Linear regressions with all three causal concepts indicate realistic value in practical use to estimate the important performance improvement rate of a technological domain.The results in this paper establish that information contained in patents in a technological domain is strongly correlated with the rate of technological progress in that domain. The importance of patents in a domain, the recency of patents in a domain and the immediacy of patents in a domain are all strongly correlated with increases in the rate of performance improvement in the domain of interest. A patent metric that combines both importance and immediacy is not only highly correlated (r = 0.76, p = 2.6*10 Estimates for k are determined by first constructing a functional performance metric (FPM) that is a measure of the generic function for a technological domain and includes the factors that affect the purchasing decision for artifacts embodying the technology (for example: Watts/$ for Solar PV). Next, data points that measure the FPM are collected over a range of time: a technological improvement rate is determined by an exponential regression vs. time and is statistically analyzed to examine robustness and reliability. While there has been considerable research into finding these improvement rates for different technologies and understanding the best way to measure them ,5, thereOne of the sources of data that has been widely used for understanding technological change in recent years is patent data –15. PateWhile many aspects of patents make it an attractive data source for innovation analyses, patents are limited in that they may not cover all inventions or discoveries due to specific patentability criteria that makes it impossible to patent some things (such as Maxwell’s equations) and not all inventions are patented for both economic (secrecy) and competitive reasons . Additionally, the temporal nature of patents can lead to truncation issues with patent data as has been explored by –18. An iAlthough there is no existing theory that directly attempts to explain the differences between technological improvement rates in technological domains, there are a large number of useful theoretical writings on technological change. This section reviews the technical change literature in order to build upon prior work in Benson and Magee  to estabThe differences in technological improvement rates among technological domains can be accounted for by the differences among patent characteristics of the domains.HYPOTHESIS 0: The remainder of this section develops hypotheses based upon various concepts from the literature on technological change. The concepts are operationalized by relationships to specific patent characteristics and the concepts and patent characteristics are summarized in There are several aspects of technological evolution where the demand or usage could play an important role in the relative rate of improvement in a technological domain. Wright's  well-knoA direct relationship between R&D effort and technical improvement has been discussed by many researchers of technical change. Christensen  related The performance improvement rate in technological domains should be higher in domains with increased number of patents within that technological domainHYPOTHESIS 1: 'intrinsically problematic because they define an innovation in terms of its effects rather than its attributes'. For our study, the impact of this concept is that we assume that technological change is faster for domains with more important inventions. Thus, we attempt to characterize the importance of innovations in different domains.One of the main explanations of technological change in the literature is based upon categorizing the improvements or inventions within a technology into distinct categories. Many researchers –31 argueThe use of forward citations for estimating the importance of a single patent was first suggested on the basis of study of the economic impact of specific patents in a domain (Computed Tomography) relative to other patents in that domain ,33. It hHypothesis 2 seeks to assess the influence of the average importance of patents in a particular domain, with the intuition being that a domain with patents of higher average importance should improve more rapidly than those with lower average importance.Technological domains with a higher average number of citations to patents in the domain should have higher rates of improvement of performance.HYPOTHESIS 2: Hypothesis three involves the impact of particularly important inventions on technological improvement. It is reasonable that technological domains with a larger concentration of very important inventions would improve in performance faster than those with less concentration of such inventions.Technological domains with a higher frequency of patents that are cited a large number of time should have higher rates of improvement in performance.HYPOTHESIS 3: Technology change researchers recognize an essential role for science in technological development; however the complexity of the specific mechanism has continued to unfold. Schumpeter’s early contribution  and Bushdomains whose patents cite more scientific articles will improve more rapidly than those who cite less such articles; the resulting hypothesis is:To test this idea through patent information, one must connect science directly to patents: some have used a patent characteristic which is the number of backward references to scientific papers  and otheTechnological domains with a higher frequency of citations to the scientific literature should have higher rates of improvement in performance.HYPOTHESIS 4: The basic intuition underlying concept D is the idea that more rapidly improving domains are newer. Schoenmakers and Duysters  showed tTechnological domains whose patents are newer should have higher rates of improvement in performance.HYPOTHESIS 5: The relationship between more immediate science and more rapidly improving scientific fields provides a promising analogy for the importance of immediacy of patents in technological improvement. The connection between immediacy of science and higher scientific improvement rates was suggested by Price , who shoDomains whose patents are cited relatively more often earlier (as opposed to later) in their existence should have higher rates of improvementHYPOTHESIS 6: to be cited soon after issuance as captured in hypothesis 6: the second is for patents in a domain to cite more immediate patents. Since domains in a patent typically cite patents not in the domain ~90% of the time, these relationships (backward and forward citation immediacy) need not have the same effect. Thus, a further immediacy hypothesis is:There are two ways immediacy can be important. One is the tendency for patents in a domain Domains that cite more immediate patents should have higher rates of technological progressHYPOTHESIS 7: The breadth of knowledge concept reflects combining knowledge from different domains, assuming that the use of information from a larger variety of different sources is likely to result in improved technological outcomes. Rosenberg  showed tTrajtenberg et al  studied Technological domains that cite higher fractions of patents from other domains will have higher rates of improvement.HYPOTHESIS 8: The concepts of recency and immediacy can work together to increase the technological improvement rate. The intuition is that the combination of two independently important drivers will lead to an even stronger effect on the rate of technological improvement through a single combined metric. A metric for recent immediacy that is tested in this paper is the average publication date of all backward citations by patents in a domain. This is directly equivalent to adding the positive linear effects of H5 (patent publication date) and H7 (backward citation age at time of patent publication)Technological domains whose patents on average cite patents that are newer will have higher rates of improvement.HYPOTHESIS 9: early years of a patent’s existence are more dynamic. Although the concept has not previously been developed in the literature (to our knowledge), it is consistent  with the disruption concepts of Christensen [This hybrid concept combines immediacy and importance and thus argues that domains whose patents are more important in the istensen  and the istensen  and otheDomains whose patents are highly cited in the early years of their existence should progress more rapidly.HYPOTHESIS 10: We attempt to explain the variation in k-values (the dependent variable) among domains by the variation in the various patent metrics (independent variables). The objective is to determine which of the patent metrics correlate significantly with the k’s.www.patsnap.com using the search term UCL:(409) AND ICL:(B23C), which is how all of the sets of patents were collected. Due to the fact that many patents are listed in multiple IPC and/or UPCs it is possible for a patent to represent multiple domains, for example, 1.4% of the ‘Integrated Circuit Processors’ patents are also represented in ‘Solar PV’ patent set. In the latter paper (68), Benson and Magee locate sets of patents that represent each of the 28 technological domains of interest.There are three main components of the methodology. The first is selecting domains and finding their corresponding k values. For this study, we used the results for 28 domains that are covered in detail by Magee et al , these 2In the third component of the methodology, the patent sets are analyzed to find the set of patent metrics for each technological domain and are then compared quantitatively with the k-value for each domain. The specifics of calculating the patent metrics for hypothesis testing are now discussed briefly below. The patent set characteristics and the k values for the 28 domains studied are given in Table A in .Hypothesis 0 is the most general and is tested by the ability of the patent data to explain the differences in technological improvement rates. This hypothesis can be supported by a patent metric that correlates highly with k and has statistical significance. The hypothesis is strongly reinforced by a set of patent metrics that correlate with k that all have statistical