The Northern Hemisphere experienced dramatic changes during the last glacial, featuring vast ice sheets and abrupt climate events, while high northern latitudes during the last interglacial (Eemian) were warmer than today. Here we use high-resolution aerosol records from the Greenland NEEM ice core to reconstruct the environmental alterations in aerosol source regions accompanying these changes. Separating source and transport effects, we find strongly reduced terrestrial biogenic emissions during glacial times reflecting net loss of vegetated area in North America. Rapid climate changes during the glacial have little effect on terrestrial biogenic aerosol emissions. A strong increase in terrestrial dust emissions during the coldest intervals indicates higher aridity and dust storm activity in East Asian deserts. Glacial sea salt aerosol emissions in the North Atlantic region increase only moderately (50%), likely due to sea ice expansion. Lower aerosol concentrations in Eemian ice compared to the Holocene are mainly due to shortened atmospheric residence time, while emissions changed little. Past climate changes in Greenland ice were accompanied by large aerosol concentration changes. Here, the authors show that by correcting for transport effects, reliable source changes for biogenic aerosol from North America, sea salt aerosol from the North Atlantic, and dust from East Asian deserts can be derived. Only recently the North Greenland Eemian Ice Drilling (NEEM) ice core4 allowed the reconstruction of the first Greenland climate record for the last interglacial period, showing pronounced warming on the Greenland Ice Sheet during the Eemian relative to the Holocene, accompanied by only moderate changes in ice sheet thickness.Greenland ice cores provide unique insight into climate changes over the last glacial cycle, revealing very cold conditions during the Last Glacial Maximum (LGM), relatively stable warm conditions during the Holocene and pronounced rapid warming events during glacial times (Dansgaard Oeschger (D-O) events)10. Chemical concentrations in the ice are affected by changes in aerosol emissions at the source, changes in atmospheric transport velocity and pathway, as well as changes in aerosol deposition en route and over the ice sheet. Due to this multifactorial control of aerosol concentrations in the ice, it has remained challenging to draw quantitative conclusions from these records about atmospheric concentration and source strength changes. This issue led to diverging interpretations of ice core aerosol records12. Some studies13 concluded that covariant changes in mineral dust and sea salt aerosol in Greenland point to large-scale atmospheric circulation changes being the main reason for their long-term variations. In contrast, other studies based on mineral dust aerosol size distributions and first order deposition estimates concluded that changes in mineral dust aerosol transport pathways were only of secondary importance14. Only recently, an ammonium (NH4+) record in annual resolution from the North Greenland Ice Core Project (NGRIP) ice core was used in combination with a simple transport and deposition model to systematically separate emission changes in the North American NH4+ source region from transport changes15.Greenland ice core aerosol records also reveal substantial variations in concentrations in the ice accompanying both slow and rapid temperature changes during the glacial15. In particular, we intend to answer the question how much of the strong variations in aerosol concentrations in Greenland ice over glacial/interglacial and stadial/interstadial16 transitions are due to changes in atmospheric circulation and precipitation and how much they are influenced by altered emissions. Further, we assess the NEEM aerosol concentration records during the Eemian with respect to potential high-latitude environmental changes connected to the amplified warming signal in high latitudes during that time which is similar to what would be expected in this region for a globally about 1 °C warmer world in the future17.Here, we investigate high to mid northern latitude environmental and atmospheric changes during the last glacial and the Eemian warm period, using the extended suite of aerosol species analysed in centimetre resolution on the NEEM ice core. We assess the environmental changes implied by the ice core aerosol concentration records using the transport and deposition model approach by ref. 19 and our extensive back-trajectory study  (and of soil derived nitrate (NO3−)) at NEEM originates from North American sources. The NH4+ found in preindustrial Greenland ice is primarily derived from nitrogen turnover in soils and vegetation as illustrated by the clear summer maximum in NH4+ deposition at NEEM and other Greenland drill sites20. Moreover, extraordinarily high NH4+ peaks during summer in some years are derived from boreal wildfires mainly in North America20. A marine biogenic source is only of secondary importance in Greenland21. In the case of NO3−, additional important sources of nitrate precursors are NOx production from lightning at high and mid northern latitudes as well as downward transport of NO from stratospheric oxidation of N2O22.Previous studies25, however the relative contributions of the open ocean and sea ice are more difficult to assign for Greenland. A back-trajectory analysis performed for this study  to Greenland originate from the open ocean of the North Atlantic12. However, those trajectories are also connected to higher precipitation, hence greater loss en route, than air masses originating from more local marine source regions such as Baffin Bay. Simulations with a 3D-transport-chemistry model27 suggest that sea ice related processes  contribute up to 50% to the recent winter maximum in sea salt aerosol concentrations at NEEM. In summary, we conclude that a large part of the sea salt aerosol in Greenland today comes from the open North Atlantic, however sea ice, especially in Baffin Bay, represents a significant additional winter source, which is expected to become relatively more important in glacial times, when sea ice largely expanded.In Antarctica, sea ice is suggested to be the major source of sea salt aerosol29. Given that the major source region does not change substantially over time, it is reasonable to assume that also the elemental composition of the mineral dust aerosol mobilized at the source did not change substantially. Here, we use high-resolution Ca2+ data to quantify past changes in mineral dust aerosol. From the East Asian source regions mineral dust derived Ca2+ is efficiently uplifted by high wind speeds during dust storms into the upper troposphere (ref. 30 and references therein) in boreal spring, allowing for efficient long-range transport to the Greenland ice sheet. The remote source location of mineral dust derived Ca2+ and its transport at high altitudes above cloud-level imply longer transport times and reduced wet deposition en route33 compared to the other major aerosol species found in Greenland ice (see Methods). Mineral-dust derived Ca2+ (which is partly soluble) may have a somewhat different atmospheric residence time compared to particulate dust. This could lead to different relative changes in Greenland ice core concentrations, however, long-term changes in the Ca2+/dust ratio in Greenland ice are typically smaller than a factor of 2  aerosol in Greenland are mainly derived from Northern Hemisphere marine biogenic (dimethyl sulfide) and non-eruptive volcanic emissions36. In addition, volcanic sulfur emissions into the stratosphere strongly influence sulfate concentrations in the years directly following major eruptions37. Only a small terrestrial contribution to current Greenland SO42− levels exists, but may have varied somewhat on glacial/interglacial time scales38.Finally, preindustrial background concentrations of sulfate  and mineral dust aerosol (Ca2+) based on continuous melt water analyses (see Methods section). The records essentially cover the time interval from the Eemian to the early Holocene period in 10-year resolution. In line with previous studies, all aerosol concentrations in the ice exhibit millennial-scale variability in parallel to local temperature changes as indicated by δ18O of the ice  are temporally changing precipitation at NEEM, which locally affects the deposition of the ion species, and temporally changing precipitation en route, hence atmospheric residence time, during transport from the source region to the ice sheet. As the precipitation rate en route for the past is not known from paleodata, we assume that it linearly scales at first order with changes in accumulation at NEEM (see Methods section), assuming that large scale circulation changes from the source to Greenland control the precipitation at NEEM and en route. Correcting for these temporal changes in aerosol deposition, we can derive the net changes at the source potentially related to factors as changes in aridity, wind speed or biogenic activity.Applying a simple mean aerosol transport model39, while regional changes in wind speed may have occurred. Somewhat higher glacial wind speeds are modelled in the mid latitude North Atlantic region as well as a switch of the jet stream from a glacial strong zonal to a more meridionally tilted interglacial configuration40. However upstream of Greenland, wind speed changed only little40. Overall the magnitude of regional wind speed changes is on the order of tens of percent, while the expansion of the continental ice sheets and sea ice is very large, effectively suppressing a huge part of recent continental and open ocean source areas in the glacial. Accordingly, the about two times larger distance from the aerosol source to Greenland is likely to dominate the transport time variations. In our best-guess model runs we assumed a factor of ~2 longer glacial transport time for continental NH4+ and marine Na+, reflecting the expansion of the Laurentide ice sheet and North Atlantic permanent sea ice cover, respectively. In addition, we performed sensitivity runs to assess the effect of varying transport time.Changes in transport time from the source to NEEM are controlled by potential changes in glacial wind speeds relative to modern times on the one hand and larger glacial transport distance due to expansion of continental ice in North America and multiyear sea ice cover in the North Atlantic region on the other. Observational evidence for past wind speed is rare. Atmospheric models suggest a relatively small surface wind speed change on a global average41 showed that the source region, hence the transport distance to Greenland, remained essentially the same in the glacial and interglacial. Atmospheric models find that the jet stream may have been seasonally somewhat stronger than present40 and may have been split around the Laurentide Ice Sheet during the LGM42, however, wind speed changes were much smaller than a factor of 2. Another possibility for a change in dust transport time could be a contribution of glaciogenic dust on the North American continent in glacial times. Dust model runs show an improved agreement with Greenland dust deposition when tuning glaciogenic dust source strength in the US great plains for glacial conditions43, however, these sources were previously rejected based on the isotopic signature of dust in Greenland ice cores29. In summary, in our best-guess scenario we assumed the location of the main dust source region and the transport time from the East Asian desert regions to NEEM to stay constant in time, but performed sensitivity studies for a very wide range of transport time scenarios  compared to the glacial  that is markedly smaller than the change directly measured in the ice. While Na+ concentrations in the ice change by a factor of up to 10 between glacial and interglacial, the emissions of sea-salt aerosol during colder periods were increased by only a factor of about 1.5  into account. Due to the much lower precipitation rate en route assumed for Ca2+ along its upper troposphere transport pathway from