Perovskite light-emitting diodes have recently broken the 20% barrier for external quantum efficiency. These values cannot be explained with classical models for optical outcoupling. Here, we analyse the role of photon recycling (PR) in assisting light extraction from perovskite light-emitting diodes. Spatially-resolved photoluminescence and electroluminescence measurements combined with optical modelling show that repetitive re-absorption and re-emission of photons trapped in substrate and waveguide modes significantly enhance light extraction when the radiation efficiency is sufficiently high. In this manner, PR can contribute more than 70% to the overall emission, in agreement with recently-reported high efficiencies. While an outcoupling efficiency of 100% is theoretically possible with PR, parasitic absorption losses due to absorption from the electrodes are shown to limit practical efficiencies in current device architectures. To overcome the present limits, we propose a future configuration with a reduced injection electrode area to drive the efficiency toward 100%. Perovskite light-emitting diodes have shown unexpected high external quantum efficiency of 20%, breaking the ray-optics limit. Here Cho et al. reveal that photon recycling is responsible for the enhancement and propose photonic structures to further improve the device efficiency. It is notable that the reported EQEs are significantly above the ray-optics limit11 of 1/2n2 (corresponding to between 7 and 13%), as typical perovskites have relatively large refractive indices, n, between 2 and 2.615 compared with organic emitters with n < 1.816. Although there have been many reports of OLEDs overcoming this limit by optimising microcavity effects with thin emissive layers17, it is surprising that PeLEDs have achieved efficiencies of almost twice the limit even with thick emissive layers (~ 200 nm)4 in which the positions and orientations of emissive dipoles are difficult to control and the corresponding wave-optical effects are diluted. This discrepancy raises three questions: (i) how do PeLEDs achieve high EQEs overcoming their low ray-optical limit; (ii) what internal quantum efficiencies (IQEs) and light extraction efficiencies (LEEs) are being achieved in current PeLED devices; and (iii) what is the upper limit of PeLED efficiency and how might it be obtained?Perovskite light-emitting diodes (PeLEDs) have recently shown great advances in performance and have reached external quantum efficiencies (EQEs) of up to 22%19. Although re-absorption has been typically considered as a loss mechanism in LEDs21, with sufficient luminescence efficiency, the process of photon recycling (PR) can assist with optical outcoupling by randomising the direction of photon propagation and redirecting photons from trapped to outcoupled modes22. PR has been previously reported to enhance the externally outcoupled photoluminescence (PL) of perovskite films and to improve the voltage characteristics of photovoltaics (PVs)30. Although PR gives PeLEDs the potential to achieve 100% EQE theoretically, its practical contribution to the device efficiency is still under debate28.Perovskite semiconductors have relatively small Stokes shifts, which lead to significant levels of re-absorption of emitted photons2Csn−1PbnBr3n+1 with luminescence peaking at 520 nm, where PEA refers to phenylethylammonium, we measure spatially resolved PL and electroluminescence (EL). By detecting recycled photons at large distances from the excitation, we find that PR can significantly increase extraction of photons from trapped modes. Moreover, our modelling approach allows quantitative analysis of the LED efficiency. In state-of-the-art PeLEDs having EQE > 20%, PR is calculated to be able to contribute > 70% of light emission . Although the recently reported EQEs are already close to calculated limits for planar architectures, we propose several photonic structures maximising the PR effect, which could further improve PeLED performance.In the present study, we aim to verify and quantify the contribution of PR in PeLEDs and to suggest design principles to maximise the benefits from PR. Using (PEA)2Csn–1PbnBr3n+1 perovskite having high PL efficiency and a smooth surface  of the perovskite is higher at low excitation fluxes (37%) than at higher excitation fluxes (19%) (probably owing to increased Auger recombination28), allowing more precise investigation of the effect of PR at distances away from the original excitation.In this study, we used films of the 2D–3D mixture PEAα520nm = 1.3 μm in our perovskite) and the typical charge carrier diffusion lengths (on the order of 1 μm) of perovskites34, the signal collected at such large distances is expected to arise mostly from re-absorbed photons in the substrate mode rather than those in the waveguide mode or from diffused charge carriers.Figure 24, their contributions can be distinguished by their different spectral characteristics: for a sufficiently narrow PL spectrum, the scattering length does not change significantly for emitted wavelengths and the scattered spectrum represents the spectrum of trapped photons at the relevant position. As trapped photons with shorter wavelengths have higher probability to undergo re-absorption, the trapped light and its scattering signal tend to be more red-shifted along the distance of propagation, whereas the signal from PR always resembles the original PL spectrum, as observed in Fig. As shown in Fig. To quantify the contribution of PR, we created a gap in the perovskite film by mechanically removing the region at distances between 230 μm and 290 μm. Then, as shown in Fig. To study the effect of PR in a more practical setting, we measured the spatially resolved EL of a full PeLED device with a structure of glass/indium tin oxide ITO, 150 nm)/poly(9-vinylcarbazole) /perovskite (50 nm)/2,2’,2”--tris(1-phenyl-1-H-benzimidazole) /LiF (1 nm)/Al, of which the measured maximum EQE was 12.5% at 2.6 V. When a voltage (4 V) is applied to a pixel, as shown in Fig. 0 nm/poly35. By assuming that the ratios of direct light outcoupling (LEE0), perovskite re-absorption (Aact) and parasitic absorption loss (Apara) (LEE0 + Aact + Apara = 1) are consistent along the recursion, the EQE becomes:ηrad) and charge balance efficiency (ηinj)36. With ideal (near-unity) ηinj and ηrad, Eq. The outcoupling efficiency of PeLEDs can be calculated by integrating recursive PR processes39. In PeLEDs, the presence of re-absorption is a major obstacle to calculations of dipole emission, leading to a divergence of dipole density within the absorbing medium40. Although previous studies ignored the re-absorption of the emissive layers to avoid this problem41, we resolved the divergence by assuming that (i) internal dipoles are uniformly distributed over the perovskite divided into 20 slices, (ii) only the mesh slice containing the dipole is non-absorbing  and the other 19 mesh slices retain their absorption property and (iii) the non-radiative coupling42 of the dipole with other absorbing meshes in perovskite, which is the main reason for divergence, does not affect the external radiation efficiency as the energy remains in the perovskite. The third statement can be understood as virtual PR in the same manner as Förster resonance energy transfer. The transfer matrix formalism (TMF)43 was adopted to calculate the efficiency of each dipole. Full details for our approach and its physical background are provided in Supplementary Figs. To maximise the benefit of PR, detailed design principles for LED devices can be established with the assistance of optical device modelling2Csn−1PbnBr3n+1 perovskite) has a refractive index with real part (n) of ~ 2 Aact) tends to increase in all radiative modes and the fraction of direct outcoupling decreases. The corresponding maximum EQEs with perfect ηinj and ηrad are plotted in Fig. n2, which is 13% for n equal to 2. The EQE further decreases when re-absorption is considered as a loss mechanism (closed grey squares). On the other hand, if re-absorbed photons recursively generate dipoles with perfect recycling efficiency   the benefit of PR does not exceed the re-absorption loss and the EQE with PR is similar to that for a non-absorbing perovskite. However, as ηrad increases, a maximum EQE of 18.0% is reached with the aid of increased PR, which is substantially higher than the value without re-absorption (14.5%), demonstrating the counter-intuitive principle that a reduced Stokes shift enhances outcoupling efficiency in highly radiative devices. This relationship can be used to correctly quantify the IQE and PR contribution in practical devices. For example, for our current device structure giving an EQE of 12.5%, ηrad is found to be 75% and the fractional contribution from PR is 17.5%  for effective re-absorption coefficients (α) above 1.3 × 104 cm−1 and 4 × 103 cm−1, respectively. Here, we assumed that these α values are sufficiently high for re-absorption (and hence PR) to dominate over scattering, at least in the planar devices. Although scattering can in general provide an effective means to extract photons from trapped modes by randomising the propagation angle, we expect it can dominate over PR in some devices having (i) exceptionally rough interfaces or nanostructures;41 (ii) large Stokes shifts ; or (iii) low radiation efficiency . The study of devices where both PR and scattering are important will be an important goal for future research.Our model incorporating PR is important to explain the recent successes of achieving high EQE (> 20%) PeLEDsn and increased re-absorption, and transparent conductive electrodes with reduced parasitic absorption.As shown in the previous section, the maximum achievable EQE is limited to between 20% and 25% in current PeLED architectures owing to losses from parasitic absorption. Although recently reported devices already approach this upper bound, Supplementary Fig. Apara and maximise the PR effect. Figure ηrad all photons will eventually be outcoupled. A back mirror (not necessarily conductive) with high reflectivity ensures all photons are extracted in the forward direction. Figure 45. Moreover, although this calculation assumed dipole generation immediately beneath the electrode, charge carrier diffusion can improve the effective injection area of LEDs with nanostructured electrodes, without increase of parasitic absorption loss. Accordingly, the benefit of efficient PR can be achieved without damaging the areal density of light emission, by setting the distances between nanostructured electrodes to be similar to the diffusion length of charge carriers.Ultimately, to achieve ultrahigh EQEs approaching 100%, an improved device architecture design is essential to remove 47 that aligns polarisation; an angle confinement microstructure49, which confines emission angle; and a distributed Bragg reflector51, which narrows both emission angle and spectrum. Polarised emission will be especially useful in display applications, reducing the 50% efficiency losses typically encountered in the circular polariser needed to achieve high contrast ratios.Not only the quantity of photons, but also properties of emitted photons can be optimised utilising PR. When emitted photons are filtered by a selective transmitter, photons having the non-desired property can be recursively recycled with the