These changes were not seen with placebo. Dopamine also decreased ventilatory and mean arterial pressure responses to hypoxia (p < 0.05 for both). Inhibition of PChRs led to a decrease in V˙E/V˙CO2 comparing to placebo , with no effect on peak oxygen consumption. We found a significant relationship between PChT and the relative decrement of V˙E/V˙CO2 on dopamine comparing to placebo . There was a trend for correlation between PChS (on placebo) and V˙E/V˙CO2 during placebo infusion , but the relative improvement in V˙E/V˙CO2 was not related to the change in PChS (dopamine vs. placebo). We did not find a significant relationship between PChT and PChS. In conclusion, inhibition of PChRs in HFpEF population improves ventilatory efficiency during exercise. Increased PChS is associated with worse (higher) V˙E/V˙CO2, whereas PChT predicts an improvement in V˙E/V˙CO2 after PChRs inhibition. This results may be meaningful for patient selection in further clinical trials involving PChRs modulation.Peripheral chemoreceptors (PChRs) play a significant role in maintaining adequate oxygenation in the bloodstream. PChRs functionality comprises two components: tonic activity (PChT) which regulates ventilation during normoxia and acute reflex response , which increases ventilation following a specific stimulus. There is a clear link between augmented PChS and exercise intolerance in patients with heart failure with reduced ejection fraction. It has been also shown that inhibition of PChRs leads to the improvement in exercise capacity. However, it has not been established yet: 1) whether similar mechanisms take part in heart failure with preserved ejection fraction (HFpEF) and 2) which component of PChRs functionality (PChT vs. PChS) is responsible for the benefit seen after the acute experimental blockade. To answer those questions we enrolled 12 stable patients with HFpEF. All participants underwent an assessment of PChT (attenuation of minute ventilation in response to low-dose dopamine infusion), PChS (enhancement of minute ventilation in response to hypoxia) and a symptom-limited cardiopulmonary exercise test on cycle ergometer. All tests were placebo-controlled, double-blinded and performed in a randomized order. Under resting conditions and at normoxia dopamine attenuated minute ventilation and systemic vascular resistance ( The num of 1-2% .Clinically HFpEF presents with typical signs and symptoms of HF . Among tThere is some evidence that abnormal reflex control contributes to exercise intolerance in HFrEF , 2001. TApart from an augmented reflex response , the potential role of heightened tonic activity  of PChRs in exercise intolerance must be acknowledged. Its relation to worse exercise tolerance in HF population has not been extensively studied. Similarly, it is unclear whether the level of tonic activity is related to the sensitivity of acute reflex response in a given individual with HF. It is possible to directly assess the magnitude of tonic activation of PChRs using various approaches including hyperoxia  and low-2 slope) were observed. Based on these results obtained from HFrEF patients, one could speculate, that similar mechanisms may be in play in HFpEF. Data from some animals models indicate that central but not peripheral chemoreceptors are predominantly responsible for the autonomic imbalance seen in HFpEF   with a diagnosis of HFpEF in NYHA (New York Heart Association) II or III functional class were enrolled into the study after signing an informed consent. All subjects had to be clinically stable and optimally treated for at least 12 weeks before the study entry. The diagnosis of HFpEF, according to the current European Society of Cardiology guidelines criteria, was verified at initial evaluation and was based on the presence of signs and symptoms of HF, results of blood sampling, spirometry, electrocardiography and echocardiography . The preformula) , seriousThe study was performed in accordance with the Helsinki Declaration and was approved by the local Institutional Ethics Committee .−1 min−1, which is known to effectively inhibit PChRs   and Kansit PChRs . The samEchocardiographic imaging was performed according to recommendations of the American Society of Echocardiography and the European Association of Cardiovascular Imaging  using st2 (EtCO2) was sampled from the expiratory arm of the circuit and measured with capnograph . The inspiratory arm of the circuit was connected to the electric valve allowing for the silent switching between 100% nitrogen gas and room air. Hemodynamic parameters including: mean blood pressure (MAP), heart rate (HR), cardiac output (CO) and systemic vascular resistance (SVR) were continuously, non-invasively measured using Nexfin device . Oxygen saturation (SpO2) was collected with a pulse oximeter  using a lightweight probe attached to the earlobe. All the parameters were processed with PowerLab  and recorded on a laptop computer .Peripheral chemoreceptors function testing was performed twice in each subject—during an infusion of low-dose dopamine and during the placebo infusion in a supine position. After adjusting silicone nasofacial mask  patients were connected to a one-way open breathing circuit. A spirometry set  was attached to the expiratory arm of the circuit for continuous measurements of tidal volume (TV) and breathing rate (BR) from which minute ventilation (MV) was calculated. End-tidal CObaseline was recorded. Subsequently, the infusion of dopamine or placebo was initiated and continued for 10 min. This period was defined as “recording during infusion”. Next, after 5 min of rest, an analysis of acute sensitivity commenced which consisted of several (5-7) administrations of pure nitrogen gas (each for 2-20 s), which resulted in minimal values of SpO2 in a range between 90% and 65%. Length and order of hypoxic exposures was random and they were separated by 3-4 min of breathing with room air which allowed for the normalization of recorded parameters. Finally, the infusion of dopamine or placebo was withdrawn and the test ended.All patients were tested according to the same protocol depicted on 2 gas for time period lasting between 2 s and 20 s. This procedure was repeated 5–7 times per study participant which resulted in minimal SpO2 between 90% and 65%. After each N2 administration subjects were allowed to rest for 5 min breathing room air. A ventilatory response was averaged from the three largest consecutive breaths following the end of N2 administration and plotted against the associated nadir of SpO2 providing Point 1. Baseline values of MV and SpO2 were averaged from a 90 s period preceding each N2 administration. Then, baseline MV was plotted against baseline SpO2 providing Point 2. The slope of the regression line linking Point 1 and Point 2 was found for each N2 exposure. Arithmetic average of values of the slopes for all N2 administrations (−1 %−1) (PChS was assessed using well-described transient hypoxia method . Subjecttrations  was take(−1 %−1) .2 nadirs was calculated (HR slope and MAP slope respectively) to express the magnitude of acute hypoxic reactivity of a given hemodynamic variable.The hemodynamic responses to hypoxia were calculated in the analogous way as PChS. Hemodynamic data were smoothed by a moving average (10 s window) in order to eliminate the effect of fluctuations in HR caused by respiratory sinus arrythmia or atrial fibrillation. The slope of linear regression describing the relation between the peak values of HR and MAP after nitrogen administrations and corresponding SpO−1) was defined as the absolute decrease in MV following initiation of dopamine infusion. MV was averaged from the last 2 min of steady baseline recording and from the 2 min of recording during infusion, when changes in ventilatory and hemodynamic parameters stabilized following initiation of dopamine infusion . ECG was continuously monitored during the stress test . The cardiopulmonary exercise tests begun with a 5-min long resting phase to allow for familiarization with the equipment. Following the resting phase workload was set at 20 W and increased by 10 W every minute until maximal tolerated level of exertion was achieved  was performed in the upright seated position twice in each subject—during an infusion of low-dose dopamine and on saline. During the tests ventilatory parameters, end-tidal COachieved . The sub2), peak carbon dioxide production (peak V˙CO2), slope relating ventilation to oxygen uptake (V˙E/V˙O2 slope), slope relating ventilation to carbon dioxide production (V˙E/V˙CO2 slope), respiratory exchange ratio (RER) : peak oxygen uptake (peak V˙Oio (RER) , and peaexercise .P value < 0.05 was assumed as statistically significant.LabChart 8 , MATLAB  and Statistica 13  were used for analyzing the data. The data were blinded for the researchers responsible for PChS and PChT calculations. The statistical analysis was performed with the Wilcoxon matched pairs test and variables were presented as mean and standard deviation (SD) or mean and standard error of the mean (SEM). Spearman rank method was used for correlation calculation. The baseline clinical and physiological characteristics of the study population (n = 12) are presented in Δ = 6.2%, p = 0.03), SpO2 , SVR  but increased HR  and CO   and a trend for increase in EtCO2 . After placebo infusion a fall in SpO2  and increase in MAP  were observed while other ventilatory and hemodynamic parameters remained unaffected.Under normoxic resting conditions dopamine administration significantly attenuated MV  . We also−1 %−1 comparing to -0.4 ± 0.4 L min−1 %−1 (Δ = 35.1%) on dopamine. This difference was statistically significant (p = 0.0096). Additionally, dopamine infusion decreased MAP slope  with no effect on HR slope  .The mean PChS measured during placebo infusion was -0.6 ± 0.7 L min p = NS) . There wp = 0.24). There was a trend for a correlation between PChS on placebo and V˙E/V˙CO2 slope on placebo . Hemodynamic slopes on placebo  did not correlate with peak exercise indices .We did not find a relation between PChS (when measured