Lakes occur in most marginal areas where they typically develop at low elevations (<100 m) and on low surface slopes (<1°), but they can exist 500 km inland and at elevations >1500 m. We find that lakes often cluster a few kilometres down-ice from grounding lines and ~60% (>80% by area) develop on ice shelves, including some potentially vulnerable to collapse driven by lake-induced hydro-fracturing. This suggests that parts of the ice sheet may be highly sensitive to climate warming.Supraglacial lakes are important to ice sheet mass balance because their development and drainage has been linked to changes in ice flow velocity and ice shelf disintegration. However, little is known about their distribution on the world’s largest ice sheet in East Antarctica. Here, we use ~5 million km They range in size from a just a few metres to tens of kilometres in area4 and they play an important role in an ice sheet’s mass balance. Firstly, they decrease the ice surface albedo and increase the absorption of incoming solar energy, thereby setting up a positive feedback that may further enhance melting7. Secondly, their rapid drainage has been implicated in the collapse of floating ice shelves12, which can then cause increased ice discharge from tributary outlet glaciers14. Thirdly, the drainage of SGLs to the bed of grounded ice in Greenland has been linked to transient speed-ups in ice velocity19. This process has yet to be observed in Antarctica, although it has been noted that future warming could increase the connectivity between surface and basal hydrological systems20.Supraglacial lakes (SGLs) form when meltwater ponds in depressions on the surface of a glacier or ice sheet25 and, to a lesser extent, ice shelves in the Antarctic Peninsula, particularly Larsen B Ice Shelf10. Until very recently, there were fewer reports of their existence in East Antarctica, which hosts the world’s largest ice sheet, and where surface melting is thought to be less intense and generally restricted to near-coastal regions29. However, the margins of the EAIS extend to latitudes of ~66° S (comparable to the Larsen B Ice Shelf), which contrasts with the margins of the neighboring West Antarctic Ice Sheet . Moreover, several recent studies have shown that SGLs are more widespread than previously thought, and are often connected to channelized drainage systems on the ice sheet surface33. Indeed, it has been noted that future warming could increase surface melt and that such drainage systems could deliver excess meltwater to ice shelves that may be vulnerable to collapse34, unless surface channels export meltwater off the ice shelf33.To date, much of the research on SGLs has focused on the Greenland Ice Sheet (GrIS)33. For example, Antarctic-wide estimates of surface meltwater production are now available from both satellite data and regional climate modelling28, but there are, as yet, no comprehensive and consistent observations of where excess meltwater is ponding and generating SGLs across the entire ice sheet surface. One recent study4 identified ~700 drainage systems (SGLs connected to surface streams), but this was thought to be an underestimation due to the spatial and temporal coverage of the satellite imagery, which was acquired from multiple years and not necessarily from the summer melt season. A recent review20 of Antarctic surface hydrology highlighted the need for robust observations of processes related to surface melt, noting that new high-resolution satellite sensors (such as Landsat 8 and Sentinel) could help address this data void.Despite recent progress, the underlying processes governing meltwater production, ponding and runoff in East Antarctica remain unclear2 of imagery from Landsat 8 and Sentinel 2A and use a consistent semi-automated approach to identify and quantify the distribution and extent of SGLs produced around the peak of a single melt season in January 2017 (see Methods). Note that the austral summer of 2016/2017 was characterised by an unprecedented retreat of Antarctic sea ice linked to atmospheric circulation anomalies35, which may also have increased ice sheet surface melting. With this in mind, our aim is to determine where meltwater is ponding in SGLs and to use these spatial patterns to understand the controls on their distribution. We deliberately focus on capturing the first consistent observations of their spatial distribution across the whole ice sheet, rather than tracking their temporal evolution through time, which is perhaps better suited to regional studies31 and which is currently precluded by image availability across the whole ice sheet. We then discuss their potential impact on ice sheet mass balance and stability, specifically in relation to ice shelves that are deemed potentially vulnerable to hydro-fracturing11.In this paper, we analyze ~5 million km36. Given our focus on ascertaining a consistent record of the spatial extent of SGLs around the peak of the melt season, we therefore limited our imagery to January 2017. This is a part of the first Antarctic  summer to benefit from the near-complete coverage of medium-resolution imagery from the Sentinel 2A (up to 10 m) and Landsat-8 (up to 15 m) satellites. Due to the difficulty of acquiring a single image mosaic of the whole ice sheet on the same day (or even from within a period of a few weeks), these images span 1st January to 31st January 2017, but with the majority from mid- to late January  reported for well-studied regions of the GrIS3. We also discover SGLs in several regions where their widespread development has not been previously reported, such as Kemp Land, Terre Adélie and George V Land  available in Supplementary Data 2 (±13.8 km2) and individual lakes range in area from 0.0002 km2 (our minimum threshold for lake detection: see Methods) to a maximum of 71.5 km2 (±0.7 km2). It is likely that our analysis misses very small lakes that fall below our minimum threshold, but they are unlikely to add substantially to the total area (see Methods). The largest lake is an elongate feature tens of kilometres long on the Amery Ice Shelf, Mac. Robertson Land , but lakes approaching this size are rare: only 11 lakes in our dataset from East Antarctica are >10 km2. Indeed, the size-frequency distribution of SGLs in East Antarctica is highly skewed towards smaller lakes . Similar positively-skewed size-frequency distributions  have been reported from the GrIS25 and the Antarctic Peninsula9  occur on floating ice, with a clear clustering of lakes within a few kilometres down-ice from grounding line locations  between 0 (representing the ice margin) and 20 km from the margin  found two thirds of surface drainage features (streams and ponds) originated on ice flowing <120 m a−1. For comparison, we find that just less than half of the population of lakes (48.9%) formed on ice flowing <120 m a−1. Indeed, thousands of lakes form on rapidly-flowing ice (i.e. >500 m a−1) and these tend to form in longitudinal troughs between flow-stripes on outlet glaciers and/or where they transition into ice shelves  equates to ~18% of the total. Thousands of lakes exist at elevations >500 m and hundreds >1000 m  is also higher and the firn air content (FAC) is correspondingly higher32. This allows any surface melt to percolate into the firn and precludes the formation of SGLs. However, whilst it was generally assumed that most East Antarctic ice shelves had a high FAC, recent evidence has shown that this may not be the case and that extensive meltwater-induced firn air depletion is occurring32. This is because SGLs and channels down-stream of grounding lines are draining to englacial positions, and then being advected within the ice shelf and progressively submerged beneath snow/firn32. Thus, large areas of saturated firn and/or refrozen ice lenses may exist in several East Antarctic ice shelves and are likely to influence the vulnerability of ice shelves to hydrofracturing41 (discussed below).Surface drainage systems can also deliver water from higher elevation grounded ice to lower elevation areas, whereupon it is more likely to be stored on flatter surfaces just beyond the grounding linet32 Figs  and 5c. 36  develop as a result of increased strain, particularly in areas of flow acceleration and confluence48. Large numbers of highly elongate SGLs are often found in the intervening troughs between flow-stripes  regional climate modelling42. Rather, clusters of high lake density reflect the interaction between local-scale climatic controls and ice surface characteristics, including regional-scale wind patterns, ice surface albedo and topography, and firn air content and thickness49. Thus, the complex interplay of these local-scale processes makes it difficult to predict the location of SGLs based only on the current generation of