , MRT, t 1/2z , and CL z /F for buspirone had no statistical difference between the two groups, which may result from individual differences between rats. As shown in the concentration-time curve and pharmacokinetic parameters ( Table 1), coadministration of buspirone with axitinib increased the plasma 6′-OH buspirone concentration (2.4-fold increase in AUC). This may have resulted from the increased plasma buspirone concentration after coadministration with axitinib, which indicated that a large amount of buspirone in the blood could promote metabolism in 6′-hydroxylation. Axitinib also decreased the CL z /F for 6′-OH buspirone by 57%, and may have inhibited further elimination of the main metabolites. However, no statistically significant differences in most of pharmacokinetic parameters were observed for 1-PP compared with the control. Although a statistical difference in the T max value for 1-PP was discovered between the two groups, it is unlikely to hold any clinical significance. This may indicate that the blood concentration of buspirone is not the only factor influencing the 1-PP metabolism pathway. Furthermore, as both 6′-OH buspirone and 1-PP are considered to be the major active metabolites of buspirone, 22,23 high concentrations are likely to increase the risk of severe side effects.
To characterize axitinib inhibition on buspirone in rat liver microsomes, various concentrations of inhibitors and substrates were used for enzyme kinetic analysis in vitro. The Lineweaver-Burk plots showed that axitinib noncompetitively inhibited buspirone metabolism and therefore could exert an effect by binding to the inactive sites of hepatic microsomal enzymes. Axitinib did not affect binding of buspirone to liver drug-metabolizing enzymes (especially cytochrome P450), and buspirone had the same K m value regardless of whether or not axitinib was added. The concentration of buspirone, however, did not influence the axitinib binding these enzymes nor its inhibition.

Conclusion
Axitinib is a potent inhibitor of buspirone metabolism in vivo and in vitro. The interaction between two drugs can induce high blood levels of buspirone, which will greatly increase the risk of drug-induced diseases. Our results demonstrated that pharmacokinetics and microsome incubation assay can be used to evaluate the effect of axitinib on buspirone metabolism in humans. The results also indicated that axitinib is a noncompetitive inhibitor of buspirone metabolism. Axitinib likely exerts an inhibitory effect via CYP3A4. These results suggest that doctors who prescribe the combination of buspirone and axitinib should focus on the severe side effects and dosing strategies of buspirone. If necessary, therapeutic drug monitoring can be conducted to ensure rational drug use.


s2fieldsofstudy: Biology Chemistry

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Identification of a Dual Inhibitor of Secreted Phospholipase A2 (GIIA sPLA2) and SARS-CoV-2 Main Protease

The development of novel agents to combat COVID-19 is of high importance. SARS-CoV-2 main protease (Mpro) is a highly attractive target for the development of novel antivirals and a variety of inhibitors have already been developed. Accumulating evidence on the pathobiology of COVID-19 has shown that lipids and lipid metabolizing enzymes are critically involved in the severity of the infection. The purpose of the present study was to identify an inhibitor able to simultaneously inhibit both SARS-CoV-2 Mpro and phospholipase A2 (PLA2), an enzyme which plays a significant role in inflammatory diseases. Evaluating several PLA2 inhibitors, we demonstrate that the previously known potent inhibitor of Group IIA secretory PLA2, GK241, may also weakly inhibit SARS-CoV-2 Mpro. Molecular mechanics docking and molecular dynamics calculations shed light on the interactions between GK241 and SARS-CoV-2 Mpro. 2-Oxoamide GK241 may represent a lead molecular structure for the development of dual PLA2 and SARS-CoV-2 Mpro inhibitors.

Introduction
With more than 450 million cases of infected people and 6 million casualties globally, the discovery of efficient agents to treat COVID-19, which is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is an unmet need [1]. Pioneering studies showed that enzymes, such as RNA-dependent RNA polymerase (RdRp) and SARS-CoV-2 main protease (M pro ), are attractive targets for the development of novel antiviral agents [2,3].
Studies aiming to understand the pathobiology of COVID-19 have also demonstrated the involvement of lipids and lipid metabolizing enzymes in this potentially lethal infection [4,5]. Phospholipases A 2 (PLA 2 s) are enzymes which catalyze the hydrolysis of membrane glycerophospholipids, releasing free fatty acids (FFAs) and lysophospholipids and initiating arachidonic acid (AA) cascade and promotion of inflammation [6][7][8]. Proteomics studies on SARS-CoV-2 infected cells have revealed alterations of proteins linked to the inflammatory response due to the viral infection [9]. The expression of two PLA 2 s, namely cytosolic PLA 2 (GIVA cPLA 2 ) and secreted PLA 2 (GIIA sPLA 2 ) was notably differentiated after 24 h of infection [9]. Plasma metabolomic and lipidomic studies associated with COVID-19 showed elevated levels of FFAs and reduction in phosphatidylcholines (PCs), which indicated increased enzymatic activity of PLA 2 s [10]. Large-scale plasma analysis has revealed that lipids are strongly involved in the response to infection [11]. The concentrations of oleic acid (OA, C18:1) and AA (C20:4) were directly correlated to the severity of the disease in COVID-19 patients who required admission to an intensive care unit [11]. Most recently, an independent cohort study has demonstrated elevated levels of GIIA sPLA 2 in the plasma of deceased patients in comparison to patients with severe or mild COVID-19, indicating that GIIA sPLA 2 is associated with increased mortality due to COVID-19 [12]. This study highlights the importance of GIIA sPLA 2 , establishing this enzyme as a factor that leads to severe COVID-19 morbidity and mortality, and suggesting it as a therapeutic target to prevent COVID-19 mortality.
Previously described data [4,5,[9][10][11][12], as well as data reported in recent review articles summarizing the role of PLA 2 s in inflammatory diseases [13,14], prompted us to explore if we could identify a small-molecule inhibitor able to simultaneously inhibit PLA 2 and SARS-CoV- 2 M pro . It would be advantageous, if we could target two enzymes with a dual inhibitor able to simultaneously block virus replication by inhibiting SARS-CoV-2 M pro and regulate the inflammatory response by inhibiting PLA 2 . In the present study, we focus on 2-oxoamide (also known as α-ketoamide) small molecules as appropriate agents to inhibit both PLA 2 and SARS-CoV-2 M pro and we describe the first dual inhibitor of GIIA sPLA 2 and SARS-CoV-2 M pro .

Design of Inhibitors
In 2020, Hilgenfeld and coworkers demonstrated that 2-oxoamides are potent inhibitors of SARS-CoV- 2 M pro [15] and reported the X-ray structure of SARS-CoV-2 M pro in complex with the 2-oxoamide inhibitor 1 (Figure 1) [15]. SARS-CoV-2 M pro is a cysteine protease and its key cysteine residue may attack small-molecule inhibitors containing either a reactive carbonyl group or a Michael acceptor functionality [15][16][17][18][19][20][21]. In previous years, we have designed and synthesized a variety of 2-oxoamides as inhibitors of PLA 2 s. More specifically, we have developed 2-oxoamides (2), which are based on non-natural δor γ-amino acids and selectively inhibit GIVA cPLA 2 [22,23], while 2-oxoamides (3) based on natural α-amino acids selectively inhibit GIIA sPLA 2 [24]. after 24 h of infection [9]. Plasma metabolomic and lipidomic studies associated with COVID-19 showed elevated levels of FFAs and reduction in phosphatidylcholines (PCs), which indicated increased enzymatic activity of PLA2s [10]. Large-scale plasma analysis has revealed that lipids are strongly involved in the response to infection [11]. The concentrations of oleic acid (OA, C18:1) and AA (C20:4) were directly correlated to the severity of the disease in COVID-19 patients who required admission to an intensive care unit [11]. Most recently, an independent cohort study has demonstrated elevated levels of GIIA sPLA2 in the plasma of deceased patients in comparison to patients with severe or mild COVID-19, indicating that GIIA sPLA2 is associated with increased mortality due to COVID-19 [12]. This study highlights the importance of GIIA sPLA2, establishing this enzyme as a factor that leads to severe COVID-19 morbidity and mortality, and suggesting it as a therapeutic target to prevent COVID-19 mortality.
Previously described data [4,5,[9][10][11][12], as well as data reported in recent review articles summarizing the role of PLA2s in inflammatory diseases [13,14], prompted us to explore if we could identify a small-molecule inhibitor able to simultaneously inhibit PLA2 and SARS-CoV-2 M pro . It would be advantageous, if we could target two enzymes with a dual inhibitor able to simultaneously block virus replication by inhibiting SARS-CoV- 2 M pro and regulate the inflammatory response by inhibiting PLA2. In the present study, we focus on 2-oxoamide (also known as α-ketoamide) small molecules as appropriate agents to inhibit both PLA2 and SARS-CoV-2 M pro and we describe the first dual inhibitor of GIIA sPLA2 and SARS-CoV-2 M pro .