on placebo) and PChT (p = 0.007) and between PChT and peak workload . No other correlations were found between PChS, PChT and exercise-derived parameters.Interestingly, significant positive relation was found between PChT and exercise time  and increased EtCO2  but had no effect on other reported peak exercise parameters . Furthermore, dopamine improved ventilatory efficiency by reducing V˙E/V˙CO2 nadir .The peak exercise values of the ventilatory and hemodynamic parameters are presented in 2 slope was related to PChT  (We found that both relative and absolute improvement in V˙E/V˙COctively) . Such co2 slope) following inhibition of PChRs with low-dose dopamine. We also present the inhibitory effect of dopamine on ventilatory response to hypoxia, and on resting minute ventilation. Using a novel approach based on the separate assessment of two components of PChRs functionality  . The stu−1 %−1 vs. 0.58 L min−1 %−1)  . This isTwo-thirds of the study population suffered from diabetes mellitus or impaired glucose tolerance. There are some premises suggesting that PChRs contribute to the control of glucose metabolism . RibeiroVisceral obesity was also present in most patients investigated in our study. Obesity often coexists with obstructive sleep apnea syndrome where repetitive apnea/hypopnea episodes augment CBs sensitivity and increase sympathetic gain . FurtherMoreover, all patients in our population suffered from hypertension which has been previously linked to PChRs’ oversensitivity  and hype−1 %−1). However, all those groups were characterized by considerably lower age than currently studied HFpEF population.The interpretation of PChS level in our work is limited by the lack of control group of age- and sex-matched healthy individuals. In the previous studies, where identical methodology of PChS assessment was employed  consiste−1 min−1 in order to activate selectively D2 presynaptic receptors (2 and post-synaptic type 1 dopamine receptors (D1) resulting finally in the augmentation of the neural traffic from CBs with subsequent hyperventilation, due to relative domination of D1 receptors  shows an affinity to β1‐receptors which may lead to mild positive inotropic and chronotropic effects , low-dose dopamine infusion also diminished the ventilatory response to hypoxia (PChS) and MAP slope, but did not influence HR slope when compared to placebo. This observations are in line with the results of our previous studies performed in healthy individuals . The dis2 slope. The decline in V˙E/V˙CO2 was modest but still statistically significant. Our results are supported by the fact that dopamine infusion did also significantly decrease nadir V˙E/V˙CO2 . Furthermore, our findings correspond well with previous papers reporting numerically modest but statistically significant improvements in ventilatory efficiency (reflected by V˙E/V˙CO2 slope) following various interventions. In the paper by Chua et al. blockade of peripheral chemoreceptors with dihydrocodeine led to decrease in V˙E/V˙CO2 slope from 34.19 ± 2.35 to 30.85 ± 1.91 (p = 0.01)   as recently reported by Vitale et al. (We showed that inhibition of PChRs with low-dose dopamine results in an improvement (decrease) of V˙E/V˙CO = 0.01) . Modulatp < 0.01 . Treatme= 0.023) . Finallye et al. .2 is an index of ventilatory effectiveness on exertion. Higher level of this parameter reflects increased ventilatory drive and is a well-recognized marker of poor prognosis  (p < 0.001)  . Similar< 0.001) .2 slope could be a result of either diminished ventilation or increased production of CO2. As we did not find a significant difference in peak V˙CO2 between stress tests performed on placebo and dopamine, it should be assumed that the attenuation of ventilation during exercise is mostly responsible for this benefit. An inhibition of PChRs with dopamine diminishes ventilation at rest and we assume that this effect is also in operation during whole exercise. This is further supported by the fact that the degree of improvement (decrease) in V˙E/V˙CO2 slope was proportional to the magnitude of MV attenuation following dopamine initiation (PChT). A decrease in tonic respiratory drive from PChRs might be further aggravated by a concomitant decrease in central respiratory drive, as a hyperadditive interaction between PChRs and central chemoreceptors has been previously described (−1 min−1) caused improvement in vascular conductance and oxygen delivery with no changes in ventilation (2 of 25 ml kg−1 min−1 and V˙E/V˙CO2 of 31.7). Therefore, we speculate that due to possibly low PChT in this apparently mildly affected population low-dose dopamine could not exert its ventilatory benefits as seen in our study.Mathematically a decrease in V˙E/V˙COescribed . Interestilation . This di2 slope has important clinical consequences. Attenuation of excessive ventilation on exertion reduces the subjective sensation of dyspnoea  . It should be noted that in all mentioned studies (including our work) the improvement in V˙E/V˙CO2 occurred following the inhibition of both components of PChRs functionality.The unique protocol employed in our study allowed for the separate assessment of the involvement of PChS and PChT in the ventilatory efficiency during exercise. In the study by Chua  inhibiti = 0.01) . CB rese = 0.01)  and bettInterestingly, we found that only PChT reflected the magnitude of improvement in exercise tolerance. In the study by Stickland et al.  dopamine2 slope. This can be explained by the following mechanisms. First, it is possible that the degree of inhibition of acute responsiveness arising from PChRs achieved with low-dose dopamine is not sufficient to translate into meaningful decrease in ventilation on exertion. Second, keeping in mind that the partial pressure of O2 remains fairly stable during exercise (2 slope (during placebo infusions) seen in our and in numerous previous studies? We believe that high PChS ought to be seen more as a marker of advanced HF  reduction in V˙E/V˙COexercise , it coulough CBs , where n2 slope in our study, it did not improve exercise tolerance as reflected by unchanged peak V˙O2. Thus, the exercise tolerance in HFpEF is likely determined by factors other than dysfunctional PChRs. For example, Toledo et al. demonstrated overactivation of central but not peripheral chemoreceptors in rats with HFpEF. Furthermore, acute stimulation of central chemoreceptors provoked increase in sympathetic gain, abnormalities in cardiac function and induced cardiac arrhythmogenesis  . This as−1 min−1 employed in our work has been shown to effectively inhibit both acute and tonic activity of PChRs  in HFpEF, the magnitude of which was similar to that previously reported in HFrEF . Our pro


Amyloid fibrils of the protein α-synuclein (αS)haverecently been identified as a biomarker for Parkinson’s disease(PD). To detect the presence of these amyloid fibrils, seed amplificationassays (SAAs) have been developed. SAAs allow for the detection ofαS amyloid fibrils in biomatrices such as cerebral spinal fluidand are promising for PD diagnosis by providing a dichotomous (yes/no)response. The additional quantification of the number of αSamyloid fibrils may enable clinicians to evaluate and follow the diseaseprogression and severity. Developing quantitative SAAs has been shownto be challenging. Here, we report on a proof-of-principle study onthe quantification of αS fibrils in fibril-spiked model solutionsof increasing compositional complexity including blood serum. We showthat parameters derived from standard SAAs can be used for fibrilquantification in these solutions. However, interactions between themonomeric αS reactant that is used for amplification and biomatrixcomponents such as human serum albumin have to be taken into account.We demonstrate that quantification of fibrils is possible even downto the single fibril level in a model sample consisting of fibril-spikeddiluted blood serum. PD diagnosis often remains ambiguous.3 A definitive diagnosis can only be achieved by a postmortem histologicalexamination of brain tissue for the presence of Lewy bodies and Lewyneurites, which are deposits composed of amyloid fibrils of the proteinα-synuclein (αS).Parkinson’s disease (PD) is thesecond most common and fastest-growingneurodegenerative disease.9 For reasons that are not well understood, αS self-aggregatesin dopaminergic neurons of PD patients. This aggregation process isthought to result in cell death due to the formation of, e.g., toxicoligomers, membrane disruption by αS fibrils, or formation ofintracellular amyloid aggregates.14Under normal conditions, αSis abundantly present in thebrain where it is thought to play a role in vesicle formation andtrafficking.15 αS amyloid fibrilshave been found not only in brain tissue but also in other biomatriceslike cerebral spinal fluid, skin, and blood to which they apparentlyleaked from the brain or from other tissues that share the αSpathology.16 The concentration of amyloidfibrils in these different biomatrices is however extremely low. Toallow for the detection of such low concentrations of amyloid fibrils,seed amplification assays (SAAs) have been developed. Initially, theassays were developed for prion detection. Later, they proved to beof use for amyloids of other proteins found in other diseases.19Recently, αS amyloid fibrils have beenidentified as a suitablebiomarker for PD.22 When these de novo processes are efficient, the assayis dominated by the amplification of de novo formed fibrils; the presenceof seeds only plays a minor role. The sensitivity of the SAA is hencelimited by de novo fibril formation. The presence of seeds in a sampleis visible as a shortening of the time required to reach a thresholdThT intensity compared to a control sample obtained under identicalconditions in which seeds are absent.SAAs exhibit low experimental complexity and high specificityandsensitivity. In SAAs, the initial very low number of fibrils act asseeds for the amplification of the fibril mass to a detectable level.Amplification is achieved by adding non-aggregated monomeric