V–3/2, is interpreted with an ionic migration model obeying a ballistic-likevoltage-dependent mobility (BVM) regime of space-charge-limited current.Ionic kinetics effectively modify the long-time electronic current,while the steady-state electronic currents’ behavior is nearlyohmic. Using the ionic dynamic doping model (IDD) for the recoveringcurrent at zero bias (ion diffusion), the ionic mobility is estimatedto be ∼10–6 cm2 V–1 s–1. Our findings suggest that ionic currentsare negligible in comparison to the electronic currents; however,they influence them via changes in the charge density profile.The optoelectronicproperties of halide perovskite materials havefostered their utilization in many applications. Unravelling theirworking mechanisms remains challenging because of their mixed ionic–electronicconductive nature. By registering, with high reproducibility, thelong-time current transients of a set of single-crystal methylammoniumlead tribromide samples, the ion migration process was proved. Samplebiasing experiments (ionic drift), with characteristic times exhibitingvoltage dependence as ∝  The major issues are the overlapping timescales of both ionic and electronic phenomena, giving rise to theso-called hysteresis of halide perovskites,26 and the materials reactivity causing performance degradation. Bothphenomena hinder the interpretation of many experiments because ofsignal instability, lack of reproducibility, and strong dependencyon several parameters, such as the applied voltage (V), polarization history, temperature (T),27 and moisture. Accordingly, for any study onthe electrical response of mixed ionic–electronic halide perovskiteit is essential to (i) identify a state (or regime) where one of thetwo contributions can be negligible, (ii) validate reproducibility,and (iii) check whether material or interface degradation may affectthe conclusions.The ion migration in MAPbBrIn order to explore purely electronic currents,one can eitheranalyze a signal so fast that the ions cannot follow or so slow thata steady-state is attained and the ionic displacement currents nolonger contribute to the total direct-current-mode (DC) flux of chargecarriers. High-frequency perturbation studies are an example of fastsignal where the mobile ions are kept “frozen” in ahomogeneous quasi-equilibrium state. As such, these studies are usefulfor evaluating the electronic phenomena without ionic contributionsto the current or the charge density profile. However, they do notcorrespond to a realistic situation for device operation. In practicalapplications, the total DC currents are affected by the coupled contributionsof electrons and ions to the charge density profile, hence definingthe magnitude and time evolution of the total current.3 SC samples, symmetrically contacted withchromium electrodes. The measured current exhibits exponential riseuntil saturation at the steady state. On the other hand, relaxationunder zero bias for enough time allows reaching equilibrium, whichensures negligible electrostatic potential energy before subsequentbiasing. Thereby, a specific biasing protocol is followed that guaranteessufficient stability and permits high reproducibility. Ion migrationis proved by either electrical field drift (current transient experiments)or ion diffusion (zero-bias impedance spectroscopy). As expected,dissimilar time scales are encountered for ion movement because ofa change in transporting driving force. Experiments are analyzed eitherby means of the ionic dynamic doping model (IDD)21 or the model of ballistic-like voltage-dependent mobility (BVM)28 regime of space-charge-limited currents (SCLCs)accounting for the separate regimes of ion diffusion and ion drift,respectively. Our findings suggest an ionic–electronic couplingin which purely electronic currents are measured that follow the slowkinetics of mobile ion redistribution. Ionic mobility values in theorder of μi ≈ 10–6 cm–2 V–1 s–1 result in a consistent way through our analysis.In thiswork, an experiment is presented that consists of registeringthe long-time current transient response to different biases for aset of MAPbBr3 were prepared following theinverse temperature crystallization(ITC) growth method.10 The precursors MABrand PbBr2 were dissolved in N,N-dimethylformamide (DMF) with an equimolar ratio. The precursorsolution containing a seed crystal was placed in an oil bath whosetemperature was programmatically raised from room temperature to 85°C. Finally, the obtained high-quality MAPbBr3 singlecrystals were polished and then contacted with chromium electrodes.This metal has been selected because it spontaneously oxidizes duringsample preparation giving rise to a thin layer of Cr2O3,29 preserving the contact fromrapid chemical degradation. The thicknesses L ofthe samples ranged from 0.96 to 2.20 mm. The evaporated electrodeshad an active area A of ∼20 mm2.Single-crystals of MAPbBrFigure S1) and X-ray powderdiffraction . The transmissionspectrum was recorded on a Perkins-Elmer Lambda 900 spectrometer,using an unpolarized beam. Polished samples were mounted in frontof an aperture with a diameter of 2 mm. The optical band gap, extractedfrom Tauc plot, shows a value of 2.21 eV. Structural characterizationswere made using a D8 Endeavor diffractometer equipped with a Johanssonnmonochromator. The single-crystal sample was grinded into powder andmeasured in the Bragg–Brentano θ–2θ geometry.The diffractogram reveals the standard cubic space group Pm3m of MAPbBr3 crystals with lattice dimension a = 5.928 Å, and without any trace of secondary phase.The single crystals were characterized by optical transmissionspectroscopy  measurementswere conducted with a PGSTAT302N potentiostat from Metrohm AUTOLAB.Current measurements were carried out under several long-time direct-currentmode (DC) bias conditions in the ranges of ±200 to 0 V. The sampleswere kept in the dark at 300 K with NJ–V characteristics of MAPbBr3 SCsamples are shown in Figure S3. One caninfer from the linearity of the J–V response an ohmic behavior in the selected voltage range,without significant evidence of hysteretic current contribution. Infact, at the used scan rate of 90 mV/s, the electronic current isinstantly observed because of a much faster speed of electrons/holescompared with that of ions.30 However,it is not evident that the J–V responses have necessarily reached the steady-state regime, whichmight require much longer polarization times.The 3 SC sample upon the application (solid dots)and removal (open dots) of step voltages . In this biasing protocol, after each 9600 s interval of positivebias, the crystal relaxes at 0 V for 3000 s. At this zero-bias, asmall current undershoot appears of the order of nA cm–2 with the opposite sign and long decay time . As expected, that negative current seems to exclusivelyobey the ion dynamics.30t after a DC polarization of10 V and fitted to the equivalent circuit of Figure S5. The high-frequency resistance (R) valueswere normalized and shown to follow a trend R ∝ t1/2 , in agreement with the IDD model (see section S2 of the Supporting Information).21In the zero bias, recovering experiment,the IS spectra were measuredas a function of time Je) exponentially risesand finally saturates approaching steady-state values J0 at long times (10–1000 s). We interpret the currentlevel as being originated by electronic (electrons and holes) carriers.However, such long response times suggest that the kinetics of currentsaturation is governed by the slow movement of ionic species, thenentailing a coupling between electronic drift and ionic transport.The J0–V curveis shown in J–V curve  for comparison. From the allometric fitting, a J0 ∝ Vn law is extracted with the power n = 0.96± 0.07, which is more likely due to the occurrence of an ohmicconduction regime for the electronic carriers. It is also worth notingthat fast J–V curves exhibitlower current values than those extracted from the steady-state regime.It is of major importance to study the drift current uponbiasing.In Figure S7.As shown in Figure S8).The exponential rise can be explicitly expressed as Je(t) = J0(1 – exp[−t/τ]) where τindicates the time constant of the ion migration process. Becauseτ accounts for only 63% of the variation, we rather use thetotal characteristic time tt= 4τ, which corresponds to 98% of the transition to the steady-state.Then, by plotting the resulting time constants as a function of theapplied bias at the power of −3/2, a clear tt ∝ V–3/2 relationshipis identified in To quantify the ionic kineticsand estimate ionic transport parametersunder different biases, we explored the shape and magnitude of thecurrent transients. J0 ∝ Vn, with n ∼ 1 and tt ∝ V–3/2. The ohmic behaviorof the saturated current as a function of voltage indicates that,once the steady-state is attained, there is no significant influenceof the actual charge density profile on the electronic currents. Importantly,that ohmic regime is obeyed irrespective of the sample thickness (J0 variation on biasing cycle (Thelong-time currenttransient experiments result in two main trends: hickness 1b. Henceng cycle 1c is cauV = 0 V. By using the IDD model (see Section S2),21 the evolutionof R with time from the IS characterization resultsin an ionic diffusion coefficient as Di = (3.1 ± 0.4) × 10–8 cm2 s–1, which corresponds to ion mobilities of about μi = (1.20 ± 0.15) × 10–6 cm2 V–1 s–1 by using Einstein’srelation (eq S8). Moreover, the crystalelectronic conductivity can be inferred from the linear relationship R ∝ L/A  and results in σe = (20 ± 5) × 10–8 Ω–1 cm–1, also in agreement with previous reports.21 In addition, high electronic mobility (μe) has been measured using laser time-of-flight techniquesin our samples being μe = 17 cm2 V–1 s–1  with a similar procedure as the one previously reported.19 Note therefore the huge difference in mobilitybetween ionic species and electronic carriers. In fact, it makes senseto estimate the order of magnitude of the ionic drift currents fromthe maximum diffusion currents in each short-circuit period of theexperiments . The comparisonis made in J is greater than Ji by more than 2 orders of magnitude. This wouldindicate that ionic currents, although present, should be negligibleas part of the total current measured during the relaxation towardthe steady state , which have to be considered as being mainly dominatedby electronic carriers (J ≃ Je). The difference in current level should also applyfor the respective conductivity.13 However,the measured time constants within the range of 10–1000 s , which suggests the occurrence ofionic currents with a Ji ∝ V3/2 