randomised property within the emitting film. In the limit of perfect PR and zero parasitic absorption loss, a 100% filter transmission could be achieved for the desired property. Figure ηrad, such as PeLEDs. Schemes incorporating reduced electrode area and various filtering structures have been proposed to maximise the benefit of PR in current PeLED architectures.The study illuminates the current state and potential of PR in PeLEDs, demonstrating how the efficiency and properties of light emission are enhanced. Spatially resolved luminescence measurements have shown lateral propagation of emission over 300 μm in perovskite films, demonstrating efficient PR in the material. By recycling the photons trapped in the substrate and waveguide modes, PR has been shown to significantly contribute to the light outcoupling in luminescent perovskite optoelectronic devices having high 2 (Sigma-Aldrich), 63.8 mg CsBr (Sigma-Aldrich) and 67.46 mg PEABr (Dyesol) in 1 mL of anhydrous dimethyl sulfoxide (Sigma-Aldrich). The precursor solution was stirred using a magnetic stir-bar for ~ 12 h at room temperature before use. For the experiment of spatially resolved PL, the perovskite film was prepared by dropping 20 μL perovskite precursor onto a PET substrate spinning with 2000 rounds per minute (RPM).The perovskite precursor was prepared by dissolving 110.1 mg PbBr−1, Colorado Concept Coatings) was cleaned using ultrasonication in acetone and isopropanol for 15 min, respectively, and then dried with a nitrogen blow gun, after which the substrate was treated under oxygen plasma etching . The ITO substrate was then transferred to a nitrogen-filled glovebox. PVK was spun from chlorobenzene solution (6 mg mL−1) at RPM 3000 and was annealed at 120 ˚C for 10 min. Subsequently, the perovskite was deposited from the precursor to form a ~ 50 nm layer using 4000 RPM, and was annealed at 70 ˚C for 8 min. Finally, 50 nm TPBi, 1 nm of LiF and 80 nm of Al were sequentially evaporated through a shadow mask at a pressure of 10−6 mBar. The device was encapsulated with UV epoxy /cover glass to avoid exposure to oxygen and moisture and degradation during measurement.To measure spatial EL, a pre-patterned ITO substrate (15 Ω sqJ–V) characteristics. The relative angular characteristics of the emission were measured by rotating the device at 20 cm from the silicon photodiode. The luminances and EQEs were calculated by applying the relative angular characteristics to the front emission measured using a silicon photodiode of which spectral response is known. The LED measurement setup was previously cross-checked against a third-party industrial laboratory8.A Keithley 2400 source-metre was used to obtain the current density–voltage (52. A continuous wave 405 nm diode laser with a beam size of 0.3 mm2 was used for excitation. Photons were collected using an Andor iDus DU420A Si detector with an integration time of 0.02 s (for excitation > 1018 m−2 s−1) or 0.2 s (for excitation < 1018 m−2 s−1).PL was measured with an integrating sphere according to the method previously reportedAbsorption spectra of thin-films deposited on fused silica substrates were measured using Hewlett-Packard 8453 UV−vis spectrometer with blank substrate correction. The photoluminescence excitation (PLE) spectrum was obtained by measuring a perovskite-coated glass with FLS980-S2S2-sm (Edinburgh Instruments Ltd.) equipment. Each measured value was normalised to incident excitation intensity. The excitation wavelength was scanned while detecting the fixed wavelength of 525 nm  or various wavelengths  with a detection range of 1 nm.The spatially resolved PL was measured using a WITec Alpha RAS system. The sample was rested on a XYZ piezo stage of the microscope and a black aperture was inserted below the substrate to prevent any unexpected light pathway such as diffusion at the excitation lens and reflection at the bottom stage. The film coated on the top of the PET substrate was excited by a 405-nm c.w. laser (Coherent CUBE), focused using a × 40 objective lens (NA = 0.60) from the bottom side and the PL was collected in transmission geometry using a × 20 objective lens (NA = 0.40) above the top side. The lateral distance between the excitation and collection was controlled by WITec ScanCtr Spectroscopy Plus software. The signal at each point was obtained by averaging several repetitive measurements with the integration time of 1 s. The signals for 505 nm and 525 nm were collected by integrating the ranges of 500–510 nm and 520–530 nm, respectively. The spatially resolved EL has been measured using the same setup by replacing the excitation light with an applied voltage of 4 V. The full device with a structure of glass/ITO (150 nm)/PVK (10 nm)/perovskite (50 nm)/TPBi (50 nm)/LiF (1 nm)/Al was measured. As photon flux is diluted at the far distance, the far range signal was constructed by averaging 36 measurements with integration time of 26 s to secure sufficient signal-to-noise ratio. All the measured quantities of the signal were divided by the integration time. Refer to the SI for further details of reliability issues related to this measurement.43 was used to calculate the emissive characteristics in PeLEDs having a structure of glass /ITO (150 nm)/PVK /perovskite/TPBi /Al, where n indicates the refractive index of each layer. Refractive indices of ITO53 and Al54 were obtained from the literature and that of perovskite was obtained by fitting the Kramers–Kronig relation55 for the measured transmission and PLE spectrum  of the refractive index in perovskite sharply varies within the range of the luminescence spectrum, we performed calculations throughout the wavelength range from 480 nm to 560 nm and integrated /ITO /PEDOT:PSS /perovskite /poly(methyl methacrylate) /C37H26N6 /Al  and glass /ITO /ZnO:PEIE /perovskite /polydiphenyl-amine)  /molybdenum oxide /Au  were used for the devices of Lin et al.4 and Xu et al.5, respectively. For simplicity, a monochromatic model was used for the wavelength (λ) of 525 nm and 800 nm, respectively, varying effective k values (= αλ/4π) of perovskite. Refractive indices at each wavelength were obtained from various literatures54.Reported structures of glass  and αpara indicates a constant for parasitic absorption loss, assumed to be αpara = αact × Apara/Aact in the waveguide mode. All photons in the substrate mode can directly escape the electrode because their single-trip propagation distance (> 2 mm) is longer than the electrode widths used in the calculation. The calculation was recursively performed until no photon remains in perovskite of the electrode-covered area.In the proposed system with reduced injection electrode area Fig. , we assuSupplementary Information


Microporous membranes support the growth of neurites into and through micro-channels, providing a different type of neural growth platform to conventional dish cultures. Microporous membranes are used to support various types of culture, however, the role of pore diameter in relation to neurite growth through the membrane has not been well characterised. In this study, the human cell line (SH-SY5Y) was differentiated into neuron-like cells and cultured on track-etched microporous membranes with pore and channel diameters selected to accommodate neurite width (0.8 µm to 5 µm). Whilst neurites extended through all pore diameters, the extent of neurite coverage on the non-seeded side of the membranes after 5 days in culture was found to be directly proportional to channel diameter. Neurite growth through membrane pores reduced significantly when neural cultures were non-confluent. Scanning electron microscopy revealed that neurites bridged pores and circumnavigated pore edges – such that the overall likelihood of a neurite entering a pore channel was decreased. These findings highlight the role of pore diameter, cell sheet confluence and contact guidance in directing neurite growth through pores and may be useful in applications that seek to use physical substrates to maintain separate neural populations whilst permitting neurite contact between cultures. Differing from conventional dish cultures, membrane pores permit nutrient diffusion to the underside of the cell sheet and act as a reservoir for extracellular matrix and expressed factors. When cells are cultured as sheets, this can result in the polarisation of the cell soma3. Where cells are cultured on both sides of the membrane, pores allow for restricted connectivity between the cultures, for example between the astrocytes and endothelial cells in systems which model the blood brain barrier4. Porous membranes also play a key role in many of the emerging ‘lab-on-a-chip’ type culture systems, including lung5, stem cell differentiation6, blood-brain-barrier7, skin8, neural differentiation9, gut10, and liver11 applications.Microporous membranes are commonly used in many different types of cell culture application including the study of cell migration and the culture of cell sheetsThe culture of neural networks directly on microporous membranes extends the study of neural cultures in flat bottomed dishes, enabling both neurons and neural processes to grow into and through membrane channels. In this way, the porous membrane acts as both a permissive substrate that supports neuron attachment and growth, and a restrictive substrate that limits the amount of connectivity between the culture surfaces on either side of the membrane. This arrangement also provides a two-layered culture environment, with both sides of the membrane accessible to conventional analysis using planar microscopy and dish-based assays.ex-vivo neural tissue slices12 allowing diffusion of nutrients and oxygen into the slice, the use of porous membranes as a culture substrate that facilitates the growth of neural networks is not well established. There is also a need to better understand how microporous substrates modulate network growth through investigation of the role played by pore shape, spacing, diameter, and channel length and structure. During neural network formation, the neurite growth cone is sensitive to surface features, such that nanostructures15 and microstructures21 encountered on the surface direct and modulate the growth of neural processes. Of the types of commercially available porous membranes, track-etched polymer membranes have flat culture surfaces and highly uniform diameter pores and channels22, making them especially appealing for the study of neural migration and neurite growth. Although neural cells have been found to migrate through track-etched micro-porous membranes with 8 µm diameter pores23, and smaller pore diameters (1 µm to 3 µm) have been found to restrict whole cell migration in the study of neurite outgrowth26, a systematic study of neuron and neurite response to track-etched membrane pore and channel diameter has not been reported.Whilst porous membranes have long been used to support the viability of In this report, fluorescence microscopy was used to investigate neuron and neurite growth through track-etched membranes with pore diameters ranging from 0.8 µm to 5 µm. Electron microscopy was used to gain a more detailed perspective of the interaction of neurites with pore edges. Based on the findings presented, an optimised pore diameter of 1.2 µm was used to demonstrate neurite growth through membrane channels between two separated