Crat) in mice. We hypothesised that metabolic sensing in AgRP neurons is required to increase motivation for food reward by modulating accumbal or striatal dopamine release. Studies confirmed that Crat deletion in AgRP neurons (KO) impaired ex vivo glucose-sensing, as well as in vivo responses to peripheral glucose injection or repeated palatable food presentation and consumption. Impaired metabolic-sensing in AgRP neurons reduced acute dopamine release (seconds) to palatable food consumption and during operant responding, as assessed by GRAB-DA photometry in the nucleus accumbens, but not the dorsal striatum. Impaired metabolic-sensing in AgRP neurons suppressed radiolabelled 18F-fDOPA accumulation after ~30 min in the dorsal striatum but not the nucleus accumbens. Impaired metabolic sensing in AgRP neurons suppressed motivated operant responding for sucrose rewards during fasting. Thus, metabolic-sensing in AgRP neurons is required for the appropriate temporal integration and transmission of homeostatic hunger-sensing to dopamine signalling in the striatum.Agouti-related peptide (AgRP) neurons increase motivation for food, however, whether metabolic sensing of homeostatic state in AgRP neurons potentiates motivation by interacting with dopamine reward systems is unexplored. As a model of impaired metabolic-sensing, we used the AgRP-specific deletion of carnitine acetyltransferase ( The motivation to approach and consume food depends not only on the palatability and caloric density of the available food source, but also on the energy state of the organism. For example, when food is abundant many prey species forage within known territories to reduce survival threats . ConversAgouti-related peptide (AgRP) neurons in the arcuate nucleus of the hypothalamus (ARC) are a critical population of hunger-sensitive neurons that primarily function to increase appetite or conserve energy . A key eSensory cues that predict food availability and palatability rapidly suppress hunger-sensitive AgRP neuronal activity in hungry mice . AlthougCrat) in AgRP neurons was required as a molecular sensor for peripheral substrate utilisation during fasting and refeeding  or dorsal striatum, over different time frames, in response to palatable food rewards. These studies highlight that metabolic-sensing in AgRP neurons is required for the appropriate temporal integration of hunger-sensing to potentiate food reward-related dopamine release in the striatum and control motivation for palatable food rewards.Previously, we demonstrated that carnitine acetyltransferase  were detected  and the fall in AgRP activity was measured, as previously described . The falactivity . IP injeactivity , althougactivity , suggestPrevious studies show that chemogenetic activation of AgRP neurons modulates dopamine release in the NAc to food . To asseFurthermore, we aligned the dopamine signal to first contact with the PB chip  and showMost operant conditioning protocols are conducted in stand-alone operant chambers and typically include a mild calorie restriction to facilitate learning the operant task. This exploits the fact that food restriction enhances appetitive drive, which is a result of elevated AgRP neuronal activity . To avoiTo establish that deficits in motivation were associated with impaired dopamine release in the NAc, we used FED3 as it allows for programmable transitor-transitor logic (TTL) output to synchronise nose poking and pellet retrieval with measurements of dopamine release by GRAB-DA photometry . DopaminWe also analysed dopamine release aligned to pellet retrieval  and obsePrevious studies have suggested that neural encoding of non-caloric and caloric solutions is differentially processed in the NAc and dorsal striatum respectively . Next, wWe also examined dopamine release in the dorsal striatum during a progressive ratio schedule . AligninCrat deletion in AgRP neurons is a valid model of abnormal metabolic-sensing since it impairs glucose-sensing using ex vivo electrophysiological recordings and impairs in vivo AgRP GCaMP6 responses to IP glucose injection and repeated palatable food intake. An important role for Crat in metabolic sensing is supported by studies deleting Crat from myocytes, as this diminishes the switch from fatty acid metabolism to glucose metabolism after pyruvate administration  neurons Low/JAgrp (stock no. 012899) and bred with NPY GFP mice (B6.FVB-Tg(Npy-hrGFP)1Lowl/J; stock number 006417; The Jackson Laboratory, Maine, USA). AgRP-ires-cre::NPY GFP mice were then crossed with fl/flCrat mice donated by Randall Mynatt  in order to delete Crat from AgRP neurons . wt/wt::Cratfl/flAgrp littermate mice were used as control animals (designated as WT). For in vivo photometry cre/wt::Cratwt/wtAgrp mice; designated as WT to allow for cre-dependent expression of GCaMP6s specifically in AgRP neurons (KO same as above). No statistical methods were used to determine samples sizes. Experimental mice for operant behaviour and photometry were individual housed.All experiments were conducted in compliance with the Monash University Animal Ethics Committee guidelines. Male and female mice were kept under standard laboratory conditions with free access to food  and water at 23°C in a 12 hr light/ dark cycle and were group-housed to prevent isolation stress unless otherwise stated. No sex differences were observed and data from both male and female mice were grouped together, as indicated in figure legends. All mice were aged 8 weeks or older for experiments unless otherwise stated. Crat KO and 7 WT mice (8–12 weeks) expressing GFP in NPY neurons, and stored at room temperature before transferral to the recording chamber. Slices were continuously superfused at 4–5 ml/min with oxygenated  artificial cerebrospinal fluid (aCSF) of the following composition (in mM): NaCl 127, KCl 1.9, KH2PO4 1.2, CaCl2 2.4, MgCl2 1.3, NaHCO3 26, D-Glucose 2, Mannitol 8 . Hypothalamic neurons were visualised under IR illumination using a 63 x or 40 x water immersion objective on an upright microscope  and an Axiocam MRm camera (Zeiss). AgRP neurons were identified using a GFP filter set. Patch pipettes (8–11 MΩ) were pulled from borosilicate glass capillaries (Harvard Apparatus) and filled with intracellular solution containing (in mM): K-gluconate 140, KCl 10, EGTA 1, HEPES 10, Na-ATP 2, Na-GTP 0.3 . Whole-cell current clamp recordings were made using the MultiClamp 700B amplifier, digitised with the Digidata 1,550B interface, and acquired in pClamp 10.6 at 5 kHz sampling rate (Axon Instruments). To test the influence of an elevated extracellular glucose concentration on neural activity, aCSF was prepared as described above with the following changes: D-Glucose 5 mM, Mannitol 5 mM, and bath-applied for 10–15 min. Data were analysed in Clampfit 10.6 (Axon Instruments) and plotted in Graphpad Prism 8.3. Figures were further prepared in Adobe Illustrator CC 2020.Animals were fasted overnight and 250-µm-thick coronal hypothalamic brain slices containing the ARC were prepared from seven male AgRP Mice for fiber photometry experiments were anaesthetised (2–3% isoflurane) and injected with Metacam (5 mg/kg) prior to placing into stereotaxic frame (Stoelting/Kopf) on heatpad (37°C) and viral injections were performed as previously described . Cre-dep2+], allowing for an assessment of motion artefact. For data analysis, we used a modified python code provided by TDT (GitHub(swh:1:rev:089ab86fb0586563bbd9cdaf0c6bc73b96ce905f). Briefly, raw traces were down sampled and df/f (f465 nm-f405 nm/f405 nm) was calculated to detrend signal bleaching and remove any motion artefact. Individual z-scores around each precisely timed transistor-transistor logic (TTL)-triggered event were extracted to allow a standardised comparison between events. Z-score normalisation indicates the number of standard deviations a particular data point is away from a defined baseline mean and was calculated according to the following equation All fiber photometric recordings were performed with a rig using optical components from Doric lenses controlled by Tucker Davis Technologies fiber photometry processor RZ5P. TDT Synapse software was used for data acquisition. Prior to experiments, baseline GCaMP6s or dopamine signal was measured and LED power was adjusted for each mouse to achieve approximately 200 mV for 465 nm (530 Hz) and 100 mV for 405 nm (210 Hz). This approach is designed to minimise the impact of variable GCaMP6s expression, tissue irradiance, surgery quality and distance of the fibre optic from GCaMP6s fluorescence. 405 nm was used as an isosbestic control, which is wavelength at which GCaMP6 excitation is independent from intracellular , allowing for an assessment of motion artefact. This approach is designed to minimise the impact of variable GCaMP6s expression, tissue irradiance, surgery quality and distance of the fibre optic from GCaMP6s”.”Prior to experiments, baseline GCaMP6s or dopamine signal was measured and LED power was adjusted for each mouse to achieve approximately 200 mV for 465 nm (530 Hz) and 100 mV for 405 nm (210 Hz). 405 nm was used as an isosbestic control, which is wavelength at which GCaMP6 excitation is independent from intracellular [caWe have also added the following text to the discussion.“One potential limitation from our studies is that reduced dopamine release in KO mice may reflect less active AgRP neurons at baseline or during fasting. Although our ex vivo electrophysiology studies show no differences at baseline, they cannot rule out in vivo differences that could not be addressed with ex vivo slice recording or population calcium changes using GCaMP6”.– In figure 1 – food intake/re-feeding data to accompany the photometry experiments showing decreased AgRP neuron responses to repeat rewards should be presented to show the correlation between the AgRP neuron response to food and subsequent food intake. Prior studies by the authors have showed decreased re-feeding in KO mice over 24 hours but have not reported food intake immediately following food presentation. If immediate food intake does not correlate with AgRP neuron inhibition on food presentation/re-presentation it would be the first example where these findings are dissociated and would warrant explanation and follow-up.We designed these experiments so that mice were given single PB pellets, weighing approximately 70 mg, and all was consumed during exposure – therefore all mice ate the approximate amount. We have now described this in the methods.“Peanut butter chips were measured to ~70mg per pellet and one pellet was given per trial. Mice consumed all of this peanut butter chip during each trial such that no differences in consumption were observed.”We have also added the additional data.During each trial the time to peanut butter consumption was not different between genotypes – For the experiments in figure 4 (and other GRAB-DA experiments), how are mice evaluated for inclusion or exclusion from photometry experiments. Photometry signals between animals can vary much more than within animals, and comparing groups of 4 WT vs KO mice as is done in D and E could yield skewed results based on low virus expression or implant placement .The increases in dopamine release before contact with PB in the NAc or dorsal striatum  and before pellet retrieval  is similar between genotypes, suggesting equivalent capacity to increase dopamine release to stimuli not affected by consumption. Thus, genotype differences in response to palatable food or sucrose pellets could not be due to differences in GRAB-DA expression in the NAc. Moreover, a postmortem analysis was conducted to identify the localization of GFP expression .We have added the following text.“GRAB-DA responses in WT and KO mice were similar on approach to PB and prior to pellet retrieval in both the NAc and dorsal striatum showing that genotype differences in response to palatable food or sucrose pellets could not be due to differences in GRAB-DA expression in the NAc. Moreover, a post mortem analysis was conducted to identify the localization of GFP expression ”.– Related to this, to more accurately represent the biological data collected, I think the scatter plots and statistics in figure 4 F,G,J should use the number of mice as N and average nose poke z-scores within animal. If I'm incorrect about this, would appreciate an explanation.