significance.Simple Patent Count is the total number of patents within a technological domain. In this research, this includes patents that were published between January 1st, 1976 and July 1st, 2013. This measure is calculated using COUNT’ returns the total number of elements in a set.The Two patent metrics are used to test Concept B and both are directly related to the future (or forward) citations to the patents within a domain. These attempt to measure the impact that a field has on future inventions.Average Number of Forward Citations per Patent is the average number of Forward citations for the patents in a technological domain. This measure is calculated using FCi is the number of Forward citations for patent i.The Total Number of Patents with more than 20 Forward Citations. The specific cutoff of 20 citations is based on work done by Schoenmakers and Duysters [FCi is the number of Forward citations for patent i, and the function IF(arg) only counts the values if the argument is satisfied. In this situation, IF(FCi>20) will only be counted if patent i has more than 20 forward citations.A test of Hypothesis 3 (high frequency of highly cited patents) is the Duysters . This meNon-Patent Literature Citation Ratio is the ratio of citations in a patent to non-patent literature (NPL)—usually scientific journals—to the total citations in the patent and for our purposes is averaged over all patents in the domain. This measure is calculated using NPLi is the number of non-patent literature citations for each patent i, and BCi is the number of backward patent citations for each patent i. Not all patents have citations to NPL; in our data sets, 43% of the patents cited at least 1 NPL reference, ranging from 16% of patents in the ‘electrical information transmission’ patent set to 93% of patents that represent ‘genome sequencing’ citing NPL.The Average Publication Year for the patents in a domain, which provides a simple and effective method of gauging the recency of a technological domain. In this research, this includes patents that were published between January 1st, 1976 and July 1st, 2013. This measure is calculated using i.Hypothesis 5 is evaluated using the Price Index (3 years) . This metric is an immediacy metric for usage of information generated in a domain and thus involves forward citations. The measure is calculated using FCi is the number of Forward citations for patent i, i, j of patent i, and the function IF(arg) only counts the values if the argument is satisfied.Hypothesis 6 is tested by the Average Age of Backward Citations. This measure is calculated using BCi is the number of backward citations for patent i, j of patent i and i. Note that this equation is the average publication date minus the average publication date of backward citations.The immediacy concept is also tested by the Ratio of Backward Citations to other Domains. This measure is calculated using BCi is the set of backward citations for patent ii, P is the total set of patents within the domain and ∪ is the union of two sets across all values of i, ∩ is the intersection between two sets and COUNT counts the number of elements in a set.The patent metric that is used to evaluate Hypothesis 8 is the Average Date of Publication of Backward Citations. This measure is calculated using BCi is the number of backward citations for patent i, j of patent i and i. Note that Combining the recency and immediacy concepts, it is possible to test a combination of the two using the Average number of Forward Citations within 3 years of publication is the numerator of the price index  only counts the values if the argument is satisfied.The ce index  and a gowww.patsnap.com in bulk for each patent set to allow for manipulation into the final forms shown in Equations The raw patent variables  for each of these metrics can be downloaded from no relationship, demonstrated in weak relationship with a moderate correlation coefficient and p-value with an example in strong relationship with a high correlation coefficient and low p-value as in The relationship between a particular patent metric and the k values for all domains was examined graphically as well as statistically. no statistically significant relationship with technological improvement in a domain.weak relationship between the values for this patent metric and the k values for the 28 technological domains.6, indicating that the correlation is quite unlikely to be due to random scattering of the data. The combination of the statistical tests and the visible trend in strong relationship between the average citations in the first three years to the patents in a technological domain and the associated k value.Contrastingly, All of patent metrics discussed in sections 2 and 3 were tested using this approach and the summary statistics and correlation coefficients are given in Concept A, that effort is an important determinant of relative progress rates among domains surprisingly failed to achieve statistical empirical support. The hypothesis derived from this concept is tested in column 1 above and achieves a p value of. 095: this is above the normal cutoff for statistical significance. On the other hand, Concept B that technological improvement rates are higher in domains with more important/cited patents in a domain is supported. The hypotheses derived from this concept (H2 and H3) are both supported—see columns 2 and 3. The total forward citations (column 2) correlation is 0.48 and has a p value of. 009 which is relatively strong whereas the fraction of patents with more than 20 citations has a more modest correlation of 0.38 with p value of 0.043.Concept C, which states that domains with closer connections to science improve more rapidly is surprisingly not supported statistically by the results. The test of hypothesis 4 is shown in column 4 of Concept D—Recency- and hypothesis five that is derived from it (domains with newer patent sets should improve more rapidly) does achieve firm empirical support. The test of this hypothesis is shown in column 5 above and demonstrates strong correlation of 0.54 with a p value of 0.003. Likewise, concept E—Technology improvement is enhanced by increased immediacy of use and knowledge base- is supported strongly. The hypotheses derived from it (H6 and H7) are tested in columns 6 and 7 in −5) with excellent explanatory power. Column 10 tests the hybrid of immediacy and importance and also shows a very strong correlation  with perhaps even more explanatory power. The immediate importance metric has the strongest correlation of any of our patent metrics with the technological improvement rate.Concept F breadth of knowledge led to H8: domains that cite other domains more frequently will improve more rapidly. This hypothesis is tested in column 8 and does not show any sign of correlation with Cp = 0.11 and p = 0.57. The result of testing the combined recency and immediacy hypothesis is shown in column 9 to achieve a very strong correlation . Not surprisingly, the combined/hybrid metrics have significant cross-correlations with other significant variables. The recent immediacy metric (column 9) shows cross-correlation greater than 0.6 with recency (column 5) as well as both immediacy metrics (6&7) as well as with the immediate importance metric (column 10). The immediate importance (10) metric has correlations greater than 0.6 with both importance metrics (columns 2&3) as well as the backward citation immediacy (column 6), and the recent immediacy metric (column 9), but not the forward citation immediacy metric (column 7). We will return to the issue of overall correlation with multiple regression models shortly but it is useful to first present results concerning robustness of the correlations.An important issue is whether our 28 domains contain significant selection bias. It is possible that domains we have not yet studied could change our results. Although this concern cannot be fully answered, one way to examine this issue is to look at correlations with smaller subsets of the 28 domains. We proceeded  with a relatively stringent test by randomly separating the set of 28 domains into 2 independent sets of 14 domains (with no domains repeated twice) and the correlation coefficients were re-calculated using only 14 domains each time. This trial was then completed 10 times for a total of 20 different sets of 14 domains and corresponding correlation coefficients. To examine each variable, the mean and standard deviation of the values were calculated, with the signal (r) to noise (sigma) values taken as a measure of robustness. Not surprisingly, the correlations with the lowest p values were the most robust to this domain selection test. Given the severity of the test in removing ½ of the domains, there is quite good consistency of the correlations of the metrics on the rate of improvement for each of the metrics with p values < 0.01. In particular, the immediate importance metric of average forward citations within 3 years of publication is remarkably consistent across 20 different correlation tests, indicating that the strength of that signal is not likely to be due to the selection of these specific 28 domains. In the linear regression analysis below, we only use the 5 metrics that are shown to be strongest by this test and by their p values for the entire 28-domain correlation.The five metrics identified above as showing statistically significant and robust correlation with the k values were included in linear regression models for predicting the technological improvement rate. Numerous regression models were tested using a combination of these variables and the most informative are shown in 2 of 0.53 which indicates that this single variable can “explain” more than ½ of the variation in k across the domains. It is the most powerful of the variables tested and we use it as the basis for Models B through F in 2 (0.57) is seen relative to model A, the p values for the coefficient of variable 9 and the intercept indicate that the improvement could well be due to over-fitting. Model C adds the strongest immediacy metric (#6) to the immediate important metric (#10) and similarly improves R2 but with p values that make over-fitting a significant concern. Note that the only