East Asian desert regions to Greenland, much stronger temporal changes in source strength are reconstructed by our simple model compared to sea salt aerosol. The Ca2+ source concentration, reconstructed assuming that East Asian desert regions were always the major source of mineral dust aerosol in Greenland, is enhanced considerably by up to a factor of about 8 in the Last Glacial Maximum (LGM) compared to the early Holocene in line within the uncertainty with mineral dust aerosol flux changes recorded in a northern Pacific sediment core downwind of Asian dust sources51. Stadial emissions are increased by up to a factor of 10 relative to the early Holocene and by about a factor of 4 relative to interstadials , i.e., representative of dust aerosol transport below cloud level), would imply much smaller source changes. In view of current observations of mineral dust mobilization in East Asian dust areas and its long-range transport to Greenland at high altitudes, such high precipitation rates are, however, very unlikely.We also applied our transport model to the Caals Fig. . The amp2+ concentration increase in the ice by at least a factor of ~5 over the last glacial cycle. Thus according to our idealized transport model, Ca2+ concentration changes in the NEEM ice core are primarily attributed to changes in the source strength in the East Asian desert regions with only a secondary albeit sizable influence of transport related changes . In line with previous work52, we propose that glacial environmental changes involved strongly enhanced dust storm activity with  higher wind speeds and enhanced gustiness over the East Asian desert regions, increased aridity related to changes in the Asian monsoon system34, and/or a shift in position or strengthening of the jet stream over East Asia during cold climate conditions.The results imply that transport/deposition effects contributed to the 40–80 fold Ca42−, the reconstructed changes in sulfate aerosol show little change in peak glacial source concentrations compared to the early Holocene—as was the case for sea salt aerosol—but a more pronounced stadial/interstadial variability—as seen in mineral dust aerosol . However, we attribute the observed concentration changes in the ice mainly to the higher precipitation rate en route (see below and the Methods section for estimates of past precipitation rate) during the Eemian, which led to enhanced wet deposition during transport.In addition to the glacial/interglacial and stadial/interstadial variations in environmental conditions recorded in the NEEM aerosol concentration records, we are now for the first time able to compare aerosol concentration records from the Eemian interglacial period in Greenland ice with the early Holocene. The Eemian is characterized by similar or lower concentrations in the ice in all five aerosol species, with particularly pronounced reductions in Na3− Figs.  and 3. T54) due to higher Eemian temperatures, our transport model predicts also higher precipitation rates en route. Correcting for the accompanying transport deposition effects shows that the median in Eemian NH4+ and NO3− source concentrations . This may suggest slightly higher dust emissions in the East Asian desert regions, potentially related to increased aridity or uplift.For the mineral dust aerosol tracer Ca58. Despite the different causes of the Eemian warming  and the present anthropogenic climate change , the Eemian temperature distribution looks similar to the polar amplification signal expected for a global warming of 1.5–2 °C by the end of the 21st century59. Allowing for caveats in rates of change and transient vs. equilibrium climate response, our records may serve as a first order estimate of environmental changes in the mid to high latitude Northern Hemisphere at 2100. Accordingly, our records suggest that keeping global warming below 1.5–2.0 °C will likely avoid drastic changes in the environmental factors in this region controlling the formation of the aerosol species investigated in this study.In summary, the reductions observed in Eemian ice core concentrations largely disappear when the higher wet scavenging in the Eemian is taken into account. The remnant environmental changes reflected in aerosol source changes during the Eemian are moderate, even though the Eemian was significantly warmer in the Arctic, and globally showed significant warming and elevated sea level4). The NEEM core shows clear stratigraphic disturbances in the bottom part due to folds in the ice. However, the stratigraphy was successfully restored4, resulting in the first dated Eemian climate record from a Greenland ice core. The folding in the ice results in replicate sections of ice from certain age intervals  and in a gap (110–114 kyr BP) in the records due to missing ice in the vertical profile of the Greenland ice sheet at NEEM  per year) was drilled and recovered to a depth of 2540 m  at NEEM led to sizable adsorption/desorption effects in the CFA system. This implies that the Ca2+ concentration at the beginning of each 110 cm run was systematically too low but approached the true mean concentration within several tens of centimeters. We used an empirical correction to remove this artificial trend in each run by assuming that the mean of the second half of each run is representative for the entire run  system2+, Na+, NH4+, NO3−, H2O2, and insoluble particles) other analytical systems were connected to the melthead and sample distribution system. These comprised: Fast Ion Chromatography (FIC) ; a Single Particle Soot Photometer (SP2) to detect black carbon particles; and various sampling vials to collect the uncontaminated part of the waste lines for additional discrete low-resolution Ion Chromatography (IC), Coulter Counter (CC), inductively coupled plasma mass spectrometry (ICPMS), and tephra measurements. The British Antarctic Survey FIC system used two discrete anion chromatography channels with rapid isocratic elution through columns held at high temperature to reduce eluent viscosity and column pressure. The full suite of anions was eluted in 2.7 min, while interlacing of the two channels allowed a sample to be injected every 1.35 min. Continuous loading of one channel or the other from the melthead liquid flow implies that the depth resolution was 1.35 times the melt speed . We report here the sulfate data from a single channel through the whole section, i.e., approximately an average over 5 cm of ice every 10 cm of ice.In addition to the measurements incorporated in the CFA analysis system , 15 cm during interstadials and 5–10 cm during stadials in the time interval 28–59 kyr BP (corresponding roughly to MIS3). In the time interval 59–70 kyr BP  the layer thickness is further reduced due to low accumulation and thinning, resulting in 10 year means which are recorded within 3–4 cm of ice, while it is again more than 5 cm from 70 to 96 kyr BP. Due to a kink in the layer thickness of the age scale at 96 kyr BP62, 10 years correspond to only 1–2 cm between 96 and 110 kyr BP. In the Eemian warm period , 10 years correspond to 2–10 cm of ice4. Thus, with the resolution of our CFA, we achieve 10 year resolution throughout the entire NEEM ice core except for the time interval 96–110 kyr BP, where the resolution, however, is still better than 20 years. For the FIC single channel sulfate data, the maximum resolution that can be achieved over the entire length of the core is only about 40 years, however decadal resolution is possible over an extended time period between the Holocene and 60,000 years BP. We provide a record in 40 years resolution in Fig. NEEM CFA data is available in 1 mm resolution. However, due to sample dispersion in the system, analytic response time, and the melt speed, the effective resolution is reduced+ is largely derived from sea salt aerosol in Greenland, however, there may be a small contribution of Na+ from mineral dust in occasionally occurring thin layers with very high dust content. Here we use only 10 years averages, which are not significantly affected by a mineral dust contribution. Vice versa, Ca2+ is dominated by mineral dust sources, but also a small sea salt contribution cannot be excluded. The sea salt contribution to Ca2+ has been estimated using the mean Na+ concentration in the ice and the Ca2+/Na+ ratio in sea water to be around 10% in the Holocene but much less in the glacial, where very high mineral dust levels prevail12. In view of this small contribution, we refrain from a sea salt correction of our Ca2+ data.Na15 and applied this deposition model  back to the concentration in the atmosphere (Cair) above the deposition site according to:A is the accumulation rate, εs is the scavenging ratio in snow, and vdry is the dry deposition velocity.To simulate the deposition process we followed the simple approach by Fischer et al.C0) of the respective component. We use a simple model of aerosol atmospheric transport along a mean transport air mass trajectory assuming an exponential decrease of the concentration in the air parcel on its way to the ice sheet15 leading to:The reconstructed atmospheric concentration is then used as starting point to calculate the concentration in the air at the source  and over the ice εs (representative for snow) we used typical literature values listed in Supplementary Table Here, + of the same order as the observed glacial/interglacial and stadial/interstadial variations. For NH4+, however, where only glacial/interglacial variations in the source concentrations are observed, the uncertainty is significantly smaller than the observed long-term changes. The same holds true for Ca2+, where also stadial/interstadial changes in the source strengths are much larger than the uncertainty.Based on this model we performed a systematic Gaussian error propagation and performed sensitivity runs to constrain the uncertainty of this reconstruction and their impact on our conclusions. The uncertainty of the deposition effect is dependent on the deposition velocity, hence also on the scavenging ratio, which has a large uncertainty itself. This implies that the uncertainty of the reconstruction is generally large and in the case of Nah for NH4+, NO3−, Na+, SO42−, and Ca2+ of 4 km but also used 8 km in a sensitivity run for Ca2+  and marine  boundary layer. This led to P0,terr = 815 mm water equivalent (WE)/year and P0,mar = 1288 mm WE/year for terrestrial and marine trajectories, respectively. For sea salt aerosol this translates to a modern atmospheric residence time of 1.6 days, in line with the wet deposition lifetime in global circulation models39. Since precipitation in the upper troposphere above cloud level is strongly suppressed, we reduced the effective precipitation rate for Ca2+ to P0,dust = (0.1 ± 0.1) ·P0,terr. This leads to modern atmospheric residence times of 7.3 days, in very good agreement with global circulation model studies43. In addition, we performed a sensitivity run where we reduced the current precipitation rate en route for dust only to one third of the below-cloud value  and 6.4 days for NH4+ and NO3− (main source region is North America between 40° and 70°N). The mean values vary somewhat dependending on assumed boundary level height and altitude of the back-trajectory starting level above the NEEM site. We include this variability in the uncertainty estimate (1 day) of our transport time. In the case of Na+, which is both of open ocean and sea ice origin, the transport time to NEEM for the modern sea ice source in winter (mainly located in the Baffin Bay) is shorter than 5.7 days, however, the number of trajectories from the Baffin Bay to NEEM has only a small influence on the mean annual transport time. To study the potential influence of the range in transport times we performed sensitivity runs displayed in Supplementary Fig. For the modern transport time, we use the average time of all back-trajectories  starting at NEEM to reach the boundary layer at the source region for the first time. These mean values are ~5.7 days for Na2+ from East Asian dust origin it is not possible to estimate the current transport