Antarctic-wide observations and modelling of surface meltwater production.In summary, SGLs occur in most low elevation, gently-sloping marginal areas of the EAIS, which reflects the fact that the ice sheet margin extends to relatively low latitudes where summer temperatures are high enough for surface melting to occurity Fig.  that do 20, which we now consider: (i) reducing ice surface albedo and increasing ablation; (ii) draining to the ice sheet bed and locally enhancing basal lubrication; and (iii) draining through the ice and fracturing ice shelves, leading to their collapse.SGLs can potentially influence ice sheet mass balance in three main ways6. Thus, the high density of SGLs in some regions of East Antarctica  of lake areas and volumes measured in two previous studies in Antarctica on Larsen B Ice Shelf56 and on the Langhovde Glacier, East Antarctica31. Similarly strong relationships have been found for lake areas and volumes on the GrIS57 and our approximation gives a total volume of ~1 km3 (~1 Gt liquid water), with maximum lake volumes up to 0.05 km3. Mean volumes are only 0.000015 km3 (st. dev. 0.0003 km3), but ~1,500 SGLs in our dataset (70% of these are on floating ice) are likely to contain water volumes that are greater than the average volume calculated for lakes on the Larsen B Ice Shelf prior to its collapse56 , can trigger an acceleration in the flow velocity and discharge of their tributary outlet glaciers, as has been observed in the Antarctic Peninsula14.Potentially of most significance to ice sheet mass balance are the large number of lakes  that we observe on floating ice shelves that fringe the EAIS. These lakes constitute 60.4% of the total number of lakes, but 81.6% of the total lake area. Their potential importance stems from observations that SGLs provide effective reservoirs to drive the process of hydro-fracturing, whereby meltwater fills crevasses and the resultant water pressure propagates the tip of the crevasse until full-thickness fracture occurs64 (e.g. in Wilkes Land); and that some of these ice shelves may be more vulnerable to hydro-fracturing than previously thought11. Specifically, a recent study11 used the relationship between active microwave backscatter and average annual melt days to create a relative index that shows ice shelf vulnerability to surface-melt induced collapse via hydrofracture across Antarctica. Consistent with observations52, they found several ice shelves on the Antarctic Peninsula have significantly ice-saturated firn layers that make them vulnerable to surface meltwater ponding and hydrofracture11, but they also noted several ice shelves in East Antarctica had relatively high vulnerability indices, e.g. the Amery, West, and Shackleton ice shelves. As mentioned earlier, these ice shelves experience high melt rates due to localised katabatic winds converging over their grounding lines32. Shackleton Ice Shelf, for example, experiences upward of 60 days of melting per year27, with melt rates as high as 200 mm w.e. a−1 (ref.28).Of particular relevance to our study is recent work that has shown that several ice shelves in East Antarctica are dynamically important in terms of buttressing inland ice11, but the presence/absence of lakes was not investigated in any detail. However, our data clearly show that high densities of lakes exist on some of the ice shelves deemed vulnerable to hydrofracturing, particularly near to the grounding lines of Amery, Shackleton and Moscow University ice shelves . We acquired all cloud-free scenes available from January 2017, but also included a smaller proportion (~10%) of scenes with minimal cloud cover (<10%) of the marginal areas of the ice sheet. Due to incomplete image coverage and/or scenes with larger amounts of cloud cover, we supplemented the Sentinel 2A imagery with cloud-free scenes from the Landsat-8 Operational Land Imager (OLI), which were acquired free-of-charge from the United States Geological Survey (USGS) Earth Resources Observation Science (EROS) Centre (https://eros.usgs.gov). The majority of lakes were mapped using the Sentinel imagery (~75%), but Landsat was particularly useful to search for lakes further inland and to fill gaps in between Sentinel imagery. The multi-spectral bands of the Landsat-8 images were ‘pan-sharpened’ to 15 m using the panchromatic Band 8 and the High Pass Modulation (HPM) method. This was to bring the spatial resolution of the Landsat imagery closer to that of the Sentinel imagery, but it should be noted that the coarser resolution might be unable to detect some small lakes that would be mapped on the Sentinel imagery . In total, we acquired 312 individual scenes totaling almost 5 million km2, see Supplementary Fig. http://desktop.arcgis.com), where all subsequent analyses, described below, were undertaken.Our primary source of imagery was from Sentinel 2A, which represents the highest spatial resolution imagery 10 m) that is available free of charge (from the Copernicus Open Access Hub: 0 m that 31). Given the large size of our study area and the large number of scenes to be analysed, we used the semi-automated Normalised Difference Water Index (NDWI). Although most glaciological studies use a variant of the NDWI that includes the blue and red bands73, we found that the standard NDWI equation performed very well compared to manual digitization , and excluding shallower areas or areas of slush; and with lower thresholds tending to identify larger numbers of lakes (and larger lake areas), and potentially including shallow lakes and areas of slush. In this study, we experimented with a number of thresholds within this range and found a value of >0.3 performed most accurately compared to manual digitization .Various approaches have been used to map the area of SGLs on satellite imagery, including manual delineation and a range of automated/semi-automated techniques e.g. refs1. Given 31, and to reduce noise in the initial output, we used a minimum size-threshold of two pixels for lake detection, which gives a minimum lake size of 200 m2 for Sentinel and 450 m2 for Landsat imagery. Pixels classified as lakes in a raster image were then converted to a vector format (shapefile) in ArcGIS , these changes were largely cosmetic and are insignificant in terms of the uncertainties associated with identifying lakes and calculating total lake area, described in the next section. The lake outlines are available as GIS shapefiles (.shp) in Supplementary Data The NDWI assigns each pixel a value, which was classified as ‘lake’ or ‘no lake’ using our threshold of >0.3. Following previous work74 or areas of shadow cast by nunataks. We then quantified the uncertainties of our automated mapping technique by comparing our results with those obtained from manual digitization. Three sample areas containing a variety of SGL shapes and sizes deemed to be broadly representative of the range of lake characteristics across the ice sheet were selected. The boundaries of lakes were manually digitized on screen making full use of various band combinations and varying the scale to suit the size of the lake  generating the largest percentage differences, but where the absolute area differences were obviously much smaller. For larger lakes, the two methods were much more similar. However, the differences between the total lake area for each of the three sample areas  lakes, the total area of lakes mapped across much larger areas is likely to be very similar for each technique and we assign a conservative uncertainty of 1% to our total lake area of 1,383 km2. It is also worth noting that varying the threshold that was applied to the NDWI output (but without obviously misclassifying lakes) was within the range gleaned from the manual versus automated digitizing uncertainty.Initially, we performed a visual cross-check of the lake polygons against the underlying imagery and removed any obvious false positives (less than a few hundred), which were mainly associated with nunataks, blue ice areasQuantifying the uncertainty regarding lake identification (as opposed to lake area) and, therefore, the total number of lakes is much more difficult, especially with limited ‘ground truth’ data. Having compared our mapped lake outlines with imagery and removed obvious ‘false positives’, we are confident that there are very few (if any) non-lake areas in our dataset. However, it is much more difficult to ascertain and quantify how many lakes might be missing from our January 2017 dataset, especially very small lakes.Firstly, it is important to note that it was not possible to acquire all imagery on the same day and so we had to sample/observe imagery from different days in January , especially where we were restricted to using the 15 m Landsat 8 imagery. We sampled several small areas where some