p values that are strong in both models B and C are for the coefficient for the immediate important metric indicating again the strength of this variable.Model A in 2 (0.64) and does so with p values that make over-fitting unlikely. The combination of the strongest importance metric (#2) with the immediate importance metric is model E and this (like models B and C) gives very modest improvement in R2 with p values that raise significant concern about over-fitting. Models F and G leave out the strongest metric (immediate importance) and start with the second strongest  as the basis. Model F combines the recent immediacy metric and the strongest immediacy metric : the p value for the coefficient on metric #6 indicates over-fitting for this variable is very likely. Model G, on the other hand, incorporates the strongest importance variable  with the recent immediacy metric (#9) and achieves the (tied for) second best R2 along with p values that make over-fitting unlikely. Model H uses neither of the two strongest (hybrid) metrics but instead each of the strongest singular metrics for the three concepts and also achieves the (tied for) second best R2 (0.59). Perhaps most interesting is that the p values for all three coefficients in Model H indicate significance.Model D combines immediate importance with recency (patent publication date- metric # 5). Despite this variable having the fourth highest correlation with the k-values, it is the first to add significantly to Rall three concepts have a role in explaining variation in k among a variety of technological domains.Overall, the results in An important issue is the ability of the correlations to work in the future not just in the past. A second robustness test examines the predictive capability of the correlations by testing how sensitive the patent metrics correlations were to variations in time. In order to do this, the patent metrics were analyzed for only patents from a variety of time frames that were less than the total time frame. The time frames were analyzed to see how far back from 2013 they could be analyzed and still find similar correlations as the patent metrics show during the entire time frame (1976–2013) and are shown in the supporting information. Ultimately the two strongest and most robust patent metrics are robust to time up to 12 years prior to the experiment reported in detail here, indicating a promising amount of predictive capability.cause the faster rate of improvement. However, it is reasonable to postulate (as we did in the hypotheses development) that the concepts being tested by the metric  are causing both the increase in the metric and an increase in the rate of progress.The major finding of the present study is robust, strong correlations between technological improvement rate and patent metrics for a wide variety of technological domains. An unacceptable interpretation is that the metrics that are strongly correlated with technological improvement rate average forward citation rate to patents in a domain is strongly correlated with the differing rates of progress in these domains. This represents significant additional support for the usage of patent citations to assess patent importance. Moreover, interpreting that variations in both forward citation frequency and technological progress in a domain are due to the importance of the patents in the domain receives support from these results.As discussed in the literature review supporting hypothesis development, the use of forward citations for estimating importance of a single patent has been well established. The results reported here show that the Average publication date correlating strongly with technological improvement rate in the variety of domains is also not surprising. Although technology overall being hyper-exponential and thus many rates might increase over time  can be pindependently drive faster technological improvement. More rapid knowledge incorporation as signaled by the immediacy metrics does appear to lead to higher technological improvement rates across domains. The fact that all three concepts  have independent effects on the technological improvement rates is supported by the multiple regression results in The concept of immediacy, first developed by Price  as a key2 values for the regressions and the multiple strong correlations with patent variables: these findings clearly demonstrate that patents do contain information that is essential to increases in technological improvement rate.One of the most important implications of our findings is that patents do contain much information relevant to distinguishing among technological improvement rates in the 28 domains investigated here. Hypothesis 0 is strongly confirmed by the high R2 indicates that more than 1/3 of the variation in k is not explained by combinations of the best variables we have examined) indicates that perhaps only a small part of the issue is lack of information in patents. A Monte Carlo analysis was performed (see 2 even with a perfect theory would be reduced to 0.8 to 0.84 due to the imperfect ability to measure k. This indicates that estimating k introduces sufficient noise to account for about ½ of the imperfection found with our model fit to the data. The imperfections in our patent sets representing the domains (62) can diminish the correlations and the possibilities of inconsistent patent writing practices among domains, of better but unknown metrics, for non-linear relationships contributing to imperfect linear correlations and for real effects from textual facts contained in the patents all appear also likely to diminish correlation. Therefore, improvement contributions not captured in patents is definitely less than the contribution of k estimation noise and may not be a significant factor in understanding the imperfections in the regressions.This result is much more aligned with the position that patents are the major data source for technological progress than the contrarian position that patents have very little to do with technological progress. Moreover, analysis of why the explanatory power is not even higher  that the metric(s) we have tested do not appropriately represent the concept.The results did not support three of the concepts for which we developed hypotheses about their potential influence on the relative rate of performance improvement: effort within a domain, the breadth of knowledge used by a domain and the directness of the science link to a domain are the three unsupported concepts that will each be discussed now. The reasons for the failure to find correlation in each of these cases can be of two kinds: 1) that the concept in fact does not drive within a domain does not necessarily lead to relatively greater progress in that domain since so much work has shown the importance of “spillovers” from other domains and from science that are not dependent upon effort within the domain. Indeed, knowledge flows from citations indicate that all domains are more dependent upon developments in other domains (spillover) and scientific findings not arising from the effort within a domain than they are to effort within the domain [It is a truism that human effort is needed to get any technological progress. However, relatively higher effort e domain . Thus, tnone of them showed significant correlation. It appears that broad utilization of knowledge is a primary and important feature of technological development but that knowledge breadth differences do not drive differences in performance improvement dynamics among domains {and perhaps not among important and unimportant patents. Spillover seems to be generally important in individual patents and even then it appears that an intermediate amount of breadth of knowledge may be optimal [Although breadth of utilized knowledge is a reasonable concept to hypothesize as driving differences in performance improvement among domains, the failure of our test (no sign of correlation) is not as surprising as for the other two failed concepts. This is because a number of tests of breadth of knowledge  using various metrics (including number of patent classes per patent) have shown weak and sometimes contrary results ,63,70,71 optimal .negative correlation of scientific references with progress rate and this could negate any positive effects and thus this framework for understanding the interaction of science and technology is also potentially consistent with our findings of no effects.To question whether science has any impact on technological progress is not a reasonable line of inquiry but the process by which science impacts technology is not yet fully established. Thus, it is not clear that the impact of science should have different impact on performance improvement among domains nor that the impact of science is measured well by citations in patents to scientific articles. Price argued quite early  that sciSome authors suggest that more heavily cited patents themselves cite more scientific articles . More deOverall, it appears that the concept-that breadth of knowledge affects differential improvement rates among domains- is not viable with any metric. On the other hand, we feel that the evidence suggests that the concept- differential science links explain some of the performance rate differential- remains quite viable as a potential explanation despite the failure of our framework to find the effect. The most we can conclude about the third concept- differential effort among domains explain some of the performance rate differential- is that our failure to find such an effect could be due to non-viability of the concept or to metric/framework shortfalls.One clear implication of the work reported here is that the patent data contains information that can be used to understand the relative rate of improvement among technological domains. The results also strongly support the current practice of using forward citation counts to represent the importance of patents while giving the first indication that importance assessed this way can be extended to entire domains by simple averages across the domains. The work reported here also suggests that little used metrics such as the average patent publication date and the average age of backward