neuronal populations.Track etched membranes have uniform pore diameters and straight channels that pass directly through the membranes. Analysis of scanning electron microscope images was used to confirm that pore distribution across the membrane surface, as well as porosity and pore channel diameters fell within manufacturer specified tolerances Fig. . Channel4 cells/cm2) and incubated for one hour to allow for attachment before adding extra medium to the well . Image analysis revealed that the amount of neurite coverage below the membrane was similar for all seeding densities above 9 × 104 cells/cm2, and significantly reduced for lower seeding densities, which resulted in non-confluent cultures over the 5-day culture period. Very few neurites extended through membrane pores for seeding densities of 3 × 104 cells/cm2.The SH-SY5Y neuronal cell model was chosen to study the effect of seeding density on neurite growth through pores, as SH-SY5Y neurons remain evenly distributed across the membrane over the 5 day culture period, facilitating image analysis, whereas we have found that other human neuronal cell types such as NT2/D1  and no cell migration occurred between the two networks Fig. . It is eThe architecture of cultured neural networks can be constrained by engineering microscale channels into culture substrates. The growth of stable neurite connection pathways inside these channels during long term cultures is a viable approach for producing complex network structures. However, greater understanding is needed as to how neurite uptake and subsequent neurite extension is modulated by channel diameter, length and the shape of the surface pores at the entrance and exit to channels in culture substrates. In this report it was demonstrated that channel diameters can be used to constrain cell migration whilst facilitating neurite connections between neurons in culture. Specifically, a 1.2 µm channel diameter was found to be ideal for restricting the migration of neural soma whilst permitting extensive neurite growth and interaction between two distinct neural networks. A contact guidance effect on the membrane surface may have reduced the likelihood that cellular processes entered pore channels, such that a neurite growing from a neuron in a non-confluent culture would be less likely to extend into the channels that it encountered when exploring the surface of the culture substrate. For non-confluent cultures, tailoring the shape of pore entry geometry may provide a way to use contact-guidance to control the direction of neurite growth into membrane channels.Elastomer rings were punched from cast elastomer sheet to securely hold the porous membrane in wells of a 24-well plate  for 7 days through exposure to 10 µM all-trans-retinoic acid  and harvested using 1x Trypsin (0.5% w/v) with EDTA (0.02% w/v)  for seeding onto membranes. To investigate the effect of pore diameter on cell migration and neurite growth through the membrane, cells were seeded at high density (30 × 104 cells/cm2) to obtain confluent cell layers. To investigate the effect of seeding density on neurite growth through the membrane, cells were seeded at lower densities  and at very low density (1 × 104 cells/cm2) to reveal neurite interaction with pores. In all investigations, cells were cultured on membranes for 5 days. To stimulate neurite outgrowth whilst attached to membranes, cells previously differentiated in RA were cultured in Neuronal Base Medium P  supplemented with 1% PS, 2% (v/v) Neuronal Stem Cell Supplement , 10 ng/ml nerve growth factor  and 50 ng/ml brain-derived neurotrophic factor .The SH-SY5Y human neuroblastoma cell line was obtained from the European Collection of Cell Cultures (cat. no: 94030304) and routinely cultured in complete media composed of RPMI 1640 with stable glutamine , supplemented with 0.1 mM nonessential amino acids , 10% (v/v) foetal bovine serum  and 1% penicillin (100 U/mL) with streptomycin (100 mg/mL) . Cells were incubated with 5% CO2 flasks at a multiplicity of infection (MOI) of one viral particle per cell. After transduction for 12 hours, flasks were washed three times with media and then allowed to recover for 6 hours. Subsequently cells were washed with PBS and detached from the flasks using 0.5% trypsin EDTA . Cells were washed by centrifugation, and resuspended in media. Transduced cells were seeded into 6-well cell culture plates  with an initial seeding density of (200 cells/cm2) in the first well, followed by a serial 1:2 dilution across the remaining wells. Cells were allowed to recover for 24 hours prior to selection by the addition of Blasticidin  to the medium at a final concentration of 3 µg/ml. After selection, Blasticidin resistant colonies were isolated by trypsinisation using glass cloning cylinders , expanded and subsequently maintained in SH-SY5Y media containing Blasticidin (3 µg/ml).To distinguish SH-SY5Y cells in two-layer culture, cells that were to be used in the lower layer were transduced with lentiviral constructs driving constitutive expression of enhanced green fluorescent protein (EGFP) under the control of the human elongation factor-1 alpha promoter (EF-1α). Cells to be used in the upper layer were transduced with lentiviral constructs encoding mCherry fluorescent protein. Briefly, the sequence encoding EGFP or mCherry was placed downstream of the EF-1α promoter in the lentiviral expression vector pLenti6.4/R4R2/V5-DEST . Viral particles were quantitated using the QuickTiter™ Lentivirus Titer Kit  and used to transduce SH-SY5Y cells in 25 cm4 cells/cm2) on top of each membrane and incubated for 1 hr, after which time most cells had attached. Non-attached cells were removed by washing with fresh media, and to facilitate two layer cultures, the upper PDMS ring was removed, and the membrane inverted and replaced such that attached cells were positioned beneath the membrane. The top PDMS ring was then replaced and pushed securely into place to hold the membrane for the second seeding. Cells expressing mCherry protein were seeded on top of the membrane at a higher density of 20 × 104 cells/cm2 and the dual layer culture was incubated for a further 5 days, changing media above the membrane every 2 days.EGFP expressing cells were seeded at lower densities of  in PBS at 4 °C for 15 minutes. Fixed membranes were washed three times in PBS and stored for up to one week in PBS at 4 °C. For dual layer cultures, direct imaging of the expressed fluorescent protein was used to visualise cells and neurites. For all other cultures, neurites were imaged after immunostaining of βIII tubulin. Prior to staining, cells were blocked and permeabilised at room temperature for 1 hour in PBS containing 10% bovine serum albumin  and 1% Triton X-100 . For βIII tubulin staining, membranes were inverted and placed into wells of a 24-well plate, such that neurite outgrowth was exposed above the membrane. The membranes were incubated overnight at 4 °C with mouse monoclonal anti-βIII tubulin antibody , diluted 1:1000 in staining buffer (1% BSA and 0.1% Triton X-100 in PBS). After incubation membranes were washed three times in staining buffer and incubated at room temperature for 2 hours with Alexa Fluor 568 goat anti-mouse IgG  diluted 1:500 in staining buffer.Removal of cells from the upper seeded side of the membrane is a technique commonly used in migration assays that reduces background florescence signal and permits more rapid and accurate imaging of the lower non-seeded side of the membrane using widefield microscopy. Excess liquid was removed by blotting with filter paper, the membrane was held taught and the top side wiped thoroughly using a PBS soaked cotton swab to remove cell bodies and neurites from the seeded side of the membrane. Membranes were gently washed three times in PBS and mounted onto slides with mounting medium  containing the blue fluorescent nuclear dye 4′,6-diamidino-2-phenylindole (DAPI).SEM imaging of cells cultured on membranes was carried out after fixing cells in 4% PFA. Membranes were dehydrated in a graded series of ethanol concentrations in PBS  for 5 minutes per rinse followed by chemical drying using two rinses in 1,1,1,3,3,3-hexamethyldisilazane  for 5 minutes each, prior to air drying. Membranes imaged without attached cells did not require dehydration. All samples were sputter coated with platinum and imaged under vacuum using a field emission SEM  operating at an accelerating voltage of 5 kV.2). To ensure a fair comparison, neurite growth through each membrane was normalised by dividing the calculated neurite area per field against the calculated porous area per field and then adjusting results relative to the calculated neurite growth through 0.8 µm pores. Characterisation of membrane pore size and porosity was performed semi-automatically using routines written in ImageJ software. Briefly, to calculate porosity a binary threshold was applied to SEM images using the default ImageJ algorithm and the black pixel area in 10 fields (representing the pores) was divided against the total pixel area to calculate the porous and non-porous ratios. To determine pore size, lines were manually draw onto the SEM images and the pixel length of the lines was used to calculate the average pore diameter, calibrated against a given scale. The results averaged across fields a number of fields (n > 10) with at least 3 pores per field (n > 30). To determine neurite interaction with pores, counting occurrences was performed using the imageJ Cell Counter plugin across multiple fields , with at least 7 interactions counted on average per field (n > 28).Fluorescently stained and fluorescent protein expressing cells were imaged using a cooled CCD camera  attached to an inverted microscope  with LED illumination . Manual counting of in-focus DAPI stained cell nuclei below the membrane was used to estimate cell migration. Estimates for the area of neurite coverage below the membrane were obtained from image analysis of grayscale fluorescence intensity images of βIII tubulin stained cultures. For each field of view, counting of pixels with a fluorescence signal above a threshold determined using a default thresholding process  was used to obtain the approximate coverage of βIII tubulin comparison to the total field area. Studies were performed in triplicate, with 7 or more fields imaged per sample . One-way ANOVA Figs  and 3–5 Supplementary InformationFigure S3Figure S4Figure S5Figure S6