of the smallest lakes in our dataset were clustered. In these regions, there is often a transition from what is likely to be saturated firn to small, shallow ponds, and to larger and more obvious lakes . Thus, it is very difficult to work to a binary definition of ‘lake’ versus ‘non-lake’ in these areas, especially given the resolution of the imagery (field observations would encounter similar issues). It is for this reason that we use a lower size threshold of 0.0002 km2 (200 m2) and we performed some of the statistical filters to clean and generalize our SGL polygons. This is another reason why we view our estimate of the total number of lakes as a minimum and why their cumulative surface area is also likely to be a minimum. That said, even if we had missed ~25% of the total number of lakes identified in our dataset  that existed at our minimum size limit (0.0002 km2), they would together only add 3.2 km2 to our total area of 1,383 km2 (just 0.2%). We also compared the results from the automated mapping of the same area to test the impact of image resolution. Clearly, mapping from Sentinel 2A imagery enabled the detection of smaller lakes (minimum of 200 m2) compared to the Landsat 8 (450 m2), but the agreement was generally excellent for lakes >450 m2. Overall, we suggest that whilst our estimate of the number of lakes is a only a minimum, any missing lakes (e.g. not mapped in the Landsat imagery) are unlikely to add substantially to the total area of 1,383 km2 and this certainly falls well below our total lake area uncertainty of 1% (13.8 km2). Moreover, the absolute number of lakes is less useful/important than their distribution and cumulative area (e.g. when comparing patterns across the ice sheet and between different regions).Secondly, it is likely that some very small and/or shallow lakes were not identified  and Langhovde Glacier in East Antarctica31 . We acknowledge that these two settings may not be representative of the full spectrum of lakes in our dataset, but they reveal a strong and significant relationship (r2 = 0.86) between area (A) and volume (V), albeit with greater scatter of volumes at lower areas 31 n = 1,38. We acionship r = 0.86 b38. This allowed us to extract values of surface elevation at the geometric centre of each SGL. We also converted the ice surface topography into a slope map to extract the surface slope of the ice sheet topography at the location of each lake. Bedmap2 also provides a ‘rock mask’, which we used to calculate the planar distance of the nearest edge of each lake polygon to the nearest edge of exposed rock. Closer inspection of the rock mask dataset indicated that some very small nunataks were missing  and so a small number of the lakes might be nearer to bedrock than we measured, i.e. distances presented in Figs 75 (gridded at 450 m) based on satellite radar interferometry (2007–2009).Each SGL was represented by a polygon within a single vector shapefile  since the compilation of the Bedmap2 dataset. Thus, we did not analyse the physiographic characteristics of this small percentage (2.6%) of the overall population of lakes, although we do include them in our calculations of the number and area of lakes.11 quantified an ice shelf vulnerability index for Antarctica based on the relationship between active microwave backscatter data and average annual melt days. This was based on field data from a transect in Greenland that demonstrated that backscatter values increased with increasing mean annual melt days until specular reflections due to large, continuous ice lenses in the firn layer at very high melt days causes the backscatter to decrease. They used these relationships to create an index that quantified ice shelf vulnerability to surface-melt-induced collapse via hydrofracture, which was then applied to Antarctica. This assumed that the ice shelf backscatter/melt days relationship represents the temporal evolution that any given ice shelf might experience under changing climate conditions. This allowed them to identify which ice shelves are currently, or may soon be, vulnerable to hydrofracture. We compared our data on lake area density  to this previously-published vulnerability index . The vulnerability data were supplied in tagged image format (.tif) and gridded at 4.45 km resolution, which we ingested into our GIS for directly comparison (see Fig. A recent studysee Fig. .Supplementary InformationSupplementary Dataset 1Supplementary Dataset 2


Furthermore, we show that a global model of desert dust INPs dramatically underestimates the measured INP concentrations, but is consistent with the thermally-stable component. Notably, the heat sensitive INPs are active at temperatures where shallow cloud layers in Northern Europe are frequently observed to glaciate. Hence, we suggest that biogenic material is important for primary ice production in this region. The prevalence of heat sensitive, most likely biogenic, INPs in this region highlights that, as a community, we need to quantify the sources and transport of these particles as well as determine their atmospheric abundance across the globe and at cloud altitudes.A minute fraction of atmospheric particles exert a disproportionate effect on the phase of mixed-phase clouds by acting as ice-nucleating particles (INPs). To understand the effects of these particles on weather and climate, both now and into the future, we must first develop a quantitative understanding of the major INP sources worldwide. Previous work has demonstrated that aerosols such as desert dusts are globally important INPs, but the role of biogenic INPs is unclear, with conflicting evidence for their importance. Here, we show that at a temperate site all INPs active above −18 °C at concentrations >0.1 L Atmospheric aerosol can contain ice-nucleating particles (INPs)3, which permits primary ice nucleation at temperatures above about −33 °C, where the homogenous nucleation of supercooled water is so slow that water would otherwise persist in a supercooled state4. Common aerosol particles that are thought to be effective as INPs in the mixed-phase cloud regime include desert dusts7 and, in remote marine locations where dust concentrations are low, marine sea sprays9. While desert dust is thought to be a globally important INP type6, it has been found that shallow clouds over Morocco only glaciated below −18 °C, despite being collocated with dust10. In contrast, similar clouds in other terrestrial regions, such as N. Europe, typically glaciate at temperatures up to or even above −10 °C11. This difference is thought to be related to differences in INP populations rather than other variables such as cloud properties or meteorology11, but the INP type that drives this relatively high temperature nucleation in Northern Europe is unknown. While certain bioaerosols are known to be exceptional in their ice-nucleating abilities12 and have been posited as drivers of ice formation in clouds at low supercoolings19, there are conflicting conclusions regarding their global importance21. Although biogenic INPs have been examined since the 1960s , a major source of uncertainty concerning the impacts of biogenic INPs is due to the lack of field studies that have determined their abundance relative to other ambient atmospheric INPs.The phase transition of water to ice in supercooled droplets can bring about precipitation and modulate the radiative properties of clouds28. Estimates of atmospheric INP concentrations at cloud altitudes can be made based on the INP content of precipitation29 and heat tests suggest that some of these INP are biological27. In addition, measurements indicate that there is a major biogenic INP component in cloudwater at Puy De Dôme in France28. Also, Garcia et al.30 monitored the amounts of biogenic INPs released to the air from crops pre- and post- harvest in Colorado and Nebraska, and found using heat tests on sampled aerosol that a major proportion of emitted INPs were biogenic. In forested ecosystems, INPs have also been found to correlate well with the amount of fluorescent bioparticles and carbonaceous material in the aerosol32. Further suggestions for the importance of biological INPs in atmospheric ice nucleation have emerged from particle mass spectrometry of cloud ice crystal residues33. Notably, however, significant questions on the use of particle mass spectrometry to identify bioaerosols remain, in particular due to the potentially large misattribution rate based on the selected markers used34. Overall, despite there being evidence for biogenic INP in rain water and associated with specific events, such as harvests, there have been very few measurements of the relative importance of biological INPs versus other INP types in ambient aerosol samples around the world and none in the atmosphere