Inhibition of SARS-CoV-2 M pro by 2-Oxoamide PLA2 Inhibitors and Analogs
The inhibitory potency of the known PLA2 inhibitors and all of the new 2-oxoamides synthesized against SARS-CoV-2 M pro was assessed by determining the extent of enzyme inhibition (% inhibition); the results are summarized in Tables 1 and 2 Amine 5b was synthesized from carbobenzoxy-L-valinol by protection of the hydroxyl group, using tert-butyldimethylsilyl chloride, as described in [27], and then removal of the Cbz group. Amine 5c was synthesized from tert-butyloxycarbonyl-L-valinol (9) by protection of the hydroxyl group, followed by removal of the Boc group (Scheme 3). Amine 5b was synthesized from carbobenzoxy-L-valinol by protection of the hydroxyl group, using tert-butyldimethylsilyl chloride, as described in [27], and then removal of the Cbz group. Amine 5c was synthesized from tert-butyloxycarbonyl-L-valinol (9) by protection of the hydroxyl group, followed by removal of the Boc group (Scheme 3).
The results for the in vitro inhibition of SARS-CoV-2 M pro by the analogs of GK241 are summarized in Table 2. Conversion of the free carboxyl to the corresponding amide 7d or to a hydroxymethyl-protected group 7c, 7b resulted in abolishment of the inhibitory potency (entries 2-4, Table 2), indicating that a free carboxyl group was necessary for the inhibition. When the long chain of GK241 was replaced by a shorter one (reduction  Table 2).
When the valine residue of GK241 was replaced by alanine, 8a (entry 7, Table 2) was found to inhibit SARS-CoV-2 M pro by 65.49% at 40 µM, while the conversion of the free carboxyl group to an ester (7a, entry 1, Table 2) again led to the abolishment of the inhibitory potency. The derivatives 8b and 7f, based on an Ala-Ala dipeptide, presented almost no activity (entries 8 and 6, Table 2). Finally, compound 7e, based on a glutamine surrogate, did not present any activity (entry 5, Table 2).

Molecular Mechanics Docking and Molecular Dynamics Calculations
To obtain a better insight into the interactions between SARS-CoV-2 M pro and the most active compound GK241, we applied molecular mechanics docking and molecular dynamics (MD) calculations. More specifically, to simulate the specific interaction, compound GK241 was subjected to covalent docking calculations as implemented in the Maestro Schroedinger suite by creating a covalent bond between Cys145 and the 2-carbonyl carbon of the 2-oxoamide moiety. The procedure transformed carbonyl to an sp 3 carbon atom and the adjacent oxygen to a hydroxyl group. The crystal structure of SARS-CoV-2 M pro protein PDB 6Y2F [15] was adequately prepared for simulations by adding the two missing flexible residues E47 and D48, as this loop was near the binding cavity and initial calculations showed that it could interact with the ligand. Moreover, initial calculations showed that the formation of the covalent bond could result in both R and S configurations for the 2-carbon atom, which is not surprising, since there are examples in the literature reporting inhibitors that may lead to both R and S configurations [28]. Thus, docking calculations were finally performed to collect 100 structures for each 2-carbon atom configuration. These structures were further ranked according to the ligand binding energy calculated using the MM-GBSA approach, ranging between −58.69 to −10.66 kcal/mol. Common structural characteristic of the generated structures for both the R and S configuration groups was the tendency to orient the long aliphatic chain to S2, S3, S4 protease clefts (Figure 2A,B), while differences were mainly observed in the conformation of the covalent bond formatted between Cys145 and the 2-oxoamide carbonyl, as expressed by the dihedral angle Cβ cys145 -S cys145 -C2-O2. The lowest energy structures of up to 3 kcal relative binding energy were grouped according to common conformational characteristics of the ligand; representative structures are shown in Figure 2C and Figure S1 (Supplementary Materials). The resulting docking structures appeared to sample the available conformational space by orienting the valine moiety carboxylate (structures 3 and 5) or isopropyl (structures 2 and 4) to the S1 cavity, while in structures 1 and 6 the -OH group or the initial part of the aliphatic chain were oriented in this cleft. Another interesting structural characteristic was that only structures 2, 5 and 7 interacted with H41 specifically through the -OH group. These seven selected structures were further subjected to 50 nsec MD calculations to assess the stability of the protein-ligand interaction. The calculated binding energies and mean RMSD for both protein and ligand are summarized in Table S1 (Supplementary Materials) along with major interactions between the ligand and specific protein residues. Visual inspection of the MD trajectories and conformational flexibility of both the protein and the ligand showed that, in most of the structures, the long aliphatic chain had the tendency to widely explore the conformational space, probably inducing protein conformational changes. The RMSF calculated for the protein Cα showed that the loop between residues 45-50, in particular, exhibited increased flexibility ( Figure S2, Supplementary Materials) which appeared to be related to interactions with part of the long aliphatic chain. A relative flexibility was also observed for residues 185-192, specifically in the case of structure 1. Among the seven structures, the most stable during MD simulations was found to be structure 7, and, thus, MD simulations were extended to 150 nsec to validate the initial observation ( Figure 2D). In structure 7, the 2-carbon atom exhibited an S configuration and both the -OH and amide moieties aligned, in general, very well with the ketoamide crystal structure reported by Hilgenfeld and coworkers [15] (Figure 2A,B). The -OH group interacted with H41 for 50% of the MD sampled structures, while the valine side-chain occupied the S1 cavity with the carboxylate interacting with Q166 and the amide NH forming an H-bond with the T26 backbone carbonyl during the whole MD simulation, both directly and through a water molecule. Both protein and ligand RMSD appeared to be low during the whole MD simulation and the protein RMSF validated the stability of all parts of the protein (Figure 2C,D).
( Figure S2, Supplementary Materials) which appeared to be related to interactions with part of the long aliphatic chain. A relative flexibility was also observed for residues 185-192, specifically in the case of structure 1. Among the seven structures, the most stable during MD simulations was found to be structure 7, and, thus, MD simulations were extended to 150 nsec to validate the initial observation ( Figure 2D). In structure 7, the 2carbon atom exhibited an S configuration and both the -OH and amide moieties aligned, in general, very well with the ketoamide crystal structure reported by Hilgenfeld and coworkers [15] (Figure 2A,B). The -OH group interacted with H41 for 50% of the MD sampled structures, while the valine side-chain occupied the S1′ cavity with the carboxylate interacting with Q166 and the amide NH forming an H-bond with the T26 backbone carbonyl during the whole MD simulation, both directly and through a water molecule. Both protein and ligand RMSD appeared to be low during the whole MD simulation and the protein RMSF validated the stability of all parts of the protein (Figure 2C,D). In order to further rationalize the experimental results, the derivatives 8d and 8a were subjected to covalent docking following the same procedure as above, resulting in 100 structures for each of the R and S 2-carbon configurations. The calculated MM-GBSA interaction energies were higher in both cases than those observed for GK241, ranging between −50.91 and −8.35 kcal/mol for 8d and −56.99 and −25.98 kcal/mol for 8a. For comparison with GK241, we selected structures, similar to structure 7, specifically having an In order to further rationalize the experimental results, the derivatives 8d and 8a were subjected to covalent docking following the same procedure as above, resulting in 100 structures for each of the R and S 2-carbon configurations. The calculated MM-GBSA interaction energies were higher in both cases than those observed for GK241, ranging between −50.91 and −8.35 kcal/mol for 8d and −56.99 and −25.98 kcal/mol for 8a. For comparison with GK241, we selected structures, similar to structure 7, specifically having an S configuration and forming an H bond between the -OH and residue H41, which are presented in Figure S3 (Supplementary Materials) along with the crystal structure and structure 7 for comparison. Concerning the derivative 8d, a major difference observed was that the 10-carbon-atom aliphatic chain was always oriented differently covering part of the S1 and S2 cavities, as shown in Figure S3A (Supplementary Materials). This major difference in the conformation of the aliphatic side-chain reflected a major difference in the MM-GBSA calculated binding energy of~4 kcal compared to GK241 structure 7 and was in agreement with the experimental results showing no activity at 40 µM concentration. On the other hand, derivative 8a showed major similarities with GK241 as far as the aliphatic chain was concerned, mainly occupying the same part of the enzyme active site. However, the alanine moiety of 8a occupied the S1 cavity differently to GK241 as the N-Cα ala bond adopted a different conformation compared to GK241, resulting in a different orientation of the methyl group of the alanine moiety compared to the corresponding valine isopropyl. These differences can explain the small differences observed in the experimental activity of these derivatives.