citations are quite useful in studying differences among domains. We also introduced two new fairly simple-to- calculate metrics, the average number of forward citations to a group of patents in the first three years after patent publication and the average publication date of the backward citations from a group of patents, that were shown to be particularly powerful in distinguishing among groups of patents. We believe these metrics should be useful to others interested in understanding differences between groups of patents beyond our focus here on understanding the relative rate of progress among a well-defined set of technological domains.The individual significance of importance, recency and immediacy on the relative rate of progress in technological domains is conceptually significant. Although we did not create any of these concepts, we believe we have distinguished more carefully among them: the empirical work establishes the distinction among these three concepts as meaningful. We suggest that each of these concepts can have causal implications in other technical change phenomena and might fruitfully be more widely studied in other contexts.The strong explanatory power of models that combine all three concepts also has conceptual implications. A possible connection to prior concepts is with the conceptual frameworks that attribute much of technological change to discontinuities; however, we believe it is important to make the connection with some care. Although not always clearly specified, these concepts often seem to focus on a sharp technological discontinuity whereas our results show that dynamic domains remain such. For our 28 domains, many of the more rapidly improving cases have shown such behavior for more than the 35+ years for which we were able to obtain the corresponding patents and none of these have appreciably yet slowed in performance improvement. A second reason for care is that many of the prior examples of qualitatively selected very important inventions are represented by a large set of patents in this paper- perhaps even a domain such as integrated circuits with its almost 150,000 patents.emergence of new dynamic domains; however, even this discontinuity focus may obscure the fact that dynamic domains (such as integrated circuits or wireless transmission among our domains) do not have their major economic and societal impact at emergence. Their disruptive and apparently discontinuous impacts instead often occur after decades of dynamic improvement. As such a domain continues to rapidly improve, the performance of artifacts in the domain rapidly rises so that more and more application fields are affected in the manner of general purpose technologies [The preceding points suggest that a potentially better way to make the connection between technological discontinuities and domains with patents of high importance, recency and immediacy is to assert that the discontinuity of interest is the nologies . Althougdomain level of importance, recency and immediacy correlate strongly with the rate of progress in that domain; however, the results also indicate that effort and science links measured at the domain level do not correlate with the rate of progress in the domain. The rising sea conceptualization imagines the contributions of science and inventions from all domains to be equally available to all domains but the ability of domains to convert that rising sea to performance improvement is strongly dependent upon fundamental characteristics of that domain. Such fundamental characteristics could involve the intensity of interactions among components in the domain [One more speculative conceptual contribution is largely based upon the failed correlations as well as the successful ones: we call this concept the rising sea metaphor. Our results show that measurements at the e domain ,73 as wee domain ,77.The technological improvement rate of a domain can be very useful in understanding the potential of a specific technology particularly if one compares it to the improvement rate of competitive and complementary technological domains. This is because the improvement rates are reasonably consistent across time  so a domThe results of the research reported here are correlations robust to the domains analyzed and consistent for 12 years into the future (2001–2013). These findings statistically (in a robust way) reflect what is likely to happen—or at least what is happening now- in performance trends. The process of estimating a technological improvement rate given a domain of interest works as follows:Select a domain of interestUse the COM ,68 to seCalculate the average number of forward citations in 3 years  and is probably nearly as accurate as an estimate that might take more than 30 hours of data search (and might not be possible to find in infinite time). A major implication from the research reported here is the potential to greatly expand the usage of technological improvement rates in technology strategy and research policy. Some useful approaches include:The RQuantitatively monitoring improvements at all phases of technological maturity to understand if large (unexpected) changes have occurred.Monitoring improvement rates in key competing (threat and opportunity) technologies.The patent based approach to estimation of improvement rates described above can be the basic approach to the monitoring task and it might be applied even very early in the technology’s history possibly even before the start of commercial production as long as sufficient patenting has started.Often times a competing technology has been used in other application fields and thus improvement rates might be found from actual data but using the patent based approach above would still be useful to improve the robustness of the estimate.Based upon the prior discussion, relative rates of technical performance increase can have large implications for the future viability of component technologies in products and systems as well as the viability of industries and thus have great importance to forward-looking firms. Acquisition strategy, product component technology choice and appropriate research goals could be informed by improved understanding of the probable improvement potential of relevant technologies. Moreover, the results of performance improvement monitoring have implications for choosing technologies that should receive research funding from firms and governments and for choosing ventures in which to invest risk capital.2 = 0.64) establish an important empirical finding: patents do contain much significant information relevant to quantitatively determining the differences in technological improvement rates.This paper represents the first statistically significant comparison between metrics that were derived from individual patent sets from a group of technological domains and the performance improvement rates of the same individual domains. This was done to test hypotheses derived from existing theories of technological change, to initiate predictive theory development and to establish a stronger practical basis for technology strategy and planning for firms and governments. The strong correlations (r = 0.76 for the strongest case) and multiple regressions  of the practical application of the results of this research will only be known if and when widespread application occurs.S1 FileTable B. Raw values of 10 variables for 28 domains. Table C. Raw values of extra variables for 28 domains. Table D. Correlation values for all variables for 28 domains. Table E. Domain Robustness Tests for 10 variables for 20 trials (14 domains each). Table F. Time Robustness Analysis for 2 Patent metrics showing Pearson correlation and p-value.(DOCX)Click here for additional data file.


NEAr-iron Transporter (NEAT) domains have been studied in pathogenic Gram-positive bacteria to understand how their proteins obtain heme as an iron source during infection. While a 2002 study initially discovered and annotated the NEAT domain encoded by the genomes of several Gram-positive bacteria, there remains a scarcity of information regarding the conservation and distribution of NEAT domains throughout the bacterial kingdom, and whether these domains are restricted to pathogenic bacteria. This study aims to expand upon initial bioinformatics analysis of predicted NEAT domains, by exploring their evolution and conserved function. This information was used to identify new candidate domains in both pathogenic and nonpathogenic organisms. We also searched metagenomic datasets, specifically sequence from the Human Microbiome Project. Here, we report a comprehensive phylogenetic analysis of 343 NEAT domains, encoded by Gram-positive bacteria, mostly within the phylum Firmicutes, with the exception of Eggerthella sp. (Actinobacteria) and an unclassified Mollicutes bacterium (Tenericutes). No new NEAT sequences were identified in the HMP dataset. We detected specific groups of NEAT domains based on phylogeny of protein sequences, including a cluster of novel clostridial NEAT domains. We also identified environmental and soil organisms that encode putative NEAT proteins. Biochemical analysis of heme binding by a NEAT domain from a protein encoded by the soil-dwelling organism Paenibacillus polymyxa demonstrated that the domain is homologous in function to NEAT domains encoded by pathogenic bacteria. Together, this study provides the first global bioinformatics analysis and phylogenetic evidence that NEAT domains have a strong conservation of function, despite group-specific differences at the amino acid level. These findings will provide information useful for future projects concerning the structure and function of NEAT domains, particularly in pathogens where they have yet to be studied.Iron is essential for bacterial survival, being required for numerous biological processes.  