of the UK.Biogenic components of INPs have previously been detected in precipitation samples collected at sites across the globeet al.20 simulated the global annual average INP concentrations using a subset of known biogenic ice-nucleating particles, including P. syringae bacteria. They found the proportion of nucleation due to bioaerosols was very small (≤0.6%). Similarly, Spracklen and Heald35 concluded that the fungal spores and bacteria only contribute a minor proportion of INPs, but do suggest that they may contribute to INP populations at warmer temperatures in some locations. However, these studies did not consider the possible roles of subcellular INPs, such as macromolecules, which are generated in large amounts by certain fungi and plants (e.g. pollen)40. These nanoscale entities could substantially increase the relative importance of biogenic particles as INPs41, especially if they become internally mixed with other aerosol particle types43. Conversely, using a cloud system resolving model, Phillips et al.21 concluded that cloud properties such as ice crystal number and precipitation are significantly influenced by bioaerosol particles when bioaerosol concentrations are elevated above average (but within previously observed levels). Despite these and other attempts to simulate the net contribution of biogenic INPs to cloud properties, the lack of field studies examining the biogenic INP burden in atmospheric aerosol makes it impossible to accurately predict their influence on clouds.Given the dearth of information on the contribution of biogenic INPs to the total burden, it is perhaps unsurprising that models simulating the impacts of biologically-derived INPs on clouds come to differing conclusions. In an aerosol-climate model, Hoose −1. Such a wide variability has previously been seen at other ground based measurement sites. For instance, at a rural site in Italy, Belosi et al.44 report concentrations at −18 °C to fall within the range 0.07–1 INP L−1. Despite the wide variability in INP concentrations, Fig. −1 at −22 °C. This distinct maximum in the INP concentration frequency plot is consistent with a single persistent INP type, whereas the concentrations at higher temperatures are consistent with a much more variable INP type.To quantify and characterise INPs in the atmosphere at a temperate site in Europe, a six week campaign was held at a rural location in the UK. INP concentrations at the site throughout the campaign are illustrated in Fig. 45. Conversely, known inorganic INPs such as mineral dusts are not affected by heating to temperatures of about 100 °C47. Previously, studies have focused on examining the effects of heat treatment on either surface-collected samples such as soils48, leaf litter49 and sea water samples50, or on particles found in precipitation51 and aerosol collected during harvest periods30.Determining the nature of the INPs which make up the population in a typical atmospheric INP spectrum is challenging. This is in part because biogenic INPs are highly varied, being composed of whole cells, cell fragments or subcellular entities, such as proteins, which become internally mixed with other aerosol types, hence they are very difficult to identify directly. In this study we have used the commonly used heat treatment to assess the contribution of biogenic INPs to the overall INP population. This test is based on the fact that many known biological ice-nucleating materials nucleate ice because of the presence of specific ice-nucleating proteins. These proteins are disrupted and denatured on heating which inhibits their ice-nucleating ability whereas inorganic ice-nucleating materials tend to be insensitive to heat, hence heating a sample in water has become a standard and effective test for protein based biological ice-nucleating materialT > −20 °C 6. INP concentrations simulated in GLOMAP from desert dust (K-feldspar) and marine sea spray emissions, i.e. neglecting other INP species such as terrestrial biogenics, were within one order of magnitude of 57% of the INP observations from around the globe6. As can be seen in Fig. et al.9, are predicted to be of minor importance at this location. In Fig. 5. Being the most ice-active mineral in desert dust found to date, and given its natural abundance, K-feldspar has been suggested to be of first order importance in determining the ice-nucleating activity of lofted desert dusts. Accordingly, the nucleating activities used here are taken from Atkinson et al. (A13)5 in conjunction with the modelled global K-feldspar distribution in order to estimate the INP concentration associated with desert dust. The initial fraction of desert dust which is feldspar is derived from soil composition maps from Claquin et al.60 Of this feldspar, 35% is assumed to be K-feldspar. Further details can be found in Vergara-Temprado et al.6. Two limiting assumptions are made, one where K-feldspar is externally mixed and one where it is internally mixed throughout the dust particle population. In reality, dust particles will be somewhere between these two mixing assumptions. In Fig. et al.61 (N12), which is based on surface samples from areas including the Nile delta, the Sahara and Israel.We now examine what the heat resistant INP type we observe may be. Desert dust is thought to be a globally important INP type6, the agreement between the model-predicted INP concentrations and the heat resistant INPs is reasonable. Both the A13 and N12 parameterisations were found to yield reasonable agreement to observed heat-resistant INP concentrations. For the A13 parameterisation, the internal mixing assumption gives better agreement than the external mixing assumption. Overall, the thermally resistant component of INPs at this site is consistent with transported desert dust, defined by either N12 or A13, possibly together with heat resistant biological material. The presence of mineral dust within the aerosol at this site was confirmed through conducting energy dispersive x-ray analysis on a sample collected on the 17th Oct  and with an aerosol subsampling system was stationed at the site. Ambient particles were sampled onto 0.40 µm Nucleopore track-etched membrane polycarbonate filters at a flow rate of 5 L min−1. Note that these filters collect particles across the full aerosol size range, including at sizes below the size of the pore, with high efficiency63. Handling blanks, where the sampling system was set up and a HEPA filter placed on the inlet, were conducted to verify that in the absence of ambient particles contamination was not an issue (see SI). The average sampling time was approximately 3 hours, and the average volume of air sampled was 890 litres (see supplementary information). Further information can be found in Supplementary Information (SI) Tables et al.64. A compilation of all the particle size distributions is shown in SI Fig. Field experiments were conducted at the University of Leeds Research Farm  from 19/09/16 to 02/11/2016, during which time a mobile laboratory (the “IcePod”) equipped with a PM65. Nucleation was taken as the first visible occurrence of ice formation within the droplets, which was recorded using a high definition webcam. The cumulative number of INPs per mL of washing water (K(T)), was calculated using the singular approximation for ice nucleation as per Vali 197166:F(T) is the cumulative fraction of droplets frozen, and Vd is the droplet volume (0.001 mL). This can then be related to the number of INPs per litre of sampled air by:Vww is the volume in mL of water used to wash the filter, and Vair is the volume of air sampled through the filter in L. For the heat treatment tests, 0.75 mL of the filter washing waters was placed into a sealed Eppendorf tube, and heated to 95 °C for 1 hour. Mass loss from heating was determined gravimetrically and accounted for. Following heating, particles were resuspended in the Eppendorf tubes using a vortex mixer for 20 s prior to analysis via the μL-NIPI. Daily control freezing spectra were taken of the ‘pure’ MilliQ® water, to ensure that any background freezing on that day (due to impurity particles in the water) was diminishingly small in number relative to the number of INPs in the water after aerosol sampling. The pure water backgrounds are illustrated in Supplementary Information Fig. Sampled INPs were extracted from filters by placing the filters into a centrifuge tube containing 5 mL Milli-Q® purified water, which was subsequently placed in a rotary mixer at 30 rpm. Detection of INPs was carried out using the Leeds microliter nucleation by immersed particles instrument (μL-NIPI)67:µ(T) is the number of INPs per droplet, Zα/2 is the standard score at a confidence level α/2, which for a 95% confidence interval is 1.96.A principle source of uncertainty