Discussion
PLA 2 s are a superfamily of enzymes [6][7][8] which are involved in almost any inflammatory disease [6][7][8]13,14,29]. In humans, three PLA 2 types, represented by GIIA sPLA 2 , GIVA cPLA 2 and GVIA iPLA 2 , are of high medicinal interest and have been targets for the development of small-molecule synthetic inhibitors [13]. Among the various classes of synthetic inhibitors, 2-oxoamides constitute a class of compounds whose members can selectively inhibit either GIVA cPLA 2 or GIIA sPLA 2 . The results of the present study showed that the selective 2-oxamide inhibitors of GIVA cPLA 2 AX109 and AX074 [22,23] did not exhibit any appreciable inhibition of SARS-CoV- 2 M pro . Similarly, the selective pentafluoroethyl ketone inhibitor of GVIA iPLA 2 GK187 [25] did not show appreciable inhibition of SARS-CoV-2 M pro . On the contrary, the potent 2-oxamide inhibitor of GIIA sPLA 2 (IC 50 143 nM) [24] was found to inhibit SARS-CoV-2 M pro with an IC 50 value of 24 µM. Given that GIIA sPLA 2 has most recently been recognized as a factor contributing to the severity and mortality of COVID-19 [12,30], this finding is of high importance.
Peptide and peptide-mimetic 2-oxoamides have been identified as potent inhibitors of SARS-CoV-2 M pro and their interaction with the catalytic site of the cysteine protease SARS-CoV-2 M pro has been defined by determining the X-ray structure of the enzyme-inhibitor complex [15]. Inhibitors of SARS-CoV-2 M pro have attracted high interest as candidate antiviral drugs [31,32], and, recently, the inhibitor PF-07321332 (nirmatrelvir) has received emergency approval by the Food and Drug Administration (FDA).
Inflammation is a critical factor in COVID-19 [5,33], and, consequently, agents able to combat virus replication, and, at the same time, regulate inflammation, could offer a new approach for the treatment of COVID-19. Since GIIA sPLA 2 is associated with increased mortality by COVID-19 [12], and lipid mediators arising from the activity of PLA 2 have been correlated with severe SARS-CoV-2 infection in humans [34], a therapeutic compound able to simultaneously inhibit both SARS-CoV-2 M pro and GIIA sPLA 2 would be of great value, as it would significantly reduce the risk of COVID-19 mortality. For the first time, a dual inhibitor of GIIA sPLA 2 and SARS-CoV-2 M pro is identified. GK241 shows weak inhibitory activity against SARS-CoV-2 M pro compared to other known 2-oxoamide SARS-CoV-2 M pro inhibitors; however, it may represent a basis for the development of a new class of potent dual-action inhibitors.

General Chemistry Methods
Forced-flow chromatography on Merck ® (Merck, Darmstadt, Germany) Kieselgel 60 F 254 230-400 mesh was used for the purification of the products, while aluminumbacked silica plates (0.2 mm, 60 F 254 ) were used for thin-layer chromatography (TLC). The visualization of the developed chromatograms was performed by fluorescence quenching using phosphomolybdic acid, ninhydrin or potassium permanganate stains. The melting points were determined on a Buchi ® 530 apparatus (Buchi, Flawil, Switzerland) and were uncorrected. Specific rotations were measured on an AA-65 series (Optical Activity Ltd., Bury, UK) polarimeter. 1

General Procedure of Deprotection of tert-Butyl Esters to Carboxylic Acids 8a-c
To a stirred solution of tert-butyl ester 7a,f,g (1 mmol) in dry CH 2 Cl 2 (1 mL), TFA (1 mL) was added and the reaction mixture was left stirring for 3 hrs. After removal of the solvent, the residue was diluted in diethyl ether and precipitation by petroleum ether (40-60 • C) and filtration afforded the desired product.    To a flame-dried flask, under argon, NaH 60% (1.3 mmol, 52 mg) and dry N,Ndimethylformamide (DMF) (1.3 mL) were added. A solution of alcohol 9 (1.0 mmol, 203 mg) in dry DMF (0.7 mL) was added dropwise at 0 • C. The reaction mixture was stirred for 30 min at 0 • C and then benzyl bromide (1.1 mmol, 0.13 mL) was added dropwise. The reaction mixture was left stirring for 16 hrs at room temperature. Upon completion, the reaction mixture was quenched with a saturated aqueous solution of NH 4 Cl (1 mL), H 2 O (3 mL) was added, the aqueous layer was extracted with ethyl acetate (2 × 10 mL) and the combined organic layers were washed with H 2 O (15 mL). The organic layer was collected, and after drying over Na 2 SO 4 , the solvent was removed under reduced pressure.

Enzyme Assay
The enzyme inhibition assay was performed as previously described [15]. A buffer composed of 20 mM Tris, 100 mM NaCl, 1 mM EDTA, pH 7.3 was used for the enzyme inhibition assay. For the determination of the inhibition rate, 0.5 µM of SARS-CoV-2 M pro was incubated with 40 µM or 100 µM of 2-oxoamide in the buffer at 37 • C for 10 min. The FRET substrate was then added to each well at a final concentration of 10 µM and a final total volume of 50 µL, to initiate the reaction. The GraphPad Prism 6.0 software (GraphPad) was used for the calculation of % inhibition rate. Measurements of the inhibition rate for the compounds were performed in triplicate and are presented as mean ± SD.

Protein Preparation
Docking calculations were performed using the SARS-CoV-2 M pro crystallographic structure in complex with the covalent α-ketoamide inhibitor 13b (PDB ID: 6Y2F) [15]. Preparation and minimization of M pro , using the Protein Preparation Wizard tool within the Maestro Schrodinger suite, were performed to ensure structural correctness. Hydrogen addition, bond orders and steric clashes correction, water molecules and HetAtoms deletion, charge optimization and restrained minimization supported by the OPLS3 force field were achieved [35]. Moreover, addition of the missing residues E47 and D48 was performed using the Crosslink Proteins tool, in the Maestro Schrodinger suite. The inhibitor GK241 and analogs 8a and 8d were prepared for docking using the LigPrep tool, in the Maestro Schrodinger suite [36].