NEAT is domain with a predicted β-strand secondary structure, and NEAT-containing proteins were proposed to be cell membrane anchored and exposed to the surface of the cell. NEAT domains were originally identified as being encoded by the genomes of several Gram-positive pathogens  and two non-pathogens . This in silico study reported the initial identification of NEAT domains and provided information critical to perform later biochemical, structural and biophysical characterization of domain function. Indeed, studies performed over the past ten years have shown that NEAT domains enable Gram-positive bacterial proteins to acquire heme-iron from host hemoglobin or the haptoglobin-hemoglobin complex, contrary to the initial proposed role of NEAT domains as a siderophore-binding B. cereus, L. monocytogenes, S. aureus, and S. pyogenes, and they are secreted and cell wall-anchored in B. anthracisS. aureus and B. anthracis NEAT systems, see Grigg et al. 2010 and Honsa and Maresso 2011, respectively.In 2002, a bioinformatics study examined genes mapping near putative Fe10-helix  that fold to form a hydrophobic heme-binding pocket B. anthracis, B. cereus, L. monocytogenes, S. aureus and S. pyogenes. For example, when certain genes encoding NEAT proteins are deleted in S. aureus (isdC), B. anthracis  or B. cereus (ilsA), the bacteria cannot survive when hemoglobin is the sole iron source, and some of these mutant strains exhibit decreased virulence in murine or insect models of infection Clostridium botulinum. In particular, we were interested in identifying new NEAT domains encoded by additional pathogenic species, to provide information needed for future studies that focus on iron acquisition systems in clinically relevant bacteria.NEAT domains are conserved heme binding modules, thought to be exclusive to Gram-positive bacteria, although the restriction based on this classification has not been confirmed and has not been addressed since the initial 2002 study B. anthracis IsdX1 NEAT protein is shown in 10-helix , is a completely conserved sub-structure of all NEAT domains that lies on top of the distal side of heme. This functional region is necessary for heme binding by the B. anthracis IsdX1 NEAT protein, and is essential for heme extraction from hemoglobin by the B. anthracis IsdX2 NEAT protein 10-helix is critical for IsdX2 to scavenge heme, and this activity is attributed to its amide side chain S. aureus IsdB (2 domains) and IsdH (3 domains) proteins, the B. anthracis IsdX2 protein (5 domains), and the S. pyogenes Shr protein (2 domains) 10-helix sequence (SXXXXY) and the heme-binding sequence on the eighth β-strand (YXXXY) are important for NEAT function, at least in those NEAT domains that have been studied so far. Thus, they must be considered when analyzing other NEAT domains and when generating predictions about the role of NEAT proteins in heme-iron acquisition and their possible role in bacterial pathogenesis.To illustrate the features of the conserved NEAT domain, a structure of the www.hmpdacc.org) and found homologues only in samples corresponding to the vaginal sites , and skin sites (anterior nares) one 100% homologue to IsdC; left retroauricular crease: one partial hit to an iron regulated cell surface protein in Staphylococcus capitis; right retroauricular crease: one partial hit to a cell surface protein in Staphylococcus caprae. Identical sequences were discovered in the search of the nr database so these did not contribute any new diversity to the NEAT family. All proteins were predicted to be secreted or cell-surface associated, with many possessing sortase motifs for covalent anchoring to the cell wall B. anthracis BslK protein, which possesses a single heme-binding NEAT domain, and three SLH-domains  or Syntrophobotulus glycolicus (orange text)]. Also, clusters of NEAT domains were identified that included members that have been the subject of previous functional studies such as: i) a staphylococcal cluster that contains the IsdA, IsdB and IsdH heme-acquisition domains from S. aureus (black text), which now also includes NEAT domains from coagulase negative staphylococci Bacillus NEAT domains (red text) that resemble those in B. anthracis IsdX2, which contains five or six NEAT domains. The multi-NEAT IsdX2 protein is unique, as it is the only secreted NEAT protein and it possesses multiple domains that selectively acquire heme from hemoglobin (hemophores). Other members from the Bacillus genus cluster near the IsdX2 NEATs so are likely hemophore proteins. In addition, a cluster containing B. anthracis IsdX1 (single NEAT-containing protein) includes members of the Bacillales family, which are also likely hemophores. These two groups surround clusters of domains such as those in the Paenibacillus genus , which is not demonstrated in any other region of the tree  inside plant cells, or in the environment itself, such as in soil and decaying plant matter. Therefore, we employed in vitro biochemical studies using one of the 20 predicted P. polymyxa NEAT domains, to determine the conservation of porphyrin (heme) binding-function. The complete amino acid sequence of Pp-IsdCN from P. polymyxa, with the NEAT domain highlighted in grey, is shown in N into a pGEX2TK vector and over-expressed the protein in Escherichia coli BL21 then purified the 14 kDa product to homogeneity using affinity chromatography  encodes a heme-binding NEAT domain, we chose to clone and purify an IsdC-like NEAT domain homologue from the nitrogen-fixing agricultural inoculant, tography , inset.N was analyzed for the ability to bind endogenous heme synthesized by E. coli by detection of a strong absorbance (Soret band) at 400 nm, a commonly used absorbance profile that is specific to bound heme N produced a strong Soret band at 404 nm, indicative of co-purification with heme (red spectra), characteristic Q-bands were detected at 500 and 630 nm, indicating oxidized heme was bound by the NEAT domain N can bind oxidized heme P. polymyxa is exclusively environmental, the ability of Pp-IsdCN to retain heme-binding activity suggests that the function of the NEAT domain is remarkably conserved, through the evolution of Gram-positive pathogens vs. soil-bacteria. As discussed, P. polymyxa has been shown to invade plant tissue as part of its natural relationship with plants Pp-IsdCith heme . AdditioC. perfringens were discovered, although no clostridial NEAT domains have been functionally characterized S. aureus NEAT proteins IsdA, IsdB and IsdH that also contain the LPXTG motif Clostridium bartlettii p2, Clostridium botulinum p1 and p2, Clostridium butyricum p1, Clostridium celatum p2, Clostridium chauvoei p2, and C. perfringens p2 are predicted to be cell surface-associated, however the exact cellular localization of these proteins unknown.During the initial NEAT domain identification study in 2002, two putative NEAT proteins from C. chauvoei, C. novyi, C. perfringens and C. tetani, being able to cause systemic infections that would allow exposure to the circulatory system and therefore to heme C. botulinum is also a pathogen, however is mostly found within soil; its neurotoxins contaminate food supplies to cause the botulism disease C. botulinum may be exposed to heme, or similar porphyrins such as chlorophyll, during normal growth in the environment, and exploit them as a nutrient supply. The remaining species within the Clostridial Group are non-pathogenic gastrointestinal commensals [C. bartlettii and C. butyricum ], and as such may use their NEAT domains to acquire heme from ingested foods in the gut as a source of iron Within the Clostridial Group, five species are considered pathogens, with four of these, 10-helix sequence (SXXXXY) in 33/51 of the clostridial NEAT domains, similar to the helix in the B. anthracis IsdX1 and IsdX2 heme-binding domains  is absent from all NEAT domains within the Clostridial Group . Since tnthracis . We propC. botulinum protein4 (Cb-p4) against the known structure of Ba-IsdX1. 10-helix. Phe-108, noted as a possible heme-iron coordinating residue, is located on the β8-strand at the position comparable to the second tyrosine in the conventional YXXXY heme-binding sequence  can act as heme-axial ligands Taking into account our current knowledge of the relationship between NEAT sequence, structure and function, we sought to predict the structure of clostridial NEAT domains, and the location of the putative heme-iron coordinating residues. Predicting such a model would provide preliminary data needed to unravel the potentially unique heme-acquisition mechanism of clostridial NEAT domains. We employed comparative structural modeling of the NEAT domain of sequence . Using C10-helix residues of Cb-p4 are highly similar to those of the Ba-IsdX1 and Ba-IsdX2 heme-binding NEAT domains 10-helix  do not contain the canonical SXXXXY 310-helix sequence , nor the YXXXY heme-binding sequence . Since they lack both functional regions, these domains cannot scavenge heme from hemoglobin, or bind heme B. anthracis lacks the iron-coordinating tyrosine in the YXXXY sequence (YKQTH), and is unable to bind heme, yet it interacts with hemoglobin (SXXXXY sequence is conserved: SKMNTY) and may form a stabilizing contact for the other IsdX2 NEAT domains to extract heme from hemoglobin While the Cb-p4 structure is a model based on homology to IsdX1, it is encouraging that the conserved structure and fold of the NEAT domain is retained and the fundamental residues needed for heme binding are analogous to those already established. The non-heme binding NEAT domains of 10-helix that may H-bond with a propionate side-group of heme; iv) a possible interaction of Met-101 with heme; and v) overall hydrophobic interactions with the internal NEAT heme-binding pocket and heme. Also, as noted, IsdB of S. aureus possesses a unique heme-iron coordination requirement at the amino acid level, so the concept of a new heme-binding regime is not unprecedented in silico analysis of possible clostridial NEAT-heme acquisition function. Future studies are needed to solve the crystal structure of Cb-p4 and to test the biochemical function(s) of the clostridial NEAT domains. Our data suggest that several clostridial species harbor NEAT domains that may act to acquire nutrients from the host by a novel heme-binding mechanism. Also, this is the first homology-modeling and in silico analysis of a NEAT-domain from an anaerobic pathogen since the initial identification of the two C. perfringens proteins Together, we have identified five possible interaction events that may allow clostridial NEAT domains to bind heme in a novel manner: i) Phe-108, which may provide an axial-ligand interaction with iron; ii) π-stacking interaction(s) of the aromatic side chain of Tyr-29 and Phe-108 with each side of the heme porphyrin; iii) Ser-24 in the 3in vitro function, which we elucidated from previous studies focusing on NEAT proteins from Gram-positive pathogens. However, as the phylogenetic tree shows, the majority of the 343 NEAT domains do not fit into a subgroup that contains characterized NEAT domains. Therefore, the overall amino acid sequence conservation in critical regions of the NEAT domain, as well as similarities and differences, are addressed here.Thus far, we have provided evidence for possible groups of NEAT domains based on their 10-helix, a stretch of six amino acids that is canonically SXXXXY. The serine in this region interacts with a heme propionate group; therefore, it is an important determinant of heme binding function  have the SXXXXY sequence. Seven of these NEAT domains (2%) contain a one amino acid insertion within the 310-helix, yet they retain the amino- and carboxy-terminal serine and tyrosine. Two of these NEAT domains (0.6%) harbor a single amino acid deletion within the helix. Thirty-nine NEAT domains (11.3%) possess the serine within the 310-helix, however they have a different aromatic residue in place of the tyrosine (SXXXXF/H); of these, 38 contain a phenylalanine, and one has a histidine. These NEAT domains may have a somewhat different heme-binding environment, utilizing phenylalanine π-stacking, similar to what was proposed for the clostridial NEAT domains. Finally, 59 of the NEAT domains (17%) do not have the canonical SXXXXY sequence within the 310-helix. This group includes the IsdB NEAT1 and IsdH NEAT1 and NEAT2 domains of S. aureus, which do not bind heme or acquire heme from hemoglobin. This indicates that the NEAT domains that do not have the serine or an aromatic residue at the terminus of the 310-helix, do not function as heme acquisition modules, but instead might provide a stabilizing action for other NEAT domains within the same protein to bind heme We have previously discussed the importance of the 3function . AdditioThe slight extension of the β7-β8 loop that was observed in Cb-p4  is predoe.g. Pp-p4, IsdC and BslK proteins of B. anthracis and S. aureus, IsdX1, IsdX2 NEAT1, NEAT3, NEAT4, and NEAT5, IsdA, IsdB NEAT2, and IsdH NEAT3) e.g. IsdX2 NEAT2 of B. anthracis, which is unable to bind heme); and iii) lacks both tyrosine residues. Many of the NEAT domains that belonged to the third group lack any noticeable heme-binding motifs, suggesting that either these NEAT domains play a structural role, as is the case with the non-heme binding NEAT domains of IsdB and IsdH of S. aureus, or there is an as yet unidentified heme-coordinating axial ligand(s) in these proteins Analysis of the YXXXY heme-binding sequence revealed that approximately half of the predicted NEAT domains contain this critical motif . These 165 NEAT domains fell into three groups: i) has both tyrosines (48%), suggesting they are able to bind heme (Clostridium bartlettii (89 amino acids). It did not cluster with the other clostridial NEAT domains, but rather it clusters near the IsdC group. The two longest NEAT domains identified are p1N2 of Eggerthella sp. and p1 of Clostridium methylpentosum (both 159 amino acids long). These two NEAT domains cluster close to each other, with high bootstrap scores, but they map at the terminus of the tree that had few groups with multiple family members. Neither have a SXXXXY or YXXXY motif. Thus, while the amino acid similarity between all NEAT domains and the lengths may vary, the importance of NEAT structure and function relationships is more related to secondary structure, specific amino acid residues within the 310-helix, the heme-binding YXXXY sequence, and the overall hydrophobic nature of the heme-binding pocket.Finally, the 343 NEAT domains analyzed are approximately the same length as previously characterized NEAT domains (average length 120 amino acids). The shortest NEAT domain was p1N1 of We identified 343 putative NEAT domains from 82 different bacterial species that were almost exclusively members of the Firmicutes. Perhaps surprisingly, no new members were discovered in metagenomic data sets from the Human Microbiome Project. This may indicate that in humans, NEAT domain proteins are generally restricted to pathogenic species. Protein parsimony analysis allowed clustering of predicted NEAT domains into known groups that included new members, and into new NEAT domain Groups that have yet to be functionally characterized. These results also allowed us to report: i) additional pathogenic organisms that encode putative NEAT domains that potentially act as heme-iron acquisition systems employed during infection; ii) the conservation of NEAT domains within the Firmicutes, including their presence in environmental and plant symbiotic bacteria; iii) the conservation of heme-binding function by a NEAT homologue encoded by a non-pathogenic environmental species; iv) comparative-modeling to demonstrate that NEAT structure may be conserved despite amino acid sequence differences; and v) altered structural requirements for heme binding by several divergent clostridial NEAT domains. Together, the data presented provide information describing 343 NEAT domains, 328 of which are new. Our data furthers the understanding of NEAT structure and function. As new bacterial genome sequences become available, more NEAT domains will be discovered. Work presented here will assist future research projects that target NEAT domains with anti-microbial molecules as a strategy to inhibit pathogens from accessing the rich heme-iron pool during infection.S. aureus IsdC protein sequence as the query (gi: 285816811). It is a representative member of the Conserved Domains family cd06920, NEAr Transport domain, and pfam05031 −11 were removed, resulting in a final count of 185 unique proteins, encoding 343 NEAT domains. Protein subcellular localization was predicted using PSORTb  against the NCBI Non-redundant protein sequences (nr) database (update 11/1/2013) using the www.hmpdacc.org). A separate blast database was created for each of the 18 body sites then was searched by blastp 2.2.28+ using IsdC as the query, as before.We also performed a blastp search of the human filtered, translated whole genome shotgun sequences corresponding to each body site sampled and sequenced for the Human Microbiome Project . The seed bacteria were inoculated into 6 mL lysogeny broth (LB) and grown for 48 hr at 30°C. Chromosomal DNA was isolated from cultures using the E.Z.N.A bacterial DNA kit . The genome of P. polymyxa ATCC 842 was recently sequenced www.patricbrc.org/portal/portal/patric/), we determined that the putative P. polymyxa isdC (Pp-isdC) gene was located on contig 36 Pp-isdC from the E681 strain  as the template, identified 32 nucleotide mismatches between E861 and ATCC 842 Pp-isdC; however at an amino acid level, there were only eight amino acid mismatches, none of which were located within the NEAT domain (NEAT-BamPp-isdC HI (5′-GTT-CGG-ATC-CCC-AAA-ATT-GGC-GGA-TGG-TAC-3′) and reverse primers NEAT-EcoPp-isdC RI (5′-GCT-CGA-ATT-CAA-TGC-TTT-TGG-AAT-CAA-AAG-CGA-AGC-G-3′) that allowed the NEAT domain of Pp-isdC (NPp-IsdC) to be PCR-amplified from the ATCC 842 strain, using Pfu AD turbo polymerase . The reverse primer had an artificial stop codon (UAA) inserted before the Eco RI restriction site, as only the nucleotides encoding the NEAT domain were PCR-amplified, and the Pp-isdC stop codon was not cloned. The resulting PCR product was digested using Bam HI and Eco RI restriction enzymes  and ligated between the Bam HI/Eco RI sites of the pGEX2TK vector S-transferase (GST). The recombinant plasmid was then transformed into E. coli DH5α, plasmid DNA was recovered, the sequence of the insert was confirmed, and pGEX2TK::gst-NPp-isdC was transformed into E. coli BL21 for protein expression.T domain . We desiE. coli BL21 strain harboring pGEX2TK::Ngst-Pp-isdC was grown in LB broth supplemented with 50 µg/mL ampicillin and 25 µg/mL kanamycin at 37°C. Pp-IsdCN was expressed using 1.5 mM isopropyl β-D-thiogalactopyranoside  induction for three hours at 37°C. Cells were centrifuged  and resuspended in 50 mM Tris-HCl, pH 7.0. Bacteria were lysed using a French press and centrifuged at 14,000×g, and supernatants were applied to glutathione-Sepharose resin . After one 30 mL wash with Tris-HCl buffer , Pp-IsdCN was eluted off the column after an overnight incubation with 50 units of thrombin  at room temperature to isolate Pp-IsdCN. Thrombin was removed using aminobenzamidine resin . Five µg purified, recombinant Pp-IsdCN was analyzed by SDS-PAGE Coomassie stain .To measure heme binding, spectroscopic scans were taken of the purified Pp-IsdCC. botulinum (Cb-p4) was modeled using SWISS-MODEL B. anthracis IsdX1 chain A (heme-bound) as the target structure  and protein (B) sequences from Paenibacillus polymyxa from strains ATCC 842 and E681. The NEAT domains are highlighted in grey. Nucleotide mismatches are highlighted in black in (A). In (B), asterisks indicate identical residues and colons indicated conserved residues; the 310-helix sequence is designated by the horizontal line and the conserved phenylalanine residues are indicated in bold; the red arrowhead points to the single non-conserved amino acid residue.(TIFF)Click here for additional data file.Table S1List of 185 putative NEAT domain-containing proteins identified by blastp using Staphylococcus aureus IsdC (gi: 285816811) as the query. Protein Name, GenBank Accession Number, Amino Acid Length, Number of NEAT domains per protein, Additional Features and Predicted Cellular Localization, based on PSORTb prediction, are reported. Abbreviations: LRR, leucine rich repeat; FMN flavin mononucleotide; SLH, surface layer homology; FIVAR, found in various architectures domain; LPXTG, cell wall anchor domain; YSIRK, gram-positive signal peptide motif; fn3, fibronectin type 3 domain.(PDF)Click here for additional data file.Table S2List of organisms carrying genes predicted to encode NEAT domain proteins arranged by phylum, class, order, family, genus and species.(PDF)Click here for additional data file.