trend. The ballistic SCLC tackles the spacecharge modification when the electrostatic energy is totally convertedinto kinetic energy upon application of an external electric field.Consequently, the drift velocity relates with the electrostatic potentialas vd ∝ φ1/2,producing characteristic behaviors in the current (J ∝ V3/2), the potential versusposition (φ ∝ x4/3), andthe time-of-flight (τtof ∝ V–3/2). This deviates from the ohmic behavior where vd ∝ φ; hence, J ∝ V, φ ∝ x, and τtof ∝ V–1, giving rise to the simpler form τtof = L2/μV. However, the classicballistic regime applies only to vacuum,32 low-temperature,33 or short enough distance34 and time scale conditions.38 Hence, for more typical perovskitesamples at room temperature, one can take the ballistic-like voltage-dependentmobility (BVM)28 regime that assumes instead vd ∝ (dφ/dx)1/2, which results in J ∝ V3/2, φ ∝ x5/3, and τtof ∝ V–3/2. Considering the BVM formalism, the slow kinetics from our experimentswould imply an ionic time-of-flight τtof,i ∝ V–3/2 due to a maximum ionic drift velocity vd,i ∝ V1/2, allowing us to describe consistently the observed ionic time-of-flightvalues as28L is the distance betweenelectrodes, ϵ0 the vacuum permittivity, ϵr the dielectric constant, V0 theonset potential for the BVM-regime, Q the charge,and N an effective homogeneous density of chargecarriers (mostly mobile ions in this case). The τtof,i values calculated from 3 single crystal in conditions similarto those of the experiment. It can be seen that mobile ions with μi ≈ 10–6 cm–2V–1s–1 (from the IDD model) reproduceτtof,i ≈ 103 s (from the experiment)with reasonably low values of charge concentration N ≈ 1011 cm–3 for a single-crystalsample. Here we have assumed unity for the charge Q as it corresponds to fast, bromide-related mobile ionic species.It is also noticeable that the electronic density calculated fromthe conductivity σe = 20 × 10–8 Ω–1 cm–1 results in valuesas low as n = 7 × 1010 cm–3, comparable with the ionic concentration estimated from n ≈ N, consistent with the IDD model outlinedin section S2 in the Supporting Information.However, it should be noted that only ionic species acting as electronicdopants contribute to the increment in electronic conductivity, insuch a way that N might just constitute a part ofthe total mobile ions. In contrast, electronic charge carriers withμe = 17 cm2 V–1 s–1, would require unrealistically large doping density n > 1018 cm–3 for a singlecrystal to relax in the order of ks. The different ways in which thedrift velocity of electrons and ions relate to the voltage can explainthe electronic currents following an ionic relaxation.The behavior of the ionic-related relaxationtimes J0 values show nearlyohmic character, which may indicate that the electronic drift velocityis linear with the field. Then, one can take vd,e ∝ V with kinetics in the rangeof μs, and a final bulk distribution of the electrostatic potentialthat is linear (φ ∝ x). The behaviorof vd,e is evidenced through electronictime-of-flight techniques in Figure S10, and a possible description of the potential is presented in theenergy diagram of Figure S11. The ionic-inducedband bending of the bulky perovskite as φ ∝ x5/3 could favor the charge collection during the relaxationperiod. At steady state, a seemingly ohmic behavior occurs in thebulk and a larger current is reported, possibly due to the IDD effectwhere the bias-induced accumulation of ions toward the interfaceseases the transport.The electronic Our findings indicate that a coupling betweenionic and electroniccurrents exists in such a way that the slower species (ions) conditionthe value of the measured current, which is actually determined bythe faster carriers (electrons/holes). Consequently, ionic movementestablishes the kinetics of the electronic response. Whatever theinterplay mechanism is behind the current transients, it is clearfrom 3 samples were studied using a measurement protocolfocusedon the long time response toward steady-state current in cycles ofbiasing routines. This protocol has proven to be robust and reliableby delivering reproducible responses, regardless of possible ionic-relatedhysteresis and instability issues. The current transient upon biasapplication exhibits exponential increment. The behavior of the steady-stateelectronic drift currents suggests a seemly ohmic conductivity forelectronic charge carriers. However, the most-likely ionic-relatedrelaxation times follow a tt ∝ V–3/2 trend up to the order of hours,which can be modeled with the formalism of the BVM regime of SCLC.Furthermore, we also studied the diffusion relaxation via IS measurements,which allowed us to estimate the ionic mobility by using the IDD model.By combining the BVM and the IDD models, it is suggested that theionic currents are negligible in comparison to the total currentsin our samples, for the measured bias and time ranges. The mobileions, however, influence significantly the long-time electronic transportprocess via the modification of the charge density profile.In summary, symmetrically contacted millimeters-thickMAPbBr


Polymers are described by generic hindered-rotationchains. Anisotropic nonbonded potentials, with strengths comparableto the thermal energy, mimic board-like monomer shapes. Lamellae equilibratedwith Monte Carlo simulations, for a broad range of model parameters,have intralamellar order typical for Σr mesophases:periodically stacked polymers that are mutually registered along theirbackbones. Our mesophase shows registration on both monomer and chainlevels. We calculate scattering patterns and compare with data publishedfor highly ordered sanidic mesophases of two different polymers: polyestersand polypeptoids. Most of the generic structural features that wereidentified in these experiments are present in our model. However,our mesophase has correlations between chains located in differentlamellae and is therefore closer to the crystalline state than theexperimental samples.Board-shaped polymersform sanidic mesophases: assemblies of parallellamellae of stacked polymer backbones separated by disordered sidechains. Sanidics vary significantly with respect to polymer orderinside their lamellae, making them “stepping stones”toward the crystalline state. Therefore, they are potentially interestingfor studying crystallization and technological applications. Buildingon earlier mesoscopic models of the most disordered sanidics Σ The simplest case is translationallyinvariant polymer biaxial nematics Nb,11 where the twodirectors are oriented along and orthogonally to the backbones, respectively translational freedom withineach lamella, because their backbones shift arbitrarily with respectto each other, and there is no long-range positional order along thestacking direction . In “ordered sanidics” Σo, the chain backbones are still not registered, so may shift longitudinally,but are now regularly spaced along their stacking direction. The symmetryof the “rectangular sanidic” Σr mesophaseis the closest to crystalline, exhibiting both long-range order alongthe stacking direction, and also registration of chain backbones.However, the positions of stacks are uncorrelated between neighboringlamellae , at least along the stack normal.12 that sanidics can serve as processingintermediates for manufacturing solid state morphologies with favorableproperties, such as increased charge mobility,6 becausethey offer thermodynamically stable states, where board-like polymersare ordered along multiple directions. Inspecting 15 which brings them even closer to sanidic liquid crystals (LC). Hence,studying sanidic mesophases can offer  insightsinto the properties of crystalline states in board-like polymers.Interest in the structure of sanidic mesophases has recently grown,partially because of organic electronics. It is argued23 where each effective particle represents a large number of atomsor even an entire monomer. Drastic coarse-graining smears local moleculardetails, which are crucial for crystallization. As a consequence,to the best of our knowledge, the various highly ordered arrangementsof board-like polymers that have so far been generated with mesoscopicmodels are not crystals. They are partially ordered, akin to sanidicmesophases.This approximation is used, often implicitly, in molecular simulationsof board-like polymers on device-relevant scales. The reason is thatsuch large-scale simulations must use computationally efficient mesoscopicmodels,22 provide valuable insights. One example is the useof mesoscopicsimulations20 to elucidate how free volumebetween side chains influences intercalation of fullerenes and, subsequently,how such intercalation affects the ordering of conjugated oligomers.These simulations were found to be in agreement with experiments24 on crystalline materials.Nevertheless, simulations of partially ordered lamellarmesophasesr, is particularly interesting. It is challenging, however, to finda balance between simplifying the molecular description as much aspossible and retaining enough detail to capture high structural order.To identifyuniversalities in structure–property relationships,it is frequently desirable for mesoscopic models to have a simplegeneric construction. Taking into account the relevance for approximatestudies of crystalline materials, the development of generic modelsdescribing the most ordered sanidic mesophases, Σr mesophase. We combine a drastically coarse-grained (CG) descriptionof the molecular architecture, where each interaction site representsan entire repeat unit of a board-like polymer with special nonbondedinteractions. These are expressed through potentials that are “soft” and anisotropic. In the spirit ofother models33 of LC, the choice of the anisotropicity of the interactions is “top-down”;it is guided by the symmetries of the sanidic mesophase one wantsto model. Here, we build upon a strategy previously developed19 to simulate biaxial polymer nematics and the least ordered sanidicsΣd and create a simple, generic model for capturinga highly ordered Σr mesophase.Here, we develop a generic model that, despite the significantreduction of chemical details, enables simulations of a Σr mesophaseand qualitatively study the phase behavior of our model across a broadrange of parameter space. We compare the molecular arrangement inour mesophase with structures that have been reported in experimentalstudies8 of highly ordered sanidic mesophases inboard-like polymers from two different families: polyesters3 and polypeptoids.8 In the experiments, the molecular organizations of the mesophaseswere extracted from scattering