in the experiments stems from the representativeness of sampling of INPs into droplets from the bulk suspension. This is of particular importance at temperatures where only a minor fraction of droplets contains active ice-nucleating particles. At such temperatures, the observed number of INPs per droplet in the subset sample removed from the vial can vary from that in the population . Confidence intervals for the population number of INPs per droplet are constructed using the variance scores interval from Barkeret al.68. The horizontal resolution of the model is 2.8° × 2.8°, and contains 31 pressure levels from the surface to 10 hPa. The surface level is about 60 m deep. The model uses wind, temperature and humidity fields from the European Centre for Medium-Range Weather Forecasts (ECMWF) from the year 2000 to 2001 in order to reach a steady-state aerosol distribution before running the model for the year 2001 to 2002. Further details of the model setup are given in Vergara-Temprado et al.6, but the major uncertainties in the model arise from uncertainties in the evolution of dust concentrations and aerosol microphysical processes70, along with the differences in the density of active sites for different types of K-feldspar71 and the effects of acid aging on the feldspar nucleating activity.The GLOMAP mode global aerosol model used here has been described in detail in Mann 58 using data from the Global Data Assimilation System archive. Hourly back trajectories were calculated to coincide with the sampling times. In order to probe whether the 5 day back trajectories could account for INP observations at the site, each trajectory was assigned a value of Easterly, Westerly, Northerly or Southerly, depending on the major origin of the air mass. As indicated in Fig. To examine the origin of air masses arriving at the rural site, 120 hr (5 day) air mass back trajectories arriving at 100 m were calculated using the NOAA HYSPLIT model v4Details of the SEM-EDS analysis are provided in the supplementary information.Supplementary information


Reactive oxygen and nitrogen species have cell signaling properties and are involved in a multitude of processes beyond redox homeostasis. The peroxiredoxin (Prdx) proteins are highly sensitive intracellular peroxidases that can coordinate cell signaling via direct reactive species scavenging or by acting as a redox sensor that enables control of binding partner activity. Oxidation of the peroxidatic cysteine residue of Prdx proteins are the classical post-translational modification that has been recognized to modulate downstream signaling cascades, but increasing evidence supports that dynamic changes to phosphorylation of Prdx proteins is also an important determinant in redox signaling. Phosphorylation of Prdx proteins affects three-dimensional structure and function to coordinate cell proliferation, wound healing, cell fate and lipid signaling. The advent of large proteomic datasets has shown that there are many opportunities to understand further how phosphorylation of Prdx proteins fit into intracellular signaling cascades in normal or malignant cells and that more research is necessary. This review summarizes the Prdx family of proteins and details how post-translational modification by kinases and phosphatases controls intracellular signaling. The relative reactivity of these species spans several log orders of magnitude to affect the half-life and distance traveled within the intracellular environment. The hydroxyl radical is the most reactive of these species with a half-life on the order of 10−9 s, while H2O2 is much less reactive in comparison with a half-life of 10−3 s [In biological systems, redox reactions can regulate intracellular levels of reactive oxygen (ROS) and nitrogen species (RNS) to control a multitude of intracellular processes. These reactive species include both radical and non-radical forms of ROS and RNS such as superoxide anion  [2O2 load as well as the extracellular secretion of H2O2, which can reach 2 µM in stimulated neutrophils [There are diverse sources of ROS that emerge from several organelles within the cell. The intracellular concentration of Hto 10 nM . Mitochopiration , but thepiration  and the  in vivo . Complex in vivo ,8 and II in vivo  produce by MnSOD . The stevely low  based onM−1·s−1)  and mitoM−1·s−1) . Other oM−1·s−1) , the endM−1·s−1) ,15 and lM−1·s−1) . The plaM−1·s−1) , prostagM−1·s−1) , lipoxygM−1·s−1)  and xantM−1·s−1)  and tranM−1·s−1) , respecttrophils . Reactive species have a complex relationship in cancer. An overabundance of reactive species can cause cancer initiation and drive progression and accumulation of additional DNA mutations to support further growth . Ant2O2 is a particularly important reactive molecule with second messenger function. Spatiotemporal features of the molecule enable it to possess reactivity, yet move through biological macromolecular microenvironments intracellularly within different organelle compartments and intercellularly to neighboring cells. Organ and cellular systems coordinate the balance of the H2O2 through enzymatic-catalyzed reductant proteins in conjunction with the pro-oxidant sources mentioned above to form an interconnected network that maintains homeostasis or drives oxidative signaling. The enzymatic metabolism of H2O2 is primarily catalyzed through the action of catalase, glutathione peroxidases (GPx) and peroxiredoxins (Prdx). While all three enzymatically metabolize H2O2, important biochemical and biological differences exist. Insight into the basal function of the three enzymes in vivo can be drawn from the phenotypic effects observed in gene knockout studies. Deletion of catalase displays no overt pathological changes under basal conditions in mice, while GPx1 knockout mice were found to be smaller sized [Her sized  and harber sized ,29,30. Ter sized . Deletioer sized ,33. Prdxer sized .2O2 via an iron heme porphyrin complex [2O2 is enzymatically scavenged through oxidation followed by reduction of the active site heme iron. The active site heme is initially oxidized to an oxyferryl species, which is subsequently reduced by a second H2O2 molecule to regenerate enzymatic function. Sequestration of catalase to a single organelle enables control of peroxisomal H2O2 levels but also requires H2O2 derived from other intra- and extracellular sources to diffuse to the peroxisome in order for catalase-dependent catalysis to occur. Catalase exhibits a high H2O2 turnover rate [m close to 100 mM in human erythrocytes [2O2 concentrations are low. Contrasting catalase, GPx family members are found within several organelles. There are eight family members in the glutathione peroxidases (GPx) family (GPx1-8). GPx1-4 and 6 utilize a selenocysteine active site and glutathione (GSH) as a co-factor to reduce H2O2 [. GPx1 and 4 are present in most tissues, with GPx1 expression found in the cytoplasm and mitochondria, while the phospholipid hydroperoxide reducing GPx4 is found in the plasma membrane and cytoplasm [5 M−1 s−1 [Catalase is localized within peroxisomes and catalyzes the decomposition of H complex . A two-sver rate , but seqhrocytes , yield auce H2O2 ,38. GPx1 M−1 s−1 . These p2O2 to water. The family is subdivided into groups classified as 2-Cys (Prdx1-4), atypical 2-Cys (Prdx5) and 1-Cys (Prdx6) isoforms based on their structure and mechanism of action [p) is conserved among all family members at roughly 50 amino acids from the N-terminus. The Cysp is highly reactive to H2O2 due to its surrounding amino acids, which yield rate constants on the order of 106 to 108 M−1 s−1 [p under conditions of heightened H2O2 concentrations, resulting in a cysteine sulfinic acid, which can be further oxidized to a Cys sulfonic acid to cause irreversible inactivation of the enzyme [p [2O2 induced sulfinylation reactions that are characteristically observed in typical 2-Cys Prdxs [The Prdx family has six members (Prdx1-6) that are present in many cellular compartments. Prdx1, 2 and 6 are located in the cytoplasm, and nucleus; Prdx3 is localized to the mitochondria; Prdx4 is found in the endoplasmic reticulum; and Prdx5 is located in the peroxisomes, cytoplasm and mitochondria . The Prdf action . The act M−1 s−1 . Typicale enzyme ,44. Typinzyme [p ,44,45. Tys Prdxs ,45,46.p to the mechanistically important resolving Cys located on the opposing Prdx homodimerization partner near the C-terminus. Prdx1 and 2 homodimers can associate non-covalently to form larger decameric complexes that are ordered as a pentamer of dimers to form a doughnut-like structure [p is oxidized by H2O2 to a sulfenic acid moiety, which then forms a disulfide bond with the resolving Cys on the homodimerization partner [p can become overwhelmed in the presence of high levels of H2O2 and become