time using back-trajectories, because very long back-trajectories become increasingly uncertain and the back-trajectories will very rarely enter the boundary layer in the Asian desert source regions. In fact, a maximum 10-day back-trajectory analysis for the NEEM site showed very little chance for air parcels to originate from East Asian desert regions  and SO42− from the ocean surface were shifted southward63, i.e., away from Greenland, which leads to a generally longer transport time t. It is very difficult to quantify these two contrary effects without dedicated 3D modelling studies, however, in view of the vast expansion of continental ice cover in North America and in sea ice cover around Greenland and over the North Atlantic, the longer transport distance is likely to dominate changes in the transport time and in our best-guess estimate we assume a two-fold increase in transport time under glacial conditions.During the last glacial period, wind strength between mid and high latitudes may have been enhanced through more pronounced meridional pressure and temperature gradients. This would lead to faster  circulation and enhanced  eddy mixing, hence to a potential decrease in transport time t constant for all species but performed individual runs over a large range of transport times for NH4+, Na+, and Ca2+ , where the residence time is short, the effect of transport time is much larger. Higher glacial sea salt aerosol source concentrations relative to the early Holocene can only be achieved either by short constant mean transport times of around 3 days (not supported by our back-trajectory study) or by increasing transport time in the glacial relative to today as expected from the longer glacial transport distance from the source region to NEEM. Assuming a constant transport time of 5.6 days as today would imply slightly reduced glacial sea salt aerosol emissions, which is highly unlikely in view of higher wind speeds and increased sea ice formation under cold climate conditions. Our best-guess estimate implies about a factor of 1.5 higher sea salt aerosol emissions with a potential range of 1–2. Increases by a factor of 3 are less likely and also reduced glacial source concentrations are still possible within our error limits.In our sensitivity runs, we kept transport time 2+ the location of the main source region (predominantely East Asian deserts) is assumed to remain the same for the glacial as for the interglacial as suggested by previous provenance studies29. Combined with stronger and more zonal jets (which are the main transport pathway for particulate dust and Ca2+) during glacial climate conditions, this could lead to decreased glacial transport time and, thus, to more efficient transport. Accordingly, in addition to our best-guess Ca2+ run (where transport time was constant at 11.5 days), we performed runs with lower or higher but constant transport time and an alternative run where transport time t scaled with temperature, thus, transport during the LGM being only about half as long as during the Holocene. The results of these alternative runs are contrasted with the constant t runs in Supplementary Fig. 2+ to 1/3 of the below-cloud value (instead of 1/10 in the best-guess run) reduces the increase in glacial source concentrations substantially to only a factor of 2 compared to the early Holocene. Thus, the assumption on the degree of wet deposition en route, i.e., the atmospheric residence time controlled by wet deposition, is the most critical parameter for our mineral dust aerosol source reconstruction. In view of the modern atmospheric residence time of mineral dust aerosol in our approach being supported by global circulation modelling studies43 and because of the agreement of past mineral dust aerosol changes in our reconstruction with data from the northern Pacific51, the very low wet dust deposition during transport, as assumed in our best-guess run, appears to reflect atmospheric conditions realistically.For Ca4 increase at the onset of both interglacials64. As the NEEM age scale in the Eemian has been derived by synchronizing the NEEM gas records4 with respective EPICA Dronning Maud Land (EDML) ice core records and as the NGRIP/NEEM age scales for the Holocene have been previously synchronized to EDML65, we can use the EDML CH4 record to define a common onset of both the Eemian and Holocene time period  are synchronized. Due to the brittle ice, it was not possible to measure the entire Holocene section of the NEEM ice core using our CFA analysis. Accordingly, the windows for the Eemian–Holocene comparison were chosen of the same duration within the periods of stable δ18O: 7.6–9.8 kyr BP vs. 124.3−126.5 kyr BP.As this is the first time records of ice core impurities cover the entire last interglacial period in Greenland are available, we are now able to compare the current warm period with the Eemian in terms of aerosol concentrations. However, to allow for an unbiased comparison we have to synchronize the Eemian and Holocene sections by shifting the age scales to a common onset of both interglacials. To this end, we superimposed the two warm periods synchronizing the fast CH62, available for the time period from 108 kyr BP to the present. This accumulation rate was also used to scale the precipitation en route as described above and used in our model reconstruction in Fig. 18O values of the snow and ice in Greenland. These temperature-δ18O-accumulation relationships were determined using various ice cores from different sites on the Greenland ice sheet covering the most recent period66, or the Holocene and the last glacial period68. The relationships determined in these studies range from a 8% to 14% increase in accumulation for each permil increase in δ18O. Only ref. 68 found a stronger dependency of accumulation on δ18O during the last glacial of ~17%/‰. However, it remains unclear if this strong relationship remained valid also for earlier warm periods on the Greenland ice sheet. For example an increase in the fraction of summer precipitation due to the strong change in summer insolation during the Eemian69 may alter the δ18O-accumulation relationship. In the absence of any direct accumulation proxy or model-based results from age scale calculations for the Eemian period, we assume the local spatial δ18O-accumulation relationship to be valid also during the Eemian. In line with the location of the NEEM site, we use the relationship as described by Buchardt et al.54 for north-west Greenland sites, which represents an intermediate δ18O-accumulation sensitivity:A being the accumulation rate in cm ice IE per year, 20.5 cm IE/year the modern accumulation rate and −33.7‰ the mean modern δ18O value at the NEEM site. In order to account for the entire range covered by the different estimates of the interglacial δ18O-accumulation relationships as mentioned above, we use an uncertainty of the Eemian accumulation rate of ±10%, which is considerably larger than the uncertainty indicated in Buchardt et al.54. To avoid a systematic bias when comparing Eemian with early Holocene source concentrations in Fig. 62. Using Eq. (For the past accumulation rates at NEEM over the last glacial we used the values modelled by ref. All data generated or analysed during this study are included in this published arcticle (Supplementary Data Supplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2


The incidence of lumbar disc degeneration disease has increased in recent years. Lumbar interbody fusion using two unilateral pedicle screws and a translaminar facet screw fixation has advantages of minimal invasiveness and lower costs compared with the traditional methods. Moreover, a method guided by a three-dimensional (3D) navigation template may help us improve the surgical accuracy and the success rate. This is the first randomised study using a 3D navigation template to guide a unilateral lumbar pedicle screw with contralateral translaminar facet screw fixation.Patients who meet the criteria of the surgery will be randomly divided into experimental groups and control groups by a computer-generated randomisation schedule. We will preoperatively design an individual 3D navigation template using CATIA software and MeditoolCreate. The following primary outcomes will be collected: screw angles compared with the optimal screw trajectories in 3D digital images, length of the wound incision, operative time, intraoperative blood loss and complications. The following secondary outcomes will be collected: visual analogue scale (VAS) for back pain, VAS for leg pain and the Oswestry Disability Index. These parameters will be evaluated on day 1 and then 3, 6, 12 and 24 months postoperatively.The study has been reviewed and approved by the institutional ethics review board of the Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University. The results will be presented at scientific communities and peer-reviewed journals.ChiCTR-IDR-17010466 This is the first multicentre randomised controlled trial to compare a three-dimensional (3D) navigation template for guiding a unilateral lumbar pedicle screw with contralateral translaminar facet screw fixation versus traditional multiple X-ray fluoroscopy.We will first use Mimics and CATIA software to design the 3D navigation template of a unilateral lumbar pedicle screw with contralateral translaminar facet screw fixation.The clinical data will be collected prospectively at least 24 months after the operation.Because this is a multicentre randomised controlled trial, the surgeons’ experiments at different research sites may influence the outcomes.With the ageing of society, the incidence of lumbar disc degeneration disease is increasing,et alet alThe translaminar screw is a long screw that goes through the spinous process and zygapophyseal joints and ends in a lower vertebral facet to fix the other side of the joint.However, there is higher risk of nerve and vascular injury when the angle deviation of the translaminar screw or screw entry point is incorrect.To the best of our knowledge, there are no randomised controlled studies of a 3D navigation template versus traditional multiple X-ray fluoroscopy for guiding a unilateral lumbar pedicle screw with contralateral translaminar facet screw fixation. In this study, we will conduct a randomised controlled trial (RCT) to compare 3D navigation template for guiding a unilateral lumbar pedicle screw with contralateral translaminar facet screw fixation versus traditional multiple X-ray fluoroscopy.The study has been reviewed and approved by the institutional ethics review board of the Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University. All of the participants will sign their informed consent. The protocol has been registered in the Chinese Clinical Trial Registry (ChiCTR), assigned to be the representative registry of China to join the WHO ICTRP in 2007, with protocol number ChiCTR-IDR-17010466. The 2013 SPIRIT checklist ); andInefficacy after strict conservative treatment for more than 6 months.Serious deformity of the lumbar vertebrae;Dysplasia of the lumbar pedicle or vertebral lamina;Obvious osteoporosis of the lumbar vertebrae;Metabolic bone diseases such as osteomalacia or Paget’s disease;Spondylolisthesis grade >2 (Meyerding);Cauda equina injury or severe radiculopathy;Postinflammatory instability of the vertebral spine;Body mass index >30;Immunological diseases or metabolic syndrome;Therapy with systematic corticosteroids or immunosuppressants; andCurrent use of Coumadin (warfarin) or heparin therapy for more than 6 months at the time of the operation.We performed a power analysis to assess the required sample size to show safety with a power (1−b) of 0.8 and α of 0.05. Based on the pre-experiment and related literature,Patients will be randomly divided into an experimental group and a control group using a computer-generated randomisation schedule. The random sequence will be stored in a sealed opaque envelope to ensure that the patients, personnel and the outcome assessor will be blinded to the group allocation. Until the last questionnaires have been