– In figure 6, I think – as above – that z-scores should be presented by animal in the scatter plots in F,I,L,M. I could understand using z-scores from individual nose pokes if trying to show a difference in DA response across the session (or something like that), but since this is not the point of the figure I think treating nose pokes within animal as technical replicates and each animal as a biological replicate with a single data point on the scatter plot is appropriate.We also recognised this as a weakness and have now repeated these experiments using multiple additional animals. All operant GRAB-DA data in the accumbens and dorsal striatum is now presented as the averaged nose poke or pellet responses recorded for each mouse. Data points in Figure 4 and Figure 6 now reflect analysis by mouse.We have also updated this in the methods section:“For DA photometry during PR session, data are presented as the averaged dopamine response for each animal. On average mice collected ~3.5 pellets during the PR in ad libitum fed conditions and ~6 pellets when fasted .”Recommendations for improving the writing and presentation.– the authors describe how AgRP photometry implants are determined to be functional with ghrelin injection. What were the cut-offs for inclusion? It would also be helpful to know how GRAB-DA implants are evaluated for inclusion either prior to experiments or post-mortem.For AgRP photometry studies, only mice with a maximal z-score response to IP ghrelin greater than 4 were included for analysis, ensuring differences in AgRP neural activity to food cues were not related to differences in GCaMP expression or illumination rates.We have added the following text to the manuscript.“For AgRP GCaMP6 photometry studies, an increase in activity to ghrelin response was used as an index of correct viral expression and fibre optic placement. Only mice with a maximal peak z-score of >4 were included for analysis in experimental group, using this criterion 5/20 mice, across both WT and KO mice, were excluded for experimentation ”.In addition, increases in dopamine release before contact with PB in the NAc or dorsal striatum  and before pellet retrieval  is similar between genotypes, suggesting equivalent capacity to increase dopamine release under stimuli not affected by AgRP input. Thus, genotype difference in response to palatable food or sucrose pellets could not be due to differences in GRAB-DA expression in the NAc. Moreover, a postmortem analysis was conducted to identify the localization of GFP expression .We have added the following text.“GRAB-DA responses in WT and KO mice were similar on approach to PB and prior to pellet retrieval in both the NAc and dorsal striatum showing that genotype differences in response to palatable food or sucrose pellets could not be due to differences in GRAB-DA expression in the NAc. Moreover, a post mortem analysis was conducted to identify the localization of GFP expression ”.– why is sex mentioned in some but not all figure legends. Where not mentioned are they all male or all female?Not all studies involved females – females were used when mentioned in figure legends.– it would be helpful to mention in figure legends or schematics where PB chips are used whether mice in a given experiment are naïve or habituated to the chips.Only in Figure 1 were mice naïve to peanut butter. Naïve mice in experiment 1 took between 1 and 5 min before approaching peanut butter chip. For our experimental design in Figure 2 and 5 we needed guaranteed approach and consumption within a reasonable timeframe, we therefore provided 1 peanut butter pellet daily for 5 days to accustom mice to peanut butterWe have included the following text in the methods.“To measure AgRP responsiveness to palatable food, mice were presented with Reese’s peanut butter chips. Mice were habituated to peanut butter chips for 5 days (1x 70mg pellet/day) unless otherwise stated as naïve ”.Correction to text and figures:Thank you for pointing these out.– figure supplement 1 – I think A/ B and C/D are reversed on the legend relative to the figure.changed– figure 4 – does panel J contain any data not in F,G? If not I think it can be omitted.Removed and added a graph  showing the pellets collected by each mouse during PR session (as this can’t be seen in the averaged data for each mouse).Apologies if I'm missing something.– figure 5 – D,E,H,I – Y axes seem pretty expanded. Responses to all stimuli would be easier to appreciate if they could be scaled down.done– line 166 – Beutler et al., 2017 also show that the response to presentation of food predicts calories consumed using complementary experiments and should be cited alongside Su et al., 2017 when discussing this point.Reference included.Reviewer #3 (Recommendations for the authors):Almost all data are presented as Z scores. While this is acceptable it does not allow to get an idea of the magnitude of the activity change. Is there some other metric that could be used at least in one experiment to allow this to be compared to other responses seen in the literature?A normalisation approach is commonly used in the field. This allows comparison to a defined baseline where a z-score of 1 represents 1 standard deviation away for the baseline and z-score 2 represents 2 standard deviations away from the baseline etc.We have now also included supplement videos of real-time changes in GCaMP6s or GRAB-DA fluoscence (Videos 1-6).Despite missing the mention of  in the legend of SubFigure 2, the data on the behavioural experiments (L/D box and EPM) need to be extended showing all parameters eg #entry into the different zones, total distance travel in the zone and over all, etc to allow to give a conclusive answer whether the animals show anxiety behaviour or not.We have now added this new data in Figure 1—figure supplement 2I-P. There is no difference in open arm time or entries in the elevated plus maze and no differences in the time spent in the light zone of light zone entries in the light dark box. There were no differences in the light zone velocity and distance moved however, KO mice moved less with a reduced velocity in in the ad libitum fed state.The discussion is rather long and a bit repetitive, it could be more concise and only fucus on the main points. It could however, expand a bit on how the authors think AgRP neurons mediate this response to dopamine changes eg is it dependent on AgRP, NPY or GABA signalling from these neurons etc? Are AgRP neurons the only ones that mediate energy sensing responses eg what is the role of POMC neurons in that process?We have now modified the discussion to shorten.In the PET analysis were any other brain areas also affected and analysed by the treatment?No other regions were examined. Regions had to be manually annotated, which was very time consuming. The striatum is the major region for accumulation of fDOPA and our hypothesis was specific to the striatum .


R)- and (S)-pantolactone have been recorded in three solvents. ROA has beenemployed on water and DMSO solutions, VCD on DMSO and CCl4 solutions. In the last solvent, monomer–dimer equilibriumis present. Due to the low conformational flexibility of the isolatedmolecule and to the possibility of aggregation, this compound hasbeen used here to test different protocols for computation of thespectroscopic responses taking into account solvent effects. Moleculardynamics (MD) simulations have been carried out together with statisticalclustering methods based on collective variables to extract the structuresneeded to calculate the spectra. Quantum mechanical DFT calculationsbased on PCM are compared with approaches based on different representationsof the solvent shell (MM or QM level). Appropriate treatment of thesolvent permits obtaining of good band-shapes, with the added advantagethat the MD analysis allows one to take into account flexibility ofdimeric structures justifying the broadness of observed bands andthe absence of intense VCD couplets in the carbonyl and OH stretchingregions.Ramanand Raman optical activity (ROA), IR, and vibrational circulardichroism (VCD) spectra of ( The use of molecular dynamics (MD)simulations within a box of solvent molecules seems mandatory in watersolutions, usually studied with Raman optical activity (ROA) spectroscopy.8 Recently, the use of molecular simulations has been exploited tocalculate VCD response directly from the trajectories through thecross-correlation function of the electric and magnetic dipole momentsas proposed in ref , permit gaining of information not only concerningconfiguration assignment but also with respect to conformations andintermolecular interactions: solute–solvent interplay influencesthe solute conformational landscape; solute–solute interactionsmay originate aggregation effects. On these aspects, recent literaturehas proposed many protocols to deal with solute–solvent interactionsusing geometrical initial conditions for optimization based on chemicalintuition or by modeling solvent interactions with the aid of moleculardynamics (MD) classical or ab initio simulations. Good results wereobtained with the “cluster in a liquid” approachd in ref . IncreasR)- and (S)-pantolactone explicitlytaking into account solvent molecules with a detailed analysis ofclassical MD results. This molecule possesses few and to some extentrestricted conformational degrees of freedom, so one cannot expectgreat differences due to different conformer populations such thatthe observed spectral variations from solvent to solvent can be attributedeither to subtle solute–solvent interactions or to aggregationphenomena. For this reason, this molecule may be considered a goodbenchmark to test the usefulness of classical MD simulation to obtaina number of representative snapshots and subsequent QM calculationof the chiroptical responses with the usual magnetic field responsetheory developed for VCD17 and for ROA.19In the following, we critically discuss new VOAdata regarding willshow to what extent the MD–QM treatment is appropriate. Thesame compound can be dissolved in CClR)- and (S)-pantolactoneenantiomers were purchased from ACROS Organics and Tokyo Chemical Industry. Thesecompounds have been used without further purification. IR and VCDspectra have been recorded on 49 mM CCl4 and 410 mM DMSO-d6 solutions, usinga JASCO FVS-6000 VCD spectrometer. A fixed path length 200 μmcell with BaF2 windows and 2 mm cell with CaF2 windows were used for 2000–850 cm–1 and4000–2650 cm–1 spectral regions. The spectralresolution values for 2000–850 cm–1 and 4000–2650cm–1 spectral regions are 4 and 8 cm–1 respectively. The spectra for 2000–850 cm–1 and 4000–2650 cm–1 spectral regions havebeen measured using MCT detector and InSb detector with a collectiontime of 5 and 2 h, respectively. The presented spectra are solventsubtracted.The . The linearly polarized excitation lightis converted to the circularly polarized light using a quartz λ/4wave plate. The left and right circularly polarized light can be switchedby inserting two λ/2 wave plates. The backscattered light fromthe liquid sample in a rectangular quartz cell was collected by alens and passed an edge filter. Finally, the scattered light was focusedon a bundle fiber, introduced into a high-throughput spectrometer,and then detected by a Peltier cooled CCD. Raman and ROA spectra havebeen recorded on 873 mM water and 410 mM DMSO-d6 solutions, using our ICP backscattering ROA spectrometer.The spectral resolution for the 2000–200 cm–1 spectral region is 4 cm–1. The collection timesfor water solution and DMSO-d6 solutionwere 4 and 16 h, respectively. The presented spectra are solvent subtracted.The ROA experiments were carried out using a newlydeveloped apparatusbased on incident circularly polarized (ICP) backscattering ROA.21 Subsequentanalysis has been conducted also using the CREST program27 which is based on a semiempirical tight-bindingquantum chemistry method (GFN2). The use of metadynamics coupled withgenetic z-matrix crossing approach allows for a thorough conformationalsearch. For the conformational sampling of the dimer, the CREST programwas used in the NCI modality.27A molecular mechanics conformationalsearch has been undertaken for the monomer and for the dimer, confirmingthe results by Beratan et al.28 Bonds with H atoms were constrained by the LINCS algorithm.29 The 10 Å