αSas reactant to the sample of interest. The seeds in the sample willrecruit monomeric αS reactant and elongate into longer fibrils.Shaking the sample induces fragmentation of the elongated fibrils,which increases the number of fibrils. These newly created fibrilsagain grow by recruiting monomeric reactant, and this cycle continues.This combination of events leads to an explosive increase in the numberof fibrils and thus the fibril mass. In the SAA, the amplificationis monitored using the fluorescent amyloid binding dye thioflavinT (ThT). Upon binding to the fibril, ThT becomes strongly fluorescent,which allows for the use of the total fluorescence intensity as areadout for the presence of fibrils once the seeds are sufficientlyamplified. Although the SAA is in principle very sensitive to thepresence of seeds, SAAs are only effective when de novo fibril formationis slow or inefficient compared to fibril amplification. De novo formationof fibrils can occur via several pathways. At sufficiently high αSreactant concentrations, nucleation can occur spontaneously. In addition,nucleation may also occur at interfaces depending on the experimentalconditions.30 Currently, the outcome of SAAs is used to determine whether seedsare present or not, providing a dichotomous response. QuantitativeSAAs, in which the number of seeds in a sample is determined, wouldbe a step toward enabling clinicians to monitor the effect of treatments,compare patients, and make predictions on disease progression. However,for a quantitative assay, it would be necessary to calculate backthe initial seed concentration.SAAs have been used todetect the presence of αS seeds indifferent biomatrices including cerebrospinal fluid and skin obtainedfrom PD patients, and their applicability to other biomatrices isbeing explored in several laboratories.31 Additionally,the relation between seed dilution and the timepoint at which halfof the maximum ThT fluorescence is reached was explored. Especiallyin compositionally more complex biomatrices, quantification has provenchallenging.32 One of the complicating factorsin these complex biomatrices is presumed to be the interaction ofreactant αS with matrix components.33First steps toward developingquantitative SAAs have been takenby using end-point dilution assays in the plate reader or by usingdigital microfluidics.34 This enables quantification as the combined effect of both contributionsto the amplification can be modeled. Here, we show in a proof-of-principlestudy under controlled conditions that it is possible to use the timeto reach a threshold ThT intensity (tthreshold) to make αS SAAs quantitative. We performed experiments inmodel solutions of increasing compositional complexity, includingblood serum, spiked with known amounts of αS seeds (Nseed). We measured the seed length distributionto determine the Nseed used for spiking.As for all conditions tested, the measured tthreshold scales with Nseed; thisrelation allows for quantification via a reference curve. We showthat it is possible to approach the single seed level in quantification.We identified human serum albumin (HSA) as the main interaction partnerof reactant αS and hence the major complicating factor in quantificationof SAAs in blood serum. Determining the αS–HSA interactionstrength allowed us to shift the equilibrium toward free reactantαS by diluting the serum, which restored the seed amplification.For αS, we have shown earlier that, at neutral pH andunderagitation, fibril growth can be described taking into account onlyfibril breaking and monomer addition.48 Briefly, αS was produced in Escherichiacoli (E. coli) cellstransformed with the pT7–7 plasmid carrying the αS gene.αS production was induced using IPTG. Finally, E. coli cells containing the protein were lysed andαS was purified by standard methods. Aliquots of αS werestored at -80 °C.αS wasproduced recombinantly, as described by Sidhu et al.2-coated 9 mLtubes  with each 9 mL of whole blood wererequested and obtained from the TechMed Centre donor service . Informed consent was obtainedfrom the donors, and the study was approved by the TechMed Centredonor service. The tubes containing blood were left for 24 h in thefridge at 4 °C before they were centrifuged for 10 min at 1000× g at 4 °C. The supernatants (serum) werepooled. 1 mL aliquots of the serum were stored in 1.5 mL tubes at−20 °C until needed for further use.SiO–1 cm–1. This solution of αS was diluted to 100 μM in 10 mMTris, 10 mM NaCl, and 0.1 mM EDTA at pH 7.4. The αS solutionwas incubated in low-bind round-bottom Eppendorf tubes at 37 °Cin an Eppendorf Thermomixer Comfort at an orbital shaking speed of750 rpm for 1 week. After this incubation time, αS had aggregatedinto amyloid fibrils. For further use, the tubes were pooled and centrifugedat 21,000 × g for 1 h at room temperature. Thesupernatant was used to determine the residual monomer concentrationby measuring the absorbance at 280 nm. The pellet was resuspendedin a fixed volume, and the fibril concentration was determined considering the residual monomer concentration. Thefibril solution was stored at room temperature. To induce fragmentationand produce seeds, the fibrils were sonicated in a Branson 2510 UltrasonicCleaner bath sonicator .Recombinantlyproduced αS monomers were thawed and filtered through an Anotop10 mm Whatman 0.02 μm filter. The protein concentration wasdetermined by measuring the absorbance at 280 nm and using a molarextinction coefficient of 5600 M2O to remove unbound seeds before thesample was dried with a soft flow of nitrogen (N2) andstored overnight at room temperature. AFM images were acquired usingabioscope Catalyst  in softtapping mode in air using the NSC36 tip B probe  with a force constant of 1.75 N/m. Images were acquired witha maximum scan size of 10 μm × 10 μm, a scan rateof 1.0 Hz, and a resolution of 512 pixels/line. Images were post-processedusing the Gwyddion software package . The seedlength distribution was determined by measuring the length of theindividual fibrils using Scanning Probe Image Processor-6.0.13  software.20 μL of the seed solution wasplaced on top of a freshly cleaved mica disk  and incubated for 4 min. The mica was rinsed three timeswith demineralized H2HPO4, 1.8 mM KH2PO4, 137 mM NaCl, 2.7 mMKCl, pH 7.4). The αS reactant was filtered through an Anotop10 mm Whatman 0.02 μm filter, and the protein concentrationin the SAA was set to 22 μM. The samples were spiked with preformedseeds at the equivalent monomer concentrations given in the main text.To monitor seed amplification, a total of 22 μM of ThT was added.The experiments were performed in 96-well polystyrene microplates and covered with a seal . The sample volume was 200 μL, and the experiments wereperformed in quadruplet. Seed amplification was monitored for 1000cycles at 37 °C with each cycle consisting of five repetitionsof 1 min of orbital shaking at 355 rpm and 1 min of no shaking ina plate reader .The fluorescence intensity  was measured from the bottom of theplate at the beginning of each new cycle with a gain setting of 100to obtain αS aggregation curves for each individual well.SAAs were performed in two different buffer conditions,one of low ionic strength  and another of high ionic strength  before adding αS reactant and seeds.The SAAs were also performed in human serumand diluted human serumfollowing the same protocol. By adding αS reactant and seeds,the serum was diluted by 10%. For the experiments in diluted serum,serum was diluted 70 times in the high ionic strength buffer . Capillaries were filled with the different samples. A capillary scanwas made to ensure that the initial fluorescence intensity was thesame in each of the capillaries. The MST was measured using a LEDpower of 20% and a MST power (IR laser) of 20, 40, and 80%. The plateausin the binding curves obtained at the different MST powers were usedto normalize the data. For each concentration, the data was averaged.The affinity betweenHSA and Alexa Fluor 488 labeled αS (αS-AF488) was determinedusing a Monolith NT.115 MST system. The thermophoretic movement was monitored using a constantconcentration of αS-AF488 (50 nM) with a dilution series of16 different concentrations of HSA (from 50 μM to 6.25 nM) preparedin high salt buffer  of around 84 ± 20 h. This implies thatthreshold times in this range are the result of de novo fibril formationand not of seed amplification. In analyzing the dataset, we thereforedifferentiate between tthreshold <64 h and tthreshold > 64 h, representingthe regimes in which the presence of seeds can and cannot be detected.In tthreshold is plotted as a function of the equivalentmonomer concentration; the regime in which seeds cannot be detectedis shaded. For equivalent monomer concentrations >10–15 M, we consistently find a tthreshold < 64 h, evidencing the presence of seeds. For equivalent monomerconcentrations <10–17 M, we consistently finda tthreshold > 64 h, indicating thattheassay is dominated by de novo fibril formation at these equivalentmonomer concentrations. At an equivalent monomer concentration of10–16 M, three of the four replicates have a tthreshold > 64 h and one has a tthreshold < 64 h. The average of tthreshold > 64 h and the single data point for tthreshold < 64 h are shown separately in tthreshold andthe relative spread on the data decrease. The observations qualitativelymatch expectations. At very low equivalent monomer seed concentrations,the reaction volume contains only a low number of seeds. At theselow numbers, the amplification of de novo formed fibrils may dominateover the seed amplification. In this case, tthreshold will remain constant and comparable to tthreshold in the control samples. The spread of the dataat very low seed concentrations represents the stochasticity of thede novo fibril formation. With increasing seed concentration, thecontribution of de novo formed fibrils to the amplification decreases,resulting in a decrease in tthreshold sincefewer rounds of amplification are needed to obtain the fibril massrequired to reach the threshold ThT fluorescence.To quantify the seed