Hemoglobin (Hb)-based oxygen carriers (HBOCs) have been engineered to replace or augment the oxygen carrying capacity of erythrocytes. However, clinical results have generally been disappointing, in part due to the intrinsic oxidative toxicity of Hb. The most common HBOC starting material is adult human or bovine Hb. However, it has been suggested that fetal Hb may offer advantages due to decreased oxidative reactivity. Large-scale manufacturing of HBOC will likely and ultimately require recombinant sources of human proteins. We, therefore, directly compared the functional properties and oxidative reactivity of recombinant fetal (rHbF) and recombinant adult (rHbA) Hb. rHbA and rHbF produced similar yields of purified functional protein. No differences were seen in the two proteins in: autoxidation rate; the rate of hydrogen peroxide reaction; NO scavenging dioxygenase activity; and the NO producing nitrite reductase activity. The rHbF protein was: less damaged by low levels of hydrogen peroxide; less damaging when added to human umbilical vein endothelial cells (HUVEC) in the ferric form; and had a slower rate of intrinsic heme loss. The rHbA protein was: more readily reducible by plasma antioxidants such as ascorbate in both the reactive ferryl and ferric states; less readily damaged by lipid peroxides; and less damaging to phosphatidylcholine liposomes. In conclusion in terms of oxidative reactivity, there are advantages and disadvantages to the use of rHbA or rHbF as the basis for an effective HBOC. Globally, there is a need for a sustainable, long-lasting, artificial blood substitute due to increased demand, the risk from new blood-borne diseases, difficulty in matching rare blood types, and religious aversion to blood products . There iThe use of the oxygen carrying hemoglobin (Hb) is favored as a starting material for such an extracellular oxygen delivery product; consequently the field of Hb-based oxygen carriers (HBOCs) has resulted in a wide variety of preclinical and clinical trials in this area, although with rather limited current success . TraditiEscherichia coli [E. coli and produced human Hb in clinical trials [The starting material for Hb production has varied. Bovine Hb has been used due to ease of production , similarhia coli . Somatogl trials .Baxter Healthcare subsequently bought Somatogen ensuring a long-term production platform for its HBOC products combined with the additional flexibility of engineering favorable properties into the product . The res2ε2); HbE Portland-1 (ζ2γ2); HbE Gower-2 (α2ε2); HbF (α2γ2); and HbA (α2β2). These proteins have different functional properties suitable for their developmental roles.HBOC products have largely focussed on using the adult HbA-based molecule. However, HbA is not the only form of human Hb. Human Hb is a tetramer of homologous protein dimers of α- and β-type subunits. α-like genes are encoded on chromosome 16  and β-like genes on chromosome 11 . During development, the Hb tetramer changes from embryonic form of Hb to the fetal and then adult forms. The development lifetimes overlap, but is broadly in the order: HbE Gower-1  cells transformed with pETDuet plasmid containing genes for the adult or fetal wild-type Hb were grown in 2 l Erlenmeyer flasks containing 1.4 l growth medium at 37°C, and agitated at 180 rpm until an OD600 ~2 was achieved. Hb expression was then induced by the addition of 0.5 mM IPTG, 0.25 mM ALA (aminolevulinic acid), and 0.1 mM ferric citrate. Cultures were then bubbled with pure CO gas, flasks sealed thoroughly with rubber bungs, and grown for a further 18 h at 30°C at 90 rpm. Cells were then harvested by centrifugation at 3500 g for 20 min at 4°C.Our previous rHb purification method used cation exchange and size exclusion methodology . A smallg for 30 min at 4°C and the pH was adjusted to 6.0 by the addition of small quantities of orthophosphoric acid. The centrifugation step was then repeated and the lysate filtered through a 0.45-µm syringe filter before being loaded on to a CM Sepharose column  pre-equilibrated with 10 mM sodium phosphate buffer, pH 6.0. Hb was then eluted with a gradient of 70 mM sodium phosphate, pH 7.2. Selected fractions were then pooled and the volume decreased in a spin concentrator and loaded on to a 5 ml Q-HP column  pre-equilibrated with 70 mM sodium phosphate buffer, pH 7.2. Protein was eluted with a 100 ml gradient of 50 mM sodium phosphate, pH 7.2, and 100 mM sodium chloride. Fractions containing Hb were pooled and applied to a 5 ml HisTrap HP column  and eluted with a 100-ml gradient of 50 mM sodium phosphate, pH 7.2, 100 mM sodium chloride, and 100 mM imidazole. Finally, Hb was concentrated using an Amicon Ultra 30000 MWCO (Millipore) and then buffer exchanged into 70 mM sodium phosphate, pH 7.2. All buffers used during the purification procedure were bubbled with CO and the lysate and proteins were bubbled with CO at every stage. Four to fifteen percent of gradient TGX stain free precast gels (Bio-Rad) were used to assay purity following each column stage. The concentration of the ferrous CO (carbonmonoxyHb) bound form of Hb was calculated using an extinction coefficient at 419 nm of 191000 M−1.cm−1 [Cell pellets were resuspended in 10 mM sodium phosphate buffer, pH 6.0, before being lysed using an Avestin C3 Emulsiflex homogenizer. The cell lysate was cleared by centrifugation at 38000 M−1.cm−1  and stor3+) form by the addition of excess potassium ferricyanide, while under constant illumination under a strong but low temperature light source that acts to photolyze the CO from the ferrous iron. The ferricyanide was then removed by gel filtration down a PD-10 column . The deoxyHb form was made by addition of a slight excess of sodium dithionite to the metHb form. This was then applied to a PD-10 column to generate oxyHb.Unless stated otherwise, all optical spectra were taken using a Cary 5000 spectrophotometer (Agilent). To produce the various different forms of Hb, the carbonmonoxyHb was first oxidized to the metHb  and 10 nM catalase, at 37°C, was monitored optically. The oxyHb concentrations were calculated using the extinction coefficients of 125000 (415 nm) and 14600 (577 nm) using the units M−1.cm−1 . Time co−1.cm−1 at 405 nm for the H2O bound high-spin form at pH ~7. The time courses (401–418 nm) were fitted to double exponential functions.The metHb (4 µM) was incubated with hemopexin (4.5 µM) obtained from human plasma (Sigma) in 70 mM sodium phosphate buffer, pH 7.2, at 37°C. The concentration of the metHb proteins were calculated optically using the extinction coefficient of 184000 M2O2 and incubated overnight in 20 mM sodium phosphate buffer, pH 7.4 at 25°C. All samples were processed and trypsinized using standard procedures. LC-MS/MS analysis and targetted quantitative proteomics were utilized to identify and quantitate oxidative modifications in both Hb samples. All data were performed in triplicate on a Q-Exactive mass spectrometer (Thermo Scientific) coupled to a Proxeon HPLC system. MS/MS spectra were initially searched against the human database supplemented with the above recombinant sequences using both Protalizer software  and the Mascot database search algorithm (Matrix Science) to confirm sequence identity and identify unmodified and oxidized version of ‘hot spot’ peptides; all oxidized peptide reproducibly identified from database searches were then quantitated. Extracted ion chromatograms (XICs) of modified (and unmodified) tryptic peptides were used to quantitate oxidative differences. For relative quantitation, the ratio of each oxidized ‘hot spot’ peptide was calculated based on the sum of the XIC peak area of all forms (oxidized and unmodified) to be 100%. Hotspot residues used for oxidative comparisons included only conserved residues found on β and γ. All other ‘hotspot’ containing peptides identified in the present study were consistent with previously published data.HbA and HbF proteins were treated with incremental doses  of H2O2 were reacted with 10 µM metHb in a rapid mixing stopped-flow diode array spectrophotometer (Applied Photophyiscs) in 10 mM sodium phosphate buffer, pH 7.2 at 37°C. For each concentration of H2O2, three reactions were carried out, and the time courses generated averaged to a single rate trace and then analyzed. The time courses (552–630 nm) were fitted to double exponential functions using the fitting program incorporated within the instrument. The contribution of the absorbance for both phases and for all the kinetic traces generated was approximately the same. The two rate constants were then plotted against H2O2 concentration and straight lines of best fit applied to the data points.Varying concentrations of H2O2 at 25°C for ~10 min to produce ferrylHb (Fe4+). The reaction of metHb proteins with H2O2 was monitored optically to ensure 100% ferryl formation. Trace catalase was added to remove excess H2O2 and this was incubated for a few seconds to fully react. Sodium ascorbate was then added in a 1:1 volume ratio so that final concentration of Hb was 5 µM. The reactions were then followed to completion, optically, using an Agilent 8453 diode array spectrophotometer. The time courses (425–406 nm) were fitted to double exponential functions minimizing the least squares using Microsoft Excel Solver. For each time course, the two calculated rate constants were assigned to the reactions of the α and β/γ subunits, and the data plotted as a function of reductant concentration for each protein. This ascorbate concentration dependent kinetic profile was fitted to a rectangular hyperbola plus a straight line (α subunits) or a single rectangular hyperbola (β/γ subunits).MetHb (10 µM) in 70 mM sodium phosphate buffer, pH 7.2, was reacted with 30 µM HMetHb (20 µM) in 70 mM sodium phosphate buffer, pH 7.2, was reacted with a 1:1 volume ratio with sodium ascorbate at 25°C so that the final concentration of Hb was 10 µM and ascorbate was 0.1 or 10 mM. The time courses (577–630 nm) were fitted to a single exponential function.The proteins were made and maintained in their deoxy states by addition of an excess of the reductant sodium dithionite to metHb. DeoxyHb (10 µM) was reacted with sodium nitrite of varying concentrations in 70 mM sodium phosphate buffer, pH 7.2 at 24°C. The reactions were monitored optically using an Agilent 8453 diode array spectrophotometer. The time courses (432–413 nm) were fitted to a single exponential function minimizing the least squares using Microsoft Excel Solver. The data were plotted as a function of nitrite concentration for each protein and the second order rate constants were determined by fitting to a straight line.−1.cm−1 at 250 nm . The ProliNONOate was then diluted into thoroughly degassed 70 mM sodium phosphate buffer, pH 7.2. 