completed, the participant’s allocated intervention will be revealed by the study secretary. If a patient's condition deteriorates, the blinding experiment will be terminated, and the patient’s safety will be given the highest priority .After screening, patients meeting the inclusion criteria should participate in the study as long as possible. If not, we must save the record to judge bias. Meanwhile, recording the patient’s basic information is necessary to discuss the results of the experiment.Before the experiment, we will explain the purpose of the experiment and the importance of the experimental procedures, to obtain consent and ideal compliance. If the selected patient is unqualified, elimination will be undesirable, and the data of the patient will be substituted by the average of the group. Furthermore, loss to follow-up is inevitable; the data of these patients will also be replaced by the average.Surgeons and data collectors will undergo training, and a preliminary experiment involving the data measurement and questionnaire will be conducted in advance. Recording the time and staff is necessary when the collector gathers the data, which will be convenient to review.A retrospective review of all patients will be conducted by examining their medical records before the operation. The involved segments were identified via a C-arm machine and then marked on the patient’s skin. The patients’ CT images with a thickness less than 1 mm will be exported from the Star PACS image system of the hospital and imported into the Mimics 16.0 to construct 3D images, in which we adjust the threshold depending on the bone density. We regard the two adjacent segments as a functional segmental unit (FSU), such as L2-3, L3-4, L4-5 or L5-S1.Then, the individual 3D navigation templates will be designed and printed using CATIA software and MeditoolCreate. The detailed steps are as follows: the FSU digital data in the Mimics 16.0 will be saved in STL format and imported into CATIA software. We will establish the optimal screw trajectory, which includes two vertebral pedicle screws trajectories and one contralateral translaminar facet screw trajectory. We will measure three angles of the translaminar facet screw trajectory: α, β and γ; α is the angle between the screw trajectory and the vertical line in the anteroposterior view; β is the angle between the screw trajectory and the upper endplate of the lower vertebra in the lateral view; γ is the angle between the screw trajectory and the midline of the lumbar vertebra in the top view . The pedAfter the optimal screw trajectories were determined, the curved posterior surface of the lumbar vertebra around the screw entry point was extracted to create the 3D navigation template . Then, wThe 3D navigation template will be sterilised and used to guide the screw in further operations on the patients. In experimental group, the dissection of the paraspinal tissue will performed at one side to expose the part of spinous process, laminar and facet joint; the 3D navigation template will be attached to the surface of the above bony construction. Then, the Kirschner wire (K-wire) will be inserted inside the 3D navigation template, and a trajectory for the screw will be fashioned with a cannulated drill; screws will be subsequently introduced. In the control group, multiple X-ray fluoroscopy will be used, and the screw trajectory will be adjusted by intraoperative X-ray fluoroscopy.After the operation, CT scans of the patients in both groups will be obtained, and the α1, β1, γ1, δ1 and ε1 angles will be measured corresponding to the angles of the optimal screw trajectory in 3D images. The placement and position of the screws will be divided into three types .Screw angles compared with the optimal screw trajectories in the 3D digital images and the position of the screws.Wound incision length, operative time, intraoperative blood loss, times of X-ray exposure and complications.VAS for back pain;VAS for leg pain; andODI.The data will be collected preoperatively; on day 1 postoperatively; and then at 3, 6, 12 and 24 months postoperatively.2 test.All data will be analysed using SPSS V.19.0 software. The differences in wound incision length, operative time, intraoperative blood loss and angles between the two groups will be analysed using a two independent-sample t-test with an α of 0.05. VAS and ODI scores at preoperation, postoperation, 3 months postoperatively, 6 months postoperatively and 12 months postoperatively will be analysed using a repeated-measures analysis of variance. The times of X-ray exposure and frequency of screw penetration out of the cortex will be compared using the χet alet alTranslaminar facet screw fixation has been reported as a minimally invasive technique,Current computer-assisted surgery systems can achieve the accurate screw trajectory; however, the cost of computer-assisted surgery systems is considerable, and the manipulation is too complicated,Combining 3D reconstruction and 3D rapid printing is a new mode of production, which is applied in many fields because of the advantages of visualisation, plasticity and rapid printing.In this study, we will compare the 3D navigation template to multiple X-ray fluoroscopy for guiding a unilateral lumbar pedicle screw with contralateral translaminar facet screw fixation. The compared results will include the perioperative parameters ; screw angles of α1, β1, γ1, δ1 and ε1; postoperative complications; the VAS of back and leg pain; and the ODI.The main strength of the study is the design as an RCT rather than an observational comparative study. An RCT has the advantage of controlling all possible variables due to the random sequence generation as opposed to observational studies, where confounding and bias may be more problematic. High-quality RCTs are generally regarded as the gold standard for studying the effectiveness of an intervention.Because of some patients’ death, relocation or other reasons, the representativeness of the sample is destroyed. Meanwhile, if some patients accept experimental treatment measures such as therapeutic drugs, the results will appear to be deviated. For these experiment biases, strict monitoring can reduce the loss of follow-up and can also improve patient compliance, through which bias will decrease.The study had been reviewed and approved by the institutional ethics review board of the Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University. The procedure will be performed following the principles described in the Declaration of Helsinki. All of the participants will sign their informed consent. The protocol has been registered in the ChiCTR, assigned to be the representative registry of China to join the WHO ICTRP in 2007, with protocol number ChiCTR-IDR-17010466.We will share individual patient data within 2 years after the trial is completed, and the original data will be collected using a clinical recording formula (both paper and electronic versions). The results will be presented at scientific communities  and peer-reviewed journals.


The calculated enthalpy of formation agrees with experimental measurements of related hollandite phases from melt solution calorimetry. Ground state geometry optimizations show that, for intermediate compositions , the presence of both Cs and Ba in the A-site tunnels is not energetically favored. However, the decay heat generated during storage of the Cs-containing waste form may overcome the energetics of Ba and Cs mixing in the tunnel structure of hollandite. The ability of the hollandite structure to accommodate the radioparagenesis of Cs to Ba is critical for long term performance of the waste. For the first time, B-site ordering was observed along the tunnel direction ([001] zone axis) for the Ga-hollandite compositions, as well as the intermediate Al-hollandite composition. These compositionally dependent structural features, and associated formation enthalpies, are of importance to the stability and radiation damage tolerance of ceramic waste forms.The titanate-based hollandite structure is proposed as an effective ceramic waste form for Cs-immobilization. In this study, quantum-mechanical calculations were used to quantify the impact of A-site and B-site ordering on the structural stability of hollandite with compositions Ba A Ba- and Cs-containing hollandite is predicted to form during fabrication of multiphase ceramics from melt processing2. Hollandite has a general formula of Ax8O16 and structurally consists of TiO6 and BO6 octahedra, with A-site cations held within the tunnel cavities3. Cs is known to incorporate into the A-site tunnels of hollandite during processing, while other dopants such as Zn and Ga are incorporated as B-site cations to maintain charge neutrality4. Since 137Ba is a major decay product of 137Cs, Ba-hollandite is a promising material to account for radioparagenesis.Cesium is a key fission product in spent nuclear fuel. With a half-life of 30 years, Cs-137 releases a large amount of heat from radioactive decay. Current spent fuel and high level waste disposal strategies call for Cs-immobilization in glass waste forms; however, multiphase ceramic waste forms have the potential to sequester the myriad of elements included in advanced multi-component waste streams1.04Cs0.24Ga2.32Ti5.68O16 with 4 at% loading; however, recent work has investigated higher Cs-loading with the synthesis of a pure Cs-hollandite end member 6. In terms of stability, different B-site cations may impact the thermo-stability of the hollandite structure2. Different B-site cations also impact the amount of A-site cations in the lattice necessary to maintain charge neutrality. A challenging stability problem arises in multiphase ceramic waste-forms containing more than one type of B-site cation. Studying the potential for cation and vacancy ordering in hollandite structures will contribute to the understanding of the stability of hollandite over geologic timescales associated with waste storage.The typical hollandite composition reported in waste form literature is close to Ba6. Costa et al.7 discussed B-site dopant effects on the thermodynamic stability of hollandite for a single composition of Ba1.04Cs0.248O16. In this paper, both the A-site composition and B-site dopant effects are systematically explored using density functional theory calculations.In our previous work, we investigated the compositional effect of the A site of Ga-doped hollandite, where increasing Cs concentration corresponds to increased structural and thermodynamic stability of the hollandite phase12 and defect ordering15 in ceramic waste form materials. Fluorite-related structures, such as pyrochlore, have proven resistant to radiation damage17, which has been attributed to the flexibility of the system to withstand disorder19. Such disorder has been observed experimentally and both confirmed and predicted computationally. Here, DFT calculations are used to quantitatively compare the energetic favorability of different A-site and B-site configurations across a range of hollandite compositions with a fixed A-site occupancy. Ordering observed through theoretical simulations can guide future experimental exploration into preferential cation ordering in hollandite with implications on radiation damage tolerance and long-term stability related to radioparagenesis.Density functional theory (DFT) calculations have been used to investigate cation incorporation20 for the electron correlation and exchange energy as implemented in the CAmbridge Serial Total Energy Package (CASTEP)21. Ultra-soft pseudopotentials were used to describe the behavior of the core electrons and their interactions with the valence electrons, while Ba 5s/4d2 5p6 6s2, Cs 5s/4d2 5p6 6s1, Zn 3d10 4s2, Ga 3d10 4s2 4p1, Al 3s2 3p1, Ti 3s2 3p6 3d2 4s2, and O 2s22p4 valence electrons were calculated explicitly. A k-point mesh of 2 × 2 × 2  was used for the 1 × 1 × 3 hollandite supercell calculations. A k-point mesh of 1 × 2 × 2  was used for the 2 × 1 × 3 supercells. An energy cut-off of 700 eV was chosen based on initial convergence testing. Electronic and geometry