concentration dependence ofthe SAA, we determineda threshold time from the aggregation curves. This threshold timeis defined as the time required to reach a defined fraction of thefinal, plateau ThT intensity detected in the well. The threshold timesare selected to be in a regime where the fibril mass increases exponentiallywith time. In this series of experiments, we set the threshold to5% of the plateau ThT intensity. For control samples containing noseeds, we find an average time to the threshold  and plot this as a function of Nseed present in the sample interact with αS. We used an MST assay to investigate the interactionbetween HSA and αS and to quantify the binding affinity. In KD ≈ 300 nM. With this affinityand a reactant αS concentration of 22 μM, approximately99.9% of the αS is bound to HSA and not readily available forseed elongation. One way to address this problem is by diluting theserum while keeping the αS reactant concentration constant.To have at least half of the reactant αS directly availablefor seed amplification, we diluted the samples 70 times. With a KD ≈ 300 nM and a reactant αS concentrationof 22 μM, diluting the serum 70 times results in a decreaseof the fraction of reactant αS bound to HSA to approximately40%. In serum that was 70 times diluted with PBS, αS aggregationrestores as evidenced by the increase in ThT signal with time  is the number of fibrils at the timepoint t and tD is the doubling time. At the time tthreshold, a fixed (but unknown) number of seeds, Nthreshold, will be present in the sample. Theexpression can therefore be rewritten as Nseed and the observed tthreshold scales as tthreshold is linear for constant tD. In tthreshold for all three conditions tested. We include Nseeds for which we observe amplification asevidenced by a shortened lag time. Seed amplifications in low (blue)and high salt buffer (green), as well as in diluted serum (orange),show the expected linear relation. For all tested model solutions, tD is constant and hence independent of Nseed. The observed linear relation evidencesthat the contribution from de novo fibril formation to the amplificationcan be neglected for the range of seed concentrations shown and theexperimental conditions used.The αS SAAs rely on fibril elongation andfragmentation.In the ideal case, de novo fibril formation is negligible and thefragmentation and elongation rates are constant. In this case, thefibril mass doubling time is constant. This can be expressed as tthreshold and log(1/Nseed) in the regime where seed amplification dominated over the amplificationof de novo formed fibrils. With this linear relation, quantificationof Nseed in samples of interest is possible.However, the single seed level was not reached for all the conditionstested, e.g., due to efficient de novo fibril formation or inter-fibrilinteractions. An additional complication that needed to be consideredis the interaction of reactant αS with biomatrix components,such as HSA in blood serum, which reduces the amount of reactant αSavailable for seed amplification. We show that simple dilution ofblood serum restored seed amplification by shifting the binding equilibriumbetween αS and the αS–HSA complex to free reactantαS. An alternative approach to ensurethat there is sufficient αS reactant available might be increasingthe αS reactant concentration. This approach would however consumelarge amounts of αS and make the SAA more costly. A possibleadvantage of increasing the reactant αS concentration over sampledilution is that it likely does not suffer from the decrease in sensitivitythat comes with dilution of the sample. However, higher αS reactantconcentrations facilitate de novo fibril formation, which negativelyaffects the sensitivity of the SAA.Our proof-of-principle studyshows that SAAs performed in standardfluorescence plate reader experiments can provide quantitative resultsdown to the single fibril level for the well-defined conditions testedhere. In the experiments, we observed a linear relation between 3, [αS] ≈ 20–40μM) has to leak its full αS content in the form of seedsinto the blood stream. Performing an SAA on diluted samples effectivelyshifts the sensitivity of the SAA to higher initial seed numbers,in our case 70 times. The number of αS seeds in the bloodstreamis however most likely higher than the five fibrils per 200 μLmentioned above. Aggregation competent αS species are continuouslyreleased from cells, and seeds probably not only originate from thebrain but also from other tissues that are autonomously innervatedand share the αS pathology.40Although the assay can beextremely sensitive, the question remainsif this sensitivity can match the seed concentrations that may bepresent in patient material. For the experiments in diluted bloodserum, our data indicates that in quantification the single fibrillevel can be approached. For a sample of 200 μL to contain fivefibrils with a median length of 0.57 μm 1C, approtthreshold to Nseed in a patientsample, a reference curve is required. The data shownin tthreshold and log(1/Nseed), but the offset between the conditions differs. The nature of thedifferences in offset is currently unknown. The presence of the offsethighlights the need for reference curves obtained under the same experimentalconditions instead of relying solely on measured doubling times, tD. Due to compositional differences betweendifferent biomatrices, it will be necessary to optimize and obtainreference curves for each biomatrix. We do however not expect thatfor a given biomatrix, patient-to-patient differences in compositionwill play a major role. Small patient-to-patient differences in matrixcomposition are expected but are unlikely to play an important rolein the SAA by, e.g., changing the available reactant αS concentration.It is worth noting that there are compounds that can induce aggregationof reactant αS and the presence of these compounds in patientsamples would interfere with the SAA.43To establishthe sensitivity of the SAA and to convert the measured 44 In red blood cells, the αS concentrationis of the order of 26,200 ng/mL, which is approximately 2 μM.45 Even if red blood cells leak αS into serum, the αS concentrationwill be low compared to the added reactant αS. We thereforeexpect that red blood cell αS does not affect the assay in (diluted)blood serum.In blood serum,the presence of αS from red blood cells isa concern. However, αS concentrations in blood plasma have beenreported to be in the order of 25 ng/mL or equivalently 2 nM.26 A well-defined aggregation lag time in absence of seeds,as we observe for experiments in diluted serum, is beneficial forthe quantification of low seed numbers. Why de novo fibril formationis so well defined in diluted serum is unknown. Potentially interactionswith serum components limit the configurational freedom of αS,leading to a better defined nucleation of new fibrils. Additives suchas low concentrations of SDS may increase the accuracy of the SAAby this mechanism.47Although the presented quantification of αSseed numbersis promising, the SAA can be further improved. Quantification in thepresence of de novo fibril formation remains a challenge especiallyfor low seed numbers. In our experiments, de novo fibril formationis most likely mediated by surfaces; we expect that it can be furthersuppressed by using low bind microplates. Alternatively, de novo fibrilformation can be slowed down or completely suppressed by using theαS K23Q mutant as the αS reactant.Nseed, the amplification is not hampered by de novo formationof fibrils; for these Nseed, we find aconstant doubling time for all solution conditions tested. We showthat under controlled conditions, seed quantification is possibledown to the single seed level via a reference curve in a standardfluorescence plate reader assay. In compositionally more complex biomatrices,interactions with reactant αS interfere with the assay but relativelysimple measures, like a dilution step, can restore αS seed amplification.Our study demonstrates the potential of SAAs for fibril seed quantification,but at the same time, it indicates that inhomogeneity of the seedpopulation, compositional differences of the biomatrices, and interactionsbetween biomatrix components and reactant αS remain a challenge.In summary, our proof-of-principlestudy shows the potential ofSAAs for the quantification of seed concentrations, even in compositionallycomplex samples. The sensitivity of the SAA is limited by the de novoformation of fibrils. However, for a broad range of


The authors would like to make corrections to the reference citations in the original article , includiAs a result of the corrections to citations, the main text needs to make the following corresponding changes:In Table 1, “Protects myocytes against volume overload post-I/R injury” should be corrected to “Protects myocytes against”.In Section 3.1.1, “A review characterizing the possible mechanism of action for extracellular loop peptides is found in the literature by Beyer et al.” should be corrected to “A review characterizing the possible mechanism of action for extracellular loop peptides is found in the literature by Berthoud et al.”.In Section 3.1.2, “Other investigations of Peptide5 in preclinical models have included elucidation of its salutary effects on retinal pigment epithelial cell barrier function [107], diabetic retinopathy [108], and chronic kidney disease [109]” should be corrected to “Other investigations of Peptide5 in preclinical models have included elucidation of its salutary effects on retinal pigment epithelial cell barrier function [106] and chronic kidney disease [107]”.2.As a result of the corrections to citations, the “References” section needs to make the following corresponding changes:References  in the original article are deleted.References  in the correction are newly added.With this correction, the order of some references has been adjusted correspondingly. The Academic Editor has checked this correction. These changes do not affect the conclusions presented in the paper. The original article has been updated.