cutoff value was used for nonbondedinteractions, and long-range electrostatic interactions were handledwith the PME scheme.30 The stochastic velocityrescaling thermostat31 with 0.1 ps timeconstant and the Parrinello–Rahman pressure coupling protocol32 with 2 ps time constant were used. The generalAmber force field (GAFF)33 was used forall simulations. (R)-Pantolactone atomic chargeshave been calculated at the HF-6.31G* level through the RESP34 protocol implemented in Amber-Tools1635 package. The parameters reported in the Foxand Kollman work36 have been used for CCl4 and DMSO solvents. TIP3P model was used for water solvent.Three simulations have been conducted, one for each solvent, at 300K and 1 atm. In each simulation two molecules of (R)-pantolactone have been considered in cubic solvent boxes with 750CCl4, 870 DMSO, 3660 water molecules, respectively. Preliminarytests have been carried out considering various initial distance valuesbetween the two molecules of pantolactone within the box. In waterand DMSO the two molecules throughout the simulation are far apartfrom each other; that is to say they may be considered in monomericform. In CCl4, instead, the dimeric form seems to prevail.Water and DMSO solutions have been simulated for 60 ns, and CCl4 solution has been simulated for 150 ns.MD simulations werecarried out using the GROMACS-2016 package.37 Criteria for the formation of hydrogen bondsare donor–acceptor distance less than 3 Å and D–H–Aangle less than 30°.Analysis has been conducted onframes taken every 10 ps. H-bonds have been evaluated using VMD software.38 a pluginof VMD software.37 Since during the simulationsin water and DMSO no dimerization occurs, the two (R)-pantolactone molecules have been analyzed individually, as independentsystems. Two collective variables (CVs), defined and implemented inthe PLUMED39 modulus, have been chosen:hydroxyl torsion , five-membered ring puckering for the second pantolactone phase(PθB), and a “pseudo”-six-memberedintermolecular ring puckering phase (φ) evaluated accordingto the definition of Cremer and Pople44 considering the ring defined by atoms numbered as 6–1–8–6′–1′–8′in The frames of the trajectories havebeen clustered using Metagui3,ringsee 1.The phaR)-pantolactone were performedat the DFT B3LYP/6-311++G level of theory with IEF-PCM approximation45 as implemented in the Gaussian 1646 program. Considering the structures obtainedthrough the conformational search, the simple IEF-PCM implicit solventscheme has been first adopted, and the population factors of the variousconformers have been calculated from DFT energy values.All QM optimizations andfrequency calculations of (R)-pantolactone at the DFT B3LYP/6-311++G level of theory,while the solvent layer (6 Å) was considered at the MM levelwith the same parameters used in the MD simulations, adopting electronicembedding and IEF-PCM. For brevity, we call this approach QM/MM. Inaddition, for water and DMSO solutions, on the same representativestructures obtained by MD analysis, a 4 Å shell of solvent moleculeshas been treated at the same DFT, IEF-PCM level as pantolactone; hereafterthis approach is called QM/QM.Forthe three solvents considered in this work, after obtaining structuresby MD simulations and clustering, a two-layer ONIOM calculation hasbeen conducted on the representative of each cluster: optimizationsand frequency calculations were carried out treating  followed by B3LYP/aug-cc-pvdz.6 cm–1 Lorentzian bandwidth has been applied toall vibrational transitions.Raman and ROA spectra have beencalculated using the “twosteps” procedure proposed by Cheeseman and Frisch:–1 is more intense than the nearby bands,while the negative band at 1184 cm–1 observed inH2O is absent in DMSO . In both solvents one expects monomericpantolactone molecules and strong solute–solvent interactionsthrough H-bonds: water presents both acceptor and donor properties,while DMSO acts just as acceptor. In the second solvent also IR andVCD spectra have been collected (We observe from Table S1). One mayobserve that the dominant ring structure is 3E-type envelopewith the carbon atom bearing the two methyl groups, . Considering solute–solvent interactions, the radial distributionfunction g(r) reported in Figure S3 suggests strong interactions of waterwith the carbonyl oxygen and with the hydroxyl group; this has a correspondencewith H-bond distribution, as evaluated from the frames of the MD trajectories,based on the criteria defined in the methods section. In particular,while the ring oxygen is H-bonded to water for 13% of the frames,the carbonyl forms one H-bond with water with 60% probability andtwo H-bonds with 11% probability. For 82% simulation time the hydroxylgroup interacts with water as a donor and for 50% as acceptor.In order toreproduce the observed data, a first analysis has been conducted byadopting the PCM approximation for the solvents and by calculatingthe spectra on the five most populated conformers obtained after conformationalsearch in vacuo  3, top, cFigure S4) how some bands are particularly “robust”with respect to different yet similar structures while other featureschange upon little perturbations.49 The analysisshows that the most intense bands are well accounted for by the adoptedclustering operation. In Figure S5, thecomparison is also made between calculated spectra with shell watermolecules treated explicitly in the normal-mode analysis and calculatedspectra with shell water molecules frozen in the vibrational analysis.In orderto calculate the spectra, the cluster representativesmust be optimized; the solvent effect on pantolactone structure ispreserved, either considering a solvent shell treated in the MM approximation(QM/MM) or considering a reduced shell treated at the same QM levelfor pantolactone and solvent molecules (QM/QM). Some tests have beenconducted to examine the variability of the calculated spectra byconsidering many different snapshots at fixed time intervals withinthe same cluster in order to judge how reliable it is to take justthe representative structure of the cluster. This indicates (see Table S1 for details); (ii) weighted average spectra calculatedon six cluster representatives obtained after MD simulation (weightsgiven by the cluster populations) and ONIOM treatment, precisely withthe solute at QM level and a 6 Å solvent shell (about 50 watermolecules) treated at the MM level (QM/MM); (iii) weighted averagespectra calculated on the same six cluster representatives in whicha reduced 4 Å solvent shell has been considered (containing approximately10–12 water molecules), with QM optimization of both soluteand shell solvent molecules (QM/QM) however excluding solvent moleculesfrom the subsequent vibrational analysis.In –1 band better in intensity than thePCM approximation and also correctly predicting the 1184 cm–1 negative band, which is associated with CH2 twistingcoupled with stretchings of the ring simple CO-bonds, being the ringoxygen an HB-acceptor for nearby water molecules; furthermore theQM/MM and QM/QM calculations suggest a broad, low intensity featurefor the carbonyl.As anticipated above, the PCM calculations are already acceptablein comparison with the results obtained after MD analysis, while theQM/MM calculations are not fully satisfactory, especially as regardto ROA. The QM/QM calculation is definitely better: it predicts allthe ROA experimental features with good relative intensities, representingthe 1229 cmTable S2 forconformers obtained after in vacuo conformational search and PCM optimization).Also accordingto DMSO simulation, the two pantolactone molecules are predicted notto interact with each other but they show strong interaction withthe solvent: H-bond analysis shows that 90% of the time the pantolactoneOH is H-bonded to the solvent. Also in this case the same CV variablescan be adopted to compare the structures and for clustering. The CVdistributions . The results are reported in –1 in the ROA spectra gainsintensity in the QM/QM approach. The  triplet at 880,913, and 946 cm–1 shows better relative intensityof the three bands, and also the three features with  signs at 1264, 1327, and 1364 cm–1 are betterrepresented. From Figure S1, one may appreciatehow the differences between the ROA spectra recorded in the two solvents,observed in the range 1150–1250 cm–1, arewell reproduced by the QM/QM calculations, especially the band observedat 1184 cm–1 in water.Also, the ROA spectrum is well accounted for see 6. As poiR)- and (S)-pantolactone have been recorded also in carbon tetrachloride, notonly in the mid-IR region but also in the CH and OH stretching regions(–1 (both negative for (R)-pantolactone)quite similar to the ones observed in the DMSO solution; only a fewdetails of the weaker features in the 1230–1300 cm–1 range and at about 1450 cm–1 present some differences.It is important to recall that the first evidence of dimer formationhad been provided by considering the CO and OH stretching absorptionband;20 for this reason, we decided toevaluate IR and VCD spectra not only considering the PCM approximationsubsequent to a standard MM conformational search but also takinginto account MD simulation results. Due to the different solvent properties(no H-bond interactions with the solvent), the QM/MM approach is sufficientin this case.VCD spectra of . The two molecules then separate from each other,and then they dimerize again such that the dimeric form is presentfor 85% of the simulation time. The dimer, although stabilized byintermolecular hydrogen bonds, is quite flexible.Pθ variables (onefor each pantolactone ring) and the phase φ of the six-memberedring puckering44 relative to the “pseudo”ring bridging the two pantolactone molecules. This last CV allowsone to describe the dimer assembly held together by the H bonds. Considering Figure S6). In 43 on the three distributions, 16 clusters have been obtained .Literature data22 show that important contributions from dimers shouldbe considered, being responsible inter alia for the observed opticalrotation value. In R)-γ-butyrolactones.50 However, theweak VCD features at about 1180 and 1756 cm–1 . In the mid-IRregion, as shown in Considering then results from the cluster representativesobtainedwith MD simulations, also for the monomeric regime ,we have calculated the spectra after optimization of the solute witha CCl4. In Figure S7, analogousto what done in –1,which is predicted to be quite sharp in the PCM approximation, isbroadened according to QM/MM representation, in agreement with experimentaldata.In order to confirm whether theadopted QM/MM protocol is appropriatealso for a (slightly) different case, we considered pantolactone witha deuterated hydroxyl group and recorded the mid-IR VCD spectrum inCCl–1, whichcan be assigned to free OH stretching, while no bands are observed(within the sensitivity limits of our experiment) in correspondenceof the broad absorption band at 3450 cm–1, despitethe fact that dimeric structures generate huge calculated VCD doublets. Due to the sharp, intensecalculated OH stretching absorption and VCD doublet, the stable dimerspredicted by PCM cannot account for the observed broad IR features.The same type of calculation hasbeen used for the high wavenumberrange, comprising the OH and CH stretching regions. The spectra inthe OH stretching region should in principle discriminate betweenmonomer and dimer. This is true for absorption. For VCD instead onlya monosignate band is observed at 3573 cmFigure S8). In the OH stretching region, the band due to the monomeric formis better represented in intensity and shape by the QM/MM procedure.As expected, the calculated features of the CH stretching regionare not very sensitive to dimerization but seem quite sensitive tothe presence of the explicit solvent shell since in this case theband shape improvement is evident see S8. In th–1 IR and VCD feature, thepresence of dimers appears evident from the broad IR absorption at∼3400 cm–1, as already well-known; however,if one wishes to construct a satisfactory model for the hydroxyl stretchingregions, the number of optimized conformers is deemed to be fairlylarge. As a general result, the calculations presented here clearlyshow that in the case of CCl4 the inclusion of the solventshell, treated simply by MM, can really improve the band-shape andsuggest how calculated OH stretching intense