patterns. Therefore, we discuss thesimilarities and differences between the structure of our mesophaseand the experimentally observed ones via a qualitative comparisonof their scattering patterns.We thoroughlyexplore the structure of our Σ2r mesophases,we advance an approach19 that has been designed to describeless-ordered mesophases in conjugated polymers. The new model is ageneric representation of board-like polymers (not necessary conjugated)and, as such, uses a minimum set of features to describe polymer architecture.Within this generic framework, we expand ideas of symmetry and interactionsdeveloped in the previous studies19 and constructa new nonbonded potential that enables modeling of a highly orderedΣr mesophase.To developa mesoscopic model for Σ2.1n polymers described by ahindered-rotation model. Each polymer consists of N monomers connected by bonds with fixed length b.Our systems contain rj(s), where j = 1, ..., n and s = 1, ..., N indicate thechain and the monomer, respectively. To represent an underlying anisotropic,board-like, repeat unit, each CG site also requires orientationaldegrees of freedom. These are introduced19 by assigningthree orthonormal unit vectors {njk)((s)}  to each monomer (see uj(s) = rj(s + 1) – rj(s) is a vector along the bond connecting the sthand (s + 1) th CG sites, then nj(1)(s)∥uj(s) + uj(s – 1), nj(2)(s)∥uj(s) – uj(s –1), and nj(3)(s) = nj(1)(s) × nj(2)(s). The orientationvectors associated with the end monomers of each chain are definedby adding ghost bonds to ghost monomers, indexed by s = 0 or N + 1, depending on which end of the polymerthey are attached to. The ghost bonds are subjected to the bondedinteractions of the model, but the ghost monomers do not induce anynonbonded interactions.The position of each CG monomer (site) in space is givenby the vector omer see 2, which 0 is themost probablebond angle and kθ is the stiffnesscoefficient. In real materials, bond angles tend to only fluctuatea small amount around their equilibrium values,34 so we set kθ to a generichigh value of 100 kBT. Later, we find that smectic order is part of the structure of ourΣr mesophase. As the most probable bond angle θ0 affects the local bent-shape of molecules, which is knownto correlate with smectic behavior,35 wetest the robustness of the smectic order by varying θ0 in a broad range from 140° to 170°.The bond angles θ between neighboring monomers along eachpolymer chain are controlled by an angular potential:Vϕ in order to promote board-like conformations. We requireminima corresponding to the cis and trans states, at angles of ϕ= 0° and ϕ = ±180°, respectively. The final molecularshapes in a self-assembled structure are determined in combinationwith nonbonded potentials that favor relatively linear arrangements and then present the structure of Vreg.To present the model coherently andfacilitate the discussion ofresults, we first recapitulate the main features of 2.2.1Vlamella servesa specific purpose and is defined as follows:19Viso providesfinite compressibility and depends only on the distance between twoparticles rjl = |rj(s) – rl(m)| via a repulsive isotropic core U(r) ). We define U(r) by1919 the normalizationconstant C depends on a characteristic(constant) reference density of the modeled material and is consideredexplicitly. In our generic simulations, there is no need to specify C, and we simply incorporate C into thedefinition of the coefficients κ, λ, and ζ. Therange of the potential is 2σ, as indicated by the Heavisidefunction Θ(2σ – r).Eachof the three parts of 37 from a generic classical density functional used in field-theoryof polymers. Alternatively, the functional form of U(r) in 19 the length spanned by the side chains of the board-like monomers.Hence, in a disordered melt, each monomer has a characteristic volume v0 = 4πσ3/3. When twomonomers approach in real materials, steric exclusions reduce theallowed conformations of side chains. Let f(r) be the free energy of a pair of monomers separated bydistance r. When monomers are described as singleobjects, they interact via an effective potential that approximatelyequals38 Δf(r) = f(r) – f(r → ∞). Simplifying evenfurther, one can assume38 that Δf(r) ∼ v(r), where v(r) is thevolume of the region where the characteristic volumes v0 of the two monomers overlap. The choice of U(r) in 38 of v(r) on r. To implement Viso, we therefore onlyneed to specify σ. In all cases, we use σ = 2 b. In the following, all lengths will be presented in unitsof σ.Formally, Vbiaxial on rjl is also defined via U(r) (see U(r) as Viso simplifies19 the modeland turns to be sufficient for obtaining a Σr mesophase.In addition, Vbiaxial depends on the Frobeniusproduct bj(s): bl(m) of the biaxial tensors associated with the two interacting sites.The tensor bj(s) is defined asbl(m). 39 for the quadrupolar orientational interactionenergy between two biaxial particles. However, it is sufficient todefine a potential with a global minimum corresponding to a relativeorientation of chains where the planes of their backbones are parallelto each other, forming a biaxial nematic.The dependence of U(r) see 5. UsingVstack, given by 7 of Viso, and is definedas convolution of U(r) with a combinationof second-order Legendre polynomials P2, where r̂jl = rjl/rjl is the unit intermonomer vector. This perturbation creates an interactionthat is minimal when polymers stack face-to-face on top of each otherand maximal when they are situated side by side.7 The combination of Vbiaxial and Vstack creates an anisotropy thatfavors the formation of lamellae with stacks.7 The effect of this synergy is illustrated in Vlamella for two biaxially aligned monomers.This cylindrically symmetric plot is shown as a function of the componentsof the intermonomer vectors rjl parallel (rn(3)) and perpendicular (r⊥) to the n(3) orientation vectors of themonomers  is the same for both monomers). However, dueto competing interactions from neighboring monomers along the chainbackbones, the corrugation created by Vstack is not sufficient to break translational invariance along the backbonedirection. Therefore, we augment Vlamella with a registration potential introduced in the next section.2.2.2Vreg, which provides regularityin monomer spacing along the stacking direction and prevents translationalfreedom along the chain backbone direction, is defined asVreg enhancesthe strength of Vstack in a sphericalshell between the cutoff distances R1 and R2 (where R1 < R2). This creates a zone of lower energy in Vnb  and periodicboundary conditions (PBC) in each direction. Strictly monodispersemolecules in the all-trans conformation are evenly distributed among ny lamellae; the normals ofthe lamellae are parallel to the y-axis. The chainsin each lamella are placed into nz equally spaced stacking layers. Each of them contains thesame number of molecules, nx. Chains lie with their backbones, that is, the nj(1)(s) of the monomers, parallelto the x-axis and stacked along the z-axis (s) is parallel to the z-axis). Importantly, thereis no correlation across different stacking layers regarding the positionof chains along the x-direction. Note that nx, ny, and nz refer to the organization of molecules in the initial setups; thearrangements can change during the simulations. For each system inthe rest of the paper, we quote nx, ny, and nz for the initial configurations.The systems are initially set up in monodomains in boxes with edgelengths V and, therefore, the average densityρ0 = nN/V are fixed.We mostly use ρ0 = 2.05 monomers/σ3, which in isotropic melts corresponds to a packing fraction of monomersof Φ ≈ 8.58, where Φ = ρ0v0. These choices of ρ0 andΦ correspond to rather moderate values among the coarse-graineddensities and packing fractions one finds when representing real polymersusing our drastically coarse-grained approach. For example, usingone single coarse-grained site to represent one repeat unit, we estimatethat for poly(3-hexylthiophene), poly(3-dodecylthiophene), PE12 polyester,3 and Ac-Ndc9-Nte9 polypeptoid,8 ρ0 ≈ 1.6, 8.6, 3.4, and6.5, respectively. The corresponding packing fractions are Φ≈ 6.8, 36, 14, and 28. In Section 1 of the Supporting Information, we explain how these estimationsare made. Other choices of ρ0 are considered in r mesophase. The temperature T enters implicitly via the coefficients governing the strengthof the potentials  simulations are usedto equilibrate the systems and sample the configuration space. Weuse two ensembles: standard canonical and isostress. In both ensembles,the volume 47 and “flip”48  with 80% and 20% probability, respectively. The reptationmove is modified to account for the presence of ghost bonds, as describedpreviously.19Two MC moves are employed forsimulations in the canonical ensemble:reptationFlip moves are performeddifferently depending on whether a realor ghost monomer is randomly selected. If a real monomer is chosen,it is rotated by a random angle (from a uniform distribution between−180° and 180°) around a local axis joining the positionsof the previous and next monomers of the chain (even if one of theseis a ghost). If a ghost monomer is chosen, its connecting ghost bondis rotated by a random angle around the axis defined by the bond immediatelynext to it.53 (VSCV) MC move with 0.1% probability.This move optimizes the boxdimensions Lα to make them commensuratewith the natural geometry of the lamellar structure, under the constraintof constant volume V . We emphasize, however, that the movemaintains an orthogonal shape of the box and does not optimize theangles between its edges . Theapplication of the VSCV algorithm has been described in detail previously7 for a similar system. Proposed new values for Lα are chosen randomly, and the first realmonomer  of each chain undergoes an affine transformationso that its coordinates maintain their original proportions relativeto the box lengths Lα. The othermonomers are translated to preserve internal structures  and orientations that the chains hadimmediately before the move. Here, the maximum allowed changes to Ly and Lz are ±0.05; Lx is then determined by the constant volume constraint.Simulations in the isostress ensemble also includea third, variable-shape-constant-volumen ≤400. Simulations of larger systems are performed in the standard canonicalensemble. In this case, Lα are setto optimum values commensurate with periodicities (lamellar and stackingspacings) estimated from isostress simulations of smaller systems. For each of these smaller systems, we performeight simulations starting from configurations with different initialbox dimensions Lα. The runs continueuntil the