Covalent Docking
Covalent docking is a multiple step process, that is designed upon Schroedinger's Glide and Prime, capable to determine ligands activity against a protein target taking into account both non-covalent interactions and covalent bond formation. Covalent docking calculations were carried out using the Covalent Docking application, implemented in Maestro Schrodinger suite. Initially, pose selection was carried out using non-covalent docking simulations (Glide) and positional constraints. Specifically, ligand docking was performed in a mutated binding site. The reactive residue was transformed to alanine and the ligand warhead (the ligand moiety able to form covalent bond) was docked closely to the catalytic residue avoiding unfavorable clashes. Subsequently, the mutation was reversed, and receptor sampling was performed. Covalent bond formation was achieved based on geometric criteria and structural optimization. The following step involved both minimization of protein-ligand complexes in vacuum, and clustering of the optimized poses. This early selection was used as a basis for the further minimization, scoring and


s2fieldsofstudy:
Biology
Agricultural And Food Sciences

text:
Antimicrobial Resistance in Escherichia coli from the Broiler Farm Environment, with Detection of SHV-12-Producing Isolates

Antimicrobial resistance is an important One Health challenge that encompasses the human, animal, and environmental fields. A total of 111 Escherichia coli isolates previously recovered from manure (n = 57) and indoor air (n = 54) samples from a broiler farm were analyzed to determine their phenotypes and genotypes of antimicrobial resistance and integron characterization; in addition, plasmid replicon analysis and molecular typing were performed in extended-spectrum-beta-lactamase (ESBL) producer isolates. A multidrug-resistance phenotype was detected in 46.8% of the isolates, and the highest rates of resistance were found for ampicillin, trimethoprim–sulfamethoxazole, and tetracycline (>40%); moreover, 15 isolates (13.5%) showed susceptibility to all tested antibiotics. None of the isolates showed imipenem and/or cefoxitin resistance. Twenty-three of the one hundred and eleven E. coli isolates (20.7%) were ESBL producers and carried the blaSHV-12 gene; one of these isolates was recovered from the air, and the remaining 22 were from manure samples. Most of ESBL-positive isolates carried the cmlA (n = 23), tet(A) (n = 19), and aac(6′)-Ib-cr (n = 11) genes. The following genetic lineages were identified among the ESBL-producing isolates (sequence type-phylogroup-clonotype): ST770-E-CH116–552 (n = 12), ST117-B2-CH45–97 (n = 4), ST68-E-CH26–382/49 (n = 3), ST68-E-CH26–49 (n = 1), and ST10992-A/B1-CH11–23/41/580 (n = 4); the latter two were detected for the first time in the poultry sector. At least two plasmid replicon types were detected in the ESBL-producing E. coli isolates, with IncF, IncF1B, IncK, and IncHI1 being the most frequently found. The following antimicrobial resistance genes were identified among the non-ESBL-producing isolates (number of isolates): blaTEM (58), aac(6′)-Ib-cr (6), qnrS (2), aac(3)-II (2), cmlA (6), tet(A)/tet(B) (22), and sul1/2/3 (51). Four different gene-cassette arrays were detected in the variable region of class 1 (dfrA1-aadA1, dfrA12-aadA2, and dfrA12-orf-aadA2-cmlA) and class 2 integrons (sat2-aadA1-orfX). This work reveals the worrying presence of antimicrobial-resistant E. coli in the broiler farm environment, with ESBL-producing isolates of SHV-12 type being extensively disseminated.

Introduction
Antimicrobial resistance (AMR) is one of the biggest problems that face health authorities worldwide. For a long time, AMR has been focused on the clinical setting, but nowadays, it is clear that this is a problem that involves humans, animals, and the environment, and AMR bacteria can be disseminated throughout the environment, which requires a One Health approach. The emergence and the spread of AMR are closely related to the were cleaned with mobile machinery. Before loading new flocks, the farm was disinfected. Broiler farm samplings were conducted at 15-16 days after chick entry, and temperature and relative humidity inside the building were 27 ± 1 • C and 70%, respectively. Air samples were taken inside the farm by stationary and mechanical sampling methods (Air Ideal), and non-antibiotic supplemented Chromocult coliform agar (CCA, Merck) plates were used for E. coli recovery. The manure samples were collected aseptically at the same time and place. Free mobility of the chickens in the enclosure ensured the homogeneity of the litter. Microbiological analysis was performed on 10 g of each litter sample homogenized with 90 mL of sterile peptone water. Serial dilutions of homogenized litter samples were performed and spread on the surface of CCA agar plates. By this procedure, 54 isolates of indoor air and 57 of manure from the farm were obtained. These isolates were identified by MALDITOF-MS (Matrix-Assisted Laser Desorption/Ionization) (Bruker Daltonik, Bremen, Germany) and preserved at −80 • C, and they were included and characterized in the present study.

Characterization of Antimicrobial Resistance Genes, Integrons, and Plasmids
DNA extraction from E. coli isolates was performed using the boiling method; briefly, one colony of an overnight culture was suspended in 1 mL of MilliQ water, and later, it was boiled for 8 min to break down the cell wall and centrifuged at 12,000 r.p.m. for 2 min to remove the pellet. DNA concentration was checked using the Nanodrop spectrophotometer.
In addition, the presence of integrase genes (int1 and int2) of class 1 and class 2 integrons and their variable regions were analyzed by PCR "primer-walking" strategy and subsequent sequencing [11,25].
Plasmid incompatibility (Inc) groups were determined by the PCR-based replicon typing (PBRT) [26] in all the ESBL-producing E. coli isolates.

Molecular Typing
All the isolates of the collection were assigned to different phylogroups by multiplex PCR assay [27]. Multilocus sequence typing (MLST) of the ESBL-producing isolates was performed by PCR and sequencing of seven housekeeping genes, according to the guidelines available at https://pubmlst.org/bigsdb?db=pubmlst_ecoli_achtman_seqdef (accessed on 10 January 2022), to determine the sequence type (ST) and the clonal complex (CC). Clonotype identification was performed by sequencing of fumC and fimH genes (CH) [28].

Statistical Analysis
Statistical analysis was carried out in IBM SPSS 26.0 using the chi-square test to compare pairwise differences in resistance rates to each antimicrobial agent between indoor air and manure samples and also among ESBL-and non-ESBL producers. A p-value < 0.05 is considered a statistically significant difference. Statistical analysis of the correlation between phenotypic and genotypic resistance was performed by calculating Pearson's correlation coefficient with R Study (SAS Institute Inc., Cary, NC, USA).

Antimicrobial Susceptibility Testing
Fifteen of the one hundred and eleven E. coli isolates (13.5%) showed susceptibility to all antimicrobial agents tested, and the remaining isolates (86.5%) exhibited resistance to at least one agent, with 52 isolates being considered as MDR (46.8%). High resistance rates were obtained for AMP, SXT, TET, and CIP (75.7-38.7%) and lower rates for CHL, CAZ, CTX, AMC, and GEN (27-10%). No IMP or FOX resistances were found in this collection of isolates. In addition, significant differences were observed between indoor air and manure isolates for AMP, AMC, CAZ, CTX, CIP, CHL, SXT, and TET resistance rates ( Figure 1).

Statistical Analysis
Statistical analysis was carried out in IBM SPSS 26.0 using the chi-square test to compare pairwise differences in resistance rates to each antimicrobial agent between indoor air and manure samples and also among ESBL-and non-ESBL producers. A p-value < 0.05 is considered a statistically significant difference. Statistical analysis of the correlation between phenotypic and genotypic resistance was performed by calculating Pearson's correlation coefficient with R Study (SAS Institute Inc., Cary, NC, USA).

Antimicrobial Susceptibility Testing
Fifteen of the one hundred and eleven E. coli isolates (13.5%) showed susceptibility to all antimicrobial agents tested, and the remaining isolates (86.5%) exhibited resistance to at least one agent, with 52 isolates being considered as MDR (46.8%). High resistance rates were obtained for AMP, SXT, TET, and CIP (75.7-38.7%) and lower rates for CHL CAZ, CTX, AMC, and GEN (27-10%). No IMP or FOX resistances were found in this collection of isolates. In addition, significant differences were observed between indoor air and manure isolates for AMP, AMC, CAZ, CTX, CIP, CHL, SXT, and TET resistance rates ( Figure 1). Figure 1. Percentages of antibiotic resistance among the total E. coli isolates (n = 111) and from those obtained from manure (n = 57) and indoor air (n = 54). Abbreviations: AMP-ampicillin; AMCamoxicillin clavulanate; CAZ-ceftazidime; CTX-cefotaxime; CIP-ciprofloxacin; GEN-gentamicin; CHL-chloramphenicol; SXT-trimethoprim/sulfamethoxazole; TET-tetracycline. No resistance for imipenem and cefoxitin was identified among the isolates. * p-value < 0.05. Resistance rates for CIP, CHL, and TET were higher among ESBL-positive isolates, but the pattern was different for GEN and SXT. It is important to highlight that significant differences were detected between ESBL-and non-ESBL-producing isolates for CIP, CHL, SXT, and TET, in addition to, as expected, broad-spectrum cephalosporins ( Figure 2).
Resistance rates for CIP, CHL, and TET were higher among ESBL-positive isolates, but the pattern was different for GEN and SXT. It is important to highlight that significant differences were detected between ESBL-and non-ESBL-producing isolates for CIP, CHL, SXT, and TET, in addition to, as expected, broad-spectrum cephalosporins ( Figure 2).