convergence criteria for total energy per atom was set to 2 × 10−6 eV and 2 × 10−5 eV, respectively.Quantum-mechanical DFT calculations were performed using the generalized gradient approximation (GGA) with the Perdew-Burke-Ernzerhof functional+ and Ba2+. The occupancy of the A-site ranges from one-half to one mole fraction depending on both the A-site and B-site dopant22. Hollandite with divalent A-site cations generally have tunnel site occupancy near one-half and less than two-thirds, while hollandite with monovalent cations, such as Na, K or Cs, have tunnel site occupancy of two-thirds to three-quarters, depending on the cation size. For this study the occupancy was 1.33/2 (two-thirds filled), which is achievable for both divalent Ba and monovalent Cs. For the 1 × 1 × 3 supercell used in this study, 4 of the 6 A-sites are occupied. Additional calculations were performed for 2 × 1 × 3 supercells of a subset of hollandite compositions to clarify energetic and structural trends according to increasing Cs concentration. The B-site is predominately composed of Ti4+, as well as di and/or trivalent cations for charge-balance. For this study, Zn2+ and Ga3+ were used. Al-hollandite was also included for comparison to experimental calorimetry measurements7. Table Hollandite is a titanate structure composed of octahedral B-site cations that form tunnels, which incorporate A-site cations. The A-site is composed of mono and/or divalent cations, specifically Cs23. In total, three different energetic terms are highlighted for the evaluation of ordering and stability in the hollandite system − 1. Change in total energy for systems with the same composition, but differing configuration (ΔEconf), 2. Enthalpy of formation for a given configuration based on formation from the simple oxides (ΔHfoxides), and 3. Enthalpy of mixing across a given binary solid solution series, where the end-member compositions are pure Ba-hollandite and pure Cs-hollandite (ΔHmix). For example, the formation enthalpy for the Ba-Zn end-member hollandite composition (Ba4Zn4Ti20O48) is calculated according to Equation The total energy from the DFT calculations does not include any contribution from entropy ; therefore, the total energy can be considered an enthalpy. In fact, the total energy from the CASTEP calculations is a sum of the energies of the zero valent components. The total CASTEP energies are used only for comparison of different hollandite configurations with the same composition. To gleam translatable meaning from the calculated total energy, the enthalpy of formation based on the simple oxides and the enthalpy of mixing across a binary solid solution are computed24. The lowest enthalpy configurations for the end-members are set to zero, and the enthalpy for the other configurations are with respect to the lowest enthalpy configuration. The enthalpy for the intermediate composition is actually the enthalpy of mixing with respect to the lowest enthalpy end-member configurations.The enthalpy of mixing for the solid solutions are determined based on a linear combination of the lowest enthalpy end member configurations, where a positive enthalpy of mixing value indicates a preference for a mechanical mixture of the end membersi.e., mixing on both A and B sites) and an interdependency of the A-site and B-site composition. Following the derivation for the configurational entropy for the plagioclase [(Ca1−xNax)(Al2−xSi2+x)O8] coupled-substitution solid solution25, the configurational entropy for the 1 × 1 × 1 unit cell of hollandite, with the number of mixing components N = 4, is defined in Equation N = 5 and Configurational entropy is considered in the final evaluation of cation ordering for hollandite compositions containing trivalent B-site cations. The mathematical expression for the configurational entropy for the hollandite system is complicated due to the coupled nature of the solid solution, which includes two-site mixing (1−xNax)Al−xSi2+xO82+, Ga3+, and Al3+). Figure i.e., non-Ti atoms) are noted.B-site ordering was evaluated across the Ba-Cs solid solution with varying B-site dopants . The difference in the B-site ordering for these systems stems from the difference in B-site dopant ionic radii, where the Ga3+ (RGa = 0.76 Å) is most similar to Ti4+ (RTi = 0.745 Å), while the Al3+ (RAl = 0.675 Å) and Zn2+ (RZn = 0.88 Å) differ from the Ti4+ by 9% and 18%, respectively26.Generally, the lowest energy configuration is one in which the B-site dopants are arranged with the highest symmetry. For example, the Ba-end member for the Zn-hollandite, which contains four Zn atoms in the 1 × 1 × 3 supercell, has a lowest energy configuration in which the Zn are evenly spaced around the eight B-sites of a single tunnel layer Fig. . The Zn 3+ dopants), the lowest energy Ga-hollandite configuration prefers Ga dopants stacked in adjacent layers, while the Al-hollandite prefers the Al dopants to be shifted in adjacent layers , as compared with the Ga3+ and Ti4+ (|∆R| = 0.02 Å), likely causes the Al3+ in adjacent layers to be shifted.To maintain charge balance, the trivalent B-site dopants are incorporated with a higher concentration than the divalent B-site dopants. The increase in dopant concentration leads to changes in the favorability of the B-site configurations. Optimal configurations still maintain symmetry; however, some deviations are observed related to the size of the dopant cation. For example, for the Ba-end member eight M+ dopantsThe intermediate trivalent cation compositions contain six B-site dopants, and therefore, the symmetry is inherently broken. Six cations cannot be symmetrically spaced across eight sites. In these cases, the B-site dopants align along the tunnel direction, maintaining two-fold rotational symmetry, rather than the standard 4-fold rotation in the 4-dopant systems.2Cs2Ga6Ti18O48 indicates that Ba and Cs prefer to be arranged homogeneously, such that each tunnel contains only one cation type; the homogenously ordered configuration is 0.0356 eV lower in energy than the configuration with A-site cations heterogeneously arranged. This energy difference is relatively low, as discussed below, and may be overcome with slightly elevated temperatures.As expected, the A-site cations are distributed equally between tunnels within a unit cell; that is, for an occupancy of 1.33, two cations and one vacancy are located in each tunnel within the 1 × 1 × 3 and 2 × 1 × 3 supercells. For intermediate compositions, Cs and Ba prefer to arrange homogeneously within the tunnels of the 1 × 1 × 3 supercell, such that one tunnel contains two Cs atoms and the other contains two Ba atoms. For example, the intermediate composition Ba27. The minimum energy configuration for the CsAl-hollandite  the total energy for the system increases by 0.1304 eV , as compared with Ba (2+), leads to longer Cs-O1 distances than Ba-O1 distances, and thus, longer overall O1-O1 distances across tunnels containing Cs. As noted from neutron diffraction studies, and confirmed with DFT calculations, the O1-O1 distance remains short enough to trap Cs in the hollandite tunnel, limiting cation diffusion5.The tunnel diameter, as described here by the diagonal O1-O1 distance, is a key factor that determines the mobility of tunnel cationsion Fig.  because + concentration, fewer B-site dopants are required for charge balance, decreasing the impact of the B-site dopant on the O1-O1 distance. For example, the ionic radius of octahedrally-coordinated Zn2+ (0.880 Å) is 18% larger than Ti4+ (0.745 Å)26, but due to the large difference in oxidation state, only one Zn2+ dopant is needed for charge balance in the 1 × 1 × 3 supercell of the Cs-end member. Thus, the average O1-O1 distance for the Cs-end member of the Zn-hollandite, is similar to the Al- and Ga-hollandite , the impact of the B-site dopant on the O1-O1 distance is limited, yet consistent. While the difference in the average O1-O1 distance between the Ba- and Cs-end members of the Ga-hollandite solid solution is 0.386 Å, the difference between the Ga- and Al-hollandite for any A-site composition is, at most, 0.078 Å. Table Ti/Ti), as well as to one Ti and one B-site dopant (O1-M-O1Ti/B), for the lowest energy configuration for the 50% Cs composition. The differing trends in the M-O1 vs. Ti-O1 distances for the Al- and Ga-hollandite are due to the size of the ionic radius of the B-site dopant, where the smaller Al dopant leads to shorter M-O1 distances, and in turn, a longer average O1-O1Ti/M distance. The structure of the Ga-hollandite is more distorted than the Al-hollandite, as seen by the difference in the O1-O1 distances across the Ba-containing tunnel  increases. For systems with different types of B-site dopants, one might expect the enthalpy of formation to increase (become less favorable) with a greater difference in ionic radii between M and Ti4+. Further, the concentration of M-substitutions on the B-site contributes to the overall lattice strain and ultimately impacts the enthalpy of formation. The percent change between the M and Ti4+ ionic radii is 2%, 9%, and 18% for Ga3+, Al3+, and Zn2+, respectively; however, the enthalpy of formation is highest for Ga-hollandite and lowest for Zn-hollandite. This is likely due to the B-site valance, where the Zn-hollandite system requires fewer B-site substitutions to maintain charge neutrality.The enthalpy of formation decreases with increasing Cs concentration, where the total system charge is balanced by increasing the concentration of B-site dopants. Therefore, with higher Cs concentration, the deviation of the average B-site radius from 0.745 Å  were performed to capture intermediate compositions of 0.25 and 0.75 mole fraction of Cs; thus, confirming the trend of decreasing enthalpy of formation with increasing Cs content. Figure 7, where the lattice parameter increased with increasing average B-site ionic radius. The B-site ordering has the largest impact on structural stability of the system, where the energy difference between the most favorable and least favorable B-site configuration for the Cs-hollandite end members range between 0.26 eV and 0.36 eV. The propensity for B-site ordering also impacts the expected radiation damage tolerance of the material. Structures that are initially ordered, but have the ability to accommodate lattice disorder are known to possess larger radiation stability19. Limited studies are available on the radiation damage behavior of hollandite, however ordered B-site structures are expected to be more resistant to damage30.The B-site dopant has been noted for impacting the tunnel diameter5. The calculated enthalpy of formation supports the conclusion that Cs stabilizes the formation of the hollandite system. Overall, the calculated variance of the enthalpy across the Ba-Cs solid solution decreases with increasing Cs concentration, further indicating the stabilization of the hollandite structure due to Cs in the tunnel cavity. The stabilization of the hollandite structure with increased Cs concentrations has positive implications for Cs-waste loading in hollandite. Thermodynamic comparisons with competitive Cs-host phases is necessary to quantify the expected maximum concentration of Cs in hollandite formed in a multi-phase ceramic.Recently published neutron diffraction data for hollandite with high Cs-loading shows that the Cs concentration has a larger effect on the tunnel diameter and overall system symmetry than the B-site dopant type137Cs undergoes beta decay (τ½ = 30.08 yrs) to become 137Ba; therefore, understanding the arrangement of Cs and Ba on the A-site provides insight into the long term stability of hollandite due to the radioparagenesis of the waste components31. Ba and Cs prefer to segregate into different tunnels by about 0.036 eV. The implication of this energetic favorability can be estimated using a Boltzmann conversion of energy to temperature , where 0.036 eV equates to about 418 K (145 °C). While elevated, this temperature is far below the temperature used during waste form processing (1000–1500 °C)33. Commercially-derived high-level waste could generate