10 μM oxyHb was reacted 1:1 with varying concentrations of ProliNONOate in a rapid mixing stopped-flow spectrophotometer (Applied Photophyiscs). Due to the speed of the reaction, the temperature was set to 15°C. Reactions were monitored at 422 nm and fitted to a single exponential. The data were plotted as a function of NO concentration for each protein and the second order rate constants were determined by fitting to a straight line.An NO solution was prepared by dissolving the NO donor ProliNONOate  in 25 mM NaOH. The concentration of ProliNONOate was determined using an extinction coefficient of 8500 Mα-phosphatidylcholine (5 mg/ml) derived from soybean  in 10 mM sodium phosphate buffer, pH 7.2, was sonicated in a water bath for ~5 min until no particulates could be seen. To produce unilamellar liposomes of uniform diameter, this suspension was then passed through a Northern Lipids liposome extruder containing a membrane with size cutoff 100 nm (Whatman) for a minimum of ten times. Liposomes were stored at 4°C and used within 4 h.MetHb or oxyHb (2 µM) was incubated with 200 µg/ml liposomes, for 10 h at 25°C. Sodium ascorbate was added at a final concentration of 50 µM as indicated. Lipid oxidation was monitored by following the production of conjugated dienes using a Tecan Infinite M200Pro plate reader. The time courses (234–650 nm) were plotted and used to determine the lag time before the onset of lipid oxidation.The lipid hydroperoxide 13S-hydroperoxy-9Z,11E-octadecadienoic acid (HPODE) was produced as previously described . HPODE , a primary cell line, was obtained from Lonza. Cells were maintained in complete primary cell EGM medium (Lonza) in a humidified atmosphere with 5% COPrior to all treatments, cells were gently washed with warm PBS and the medium was replaced by serum and phenol-free EGM medium for HUVECs. Cells were treated by adding either 50 µM Hb (recombinant adult Hb (rHbA) and recombinant fetal Hb (rHbF) in oxy or met forms), 50 µM ascorbate, or 10 mU/ml glucose/glucose oxidase system (GOX) to the medium in the total volume of 250 µl. Cells were placed back into the incubator and harvested after either 4 or 24 h as indicated. All experimental conditions were performed in four replicates.MetHb proteins were prepared as previously stated. The highly concentrated oxyHb proteins required for addition to the cells were prepared by incubating carbonmonoxyHb under bright constant illumination while gently blowing a stream of pure oxygen over the surface of the liquid, on ice. Conversion into oxyHb form was monitored spectrally and was completed by ~30–45 min.Cellular damage was assessed by measuring levels of lactate dehydrogenase (LDH) released into cellular medium. The LDH assay (Sigma–Aldrich) was performed after 24 h of exposure to the experimental treatment according to manufacturer’s instructions. The absorbance at two wavelengths (450 and 650 nm) was obtained using a Tecan Infinite M200Pro plate reader and both values were used to calculate levels of LDH.The cellular response to oxidative stress in treated cells was evaluated by activity of SOD. The SOD assay (Sod OxySelect superoxide dismutase activity assay kit (Cell Biolabs Inc.)) was performed according to manufacturer’s instructions 4 h post treatment on lysed cells. The absorbance values at 490 and 650 nm were taken and the level of SOD activity calculated.n replicate experiments  or mean and S.E.M. derived from non-linear curve fitting of n points in Kaleidagraph version 4.5.2 . The specific test used for each measurement is indicated in HbA was compared with HbF under the same experimental conditions. Data are presented as either mean and SD of The results of all experiments performed to compare rHbA and rHbF are summarized in rHbA and rHbF were expressed and purified as described in ‘Methods’ section. Gel electrophoresis was used to confirm purity of Hb . The HPLC of the two recombinant proteins  shows that no significant amount of protoporphyrin-IX was present as can occur with lack of iron. We did not observe any statistical differences in the yields between rHbA and rHbF . HoweverOxygen binding curves were measured for our preparations of rHbA and rHbF. Analysis of these curves allowed calculation of the p50 and Hill coefficient values . Our resThe autoxidation of HbA and HbF was measured at 37°C for a 3-h period in the presence of SOD and catalase. The time course (406–500 nm) was fitted to a single exponential; the rates of autoxidation of rHbA and rHbF were not significantly different . Heme lo2O2 and the second-order rate constants for the conversion of metHb into ferrylHb were calculated  levels of ascorbate the ferryl iron in the β subunit is more readily reduced by ascorbate than ferryl iron in the γ subunit.The ferryl reduction kinetics of rHbA and rHbF were compared in the presence of differing concentrations of ascorbate. The time courses for the reduction were fitted to double exponential functions and the two rates assigned to the α or β/γ subunits of rHb. There was a slight decrease in the autoreduction rate for rHbF compared with rHbA . The kinThe ferric reduction kinetics of rHbA and rHbF were measured by reaction of metHb to oxyHb with high and low ascorbate concentrations. Spectral changes were observed consistent with the conversion of the metHb into the oxyHb forms A. The tiThe nitrite reductase activities of rHbA and rHbF were compared by measuring the reaction of deoxyHb with sodium nitrite. The resulting kinetic traces (432–413 nm) were fitted to a single exponential and plotted against nitrite concentration . These dThe NO dioxygenase activity of rHbA and rHbF was compared by measuring the conversion of oxyHb into metHb at varying concentrations of NO. The resulting kinetic traces (422 nm) were fitted to a single exponential function and plotted against NO concentration . These d2O2 has on the observed post-translational oxidation of oxidative hotspots in recombinant HbA and HbF. Toward this goal, we utilized quantitative MS to target all peptide charge states. XICs were generated from the most abundant monoisotopic peak of each peptide isotopic profile and the resulting ratio differences were compared for oxidized and unoxidized hotspot peptides.Experimental oxidative conditions were performed to test the role H2O2 increases. For example, 10× H2O2 resulted in nearly a ten-fold higher ratio for HbA C93 oxidation and five-fold higher ratio for HbF compared with the control where no peroxide was added. The data in As purified  β/γ C93 The lipid oxidation of the metHb and oxyHb forms of rHbA and rHbF with and without reductant was compared . In the Cell viability due to cellular membrane damage was measured (24 h post treatment) by LDH release, while short term (4 h post treatment) oxidative stress was measured by SOD induction. Hydrogen peroxide addition (via a GOX) was used as a positive control and caused significant increases in both assays . VaryingDifferent redox states of rHbA and rHbF were then tested. Our detailed comparison of rHbA and rHbF revealed some differences that could affect their ability to be an effective component of an HBOC.Using our expression system we were able to produce similar yields of adult and fetal Hb in shake flasks, not inconsistent with historical studies . HoweverIn vivo, HbF has a higher oxygen affinity than HbA in order to enable the fetus to capture oxygen from the maternal circulation. However, in contrast with some organisms, in humans this difference is not an intrinsic property of the functional tetramer, but instead by a well-characterized modulation of the binding of the physiological effector molecule bisphosphoglycerate (BPG) [te (BPG) . This iste (BPG) , we obsete (BPG) . In this3+−O2•−) nature of the iron-oxygen bond in oxyHb, all else being equal, one might expect the oxygen affinity to vary inversely with the rate of autoxidation in globins with very high oxygen binding affinity corresponding to low autoxidation. This relationship does indeed hold for a variety of mutations in the myoglobin heme pocket that stabilize or destabilize the Fe3+−O2•− bond; mutations that stabilize the bond increase oxygen affinity and decrease autoxidation [2+−O2 and Fe3+−O2•−. A heme modification that shifts the resonance toward the Fe2+−O2 form results in an increase in both the O2 affinity and a decrease in autoxidation [Outside the red blood cell, oxyHb is oxidized easily to metHb which is physiologically inactive . MetHb ixidation . Intriguxidation . UnderstThe rate of heme release  from Hb Outside the cell, the dominant reaction regenerating oxyHb from metHb is the non-enzymatic reduction by plasma ascorbate . ReductiIn summary, both proteins have advantages and disadvantages. The oxy forms autoxidize at a similar rate. The resultant metHb is more readily reduced back to oxyHb for the adult protein. However, as long as it remains in the ferric state, the adult protein is more likely to lose its heme cofactor.3+, the resultant metHb can be further oxidized by peroxide(s) to the Fe4+ ferryl species. Lacking protective catalase, in the plasma levels of peroxide can increase under stress conditions such as tissue injury; therefore, extracellular Hb is potentially more susceptible to damage by peroxide and ferryl formation. The ferryl Hb species is known to be damaging in vivo [Once autoxidized to Fe in vivo , generat in vivo ,49. It w in vivo .KM for the low affinity pathway of the β/γ subunits was four times higher for fetal than adult meaning rHbF is less able to remove ferryl Hb via reduction by ascorbate. As it is possible to engineer increases in this rate as desired by the insertion of redox active tyrosine residues into the β subunit [Once ferryl Hb has been formed, the ferryl heme can be reduced to the met form by a range of compounds and reductants ,33,50,51 subunit ,47,50 inThe NO dioxygenase activity of oxyHb (oxidation to met) means that cell-free Hb rapidly scavenges NO, causing vasoconstriction and an increase in blood pressure ,53. Our Nitrite reduction by deoxyHb generates NO, initially binding to deoxyHb but eventually being released as NO gas resulting in vasodilation . Thus thPreviously it has been shown that βC93 is the prominent end point for free radical induced protein oxidation; oxidation at other residues  is usually lower . Our datIt is not clear what implication differences in amino acid oxidizability have for HBOC. The amino acids in fetal Hb seem less likely to be oxidized by peroxide; yet fetal Hb reacts as fast with peroxide and the ferryl and ferric states are less readily detoxified by reductants. Oxidants have to go somewhere; it could be argued that, in sacrificing its own amino acids and heme, the adult protein is less likely to damage external biomolecules. On the other hand, the features of fetal Hb (decreased Hb amino acid oxidation and decreased reactivity to reductants) mirror the effects of adding haptoglobin to Hb which is known to protect against Hb-induced oxidative damage such as lipid oxidation . We therThese experiments used liposomes formed from phosphatidylcholine, containing small amounts of lipid hydroperoxides, which react with hemoproteins as described previously . The lipThe reaction of Hb with the lipid peroxide HPODE is a complex one that leads to degradation of the heme and destruction of conjugated dienes of the lipid . Our expCytotoxicity of extracellular Hb molecule through its redox cycling reactions and generation of reactive oxidative species is well documented ,66. HUVE2O2, a potent oxidizing agent that creates substantial oxidative stress [The addition of 10 mU GOX to cellular medium generates He stress . This poThe combined Hb and GOX treatment data showed increased cellular damage and oxidative stress compared with rHb only, but decreased or similar damage compared with GOX alone, i.e. the effects of GOX and rHb are not additive in this system. This reflects the ‘Janus face’ of Hb interactions with added peroxide in cellular systems. Hb acts as a peroxidase via the formation of intermediate ferryl iron and protein bound free radicals . In certA direct-paired comparison (Supplementary Table S1) revealed very few significant differences between adult and fetal rHb. Where a difference was found, rHbF was found to be less cytotoxic than rHbA. The reactivity of fetal and adult Hb seem to vary with the assay system. In cells (the present paper) and when added to DNA , fetal HRecombinant human adult and fetal Hb are both suitable starting materials for producing a HBOC. While the core reactivity or rHbA and rHbF differ, the direction of difference is sometimes in favor of fetal and sometimes in favor of adult. In most cases, additional mutations and/or the subsequent treatment of the protein to enhance vascular lifetime  will likely have a larger effect than the original difference between the β and γ chains.