overoxidized to form Cys sulfinic or further sulfonic moieties that lack peroxidase activity. The rate constant of the sulfenic acid form of Prdx2 with H2O2 to form the sulfinic Prdx is on the order of 104 M−1 s−1 [p can be adducted with GSH (rate constant 500 M−1 s−1) under physiological concentrations to protect from overoxidation and recycle with Grx1 [Homodimerization of Prdx proteins in a an N-terminus head to C-terminus tail fashion enables 2-Cys family members to align the Cystructure ,46. In 2 partner   enable protein tyrosine kinases (PTKs) to phosphorylate downstream targets without PTP-dependent removal of the phosphate moiety. PTPs are more readily targeted by H2O2 due to the enhanced reactivity of the low pKa active site cysteine residue, which causes increased susceptibility to oxidation compared to PTKs. Cell signaling cascades, therefore, utilize local H2O2 to coordinate signal transduction pathways to promote growth [2O2 within different intracellular compartments, cells require not only the production of H2O2 but the inactivation of peroxidases to drive phenotypic responses. As Prdx proteins are highly sensitive and enzymatically responsive to low levels of H2O2, the cell has developed pathways to inhibit peroxidase activity within the cell during cell proliferation. Suppression of Prdx1 activity by phosphorylation has been shown to play a role during the cell cycle in two different intracellular compartments, namely at the plasma membrane during growth factor signaling and within the nucleus during the transition to mitosis.Outside of oxidation of the Cysch as pH , ionic sch as pH  and tempch as pH . Expressch as pH ), but toe growth ,68. To d2O2 through the action of Nox [2O2 production by NOX1 is not sufficient alone to promote and sustain signaling [2O2, thereby allowing target proteins such as the Src family kinases to become oxidized [2O2 near lipid rafts is necessary to both simultaneously activate Src family kinases and inactivate PTPs. H2O2-mediated inhibition of PTPs is therefore crucial for growth factor signaling as activation of PTKs alone is not adequate to promote sufficient levels of protein tyrosine phosphorylation [A classic counter-example to the redox relay cell signaling coordination by Prdx described above is provided by phosphorylation of Tyr194 on Prdx1 by Src . Local in of Nox  at the pn of Nox ,72. Of iignaling ,69. Rathp was found to be protected from overoxidation in phosphorylated protein during co-treatment of cells with growth factor and H2O2. In vitro studies of the phosphorylated protein found the dimeric form of the Prdx1 was present without decamers. In vivo wound healing experiments exhibited a peak in Tyr194 phosphorylation after 1 day, which remained for 1 week.Phosphorylation on Tyr194 in response to treatment of cells with EGF or PDGF displayed isoform selectivity for Prdx1 in comparison to Prdx2 . Studies2O2 accumulation through inactivation of Prdx1 by phosphorylation is also important in the nucleus during mitosis [2O2 [2O2 enables active Cdk1-cyclin B to transition cells to late mitosis where Prdx1 can be dephosphorylated to promote deactivation of Cdk1 via dephosphorylation by the now activated Cdc14B. The importance of the centrosomal H2O2 during the transition to mitosis was evaluated by expressing catalase fused to a centrosomal targeting sequence, which inhibited entry into mitosis. Local H mitosis . During sis [2O2 . Inactiv2O2 in vitro and ex vivo. In the absence of TOPK via siRNA decrease, cells were more sensitive to UVB-induced apoptosis. Melanoma cells expressing wild-type but not Ser32Ala Prdx protein was more resistant to UVB irradiation. Whether Prdx2 can also be phosphorylated by TOPK is unknown but may not be seen in experiments with RPMI7951 cells, which only express high levels of Prdx1. While the studies above indicate post-translational modifications that serve to reduce peroxidase activity, not all Prdx phosphorylation is repressive to enzymatic activity. The T-cell-originated protein kinase (TOPK) can phosphorylate Prdx1 on Ser32 to enhance peroxidase activity . Investi2 (PLA2) activity, which is unique to the Prdx family. As Prdx6 phosphorylation increases PLA2 activity, phosphorylation of the protein may mirror protein overexpression seen in bladder [2 activity [2 (aiPLA2) functions to degrade surfactant phospholipids and aide DPPC  synthesis through the deacylation-reacylation pathway, by providing the required substrate, lyso-PC. Phosphorylation of Prdx6 provides an important functional role as a PLA2; phosphorylated Prdx6 maintains activity at both acidic and cytosolic pH [2 activity through the MAPK pathway [2 activity compared to Thr177Ala protein. Phosphorylation of Prdx6 has been found to attenuate phospholipase A bladder , liver [ bladder  and lung bladder ,79,80 caactivity . Acidic solic pH . Treatme pathway . ERK1, E−/−Prdx6 PMVEC displayed dramatically decreased plasma membrane translocation of the NOX2 components Rac1 or p47phox following Ang II stimulation. Upon treatment with the known MAPK inhibitor, U0126, Prdx6 phosphorylation, PLA2 activity and ROS were significantly decreased. This result suggested that MAPK activation mediates phosphorylation of Prdx6 resulting in its translocation to the cellular membrane, whereby, PLA2 activity can function to promote NOX2 activation [2 activity when compared to wild-type protein [Phosphorylation of Prdx6 on Thr177 was found to be critical for activation of NOX2 in pulmonary microvascular endothelial cells (PMVEC) by angiotensin II (Ang II) or PMA . Phosphotivation . Whethertivation ,83. Chhu2O2 in the cell, phosphorylation of Prdx proteins has been tied to cell death. Interestingly, Prdx1 phosphorylation at Thr90, which aids in driving the cell cycle through mitosis in the nucleus as described above, can also be targeted by tumor suppressor proteins. The difference between activation of survival or death pathways based on phosphorylation of the same protein at the same amino acid highlights the importance of location and timing of Prdx phosphorylation and the possible involvement of additional phosphorylation of Prdx1 at Thr183 to control activity. The following sections will detail the mechanistic studies that implicate Prdx phosphorylation with death. While some examples below highlight neurodegenerative pathways as examples of inactivation by phosphorylation, further cancer-focused work needs to be undertaken to extend these mechanisms as both Cdk5 and LRRK2 activity have been implicated in cancer. Cdk5 activity has been noted to be involved in proliferation, migration, invasion, metastasis, the epithelial to mesenchymal transition, the DNA damage response and angiogenesis in many forms of human cancer . The LReference ,86. 2O2 cause Prdx1 to bind Mst1, which was found to promote Mst1 activation and enhance apoptosis [2O2. In contrast, phosphorylation of the Thr90 residue of Prdx1 by Mst1 and possibly Mst2 has been described to inactivate peroxidase activity [−/−Prdx1 mouse embryonic fibroblasts (MEFs) showed heightened levels of the DNA damage biomarker phosphorylated Ser139 H2AX following treatment with H2O2. This finding suggests that the inactivation of Prdx1 by Mst1 could potentially cause a positive feedback loop whereby excess H2O2 further activates Mst1. That inactivation of Prdx1 by phosphorylation can promote Mst1 activation, while knockdown of Prdx1 can inhibit Mst1 activity, suggests that a more complex pattern of regulation is present that may involve both oxidation and phosphorylation.Mammalian sterile 20–like kinase-1 (Mst1) and Mst2 have been shown to suppress tumor formation in the liver and intestines in vivo ,88,89,90poptosis . Loss ofactivity . Full-leactivity . Whetheractivity . Express+ treated cells in vitro and MPTP treated mice in vivo. Furthermore, Cdk5 activation was shown to mediate dopaminergic (DAergic) neurodegeneration by downregulation of Prdx2 peroxidase activity which ultimately leads to significant elevations of intracellular ROS and DAergic neuron death [Prdx2 phosphorylation has been primarily investigated in pathological brain diseases and injury. Mitochondrial dysfunction and excessive oxidative stress are believed to be critical facilitators of the pathogenesis of Parkinson’s disease (PD). Neurons have oxidative metabolism systems in place, such as Prdxs, to manage and prevent the accumulation of deleterious levels of oxidative stress but can be overwhelmed when ROS scavengers are decreased or inactivated. In the context of PD, Prdx2 associates with a Cdk5 kinase complex via p35 or the proteolytically cleaved products of p35, p10 and the hyper-activated p25 . Cdk5/p3on death . This obon death . Anotheron death . Expresson death , p35 seeon death . Cdk5-de−/−p35 neurons. Glutamate-induced neuronal cell