dimensions of all eight simulations converge to similarvalues of Lα.Because the VSCV move is computationally costly, we use the isostressensemble only for small systems where 33.1Vnb are sufficiently high, our model forms aΣr mesophasefor all chain lengths studied  is used to investigate the generalstructure of the mesophase. Highly asymmetrical boxes, which are longin one dimension α = x, y,or z, and short in the other two, are used to investigatecorrelation functions along each direction. Specifically, we use {Lx, Ly, Lz} = {133.89, 7.12, 7.87}, {16.74, 56.96, 7.87}, and {16.74, 7.12,62.94}. Each box contains n = 960 chains, with {nx, ny, nz} = {16, 4, 15}, {2, 32, 15}, and {2, 4, 120}, respectively. We studyconfigurations prepared with 16 independent simulations (repeats).To facilitate structural analysis,we equilibrate Σy- and z-axis, respectively.In such 3D configurations, we quantify order along each directionα by calculating 1D pair-correlation functions g(rα) defined asm ≠ s for l = j. Furthermore,·rjl;α are projections of distance vectors betweenmonomers onto the direction α, and ñα is the number of chains contributing to the calculationof g(rα). ρ̃α = (ñα –1)N/2Lα is a normalizationfactor. g(rx) probes correlations along the chain backbone direction, where ñx stands for the numberof chains located in the same lamella. For g(ry), which probes order in thedirection orthogonal to the lamellae, ñy is the total number of chains in the system,that is, ñy = n. Finally, g(rz) quantifies correlations along the stacking direction z; in this case, ñz is the number of chains in the same stack. For g(rx) and g(rz), the angular bracketsin g(ry), theangular brackets represent canonical averaging over all equilibratedconfigurations with the same size and shape. We obtain 1D pair-correlationfunctions as histograms with a bin size of 0.5 for g(rx) and 0.01 for g(ry) and g(rz).A lamellar arrangement is evident in g(ry) presented in dlam = 1.78; this value changes as the model parameters are varied.The xz-plane, chains form stacksanalogous to a “quasi-2D” Smectic A (SmA). The periodicshape of g(rx) in Lx accommodating 16 chain backbones) is consistent with SmA orderand suggests that correlations along the backbone direction do notdecay with distance within each lamella, at least for the consideredsystem sizes.Translational invariance is also broken withineach lamella, asdemonstrated by r mesophases: periodicity alongthe stacking direction. This periodicity is quantified by the g(rz) shownin dst = 0.525, but their heights decay with distance,suggesting that only quasi long-range order55 (QLRO) is present along the stacking direction. The rate of decayalso increases with Lz, when comparing simulation boxes of different shapes, as expected56 for QLRO (see Section 2 of the Supporting Information).Apart from lamellae and chain registration, xy-plane. The tilt direction is generallyconsistent across the simulation box, but tilt reversals sometimesoccur, producing zigzags. These stem from metastability: multipledomains frequently form during the early stages of equilibration,particularly when the initially developed tilt angle cannot be maintainedacross the whole simulation box due to the PBC. It is observed thatthe tilt angles adjust during the simulations to reduce discontinuities.Interestingly, the topview in r mesophase of our model is wellstructured on the level of polymer chains, it has substantial disorderon the monomer scale in some directions. We quantify monomer packingusing the 3D correlation function:c by binningthe distances between all pairs of monomers in a configuration intoa histogram, with bin size 0.05 in the x and z directions and 0.1 in the y direction.Averaging takes place over all configurations with the same tilt angle.Although the Σc that correspondsto intralamellar correlations, that is, ry = 0. It demonstrates that the monomers locally forman analogue of a 2D centered rectangular lattice. Further away, theircorrelations are washed out by thermal fluctuations. In c corresponding to monomers found in neighboringlamellae, that is, ry = dlam. Here, only a faint lattice canbe discerned, suggesting weak xz-positional correlationsbetween monomers in different lamellae. A broad vertical dark stripe,indicating higher probability, appears slightly to the right of theorigin. It corresponds to the SmC shift of chain backbones along the x direction between subsequent lamellae. When we averageover configurations with different tilt angles, we observe that interlamellarcorrelations are washed out, confirming that they are indeed veryweak.Vreg, see Section 3 of the Supporting Information for details.The intralamellar SmA order forms very quickly in our simulations,and there is evidence that there is a strong energetic contributionto its appearance, although there may also be entropic effects. Theorigin of the SmC order is less clear, because we were not able tofind clear evidence of an energetic benefit. Further discussion canbe found in Section 4 of the Supporting Information.The intralamellar monomer-levellattice has a strong energeticdriver based on minimizing r mesophase enables a back-of-the-envelope calculation. Thevolumeper chain in the Σr mesophase is dstdlam[(N – 1)b̃ + Δ]. Here, b̃ = b sin(θ/2) and Δis the intralamellar “gap” between SmA stacks. Hence,(N – 1)b̃ + Δapproximates the characteristic length of one SmA stack. Of course,this simple estimate neglects conformational fluctuations , as well as possible chain backfolding,and cross-lamellar bridging. Considering that the volume per chainalso equals N/ρ0, we obtainN. This requirement holds when:r mesophase maintains realistically smallgaps is rather narrow. We refer to a range of densities because dst and dlam arenot constant, but functions of ρ0 (and N for short chains). Second, they guide the choice of R2. In a stable sanidic mesophase, lamellae must interact.Therefore, the range of our potential provides an upper boundary for dlam, that is, dlam ≤ 2. Assuming that dst ≤ R2, we obtain from R2 ≥1/2ρ0b̃. Thus, our basic choicesof density ρ0 = 2.05 and θ = 150° correspondto R2 ≥ 0.5. Starting from thisvalue, we increased R2 in our exploratoryscans and found that R2 = 0.65 led toclear-cut Σr structures.Knowing the structure of our Σ3.2r mesophaseagainst varying the strengths of the nonbonded potentials, chain length N, preferred bond angle θ0, and averagedensity ρ0.Here, weconsider the robustness of the ΣViso to κ= 0.874 and vary the other coefficients λ, ζ, and η.The coefficients λ and ζ are allowed to change withina range that maintains a positive potential for lamellar order Vlamella > 0. This condition ensures thatβVnb is always repulsive when monomerscome close,that is, rjl ≃ 0 in the isostress ensemble. To construct the phase diagram, we combinevisual inspection with several quantitative indicators. The transitionfrom an isotropic melt to biaxial nematic Nb is identified using uniaxial and biaxial order parameters, S and B, calculated in a standard way57 (see Section 5.1 of the Supporting Information). We consider that Nb is formed when both S and B are ≥0.5. The transition into a Σd disorderedlamellar mesophase is characterized by the occurrence of regular peakscorresponding to lamellar spacing in g(ry), the 1D correlation function introducedin To investigate the effect of thenonbonded potentials, we construct a phase diagram. We fix the strengthof the isotropic repulsion  ≃ 0 see 2.2. All d to our highlyordered Σr mesophase is the appearanceof SmA order within each lamella, which we quantify using a standard-orderparameter59 Λ (see Section 5.2 of the Supporting Information). Forthe system sizes considered here, we find that Λ > 0.7 isastrong indicator of SmA order; visual corroboration is required whenΛ ≈ 0.7. The presence of cross-lamellar SmC is mainlyjudged by eye, although a method for quantification is discussed in Section 5.3 of the Supporting Information.A maincharacteristic of the transition from ΣNb,19 a Σd sanidic mesophase,7 and our Σr sanidic mesophase. We emphasizethat this diagram is qualitative because of the limited amount ofrepeats and no systematic study into finite size effects. Moreover,we use a compressible model within a statistical ensemble where twoextensive variables, total number of particles and system volume,are fixed. Therefore, the identification of phase boundaries is complicatedby the possibility of phase coexistence.60 Nevertheless, r mesophase over a broad range of parameters. Overall, Σr is encouraged when λ, ζ, and η are high.Interestingly, however, a Σr mesophase also appearswhen ζ = 0, provided that λ and η are sufficientlylarge. Although no upper phase boundary for Σr isidentified, we note that high values of η can prohibitivelyslow down equilibration.Vnb is mainly responsible for an individual featureof structuralorder, we emphasize that there is a cooperativity between them . Therefore, it is not straightforwardto develop simple guidelines for choosing values λ, ζ,or η that promote specific mesophases, by considering only theisolated effects of the interactions that are conjugated to each ofthese parameters. Nevertheless, we provide some qualitative analyticalestimations in Section 6 of the Supporting Information.Although each of the four components of 0 = 140–170°, despiteexpectations that straighter chains might produce an interlamellarSmA rather than SmC. For example, in another study,35 hard zigzag molecules were unable to form SmC for θ0 > 154° .Changing other system parameters also preserves the characteristicstructural features of our mesophase. In particular, we do not observeany qualitative changes when the most probable bond angle is variedwithin the range θ63 For board-like molecules, an odd–even effect has been recentlyreported in simulations of nonlamellar oligo-thiophenes, where onlyeven-numbered chains formed SmC mesophases.64 Therefore, we perform simulations for consecutive chain lengths, N = 13, 14, 15, and 16, with all other parameters fixed. For our model,we observe no odd–even effect: all aforementioned chain lengthsproduce mesophases with the same symmetries as described in In general, chain length parity can affect smectic behavior.r mesophaseis qualitatively insensitive even to pronounced variations in chainlength; namely, when we compare mesophases composed of molecules with N = 16, 24, and 32. Of course, the largest of these chains, N = 32, is only about five times longer than the persistencelength of the ideal chain. It is plausible that much longer chainswill destabilize (at least) some of the features of our Σr order, for example, because of increased