signals are “nonrobust”with respect to solvent perturbation justifying the experimentallyweak or absent VCD signal.In conclusion, even though the contribution of monomers isprovenby the ∼3573 cm53 It has already been observed that some bands canbe particularly sensitive to little structural changes, even promotingsign reversal and showing great intensity and frequency variations.We have considered here the most populated dimeric conformer, obtainedafter simple PCM optimization, and have displaced the structure alongwith the lowest energy normal modes, which are distortions of theintermolecular H-bonded bridge. By reporting in A further test has been conductedfor this instance, keeping inmind that the effect of the explicit solvent is to perturb the structureoptimized in a solvent continuum model. A way to monitor the influenceonto the spectra due to perturbations on the minimum geometry is todistort in little steps the dimeric system along with the lowest energynormal modes, i.e., “intermolecular” vibrations. A similarmethod indicating VCD sensitivity to large-amplitude/low-frequencymodes was adopted in the case of intramolecular degrees of freedomfor floppy molecules.3 or, finally, for representative structures chosenwith a cluster analysis usually referred to rmsd calculation. In thepresent cases we adopted statistical cluster analysis based on significantcollective variables adapted to the considered system, an idea borrowedfrom metadynamics protocols.55 Here, we have reliedon ring puckering coordinates also in the case of intermolecular ringcomprising H-bonds. After the snapshot selection, the DFT optimizationmethod has to be chosen: how much extended the solvent shell, whichapproximation to adopt for the solute and the shell, and so on. Inthis work, for solvents with H-bond donor or acceptor atoms exhibitinghigh H-bond propensity like water and DMSO we obtained good resultsconsidering a limited shell treated at the same QM level as the solute. In the case of CCl4 the shell canbe treated at the MM level adopting a ONIOM procedure ; the presence of the solvent and the variety of structurestaken from MD simulations help to obtain good band-shapes. In thecase of dimers the procedure permits taking into account perturbationsof the solvent on flexible dimeric structures and thus avoiding (orat least limiting) of artifacts due to the fixed structures proposedby PCM of the solute dimer alone. Comparison with spectra calculatedon structures displaced along low-frequency/large-amplitude normalmodes is helpful.In this work, pantolactone has been characterizedby VCD and ROAspectra in protic and nonprotic solvents; the set of new data hasled us to use this molecule as benchmark to test various protocolsfor computation of spectroscopic responses in different environmentsand allowing also for aggregation. In particular, after careful conformationalsearch, standard PCM calculations have been conducted and the resultscompared with MD analysis followed by QM/MM or QM/QM calculations(within IEF-PCM frame), the last term meaning that pantolactone andsolvent molecules within the solvent shell defined by MD were treatedat the same QM level. Such methods had been already partially testedin the literature, particularly in the case of water solutions, buttreatment of organic solvents is less common. An important point isthe criterion for how to choose snapshots from simulations to calculatethe chiroptical response. The choice is to go for either a large numberof snapshots at fixed time intervals  or for representative structures at conformational minimaidentified by previous analysis of the most significant dihedral angles58 Difficulties are encountered in the VCD OH stretching region, wherehuge features, highly dependent on minimal structure variations, arecalculated: further studies are needed to improve the statistics suggestinghow this usually disregarded spectroscopic region is quite challengingfor theoretical calculations. Also in this respect we feel that anharmonicitytreatment should be undertaken in future work in order to check theinfluence on IR and VCD intensity.The proposed spectra calculations encompassIR and VCD data inregions more extended than the usual mid-IR, which is generally notextremely sensitive to H-bond interactions, unless H-bonds heavilyinfluence the conformational landscape of the solute, which is notthe case for pantolactone. The carbonyl region is more informativein the IR band-shape and in the presence or absence of VCD signals.The less common OH and CH stretching regions are also examined: goodresults are obtained for band-shape of the OH absorption bands andfor CH stretching VCD and absorption features, despite the fact thatanharmonicity has been disregarded in our calculations.


JMJD6 gene related regulated network in three independent clinical patient cohorts.Prostate cancer is a very common malignancy worldwide. Treatment resistant prostate cancer poses a big challenge to clinicians and is the second most common cause of premature death in men with cancer. Gene expression analysis has been performed on clinical tumours but to date none of the gene expression-based biomarkers for prostate cancer have been successfully integrated to into clinical practice to improve patient management and treatment choice. We applied a novel laboratory prostate cancer model to mimic clinical hormone responsive and resistant prostate cancer and tested whether a network of genes similarly regulated by transcription factors (gene products that control the expression of target genes) are associated with patient outcome. We identified regulons (networks of genes similarly regulated) from our preclinical prostate cancer models and further evaluated the top ranked n = 18). We searched for genes  predicted to be regulated by the highest number of transcriptional factors. Using differentially expressed gene analysis (on a per sample basis) coupled with gene graph enrichment analysis, we identified candidate genes and associated GRNs in PCa within the UTA cohort, with the most enriched regulon being JMJD6, which was further validated in two additional cohorts, namely EMC and ICGC cohorts. Cox regression analysis was performed to evaluate the association of the JMJD6 regulon activity with disease-free survival time in the three clinical cohorts as well as compared to three published prognostic gene signatures . Results: 1308 regulons were correlated to transcriptomic data from the three clinical prostatectomy cohorts. The JMJD6 regulon was identified as the top enriched regulon in the UTA cohort and again validated in the EMC cohort as the top-ranking regulon. In both UTA and EMC cohorts, the JMJD6 regulon was significantly associated with cancer recurrence. Active JMJD6 regulon also correlated with disease recurrence in the ICGC cohort. Furthermore, Kaplan–Meier analysis confirmed shorter time to recurrence in patients with active JMJD6 regulon for all three clinical cohorts , which was not the case for three published prognostic gene signatures . In multivariate analysis, the JMJD6 regulon status significantly predicted disease recurrence in the UTA and EMC, but not ICGC datasets, while none of the three published signatures significantly prognosticate for cancer recurrence. Conclusions: We have characterised gene regulatory networks from preclinical prostate orthografts and applied transcriptomic data from three clinical cohorts to evaluate the prognostic potential of the JMJD6 regulon. Background: Prostate cancer (PCa) is the second most common tumour diagnosed in men. Tumoral heterogeneity in PCa creates a significant challenge to develop robust prognostic markers and novel targets for therapy. An analysis of gene regulatory networks (GRNs) in PCa may provide insight into progressive PCa. Herein, we exploited a graph-based enrichment score to integrate data from GRNs identified in preclinical prostate orthografts and differentially expressed genes in clinical resected PCa. We identified active regulons  associated with PCa recurrence following radical prostatectomy. Methods: The expression of known transcription factors and co-factors was analysed in a panel of prostate orthografts ( Prostate cancer (PCa) is the second most common cancer among men and the fifth leading cause of death worldwide . Tumour ® and Prolaris, together with scoring methods published in the literature, have been developed using microarray, Illumina or Nanostring transcriptome profiles [Inter-patient tumoral heterogeneity and intra-tumour heterogeneity among different tumour foci are well reported, making it unlikely that a single gene will be a representative biomarker of PCa progression . Investiprofiles ,10,11 toprofiles . The limprofiles , immune profiles  and stroprofiles  componenprofiles .Alterations in transcriptional programmes are frequently implicated in PCa progression . Genes tJMJD6  regulon as a prognostic marker in PCa  represent a useful tool to mimic progressive clinical disease. However, the use of preclinical PCa as a tool to identify potential GRNs involved in progressive disease has not been tested. Here, to generate a robust scoring method, we derived GRNs from a collection of preclinical hormone naïve (dependent on androgens for growth) and castration resistant (growth despite androgen deprivation therapy) human PCa orthografts to capture the heterogeneous nature of clinical disease, leveraging the strength of correlations in the expression patterns of genes transcribed by tumour cells only. Filtering the GRNs for statistically significant associations led to the identification of putative regulons, signifying the network of target genes and shared transcription factor  involved. Integrating data from preclinical orthografts and clinical PCa cohorts, we modelled regulon signatures to identify patients at risk of cancer recurrence, and identified the r in PCa .See Supplementary Information for additional details for datasets and methods.n = 3 mice per cell line) [Hormone naïve human prostate cancer cell lines  were implanted into the prostates of androgen proficient (6 weeks old) nude male mice to generate androgen dependent prostate orthografts. Castration resistant (or androgen independent) prostate orthografts were generated from the 22Rv1, LNCaPAI and VCaPR human PCa cell lines by orthotopic implantation into the prostates of castrated nude (6 weeks old) male mice. RNA-seq data were obtained from 18 orthografts derived from the six human PCa cell lines studied (ll line) , referreRNA-seq data from three clinical PCa cohorts were included in this study: The University of Tampere (UTA-EGAD00001000609), the Erasmus Medical Center in Rotterdam (EMC-EGAD00001004215), and the International Cancer Genome Consortium (ICGC-EGAD00001004791). A summary of the clinicopathological characteristics of the cohorts is provided in n = 27), were used in this study, along with the 12 benign samples.Dataset from the UTA cohort  were obtn = 37) and all the benign control samples were used in the present study. The EMC dataset was obtained from 92 radical prostatectomy specimens (51 PCa with 41 adjacent benign prostate tissue) ,22. The n = 85) and all the benign samples (n = 8) were used in the present study.The ICGC dataset consists of 125 PCa specimens (and 8 matched benign control tissue) from 100 radical prostatectomy specimens . Six tumThe PCa gene-regulatory network was generated using the R package ‘RTN’  version The graph structure was analysed using the R package ‘igraph’ v1.2.5, exploiting the functions ‘degree’, ‘betweenness’, ‘constraint’ and ‘closeness’ to retrieve metrics at the ‘nodes’ level, providing complementary information about the importance of individual nodes within the network: (1) The ‘degree’ (or ‘in-degree’) of a node in a GRN is the number of transcriptional regulators involved in the control of the expression of a specific target gene. For different GRNs, the number of regulatory genes implicated for individual target genes varies, depending on complexity of the network; (2) ‘Betweenness’ is defined as the number of shortest paths passing through the node and can be interpreted as a measure of the influence of the node of interest over the global flow of information; (3) Burt’s ‘constraint’ is a measure of the redundancy of the information received by the node and can be interpreted as its ability to