enough self-heat from decay of fission products to result in an initial storage temperature as high as 600 °C. Even 100 years after emplacement, the waste temperature may be as high as 300 °C34. Therefore, enough energy may be supplied by the elevated temperature such that, upon decay, Ba may remain stable in the Cs-dominant tunnel of hollandite. Table Over time, 6. The ordering of A-site (tunnel) cations has been both predicted35 and confirmed computationally and experimentally38.The smallest energetic difference for A-site vacancy ordering is 0.091 eV (~780 °C), which is associated with A-site ordering for the Cs-Al hollandite system. This energy difference is large enough to have implications for A-site cation mobility since it falls above the temperature range expected for storage of these waste forms. The occupancy explored in this study (1.33/2) is slightly higher than previous experimental work (1.24/2) in order to compare detailed computational geometry optimizations with experimental structural and mobility data. Thus, further analysis of A-site occupancy is critical to fully understand the cation mobility advantages of Cs-doped hollandite recently indicatedThe entropic contributions to thermodynamic stability were evaluated based on Equations i.e., the tunnel direction). Following the trends in ionic radii, B-site dopants with ionic radii close to octahedral Ti4+ (0.745 Å) may also order along the tunnel direction. Further, the present work shows the coupling of B-site and A-site ordering, which, in turn, impacts the mobility of the A-site cations. Ultimately, quantification of the A-site cation mobility is critical for predicting long term potential for radionuclide release.This study is the first to predict B-site (framework) ordering in Cs-loaded hollandite phases. The models presented here can guide future experimental efforts to confirm Ga ordering along the [001] zone axis (


The specificity of tyrosine kinases is attributed predominantly to localization effects dictated by non-catalytic domains. We developed a method to profile the specificities of tyrosine kinases by combining bacterial surface-display of peptide libraries with next-generation sequencing. Using this, we showed that the tyrosine kinase ZAP-70, which is critical for T cell signaling, discriminates substrates through an electrostatic selection mechanism encoded within its catalytic domain . Here, we expand this high-throughput platform to analyze the intrinsic specificity of any tyrosine kinase domain against thousands of peptides derived from human tyrosine phosphorylation sites. Using this approach, we find a difference in the electrostatic recognition of substrates between the closely related Src-family kinases Lck and c-Src. This divergence likely reflects the specialization of Lck to act in concert with ZAP-70 in T cell signaling. These results point to the importance of direct recognition at the kinase active site in fine-tuning specificity. The ~30 cytoplasmic tyrosine kinases are characterized by the presence of a tyrosine kinase domain and one or more modular binding domains, such as SH2 and SH3 domains . The catWe have shown recently that there is an important role for direct substrate selection by the kinase active sites of two cytoplasmic tyrosine kinases, the Src-family kinase Lck and the Syk-family kinase ZAP-70, in the response of T cells to antigen recognition . T cell To analyze the differential specificities of Lck and ZAP-70, we had adapted a high-throughput platform to simultaneously measure the efficiency of phosphorylation by a tyrosine kinase of hundreds of genetically encoded peptides in bacterial surface-display libraries  Shah et. In thisUsing this high-throughput technique, we had analyzed scanning-mutagenesis libraries of peptides derived from LAT phosphosites and ITAM motifs, and had identified mutations in these peptides that impact their phosphorylation by Lck or ZAP-70 . This anLck is one of eight Src-family kinases in the human genome . This faGiven the close similarity between the Src-family kinases, we were interested in seeing whether the inability of Lck to phosphorylate LAT and SLP-76, while maintaining robust phosphorylation of ITAMs and ZAP-70, is a property that is shared with c-Src, given that c-Src is broadly-expressed and did not evolve under the constraints of T cell signaling. Also, the conclusions of our earlier paper were based on the analysis of a small set of peptides from the T cell receptor and LAT, and did not include a more general analysis of the specificity of these kinases against a broad range of potential targets.We have now expanded our kinase specificity screening platform through construction of a genetically encoded peptide library containing ~2600 diverse sequences derived from known tyrosine phosphorylation sites in the human proteome. Using this library, we validated our earlier conclusions regarding the orthogonal specificities of Lck and ZAP-70. In comparing the specificity of Lck to that of c-Src using this library, we find a subtle, but significant, divergence in the substrate preferences of these two enzymes. While both Src-family kinases are equally efficient at phosphorylating a large group of common substrates, there are peptides that are phosphorylated efficiently by c-Src and not by Lck, and vice versa. This divergence is characterized by a suppression in the ability of Lck, relative to c-Src, to phosphorylate highly acidic phosphosites while tolerating the presence of positively charged residues in the substrates. More generally, our approach provides a tool that is easily deployed to interrogate the proteome-wide specificity of any tyrosine kinase, by leveraging the speed and accuracy of next-generation sequencing.We created a genetically-encoded library based on 2600 sequences, each spanning 15 residues surrounding known sites of tyrosine phosphorylation in the human proteome. Sequences were chosen by compiling a list of all of the tyrosine phosphorylation sites in human proteins annotated in the Uniprot database , along wThe Human-pTyr library comprises relatively diverse sequences . GlutamaIn a typical screen, the surface-displayed Human-pTyr library was phosphorylated for a limited time, sufficient to achieve approximately 20–30% of the maximal possible phosphorylation. After labeling with a fluorescent pan-phosphotyrosine antibody, cells with the highest fluorescence  were isolated by cell sorting and analyzed by Illumina deep sequencing, in comparison to unsorted cells. These conditions ensure sufficient phosphorylation for a robust signal-to-noise ratio, without saturating the system and losing discrimination. Screens were typically carried out in duplicate or triplicate , and theWe tested if the use of the Human-pTyr library in the bacterial surface-display system recapitulates the expected preferences for a well-studied kinase, c-Abl. The distribution of enrichment scores for phosphorylation by the c-Abl kinase domain is bimodal, with ~70% of the peptides being poorly phosphorylated and 30% of the peptides being phosphorylated relatively efficiently . The facWe visualized the position-dependent amino acid preferences for phosphorylation by c-Abl by generating a sequence probability logo based on sequences in the subset of peptides with high enrichment scores  Figure . We refePrevious studies have defined three strong determinants of efficient phosphorylation by the c-Abl kinase domain: a bulky aliphatic residue at the −1 position with respect to the tyrosine, an alanine at the +1 position, and a proline at the +3 position . The c-AWe also analyzed the phosphorylation of the Human-pTyr library by the ZAP-70 kinase domain. As for c-Abl, the distribution of enrichment scores is bimodal, although the separation between the inefficient and efficient substrates is more marked, with only ~20% of the peptides falling in the latter group . As expeWe next analyzed the specificities of the kinase domains of two Src-family kinases, c-Src and Lck. As for c-Abl and ZAP-70, the distribution of enrichment scores is bimodal . The phoBased on visual inspection of the phospho-pLogo diagrams, the specificities of Lck and c-Src appear indistinguishable. A subtle distinction between Lck and c-Src emerges, however, upon comparing the efficiency of phosphorylation of individual peptides by different kinases . CompariTo understand the origin of the specificity difference between Lck and c-Src we generated phospho-pLogo diagrams for two groups of sequences, one containing peptides that are good Lck substrates but poor c-Src substrates (referred to as the Lck-preferred peptides), and the other having the opposite specificity (the c-Src-preferred peptides) . For theOur previous analysis of the specificity determinants of Lck phosphorylating ITAM peptides had indicated that Lck does not have strong preferences for sidechains located before the phosphotyrosine . ConsistOur results indicate that c-Src is more tolerant of negatively charged residues in substrates than Lck, and less tolerant of positively charged residues. This is reminiscent of the comparison between ZAP-70 and Lck, as revealed by our previous analysis. In We carried out in vitro measurements of phosphorylation kinetics with purified kinase domains and five representative synthetic peptides: two c-Src-preferred peptides, two Lck-preferred peptides, and one peptide that is a good substrate for both kinases in the screening data .Lck has presumably evolved to suppress off-target phosphorylation of the highly negatively charged ZAP-70 substrates in T cells, LAT and SLP-76. Given that similar substrates exist in other hematopoietic cell types, where signaling also requires an interplay between Src- and Syk-family kinases , this elOne of these residues, Glu 398 in Lck (Gln 423 in c-Src) lies in the activation loop and is poised to sense charged residues downstream of the substrate tyrosine. In a 500 ns molecular dynamics simulation of Lck bound to a preferred substrate derived from an ITAM motif, Glu 398 repeatedly forms ion pairs with an arginine residue downstream of the ITAM tyrosine . NegativWe tested the impact of three mutations in c-Src, Q423E, R472P, and P488E, on the phosphorylation of the Human-pTyr library. Enrichment scores from these screens correlated strongly with those from the wild-type c-Src screen, with few substrates being selectively phosphorylated by either wild-type c-Src or a mutant . Each muWe measured phosphorylation kinetics for these mutants using the same panel of five purified peptides described above, which have varying degrees of charge . To accoWe also compared the specificities of c-Src and Lck to that of Fyn and Hck, which are Src-A and Src-B kinases, respectively . Fyn is In this report, we focused primarily on the subtle electrostatic differences between the Src-family kinases Lck and c-Src, and the implications of these differences for our understanding of T cell receptor signaling. The high-throughput screens using the Human-pTyr Library also provide additional insights into other aspects of tyrosine kinase specificity. For example, in comparing c-Src and Lck, it is evident that these kinases not only differ in their preference for charged residues, but they also have slightly different preferences at the −1 and +3 positions on substrates  and 5A. The specificity screens and molecular dynamics simulations of Lck and ZAP-70 presented here and in our previous report  provide The high-throughput screens presented here were carried out with a library of diverse, discrete peptide sequences derived from the human proteome. As such, they provide an opportunity analyze kinase specificity in ways that are not accessible to degenerate library approaches. For example, analysis of discrete sequences allows for the identification of independent linear motifs that are buried in the phospho-pLogo diagrams, and to assess the interdependence of specific residue preferences . We analScreening results using the Human-pTyr library can also be directly compared to data that describe interactions between signaling partners in a biological