The structure of the catalytic domain of RpfC (Rv1884) closely resembles those of RpfB and RpfE. This structural conservation highlights the importance of the versatile domain composition of the RPF family. Mycobacterium tuberculosis, is reported. The structure was solved using molecular replacement once the space group had been correctly identified as twinned P21 rather than the apparent C2221 by searching for anomalous scattering sites in P1. The structure displays a very high degree of structural conservation with the previously published structures of the catalytic domains of RpfB (Rv1009) and RpfE (Rv2450). This structural conservation highlights the importance of the versatile domain composition of the RPF family.The first structure of the catalytic domain of RpfC (Rv1884), one of the resuscitation-promoting factors (RPFs) from  These proteins resuscitate bacteria that have entered a dormant state, allowing them to proliferate normally. Despite some key advances since the first protein identification and characterization, their precise mechanism of action remains elusive. The protein was first isolated in et al., 2004M. tuberculosis, which showed that the domain is a short version of the c-type lysozyme lacking the first helix . They contain a conserved catalytic domain, but the domain composition shows variability also found in other species  protease  was cloned into the Escherichia coli Rosetta2 (DE3) strain grown in ZYM5052 auto-induction medium at 25°C for 36 h  (buffer A). The lysate was cleared by centrifugation at 48 000g for 1 h at 4°C. The supernatant was loaded onto a nickel–NTA column  equilibrated with buffer A and was eluted with buffer A supplemented with 300 mM imidazole (buffer B). The eluted protein fraction was dialysed (3 kDa cutoff) against 20 mM Tris pH 7.5, 2 mM BME (buffer C) overnight at 4°C in the presence of TEV protease. The cleaved protein was further purified by gel filtration on a HiLoad Superdex 75 column  equilibrated in buffer C before being concentrated for crystallization trials. Crystals grew readily in 22 of the 96 conditions of The Classics Suite , but all belonged to the same space group, with the condition 0.1 M sodium citrate pH 5, 20%(w/v) PEG 6000 giving the best crystals. Some optimization of this condition was carried out and a slight improvement was achieved using 0.1 M sodium citrate pH 5, 22%(w/v) PEG 6000. The crystals were cryoprotected in the crystallization condition with 20% ethylene glycol.Protein expression was carried out in 2.2.XDS  with unit-cell parameters a = 65.12, b = 88.93, c = 157.02 Å. Finally, the software REINDEX from CCP4 was used with settings h = h, k = k, l = l/2 to give the correct unit-cell lengths a = 65.12, b = 88.93, c = 78.51 Å, α = γ = 90, β = 114.50°. The free set was then reduced to the P21 asymmetric unit and used as the source of free reflection flags for all other data sets.Default processing of data sets using either 1 Table 1 with carMrBUMP  and the presence of only weak anomalous signal that only extended to around 3.8 Å as assessed by phenix.xtriage  to give eight copies in the asymmetric unit and refining with twin operators R and Rfree values on carefully selecting the free set , polymers of up to five repeats of N-acetylglucosamine and NAG-N-acetylmuramic acid, and peptidoglycan fragments that are generated by a number of enzymes, we never obtained clear density for substrates in the active site. We have therefore deposited the structure of the wild-type RpfC catalytic domain (PDB entry 4ow1).Many data sets were collected from crystals of RpfC or the point mutations RpfC_E13A or RpfC_E13M with and without potential substrates and including selenomethionine-substituted RpfC_E13M at the ESRF, SLS, SOLEIL and Diamond synchrotrons. The automatic space-group assignment for all data sets gave the space group as 3.2.a). Coupled with twinning the two folds give rise to the pseudo-C2221 symmetry.The asymmetric unit consists of eight copies of the RpfC chain. A set of four copies is generated by two twofold axes perpendicular to the crystallographic twofold; a single translation of  then generates the second set of four copies Fig. 1a. CouplA, E and S have the most residues modelled into electron density (Gly1–Lys86) with an extra helix beyond the end of the conserved domain (Gly78). Chain B has the least modelled residues (Pro4–Gly78); the other chains are between these limits. We have modelled an ethylene glycol (the cryoprotectant) where a benzamidine molecule is present in the RpfB structures with PDB codes 4kpm .Chains zs Fig. 1b.α r.m.s.d. between the two structures . Compared with the recent RpfE structure . Most of the backbone geometry is conserved, including the connecting loops between the helices. This is in accordance with the first NMR structure that we determined, where the 30 calculated structures shared a low r.m.s.d. of 0.57 Å, low thermal motion as shown by NOE (Nuclear Overhauser Effect) ratios . In RpfC two residues display an elongated conformation (42GVGN45), very similar to RpfE (137GSGS140), to connect α-helices 2 and 3, while a 310-helix (321GLRYAPR327) is present in RpfB. This small change within the secondary-structure composition does not change the relative orientation of α-helices 2 and 3 within the RPF fold . The variation in surface charge between RpfB and RpfE has previously been noted , respectively. This leads to a different charge distribution around the ligand-binding pocket, which may have a role in specificity . Mavrici et al. (2014As expected, the structural conservation between the new RpfC catalytic domain structure that we have determined in this study and the extensively studied RpfB domain is high. The calculated Cld Fig. 1c. The vty Fig. 2c. Mavri al. 2014 suggeste4.M. tuberculosis have similar substrates, although variation in charge around the active site may give rise to small variations in the specificity for different peptidoglycan modifications. The high degree of conservation of the RPF domain explains why the protein is functionally redundant, but most importantly shows that the auxiliary domain composition is mainly responsible for the functional variability.The RpfC structure catalytic domain displays a high degree of structural conservation with the other members of the mycobacterial resuscitation-promoting factor family. Based on the structure that we have solved, we propose that the five RPFs from RpfC, 4ow1PDB reference:


Structural studies reveal how an antiviral factor forms a molecular net to restrict retroviruses including HIV-1. Related research articles Li YL, Chandrasekaran V, Carter SD, Woodward CL, Christensen DE, Dryden KA, Pornillos O, Yeager M, Ganser-Pornillos BK, Jensen GJ, Sundquist WI. 2016. Primate TRIM5 proteins form hexagonal nets on HIV-1 capsids. eLife5:e16269. doi: 10.7554/eLife.16269eLife5:e16309. doi: 10.7554/eLife.16309Wagner JM, Roganowicz MD, Skorupka K, Alam SL, Christensen DE, Doss GL, Wan Y, Frank GA, Ganser-Pornillos BK, Sundquist WI, Pornillos O. 2016. Mechanism of B-box 2 domain-mediated higher-order assembly of the retroviral restriction factor TRIM5α. Image Electron cryotomography shows how TRIM5 forms a hexagonal latticeHIV-1 like other retroviruses stores its genetic material as RNA, and then converts it to DNA once inside a susceptible host cell. The process of converting RNA to DNA, which is called reverse transcription, takes place inside a protein-based shell called the capsid. The viral DNA is then integrated into the DNA of the host, where it can persist indefinitely.Host species protect themselves against retroviruses in various ways. TRIM5, for example, is a protein that recognizes the capsid and as a result inhibits reverse transcription . RecogniTRIM5 belongs to a large family of proteins that have a RING domain, a B-box domain and a coiled-coil domain . Each ofin vitro. For the same reason, fragments of TRIM proteins were used instead of the full-length version in other experiments to demonstrate that TRIM proteins form anti-parallel dimers rather than parallel ones  that the capsid cores were decorated with hexagonal nets of TRIM5. This demonstrates that native TRIM5 protein forms a hexagonal lattice that matches the lattice of In the second paper, Owen Pornillos and colleagues – including Jonathan Wagner as first author – report how the B-box domain of TRIM5 promotes the formation of the hexagonal lattice . CrystalThe crystal structures showed that the mini-TRIM proteins form both dimers and trimers via their B-box domains . This miin vivo? Moreover, the antiviral activity of TRIM5 depends on its RING domain and its activity as an E3 ubiquitin ligase (Many questions remain regarding how the structure of TRIM5 relates to its function. For example, most of the mini-TRIM crystals formed dimers via their B-box domains; do these dimers play a functional role n ligase , but how