converge different signals; (4) ‘Closeness’ quantifies the node’s participation within a network. Finally, the Jaccard Index, a statistical measure defined as the ratio of the intersection and the union of two sets, was applied to highlight network nodes sharing a meaningful proportion of targets. The threshold of 0.1 was chosen to prioritise the nodes to be shown in p-values were adjusted using the function ‘p.adjust’ from the R stat package v4.0.3, by setting the ‘method’ parameter to ‘fdr’. The DEG gene set for each cohort was analysed using the gene regulatory network that was identified in the preclinical orthografts. The derived list of positive and negative gene-gene interactions was then used as input to the function ‘nbea’ from the package ‘EnrichmentBrowser’ [The list of differentially expressed genes  for each sample was determined using the respective benign control samples within each of the clinical UTA, EMC and ICGC cohorts. Browser’  version JMJD6 regulon signature as a prognostic marker was compared to three published signatures [JMJD6 regulon signature as a prognostic marker was compared to three published signatures  levels ≥2 ng/mL above nadir PSA (the lowest PSA level after treatment) and signifies clinical evidence of relapsed cancer. Relapse free survival  was used to evaluate the prognostic utility of regulon signatures of interest in the UTA, EMC and ICGC clinical cohorts. The performance of our candidate gnatures ,29,30. Tications ,29,30:  for all the analysis were obtained by Cox proportional-hazard model regressions, using the ‘coxph’ function from the R package ‘survival’ version 3.1-8. Moreover, for multivariate analysis, Gleason score and the TNM (Tumour/Node/Metastasis) classification were added to the model formula in the form: ‘Endpoint ~ JMJD6regulon_activity + second_variable’. Kaplan–Meier curves were obtained using the ‘ggsurvplot’ function from the R package ‘survminer’ v0.4.8. The analysis was performed in R v4.03. Patients were labelled according to the enrichment status of n = 3, except for VCaP). VCaP derived orthografts were grown in both hormone proficient and castrated mice (n = 3 each). 1308 regulons with a median of 20 genes per regulon (range 2–121) were identified , shared at least one target gene , and interestingly all of these four genes have previously been implicated in PCa: BUD31 encodes for a bona-fide AR-coactivator that enhances AR transactivation in prostate cells [PLOD3 is involved in tissue remodelling and plays a role in multiple tumour types including PCa [SDR42E1 is implicated in early prostate organogenesis as well as carcinogenesis [XAGE1A belongs to the cancer testis antigens family and its expression profile is linked to the aggressiveness of PCa [Genes controlled by multiple transcription factors at the transcriptional level may suggest a functional requirement in controlling the expression of these target genes, thus signifying the likelihood of their biological importance. We searched for genes  predicted to be regulated by the highest number of transcriptional factors . Up to 1ding PCa ; SDR42E1ogenesis  and XAGEs of PCa . Hence, p-values) was then be used to identify the GRNs of interest, highlighting potential active regulons in individual tumours. In the UTA cohort (n = 27 PCa), we found a median of 2406 upregulated (range 1098–6419) and 282 downregulated (range 44–1173) genes per sample. In the EMC cohort as a validation dataset (n = 37 PCa), we observed a median of 2439 upregulated (range 827–7395) and 126 downregulated (range 1–925) genes for individual tumour samples. Through comparison of each clinical tumour with the combined benign controls within the respective clinical cohorts, lists of differentially expressed genes (on a per sample basis) were generated on a per-sample basis initially in the UTA clinical cohort as part of a discovery analysis. The list of PCa associated genes (log2 fold changes and HPN [CLDN8 (an androgen regulated gene that promotes PCa cell proliferation and migration) [ONECUT2 (a known master regulator in PCa that suppresses the androgen axis) [We ranked the differentially expressed genes by the average frequency of alteration (up- or down- regulation) within the respective patient cohorts . Of noteHPN , CLDN8 (gration) , and ONEen axis) . Hence, Data from transcription factor associated GRN identified in the preclinical prostate orthografts and individual gene sets from differentially expressed gene analysis on a per sample basis were integrated in a gene graph enrichment analysis (GGEA) to determine the activity status of the regulons  in the clinical tumours. The concordance of the positive and negative ‘transcription factor-target gene’ relationships was calculated for each sample within the UTA and EMC patient cohorts. GGEA  applies BACH1 promotes invasion and migration of PCa cells by altering metastasis related genes [CITED2  has recently been proposed as a therapeutic target to tackle PCa metastasis [DNMT1 promotes PCa metastasis through the regulation of epithelial-mesenchymal transition and cancer stem cells [To corroborate enriched gene networks shared among independent cohorts, we ranked the regulons by the respective frequency of activation in the UTA and EMC patient datasets . Consisted genes ; CITED2 tastasis ; and DNMem cells . CollectJMJD6 as the top-ranking enriched regulon , altered JMJD6 gene was detected in multiple cohorts, with the highest incidence of genetic abnormalities (up to 8%) detected in metastatic tumours  and EMC cohorts . Kaplan-Meier analysis for biochemical free survival further confirmed reduced biochemical free survival in the presence of active status for the JMJD6 regulon in patients within the UTA, EMC and ICGC cohorts  following radical prostatectomy. We performed univariate CoxPH regression analysis in the UTA dataset in the first instance to identify enriched regulons associated with cancer recurrence . Eleven  tumours . We reas cohorts A. We fur cohorts .JMJD6 regulon as a prognostic marker for progressive/recurrent PCa, three reported independent signatures were selected for comparison: two androgen receptor related signatures  were performed if the respective univariate analysis were significant. In multivariate analysis, the JMJD6 regulon status significantly predicted disease recurrence in UTA and EMC, but not ICGC (To benchmark the ignature  and the ignature ) as wellignature . The threctively A. Multivnot ICGC B. Among JMJD6 regulon in patients at risk of PCa recurrence.Collectively, our analysis highlights the feasibility of integrating data from preclinical human orthograft models of PCa with multiple clinical cohorts to generate information on the regulon landscape in identifying potential prognostic signatures. For the first time, our data identified the active status of the JMJD6 regulon as a candidate prognostic signature for biochemical recurrent PCa. Our data is consistent with a recent report on GRN-based investigation in breast cancer [We hypothesised that the study of genes positively and negatively regulated by one or more transcription factors (collectively referred to as regulons) is a suitable approach to capture the general mechanisms driving tumour progression in PCa . For thet cancer . Our datt cancer , breast t cancer , neuroblt cancer , melanomt cancer  and ovart cancer  cancers.JMJD6 regulon consists of 27 positive and 3 negative putative target genes  is associated with PCa progression [SORL1, a known hypoxia regulated gene [The et genes , includiby JMJD6 B. RAD51,sive PCa , and is sive PCa . Similarted gene , negativJMJD6 regulon. Given the small number of preclinical samples available as a starting point to infer the GRNs in PCa, we were not able to robustly compare between hormone naïve and castration resistant orthografts. Instead, we combined the available orthografts to model tumour heterogeneity of clinical PCa. Importantly, some transcription factor-target genes relationships may not be revealed because of the limited sample number, thus creating potential biases with a subset of regulons appearing transcriptionally more important. Nonetheless, even with this limitation, the JMJD6 regulon was identified as a key regulon enriched in two independent clinical cohorts, namely UTA and EMC, as well as the published independent ICGC clinical cohort. The ICGC cohort consists of relatively young patients , compared to UTA ; such case selection bias may create confounding factors that contribute to the negative multivariate analysis for the JMJD6 regulon in the ICGC cohort.We successfully identified regulons of interest from preclinical prostate orthografts and then investigated the prognostic value of our top candidate JMJD6 knockdown and anti-androgen treatment with enzalutamide produced substantially more anti-proliferative effects than each of the two treatment alone. Collectively, their data implicates JMJD6 to be important in PCa cell viability and proliferation, thus further supporting our GRN-based findings. Although androgen receptor (AR) is essential for both prostate organogenesis and carcinogenesis, to our surprise, AR was not identified as an enriched regulon in our analysis. AR may be functionally important in both benign and malignant prostatic epithelium, with distinct transcriptional profiles arising from functional re-programming. Even in CRPC, AR remains activated through by-pass mechanisms despite suppressed canonical  androgen receptor pathway activities . In addiThe strategy of standardising the analysis, by adopting a panel of benign controls within each dataset , allowed for the reduction of biases arising from different protocols for sample handling, sequencing and data processing. Indeed, by leveraging a panel of control samples within each cohort, it was possible to show commonalities among the independent data sets without resorting to batch correction. JMJD6 regulon. Given its potential role in a number of tumour types, a novel JMJD6 specific inhibitor SKLB325 has recently been developed [JMJD6 as a driver gene for progressive PCa, formal evaluation of JMJD6 targeted therapy will be warranted.JMJD6 belongs to the Jumonji C (JMJC) domain-containing family of proteins. JMJD6 is thought to function mainly as a lysyl 5-hydroxylase, and not as a demethylase , althougeveloped . Should JMJD6 regulon as a potential prognostic marker in PCa. We have characterised gene regulatory networks from preclinical prostate orthografts and applied transcriptomic data from three clinical cohorts to identify the