Saccharomyces cerevisiae industrial strains have complex polyploid genomes and are sterile, preventing genetic improvement strategies based on breeding. Here, we present a strain improvement approach based on the budding yeasts’ property to promote genetic recombination when meiosis is interrupted and cells return-to-mitotic-growth (RTG). We demonstrate that two unrelated sterile industrial strains with complex triploid and tetraploid genomes are RTG-competent and develop a visual screening for easy and high-throughput identification of recombined RTG clones based on colony phenotypes. Sequencing of the evolved clones reveal unprecedented levels of RTG-induced genome-wide recombination. We generate and extensively phenotype a RTG library and identify clones with superior biotechnological traits. Thus, we propose the RTG-framework as a fully non-GMO workflow to rapidly improve industrial yeasts that can be easily brought to the market.Breeding and domestication have generated widely exploited crops, animals and microbes. However, many  Domesticated industrial yeast strains are sterile, which hampers to breed strains with novel properties. Here, the authors employ the genetics paradigm return-to-growth to induce genome wide recombination in two sterile polyploid industrial yeasts and identify clones with superior biotechnological traits. Selective breeding, in which hybrids with improved performance are generated, was one of humanity’s first biotechnology advances and it remains widely applied2. The advent of new genetic engineering techniques enabled to directly manipulate core biological traits relevant for human activities3. However, the exploitation of genetically modified organisms (GMOs) in the food sector remains controversial, highly regulated and restricted in many countries.Humans have selected and improved organisms for centuries, leaving profound hallmarks of domestication in their genomes and lifestylesSaccharomyces since the earliest food and beverages fermentations practices6. Since then, novel fermentation processes selected new yeast strains that are still used nowadays7. Nevertheless, there is a pressing interest across different sectors that exploit Saccharomyces yeasts to create new strain variants able to better tolerate stresses encountered during the industrial fermentations or increase the yield of desired compounds. Newly designed de novo lab-hybrids that combine different Saccharomyces species have displayed good or superior fermenting properties compared to common commercial strains. Recently, other methods based on breeding have further expanded the capability of generating genetic diversity in Saccharomyces species in diploid interspecies hybrids by passing through intermediate fertile tetraploid8 or by generating hybrids with higher ploidy through iterative hybrid production (iHyPr)9. This suggests that indeed commercial strains are not yet optimized, leaving room for improvement despite the long domestication period12. However, attempts to cross industrial yeasts through selective breeding or induce genomic recombination through meiosis are often unsuccessful due to the inherent sterility of the strains, which is a hallmark of yeast domestication13 and breeding them relies on a CRISPR/Cas9 engineering14. The domestication syndrome might have derived from the lack of selection on sexual reproduction, random genetic drift or adaptation to specific fermentation niches, leading to the accumulation of punctuated deleterious loss-of-functions (LOF) alleles that inactivate genes involved in the gametogenesis (sporulation in yeast). In addition, the genomes of industrial strains often have features such as extreme sequence divergence between the subgenomes (namely heterozygosity), structural rearrangements, aneuploidy and polyploidy all of which are known to contribute to sterility15. Classic examples are strains used in beer production or in the baking industry sharing different ancestries that have repeatedly converged toward polyploid complex genomes17. However, tetraploid strains derived from designed crosses perform a correct chromosome segregation and produce viable gametes18 in contrast to triploid strains. Therefore, the genetic basis driving this extreme sterility are not yet fully understood and multiple factors likely contribute to impair the sexual reproduction of industrial polyploid strains. Thus, other approaches to improve sterile industrial strains have been proposed19 because directly fixing the lack of a complete sexual reproduction remains challenging.Humans unwittingly domesticated yeasts of the genus 21. RTG is induced when cells that have entered meiosis but are not yet committed to complete it are shifted back to a nutrient-rich environment, although some mutants can maintain an extended uncommited state23. As in normal meiosis, after DNA replication Spo11p induces multiple genome-wide double-stranded breaks (DSBs) that lead to the formation of intermediate recombinant molecules24. These molecules are then resolved upon the re-entering of the mitotic cell cycle, resulting in dispersed LOH tracts that derive from the segregation of the chromatids in the mother and daughter cells. Despite generating multiple dispersed LOH tracts, the RTG process is not mutagenic and preserves the initial diploid genome content in laboratory strains20. Furthermore, the LOHs induced by RTG can lead to rapid phenotypic diversification through the unmasking of beneficial alleles21. Given that RTG induces phenotypic variation without complete sexual reproduction, which often is defective in industrial strains, RTG may represent a powerful approach for improvement of industrial strains. However, it is still unknown whether the RTG paradigm can induce recombination and unlock novel phenotypic variability without triggering systemic genomic instability in more complex genomic scenarios. Furthermore, the selection of RTG recombinant clones either requires genetically engineered selective markers20 or a lengthy and low throughput microdissection approach21. This hinders the scaling-up of the RTG process to generate a large library of recombined industrial yeasts.Recently, we demonstrated that aborting meiosis in laboratory-derived sterile diploid hybrids and returning them to mitotic growth, a process called return-to-growth (RTG), promoted evolution by enabling recombination between subgenomes resulting in phenotypic variability in the evolved samplesIn this work, we develop a comprehensive workflow to improve polyploid industrial yeasts through RTG and easily select RTG-recombined clones. We apply this workflow to generate a non-GMO library of evolved industrial polyploid strains harbouring improved biotechnological traits.Saccharomycescerevisiae strains as test cases, hereafter called OS1364 and OS1431  with OS1431 harbouring more than the expected number . Among these polymorphisms we found pervasive heterozygous missense variants  harbouring genes derived from Zygosaccharomyces bailii  Fig. . In orde431 Fig. , and chages Fig. . A largeges Fig. . This isn = 207 OS1364, n = 338 OS1431), including 10 (OS1364) and 24 (OS1431) in genes that are essential in S288C27 , in line with its lower heterozygosity on chromosome II   of the genome affected by LOH, whereas OS1431LYS2/URA3 had an average of 6.7% . Moreover, we did not detect any chromosome loss potentially accounting for 5-FOA resistance in the RTG sequenced clones, showing that despite the strain polyploidy, LOH at the LYS2/URA3 locus arose more frequently than aneuploidy during RTG. We observed overall genome-wide stability and detected only one aneuploidy and two large CNVs across the 11 RTGs derived from OS1431LYS2/URA3, where the two CNVs likely resulted from ectopic recombination initiated by a small region of homology between chromosome IX and chromosome XIV  and therefore unable to complete sporulation    across several conditions mirroring industrial fermentations  and their LOH landscape across a core set of fermentation genes (n genes = 74), and all the M-D RTG pairs from OS1431 (n = 10)  with the argument “-p” to set an appropriate ploidy and quality >20. We annotated impactful mutations by using the VEP suite43. Mutations were annotated as impactful if they caused a stop-loss, stop-gain, or start-loss. Subtelomeric variants or frameshift ones were included in the list to make the data comparable to the table of LOFs generated for the 1011 S. cerevisiae yeast project16. The list of essential genes was obtained from Liu et al23. It is possible that some genes listed as essential are such because their deletion or alteration affects the gene on the opposite strand. We found three such cases in the essential genes detected as homozygous, which do not generate LOF on the gene on the opposite strand, so their essentiality may not be as predicted in Liu et al.27. The GO-term analysis was performed using the SGD GO-term analysis suite at https://www.yeastgenome.org/ with a p value threshold of 0.01 and selecting GO-term associated with sporulation. We identified pre-existing LOHs in the genome of the parental strains by searching for non-overlapping regions of 50 kbp where we identified 10 or less heterozygous markers that were not shared by all the unphased haplotypes. The plots were generated using ggplot2 and in-house R scripts.Short reads of the parental strains were obtained from the 1011 The genome content of OS1364 and OS1431 was measured using propidium iodide staining. Each strain was patched from a −80 °C glycerol stock onto a YPD plate  and incubated overnight at 30 °C. The following days the strains were incubated in 1 mL liquid YPD medium  and grown overnight at 30 °C without shaking. The next day 200 µL of the overnight culture was resuspended in 1 mL of fresh YPD and growth until the exponential phase. Then cells were centrifugated, washed with 1 mL water, and fixed overnight in 1 mL of EtOH 70%. The following day each sample was washed with PBS 1×, resuspended in the PI staining solution , and incubated for 3 hours at 37 °C in the dark. Ten thousand cells for each sample were analysed on a FACS-Calibur flow cytometer. Cells were excited at 488 nm and fluorescence was collected with an FL2-A filter. An increase of 50% of the fluorescence value (a.u.) compared to the fluorescence signal of the diploid cells in G1 was used to assign a ploidy of 3n. An increase of 100% of the fluorescence value (a.u.) compared to the fluorescence signal of the diploid cells was used to assign a ploidy of 4n.44. The Canu assembler mostly merged the different haplotypes and thus prevented to production of long-read phased genomes. The dotplots were generated by using nucmer and mummerplot45. The annotated non-reference regions on chromosome XIII of OS1364 were extracted from the fasta file of the collapsed assembly genomes (the haplotypes were not phased) and blasted by using the application “blastn” at https://www.ncbi.nlm.nih.gov/ against the database of ascomycetes.Yeast cells were grown overnight in a liquid YPD medium. Genomic DNA was extracted using Qiagen Genomic-Tips 100/G according to the manufacturer’s instructions. The MINION sequencing library was prepared using the SQK-LSK108 sequencing kit according to the manufacturer’s protocol. The library was loaded onto an FLO-MIN106 flow cell and sequencing was run for 72 hours. We performed long-read basecalling and scaffolding using the pipeline LRSDAYYeast strains were patched on YPD