death was rescued by viral expression of wild-type or Thr89Ala Prdx2 but not Thr89Glu Prdx2. Ischemia-dependent neuronal cell death generated by 4-vessel occlusion in hippocampal CA1 neurons could also be rescued by expression of wild-type Prdx2 but not Thr89Glu in vivo [The Cdk5-Prdx2 pathway has also been shown to cause neuronal death in ischemia models . Glutama in vivo . PhosphoDrosophila model that expressed activated kinase mutant LRRK2, where overexpression of Prdx3 rescued flies from decreased lifespan, depletion of dopaminergic neurons and dysfunctional mitochondria in flight muscles of flies [Drosophila with the Prdx mimetic ebselen, which diminishes H2O2 and peroxynitrite. Prdx3 is expressed in mitochondria and has been shown to be important for maintaining mitochondria mass and membrane potential in Myc-transformed fibroblasts and breast cancer cells . The debof flies . The impde novo expression of unmodified protein during signaling events. While information regarding the dephosphorylation of Prdx family members is relatively scarce, some information is available. The protein phosphatase PP2A has been identified to dephosphorylate Prdx1 when phosphorylated at Thr90, which could be blocked with okadaic acid [−/−Pin1 MEFs. The association between Pin1 and Prdx1 was enhanced in the presence of 50 μM H2O2 and could be inhibited by pharmacologically blocking Cdk1 activity or mutation of Thr90 Prdx1 to Ala. Further experiments found that Pin1 could also bind Prdx2, 3 and 4 but not in cell lysates containing Thr-Pro motif mutants Thr89Ala Prdx2, Thr146Ala Prdx3 and Thr162Ala Prdx4. Reports detailing the importance of interactions between kinases and Prdx family members suggest dephosphorylation may represent an equally significant process. The absence of a Prdx phosphate removal mechanism would require phosphorylated Prdx protein to be degraded or sequestered for future coordination of various signaling pathways. Protein recycling through proteasomal degradation may occur, but this would represent an energy-intensive process requiring aic acid . Dephosp−/−Ptp1b MEFs exhibited significantly higher levels of Prdx4 phosphorylation in the presence or absence of G-Csf stimulation when compared to Ptp1b-proficient MEFs. It is unclear which Tyr was phosphorylated in −/−Ptp1b MEFs or the functional consequences, but the authors suggested that the Tyr phosphorylation may decrease Prdx4 peroxidase activity. Overall, the existence of phosphatases that dephosphorylate Prdx family members is an area that requires further exploration. Dephosphorylation of Prdx4 has also been demonstrated by Ptp1b . GranuloThe current state of knowledge of phosphorylation as a means to modulate Prdx function has been relatively understudied. While biochemical details exist for modification at Ser32, Thr90, Thr183 and Tyr194 and attempts have been made to evaluate Thr18, the consequences of phosphorylation of Prdx1 at multiple sites are unclear. Phosphorylation of Prdx1 Thr90 and Thr183 would be expected to perform similar functions as both sites are targeted by Mst1, decrease peroxidase activity and promote the formation of decameric complexes, but not all combinations are as straightforward. There are questions regarding what occurs when contrasting sites are phosphorylated that cause distinct changes to the oligomeric tertiary structure or peroxidase activity. Phosphorylation of Ser32 has been shown to enhance peroxidase activity, but whether this can exert a dominant effect to rescue the decreased peroxidase functionality of Prdx phosphorylated at Thr90, Thr183 or Tyr194 is unknown. The general structure of a phosphorylated Thr90 or Thr183 Prdx1 decamer may also collapse following Tyr194 phosphorylation, which has been shown to lead to homodimers of Prdx1 primarily. Multi-site phosphorylation may be precluded from occurring in some cases due to changes in the three-dimensional protein structure that prevent sequential kinase binding from occurring, but many other proteins have been shown to have multi-layered signal transduction cascades of regulation. The existence of positive and negative phosphorylation feedback loops to control post-translationally modified proteins temporally has been well documented in transcription factors, kinases and other enzymes. In our current era where large resource experimental datasets have become more readily available due to technical advancements, large proteomic datasets can be mined to determine if protein modifications are present under a myriad of conditions. Published datasets have emerged that support existence of novel phosphorylated forms of Prdx family members. As modifications of plants have been well described in a previous review by Liebthal et al. , we willPhosphorylation of other members of the Prdx family has been less well described. There is evidence that the cdc2-cyclin B complex is capable of phosphorylating Prdx1, 2, 3 and 4 in vitro but cell compartmentalization concerns were suggested by the authors to preclude Prdx3 and 4 from the likelihood of interacting with Cdk proteins . While C2 activity but peroxidase specific phosphorylation sites have not yet been detailed. Six phosphorylation sites of Prdx6 have been described in large proteomic datasets (+/+bi-1) and −/−bi-1 mice found that Tyr phosphorylation was increased in −/−bi-1 liver, brain, heart, lung and kidney tissues [In comparison to Prdx1 and 2, the number of phosphorylation sites present in large datasets is less abundant for the rest of the protein family. Delineation of the effects of phosphorylation of Prdx3 for Thr146 in LRRK2 kinase mutant cells and flies has been described and suggests phosphorylation is a mechanism utilized to alter peroxidase activity, but other sites have yet to be studied ,100. Thrdatasets . Tyr89 i tissues . The ide2O2, ROOH and ONOO− concentration within multiple cellular organelles. Research efforts have therefore primarily focused on how oxidation of the peroxidatic Cys perturbs cell signaling. While there are many important unrealized details and properties of Prdx oxidation that remain, the effects of other forms of post-translational modifications to Prdx proteins represent another exciting area of exploration. Dynamic changes to oxidation, phosphorylation and other forms of post-translation modifications can change three-dimensional structure and function of Prdx proteins to coordinate the various processes outlined above. In addition, control of Prdx through phosphorylation further integrates redox and signaling cascades. Inactivating phosphorylations of Prdx proteins likely prevent Prdx redox relay reactions as the peroxidatic Cys loses peroxidase activity. Prdx phosphorylation cascades would thus enable attenuation of Prdx-dependent oxidative equivalent transfer to partner proteins and inhibit redox signaling. The role of peroxidase activating phosphorylation sites such as Ser32 of Prdx1 on redox relays is also unknown but may perhaps oppose peroxidase inactivating phosphorylation sites.The highly sensitive peroxidatic cysteine thiol of Prdx proteins makes them well suited to sense and control cell signaling due to minor changes in HPost-translational modifications of Prdx family members have been identified to play a significant role in several signaling cascades, but there remains to be a complete understanding of the function of several putative sites in many family members. The introduction of phosphomimetic and non-phosphorylatable mutants via genomic editing through systems such as CRISPR/Cas9 would be useful to determine the functional consequences of Prdx phosphorylation in normal non-transformed cells as well as cancer cells. Candidate phosphorylation sites to be studied further could be identified from proteomic screens in cancer cells such as those indicated in bold in