We found that PAX7 localization to the nucleus correlates with myotube-forming ability in these sorted populations. We also demonstrated that cells in unsorted, CD271+, and CD15– fractions responded differently to cryopreservation and prolonged culture expansion. Lastly, we showed that CD271 expression is essential for terminal differentiation of human PSC-derived myogenic progenitors. Taken together, these cell surface proteins are not only useful markers to identify unique cellular populations in human PSC-derived myogenic progenitors but also functionally important molecules that can provide valuable insight into human myogenesis.Human myogenic progenitors can be derived from pluripotent stem cells (PSCs) for use in modeling natural and pathological myogenesis, as well as treating muscle diseases. Transgene-free methods of deriving myogenic progenitors from different PSC lines often produce mixed populations that are heterogeneous in myogenic differentiation potential, yet detailed and accurate characterization of human PSC-derived myogenic progenitors remains elusive in the field. The isolation and purification of human PSC-derived myogenic progenitors is thus an important methodological consideration when we investigate the properties and behaviors of these cells in culture. We previously reported a transgene-free, serum-free floating sphere culture method for the derivation of myogenic progenitors from human PSCs. In this study, we first performed comprehensive cell surface protein profiling of the sphere culture cells through the screening of 255 antibodies. Next, we used magnetic activated cell sorting and enriched the cells according to the expression of specific surface markers. The ability of muscle differentiation in the resulting cells was characterized by immunofluorescent labeling and quantification of positively stained cells. Our results revealed that myotube-forming cells resided in the differentiated cultures of CD29 For instance, in vitro drug screening using human PSC-derived myogenic progenitors allows us to identify new mechanisms and molecules that have the capacity to prevent muscle wasting and atrophy during normal aging or disease processes. In the last decade, several approaches were proposed from different laboratories for efficient derivation of myogenic progenitors from human PSCs. In particular, a series of our published studies demonstrated the feasibility of producing myogenic progenitors from human PSCs directly without genetic modification using serum-free and feeder-free floating spherical culture (EZ spheres) . Fr. Fr– or + spheres and CD15– spheres displayed similar ratios of myotube-forming cells compared to unsorted spheres   . Morpholclusters .To investigate whether CD271 expression plays critical roles for myogenic differentiation, we silenced CD271 in human PSC-derived myogenic progenitors using RNA interference. EZ spheres derived from human iPSC (IMR-90) and ESC (WA9/H9) lines were dissociated into single suspended cells and transfected with two different sequences of CD271 siRNA (#1 and #2) or scrambled. At 6 hours after transfection, cells were lysed and analyzed for CD271 protein levels. Western blot results showed successful knockdown of CD271 levels by siRNA #1 and #2, whereas scrambled served as a negative control . Parallein vitro modeling or cell-based therapy. Not only that human biopsy-derived and PSC-derived myogenic progenitors do not exhibit fully equivalent properties, but significant phenotypic discrepancies were also observed even within human PSC-derived myogenic progenitors prepared via different methods. Sorted cells may also undergo changes in their surface marker profiles during expansion and differentiation in culture. This may explain the limited success and the lack of consensus on the enrichment of human PSC-derived myogenic progenitors. Even so, recent advances enabling the isolation of human myogenic progenitors based on surface marker expression have facilitated the analyses of their cell identities and myogenic potential.Strict maneuver of the cell differentiation process and isolation of desired cell types are fundamental to the successful use of human PSC derivatives for in vitro myogenic potential. Protein names and representative biological roles of these 6 markers are summarized in We previously reported that myogenic progenitor populations derived from human PSCs using our transgene-free, serum-free protocol do not all homogenously express myogenic factors PAX7, MyoD and Myogenin , 9. In t+ fraction was higher than not only CD56– fraction but also unsorted populations with great significance, implying that CD56 alone may sufficiently work for enrichment of human PSC-derived myogenic progenitors. CD29 on the other hand is insufficient as a sole marker to identify human myogenic progenitors, as CD29– fraction still contained a substantial proportion of myotube-forming cells. This finding is consistent with the previously suggested notion that not all myogenic progenitors express CD29 [+ cell populations implies that CD29 expression may have a role in promoting muscle differentiation. In our study, myogenic potential was not significantly different between CD29+ and unsorted populations following differentiation. Eliminating CD29– cells might not change the cell population makeup much, since most of the unsorted cells were CD29-postive  and CD29 (integrin beta-1) were able to isolate most myogenic progenitors from our EZ sphere cultures. Several groups have reported successful enrichment of human PSC-derived myogenic cells with CD56 , 40 and ess CD29 , 12. None Figure .+ fraction; negligible ratio of myotube-forming cells in the CD271– fraction probably reflects contamination with the CD271+ cells. Although it is not easy to decode why there were various results on driving myogenic commitment following CD271-based enrichment, the differences of derivation protocols and PSC lines between studies may explain diverse responses to each protocol. It is intriguing that since almost all cells within unsorted populations in iPSC-derived EZ spheres stained positive for CD271 with high intensity, theoretically cellular composition was not largely different between the unsorted populations and CD271+ fraction populations, yet CD271+ fraction exhibited a significantly higher ratio of myogenic differentiation compared to the unsorted populations. We speculate that CD271– cells might have inhibitory effects on the process of muscle differentiation in CD271+ cells. This hypothesis may also be supported by our finding that postsorted CD271+ spheres exhibited higher growth rate than unsorted spheres after cryopreservation and long-term culture expansion. These CD271+ sphere cells also retained status as myogenic progenitors with a higher ability of myotube formation following terminal differentiation when compared to the unsorted populations. Meanwhile, silencing CD271 expression resulted in reduced myotube formation and defective myotube morphology, confirming that CD271 is requisite for human muscle differentiation.Also known as p75 neurotrophin receptor or low-affinity nerve growth factor receptor (p75NGFR), CD271 is a very promising marker to isolate human PSC-derived myogenic progenitors and holds tremendous potential to unveil novel specifics about the mechanisms of myogenesis. Previously, mixed results were reported for the enrichment of PSC-derived myogenic progenitors using CD271 as a positive marker: one group reported unsuccessful CD271-based enrichment of myogenic progenitors from PAX7/Myf5 dual reporter ESCs cultured in a serum-containing medium , while a+ primary and C2C12 mouse myoblasts proliferated but did not differentiate, while showing increased levels of phosphorylated inhibitor of nuclear factor kappa B (I-κB) and protein kinase B, both of which promote cell survival [κB) activation and the small heat shock proteins (sHSPs) αB-crystallin and Hsp27 [+ cells were present at all timepoints tested, from early after plating in growth medium until after 6 days in differentiation medium [+ cells and Myf5+ cells from human fetal muscles during the first and second trimesters of gestation, including at time points before any other myogenic surface markers are presented on muscle progenitors [+/ErbB3+ subpopulation emerged in the muscle with expression of myogenic transcription factors at 8 weeks of gestation; this subpopulation began to co-express some cell surface markers such as CD56, CD82, and CD146 at 11 weeks of gestation, then started losing CD271 expression at 16 weeks of gestation [The function of CD271 in rodent myoblasts has been elucidated in several reports. When supplemented with neurotrophins which support the survival and differentiation of neurons, CD271survival . CD271 wsurvival . In L6C5nd Hsp27 . Anothern medium . Changesn medium . CD271/Egenitors . A CD271estation . CD271 mestation . Impairehigh myogenic progenitors expressed significantly higher levels of myogenic factors PAX7, MYF5, MYOD1 and MYOG, and displayed higher myotube-forming ability compared to CD271low cells [high and C271low subpopulations on FACS analysis, where we could see two peaks representing a subset of cells that stained positive for CD271 with high intensity and another subset with lower intensity , a member of the family of proteins which function as protein transporters to the nucleus, confirming the preposition by an earlier study that KPNA2 is important for myoblast proliferation [+, CD56+, CD271+, CD15–) or higher myotube fusion . Note that CD56+ fraction and CD271+ fraction contained more nuclear PAX7+ cells than their counterparts CD56– fraction and CD271– fraction with only moderate significance , but the former group produced more myotubes than the latter group with high significance (p < 0.001). The difference in statistical difference between these two pairs of sorted fractions may indicate an increase in muscle differentiation commitment or ability after depleting CD56– cells and CD271– cells from the cultures. This may explain why CD56+ fraction and CD271+ fraction were the only preparations that formed significantly more myotubes than their unsorted controls (in vitro evaluations in the current study, so we have not yet examined the potential of enriched cells for in vivo muscle regeneration following xenotransplantation. Our future research directions include assessing the engraftment capacity of enriched human PSC-derived myogenic progenitors to determine whether there are prospects for use of these identified markers in transplantation studies. In terms of in vitro characterization, the need to mature progenitors even more for functional and mechanistic analysis remains a challenge to be addressed in the field of muscle biology research.PAX7 as a transcription factor is mainly found in the nuclei of myogenic progenitors, but our detailed analyses revealed that PAX7 expression was also detected within the cytoplasmic compartment. Specific functions and posttranslational events of transcription factors can be inferred through their subcellular localization, but there is a lack of studies on PAX7 regulation in myogenic progenitors in terms of protein distribution and transporting. One study reported that dfd13 dystrophin-deficient mouse myoblasts had a significantly higher percentage of PAX7 which was localized in the cytoplasm compared to C2C12 wild-type mouse myoblasts . The detferation . Anotherferation . As suchcontrols . Successin vitro models that recapitulate human development and cell-specific lineages more closely, thus allowing for enhanced clinical utility. Furthering our knowledge of phenotypically distinct cells that possess myogenic progenitor properties and function could also conceivably aid the selection of promising targets to provide inroads to regenerative approaches for muscular diseases and muscle injuries. We anticipate that more studies will be done to define and distinguish the subpopulations of human PSC-derived myogenic progenitors, thereby facilitating the discovery of novel insights into human muscle development, homeostasis, aging, and disease.Cell surface marker profiling has proven useful for the enrichment of myogenic progenitors derived from human PSCs via transgene-free method, as well as the identification of previously unreported surface proteins that may have an essential role in myotube formation and maturation. Better characterization of the cellular traits of human myogenic progenitors prepared via a directed differentiation method could lead to