plates and incubated at 30 °C for 24 hours. From the patch a streak was done and incubated at 30 °C for 48 hours, then single colonies were isolated and grown overnight at 30 °C in 10 mL of liquid YPD in a shaking incubator at 220 rpm. The following day, single colonies were inoculated in different tubes containing 10 mL of the pre-sporulation medium SPS  and kept at 30 °C in a shaking incubator for 24 hours. Tubes were then centrifuged and washed three times with sterile water and cells were resuspended in erlenmeyer flasks containing 25 mL of KAc 2% to reach a final OD of 1, and incubated at 23 °C in a shaking incubator. Sporulation was monitored by DAPI staining of the sporulation cultures to detect cells that have passed the first meiotic division, and contain two nuclei, or the second meiotic division, and contain four nuclei. The cells taken from the meiotic culture were first washed with 1 mL water and then fixed with 1 mL EtOH 70% overnight. Then, 200 µL of culture were stained with 2 µL of DAPI  0.5 µg/mL, and 10 µL of stained cells were spread on a microscope slide and incubated in the dark for 40 minutes. To infer the efficiency of meiotic progression the cells were examined by fluorescence microscopy (Imager Z1 Zeiss) using a DAPI filter and scored as having one, two, or four nuclei, which indicates if they have not progressed after MI (one nucleus) or have progressed after MI (two nuclei) or MII (four nuclei). For assessing the spore viability, the spores were collected from the sporulated cultures and incubated between 30–60 minutes in 100 µL of zymolase solution in order to perform spore dissection. At least 100 tetrads per sample were dissected on YPD plates using a SporePlay(+) (Singer). Spore viability was assessed as the number of spores forming visible colonies after 4 days of incubation at 30 °C.URA3, NDT80, and SPO11 were engineered by using CRISPR/Cas9 genome editing. The plasmid harboring Cas9 was obtained from Addgene pUDP00446 and linearized with BsaI. The resistance to acetamide was replaced with the resistance cassette to Kanamycin which was amplified from a plasmid harboring the KanMX resistance cassette. The gRNA with the necessary nucleotide for self-cleavage was designed on UGENE47 and ordered as a synthetic oligo from Eurofins Genomics (™). The synthetic oligo was cloned into the plasmid backbone by using the Gibson assembly kit  and the ligation reaction was carried out for 1 hour at 50 °C. The assembled plasmid was transformed into DH5-alpha competent bacteria by heat shock and the bacteria were incubated in 3 mL of LB broth for 1 hour to induce the synthesis of the antibiotic resistance molecules and then plated on LB plates containing 100 µg/µL of ampicillin. The following day, cells were screened by polymerase chain reaction (PCR) using primers to validate the correct golden gate assembly of the construct. Successfully transformed bacterial colonies were inoculated in LB broth containing 100 µg/uL of ampicillin and incubated overnight at 37 °C. Cells were harvested from the overnight incubation and the plasmid was extracted using the QIAprep Spin Miniprep Kit following the manufacturer’s instructions.The multi-deletions of URA3, NDT80, and SPO11 were designed to be flanking 60 bp upstream and downstream of the candidate gene, which harbours the cutting site for Cas9 and ordered as a unique synthetic oligo at Eurofins Genomics. The forward and reverse cassettes were mixed at equimolar ratio, heated at 95 °C for 15 mins, and then cooled down at room temperature to be ready for the transformation. Yeast samples were transformed using between 1 and 15 µg of cassette, at least 200 ng of CRISPR/Cas9 plasmid, and following the protocol from42. Cells were then plated on selective media containing kanamycin (400 µg/mL) and incubated at 30 °C for 3–7 days. Candidate transformed clones were validated by PCR using primers designed on the outside regions of the deleted genes. Positive clones were streaked on YPD and grown for 2 days at 30 °C to allow plasmid loss. Plasmid loss was confirmed by plating again the colonies in the selective medium and positive ones were patched on YPD and stored at −80 °C in 25% glycerol tubes.The 120 bp cassettes used for the deletion of URA3 cassette was introduced in one LYS2 locus on chromosome II in URA3 knock-out OS1364 and OS1431 strains by using the classical lithium acetate protocol. The correct insertion was validated by checking for restored prototrophy on synthetic media lacking uracil and by PCR. Positive clones were stored at −80 °C in 25% glycerol tubes. For performing the URA3-loss assay, cells from the frozen stocks were patched on YPD plates and incubated at 30 °C for 2 days. Cells were then streaked on plates lacking uracil and incubated at 30 °C for 2 days. Single colonies were picked and sporulation was induced following the protocol described in the paragraph “Sporulation monitoring and spore viability”. Cells from the sporulation cultures were taken at 0, 6, and 14 hours after sporulation induction, washed three times with YPD, and incubated in YPD for 12 hours at 30 °C without shaking. Dilutions of the YPD liquid culture were spotted onto YPD plates and an appropriate dilution was chosen for each strain and plated on 5-FOA  plates. The plates were incubated at 30 °C for 2 days and colonies growing on 5-FOA plates were counted at all the time points. We calculated the LOH rate at the three-time points  as the ratio between the % of cells growing on 5-FOA and the respective percentage of cells growing on YPD, according to the following equations:5-FOA,T0 is the number of colony-forming units on 5-FOA at T0 and CFUYPD,T0 is the number of colony-forming units on YPD at T0. These LOH rates were used to calculate: (1) the fold-increase of cells experiencing LOH by dividing the LOH rate at T6 or T14 by the LOH rate at T0 (LOH ratio); (2) the absolute difference of LOH by subtracting the LOH rate at T0 to the respective LOH rates at T6 and T14.A Sporulation of wild-type hybrids was induced as described in the section “Sporulation monitoring and spore viability” for a time window compatible with RTG (14 hours). Cells were withdrawn from the sporulation medium before the appearance of MI cells (two nuclei) to avoid plating cells committed to complete sporulation. At the appropriate timepoint, cells were shifted from sporulation medium to liquid YPD. Part of the cells was incubated between 2 and 3 hours to induce RTG but not budding and separation of the mother-daughter RTG pairs, while others were incubated longer to allow complete budding and separation of candidates M-D RTG pairs. Then, the samples were plated on modified YPD media , and plates were incubated at 30 °C and monitored daily for colony formation and morphology variation. M-D RTG pairs were selected as colonies displaying two sectors with different morphology, of which one resembled the wild-type phenotype whereas the other was divergent. Cells from each side of the sectors were taken with a wooden stick and streaked on their respective modified YPD to limit contamination from cells of the other sector, and incubated at 30 °C for 2 days. Then, a single colony was taken, patched on YPD and incubated at 30 °C for 2 days, and finally stored in 25% glycerol tubes at −80 °C. Pictures of the sectoring colonies on the plates were taken with a stereomicroscope Discovery v.8 Zeiss.5 or lower coverage affecting only small chromosomes. Aneuploidies and large CNVs were detected by manually inspecting the log2 coverage profiles, while shorter CNVs (<1 Kbp) were detected by computing the median coverage across sliding windows of non-overlapping 1 Kbp. Regions showing a coverage variation with respect to the median of their respective chromosomes were then matched with the previously detected CNVs.Short reads Illumina sequencings were performed at the genomic platform of the Institute Curie. Reads were mapped to the S288C reference genome with the bwa-mem algorithm. Optical duplicates of the sequencing were removed using “samtools rmdup”. Processed BAM files were then indexed using “samtools index” and coverage was extracted using “samtools depth”. Coverage along the chromosomes was plotted using in-house R scripts in which sliding windows of non-overlapping 10 kbp were used to calculate a local average coverage, which was then normalized with the median coverage along the chromosome. Genome-wide coverage profiles were manually inspected to detect artifacts due to smiley patternLYS2/URA3 selected RTG, and ndt80Δ RTG) were filtered out because were considered to be unlikely generated by RTG, but rather representing pre-meiotic events. Additionally, LOH/AF shift regions overlapping for ≥ 90% of their length with the ones found in the T0 samples were also excluded. LOHs spanning the LYS2/URA3 locus on chromosome II were not excluded but that chromosome was not counted for calculating the percentage of markers lying in regions with AF shift. Moreover, LOHs/AF shift regions or CNV already present in the parental samples engineered with the LYS2/URA3 system, or in which NDT80 was deleted, was removed from the respective derived RTG samples. LOHs/AF shift regions in subtelomeric regions were excluded due to the unreliability of mapping in these highly repetitive regions. Finally, the list of annotated CNVs in core parts of the genome of the parental strains was used to filter the LOH/AF shift regions detected. The plots of the AF shift distribution were done using an in-house R script implemented with ggplot2 (v3.6.1) that takes into account the genotype shift of each marker in the recombination blocks.To identify LOHs in the evolved RTGs, we first generated a list of reliable markers represented by all the heterozygous positions between the reference S288C strain and the two polyploid parental genomes (OS1364 and OS1431). Reads mapping and post-processing of sequenced parental strains, T0 and RTG samples were performed as described in the previous paragraph “CNVs detection in parental strains and RTG samples”. Variant calling in the parental strains was performed by using Freebayes (v1.3.1–19) with the options “-p” to set the appropriate ploidy. The parental vcf files were then filtered to include only SNP markers with quality >20 and depth >10 using bcftools with the options “TYPE = snp, QUAL > 20, DP > 10”. Variant calling on the evolved RTG and control (T0) clones was done using Freebayes with the options “-p” to set the appropriate ploidy, “-@” to call variants at the previously identified heterozygous positions and the additional options “-m 30, -q 20 -i -X -u” for setting a minimum depth, quality score and to exclude complex variants. Vcfs were then filtered with bcftools to take only SNP variants. As an additional filtering step, the parental and sample vcf files were intersected using bedtools “-intersect” and variants with shared positions were retained from the vcf of the RTG-evolved samples. Next, we used an in-house R script to compare the frequencies of the alternative and reference alleles of each marker in the evolved samples and in the parental ones. We identified putative recombined markers like the ones showing an AF shift comparing the parental and the RTG AF, independently of the direction of the AF shift. Heterozygous markers present in the parental strain but not genotyped as heterozygous in the RTG samples were considered to have reached a homozygous reference genotype if the position