context. We compared the enrichment scores for specific kinase-substrate pairs in the bacterial surface-display screens with a curated set of kinase-substrate pairs from the PhosphoSitePlus database, where many of the interactions were reported to have been observed in an in vivo setting . In totaThe bacterial surface-display screens faithfully recapitulate phosphorylation efficiencies measured with purified peptides and kinases . The inaThere is a strong correlation between the substrate preferences and evolutionary relationships of kinases: closely related kinases typically have similar sequence preferences . DiffereOur discovery of fine-tuning within Src-family kinases stems directly from the use of a high-throughput specificity screen and a peptide library encoding thousands of sequences derived from human tyrosine phosphorylation sites. The high-throughput method to interrogate this library can be applied to the analysis of the specificity of any tyrosine kinase and is easy to deploy. The power of the method derives from the increased speed and accuracy of modern sequencing methods. We envision that our approach will not only guide our understanding of sequence recognition by tyrosine kinase domains, as described in this study, but also aid in the identification of unknown tyrosine kinase-substrate interactions in phosphotyrosine signaling pathways.The sequences in the Human-pTyr library were derived from two sources. First, we compiled a list of all phosphotyrosine sites in human proteins annotated in the Uniprot database . Second,E. coli. The sequences were not further modified to optimize GC-content or melting temperatures. The 5’ and 3’ flanking sequences ‘GCTGGCCAGTCTGGCCAG’ and ‘GGAGGGCAGTCTGGGCAGTCTG’, respectively, were appended onto each peptide-coding DNA sequence. All these sequences were purchased as an oligonucleotide pool generated by massively parallel synthesis .In the final list, ~900 sequences had more than one tyrosine residue, and so a second version of those sequences was also included in which all tyrosines except for the central tyrosine were substituted with alanine. Finally, 12 control sequences were generated with a random composition of amino acids. Three versions of each of these sequences, with a central tyrosine, phenylalanine, and alanine, were included in the peptide list. In total, our designed library contains approximately 3500 15-residue peptide sequences, which were converted into peptide-coding DNA sequences using the most prevalent codon for each amino acid in Taq DNA polymerase using a slow ramping speed (2°C/sec), long denaturing times, and only 15 cycles, as described for other diverse libraries , at a 1:50 dilution, then washed again, and subject to fluorescence-activated cell sorting.High-throughput specificity screens using the Human-pTyr surface-displayed peptide library were carried out essentially as described in our previous study , with thg for 30 min, and the supernatant was aspirated off, leaving behind approximately 500 μL of supernatant. We note that the cell pellets were not visible. The cells were resuspended in the remaining supernatant, transferred to 1.5 mL microcentrifuge tubes, and centrifuged at approximately 20,000 rcf for 10 min. The remaining supernatant was carefully aspirated off. The cells were resuspended in 100 μL of water, lysed by boiling for 10 min, then centrifuged again for 10 min at 20,000 rcf. 20 μL of the supernatant from this lysate was used in a 50 μL 15-cycle PCR reaction with the AccuPrime Taq DNA polymerase and the following forward and reverse primers: TruSeq-eCPX-Fwd (5’-TGACTGGAGTTCAGACGTGtgctcttccgatctNNNNNNaccgcaggtacttccgtagct-3’) and TruSeq-eCPX-Rev (5’- CACTCTTTCCCTACACGACgctcttccgatctNNNNNNttttgttgtagtcaccagactg-3’), where ‘N’ refers to a degenerate base at which a mixture of A, T, G, and C are included. 1–5 μL of the reaction solution from this first PCR reaction was used as the template for a second 100 μL 15-cycle PCR reaction with the AccuPrime Taq DNA polymerase and Illumina D700 and D500 series adapters. At this stage, distinct eight base pair indices were included for multiplexed sequencing on one flow cell. The resulting PCR products were purified by gel extraction. Concentrations of all samples were determined using the PicoGreen reagent , pooled to achieve equal molarity for each sample, and sequenced by paired-end Illumina sequencing. In all cases, samples were loaded on the sequencing flow cell to obtain 500–1000 reads per peptide-coding sequence in the DNA sample derived from unsorted cells.For each screen,~4,000,000 cells from the top 25% of the phycoerythrin fluorescence distribution were collected into 50 mL conical tubes containing 10 mL of LB medium. An aliquot of ~4,000,000 unsorted cells was prepared identically, as a reference sample. The cells were centrifuged at 5000 while read string ; do grep -c "$string" sample.translate.fastq ; done < peptide_list.txt > peptide_countThe raw deep sequencing data were processed as described in our previous report , by firspeptiden) were converted into frequencies (peptidef) by dividing by the total number of reads in that sample that mapped to a sequence in the full library . These frequencies were converted into ‘enrichment scores’ by dividing the frequency of a variant in a sorted sample by the frequency in an unsorted sample prepared on the same day. The enrichment scores from replicate screens with the same kinase were averaged prior to any further analysis.In every sample, the raw read-counts for each peptide  in a sample that contained a residue, i, at a specific position, j. The frequency in the sorted sample was normalized by dividing the frequency in the unsorted sample to give a residue-specific enrichment score .The enrichment ratios in These values were calculated for independent replicates and then averaged. The enrichment ratios given in 6-tag, was expressed in Sf21 insect cells and purified as described previously  overnight at 4°C, then the TEV protease, protease-cleaved His6-tag, and any uncleaved protein were removed by Ni affinity chromatography. The tagless kinase domain was further purified by size exclusion chromatography over a Superdex 200 column.The human Lck kinase domain construct, spanning residues 229–509, with an N-terminal His6-tag followed by a TEV protease cleavage site. These proteins were co-expressed in E. coli BL21(DE3) cells with YopH phosphatase and purified as described previously for c-Abl and c-Src (Constructs for the mouse c-Abl kinase domain (residues 232–502), wild-type and mutant chicken c-Src kinase domains (residues 257–525), human Fyn kinase domain (residues 261–529), and human Hck kinase domain (residues 252–520) all contained an N-terminal Hisnd c-Src . We noteTo validate the specificity trends observed in high-throughput screens, we carried out in vitro measurements of phosphorylation kinetics using purified kinases and synthetic peptides derived from sequences in the Human-pTyr library . These peptides  bound to a peptide derived from the T cell receptor ζ-chain (residues 104–118). For this simulation, a crystal structure of the Lck kinase domain in an active conformation, bound to AMP-PNP, a stable analog of ATP, was used to model the starting coordinates of the enzyme (PDB code 1QPC) . To mode2+ atoms. Next, the system was subject to another one ns equilibration step at constant number, volume, and temperature, with no positional constraints on any atoms. Finally, production runs were carried out under NPT conditions. Periodic boundary conditions were imposed, and particle-mesh Ewald summations were used for long-range electrostatic calculations .Thank you for submitting your article "Fine-tuning of substrate preferences of the Src-family kinase Lck revealed through a high-throughput specificity screen" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:eLife examining the substrate specificity of non-receptor tyrosine kinases involved in T cell receptor signaling. In the previous paper, the authors developed a bacterial surface display method that leverages next-generation sequencing technology to identify peptides phosphorylated by tyrosine kinases from a pool containing hundreds of sequence variants. Using this method the authors revealed substantial differences between the kinases ZAP-70 and Lck that allowed them to rationalize their sequential activation and specific targeting of ZAP-70 substrates. In the present manuscript, the authors extend their originally reported method by generating libraries consisting of thousands of peptides corresponding to known sites of phosphorylation within the human proteome. After validating the new library using well characterized kinases (Abl and ZAP-70), they go on to analyze Lck and the related kinase Src. As anticipated from previous analyses of the two kinases, their specificity was broadly similar when the preferred sequences are considered in aggregate. What is really interesting about their findings is that there are a substantial number of individual peptide sequences that are reproducibly phosphorylated preferentially by either Src or Lck, a phenomenon that would not have been reasonably predicted based on prior literature. They further note that Src specific substrates tended to have a more negative net charge in comparison to Lck specific substrates. Strikingly, mutation of specific residues near the peptide binding site of Src to decrease charge shifts its specificity to be more like Lck, providing a reasonable model to explain at least some of their relative substrate preferences.This manuscript follows on work the authors previously published in This study is a nice extension of their previous paper, and seems appropriate for a "research advance". The incorporation of large numbers of proteome-derived sequences in particular expands the capabilities of their method. One benefit that is clear from the current study is that by analyzing a large substrate pool one is able to better tease out residues that are negatively selected by the kinase.Minor points:1) While the focus on the differences in the electrostatic selectivity of Src and Lck is reasonable and makes sense as an extension of the work on ZAP-70, the logos showing peptide motifs that are differentially phosphorylated by Src and Lck show several statistically significant features that aren't really discussed in the manuscript. These are at key positions at which tyrosine kinases tend to be most selective (-1 and +3). Can these differences be rationalized based on distinct residues in the catalytic clefts of the two kinases?2) It would be interesting to do some analysis (other than just showing the sequence logos) of peptides that are either commonly or differently phosphorylated by the two kinases. For example, are established phosphorylation sites of the kinases enriched within their selected peptide pools? Another question is whether there might be multiple distinct sequence motifs in the data that are "buried" when examined in aggregate. Another method that similarly analyzed phosphorylation of a large number of individual peptides  was able to identify multiple sequence motifs using a web-accessible search tool (Motif-X).3) For ease of comparison, Figure 4B should have an additional graph showing data for WT Src.4) We recommend including lists of the peptide sequences used in the library (and the proteins from which they are derived) along with the enrichment ratios for each kinase examined.5) The assay with the kinases  are carried out from the extracellular side where the target peptides are exposed. These kinases are soluble constructs, that presumably do not comprise the membrane anchoring region. What are the possible consequences of this, and how should one think about the effect of membrane anchoring?6) Src-family kinases are believed to become activated through a trans-autophosphorylation of the activation loop (activation loop). Is the sequence of the activation loop consistent with the present findings? Is there some inherent specificity in the trans-autophosphorylation process?7) Because of the variations in hydrophobic