Additionally, we detected a significant increase in predicted pathogenic de novo missense mutations affecting missense-intolerant genes  in contrast to predicted benign de novo mutations. One gene we identify, RBM5, is an essential regulator of male germ cell pre-mRNA splicing and has been previously implicated in male infertility in mice. In a follow-up study, 6 rare pathogenic missense mutations affecting this gene are observed in a cohort of 2,506 infertile patients, whilst we find no such mutations in a cohort of 5,784 fertile men . Our results provide evidence for the role of de novo mutations in severe male infertility and point to new candidate genes affecting fertility.De novo mutations are known to play a prominent role in sporadic disorders with reduced fitness. We hypothesize that de novo mutations play an important role in severe male infertility and explain a portion of the genetic causes of this understudied disorder. To test this hypothesis, we utilize trio-based exome sequencing in a cohort of 185 infertile males and their unaffected parents. Following a systematic analysis, 29 of 145 rare (MAF < 0.1%) protein-altering de novo mutations are classified as possibly causative of the male infertility phenotype. We observed a significant enrichment of loss-of-function de novo mutations in loss-of-function-intolerant genes ( Germline de novo mutations can impact individual fitness, but their role in human male infertility is understudied. Trio-based exome sequencing identifies many new candidate genes affecting male fertility, including an essential regulator of male germ cell pre-mRNA splicing. Despite a clear role for genetic causes in male infertility, there is a distinct lack of diagnostically relevant genes and at least 40% of all cases are classified as idiopathic4. Previous studies in other conditions with reproductive lethality, such as neurodevelopmental disorders, have demonstrated an important role for de novo mutations (DNMs) in their etiology5. In line with this, recurrent de novo chromosomal abnormalities play an important role in male infertility. Both azoospermia factor (AZF) deletions on the Y chromosome as well as an additional X chromosome, resulting in Klinefelter syndrome, occur de novo. Collectively, these de novo events explain up to 25% of all cases of nonobstructive azoospermia (NOA)4. Interestingly, in 1999 a DNM in the Y-chromosomal gene USP9Y was reported in a man with azoospermia6. Until now, however, a systematic analysis of the role of DNMs in male infertility had not been attempted, even though a pilot exome sequencing study in 13 infertile men and their parents was recently published7. This is partly explained by a lack of basic research in male reproductive health in general8, but also by the practical challenges of collecting parental samples for this disorder, which is typically diagnosed in adults.Male infertility contributes to approximately half of all cases of infertility and affects 7% of the male population. For the majority of these men the cause remains unexplainedRBM5, which contains a possibly causative DNM in our trio cohort, and possibly causative heterozygous variants in six additional patients for which parental information is not available. This work suggests a potential role for DNM as a cause of severe male infertility and addresses the need for further investigation in larger patient–parent trio cohorts to solidify these results.In this work, we address this lack of knowledge by analysing exome sequencing data of 185 infertile males and their parents and reporting on our findings of 29 DNM in these men which are likely causative for the infertility phenotype, based on variant and gene level evidence. We emphasize an enrichment for loss-of-function (LoF) DNM in LoF-intolerant genes and missense DNM in missense-intolerant genes. We identify a number of promising candidate genes for male infertility, including the mRNA splicing gene n = 74) and azoospermia (n = 111) by performing whole exome sequencing (WES) in all patients and their parents . No such enrichment was identified in a cohort of 1,941 control cases from de novo-db v1.6.112    of Proband_076. Homozygous Greb1l knockout mice appear to be embryonic lethal, however, typical male infertility phenotypic features such as abnormal fetal testis morphology and decreased fetal testis volume are observed15. Interestingly, this patient has a reduced testis volume and severe oligozoospermia , not known to be present in our patient. Of note, all previously reported damaging mutations in GREB1L causing renal agenesis are either maternally inherited or occurred de novo. This led the authors of one of these renal agenesis studies to speculate that disruption to GREB1L could cause infertility in males15. A recent WES study involving a cohort of 285 infertile men also noted several patients presenting with pathogenic mutations in genes with an associated systemic disease where male fertility is not always assessed17.Broadly speaking, across genetic disorders, dominantly acting disease genes are usually intolerant to LoF mutations, as represented by a high pLI score00) Fig. . Similarospermia  Table 1.18. Two genes affected in both patients, QSER1 and CSTF3, are LoF-intolerant with pLI scores of 1 and 0.98, respectively. In particular, CSTF3 is highly expressed within the testis and is known to be involved in pre-mRNA 3′-end cleavage and poylyadenylation19.We also assessed the damaging effects of the two rare de novo CNVs by looking at the pLI score of the genes involved. Proband_066 presented with a large 656 kb de novo deletion on chromosome 11, spanning 6 genes in total. This deletion partially overlapped with a deletion reported in 2014 in a patient with cryptorchidism and NOA20, MutationTaster21, and PolyPhen222 with a minimum of 2 of the 3 showing pathogenicity to define a variant as Pathogenic. Using this approach, 84 of 145 rare protein-altering DNM were predicted to be pathogenic, while the remaining 61 were predicted to be benign. To further analyse the impact of the variants on the genes affected, we looked at the missense Z-score of all 122 genes affected by a missense variant, which indicates the tolerance of genes to missense mutations23. We identified no significant enrichment in missense DNMs in missense-intolerant genes in our infertile cohort when compared to controls   when compared to genes affected by predicted benign  missense DNMs in our cohort  or those affected by synonymous DNMs  on the paternal allele, we did identify a maternally inherited variant predicted to be pathogenic , CWC25, and EVC). All of these variants, however, were also observed multiple times in an exome dataset from a cohort of 5784 fertile men suggesting that these maternally inherited variants are not causative of male infertility , in collaboration with members of the International Male Infertility Genomics Consortium and the Geisinger-Regeneron DiscovEHR collaboration39. For comparison, we included an exome dataset from a cohort of 11,587 fertile men and women from Radboudumc.In addition to all systematic analyses described above, we evaluated the function of all DNM genes to give each a final pathogenicity classification . In this gene, six infertile men were found to carry a rare pathogenic missense mutation, in addition to the proband with a de novo missense mutation .In the additional infertile cohorts, we identified 17 LoF mutations in our DNM LoF-intolerant genes (pLI ≥ 0.9), although we did not detect a statistical enrichment in the LoF mutations in these genes compared to fertile men  of all our DNMs using a combination of short-read WES and targeted long-read sequencing . This suggests that DNMs with a deleterious effect on the future germline can escape negative selection in the paternal germline. This may be possible because the DNM occurred after the developmental window in which the gene is active, or the DNM may have affected a gene in the gamete’s genome that is critical for somatic cells supporting the (future) germline. Transmission of pathogenic DNMs may also be facilitated by the fact that from spermatogonia onwards, male germ cells form cysts and share mRNAs and proteins44. As such, the interconnectedness of male germ cells, which is essential for their survival45, could mask detrimental effects of DNMs occurring during spermatogenesis.Given the predicted impact of these DNMs on spermatogenesis, we were interested in investigating the parental origin of DNMs in our trio cohort. We were able to phase 29% . This work contributed to the widespread implementation of patient–parent WES studies in research and diagnostics for neurodevelopmental disorders47, accelerating disease gene identification and increasing the diagnostic yield for these disorders. The data presented here suggest that a similar benefit could be achieved from trio-based exome sequencing in male infertility. In order to achieve this there is an urgent need to expand on this work as larger studies are essential to identify recurrently DNM genes and further demonstrate the exact contribution of DNMs to male infertility. Modeling studies recently done for developmental disorders showed that more than 350k trios may be required to have approximately 80% power to detect all haploinsufficient genes causing this disorder48. Evidently, these numbers can only be reached by implementing trio-based exome sequencing as a routine diagnostic test and by sharing these diagnostic data with the international research community. This research community will also have the enormous task of functionally validating the impact of these DNMs on spermatogenesis. Altogether, this will not only help to increase the diagnostic yield for men with infertility but will also enhance our fundamental biological understanding of human reproduction and natural selection. In addition, it will indicate whether male infertility follows a dominant inheritance pattern, and this has impact for disease transmission. Couples that seek treatment for male infertility should be counseled on the risk of transmitting this condition to their offspring, something that is now limited to couples receiving fertility treatment due to Y-chromosome deletions. Male infertility is also increasingly seen as the most visible symptom of a more complex disease with associated comorbidities49. Studying the long-term health of men with DNMs in specific genes should help in identifying genotype–phenotype correlations that may impact more than the fertility of these men.In 2010, we published a pilot study pointing to a de novo paradigm for mental retardationN = 111) or severe to extreme oligozoospermia (with or without asthenozoospermia N = 74) at the Radboudumc outpatient clinic between July 2007 and October 2017 (N = 170) and at the Newcastle upon Tyne Hospitals NHS Foundation Trust  between January 2018 to January 2020 (n = 15). The reference values and semen nomenclature were used according to the WHO guidelines50  azoospermia  testicular biopsies. As staining controls testicular biopsies obtained from fertile men after a previous vasectomy was used. FFPE sections were prepared for staining following standard protocols. To detect RBM5, antibody HPA018011 from Atlas Antibodies was used in a 1:500 dilution. For detection, a donkey anti-rabbit Alexa488 antibody was used , which was applied in combination with lectin coupled to Alexa568  to detect the acrosome (both Thermo Scientific). Slides were counterstained with DAPI. Images were obtained with a Zeiss Axio Imager ZI fluorescence microscope equipped with the Zen software package.We used an anonymized exome dataset derived from 5784 Dutch men and 5803 Dutch women who had conceived at least one child as a control cohort for the frequency of rare variants in fertile men and fertile women. These men and women received routine exome sequencing at the Radboud diagnostics center as the healthy parent of a child with a severe illness. Although these men fathered a child with intellectual disability, their fertility is expected to be similar to an unselected sample of the male population.51, Picard52, and GATK v4.1.4.153. The sex, ancestry and relatedness of each samples was calculated using peddy54, samples found to have the incorrect sex or were unrelated to the correct samples were excluded from this study. Following best practice recommendations, single nucleotide variations and small indels were identified and quality-filtered using GATK’s HaplotypeCaller obtaining comparable results independently of the kit or the origin of the DNA  below 4 or allele frequency (AF) < 0.1% in all samples, whichever is more stringent, were classified as low-confidence DNMs. Variants with recalculated GQs ≥ 20 and the same AC/AF criterion were classified as high confidence DNMs. Afterwards, tagged variants with coverage <10, variant read percentage <15% and GATK quality scores <400 were removed to ensure only the most reliable variants were considered. Sanger sequencing was then used to validate DNMs calls. Ensembl’s Variant Effect Predictor (VEP)56 was used to fully annotate all de novo variants.WES samples were prepared and enriched following the manufacturer’s protocols of either Illumina’s Nextera DNA Exome Capture kit or Twist Bioscience’s Twist Human Core Exome Kit. All sequencing was performed on the NovaSeq 6000 Sequencing System (Illumina) achieving comparable results covering more than 99% of all exonic regions using either kit  and the Association for Molecular Pathology (AMP) 2015 guidelines57. All protein-altering variants predicted to be pathogenic by at least 2 out of 3 prediction models, absent from the fertile male cohort, present in <5 males in the gnomAD database were considered for further functional analysis (n = 84). Maternally inherited mutations present in genes identified as having a protein-altering DNM were identified in all patients and submitted to the exact same method of filtration and interpretation as described above.The primary stages in