was sequenced. Moreover, the allele of the marker tagged as having an AF shift was compared with the known allele of the marker present in the ancestral strain, and those not matching the expected allele were filtered out. Given the complexity of polyploids analysis, we decided to use a stringent threshold and we annotated regions of AF shift only if they contained at least nine consecutive markers with AF shift regardless of the directionality of the allele that is gained or lost due to recombination. In this way, we avoided calling false-positive AF shift regions at the cost of decreasing our resolution. This approach may decrease the number of gene-conversion events detected as they are generally small (< 2 kbp) and thus may fall below our threshold. Moreover, our resolution in mapping long recombination events was limited by the local heterozygosity between the haplotypes as we did not have information on the phased haplotypes for our strains. Regions of local homozygosity between the two recombining haplotypes may be intervaling regions of heterozygosity on which we identified an AF shift thus breaking the AF shift region and resulting in the fragmented pattern observed. For this reason, we refrained to give numbers of events but only referring to AF shift regions. Among those LOHs/AF shift regions, the ones overlapping for >80% of their length in at least ≥ 70% of the samples considering each datasets separately  and placing the plates in the Bioscreen C MBR. The optical density of the microcultures at 600 nm was automatically read every 30 min. Four replicates were performed for each strain in each medium. Growth curves for the microcultures were modeled based on the OD600 values over time using the ‘GrowthCurver’-package for R48.The osmotic stress and ethanol tolerance were assessed with microcultures in media containing 25% (w/v) sorbitol and 8% (v/v) ethanol, respectively. The microcultures were carried out in 100-well honeycomb microtiter plates at 25 °C (with continuous shaking), and their growth dynamics were monitored with a Bioscreen C MBR incubator and plate reader . The wells of the microtiter plates were filled with 300 µL of YPM medium  supplemented with sorbitol (25%) and ethanol (8% v/v). Control cultivations in media without sorbitol or ethanol were also carried out. Pre-cultures of the strains were started in 20 mL YPM medium and incubated at 25 °C with shaking at 120 rpm overnight. We measured the optical density at 600 nm, and pre-cultures were diluted to a final OD−1. Fermentations were carried out in duplicate at 20 °C for 13 days. Fermentations were manually monitored by weighing mass lost as CO2. The alcohol content of the final beer was measured with an Anton Paar density meter DMA 5000 M with Alcolyzer beer ME and pH ME modules .50 mL-scale fermentations were carried out in 100 mL Schott bottles capped with glycerol-filled airlocks. Yeast strains were grown overnight in 25 mL YPM medium at 25 °C. The pre-cultured yeast was then inoculated into 50 mL of 32 °P wort made from malt extract  at a rate of 7.5 g fresh yeast L49. Briefly, yeasts were first grown from frozen stocks 30% glycerol stocks in 100 mL YP-Maltose  and grown overnight. Then cells were transferred to 500 mL YP-Maltose and incubated overnight at 25 °C with shaking at 120 rpm. Finally, the culture was inoculated into two liters of 15°P wort and grown for 1 week (the ‘G0’ fermentation) at 20 C. This yeast was then collected and inoculated into the experimental fermentation as described below. The experimental fermentations were carried out in triplicate, in 3-liter cylindroconical stainless steel fermenting vessels, containing 2 liters of wort medium. The 20 °P wort  was produced at the VTT Pilot Brewery from barley malt and malt extract . Fermentations were inoculated at a rate of 5 g fresh yeast L-1 (corresponding to ~15 × 106 viable cells mL−1). The wort was oxygenated to 10 mg L−1 prior to pitching . The fermentations were carried out at 20 °C until the alcohol level stabilized, or for a maximum of 15 days. Wort samples were drawn regularly from the fermentation vessels aseptically and placed directly on ice, after which the yeast was separated from the fermenting wort by centrifugation . Samples for yeast-derived flavor compound analysis were drawn from the beer when fermentations were ended. Cell viability was measured by propidium iodide staining of the cells that were collected at the end of the fermentations using a Nucleocounter ® YC-100TM .Strains were characterized in fermentations performed in a 20 °P high-gravity wort at 20 °C. Cultures were propagated essentially with the use of a “generation 0” fermentation prior to the actual experimental fermentations+ (8%) LC column  was equilibrated with 5 mM H2SO4  in water at 80 °C, and samples were eluted with 5 mM H2SO4 in water at a 0.8 mL min−1 flow rate. The alcohol level (% vol/vol) of samples was determined from the centrifuged and degassed fermentation samples using an Anton Paar density meter DMA 5000 M with Alcolyzer beer ME and pH ME modules .The concentrations of fermentable sugars  were measured by HPLC using a Waters 2695 separation module and Waters system interphase module liquid chromatography coupled with a Waters 2414 differential refractometer . A Rezex RFQ-Fast Acid H−1) into a gas chromatograph equipped with an FID detector and headspace autosampler . Analytes were separated on an HP-5 capillary column . The carrier gas was helium (constant flow of 1.4 mL min−1). The temperature program was 50 °C for 3 min, 10 °C min−1 to 100 °C, 5 °C min−1 to 140 °C, 15 °C min−1 to 260 °C, and then isothermal for 1 min. Compounds were identified by comparison with authentic standards and were quantified using standard curves. 1-Butanol was used as an internal standard (50 μL of a 5 g/L aqueous solution) and was added to each sample.Yeast-derived higher alcohols and esters were determined by headspace gas chromatography with flame ionization detector (HS-GC-FID) analysis. Four-milliliter samples were filtered (0.45 μm pore size) and incubated at 60 °C for 30 min, and then 1 mL of gas-phase was injected (split mode, 225 °C, split flow of 30 mL minFurther information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Supplementary Data 9Supplementary Data 10Supplementary Data 11Supplementary Data 12Reporting Summary


In this work, we demonstrate the importanceof decoupled ion–electron transfer and charged adsorbates onthe performance of electrodes under nonequilibrium conditions. Finally,our findings on MIEC–gas interactions have potential implicationsin the fields of energy storage and catalysis.Activation losses at solid oxide fuel cell (SOFC) electrodeshavebeen widely attributed to charge transfer at the electrode surface.The electrostatic nature of electrode–gas interactions allowsus to study these phenomena by simulating an electric field acrossthe electrode–gas interface, where we are able to describethe activation overpotential using density functional theory (DFT).The electrostatic responses to the electric field are used to approximatethe behavior of an electrode under electrical bias and have founda correlation with experimental data for three different reductionreactions at mixed ionic–electronic conducting (MIEC) electrodesurfaces (H The dipole at the electrode–liquid electrolyteinterface, known as the activation overpotential (ηact), accounts for the energy barrier of charge-transfer processes suchas Li-ion intercalation.8 For SOFC systems, these phenomena do not apply, and little is knownabout the electrode–gas interactions that determine the activationoverpotential. The ambipolar transfer of ions and electrons with thegas phase means that this interface is chemical in nature.9 However, in the limit where one of these charge-transferprocesses is particularly slow, the adsorbed gas will become chargedand will therefore impose an electrostatic surface potential (χ)across the electrode–gas interface.Electrochemical devices, suchas solid-oxide fuel cells (SOFCs), allow for reversible chemical toelectrical energy conversion, with efficiency surpassing that of thecombustion engine.11(g), Voden+, eode– and Redode represent the oxidized gas species  or H2O(g)), the vacant surfacesite, mobile electrons, and the reduced species, respectively. Superscript n represents the charge of the vacant site and the numberof electrons consumed by an ambipolar charge-transfer reaction. Inthe theory outlined by Fraggedakis et al., Faradaic reactions at anelectrode–electrolyte interface can proceed through a coupledion–electron transfer (CIET) mechanism.4 The excess chemical potential landscape in The process of gasreduction at a MIEC surface can be generalizedas13 Few experiments have investigated the complex Δχ –ηact relationship, leaving this phenomenon poorlyunderstood despite its kinetic merit.17 By analyzing the shift in the outer work function using operando X-ray photoelectron spectroscopy (XPS) over anapplied overpotential range, Feng et al. measured the Δχ– ηact relationship for three different electroreductionsystems illustrated in Table S1 showthe overpotential derived from each reaction. Upon expanding the electrochemicalpotential terms, we find the general solution neηact = ±TΔS ± neΔχ. Thus, each derivationfinds a relationship consistent with which electrons and adsorbatesinteract.18 They also concluded that the space–chargepotential at the electrode surface was invariant under an appliedoverpotential .9 While this finding points toward the existence of an active mechanismcontrolling the electrochemical performance of electrified interfaces,the theoretical understanding is still in its early stages. Here,we rationalize the mechanistic basis of these observations.In a previous study, we determined that the electrostaticsurfacepotential had a profound influence on the gas reduction kinetics,where a Δχ ≠ 0 relationship is desirable.V0), of a uniform reactive mixture isgiven as the first variational derivative of the Gibbs free energy (G) with respect to the concentration8Θ and gh represents the standard chemical potentialand homogeneous free energy density of the mixture, respectively.The reservoir chemical potential (μres), or cellvoltage (V), acts as the nonequilibrium chemicalpotential of the system.22 The differencebetween the internally controlled potential (μh)and the externally controlled potential (μres) isgiven by the reaction affinity, A = μres – μh, which controls the rate of a reductionreaction.22 This can also be expressedas the activation overpotential8n is the number ofelectrons transferred in the Faradaic reaction. The Fermi energy (EF) describes the electrochemical potential offree electrons, and the shift in the Fermi energy describes the activationoverpotential at each electrode 19e)and the adsorbate (ϕad):16As defined by Bazant, the internal energy, or opencircuit voltage and the distance(r) between the adsorbed species and the first layerof the surface, E⃗ = V/r.However, modulating the adsorbate–electrode distance will resultin an energetically unfavorable distortion of the bonding. Thereforethe shift in the electrostatic surface potential is a result of achange in the coverage of polar adsorbates such that 0, ρ0, and θ represent the dipole moment normal to the surface,vacuum permittivity, density of available adsorption sites, and adsorbatecoverage, respectively.16 A positivelycharged adsorbate is controlled by the voltage  as illustrated