Molecular Characterization and Typing of ESBL-Producing E. coli
A total of 23 of the 111 E. coli isolates showed an ESBL phenotype, hosting diverse AMR phenotypes and genotypes, as well as genetic lineages. Most of these isolates were obtained from manure samples, but interestingly, one of the ESBL producers (X2583) was obtained from an indoor air sample. All these isolates carried the gene encoding the betalactamase SHV-12, with one of them (X2685) also carrying the gene encoding TEM-1.
Most of the ESBL producers showed CHL and TET resistance and carried the cmlA and tet(A) genes (with few exceptions). Eleven out of fourteen CIP-resistant isolates harbored the aac(6′)-Ib-cr gene. Two additional CIP-resistant isolates presented point mutations in the QRDR region in the gyrA and parC genes: two amino acid changes were detected in GyrA (S83L, D87N) and one in ParC (S80I). In addition, the sul1 and sul3 genes were detected in two and four isolates, respectively.
The 23 SHV-12-producing E. coli isolates were typed by MLST, and four different ST were detected: (a) twelve isolates were typed as ST770 and phylogroup-E (52.2%); the isolate from indoor air was included in this group; (b) three isolates were typed as ST68 and phylogroup-E (13%); (c) four isolates were typed as ST117 and phylogroup-B2 (17.4%); and (d) four isolates were typed as ST10992 (17.4%), two of them ascribed to phylogroup-A and the other two to phylogroup-B1. The CH typing identified seven clonotypes, with CH116-552 being the most prevalent, present in 12 ESBL producers associated with ST770. Other prevalent clonotypes were CH45-97 (two ST117 isolates), CH11-41 (two ST10992

Molecular Characterization and Typing of ESBL-Producing E. coli
A total of 23 of the 111 E. coli isolates showed an ESBL phenotype, hosting diverse AMR phenotypes and genotypes, as well as genetic lineages. Most of these isolates were obtained from manure samples, but interestingly, one of the ESBL producers (X2583) was obtained from an indoor air sample. All these isolates carried the gene encoding the beta-lactamase SHV-12, with one of them (X2685) also carrying the gene encoding TEM-1.
Most of the ESBL producers showed CHL and TET resistance and carried the cmlA and tet(A) genes (with few exceptions). Eleven out of fourteen CIP-resistant isolates harbored the aac(6 )-Ib-cr gene. Two additional CIP-resistant isolates presented point mutations in the QRDR region in the gyrA and parC genes: two amino acid changes were detected in GyrA (S83L, D87N) and one in ParC (S80I). In addition, the sul1 and sul3 genes were detected in two and four isolates, respectively.

Characterization of Antimicrobial Resistance Genes among Non-ESBL-Producing Isolates
AMR genes were analyzed in the collection of 88 non-ESBL-producing isolates. Fiftyeight of the sixty-one AMP-resistant isolates carried the bla TEM gene (95.1%). Several acquired resistance genes, such as aac(6)-Ib-cr and qnrS, were detected in six and two isolates out of twenty-nine CIP-resistant isolates, respectively. Most of the 28 TET-resistant isolates carried the tet(A) and/or tet(B) genes, either alone or combined (78.6%). Moreover, 51 of the 57 SXT-resistant isolates (89.5%) carried sul genes (sul1, sul2, or sul3), either alone or associated. The aac(3)-II and cmlA genes were detected among GEN-and CHL-resistant isolates, respectively ( Table 2). All isolates were negative for mcr-1, a gene associated with colistin resistance. Table 2. Antimicrobial resistance genes detected among the 88 non-ESBL-producing E. coli isolates in relation to their phenotype of resistance.

Characterization of Integrons among STX-Resistant E. coli Isolates
The presence of intl1 and intl2 genes was analyzed in the 62 SXT-resistant E. coli isolates detected in this study. The intI1 gene was identified in 26 isolates, intI2 in 7 isolates, and both genes in 5 additional isolates ( Table 2). The variable region of class 1 and/or class 2 integrin's could be identified in 14 of these isolates, and their gene cassettes arrays are shown in Table 3. In this regard, three types of gene-cassettes arrays (GC) have been detected in the class 1 integrons among the 11 isolates which could be characterized: (1)

Characterization of Integrons among STX-Resistant E. coli Isolates
The presence of intl1 and intl2 genes was analyzed in the 62 SXT-resistant E. coli isolates detected in this study. The intI1 gene was identified in 26 isolates, intI2 in 7 isolates, and both genes in 5 additional isolates ( Table 2). The variable region of class 1 and/or class 2 integrin's could be identified in 14 of these isolates, and their gene cassettes arrays are shown in Table 3. In this regard, three types of gene-cassettes arrays (GC) have been detected in the class 1 integrons among the 11 isolates which could be characterized: (1) dfrA1-aadA1 (n = 8); (2) dfrA12-aadA2 (n = 2) linked to sul1; and (3) dfrA12-orfX-aadA2-cmlA linked to sul3 (n = 1). The variable region of class 2 integrons was identified in five isolates, and the GC found was sat-aadA1 (Table 3).

Discussion
The AMR of E. coli isolates from the broiler farm environment was analyzed in this study, with a special focus on the characterization of ESBL-producing isolates. Of relevance is the high incidence (20.7%) of ESBL producers detected among the collection of E. coli isolates. It is important to note the detection of ESBL-producing E. coli isolates of the same genetic lineage and ESBL type in manure (n = 11) and indoor air samples (n = 1) from the broiler farm, showing dissemination of these resistant bacteria in different niches of the farm.
Among the most relevant results observed concerning the AMR patterns of the antibiotics studied, the highest resistance rates were detected for CHL, TET, and CIP (in ESBL-producing isolates, in addition to β-lactams), and for AMP, CIP, TET, and SXT (in non-ESBL-producing isolates) coinciding closely with the results reported by EFSA [1]. This could be associated with the high use of these antimicrobials in the poultry sector. The statistical analysis revealed a close correlation between antibiotics from different families, which might be explained by the location of the implicated resistance genes in the same genetic structures that could be co-selected.
ESBL genes could be transferred via plasmids between bacteria of diverse origins. The F, FIB, K, and HI1 plasmids were frequently detected among the SHV-12-producing isolates in poultry in other studies [38,39]. Moreover, IncI1 plasmids are also found associated with bla SHV-12 in the human and animal environment [17,40] and even in food isolates [10,30], where IncK and IncX3 replicons were also detected, in lower proportions. The IncF, IncF1B, IncK, IncHI1, and IncI1 replicon types have also been detected among our ESBL-producing isolates. Additional research is necessary to analyze in greater depth the genetic information associated with the ESBL and/or MDR phenotypes.
The ST770 lineage has been previously reported in CTX-M-1-or CMY-2-producing E. coli from poultry or chicken meat in different European countries [39,41] and associated with ESBL-negative avian pathogenic E. coli (APEC) [42]. Moreover, ST770 has also been detected in CTX-M-14-and CTX-M-2-producing E. coli isolates implicated in urinary tract infections [43]. Interestingly, this lineage has also been reported in ESBL producers from litter and poultry farm air (SHV and TEM-types), which reinforces the importance of cleaning and disinfection protocol to remove the microbial load before introducing the litter into the farms [44], according to the "all-in-all-out" strategy to avoid the dissemination of MDR bacteria. Furthermore, this lineage has also been detected in isolates carrying very relevant resistance genes, such as mcr-1 (colistin resistance), in that case in pets [45]. Data collected from studies in several countries show an increased association of the ST770 lineage with ESBL-and pAmpC-producing E. coli isolates.
Three of the lineages detected in this study (ST68, ST770, and ST117) have been detected in SHV-12, CTX-M-1, CTX-M-14, and/or CTX-M-15-positive E. coli isolates from food-producing animals [17]. In other origins, such as wildlife and companion animals, these three genetic lineages were found associated with the production of CMY-2 [46,47] and ST117 with the expression of CTX-M-1. [48]. In addition, ST68 has been reported in carbapenemase-positive isolates (OXA-48) [49]. Nevertheless, to our knowledge, the lineage ST68 has not been detected in Europe in SHV-12-producer isolates of poultry origin.
The ST117 is the most widespread genetic lineage in the poultry sector, being also the most frequent in our study. This lineage has been detected in SHV-12 producers from poultry slaughterhouse wastewater in Germany [34], and its high prevalence continues in the broiler production pyramid [50]. This lineage has also been detected in avian farming in ESBL-positive isolates carrying genes of the CTX-M family (CTX-M-1, CTX-M-14, CTX-M-15) or in CMY-2 producers [51]. In this sense, ST117 is considered a reservoir for ESBL and pAmpC encoding genes in poultry and is also closely associated with APEC isolates [52,53].
The unusual ST10992 lineage was firstly reported in this study, to our knowledge, in the poultry farm environment, among SHV-12-producing isolates.
Phylogenetic grouping provides epidemiological and ecological information related to the virulence capacity of E. coli isolates. Several studies revealed that phylogroups B2, D, E, and F are strongly associated with extraintestinal infections in humans (EXPEC strains), whereas A and B1 are generally associated with commensal bacteria in humans and animals, including those ESBL producers [43,51]. In this sense, phylogroups A, B1, and F have been frequently found among ESBL-producing E. coli isolates from poultry farms in different European studies, with phylogroups B2 and D scarcely detected [50,54]. Studies from the poultry environment in Africa reveal the predominance of phylogroups A and D [55]. In our study, the presence of A and B1 was evident among ESBL-producing isolates, although phylogroups E and B2 were also frequently detected.
Integrons are mobilizable genetic elements whose study in recent years has gained relevance due to their role in the acquisition and dissemination of AMR. Four types of gene cassette arrays were detected among the eleven characterized isolates in our study, associated to class 1 (dfrA1-aadA1, dfA12-aadA2, and dfrA12-orfX-aadA2-cmlA) and class 2 integrons (sat2-aadA1). They carried resistance genes to old antibiotics, such as trimethoprim (dfrA1, dfrA12), streptomycin (aadA1, aadA12), chloramphenicol (cmlA), or streptothricin (sat2), whose use in animals or humans could contribute to the selection of integron-positive isolates. The presence of integrons in poultry E. coli isolates containing the classical dfrA1-aadA1 structure has been previously reported [52,56].
Potential sources of AMR in poultry production consist of air, dust, soil, feed, and rodents or other animals. From these sources, AMR bacteria and genes can be transmitted to humans through the food chain or indirectly by the environment, posing a threat to public health [1]. Several studies have shown the role of air as a disseminating vehicle and the ability to persist both inside and outside a farm, and poultry manure is considered to be the main vector for the spread of AMR bacteria [55].