filtering of variants included removing all variants with an allele frequency of >0.1% in the gnomAD database to only include rare variants in our analysis. All variants then with <10 reads in the exome data and/or less than 15% of these reads containing the mutation were then removed. At this stage, any remaining variants lying outside the exonic regions were then removed. This provided the initial list of 192 rare de novo variants. All synonymous and non-protein-altering spice site variants were then removed, leaving a total of 145-protein-altering rare DNMs. Pathogenicity prediction was then based on SIFThttps://www.gtexportal.org/), an expression of medium (≥10 < 100 TPM) or high (>100 TPM) gave a score of 1 with low (>2 < 10 TPM) and no expression (<2 TPM) giving a score of 0. RNA enrichment was based on elevated expression  in the Human Protein Atlas58 or being among the genes up- or downregulated during spermatogenesis as found in a recent single cell RNA sequencing study59. Protein expression was retrieved from the Human Protein Atlas58 and interaction with known infertility genes3 was calculated using STRING version 1124. The final classification of the genes was then split into Not causative, Unlikely causative, Unclear and Possibly causative. These classifications were given based on the variant scores out of 6 with: [0 points + not expressed/not detected/not present on several occasions = Unlikely causative], [0 points + “Unknown” on several occasions = Unclear], [1–2 points = Unclear] and [3–6 points = possibly causative].Functional analysis was split into six different categories, each category provided a score of either 1 or 0 depending on whether they met the threshold for that category. These categories included: RNA expression of the gene in the testis, RNA enrichment in the testis or presence in spermatogenesis, protein expression in the testis, whether an infertile mouse model already exists for the given gene, the protein function in relation to spermatogenesis and finally whether the given gene interacts with any known fertility genes. For expression levels retrieved for each gene of interest from the GTEx database 62. CNVs present in more than 1% of the samples of the Database of Genomic Variants present in more than 10% of the patients were excluded from the analysis. The remaining rare deletions and duplications were individually inspected through the genomic profiles and detailed Log2Ratio plots generated by the workflow. Only CNVs involving more than 2 exons were further considered to minimize the inclusion of false positives, and we selected 2 CNVs present in the probands but absent in their parents for further validation.CNV calling was performed on our trio-based exome data with a custom GATK4-based pipeline. This workflow exploits the GATK4 sequence read depth normalization63  to confirm the presence of the mutation in probands and its absence in the parents. Primers for each SNV were designed using PrimerZNXT2 was exploited to validate the smaller CNV using the Applied Biosystems QuantStudio 7 Flex Real-Time PCR System .Validation of CNVs was performed with the whole genome Illumina Infinium CytoSNP-850K v1.1 microarray platform for the larger deletion on chromosome 11 and a gene-specific TaqMan Copy-Number assay designed for 8 containing genetic data from 141,456 individuals. We computed the likelihood of the observed median pLI score of each gene (LoF in controls) set compared to the expected median pLI based on the method described in Lelieveld et al.64. In short, we simulated the expected number of recurrently mutated genes by redistributing the observed number of mutations at random over a determined set of genes based on their specific LoF and functional mutation rates, however, in contrast to Lelieveld et al.64 and Samocha et al.23 before them instead of using the complete set of 18,226 pLI annotated genes to obtain expected median pLI scores, we used a set of 2766 coding DNMs in 1941 control individuals, downloaded from the de novo-db version 1.6.1 (http://de novo-db.gs.washington.edu/de novo-db/)12, to correct for the gene-specific mutation rate. The empirical P value was calculated by comparing the observed median pLI to the expected pLI following 100,000 random sampling simulations. Case and fertile controls were processed using the exact same filtration and annotation parameters as described above so that each variant detected was evaluated in a comparable manner. The same method was then repeated using the Loss-of-function observed/expected upper bound fraction or LOEUF score, which also is an indicator of LoF intolerance. To evaluate the impact of the de novo missense mutations to each gene, we used missense Z-scores calculated by gnomAD23 to predict the tolerance of each gene to variation in place of the pLI scores when applying the Lelieveld et al.64 methodology described above following 100,000 simulations. The presence of missense mutations in intolerant genes was compared between predicted pathogenic and benign using a two-tailed Mann–Whitney U test in our samples and in controls independently. To predict the affected protein function and the potential role in disease, we evaluated the interactions between the genes with a DNM using STRING version 1124.To evaluate the intolerance of each gene for loss-of-function (LoF) mutations, we used the probability of LoF intolerance (pLI) score, based on data from the Genome Aggregation Database (gnomAD)65. The 88 patients diagnosed with male infertility participating in the Geisinger-Regeneron DiscovEHR collaboration were selected from deidentified EHR information using the ICD-10CM code N46 which refers to “Male Infertility” including oligospermia, azoospermia, other male infertility and male infertility unspecified. All patients were sequenced at the Regeneron Genetics Center (RGC) as previously described39. In brief, 1ug of genomic DNA per sample was used for targeted exome capture using the NimbleGen VCRome 2.1 or the IDT XGen reagents. Captured libraries were sequenced on the Illumina HiSeq 2500 platform with v4 chemistry using paired-end 75 bp reads. Exome sequencing was performed such that >85% of the bases were covered at 20× or greater. Raw sequence reads were mapped and aligned to the GRCh38/hg38 human genome reference assembly using BWA-mem51, single nucleotide and indel variants were called using GATK’s HaplotypeCaller53. The Genetics of Male Infertility INitiative (GEMINI) is a multicenter study funded by the United States NIH. The GEMINI project performed whole-exome sequencing on 1,011 unrelated men diagnosed with spermatogenic failure, the vast majority with unexplained NOA. Sequencing of genomic DNA was performed at the McDonnell Genome Institute of Washington University in St. Louis, MO, USA, using an in-house exome targeting reagent capturing 39.1 Mb of exome and 2 × 150 bp paired-end sequencing on Illumina HiSeq 4000. Following sample QC, a final cohort of 924 men were analysed as part of the current study.The strongest candidate genes with DNMs were further investigated in exome data from four additional cohorts of infertile men. For the Italian cohort of 48 patients with NOA, exome sequencing was carried out as a service by Macrogen Inc. (Republic of Korea) utilizing the Agilent SureSelect_V6 enrichment and a NovaSeq 6000. The German Male Reproductive Genomics (MERGE) study comprised exome data of 887 men with azoo-, crypto-, or severe oligozoospermia. Known causes for male infertility like chromosomal aberrations and microdeletions of the AZF region were excluded in advance. WES was performed as previously described56. Following annotation variants from each of the additional case and control cohorts were filtered and processed in an identical manner as previously described. Shortly, variants with allele frequency >1% in gnomAD were discarded to focus only on rare variants: Pathogenicity predictions based on SIFT20, MutationTaster21 and PolyPhen22 were then used to exclude benign variants, all remaining variants were classified according to ACMG guidelines56. Like before, all protein-altering variants were considered pathogenic if predicted to be so by at least 2 out of 3 prediction models, absent from the fertile cohorts and present in <5 males in the gnomAD database. A similar analysis was done for all variants obtained in the control cohorts. However, just to be clear, for the male control cohort we did not exclude variants as pathogenic if they were present in this cohort itself.Genetic variants identified within the 152 candidate genes were extracted from each exome dataset. Consistent with our filtering method described above variants with <10 reads and/or <15% reads containing the mutation were discarded. To minimize discrepancies between genomic positions and annotation, genomic coordinates were recalculated to the GCRh37/hg19 where necessary and fully reannotated with VEPp values were corrected using the Bonferroni method corrections to adjust for performing 152 consecutive statistical tests and reduced the risk of Type I errors. Similarly, a gene-based burden test was performed to compare fertile fathers with fertile mothers from the control cohort of verified fertile parents to investigate whether any of the sexes predominantly carried a greater number of rare pathogenic mutations.Having identified several likely pathogenic rare loss-of-function and missense mutations in these 152 genes we performed a gene-based burden test to compare the combined data in all cohorts of infertile men with the control cohort of fertile fathers. The proportion of individuals with pathogenic variants in each of the 152 genes was statistically evaluated using two-tailed Fisher’s Exact tests, individual The origin of DNMs identified in the exomes of patients was first investigated in the short-read exome data by performing phasing analysis on those variants that contained a parental informative SNP (iSNP) within 150 bp from the DNM. As a next step, all DNMs were target-enriched with long-range PCR and sequenced using the Oxford Nanopore’s MinION sequencer . Target regions were designed to encapsulate both the DNM and a parentally informative SNP, from which parent-of-origin, and allele frequencies  could be ascertained and DNM pre-/post-zygosity could be determined.66 (version 2.3.6) and GRCh37.p5 based in-house GUI-wrapped pipeline. All expected fragment sizes were limited to a maximum of 12 kb for quality control and enrichment success rate. For those DNMs with no exome supported iSNPs within a 10 kb distance, primers were designed to cover approximately 2.5 kb on either side of the DNM with the expectation of finding additional iSNPs in the intronic regions. Long-range PCR target enrichment was carried out using our optimized running conditions of 3 separate supermixes/enzymes (see Supplementary Table Primers were designed using Primer3The long-range PCR target enrichments of >20 ng were prepared for sequencing with the ONT ligation sequencing kit (SQK-LSK109) following the manufacturer’s protocol, with adjustments for sample type and yield. Individual sample libraries were concentrated where necessary at given bead clean-up steps and pooled based on fragment size. Fragment size-based pools were combined prior to flowcell loading. Prepared samples were sequenced on the MinION using the FLO-MIN106 version 9.4 flowcell platform. Flowcells were run until complete pore exhaustion, with minimal refuel of flowcells performed whenever active pore percentages dropped below 70%, achieving an average of 30 billion basecall yields per flowcell and coverage depth per sample of >5000×.67 , resulting fastq outputs were adapter trimmed and low-quality reads discarded using cutadapt (version 2.5)68. Cleaned fastq files were mapped against Human Reference Genome (GRCh37.p5/hg19) using BWA-Mem51 (version 0.7.17), and sample targets were extracted from the resulting BAM file using SAMtools (version 0.1.19)69. Aligned ONT reads were phased using an in-house tool, with frequencies and pre/post-zygosity calls affirmed via IGV and principal component analysis using the available exome sequence data for probands and parents to support the ONT data.The sequence signal data in multi-fast5 format were basecalled using GuppyFurther information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1-13Reporting Summary