in 5 In this work, using a novel computational framework, weare able to predict the ηact – Δχrelationship of an electrode–adsorbate system using appliedelectric fields.It is therefore possible to predictthe origin of the activationoverpotential for adsorbed gas species by combining U) of the reactant and product configurations ofthe rate-limiting step for the reduction reactions detailed in Ce′ or FeFe•) as a function of the appled electricfield  code.28 The ionic cores were describedby PAW potentials , andthe wave functions were expanded in plane waves with an energy cutoffat 520 eV.29 The PBE-generalized gradientapproximation (GGA) was used.31 To describe the Ce4f and Fe 3d electrons, DFT+U was implemented using the Dudarev treatment.33 For Ce 4f electrons, we used Ueff =5 eV following the work of Castleton et al., and for the Fe 3d electrons,we used Ueff = 3 eV following the workof Grau-Crespo et al.35 The surfaces were modeled assymmetric slabs with a thickness of 12 atomic layers and 3 ×3 cell expansion in the lateral directions. The bottom three atomiclayers were fixed during geometry optimizations. The periodic imagesof the slab were separated along the c directionby a vacuum region of about 15 Å. The convergence parametersfor electronic and ionic relaxation were set to 10–7 and 10–4 eV, respectively, to guarantee the sufficientaccuracy of the calculated forces. The dipole correction was usedto decouple the electrostatic interaction between the periodic images.The calculations were performed with a 4 × 4 × 1 MonkhorstPack grid. For gases, electronic calculations were carried out ina 13 × 14 × 15 Å3 box. The standard chemicalpotential was calculated as μo = Eel + ZPE – TS, where the entropyof the gas and surface was calculated using the ASE thermochemistrypackage.36 Electric fields were implementedusing the EFIELD tag.37Spin-polarized density functionaltheory (DFT) calculations werecarried out using the Vienna 2(111) termination was studied because it was previously reportedto be the most stable termination under solid oxide cell operationalconditions.38 Additionally, Feng et al.speculated that the SDC thin film grown on the current collector was(111)-oriented.39 The rate-limiting stepof H2O reduction on CeO2 was reported to beET .20The CeOto beET 1, where2(110) termination reported that the singly chargedCOO3• state was stable during the reduction of CO2.40 However, no stable intermediate states were found when exploringthe reduction of CO2 on the CeO2(111) termination.The rate-limiting step was determined to be CIET, where we calculatedthe free energy of the pristine slab and a neutral 2(111)slab .Studieson the CeO3(100) termination with Fe on the surface layer was reportedto be the most stable termination under operational conditions.26 The IT was reported to be the rate-limitingstep .The LaFeOingstep 1,15 wher


Nd) of cold-water coral skeletons from intermediate depths (1460‒1689 m) to trace circulation changes south of Tasmania during the last glacial period. The key feature of our dataset is a long-term trend towards radiogenic εNd values of ~−4.6 during the Last Glacial Maximum and Heinrich Stadial 1, which are clearly distinct from contemporaneous Southern Ocean εNd of ~−7. When combined with previously published radiocarbon data from the same corals, our results indicate that a unique radiogenic and young water mass was present during this time. This scenario can be explained by a more vigorous Pacific overturning circulation that supported a deeper outflow of Pacific waters, including North Pacific Intermediate Water, through the Tasman Sea.The interoceanic exchange of water masses is modulated by flow through key oceanic choke points in the Drake Passage, the Indonesian Seas, south of Africa, and south of Tasmania. Here, we use the neodymium isotope signature (ε Using cold-water corals, this work identifies a deep outflow of Pacific waters via the Tasman Sea during the last ice age, thus highlighting the role of this area for the interoceanic exchange of water masses on climatic time scales. Eventually, these deep waters reach the North Pacific, which hosts the oldest waters in the open ocean2 due to the absence of local deep convection3. The return of such deep waters to the surface results from diapycnal upwelling (across density surfaces) in the Pacific, which feeds upper ocean return flows to the North Atlantic Ocean4. Both diapycnal fluxes directly into the Pacific thermocline and isopycnal upwelling  in the Southern Ocean contribute to that transport5. The Southern Ocean route is also important for returning old respired carbon to the surface ocean5. Together, these upwelling and return pathways balance the deep export of water from the Atlantic basin within the global overturning circulation system5. The return flows to the Atlantic Ocean typically follow two routes: the cold water route through the Drake Passage6 and the warm water route via the Indonesian Throughflow and the Agulhas Leakage south of Africa4.The exchange of water masses between ocean basins plays a key role in the volume transport and heat budgets of the global overturning circulation. The modern overturning circulation is characterized by strong southward export of deep waters from the North Atlantic into the Southern Ocean, as well as deep water formation in the high-latitude Southern Ocean12 , which dictates predominantly eastward transport of water masses to the south of Tasmania14 , yet the overturning circulation was more active in the Pacific Ocean at the LGM35. One possibility is that changes in the outflow south of Tasmania could have compensated for reductions in the strength of the Indonesian Throughflow, as suggested for centennial to millennial timescales12. However, it has proven challenging to test this idea for the glacial ocean, because tracing changes in the provenance of intermediate and deep water masses is difficult with traditional paleoceanographic tools in this highly dynamic region.Previous research has focused on reconstructing Pleistocene changes in hydrography and transport through the Indonesian SeasNd ~−13)36 and radiogenic Pacific-derived water masses (εNd ~−3 to −4)38. Mixing between these water masses in the ACC forms Circumpolar Deep Water (CDW), which has intermediate Nd isotope compositions (εNd ~−8)40. The Nd isotope composition of upwelling Upper CDW (UCDW) is largely preserved during the transformation to AAIW, and is similar in composition to Lower CDW (LCDW), which results in a relatively uniform vertical distribution of Nd isotopes in the modern Southern Ocean water column42  isotope composition of the aragonitic skeletons of cold-water corals collected from intermediate water depths south of Tasmania Fig.  to test n42 Fig. . HoweverDesmophyllum dianthus that were collected from south of Tasmania (~44°S and ~147°E)  cold-water coral specimens of °E) Fig.  using thh13 Fig. . The AAIm³ refs. ,.  3 towards maximum εNd values of −4.6 ± 0.2 during late MIS 2. Superimposed on the long-term evolution, the corals indicate abrupt centennial to millennial-scale Nd isotope shifts, with deviations of up to ~1.5 εNd units from the overall trend line , to εNd = −7.3 ± 0.2 at 14.8 ka BP, around the end of HS 1. Those less radiogenic values characterize the Antarctic Cold Reversal (ACR) up to the youngest analyzed sample at 12.7 ka BP 40, and with the most proximal seawater data40  measured on modern seawater40. This difference can be attributed to the mixing between northward-flowing AAIW derived from the Southern Ocean and southward-flowing intermediate waters, which deliver more radiogenic Nd from the West Pacific region (εNd ~−5)38 to the Tasman margin13  to the study area49. To evaluate possible changes in local Nd inputs in the past, it is informative to look at lead (Pb) isotopes in the same Tasman corals50. Due to its higher particle reactivity, dissolved Pb has a shorter residence time than Nd in seawater51, such that changes in local input fluxes and sediment-seawater interaction are expected to be more readily reflected in the authigenic seawater-derived Pb isotope composition of the Tasman corals50. Past seawater Pb isotope reconstructions from a subset of the corals spanning ~40 to 12 ka BP show no correspondence with our Nd isotope data  are approximately three εons Fig.  and markons Fig. . Buildin52  of ~3000 years, whereas concurrent B-atm values at the Tasman margin fluctuated around ~1200 years44 55 than our coral data (εNd ~−5) during the late glacial interval  suggests a glacial shoaling of Southern Ocean AAIW in the study area67 70 70 Fig. , are incConsequently, the highly radiogenic Nd isotope signatures observed in late glacial corals from south of Tasmania were probably not the result of changes in the composition and/or depth ranges occupied by LCDW, UCDW, or AAIW. Instead, we consider the advection of radiogenic water masses from the Pacific Ocean north of the Tasman Sea to provide the most likely explanation Fig. . ImportaNd values of ~−3 to −4 in the modern West Pacific38  in the West Pacific from north of the Tasman Sea72 are indistinguishable from those modern values 71, they were associated with much younger ventilation ages  86 alternating with shallower AAIW (higher δ13C)85 at these depths during the last glacial period  Fig.  reveals C84 Fig. . Thus, tiod Fig. . Notablynia Fig. . Hence, 12. Our coral data corroborate this idea and provide evidence that a glacial reorganization of ocean circulation in the Pacific could have involved the export of NPIW via the Tasman Sea  and thorium (Th) for U-series dating44. The Nd fractions of the fossil corals were collected during U-Th separation, whereas the Nd fractions of the three modern corals were collected from the wash fraction during Pb separation50. All Nd fractions were purified using a two-step ion-exchange chromatography protocol for analysis by thermal ionization mass spectrometry (TIMS) as NdO+88.Neodymium isotope analyses were carried out in the MAGIC laboratories at Imperial College London following established protocols143Nd/144Nd = 0.512105 ± 0.000009 . For each analytical session, the instrumental offset was corrected by normalizing the mass-bias corrected 143Nd/144Nd ratios of samples based on the JNdi-1 reference ratio of 143Nd/144Nd = 0.512115 ± 0.00000789. The mass-bias corrected 143Nd/144Nd ratios from one analytical session were subjected to a secondary correction using 142Nd/144Nd90  for JNdi-1. The long-term external reproducibility was monitored with repeat analyses of USGS reference material BCR-2 and our in-house coral reference material during all analytical sessions, yielding 143Nd/144Nd of 0.512637 ± 0.000010  and 0.512336 ± 0.000011 , respectively. These results are in excellent agreement with published results for BCR-2 (0.512637 ± 0.000012)91 and our coral reference material (0.512338 ± 0.000008)92. We report the 2 SD of the coral reference material as the analytical uncertainty for samples unless the internal 2SE is larger in which case the propagated error is reported. Full procedural blanks for combined U-Th/Pb and Nd separation from the aragonitic matrix ranged from 5 to 31 pg Nd, with a mean of 20 pg (n = 12). All Nd isotope results are reported as εNd = ((143Nd/144Ndsample)/(143Nd/144NdCHUR) – 1) × 10,000, where CHUR is the chondritic uniform reservoir93.Long-term TIMS results of 5 and 15 ng loads of JNdi-1 yielded Description of Additional Supplementary FilesSupplementary Data 1