Conclusions
ESBL-producing isolates frequently contaminate the poultry farm environment, and these resistant bacteria could be present in the farm air. In our case, SHV-12 was the only ESBL type detected, which has been observed in different E. coli clones, some of them very frequent in the poultry sector in both ESBL-producing and APEC isolates. Furthermore, the detection of the same genetic lineage in both poultry manure and airborne isolates provides further evidence of the transmissibility of these resistant bacteria and their ability to survive and adapt to any niche. Close surveillance on the dissemination of ESBL-producing isolates in the farm environment should be performed to avoid the dissemination of these isolates through the food chain or indirectly through the air or dust, among others.
This study shows that both manure and airborne dust particles are important sources of resistant bacteria and AMR genes due to the high survival of these resistant microorganisms, making it necessary to apply appropriate cleaning protocols to reduce and avoid as much as possible the survival of bacteria. Based on these results, it is suggested that broiler farms could be considered as important vehicles for the transmission of multidrug-resistant bacteria favoring their spread into the natural environment and in turn posing a risk to public health.
AMR is probably the clearest example of a global and growing problem that requires solutions to deal with the "One Health" approach. Coordinated and precise actions are needed to reduce its impact now and in the future, as well as measures to ensure the economic viability of the poultry sector together with public health assurance.


s2fieldsofstudy: Biology Medicine

text:
CD45RB Glycosylation and Ig Isotype Define Maturation of Functionally Distinct B Cell Subsets in Human Peripheral Blood

Glycosylation of CD45RB (RB+) has recently been identified to mark antigen-experienced B cells, independent of their CD27 expression. By using a novel combination of markers including CD45RB glycosylation, CD27 and IgM/IgD isotype expression we segregated human peripheral blood B cell subsets and investigated their IGHV repertoire and in vitro functionality. We observed distinct maturation stages for CD27-RB+ cells, defined by differential expression of non-switched Ig isotypes. CD27-RB+ cells, which only express IgM, were more matured in terms of Ig gene mutation levels and function as compared to CD27-RB+ cells that express both IgM and IgD or cells that were CD27-RB-. Moreover, CD27-RB+IgM+ cells already showed remarkable rigidity in IgM isotype commitment, different from CD27-RB+IgMD+ and CD27-RB- cells that still demonstrated great plasticity in B cell fate decision. Thus, glycosylation of CD45RB is indicative for antigen-primed B cells, which are, dependent on the Ig isotype, functionally distinct.

INTRODUCTION
B cell development and the formation of a highly diverse pool of long-lived antibody-secreting cells and memory B cells is crucial for the humoral immune response and lasting immunological memory. During the course of an immune response, the immunoglobulin (Ig) gene is changed by the process of somatic hypermutation (SHM), class switch recombination (CSR), and selection in response to antigen stimulation. Hypermutated and class-switched Ig genes are a characteristic of memory B cells along with the loss of IgD expression. Gain of CD27 expression, often combined with absent IgD expression, is commonly used to discriminate human memory B cells from naive B cells. However, a substantial proportion of CD27-B cells in healthy adults displays mutated and isotype-switched Ig genes like memory B cells (1)(2)(3), which disputes the feasibility of using CD27 as a truly discriminative memory marker. Mutated CD27-cells are present at birth (4) and account for 5% of the peripheral blood B cell population in healthy adults (1). The function of these putative CD27-memory cells and their relationship to CD27+ cells is not well understood but increased frequencies have been observed during aging (5), in autoimmunity (6) and several viral infections (7,8). The lack of markers to distinguish naive B cells from memory B cells resulted in novel strategies for B cell classification using phenotypical differences in addition to CD27 and Ig isotype (9). Several studies identified changes in site-specific O-linked glycosylation of CD45RB during human B cell differentiation in various secondary lymphoid organs and blood (10)(11)(12)(13)(14). This glycandependent CD45RB epitope can be detected using the mAb MEM-55 and within human peripheral blood, glycosylation of CD45RB (RB+) was absent on naive B cells, but highly expressed on CD27+ cells and on a small fraction of switched and nonswitched CD27-B cells (10). Next-generation sequencing of the Ig heavy chain variable (IGHV) genes revealed that these CD27-RB+ cells displayed intermediate levels of somatic mutations, higher than CD27-RB-but lower than CD27+RB+ cells (1,14), suggesting that these B cells are antigen-primed and no longer naive. On the other hand, these CD27-RB+ cells, with high IgM levels, were found with increased frequencies in young children and early after hematopoietic stem cell transplantation (HSCT) (11), suggesting an immature rather than memory stage. Thus, CD45RB glycosylation, in combination with CD27 expression and Ig isotype, may serve as an additional marker to improve classification of human naive and memory B cells. Here, we investigated human peripheral blood B cell subsets segregated by CD45RB glycosylation, CD27 and IgM/IgD isotype expression and studied their IGHV repertoire and in vitro functionality.

Human B Cell Isolation
Buffy coats were obtained from anonymized adult healthy donors with written informed consent in accordance to the guidelines established by the Sanquin Medical Ethical Committee and in line with the Declaration of Helsinki. Human peripheral blood mononucleated cells (PBMCs) were isolated from buffy coats using Ficoll gradient centrifugation (lymphoprep; Axis-Shield PoC AS) and CD19 + cells were isolated by positive selection using magnetic Dynabeads (Invitrogen).