CD5 and CD6 are related surface receptors that limit and promote T‐cell responses. Co‐stimulatory effects of CD6 depend on binding a cell surface ligand, CD166, and recruitment of the intracellular adaptor proteins GADS and SLP‐76 by C‐terminal phosphotyrosines. We have continued to identify interactions of CD5 and CD6 to understand their roles in T‐cell activation. In a screen to identify binding partners for peptides containing a cytoplasmic sequence, SDSDY conserved between CD5 and CD6, we identified ezrin radixin moesin (ERM) proteins, which link plasma membrane proteins to actin. Purified radixin FERM domain bound directly to CD5 and CD6 SDSDY peptides in a phosphorylation‐dependent manner (DK = 0·5‐2 μm) at 37°. In human T‐cell blasts, mutation of the CD6 SDSDY sequence enhanced CD69 expression in response to CD3 monoclonal antibody. In this proximal readout, interactions of the SDSDY sequence were dominant compared with the C‐terminal tyrosines of CD6. In contrast, in a more downstream readout, interleukin‐2 expression, in response to immobilized CD3 and CD6 monoclonal antibodies, the C‐terminal tyrosines were dominant. The data suggest that varying functional effects of CD6 and potentially CD5 depend on interactions of different cytoplasmic regions with the cytoskeleton and alter depending on the stimuli. The two receptors are related, both containing three scavenger receptor cysteine‐rich (SRCR) domains in their extracellular regions and cytoplasmic tails with signalling potential. They have roles in limiting and promoting T‐cell responses in vitro and in vivo evidence for activating and inhibitory functions of the SDSDY sequence.in vitro analyses, the effects of mutant CD5 were inhibitory or activating depending on the stimulus and assay.Parallels between the behaviour of the two related receptors suggest mechanisms in common. There is a conserved sequence, SDSDY in the cytoplasmic tails of CD5 and CD6. In CD5, there is + T cells was observed whereas the activating effect of C‐terminal phosphotyrosines, which bind GADS and SLP‐76, dominated in a more downstream readout.We report interactions of ezrin, radixin and moesin (ERM) proteins with the SDSDY sequence of CD5 and CD6, identified using a proteomics approach. We measured a direct interaction between a FERM domain of an ERM protein and CD5 and CD6 peptides using surface plasmon resonance. The affinities of the interactions were dependent on phosphorylation of the SDSDY sequence. In cells expressing recombinant receptors, mutation of the SDSDY sequence to prevent phosphorylation altered responses. An inhibitory effect of the CD6 SDSDY sequence on proximal signalling in primary CD4NP_001093259 FERM binding site (amino acids 251–275): HLRQQRMGTYGVRAAWRRLPQAFRP.Peptides representing human sequences and biotinylated at the N terminus were obtained from Peptide Protein Research Ltd : CD5 pSDpSDpY, PDNSpSDpSDpYDLHGAQRL; CD5 SDSDY, PDNSSDSDYDLHGAQRL, CD6 pSDpSDpY, GpSDpSDpYEHYDFSAQ; CD6 SDSDY: GSDSDYEHYDFSAQ; control peptide (CD5), HVDNEYSQPPRNS; ICAM‐2  vector was kindly provided by Toshio Hakoshima .graphpad prism 7 software.For surface plasmon resonance analysis, CD5 pSDpSDpY, CD5 SDSDY, CD6 pSDpSDpY and CD6 SDSDY and ICAM‐2 peptides were immobilized on streptavidin‐coated CM5 chips in a BIAcore 3000 machine. Radixin FERM was injected over the immobilized peptides at 37°. Background signals of radixin FERM over a streptavidin‐coated flow cell were subtracted and equilibrium binding data were fitted using a 1 : 1 Langmuir binding model using HSU34623) containing rat CD6 domain 1 and cytoplasmic mutants were expressed as fusion proteins with enhanced green fluorescent protein (EGFP) using lentiviral vector (pHR‐EGFP) details and detected with rat CD6 domain 1 (OX52) and human CD6 domain 3 (OX124) monoclonal antibodies (mAbs) as described elsewhere.Chimeric CD6 (Genbank: + T cells were isolated using RosetteSep™ and transduced with lentivirus. Cells were stimulated for 18 hr at 37° with platebound CD3 (UCHT1) at a range of concentrations and/or platebound rat CD6 domain 1 mAbs  for CD69 expression and for interleukin‐2 (IL‐2) expression, with immobilized CD3 (2 μg/ml), rat CD6 domain 1  or a combination of CD3 and OX52 immobilized together at 5 μg/ml.n = 11, n = 14; wild‐type n = 11, n = 14; SDSDF n = 6, n = 10; ADADY n = 6, n = 10; ADADF n = 10, n = 14; Y629F Y662F n = 11, n = 13; ADADY Y629F Y662F n = 5, n = 8; ADADF Y629F Y662F n = 5, n = 6 were combined. Statistical analyses using analysis of variance with correction for multiple comparisons (Sidak) were carried out using graphpad prism 7 software.Primary T‐cell assays were conducted as described previously.+/H+ exchange regulatory cofactor (NHE‐RF) 1 and 2. ERM proteins have an established role in connecting plasma membrane proteins to the underlying actin cytoskeleton.To identify potential interacting binding partners for the CD5 and CD6 cytoplasmic SDSDY sequence, we conducted pulldown experiments using Jurkat cell lysates and CD5 or CD6 serine and tyrosine‐phosphorylated pSDpSDpY peptides. Five proteins were repeatedly isolated with CD5 and CD6 pSDpSDpY peptides and were not identified in pulldowns with an unrelated control peptide Table . There wIt was plausible that the cytoplasmic regions of CD5 and CD6 bound directly to FERM domains of the ERM proteins in a manner comparable with several other transmembrane proteins.D = 1–2 μm for CD5 and KD = 0·5–2 μm for CD6. The affinity of radixin FERM for the ICAM‐2 peptide was measured as KD ≥ 0·2 μm, indicating that the radixin FERM domain protein was active , a single tyrosine mutant (SDSDF), a double serine mutant (ADADY), a triple mutant (ADADF), the C‐terminal mutant (Y629F Y662F) or with both regions mutated, (ADADY Y629F Y662F or ADADF Y629F Y662F) as EGFP fusion proteins.We tested the importance of phosphorylation of the SDSDY sequence for CD6‐mediated signalling in primary human CD4mutant Y69F Y662F n = 5 to n = 11) are collated in Fig. Cells were stimulated with platebound CD3 mAb.We assessed the relative effects of the two regions of the cytoplasmic region of CD6 on proximal T‐cell receptor‐mediated signalling by combining mutations of the SDSDY and the C‐terminus (ADADY Y629F Y662F and ADADF Y629F Y662F). In the proximal signalling readout of CD69 expression, responses by ADADY Y629F Y662F in which just the two serines in the SDSDY sequence were mutated and ADADF Y629F Y662F matched those of the SDSDY mutants, not the C‐terminal mutant (Y629F Y662F). The responses of ADADY Y629F Y662F and ADAF Y629F Y662F were significantly (shown for CD3 mAb 0·25 μg/ml) raised above that of Y629F Y662F . As we have shown previously, expression of CD6 increased the percentage of IL‐2‐positive cells in response to CD3 mAb and more markedly in the presence of the rat CD6 domain 1 mAb  of the interaction between the phosphorylated CD6 SDSDY peptide and the radixin FERM domain is comparable with the phosphorylated C‐terminal tyrosine interaction with the SH2 domain of SLP‐76.Binding of the cytoplasmic sequences in CD5 and CD6 to ERM proteins was novel in that it was dependent on phosphorylation. Dependence on phosphorylation suggested that negative charge was important for the interaction. This contrasts with basic residues in an ICAM‐2 peptide being important for the affinity of the interaction.3, leading to ERM protein activation and subsequent binding to other transmembrane proteins.The presence of NHE‐RF adaptor proteins which bind to a different region of the PTB‐like FERM subdomain among proteins isolated by the CD5 and CD6 peptides is consistent with the same or overlapping binding site for ICAM‐2 and the phosphorylated SDSDY sequence.489) may contribute to the electrostatic interaction with ERM proteins. Mutation of Y489F resulted in increased phosphorylation of CD6, indicating an inhibitory function and, similarly to the SDSDY sequence, was subservient to the effect of a C‐terminal mutation in IL‐2 production.Detection of phosphorylation of a cluster of serines including the two in the SDSDY sequence in the absence of stimulation is consistent with the functional effects of mutating these serines being observed in the absence of a strong stimulus Fig. b13. PhosTipping the balance from inhibitory to co‐stimulatory effects of CD6 seems to depend on the stimulus including engagement of other receptors. Increasing the number of antigen‐presenting cells obscured the inhibitory effects of transduced CD6 in a murine T‐cell hybridoma line.The region of ICAM‐2 that binds to FERM domains is membrane proximal in the linear amino acid sequence, and membrane proximal basic residues are commonly found in cytoplasmic regions of transmembrane proteins.+ T cells across the blood–brain barrier.+ cells showed reduced infiltration of the spinal cord in transgenic mice expressing CD5 with a deletion, SSDS, overlapping the SDSDY sequence, compared with the wild‐type transgene.During T‐cell activation, regulation of phosphorylation of ERM proteins facilitates redistribution of transmembrane proteins; for example, ezrin moves transiently to the site of cell contact.Can an interaction with ERM proteins account for dual activating and inhibitory effects of CD6 and by association, CD5? In preliminary experiments, mutation of the SDSDY sequence in CD5 in primary cells resulted in enhanced or reduced CD69 expression depending on the donor . In Jurkat cells, mutation of the SDSDY sequence in CD6 revealed that it had an activating effect on CD69 expression  leading to speculation that interactions of the SDSDY sequence contribute to the balance between inhibitory and activating functional effects by affecting transport or segregation of receptors rather than a direct interaction with a signalling enzyme.None declared.