conformational “defects”.Exploring this issue requires additional MC moves that enable equilibrationof long polymers, such as rebridging66 and configurationalbias67 algorithms.We findthat the structure of our Σr mesophase exists in a limited range ofdensities. For three different chain lengths, N =16, 24, and 32, we consider the same point in the parameter space and vary the average system densityρ0. For this purpose, simulations are performed inthe isostress ensemble, with a constant number of chains n = 270, but different volumes .Finally, we checkthe qualitative prediction, r mesophaseas a function of ρ0 and N. Indeed,for each N, the Σr mesophase isstable in a rather limited range of densities, marked as the “Σr” region. Outside this range, in regions “A”and “B”, some of the Σr features startto disappear.Vreg. In principle, the Σr mesophase may actually extend to higher densities: the VSCVmove optimizes only the lengths Lα while maintaining the orthogonal shape of the simulation box. Ifthe box angles were also allowed to adjust, the system might be ableto maintain Δ > 0 until somewhat higher densities by tiltingthe lamellae. Δ < 0 occurs at slightly lower densities as N increases, in agreement with In region “A”, gaps between stacks are eliminatedand chain ends overlap along the backbone direction .In region “B”, gaps are large due to low density.As Δ increases, more disorder around chain ends and bridgingbetween lamellae occur. We set the boundary of the “B”region to densities where chain ends start to bridge; an example isshown in the lower inset of r mesophase is robustagainst varying parameters such as nonbonded potential strengths,chain length, and bond angle. As expected from r mesophase formed in our softmodel is rather limited.In summary,we find that our Σ3.3r mesophasewith two highly ordered sanidics that have been reported in experiments.8 In these studies, the molecular organizations of the mesophaseswere determined from scattering measurements. In our particle-basedsimulations, molecular organizations are known without the need toperform scattering calculations, because monomer coordinates are explicitlyavailable. However, calculating scattering patterns and juxtaposingthem with experimental data offers an illustrative framework for performingstructural comparisons. Because of the drastic coarse-graining usedin our model, we know a priori that our scattering patterns cannotquantitatively reproduce properties sensitive to atomistic details,such as atomic form factors. Furthermore, in this work, our modelis not tailored to represent a specific material. Therefore, we cannotdirectly compare absolute length scales associated with scatteringpeaks in our simulations and experiments. For the same reason, theratios of lengths characterizing different geometric features of mesophasesin our generic model, such as stacking distance, lamellar spacing,and smectic period, can differ quantitatively from the ratios foundin a real material. Hence, the scattering peaks in our patterns canappear at somewhat different positions relative to each other thanin an actual scattering pattern. The goal of our discussion is toillustrate structural similarities and differences between simulationsand experiments through the presence (or absence) of scattering signalsthat are linked to certain generic features of molecular organizationin the mesophases.We now compare the structure of our ΣWe calculate scattering from sanidic monodomains,equilibrated and oriented as described in Lx, Ly, Lz} = {25.10, 21.36, 20.98}, each containing n = 1440 chains of length N = 16 . 2D scattering functions are calculated usingx, y, and z components of the scattering vector q. The components comply with the PBC, thatis, qα = 2πm/Lα , where m is an integer. Angular brackets indicate averaging over differentconfigurations and repeats. –1.We consider monodomains accommodated in approximately cubic simulationboxes, {S(q), where q = |q|, we first calculate the complete3D scattering function:q comply with the PBC, as describedbefore. S(q) is obtained by sphericallyaveragingthe data for S(q) andis presented in q for which S(q) is available.To obtain powder diffractionspectra 8 The first study by Ebert et al.3 reported a Σr mesophase in arigid-rod polyester comprising aromatic backbones and alkyl side-chains,that is, the PE12 sample.3 To obtain 2Dscattering patterns, they used flow to prepare macroscopic monodomainsoriented along well-defined directions and, in this sense, their samplesare analogous to the idealized set up of monodomains used in our simulations.Ebert et al.3 distilled the key featuresof their scattering data into sketches, which they then used to discussthe basic characteristics of molecular arrangements in their sanidicmesophases. The generic nature of these sketches makes them particularlysuitable for comparison with the scattering patterns from our genericmodel. In To compare our scattering patterns with experiments, we focus ontwo studies.8 reporteda sanidic mesophase involving polypeptoid diblock copolymers. 1D X-rayscattering patterns were obtained for their multidomain samples, andthe authors inferred the structure of the mesophase from careful analysisof this data. Greer et al.8 did not explicitlymention that their sanidic mesophase is Σr, but webelieve the structural features they found indicate that this is thecase. In 9-Nte9 at 50 °C); the original data are available in FigureS5 of the Supporting Information of ref , first and higher order peaks are evident. To avoid crowded2D scattering patterns, we label only one representative primary peakin each group of reflections; in 1D patterns, secondary and tertiaryreflections are indicated by the same label as the primary peak butwith primes, for example, “1′” and “1′′”.Compared to the primary peak “1”, the intensities ofthe secondary and tertiary reflections in the 1D patterns of Greeret al.8 are weaker than in our case; thisdifference might stem from the multidomain structure of the experimentalsamples.Intense narrow reflections, labeled “1”,appear in 8 byregular stacking were also identified in the scattering patterns ofEbert et al.3 and Greer et al.8  Thesescattering features could be present at q-valuesthat were not accessed in the experiments. (ii) The samples were preparedunder nonequilibrium conditions and flow might have inhibited smecticorder.In our mesophase, chains are organized within each lamella intoSmA layers see 3.1, whic8 in at least one of the two experimental systems. They arise fromchain-level SmC registration between molecules in different lamellaethree mesophases, biaxial nematic and two sanidics, that span almostthe entire order–disorder scale between crystalline and amorphousstates. This is achieved in a modular way, simply by activating termsin a series defining a phenomenological nonbonded potential.In our approach, polymers are representedby a hindered-rotation-chainmodel, where variations of angular and torsional degrees of freedomare subjected to a generic energy landscape. Nonbonded interactionsbetween coarse-grained monomers are described by anisotropic potentialsthat are “soft”, namely, their strength is comparableto the thermal energy. To define them, we built upon generic anisotropic“force fields” developed previously for modeling biaxialnematicr mesophasein our simulations with structures that have been experimentally determined8 for two highly ordered sanidic mesophases. The experimental studiesestablished the structures of these mesophases on the basis of scatteringdata. Therefore, we discussed similarities and differences betweenthe structures of sanidic mesophases in our simulations and the twoexperiments using their scattering patterns as a framework. The generalhallmarks of sanidic Σr order are present in allthree cases. However, there are differences in the way polymers registeralong the backbone axis. In the two experiments, backbone registrationwithin each separate lamella occurred either only on the level ofmonomers3 or only on the level of entirechains8 (leading to smectic-like orderwithin each lamella). The experiments reported no evidence that theorder along the direction of polymer backbone is correlated acrossneighboring lamellae. In our simulations, in contrast, backbones registerwithin each stack on both a monomer and chain level . Moreover, we find a regular (smectic C) couplingof chain registration between different lamellae. Therefore, the Σr mesophase generated by our model is more ordered and closerto crystalline in structure than the mesophases reported in the twoaforementioned experiments.We compared the structure of the Σ12 Second, our highly ordered Σr mesophase offersan approximation to crystalline states of board-like polymers thatcan be simulated at experimentally relevant length scales. In thiswork, we did not apply our model to any questions related to crystallizationphenomena, but instead outline a few representative research directionsfor future studies.The model developed here is interestingfor two reasons. First,sanidic materials are themselves useful for technological applications,in particular in organic electronics, where they are considered asprocessing intermediates for manufacturing solid state morphologieswith favorable electronic properties.72 We believe, however, that modelingthe equilibrium structure of Σr mesophases whilevarying molecular features, such as chain topology, polydispersity,or deviations from molecular planarity73 (twisting), can help to answer certain questions. These includeunderstanding the effects of altering these features on the generaltendency of materials to crystallize, and the likelihood of formingconformational defects74 within crystallites.One might wonder whether models with softpotentials, which byconstruction violate kinetic constraints imposed by noncrossabilityof chains in real materials, are at all applicable to polymer crystals,which are largely controlled by kinetic effects.75 Combining the expanded modelwith pseudodynamical Monte Carlo schemes that account for dynamicasymmetries between components76 wouldallow qualitative investigation into the interplay between microphaseseparation and crystallization. It is even worth applying such pseudodynamicalstochastic algorithms to homopolymer melts. In this case, it is interestingto explore whether some mesoscopic features of the developing Σr grains, such as grain size, grain shape, chain folding, andbridging, bear similarities to actual semicrystalline materials.Our model can be expanded to multicomponent polymers, where blockcopolymers with crystallizing blocks are of particular interest.