FACS Sorting
Cryopreserved CD19+ cells were surface stained in PBA (PBS supplemented with 0.1% bovine serum albumin) for 30 min at 4°C and washed in PBA. A LIVE/DEAD cell staining (ThermoFisher scientific) was used to label and exclude non-viable cells. B cells were gated as singlet, viable, CD19+ cells and were segregated further into six subsets using surface marker expression of: CD27, CD38, CD45RB glycosylation, IgD, IgM, IgG, and IgA. Subsets were FACS-sorted (FACS Aria III, BD Biosciences) into RTL buffer (Sigma-Aldrich) for next-generation sequencing or in PBA for in vitro stimulation assays.
Immune Repertoire Sequencing 5000 B cells were sorted per subset per donor (n = 3), lysed and gDNA was extracted according to the manufacturer's instructions (Qiagen). IgH rearrangements were amplified in a multiplex PCR using forward primers V H 1-6 FR1 (BIOMED-2) and J H consensus reverse primers with a Molecular Identifier (MID)-tag. A total of 40 PCR cycles were performed and a heat stable polymerase with proof-reading activity was used (AmpliTaq Gold DNA polymerase, Thermo Fisher). Equal quantities of PCR products were pooled and purified by gel extraction (MinElute gel extraction kit, Qiagen) and Agencourt AMPure XP beads (Backman Coulter) and quantified by fluorescence using the Qubit 2.0 Fluorometer (Invitrogen). Sequencing was performed using a Illumina Miseq run in standard mode using a v3 kit.

Repertoire and Mutation Analysis
Reads retrieved from the sequencing platform were processed using pRESTO (15). Briefly, paired-ends reads were assembled using the AssemblePairs.py function and assembled reads with a phred score < 25 were removed. V H , J H primers and MID-tags were annotated and masked using the MaskPrimers.py function. Obtained datasets were then submitted to IMGT/HighV-QUEST (16,17) for alignment. Aligned sequences were further processed using Change-O (18). Output of the IMGT/HighV-QUEST was parsed using the MakeDb.py function (18) and only functional rearrangements were selected. Analysis of somatic hypermutation was performed using the SHazaM R package (version 0.2.1) after germline sequence reconstruction using the CreateGermlines.py function from Change-O. All data here presented are performed on a final dataset of unique nucleotidic sequences (spacing from the IGHV to the IGHJ gene, primers excluded). Due to the lack of unique molecular identifiers (UMIs) in the amplification protocol, it was not possible to properly correct for technical artifacts such as PCR and sequencing errors. Therefore, we removed reads that occurred only once (singletons) with the assumption that technical artifacts occur randomly and independently of each sample's origin and are therefore equally distributed in all analyzed samples. Information on the total and unique rearrangements per sample, before and after singletons exclusion, and IGHV and IGHJ gene representation is reported in Supplementary Table 1. Raw sequencing data have been deposited at NCBI Sequence Read Archive (BioProject: PRJNA816414) and processed repertoires are available upon request to the corresponding author.
T cell independent (TI) stimulation assays. 96-well flatbottom plates were seeded with 10.000 B cells from each subset per well supplemented with either 0.1mM CpG ODN (In vivogen) or 1mM R848 (In vivogen), in the presence of 1mg/ml anti-IgM F(ab') 2 (JacksonImmunoResearch). After seven days of culture B cell survival, isotype switching, differentiation and Ig secretion were assessed using flow cytometry and ELISA.

IgM, IgG, and IgA ELISA of Culture Supernatants
IgM, IgG, and IgA expression levels were measured as described previously (19). In brief, 96-well maxisorb plates were coated with monoclonal anti-IgM, anti-IgG, or anti-IgA (2mg/ml MH15-1, 2mg/ ml MH16-1, or 1mg/ml MH14-01-M08, Sanquin reagents) and culture supernatants were incubated for 1h. Secreted IgM, IgG, or IgA was detected using HRP-conjugated mouse anti-human IgM, IgG, or IgA (1mg/ml MH15-1, 1mg/ml MH16-1, or 1mg/ml MH14-1, Sanquin reagents) in HPE (Sanquin reagents). The ELISA was developed using TMB substrate, stopped by addition of 0.2M H 2 SO 4 and absorbance was measured at 450 and 540 nm. OD values were normalized to values of a reference serum pool that was included in each plate. To properly determine IgM production, in vitro stimulation assays described above, were also performed in the absence of anti-IgM F(ab') 2 as this compound interferes with the IgM ELISA resulting in an incomplete picture of the IgM production. Of note, the presence of anti-IgM F(ab') 2 may alter IgM production during culture.

Statistical Analysis
Differences between groups were analyzed using a Friedman analysis of variance for non-parametric repeated measures followed by a Dunn's multiple comparison test. A p value <0.05 was considered significant. The statistical analysis was carried out using GraphPad Prism 9.1.1.

B Cell Subsets Separated Based on CD45RB Glycosylation and CD27 Expression Feature Differential Ig Isotype Usage
Human peripheral blood CD19+CD38 lo B cells ( Figure S1A, pregating strategy) can be segregated into four populations based on their CD45RB glycosylation (RB) and CD27 expression levels ( Figure 1A). The CD27-RB-(55%) and CD27+RB+ (28%) populations are more prevalent compared to CD27-RB+ (9.5%) and CD27+RB-(7%) ( Figure 1B). Within these populations differential Ig isotype usage was observed, with CD27+ cells enriched for IgG and IgA and CD27-cells mostly being IgM+ and/or IgD+ ( Figure 1C). Within CD27+ populations, the Ig isotype usage was quite similar, despite cells being RB+ or RB-. By contrast, within CD27-populations, there was an increased prevalence of all IgD-subsets within the RB+ population. By isotype-specific gating around 13% of the CD19+ cells were left unannotated, in line with a recent study (14). These cells are not mislabeled IgE+ B cells as these are extremely rare in healthy peripheral blood (20). The Ig lo cells were found across all four populations and likely represent a mixture of isotypes found on cells that recently underwent class-switching. Thus, the CD27-RB+ population features more isotype-switched cells than the CD27-RB-population, a difference not observed within CD27+ populations.

CD45RB Glycosylation Marks Antigen-Primed B Cells Independent of CD27 Expression
To refine discrimination of CD27/RB populations we included Ig isotype expression for enhanced characterization. In the current study we focused on characterizing the non-isotype switched (IgM and IgD) B cells but excluded CD27-IgD+IgM-B cells that represent a population of anergic B cells that recognize self-antigens (21)(22)(23). Based on the expression of CD27, CD45RB glycosylation and IgM and IgD we discriminated four CD27-populations (Figure 2A Figure 2A). All subsets were gated on being CD38 lo to exclude CD38+ transitional B cells and CD38+ ASCs. Combined the CD27-subsets make up~30% of the adult human peripheral blood B cell population with the largest fraction being IgMD+RB-cells (n = 7, Figure 2B). To investigate the levels of somatic hypermutation in the six different subsets we performed next-generation sequencing of IGHV genes (n = 3). We observed increased somatic mutations in V H -regions of both memory B cell subsets (IgMmem and IgG/Amem), in line with previous studies (24,25). V H -mutations were virtually absent for IgMD+RB-cells and not significantly increased for both IgM+RBand IgMD+RB+ subsets compared to IgMD+RB-cells ( Figure 2C). Remarkably, IgM+RB+ cells had comparable mutation counts as IgMmem, but less than IgG/Amem. Similar results were observed when analyzing the entire cumulative distribution of mutations in the Ig repertoire ( Figure 2D). In addition, IgM+RB+ cells displayed a reduction in V H -CDR3 length (25,26), also similar to IgMmem ( Figure 2E). Taken together, IgM+RB+ cells show characteristic that associate with being antigen-primed despite being CD27-.