Stress signals during sucking activity such as nasal flaring, head turning, and extraneous movements of the body have been attributed to incoordination of sucking, swallowing, and respiration (SSR) in premature infants. However, the association of uncoordinated sucking pattern with developmental outcomes has not yet been investigated. The aim of this study was to investigate whether uncoordinated sucking pattern during bottle-feeding in premature infants is associated with the developmental outcomes at 8–12 and 18–24 months of age (corrected for prematurity).We retrospectively reviewed the medical records and video recordings for the Neonatal Oral-Motor Assessment Scale (NOMAS) of premature infants and divided them into two groups based on the presence or absence of incoordination. The Bayley-III cognition composite scores of the incoordination-positive and incoordination-negative group were compared at 8–12 and 18–24 months of age.n = 22) and incoordination-negative groups (n = 48), respectively (p = 0.002). The average Bayley-III cognition composite scores at 18–24 months were 90.0 ± 17.9 and 100.7 ± 11.5 for the incoordination-positive (n = 21) and incoordination-negative groups (n = 46), respectively (p = 0.005). A multiple linear regression analysis indicated that the presence of uncoordinated sucking pattern, grade 3 or 4 germinal matrix hemorrhage–intraventricular hemorrhage, and moderate to severe bronchopulmonary dysplasia were independently associated with cognitive development at 18–24 months of age.Seventy premature infants exhibited a disorganized sucking pattern according to the NOMAS. The average Bayley-III cognition composite scores at 8–12 months of age were 92.5 ± 15.6 and 103.0 ± 11.3 for the incoordination-positive (Uncoordinated sucking pattern in premature infants was independently associated with a higher risk of abnormal developmental outcome in the cognitive domain of the Bayley-III at both 8–12 and 18–24 months. There may be a need for periodic follow-up and early intervention for developmental delay when incoordination of SSR that results in stress signals on the NOMAS is observed before 40 weeks postmenstrual age. Feeding skills in a newborn requires complex functions that are directed by the central nervous system (CNS), including the coordination of sucking, swallowing, and respiration (SSR) –4. PreteTwo hypotheses exist regarding the difficulty in sucking encountered by neonates: (i) CNS immaturity that is self-limiting as the child ages and (ii) neurologic dysfunction due to disruption of the CNS , 11–14. The Neonatal Oral-Motor Assessment Scale (NOMAS) is a noninvasive assessment tool to distinguish a dysfunctional or disorganized sucking pattern from a normal sucking in clinical practice , 16. A dPrevious studies have suggested that some items belonging to the disorganized sucking patterns could be more relevant to neurologic dysfunction , 20. RecPalmer et al.  considerThe aim of this study was to investigate whether uncoordinated sucking pattern during bottle feeding in premature infants is associated with the developmental outcomes at 8–12 and 18–24 months of age (corrected for prematurity).We performed a retrospective review of the medical records of premature infants born between January 2014 and December 2016 at Seoul National University Hospital (SNUH) and referred for consultation to the Division of Pediatric Rehabilitation for sucking difficulty. The results of the NOMAS evaluation were incorporated into the electronic medical records, which were analyzed retrospectively by the authors. We included those infants who were born very premature (< 32 weeks) or very low birth weight (BW) (< 1500 g), assessed as having a disorganized sucking pattern in the NOMAS before 40 weeks postmenstrual age (PMA), and evaluated using the cognitive domain of the Bayley Scale of Infant Development, third edition (Bayley-III) , at 8–12All infants born earlier than 32 weeks gestational age (GA) or less than 1500 g with feeding difficulty had been referred to the Division of Pediatric Rehabilitation, and an occupational therapist evaluated their NOMAS score within 72 h from commencement of feeding in the hospital where this study was conducted. The evaluation was performed by analyzing the video recording of sucking activity . Video rFor this study, the disorganized sucking pattern was divided into three clusters  according to the cluster system presented by the Dutch group, as shown in Table Premature infants included in this study were evaluated using the Bayley Scales of Infant Development, third edition (Bayley-III), cognition composite score at 8–12 and 18–24 months of age (corrected for prematurity). In addition to 18–24 months of corrected age, 8 to 12 months corrected age was chosen because it is known to be a good time to identify the suspicion or presence of cerebral palsy or other neurologic abnormality . It is aThrough a retrospective electrical medical record review, GA, sex, brain sonographic finding , PMA at the time of NOMAS evaluation, small for gestational age (SGA) or appropriate for gestational age (AGA), severity of bronchopulmonary dysplasia (BPD), birth weight (BW), development of sepsis, and 5 min Apgar score were obtained.Cohen’s kappa was obtained for the interrater reliability of the two evaluators. The cognitive domain of Bayley-III was compared between the incoordination-positive (cluster 4) and incoordination-negative groups (clusters 2 and 3) at 8–12 and 18–24 months of age using the independent t-test. Pearson’s correlation coefficient r was calculated between continuous variables (GA and BW) and cognition composite score at 18–24 months. Multiple linear regression was performed with the Bayley-III cognition composite score at 18–24 months as the dependent variable. Analyses were performed using IBM SPSS version 20 software . A probability value < 0.05 was considered significant in all analyses.n = 70) are shown in Table A total of 71 premature infants had both a Bayley-III cognitive domain and NOMAS score. One premature infant belonging to cluster 5, who had a grade 3 GMH-IVH and was a cardiopulmonary resuscitation survivor, showed delayed cognitive development at 8–12 months of age and was excluded from the analysis since the infant did not belong to the disorganized sucking pattern in the NOMAS cluster system. Clinical characteristics of the premature infants included in the analysis . Disagreement occurred between clusters 2 and 3 (1 infants) and between clusters 3 and 4 (4 infants). The reliability of the two evaluators on the presence of incoordination items (cluster 4 vs. clusters 2 or 3) was higher with a Cohen’s kappa value of 0.864, with four disagreements being documented.n = 22) and incoordination-negative groups (n = 48), respectively  and incoordination-negative groups (n = 46), respectively  and 5-min Apgar score  were found to be significantly correlated with Bayley-III cognition composite score at 18–24 months. All clinical variables were included in the multiple linear regression analysis model with stepwise selection to control multicollinearity between independent variables. In the multiple linear regression analysis, the R2 value of the final model was 0.331, and the variables included in this model were the presence of uncoordinated sucking pattern, grades 3 or 4 GMH-IVH, and moderate to severe BPD  were less relevant to neurodevelopmental outcomes. However, if those symptoms persist during the post-term period, the clinical relevance could be changed. For example, Wolthuis-Stigter et al.  reportedUncoordinated sucking pattern that results in stress signals  in premature infants was independently associated with a higher risk of abnormal developmental outcome in the cognitive domain both at 8–12 and 18–24 months. There might be a need for periodic follow-up and early intervention for developmental delay when incoordination of SSR that results in stress signals in NOMAS is observed before 40 weeks PMA.


Augmentation of fetal hemoglobin (HbF) production has been an enduring therapeutic objective in β-thalassemia patients for which hydroxyurea (HU) has largely been the drug of choice and the most cost-effective approach. A serum metabolomics study on 40 patients with β-thalassemia prior to and after administration of HU was done along with healthy controls. Treated patients were divided further into non-responders (NR), partial (PR) and good (GR) per their response. 25 metabolites that were altered before HU therapy at p ≤ 0.05 and fold change >2.0 in β-thalassemia patients; started reverting towards healthy group after HU treatment. A prediction model based on another set of 70 HU treated patients showed a good separation of GR from untreated β-thalassemia patients with an overall accuracy of 76.37%. Metabolic pathway analysis revealed that various important pathways that were disturbed in β-thalassemia were reverted after treatment with HU and among them linoleic acid pathway was most impactfully improved in HU treated patients which is a precursor of important signaling molecules. In conclusion, this study indicates that HU is a good treatment option for β-thalassemia patients because in addition to reducing blood transfusion burden it also ameliorates disease complications by shifting body metabolism towards normal. Nearby birth, this HbF is substituted largely by HbA as a result of gene expression switching from γ to β (beta) globin chain2. However, infants suffering from β-thalassemia lack functional β globin due to loss of function mutations in HBB gene, fail to produce normal adult hemoglobin (HbA) and start showing signs and symptoms of the disease3. Imbalance in the α/β-chain ratio is a hallmark of β-thalassemia that can be reduced by compensating defaulted chain of the β-globin molecule with increased production of the γ-globin that ultimately form HbF4. This HbF induction limits the need for blood transfusion along with iron chelation to prevent complications related to iron overload by transfusion therapy6 and also diminishes need of potentially risky treatment option i.e. transplantation of allogenic bone marrow stem cells8.Fetal hemoglobin (HbF) is a type of hemoglobin tetramer that consist of two α and two γ chains. During the development of fetus it plays the main role as oxygen transporter13. Among all these agents hydroxyurea (HU) is a Food and Drug Administration (FDA) approved HbF inducer14. A score of studies have identified that HU is well tolerated in clinical practice and can be implicated as an another option of β-thalassemia treatment17. HU is an antineoplastic agent used for myeloproliferative disorders. After being identified as a potent HbF inducer, HU became one of the key therapeutic agents for augmentation of HbF9 and it is also a cost effective approach as compared to other treatment options like bone marrow transplant and regular blood transfusion in conjugation with iron chelation costing US$3,000 per patient annually18. The most commonly accepted mechanism of HU is its cytotoxic effect resulting in stress erythropoiesis19. However, the exact mechanisms by which HU induces HbF production are not fully understood and is still controversial20. Also the response to HU therapy in β-thalassemia varies from patient to patient, some showed good respond to the therapy with hemoglobin maintained without any requirement of blood transfusions while some showed no difference in their hematological parameters22 as a result of which data on predictors of response remain inconsistent.Multiple γ-globin gene inducing therapeutic agents have been identified25. Previously it was identified that the metabolite profile of β-thalassemia patients significantly differs from healthy26. Studies have outlined the changes in metabolite profile of leukemia patients27 and fatty acid profile of β-thalassemia patients28 prior and after recieving HU therapy. However, no study has addressed the relation of β-thalassemia patient’s metabolome and metabolic pathways to the HU treatment. Though, this area can produce interesting and significant insights regarding effects of HU treatment on various metabolic pathways as various studies of metabolomics in association to pathway analysis have provided noteworthy findings32 also in analyzing response and dose of drug33. Therefore, in this study we aimed to overcome this lacking by finding out the metabolomics pattern changes of β-thalassemia patients after receiving HU treatment and to recognize the differential metabolites among variable responders i.e. non-responders (NR), partial responders (PR) and good responders (GR) to HU treatment.Currently, more than 200 causative molecular defects have been described so far in the β-globin gene causing β-thalassemia and also relation of some mutations have been found which respond to hydroxyureaHBB gene mutation analysis. β-thalassemia mutations were identified by polymerase chain reaction-amplification refractory mutation system (PCR-ARMS). Patients received HU for the treatment at a dose range of 16–20 mg/kg/d and after receiving treatment for at least 6–12 months, these patients were further divided into three groups