The traditional cultivar “Crvenka” confirmed the best tolerance to a drought stress condition, presenting higher photosynthetic efficiency, higher leaf water content, higher levels of chlorophyll content and lower lipid peroxidation with greater membrane stability. The commercial cultivar “Golden Delicious Reinders” showed decreased water content in leaves, increased lipid peroxidation levels and photoinhibition. Considering all results, the commercial cultivar “Golden Delicious Reinders” was adversely affected by drought, while traditional cultivars exhibited better tolerance to drought stress.Genotype-dependent responses of apples to drought stress were evaluated between commercial and traditional apple cultivars. The results indicate different mechanisms of tolerance to investigated drought stress conditions. Chlorophyll fluorescence induction (OJIP) parameters, chlorophyll and carotenoid content, malondialdehyde (MDA), hydrogen peroxide (H For a better understanding of the defense mechanisms of investigated cultivars, beside photosynthetic efficiency, we studied lipid peroxidation, proline, phenol, chlorophyll and water content in the leaves. To the best of our knowledge, the drought stress tolerance of these traditional apples has not been previously studied.In recent years, numerous studies have been published about the effects of global climate change on ecosystems, and it is predicted that climate change will cause extreme temperatures and droughts. Drought has become a major abiotic stress factor that adversely effects plant growth, survival and limits crop productivity , causingll death ,8. Drougll death ,10. Accoll death , the negll death ,13,14. Sll death ,16,17. Rll death  and somell death  alleviathe world . It is phe world ; therefohe world . In prevhe world , more fihe world , and thehe world  comparedt stress ,27,28. I0/RC), electron transport flux per active reaction center (ET0/RC) and dissipation energy per active reaction center (DI0/RC) at 7 and 12 DAS (day after stress) between control and drought-stressed plants were observed in cultivar “Golden Delicious Reinders” (0/RC)  (0/RC)  (0/RC)   was evaluated through analyzing several fluorescence parameters. Significant increase in absorption per active reaction center (ABS/RC), trapped energy flux per active reaction center  B, electr plants) C, dissip plants) D. Traditat 7 DAS A–D.v/Fm) and performance index on absorption basis (PIABS) (v/Fm)  (ABS)  (0/ET0) did not change significantly after 7 days of drought in all cultivars. After 12 days of drought treatment, the value of (RE0/ET0) in “Golden Delicious Reinders” was increased, while in cultivar “Dugara” it was decreased. The values of this parameter did not change in cultivar “Crvenka” even after 12 DAS (2B). However, the results showed that the highest values of (PIABS) were recorded in cultivar “Crvenka” after 7 days of drought (4.35) and 12 days of drought (4.05)  A,C. Decr plants) A, perfor plants) C. There  plants) A,C. Valut (4.05) C. SimilaCrvenka” D.The fluorescent transient OJIP curves represent a plot of fluorescence data for each cultivar plotted on logarithmic time scale at 12 days of drought treatment. They revealed distinct differences between cultivars and treatments. In drought treatments, the change of the OJIP curve of traditional apple cultivars “Crvenka” and “Dugara” was less visible than that commercial cultivar “Golden Delicious Reinders”. Our results showed that drought treated plants of the “Golden Delicious Reinders” cultivar had higher fluorescence intensity at the J step (2 ms) and I step, compared to traditional cultivars A,D,G, reThe concentration of total chlorophyll content remained unchanged in drought-stressed leaves of all cultivars at 7 DAS compared to control A. All ap2O2 content after 7 and 12 DAS compared to control was detected in “Golden Delicious Reinders” and “Dugara” cultivars (2O2 in drought-stressed plants compared to control for 30% only after 12 DAS (2O2 (3.55 µmol/g FW and 5.6 µmol/g FW).Lipid peroxidation was determined by evaluating the malondialdehyde (MDA) content in leaf tissues. In our study, the MDA significantly increased only at 12 DAS in cultivars “Golden Delicious Reinders” and “Dugara”, while the MDA content in the leaves of cultivar “Crvenka” remained unchanged A. The hiultivars B. “Crvenr 12 DAS B. After After 7 days of drought, the contents of proline remained unchanged in all cultivars, as compared with the corresponding controls C. The coThere were no significant differences in leaf water content between cultivars under control and drought condition at 7 DAS. The water content (%) in the leaves of the studied apple cultivars decreased significantly only in cultivar “Golden Delicious Reinders” after 12 day of drought treatment  .Some research has been conducted on the fruit quality characterization of traditional cultivars in Croatia and Balkan Region ,30. The A and beyond PQH2 [OsNAC10-improved drought-stress tolerance) compared to non-transgenic under drought condition [0/RC), electron transport (ET0/RC) and dissipation (DI0/RC) in the drought-stressed plants of “Golden Delicious Reinders” indicate inactivation of a certain part of RCs, due to inactivation of OEC, as well as the transformation of active RCs to silent [v/Fm. Similar behaviour of these parameters under drought-stressed grape leaves has been reported by Wang et al. [0/RC and TR0/RC and a large decrease in PIABS in drought-sensitive potato cultivars subjected to drought. In traditional cultivar “Crvenka” the values of these parameters remained unchanged under the influence of drought which indicated that the photosynthetic apparatus of cultivar “Crvenka”, with the highest values of PIABS, was the most tolerant to investigated drought condition. PItotal was used to measure the performance up to the reduction of PSI end electron acceptors and its values represent the energy flow efficiency of the photosynthetic transport chain beyond PS II [ABS and the probability that an electron can move from reduced intersystem electron acceptors to PSI end electron acceptors (RE0/ET0). There was no difference in RE0/ET0 between drought-stressed and control plants in tolerant cultivar “Crvenka”, indicating that the electron flow was proceeding normally from PQH2 to the PSI end electron acceptors. The highest values of parameter PItotal also confirmed the better performance of PSI acceptor side in traditional cultivar “Crvenka” as compared to “Dugara” and “Golden Delicious Reinders” under drought stress. Increase of RE0/ET0 in the drought treatment in “Golden Delicious Reinders” is probably due to decrease in redox balance of PSII electron acceptors because of lower PSII activity. The parameter RE0/ET0 decreased by drought only in traditional cultivar “Dugara”. According to Schansker et al. [0/ET0 indicated that drought had a negative effect on electron flow at the acceptor side of PSI caused by an inactivation of ferredoxin-NADP+-reductase. The lower value of these parameter in “Dugara” indicate unsuitable electron transfer between two photosystems and that the acceptor side of PS I might be inhibited. This was reflected in the lower level of the PI  in this cultivar. The effects of drought stress observed in parameters PI  and RE0/ET0 are in accordance with a previous report of Jia et al. [v/Fm) known as maximum quantum yield of PS II represent the efficiency of PSII primary photochemistry. Decreased value of that parameter under 0.75 indicates that PS II has been damaged [v/Fm values decreased in the sensitive cultivars of olive, whereas the tolerant cultivar did not show any decrease in Fv/Fm. In this study, we found that Fv/Fm recorded values of all three cultivar were in the range of 0.77–0.85. Despite the fact that the OJIP curves obviously showed damage to the OEC complex and lower energetic connectivity between PS II units of the “Golden Delicious Reinders”, the values of Fv/Fm, although they were significantly decreased, were not below 0.75. However, parameter Fv/Fm is a well-known indicator of stress; this result indicates that drought stress has relatively little effect on the parameter Fv/Fm in this study. Previous reports also suggest that drought has relatively slight effect on the parameter Fv/Fm; thus, it is not a sensitive parameter for analysing drought stress [Based on the chlorophyll fluorescence parameters, we investigated and compared the changes in fluorescence characteristics of PS II of selected cultivars under drought stress. The present study showed significant differences in leaf photochemistry of investigated cultivars, by analysis of OJIP kinetics. Our results showed that drought treated plants of “Golden Delicious Reinders” have higher fluorescence intensity at the J phase and I phase compared to “Dugara” and “Crvenka”, indicating a stronger decline and inhibition in electron transport beyond the Qond PQH2 ,33. Simuond PQH2 , the L bond PQH2 . Data onondition . When plondition . In thisondition  and sunfondition  when expo silent . We suppg et al. . Boguszeg et al.  noticed nd PS II . This par et al. , reduceda et al.  in droug damaged . Decreas damaged  who showt stress ,47.ABS and PItotal values of the commercial cultivar “Golden Delicious Reinders” were mainly due to an inactivation of PS II RCs, a higher increase in TR0/RC and thereby ABS/RC, ET0/RC and DI0/RC. While in cultivar “Dugara”, the most sensitive components of the photosynthetic electron transport chain seemed to be the probability that an electron from the intersystem electron carriers is transferred to reduce end electron acceptors at the PSI acceptor side RE0/ET0. The highest photosynthetic activity in “Crvenka” was due to the highest amount of active PSII reaction centers and stable absorption flux. Our results indicated that the photosynthetic apparatus of traditional cultivar “Crvenka” was more tolerant to drought stress than “Golden Delicious Reinders” and “Dugara”.Based on the obtained results we supposed that after 12 days of drought stress, decreasing trends of PIChlorophylls as the main photosynthetic pigments in plant leaves reflect the photosynthetic capacity of leaves and overall plant vitality. The chlorophyll content of plant leaves is considered as a good stress indicator for evaluating tolerance levels of various crops to different abiotic stresses, including drought stress . Previou2O2, which damage the membrane lipids [2O2 content. The significant increase in MDA and H2O2 contents with drought stress progressed in the two apple cultivars “Golden Delicious Reinders” and “Dugara” suggested that drought stress caused oxidative damages in both cultivars. The intensity of H2O2, and consequently MDA, increased with the intensity of stress. Møller et al. [2O2 and earlier significant changes of H2O2 compared to the traditional cultivar “Dugara”, suggesting that “Dugara” possessed better drought tolerance. Previous studies also showed an increased level of MDA and H2O2 in olive and poplar plants under drought stress [2O2 decreased at 12 day of drought. The finding of lower content of H2O2 under drought stress was in accordance with previous report of Umar and Shaheed-Siddiqui [2O2 production in drought stress might be due to the activation of antioxidant