CD45RB Glycosylation, Combined With Ig Isotype, Identifies Functionally Distinct B Cell Subsets
Apart from expression of mutated V H genes, memory B cells can be distinguished from naive B cells by more efficient proliferation and differentiation into antibody-secreting cells (ASCs) upon stimulation (26,27). Given that the IgM+RB+ subset carried somatic mutations they may also functionally resemble memory B cells. Therefore, we studied their in vitro functionality, and of the other CD27-subsets, using T cell-dependent (TD) and -independent (TI) stimulation and analyzed survival, differentiation and isotype-switching potential.
The six B cell subsets were cell-sorted and cultured on CD40Lexpressing cells in the presence of IL-21 for 10 days. Survival and/or proliferation was similar for most subsets ( Figure S2A). Compared to IgMD+RB-cells, IgM+RB+ cells showed increased differentiation towards activated and/or memory-like B cells (MBCs, CD27+CD38-, Figures 3A, B). Within IgMmem and IgG/Amem populations, that were sorted as being CD27+, we observed downregulation of CD27 expression, a phenomenon previously observed by others upon in vitro culture of memory B cells (28,29). Interestingly, IgM+RB+ cells, but not IgMD+RB+ cells, had poor IgG switching potential, a feature shared with IgMmem ( Figure 3C). The addition of IL-4, a TD cytokine known to enhance isotype switch to IgG, had limited additional effects and did not alleviate the reduced IgG switch observed for IgM+RB+ cells ( Figures S2B-F). Furthermore, the IgM+RB+ subset showed increased differentiation into functional ASCs (CD27+CD38+, Figures 3A, D, E and Figure S2G), however, this was less in comparison to IgG/Amem. IgMD+RB+ cells, although not significant, did show a trend in increased MBC and ASC formation compared to IgMD+RB-and IgM+RB-cells, but less in comparison to IgM+RB+ cells ( Figures 3B, D, E). Differentiation of B cells also occurs during T cell-independent (TI) immune responses that generally results in the formation of ASCs that secrete low-affinity IgM antibodies (30). Since IgM+RB+ cells showed reduced isotype switch to IgG upon in vitro TD stimulation we studied their functionality, and of the other CD27subsets, upon in vitro TI stimulation. After 7 days of TI stimulation with CpG ODN (TLR9 activator) and anti-IgM, IgM+RB+ and IgMD+RB+ subsets, but not IgM+RB-and IgMD+RB-subsets, were able to differentiate into memory-like B cells ( Figure 3F), albeit, much less when compared to TD stimulation. Furthermore, IgM+RB+ and IgMD+RB+ subsets showed a trend towards increased differentiation into functional ASCs as was observed for IgMmem and IgG/Amem, albeit to various degrees ( Figures 3G,  S3A), and with limited isotype switching ( Figure S3B). Subsets responded in a similar fashion when stimulated with R848 (TLR7/ TLR8 agonist) and anti-IgM for 7 days ( Figure S4). Thus, different from IgMD+RB+, IgM+RB-and IgMD+RB-subsets, IgM+RB+ cells showed a higher propensity for MBC differentiation with an IgM isotype commitment.

DISCUSSION
Here, by using a novel combination of markers including CD45RB glycosylation, CD27 and IgM/IgD isotype expression we segregated human peripheral blood B cell subsets and investigated their IGHV repertoire and in vitro functionality. Table 1 summarizes for each of the studied B cell subset their V H mutation status and in vitro functionality.
IgMD+ RB-cells displayed virtually absent levels of somatic hypermutation, indicating that this population corresponds to "classical" naive B cells. IgM+RB-and IgMD+RB+ cells were both in repertoire and in vitro functionality similar to IgMD+RB-cells. Because IgM+RB-cells were gated on being CD38 lo we do not assume that they represent human T1 B cells that are often characterized by a CD24 hi CD38 hi phenotype (31). Circulating IgM+RB+ cells carried mutated V H genes and reduced CDR3 length which implies previous antigen-priming. This suggests that these cells are at a later stage of development with regards to affinity maturation as compared to the other CD27-subsets. In line, IgM+ RB+ cells also showed improved ability to develop into functional ASCs using TI and TD in vitro stimulations. IgMD+RB+ cells, although not significant and less in comparison to IgM+RB+, did show a trend in increased MBC and ASC formation compared to IgMD+RB-and IgM+RB-cells. These data indicate that CD27-RB+ populations fall within the continuum of naive B cells that progress towards memory B cells and ASCs and do not represent a population of exhausted memory B cells with downregulated CD27, as was proposed previously (5). In addition, the absence of CD45RB glycosylation to define 'true' human naive B cells may advance current strategies using CD27 and IgD. Even though using the glycosylation epitope on CD45RB helps to identify antigenprimed B cells among CD27-cell, there is, however, a population of CD27+ cells, presumed memory B cells, that are RB-, meaning that glycosylation of CD45RB does not mark all antigen primed B cells.
We show that IgM+RB+ cells have properties in common with CD27+IgM+IgD-RB+ cells (IgMmem). IgM+RB+ cells seem to have an early lineage commitment to the IgM isotype as they showed reduced ability to isotype-switch to IgG, similar to IgMmem but in steep contrast to the other CD27-subsets. Moreover, CD27 expression was higher on IgM+RB+ cells after 10 days of TD culture compared to the other CD27-subsets which shows that with the same level of stimulation these cells had enhanced capacity to differentiate towards a memory phenotype. IgM memory B cells are important for the generation of a broadly cross-reactive memory repertoire with lower affinity BCRs to protect against a plethora of pathogens and their variants (32)(33)(34). The early lineage commitment of IgM+RB+ cells to the IgM isotype might represent a mechanism to ensure replenishment of the IgM memory pool for lasting B cell immunity. In contrast, the efficient IgG isotype-switching seen for IgMD+RB+ cells suggests this subset has more plasticity in B cell fate decision. Thus, within RB+ cells, differential expression of IgM and IgD, discriminates two functionally distinct B cell subsets. In line, for CD27+RB+ subsets, only IgG/Amem, but not IgMmem, outperformed both CD27-RB+ subsets in ASC differentiation. This suggest that expression of just CD27 or CD45RB glycosylation upon B cell activation is not indicative for enhanced ASC differentiation, but also relies on the Ig isotype. The notion that the Ig isotype imprints the subsequent fate of the B cell upon recall responses is consistent with data obtained from mouse and human in vitro models indicating that in general the IgM memory B cells re-entered germinal centers to undergo multiple rounds of expansion, somatic hypermutation and selection, whereas IgG memory B cells preferentially differentiated into ASCs (35)(36)(37).  In this study we did not analyze memory subsets with differential expression of IgM and IgD and only included the CD27+IgM+IgD-RB+ subset (IgMmem). For CD27+IgM+IgD+ cells it has been described that they have fewer V H -gene mutation than CD27+IgM+IgD-and class-switched CD27+ cells but more mutations than naive (CD27-IgM+IgD+) and CD27+IgM-IgD+ cells (38). CD27+IgM-IgD+ cells only make up a small fraction of CD27+ cells (7.5%, Figure 1C). Within CD27+RB+ cells, CD27+IgM+IgD+ cells make up around 25% cells and are present to a lesser degree within the CD27+RBpopulation (16%, Figure 1C). Whether, the presence or absence of glycosylated CD45RB on CD27+ cells with differential IgM and IgD expression impacts the level of detectible V H -gene mutations and in vitro functionality remains unclear.
Previous studies reported increased frequencies of CD27-RB+ cells that expressed high levels of IgM in young children and early after hematopoietic stem cell transplantation (11). Unfortunately, the dual IgM/IgD expression on these cells was not determined. Therefore, we cannot assign with certainty whether these are CD27-IgM+RB+ or the CD27-IgMD+RB+ cells. As these cells have increased frequency in children it may be more likely that these are the CD27-IgMD+RB+ cells described here that have fewer mutations and showed a naivelike behavior. However, cord blood and fetal tissues also accommodate a small population of mutated CD27+IgM+IgD+ B cells (39,40). These subsets may represent a first-line defense mechanism that respond rapidly upon both TD and TI activation.
The findings presented here provide novel insights in the phenotypic and functional progression from naive B cells via CD27-RB+ cells to memory B cells in human peripheral blood.
In conclusion, glycosylation of CD45RB is indicative for antigenprimed B cells, which are, dependent on the Ig isotype, functionally distinct.

DATA AVAILABILITY STATEMENT
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: NCBI, accession code: PRJNA816414

ETHICS STATEMENT
Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study.

AUTHOR CONTRIBUTIONS
JK, SP, ST, PvS, MB, and TR designed research. JK, ST, IPK, and ND performed research. JK, SP, and ND analyzed data. JK, SP, and TR wrote the paper. All authors critically reviewed the manuscript, gave final approval of the version to be published, and agreed to be accountable for all aspects of the work ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

FUNDING
This study was supported by Landsteiner Foundation for Blood Transfusion Research (Grant1626).