per their response i.e. non-responders (NR), partial responders (PR) and good responders (GR). Patients whose Hb maintained at >7 g/dl after receiving HU and without further blood transfusion were grouped as good responders, likewise partial responders were those who exhibited 50% reduction while non-responders exhibited <50% reduction in the need of blood transfusion post treatment with HU. Volunteers for healthy sample collection were also recruited at Dr. Panjwani Center for Molecular Medicine and Drug Research (PCMD).The patients suffering with β-thalassemia for this study were selected in National Institute of Blood Disease and Bone Marrow Transplantation (NIBD), Karachi, Pakistan after the approval of the Institutional Review Board (IRB), ethic committee of the hospital  as per The International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use and Good clinical practice (ICH GCP) guidelines. Whereas the approval of experimental protocols was taken from the ethic committee of primary research institute  i.e. Independent Ethic Committee (IEC) . This research work has been done according to the ethical standards in the Declaration of Helsinki. Our study involved 40 β-thalassemia cases and their blood was collected before initiating and after receiving the treatment with HU and 70 samples of other patients treated with HU whose sample prior to treatment was not collected. Confirmed diagnosis of disease was performed by For starting HU therapy following inclusion was followed: Patient have been registered at NIBD, diagnosed as transfusion dependent β-thalassemia with Hb less than 7 g/dL, absence of or very low HbA amount with high HbF and blood transfusions >8/year, blood was collected before blood transfusion in case if needed along with fasting of 4–8 hours. Also, patients did not receive any therapy other than HU (at each collection other therapies were hold 15 days prior to sampling). Exclusion criteria included: Patients with HU hypersensitivity, any β-thalassemia unrelated other chronic illness evidence and unwillingness to enroll in the study or initiating therapy. Informed consent in written form was attained from all the participants involved in this work including healthy controls as well as patients or from their guardians.Collection of blood samples was done according to the ethical standards as laid down in the declaration of Helsinki. First sample was collected before starting HU therapy while second or treated sample was collected from patients after receiving 6–12 months of HU treatment in fasting. Near 5 cc of venous blood was drawn from each of the participant by venipuncture and collected in gel-based BD vacutainer tubes . Serum separation was achieved by centrifugation at 2000 rpm for 10 minutes at 4 °C; aliquoted and stored immediately at −80 °C till further processing of sample. A complete and thorough questionnaire was also filled from all the patients. Patients and healthy controls basic details are presented in Table 27 acid, N,O-bis(trimethylsilyl) trifluoroacetamide (BSTFA) with trimethylchlorosilane (TMCS) , methoxylamine hydrochloric , Pyridine  and Mill-Q/deionized water .Solvents of analytical grade were used for gas chromatography-mass spectrometric (GC-MS) analysis. Reagents and solvents included methanol, hexane , myristic-d34. Shortly, first proteins were precipitated by adding 800 µL of chilled methanol in 100 µL serum containing 20 µL of myristic acid (2 mg/mL) as internal standard. Resulting supernatant was further subjected to solid phase extraction (SPE) using a 96 well plate  under vacuum . After sample loading, the phase was washed with 300 µL of water and metabolites were eluted with 600 µL methanol. The eluent was finally dried in vacuum at room temperature and stored at 4 °C until analysis. Derivatization of dried samples was performed by addition of 50 µL methoxylamine hydrochloride (15 µg/ µL in pyridine) followed by addition of 50 µL BSTFA with 1% trimethylchlorosilane for formation of trimethylsilyl derivatives. Then samples were analyzed on GC-MS with minor modifications in previous method35. Initially the oven temperature was fixed at 50 °C for 1 min then temperature was raised in three steps. In first step temperature raised at a rate of 10 °C/min to 80 °C for 3 min then again 10 °C/min to 180 °C for 3 min and in final step 15 °C per min raise to 300 °C for 5 min. After maintaining the temperature at 300 °C for five minutes, a post run was applied by further increasing to 305 °C for 1 minute. Retention time was locked to the internal standard at 20.070 min. Electron impact ionization (EI) was ionization source for the GC-MS analysis at 70 eV. Data acquisition was done in full scan mode from 50–650 m/z in 0.5 seconds scan time. To limit the chances of cross contamination a blank was run in-between samples. Mass calibration was done with perfluorotributylamine (PFTBA).Details of protocol that is followed in our study for metabolomics sample preparation has been reported previously reported35. The GC-MS spectra were uploaded on Mass Profiler Professional (MPP) software 12.5 for multistep statistical processing of data as previously reported34. Statistical significance analysis was done using T-Test Unpaired for comparing 5 groups involved in study i.e. healthy as control group, HU untreated β-thalassemia patients and HU treated patients group which was further classified into GR, PR and NR. Using T-Test Unpaired and Benjamini Hochberg FDR as multiple testing correction, the fold change (FC) of 2.0 was applied to compare these groups. Tukey’s Honest Significant Difference (HSD) post Hoc test was then applied to identify metabolites that were accountable for significant differences and also that were common in these five groups. Hierarchical clustering was also executed by applying Pearson’s uncentered distance metric and complete linkage. A partial least squares discriminant analysis (PLS-DA) model was built for healthy versus HU treated and HU untreated β-thalassemia patients. Pathway analysis of altered metabolites was also carried out using Metaboanalyst 3.0 36 which is a web based software linked to huge databases such as KEGG (Kyoto Encyclopedia of Genes and Genomes) (http://www.genome.jp/kegg/)39 and HMDB (Human Metabolome Database) (http://www.hmdb.ca/).Agilent Mass Hunter Qualitative Analysis software (version B.04.00) was used for data processing. Parameters applied for peak integration and deconvolution parameters have been described previouslySerum metabolite profile of 40 β-thalassemia patients before HU therapy was compared with their metabolite profile after treatment, in addition 70 other samples of HU treated β-thalassemia patients and 60 samples of healthy volunteers were used as controls. In total 210 serum samples were analyzed by using GC-EI-MS. Statistical analysis and multivariate data investigation including hierarchical clustering, Tukey HSD post-hoc analysis and PLS-DA plot were carried out to detect comparative alteration of statistically significant metabolites in-between healthy and β-thalassemia patient samples prior to and after getting treatment with HU including further three groups i.e. NR (non-responder), PR  and GR (good responder).On total of 717 metabolites, significant testing with fold change analysis was carried out in this experiment. At the level of p ≤ 0.05 and FC > 2, a list of 25 compounds was produced in which some were up and down-regulated in β-thalassemia patients in comparison to other 4 groups. Briefly, 11, 8, 10 and 11 metabolites were down regulated while, 14, 17, 15 and 14 were up regulated in GR, PR, NR and healthy, respectively in comparison to their sample prior to HU treatment. Out of twenty-five thirteen metabolites; geraniol, linoleic acid, phthalic acid, lauryl iodide, glycerol, M-pyrol, triethanolamine, palmitic acid, boric acid, heptadecane, decane, stearic acid and 2-ethylhexyl hexyl sulfite; were recognized putatively by relating the mass spectral peaks with the spectral data available in the National Institute of Standards and Technology (NIST) mass spectral (Wiley registry NIST 11) library at similarity index parameter of ≥70%. The difference in the pattern of significantly differentiated metabolites in β-thalassemia patients post receiving HU treatment can be seen in Fig. Tukey’s HSD post Hoc test was also applied to find significantly expressed metabolites among groups and its summary is shown in Table Hierarchical clustering was done using average intensities of twenty-five differentiating metabolites. The five groups were clustered into four classes Fig. . GR and A prediction model using another set of 70 samples of HU treated group along with healthy and HU untreated group was built by multivariate data analysis. This model included 25 GR, 23 PR, 22 NR, 64 HU untreated and healthy samples. Based on statistically differentiating as well as important metabolites that also have difference in expression between these five clusters, samples were grouped into distinct classes by supervised partial least squares discriminant analysis (PLS-DA). Plots of PLS-DA scores are given in Fig. To identify disturbed pathways of metabolism attributable to altered metabolites in serum of four groups in comparison to β-thalassemia samples before HU treatment. The pathway analysis summary formed on the basis of dysregulated metabolites are shown in Fig. 42. Linoleic acid is required in the biosynthesis of prostaglandins and cell membranes and its abnormal levels have been found in cirrhosis43, hypertension44 and cancers45. In β-thalassemia samples it is most possibly increased due to inflammation, oxidative damage and increased red blood cell (RBC) membrane turn over, but its level reduced to normal after HU treatment in all types of responders as these complications started resolving. Palmitic and stearic acids are involved in multiple metabolic pathways such as plasmalogen synthesis, β-oxidation of fatty acids, bile acid and fatty acid biosynthesis etc. These two fatty acids are also important for maintaining dynamics of cell membranes and their decrease in body further result in reduced strength of RBCs membrane, as HU decreases RBCs degradation leading to improve membrane integrity therefore the levels of these two fatty acids are also returned to normal post treatment with HU. Glycerol molecules can be converted into glucose by liver to meet the body’s energy requirements. Thus, it is logical that after treatment with HU the metabolic stress is reduced in β-thalassemia patients so less glycerol is consumed for energy production and its serum levels went back to normal. Geraniol possesses anti-oxidant with anti-inflammatory activity and in healthy and HU treated samples it is decreased as compared to the HU untreated ones. Although it is an exogenous metabolite but due to oxidative stress in β-thalassemia its uptake increased in blood. Because HU treatment reduces oxidative stress and inflammation46 therefore geraniol levels were more in β-thalassemia before treatment as compared to treated group to combat oxidative and inflammatory damage in disease. Altered levels of M-pyrol are seen in urinary tract infections, common complication of β-thalassemia because of predisposing factors. HU therapy reduces these predisposing factors, so all HU treated β-thalassemia without regarding to their response have M-pyrol levels closer to healthy individuals. Decane and lauryl iodide are found in cell membranes and their abnormal concentrations have been found in fatty liver diseases and infections. We have found that HU treated patient’s metabolome pattern of these two metabolites was like healthy persons. Heptadecane belongs to the family of acyclic alkanes and is found in membranes of cell. It is one of the metabolite whose levels were different among healthy and GR along with NR however similar in PR.In this study we have compared the metabolites pattern of β-thalassemia patients prior to and after receiving treatment with HU for 6–12 months to induce HbF. Overall, most of the metabolites in serum of HU treated patients have quite similar pattern of regulation but difference was found in their intensities as compared to their sample before treatment with HU. The possible role of metabolites having common pattern in all HU treated groups can be defined by consulting to the HMDB47 but we didn’t found any of these pathway directly involved in causing pathogenesis of β-thalassemia in our study. So, it will be reasonable to state that the pathways altered are significantly involved in complicating β-thalassemia and are not related to other types of anemias.In our pathway analysis, linoleic acid, glycerolipid and fatty acid metabolism were most affected whereas metabolites blamable for these abnormalities are linoleic acid, glycerol and palmitic acid respectively. Glycerol and palmitic acid are involved in more than one pathway, so it indicates that alteration of these two metabolites caused changes in galactose metabolism, fatty acid biosynthesis and elongation in mitochondria, respectively in addition to above mentioned pathways. Although in anemia the pathways which are most commonly