residues, the surface-display levels of each peptide may vary. However, no correction was made for this variability. Could one conceive of a chemical control to assess these differences? For example, could one utilize a chemical or enzymatic tool that modifies exposed Tyr residues without sequence selectivity, and then interrogate the results via mass spectroscopy? Minor points:1) While the focus on the differences in the electrostatic selectivity of Src and Lck is reasonable and makes sense as an extension of the work on ZAP-70, the logos showing peptide motifs that are differentially phosphorylated by Src and Lck show several statistically significant features that aren't really discussed in the manuscript. These are at key positions at which tyrosine kinases tend to be most selective (-1 and +3). Can these differences be rationalized based on distinct residues in the catalytic clefts of the two kinases?The reviewers are correct in noting that there are differences in specificity between each of the kinases analyzed beyond general electrostatic preferences, most notably at the critical -1 and +3 positions in substrates relative to the tyrosine phosphorylation site. In our previous paper, we postulated that a key residue on the F-G loop of tyrosine kinases, Lys 538 in ZAP-70 and Ile 439 in Lck, recognizes the -1 residue on substrates and that this can largely explain the difference between those kinases with respect to -1 residue preferences. This same residue is valine in c-Src, which may explain the subtle difference in hydrophobic residue preferences at the -1 position relative to c-Src. c-Abl has a serine at this position on the F-G loop, and c-Abl is generally more promiscuous with respect to -1 residue preferences.Based on our molecular dynamics simulations and based structural data in the literature, recognition of the +3 position is mediated primarily by two residues in the catalytic cleft of tyrosine kinases, one immediately downstream of the activation loop and another on the G-helix. The latter has been noted by Till et al. as important for c-Abl recognition of a +3 proline residue (PMID: 9988744). Lck and c-Src also differ at these positions.We have included a discussion and depiction of these observations in a new section at the end of the ‘Results and Discussion’ section, and in the newly added in Figure 5. These additional materials include a structural rendering of Lck bound to a peptide, highlighting the three critical positions on the kinase domain, a summary of the residue identities at those positions in all four kinases analyzed in this manuscript, and a simplified rendering of the -1 and +3 preferences for each kinase, derived from our high-throughput screening data. We have also included experimental data in Figure 5—figure supplement 1 showing that mutation of the aforementioned F-G loop residue in c-Src alters its -1 preference.2) It would be interesting to do some analysis (other than just showing the sequence logos) of peptides that are either commonly or differently phosphorylated by the two kinases. For example, are established phosphorylation sites of the kinases enriched within their selected peptide pools? Another question is whether there might be multiple distinct sequence motifs in the data that are "buried" when examined in aggregate. Another method that similarly analyzed phosphorylation of a large number of individual peptides  was able to identify multiple sequence motifs using a web-accessible search tool (Motif-X).We agree with the reviewers that a deeper analysis of the large datasets produced by our screens of the Human-pTyr Library could yield additional insights into kinase specificity. We have included the results of two analyses in line with the reviewers’ suggestions in a new section at the end of the ‘Results and Discussion’ entitled ‘Additional insights from specificity screens with the Human-pTyr library’.First, we analyzed the pool of efficiently phosphorylated peptides for each kinase using Motif-X (PMID: 16273072) to identify distinct sequence motifs that might be buried in the full sequence logos. For c-Src and Lck, this analysis recapitulated the conserved -1 Ile, Val, Leu, and Thr preferences for each kinase, but also revealed a statistically significant +3 Phe motif for c-Src that is absent in Lck. For c-Abl and ZAP-70, this analysis showed that multiple positions  independently contribute to substrate recognition. For example, either a -1 Ile or +3 Pro are sufficient to yield an efficiently phosphorylated c-Abl substrate. These results are summarized in the text and in Figure 5—figure supplement 2.Second, we compared a curated list of reported human kinase-substrate pairs in the PhosphoSitePlus database with our screening results. For c-Abl, ZAP-70, c-Src, and Lck, approximately 40-60% of the reported substrates in the database are efficiently phosphorylated in the surface-display screen, as depicted in Figure 5C and enumerated in Figure 5—source data 1. Although all of the kinase-substrate pairs in this database may not be unambiguously confirmed, this modest correlation between the database and our screens raises two important points about tyrosine kinase substrate selection. (1) While the local sequences surrounding tyrosine phosphosites likely play a significant role in substrate selection by tyrosine kinases, other factors such as localization and recruitment are also important and may partially override sequence preferences. (2) Tyrosine kinase-substrate interactions may not necessarily be optimized for the most efficient phosphorylation. There may be situations where sub-optimal phosphorylation kinetics are required in a signaling pathway, and so natural substrates deviate from idealized sequence motifs.3) For ease of comparison, Figure 4B should have an additional graph showing data for WT Src.The data in Figure 4B represent the residue abundances in the pool of peptides that are efficiently phosphorylated by each c-Src mutant but not by wild-type c-Src. For each mutant, we have added an additional graph below the original graph that shows the residue abundances in the pool of peptides phosphorylated by wild-type c-Src but not by the mutant. In addition, we have changed the figure labels on these histograms to more clearly indicate which peptides are being represented in each graph.4) We recommend including lists of the peptide sequences used in the library (and the proteins from which they are derived) along with the enrichment ratios for each kinase examined.We have appended a table to the revised manuscript that contains all of the peptide sequences, the proteins from which they were derived, the tyrosine phosphosite residue number in that protein, and the enrichment scores for c-Src (wild-type and mutants), Lck, c-Abl, and ZAP-70. These data can be found in Figure 2—source data 1.5) The assay with the kinases  are carried out from the extracellular side where the target peptides are exposed. These kinases are soluble constructs, that presumably do not comprise the membrane anchoring region. What are the possible consequences of this, and how should one think about the effect of membrane anchoring?The reviewers are correct in noting that the kinase constructs used in this study do not contain a membrane anchoring region. The major impact of membrane anchoring on kinase specificity would be to localize the kinase in proximity to its substrates, and possibly away from proteins it should not phosphorylate. Undoubtedly, sub-cellular localization of enzymes and substrates plays an important role in kinase signaling. The dominant effect of localization on substrate recognition is likely one major reason why only half of the reported substrates of these kinases are high-efficiency substrates in the bacterial surface-display screens. Another interesting consideration is that anchoring the kinase at the membrane can impose geometric constraints on substrate recognition. For example, given that many phosphotyrosine signaling proteins form dense clusters at the membrane, the relative orientations of kinases and their substrates may be constrained in a way that dictates specificity. Given that the role of localization in kinase signaling is described in the introduction, we felt that this issue did not require further modification of the manuscript.6) Src-family kinases are believed to become activated through a trans-autophosphorylation of the activation loop (activation loop). Is the sequence of the activation loop consistent with the present findings? Is there some inherent specificity in the trans-autophosphorylation process?trans-autophosphorylation of their activation loops. Notably, in our screens, Lck can robustly phosphorylate Tyr 493 in ZAP-70 activation loop, consistent with its activity in T cell signaling. It is also noteworthy that, in our screens, the Src-family kinases are poor enzymes for phosphorylation of their negative regulatory C-terminal tail sequences, consistent with the requirement for Csk to phosphorylate those tails. The structural basis for activation loop autophosphorylation in Src-family kinases was a major focus of our previous paper, and so we do not discuss this explicitly in this manuscript.Not all of the Src-family and Abl-family activation loop sequences are well-represented in the Human-pTyr Library, most likely due to poor PCR amplification of the coding sequence during library construction . The ZAP-70 activation loop sequence and that derived from the Src-family kinase Blk are abundant in the library. Analysis of these peptides, and comparison of activation loop sequences to the motifs derived from our screens, suggests that activation loop sequences of tyrosine kinases are not optimized for auto-phosphorylation. This is consistent with the observation in our previous paper that tyrosine kinases must make specific contacts between the C-lobes of their kinase domains for efficient 7) Because of the variations in hydrophobic residues, the surface-display levels of each peptide may vary. However, no correction was made for this variability. Could one conceive of a chemical control to assess these differences? For example, could one utilize a chemical or enzymatic tool that modifies exposed Tyr residues without sequence selectivity, and then interrogate the results via mass spectroscopy?As noted by the reviewers, we did not correct for variation in the surface-display levels of peptides in the Human-pTyr Library. There may be efficient chemical labeling and mass spectrometric methods to examine surface-display levels. We previously reported a method, analogous to our measurements of phosphorylation efficiency, that utilizes cell sorting and deep sequencing to accurately determine relative surface-display levels. Our surface-display scaffold bears an epitope tag lacking tyrosine residues that is distinct from the displayed substrate peptide. This tag can be detected with a fluorescently-labeled antibody and used to separate cells by fluorescence-activated cell sorting on the basis of surface-display level. By collecting cells from multiple bins spanning the surface-display level distribution, and deep sequencing cells within each bin, one can quantitatively determine the relative surface-display levels of all peptides in the library.In our previous study, we described this procedure extensively in an appendix and showed that a correction based on these measurements only marginally impacts the enrichment scores that report on phosphorylation efficiencies. Furthermore, we find that surface-display levels are highly reproducible between screens. As described in the ‘Results and Discussion’, we omitted this correction for the study presented here because most of our analyses involved comparing pairs of kinases against the same library, where any artifacts due to surface-display variation would be the same for each kinase. We have added a sentence to the ‘Results and Discussion’ briefly explaining the methodology that we previously developed to compare surface-display levels, and we refer the readers to our earlier report for a thorough description of this procedure.