enzyme activities, particularly CAT, which detoxify H2O2 and reduces H2O2 accumulation.Decreased PS II activity under drought is connected with oxidative stress and cell membrane injury caused by increased lipid peroxidation . MDA is e lipids . Our resr et al.  suggest t stress ,59. ContSiddiqui . They prWater content in leaves (WC) is an indicator of water status in plants used for drought tolerance estimation . In respProline is an important organic solute that is accumulated and increased in plants under drought conditions , acting Our study concludes that specific differences in physiological and biochemical responses to drought stress among cultivars existed. Among the investigated cultivars, the more drought tolerant characteristic was observed in the traditional cultivar “Crvenka”. Higher photosynthetic efficiency, higher content of chlorophyll and greater membrane stability indicate that traditional cultivar “Crvenka” has the highest drought tolerance, while in contrast, the commercial cultivar “Golden Delicious Reinders” was the most sensitive in the investigated condition. Good quality traits of “Crvenka”  and goodMalus domestica Borkh) cultivars were used in the experiment . “Golden Delicious Reinders” is a widespread and very common commercial cultivar grown in intensive apple orchard systems. “Crvenka” and “Dugara” are traditional cultivars, originating from continental Croatia, grown mostly in small orchards. In the Balkan region, there are also many different names amongst those apple cultivars with the same genetic origin. One-year-old apple trees, grafted into rootstock M9, were grown in 25 L pots (one plant per pot) filled with soil . All the potted plants were regularly irrigated for 3 months under greenhouse conditions before drought stress was imposed. In this experiment drought stress was imposed by withdrawing irrigation. Five plants of each cultivar were under water-deficit (non-irrigated plants) and used as drought treatment, while five plants were optimally irrigated every day (2 L of water per day) and used as a control. The greenhouse’s mean day/night temperatures were 28 °C/20 °C at 7 DAS (day after stress) and 25 °C/15 °C at 12 DAS (day after stress), mean relative air humidity was 60/80% and 70/80%. The irradiance in the greenhouse was natural.The experiment was conducted in the greenhouse of Agricultural Institute Osijek, Croatia, in the summer (July 2019). Three apple  before the midday depression of photosynthesis. Chlorophyll a fluorescence was measured by a Handy-PEA fluorimeter , which measures changes in chlorophyll a fluorescence during 10 μs to 1 s. Before measurement, all of the leaves were dark adapted using special leaf clips. After a dark-adapted period (30 min), leaves were exposed to a saturating red light pulses  m–2 s–1) which generate a fast fluorescence rise from the initial fluorescence intensity (F0) to a maximal intensity (Fm). Fluorescence intensity was measured at 50 µs, when all PS II RCs are open (the O step) (F0); 100 µs; 300 µs; 2 ms (FJ) (the J step); 30 ms (FI) (the I step) and 1 s maximal intensity when all PSII RCs are closed (Fm = P step). Recorded fluorescence values were used to calculate various parameters of the JIP test. The JIP test and analysis explore changes in photosystem II (PSII) photochemical performance, and it has been widely used as a measure of plants sensitivity to different stresses. It provides information about absorbed light energy as well as information on photosynthetic apparatus structure and function [0/RC), electron transport flux (ET0/RC), dissipated energy flux (DI0/RC), the efficiency with which an electron can move from the reduced intersystem electron acceptors to the PS I end electron acceptors (RE0/ET0), performance index (PIABS), performance index for energy conservation from exciton to the reduction of PSI end acceptors  and maximum quantum yield of primary photochemistry . Calculations are shown in The measurements of chlorophyll function . The parOP = (Ft − F0)/(FP − F0). For further analysis of drought-induced changes in the OJIP curve and to evaluate differences between control plants and drought-stressed plants of each cultivar, the differential curves were presented separately. For visualization of L-band, fluorescence data were normalized between O (50 μs) and K (300 μs) steps, as VOK = (Ft − F0)/(FK − F0) and plotted as difference kinetics ΔVOK = VOK(drought) − VOK (control). For visualization of the K-band, fluorescence data were normalized between O and J (2 ms) steps as WOJ = (Ft − F0)/(FJ − F0) and plotted as difference kinetics ΔWOJ = VOJ (drought) − VOJ (control) [Chlorophyll fluorescence transient data were demonstrated as OJIP curves and plotted on a logarithmic scale from 50 µs to 1 s, where O, J, I, P steps were marked. The OJIP transients were double normalized between O and P steps: Wcontrol) ,73.a measurements, a bulk sample of the same fifteen leaves per cultivar was used for the analyses of total chlorophyll content (Chl a + b) and carotenoids (Car). The leaves were homogenized into a fine powder using liquid nitrogen with the addition of magnesium hydroxide carbonate. Photosynthetic pigments in the samples of leaves were extracted and re-extracted seven times with absolute acetone until it was completely uncolored to obtain maximum pigment utilization in five repetitions. Absorbance of the solution was measured by spectrophotometer  at 470, 647 and 663 nm. The concentrations of chlorophyll a (Chl a), chlorophyll b (Chl b) and carotenoids (Car) were calculated according to the equations of Lichtenthaler [After chlorophyll enthaler  and exprw/v) trichloroacetic acid (TCA) per 0.20 g of tissue powder. After extraction in the ice bath, homogenates were centrifuged for 15 min at 12,000× g at 4 °C and supernatants were used for determination of lipid peroxidation and hydrogen peroxide.Extraction was performed by 1 mL of 0.1% .Lipid peroxidation was measured as content of malondialdehyde (MDA) in the leaves by the method of Verma and Dubey . A total2O2) concentration was quantified according to Velikova et al. [2O2 content was determined using a calibration curve obtained with different concentrations of H2O2 and expressed as micromoles per gram of fresh weight (µmol/g FW).Hydrogen peroxide , were dispensed into reaction tubes. In each tube, we added 100 μL of a reaction mixture prepared with ninhydrin 1% (v/v) in acetic acid 60% (v/v) and ethanol 20% (v/v). The tube content was mixed and heated in a heating block at 95 °C for 20 min. After cooling at room temperature, tubes were centrifuged at 500× g for 1 min, and then 100 μL of the mixtures were transferred to polypropylene microplate. The absorbance at 520 nm was measured by an Epoch microplate spectrophotometer . Proline content was calculated according to obtained standard curve and expressed as micromoles per gram of fresh weight (μmol/g FW).Proline content was analysed by the procedure of Woodrow et al. . Aliquot2O and 0.1 mL of Folin–Ciocalteu reagent . After 5 min, 0.3 mL of sodium carbonate solution  was added. Homogenized reaction mixture was placed for 30 min in a dark place at room temperature. Absorbance of the solution was measured by spectrophotometer  at 765 nm. The content of total phenolic was expressed as milligrams of gallic acid equivalents (GAE) per g based on a gallic acid calibration curve.Total phenolic content was determined by modified Folin–Ciocalteu method . A totalAfter measuring chlorophyll fluorescence, a fraction of the leaves were sampled from the apple cultivars grown under either control or drought conditions and weighed to obtain the leaf fresh weight (FW). Thereafter, the weighed fraction of leaves was dried in the oven at 75 °C and weighed again to determine dry weight (DW). The water content in the leaves was calculated based on the equation :WC (%) =a fluorescence parameters; five replicates for chlorophyll, carotenoid, MDA, H2O2, proline and phenols content and three replicates for leaf water content.Analysis of variance was carried out to determine differences among the treatments and cultivars on the 7th and 12th day of drought treatment. Mean comparisons were performed using the least significant difference (LSD) test at a 0.05 level of probability. The results are presented as means ± standard error of fifteen replicates for Chl


Listeria monocytogenes is a Gram-positive bacterium causing listeriosis in animals and humans. To initiate a foodborne infection, L. monocytogenes has to pass through the host gastrointestinal tract (GIT). In this study, we evaluated survival abilities of L. monocytogenes 10403S wild type (WT) and its isogenic mutants in alternative sigma (σ) factor genes  under simulated gastric, duodenal, and bile fluids. Within 10min of exposures, only bile fluid was able to significantly reduce survival ability of L. monocytogenes WT by 2 logs CFU/ml. Loss of sigL showed the greatest bile resistance among 16 strains tested, p<0.0001, . To further investigate the role of σL in bile response, RNA-seq was conducted to compare the transcriptional profiles among L. monocytogenes 10403S ΔBCH triple mutant  and ΔBCHL quadruple mutant  strains under BHI and 1% bile conditions. A total of 216 and 176 differentially expressed genes (DEGs) were identified in BHI and bile, respectively. We confirmed that mpt operon was shown to be strongly activated by σL. Interestingly, more than 80% of DEGs were found to be negatively regulated in the presence of σL. This includes PrfA regulon and its mediated genes  which were downregulated in response to bile in the presence of σL. This result suggests the potential negative role of σL on bile survival, and the roles of σL and σB might be in a seesaw model prior to host cell invasion. Listeria monocytogenes is a facultative Gram-positive intracellular bacterium that is able to adapt to a board range of habitats. It can survive and grow in a variety of temperatures, and a wide range of pH, osmotic pressure, and high salt  and the catalytic core of RNA polymerase. In L. monocytogenes, there are four alternative sigma factors . σB has been intensively reported as a key factor responsible for L. monocytogenes survival under various stress conditions including high osmolality, low or high temperature, low pH, ethanol, and oxidative stresses . A 100μl aliquot of the pre-treated control (culture before treatment at t=0) and the untreated control  along with t=10 and t=20 cultures was 10-fold serially diluted in PBS (pH 7.4); 10μl of each dilution was plated onto BHI agar plates for subsequent enumeration. Experiments were conducted in three biological and technical replicates. All survival assays were performed in the absence of complementation strains.Mid-log phase cells were challenged with simulated gastric, duodenal, and bile fluids independently. The escribed . BrieflyL. monocytogenes wild type and its isogenic mutants were determined by one-way ANOVA with Dunnett’s post hoc test using GraphPad Prism version 9.2.0 (283), GraphPad Software, San Diego, California United States. p<0.05 was considered statistically different. To assess which sigma factor has the potent role in bile survival, the listeria strains have been categorized into groups