affected include glycolysis, the oxidative pentose phosphate pathway (OPPP), the glutathione cycle, nucleotide metabolism and MetHb reductaseLinoleic acid pathway was most impact fully improved in HU treated patients. It is an essential poly unsaturated fatty acid (PUFA) for humans as it is not synthesized in body and plays important role by producing hormone like lipids that act as signalling molecules and induce inflammation and blood clotting. Although, altered levels of linoleic acid have been reported in multiple disorders, but it is correlated mostly with cardiovascular diseases. As β-thalassemia patients suffer from iron overload so in these patients linoleic acid metabolism was increased as a cardio protective agent. In addition, increase RBCs production and increased inflammatory response has been associated with transfusion dependent β-thalassemia patients. Therefore, these two factors are also likely to be responsible for elevated metabolic pathway of linoleic acid as it produces inflammatory mediators and to overcome RBC degradation. But when HU was given to these patients it ameliorated all three complications therefore linoleic acid metabolism also revert to normal as in healthy individuals. Glycerolipid and fatty acid metabolism was also augmented for compensating need of fatty acids but when this need is subsided by HU treatment, so these pathways also return to normal level. Comprehensively we can state that metabolic stress reduces in patients with β-thalassemia after receiving HU therapy which consequently result in normal metabolism of various altered pathways.In conclusion, this study showed that hydroxyurea therapy in patients with β-thalassemia restores disturbed metabolic profile to normal in addition to its reported reduction in need for blood transfusion. Our study established that serum metabolite profiling by using GC-EI-MS can be used for the establishment of a profile that can indicate weather hydroxyurea in β-thalassemia patients is effective and it should be continued or not which means that the metabolism is reverting towards normal or not because not only good responders, but also partial and somewhat non-responders showed inclined metabolic pattern towards healthy. Furthermore, our study is the first one to identify and describe metabolomic differences in the serum of healthy individuals and patients with β-thalassemia before and after receiving hydroxyurea an understanding that can be used to assess disease prognosis and response to treatment as well as supporting that hydroxyurea is a good choice for β-thalassemia sufferers.Supplementary Information


CUT&RUN is an efficient epigenome profiling method that identifies sites of DNA binding protein enrichment genome-wide with high signal to noise and low sequencing requirements. Currently, the analysis of CUT&RUN data is complicated by its exceptionally low background, which renders programs designed for analysis of ChIP-seq data vulnerable to oversensitivity in identifying sites of protein binding.http://seacr.fredhutch.org) for plug-and-play analysis with SEACR that facilitates maximum accessibility across users of all skill levels.Here we introduce Sparse Enrichment Analysis for CUT&RUN (SEACR), an analysis strategy that uses the global distribution of background signal to calibrate a simple threshold for peak calling. SEACR discriminates between true and false-positive peaks with near-perfect specificity from “gold standard” CUT&RUN datasets and efficiently identifies enriched regions for several different protein targets. We also introduce a web server  contains supplementary material, which is available to authorized users. Eukaryotic DNA is wrapped in millions of nucleosomes that restrict access of thousands of DNA binding proteins, including transcription factors (TFs) that bind to enhancers and promoters to activate or repress gene expression and often specify cell fate . DetermiStandard ChIP-seq data analysis often involves “peak calling” algorithms, which identify genomic regions at which target ChIP-seq signal is enriched in comparison with background noise from a control DNA input or non-targeting antibody experiment . Such alIn contrast with ChIP-seq, CUT&RUN is an in situ epigenome profiling technique that uses an antibody-targeted micrococcal nuclease (MNase) fusion protein to selectively digest and liberate DNA fragments at sites of protein binding while leaving the remainder of the genome behind; thus, it features exceedingly low background in comparison with ChIP-seq , 11. TheHere we introduce Sparse Enrichment Analysis for CUT&RUN (SEACR), a peak caller designed for the processing of paired-end CUT&RUN data. SEACR is model free and empirically data driven and therefore does not require arbitrary selection of parameters from a statistical model. Moreover, we show that SEACR retains superior selectivity versus common ChIP-seq peak callers from CUT&RUN data, while retaining competitive performance across a range of experimental configurations. Finally, we have made SEACR available to the community through a simple web interface. We conclude that SEACR is fast, accurate, scalable and simple to use for the analysis of CUT&RUN data.To address the problem of oversensitivity in CUT&RUN peak calling, we developed Sparse Enrichment Analysis for CUT&RUN (SEACR), a peak calling algorithm that enforces precision from sparse data by quantifying the global distribution of background signal and using it to set a stringent empirical threshold for peak identity. CUT&RUN data from target antibody and IgG control experiments are first parsed into signal blocks representing segments of continuous, nonzero read depth by fragment spanning read pairs, and the signal in each block is calculated by summing read counts Fig. a. A plot10(FDR) for MACS2, and “Peak Score” for HOMER) and calculated areas under the curve (AUPR). SEACR AUPR was competitive with MACS2 and HOMER for all datasets interrogated and outperformed both of them across all read subsampling levels for CTCF . The provision of a control IgG dataset is recommended for general use and is used in the remainder of the manuscript. Second, we implemented “stringent” and “relaxed” peak selection modes (default = stringent), which correspond to the threshold at which the maximum percentage of target versus IgG signal blocks are retained, or a threshold halfway between the maximum and the “knee” of the target percentage curve, respectively Fig. a.Fig. 2STo test how well SEACR can avoid false-positive peaks in a CUT&RUN dataset in which such distinctions are known, we used SEACR, MACS2, and HOMER to call peaks from CUT&RUN data for two transcription factors (TFs), Sox2 and FoxA2 in human embryonic stem cells (hESCs) and definitive endoderm (DE) cells. Sox2 expression is restricted to hESCs, and FoxA2 expression is restricted to DE cells . All thr10 FDR threshold of greater than 10 as a stringent “truth set”. In both stringent and relaxed modes, SEACR consistently maximized the fraction of called peaks that were inside the test set (precision), with all tests in stringent mode and most in relaxed mode surpassing 85% precision  threshold of greater than 10, and recalculated F1 scores in comparison with SEACR. Although the more stringent MACS2 peak calls had improved performance above 10 million fragments, performance suffered at fragment subsampling levels below 10 million reads, rendering SEACR superior at those levels  from an H3K27me3 CUT&RUN dataset using K562 cells  that conTo evaluate SEACR’s run time and memory usage in comparison with other peak callers, we measured run time, average disk read memory, and average disk write memory for instances of H3K27me3 peak calling described above. SEACR was superior or competitive with all peak callers tested in all three metrics Fig. a–c. Notahttp://seacr.fredhutch.org) for plug-and-play analysis of CUT&RUN data  was added to stop the reaction, and fragments were released by 30-min incubation at 37 °C. Samples were centrifuged 5 min at 16,000×g, and supernatant was recovered and DNA extracted via phenol–chloroform extraction and ethanol precipitation. Resulting DNA was used as input for library preparation as previously described [CUT&RUN was performed as previously described . Brieflyescribed . Antibodhttps://genome.ucsc.edu/goldenpath/help/bedgraph.html) that omits regions containing 0 signal; (2) control (IgG) data bedgraph file; (3) “norm” denotes normalization of control to target data, “non” skips this behavior; (4) “relaxed” uses a total signal threshold between the knee and peak of the total signal curve and corresponds to the “relaxed” mode described in the text, whereas “stringent” uses the peak of the curve and corresponds to “stringent” mode; (5) prefix for output file.SEACR was designed to call enriched regions from sparse CUT&RUN data, in which background is dominated by “zeros” . SEACR takes as input the following five fields: (1) target data bedgraph file in UCSC bedgraph format  multiplied by its bedgraph signal (column 4):t, we identified the value corresponding to the maximum value of F for the following function:T is the maximum total signal value in any signal block, ri is the total signal for an element i in the set of m target signal blocks, sj is the total signal for an element j in the set of n target or control signal blocks, and F is the fraction of target signal blocks divided by total signal blocks remaining above threshold t. Once t is established, all target signal blocks exceeding t that do not overlap a control signal block that also exceeds t are retained. For “relaxed” mode, we identified the negatively inflected “knee” of the curve k that is nearest to and less than F, and defined the threshold as F − ((F − k)/2).We designated maximum signal for each signal block as the maximum bedgraph signal value for any component region contained in the block. For normalization, we generated total signal density plots for all signal blocks from target and control data, identified the total signal AUC values that corresponded to the density peak of each plot and multiplied total signal values for all control signal blocks by a “scaling factor” calculated by dividing the density peak total signal value for target data by the density peak total signal value for control data. To determine the total signal threshold MACS2 peaks were called using macs2 callpeak -f BEDPE --keep dup all, with treatment and control files. For H3K27me3, the --broad flag was added. For local lambda-inactivated peak calling, --llocal 0 was added. HOMER peaks were called by generating tag directories for target and control datasets, then using findPeaks, -style factor for TFs, H3K4me2 or H3K4me3, and -style histone for H3K27me3.10(FDR) > 10; H3K4me3: ENCFF258PHY, −log10(FDR) > 10; CTCF: ENCFF002DDJ, no extra thresholding; H3K27me3: ENCFF126QYP, −log10(FDR) > 10. We called all peaks using loose stringency parameters in order to generate full peak files with nearly 100% recall that could be subset by ranking metrics  for MACS2, and peak score for HOMER) in order to derive full precision–recall curves. For SEACR, we artificially set total signal threshold to ½ the threshold corresponding to the knee of the curve described in the “relaxed” mode. For MACS2, we added the flag –p 0.05. For HOMER, we added the flags –F 1.0 –P 0.25 –L 1.0 –LP 0.25 –fdr 0.25. We then used custom bash and R scripts to calculate AUPR values for each dataset. Briefly, to generate values for precision calculations, we used bedtools intersect –u [For area under the precision–recall curve analysis (AUPR), we compared CUT&RUN peak calls from SEACR, MACS2, and HOMER to stringent sets of MACS2-called ChIP-seq peaks generated by the ENCODE consortium. The ENCODE accession numbers and thresholding used for each ENCODE peak file are as follows: H3K4me2: ENCFF099LMD, −logrsect –u  with the10(FDR) cutoff of 10 as the test set and used bedtools intersect with the –u flag to calculate the percentage of test set regions overlapped (fraction of true positives) or the percentage of experimental peaks outside the test set . F1 scores were calculated as follows:P is precision  and R is recall (fraction of true positives from test set identified).For recall and precision analysis with default peak calling cutoffs, we used ENCODE H3K4me2 ChIP-seq peaks (ENCFF099LMD) meeting a −logAdditional file 1: Fig. S1. AUPR analysis for SEACR. Plot of area under the precision–recall curve (AUPR) for peaks called from H3K4me2 (A), H3K27me3 (B), or CTCF (C) CUT&RUN data by SEACR, MACS2, MACS2 with local lambda inactivated , and HOMER, that were compared to a stringent test set of peaks called from ENCODE ChIP-seq data for each indicated target. Read subsampling levels are indicated on the X-axis.Additional file 2: Fig. S2. Peak calling metrics for SEACR default thresholds. A-B) Table denoting the number of bases overlapped (A) or the percentage of reads in peaks (B) called by SEACR stringent mode (top row), SEACR relaxed mode (second row), MACS2 (third row), or HOMER (fourth row). Factor and cell type from which data are derived are indicated in columns and rows, respectively.