with the presence or absence of each sigma factor. The average log reduction of all strains and replicates in each group was compared using unpaired t test.Significant differences in survival abilities between free™ DNase treatment kit  according to the manufacturer’s protocol. Total RNA concentration was quantified using NanoDrop 2000c spectrophotometer .For gene expression studies, RNA was extracted from mid-log phase cultures after 10-min exposure to 1% porcine bile or BHI (as a control) as previously described with minor modifications . BrieflyRibosomal RNA (rRNA) was depleted using Ribo-Zero rRNA removal kit  following manufacturer’s instruction. Quality of RNA was assessed using the 2,100 Bioanalyzer . Samples with RNA Integrity Number (RIN) score greater than 8.0 were considered acceptable for further library preparation and RNA sequencing. cDNA library preparation was constructed using ScriptSeq v2 RNA-seq Library Preparation kit for Bacteria . Purification of cDNA and indexed RNA-seq libraries was performed using Agencourt® AMPure® XP kit . Quantity and quality of the libraries were determined using the 2,100 Bioanalyzer. All experiments were performed in three biological replicates. Sequencing was carried out on a HiSeq 2×100 High Output paired-end, 100bp read at the Purdue University genomics core facility.L. monocytogenes 10403S (NCBI accession number: NC_017544.1). Reads were aligned and mapped with Bowtie2 and TopHat2  and adjusted p-values <0.05.Sequencing reads were mapped against  TopHat2 . The cut TopHat2 . Differe TopHat2 . The anaThe data sets generated or analyzed for this study were deposited in a public database and can be found under the SRA accession number: PRJNA544468.https://drive.google.com/drive/folders/1R3Wv3JN3ICxmY8ScbikALlzjlklfuObi?usp=sharing.For review purposes, RNA-seq data are available at L. monocytogenes utilized under BHI and/or bile conditions.GOseq package 1.34.1 package for R available from Bioconductor was used to evaluate whether differential expressed genes identified by DESeq2 were enriched for Gene Ontology (GO) terms . This torpoB and bglA as housekeeping genes and (ii) mptA, ilvD, ilvC, csbD, and LMRG_00704 for sigma L function. A list of TaqMan primers and probes designed by PrimerQuest  is shown in via Rotor-Gene Q  with the following conditions: 1cycle at 48°C for 30min, 1cycle at 95°C for 10min, followed by 40cycles at 95°C for 15s and 55°C for 1min. Reactions without Multiscribe™ reverse transcriptase  were run in parallel to account the possible genomic DNA (gDNA) contamination. Threshold cycle more than 35 was considered as undetectable. gDNA standard curve targeting each gene was performed to determine the amplification efficiency. Dilutions of gDNA in 107, 105, and 103 chromosomal copies were used as templates. Transcripts were normalized by a geometric mean of housekeeping genes rpoB and bglA. Statistical comparisons of gene expression levels among L. monocytogenes strains in each condition were performed by unpaired t test, SPSS version 23 .Select differentially expressed genes from RNA-seq results were validated using quantitative reverse transcriptase PCR (qRT-PCR) as previously described with minor modifications . Target L. monocytogenes to survive under simulated GI fluids, we exposed the bacteria to simulated gastric, duodenal, or bile for 10 and 20min. Survival abilities at 20min were not statistically different from those at 10min for all strains and conditions. Therefore, the presented data are that of 10min (T10) only. Following 10-min gastric fluid exposures, most of the deletion mutant strains survived similar to wild type, that is, similar levels of log reduction  when compared between WT and mutants  and the WT when exposed to gastric fluid, suggesting the compensatory effect of housekeeping sigma factor σA on L. monocytogenes survival in gastric treatment.To determine the ability of  mutants . Among tL. monocytogenes under duodenal fluid stress show in ΔB (p=0.0127) and ΔH (p=0.0003) mutants . Survival abilities of double mutants, on the other hand, were diverse. While ΔBC, ΔBH, and ΔBL mutants showed significantly higher susceptibilities (p<0.01), ΔCH and ΔHL exhibited lower growth when compared to WT. Among the triple mutants, the presence of σH in ΔBCL mutant resulted in higher susceptibility to duodenal fluid when compared to WT. Similar to gastric treatment, the absence of all four alternative sigma factors resulted in similar survival ability as wild type, suggesting again the compensatory role of σA under duodenal fluid exposure.Following gastric exposure, we next examined survival ability of L. monocytogenes in simulated bile pH 8.2. Survival of L. monocytogenes exposed to simulated bile is shown in L. monocytogenes WT decreased by 2 logs CFU/ml. Approximately 3-log reduction was observed at 10-min exposure for ΔB and ΔC single mutants compared to the corresponding pre-treated culture. The log reduction in ΔB was significantly higher than that of wild type (p=0.0268). The absence of σH or σL alone in ΔH and ΔL strains resulted in better survival than WT. In addition, double deletions of sigH and sigL resulted in even more pronounced ability to survive in synthetic bile for ΔHL (p<0.0001). In contrast to sigL deletion, the absence of σC in ΔBC and ΔCH resulted in a higher decline in the bile exposure survival experiment compared to WT. Nevertheless, two triple mutants (ΔBCL and ΔCHL) survived significantly better than WT (p<0.05). As observed in gastric and duodenal fluid treatment, the quadruple mutant survived similar to wild type. Collectively, we suggest that σB and σC play positive roles in response to bile exposure, while σH and σL likely play negative roles on L. monocytogenes survival under bile treatment. We further focused on the effect of each alternative sigma factor on L. monocytogenes survival in simulated bile. Among the alternative sigma factors, σL showed the greatest significant effect on L. monocytogenes survival abilities in synthetic bile (p=0.000).Following gastric and duodenal exposures, we further determined the survival ability of L showed the greatest effect on L. monocytogenes survival in bile, the effects of other sigma factors were also determined. In order to decipher the interaction among sigma factors and the redundancy effect, we performed mean interaction plots showing the mean of log reductions from the presence and absence of each sigma factor compared with one another as shown in B was compared in strains with σB  and without σB . The presence or absence of σB though could not significantly induce bile resistance if σL was present  were also downregulated.To determine the potential negative regulation of and clpE . HrcA haectively . MoreoveL, we further compared RNA-seq data between ΔL mutant grown in BHI and exposed to 1% bile. In this analysis, we found 84 genes were differentially expressed as shown in clpE gene and ilv operon ranging from 4 to 8 FC. clpE encodes ATP-dependent Clp protease, ATP-binding subunit ClpE, while the ilv operon is involved with valine biosynthesis. Universal stress response uspA2 gene was also significantly upregulated under bile exposure.To assess the effect of the absence of σL under bile exposure. Among them, approximately 3–4 FC was observed from LMRG_00042, LMRG_01298, and LMRG_01900. These genes are involved with glycerol catabolic pathway, nucleoside triphosphatase YtkD, and mannitol-specific phosphotransferase system (PTS), respectively. In addition, some transporter genes, such as LMRG_02716 and LMRG_01818, as well as flagella biosynthesis-associated gene flhF, were also downregulated during bile exposure.Conversely, 48 genes were downregulated in the absence of σL in gene regulation, RNA-seq data from ΔBCHL and ΔBCH L. monocytogenes mutant strains grown in BHI were compared. ΔBCHL lacks all alternative sigma factors and only harbors the housekeeping σA, while ΔBCH mutant represents the sole presence of alternative σL which could co-ordinate or compete with the housekeeping σA. RNA-seq data comparison of ΔBCHL and ΔBCH allowed us to evaluate the regulation of σL with minimal redundancy of alternative sigma factors σB, σC, and σH. Under BHI only condition, ΔBCHL and ΔBCH transcript comparison revealed 216 genes  that were significant differentially expressed  and 48 (18.4%) genes showed higher and lower transcripts in bile exposure condition, respectively  of positively regulated gene by σL. This result confirmed the negative role of σL in gene expression since loss of σL could upregulate some of downregulated genes shown in ΔBCH and ΔBCHL comparison. For example, LMRG_02569 encoding cellobiose-specific PTS IIB component was shown to be negatively regulated under σL by −9 FC; however, it had higher expression by 16 FC when in ΔL mutant. Beta-glucosidase encoded gene LMRG_02568 was expressed at low level in ΔBCH mutant but its transcript was increased to as high as 14.5 FC in the ΔL mutant. This suggested that deletion of sigL upregulated genes that were suppressed or downregulated. Among the upregulated gene in ΔL background, LMRG_00091 gene, identified as σL negatively regulated gene, was also upregulated as high as 61 FC.We investigated the effects of the loss of σce of σL . Howeverectively . In contL activities, selected sets of σL-dependent genes were verified in qRT-PCR assays. We confirmed the positive and negative role of σL using differential expression of mptA and csbD, respectively ; however, their transcripts are highly expressed in ΔL. Therefore, csbD and LMRG_00704 are negatively regulated by σL. Bile does not influence the level of csbD and LMRG_00704 as bile does not significantly alter the level of transcripts of these genes (ilv operon (ilvD-ilvC) is also upregulated in the presence of bile in ΔL  of expression levels in the wild type, ΔL and ΔBCH and ΔBCHL mutant at 0.87, 0.91, 0.86, and 0.93, respectively , we could not observe the reduction of ΔB mutant, in contrast to other studies showing that ΔB mutant had impaired survival in acidic culture at pH 2.5 compared to its wild type  is more harmful to bacterial cells than inorganic acid (HCl) used in our system compared to other finding  and lmo0345  were downregulated by σL. The association between σL and virulence is yet to be confirmed. It is possible the negative regulation by σL is in an indirect manner.It is likely that σanalysis . Among 2ent gene . NeverthilvC gene (ilv operon) in L. monocytogenes 10403S  in response to 1% basic bile (pH 8.2). It was concordant with previous microarray study and with our RNA-seq study showing the whole PrfA regulon was repressed under bile exposure (prfA itself upon exposure to acidic bile (pH 5.5). It is suggested that the alteration of bile pH could contribute to diverse regulation and transcription levels since pH was considered as a stimulus as well. In addition, other factors such as strain, serotype, and lineage could vary members of bile stimulon .The datasets generated or analyzed for this study were deposited and can be found under the SRA accession number PRJNA544468  for Talent Mobility Program (to SC). HO is partially supported by USDA-NIFA Hatch project IND010930.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.