Dioscorea alata andDioscorea rotundata with a view of providing information that will enhance their end use. The yam varieties were washed, chipped, parboiled at 50°C, soaked for different periods , dried at 60°C, and milled into flour. The flour samples were analyzed for their nutritional composition, pH, color, and functional properties. The flour samples were also made into pastes and were sensorially analyzed and 0 h soaked samples were used as control. The protein content of 18 h-soakedD. rotundata andD. alata flour samples was significantly different from the control and soaking had no effect (P > 0.05) on the fat and ash content but the carbohydrate content of the flour samples ranged from 83.08% to 86.13%. The 18 h-soakedD. rotundata flour sample had the lowest peak viscosity, breakdown value, and final viscosity among theD. rotundata variety samples. Pasting temperature ranged from 79.80 to 83.60°C and 6-h soakedD. alata flour sample had the lowest water absorption capacity and the highest bulk density. On the basis of sensory analysis, the panelist preferred the taste, texture, color, and appearance of paste made from the 18-h soakedD. rotundata flour to the paste of other flour samples. The results of this study show that D.rotundata should be soaked for 18 h prior to drying and milling in order to obtain a good-quality flour and paste.This study investigated the effect of soaking pretreatments on some of the properties of flour obtained from two varieties of yam namely; Dioscorea (familyDioscoreaceae) consists of some species that are commonly known as yam which are consumed perennial in Africa, Asia, Latin America, and Oceania (http://en.wikipedia.org/wiki/Yam_%28vegetable%29). Throughout the world, over 150 species are grown (Purseglove D. rotundata (white yam),D. esculenta (Chinese yam),D. alata (water yam),D. bulbifera , andD. dumenterum (trifoliate yam) are among the economically important species (Ike and Inoni http://www.iita.org/yam). Yams are usually processed into dry-yam tubers/slices and flour in West African countries such as Ghana, Benin, and Nigeria  were converted to chips using the method described by Ige and Akintunde .The yam flour samples were prepared by stirring them in hot water to make amala paste and served to 20 taste panelists who are regular consumers of amala. The pastes were rated for aroma, texture, color, and taste using a 9-point hedonic scale according to Iwe .All analyses were carried out in triplicates and the data were subjected to analysis of variance (ANOVA). SAS version 9.0  for windows was the statistical software that was used.D. rotundata andD. alata flour samples was lower than that of the control and this reduction was significant while the reduction inD. alata was insignificant. The protein content of 18 h-soakedD. alata flour sample was insignificantly different from the control. There was no significant difference in the moisture content of the 6- and 12 h-soakedD. rotundata flour samples but the moisture content of the 18 h-soakedD. rotundata flour sample was significant compared to the control. The highest moisture content (10.12%) was observed in 6 h-soakedD. alata flour sample while the 12 h-soakedD. alata had the lowest moisture content (8.16%). TableTableD. alata which was used as the control had the highest dispersibility and its dispersibility was not significantly different from that of the 12 h-soakedD. rotundata flour sample as shown in TableD. rotundata flour sample (18 h soaked) had the highest while 6 h-soakedD. alata flour sample had the lowest water absorption capacity and its value was not significantly different fromD. alata that was used as control.P > 0.05) in the color of all the yam flour samples at different soaking times as shown in TableP < 0.05) during the different soaking periods.There was no difference (D. rotundata flour sample (TableD. rotundata soaked for 12 h had the highest peak viscosity followed by samples ofD. rotundata soaked for 6 h and the control.D. rotundata soaked for 18 h flour sample had higher holding strength (471.50 RVU) compared to other samples The values of the breakdown for flour fromD. alata variety samples were lower than that of the flour fromD. rotundata cultivar except forD. alata soaked at 18 h. The final viscosities of the D.rotundata samples at different soaking times were not significantly different from each other. Setback values which are an index of retrogradation varied from 93.00 to 488.50 RVU.The lowest breakdown, final, and peak viscosity were observed in the 18 h-soakedple Table. PastingP ≤ 0.05) in the appearance, texture, taste, aroma, and the overall acceptability of the yam paste made from different flour samples. The color, taste, appearance, aroma, and the overall acceptability of the paste made from flour produced from the control sample ofD. rotundata were significantly different from the appearance, color, taste, aroma, and the overall acceptability of paste made from 18 h-soakedD. rotundata flour. After the 18 h soaking period, the overall acceptability, taste, texture color, and appearance ofD. alata were significantly different fromD. rotundata at the same soaking time.TableThe variations in the protein content of the two yam varieties may be due to genetic composition of the varieties and environmental conditions Woolfe . The redD. rotundata flour sample will reconstitute better than others. The bulk density of the 18 h-soakedD. rotundata andD. alata flour samples was significantly different from other samples with lesser soaking time and this may be due to the starch particles becoming looser during this soaking period. It has been reported that bulk density reduces as soaking time increases.D. rotundata that was soaked for 18 h before being processed into flour had the highest water-holding capacity whileD. alata soaked at 6 h had the lowest capacity, the water-holding capacity is also a function of the protein content of the yam flour . Also the increase in soaking time might have caused a decrease in pH as a result of the actions of microorganisms which could have induced acidity.D. alata samples were low compared to all theD. rotundata samples and this indicates that the carbohydrate components ofD. rotundata flour samples will not breakdown easily and quickly like theD. alata samples until it is cooked properly. Peak viscosity has been reported to be an important parameter to processors so as to obtain a useable starch paste (Adeyemi D. rotundata flour sample had the highest holding strength, holding strength indicates the capacity of a flour sample undergoing processing to resist shear stress and heating. The vulnerability of cooked starch granules to disintegrate into smaller components is measured as breakdown and this has been reported to affect the steadiness of flour products (Beta et al. D. rotundata flour sample will be higher under hot condition. Also, all the flour samples fromD. rotundata can form thick and strong gel after cooking and cooling than samples fromD. alata based on the observed insignificant differences in their final viscosity.The peak viscosity of all the Adeyemi . The 18 D. rotundata flour to the paste made from other flour samples including the control sample. The soaking period might have influenced the color, texture, and appearance ofD. rotundata as well as its acceptability. The result of some of its functional properties also showed that paste from 18 h soakedD. rotundata will have desirable sensory qualities.On the basis of the sensory analysis, the panelist preferred the taste, texture, color, and appearance of paste made from the 18 h-soakedD. rotundata for 18 h before processing it into flour led to the retention of the nutrients of the yam flour except protein and improved the color, texture, and appearance of the paste that was developed from this flour. Also, a viscous and firm gel that will be stable at high temperature as well as a useable and acceptable starch paste with superior eating quality can be obtained by soakingD. rotundata for 18 h prior to processing.SoakingNone declared.


Hepatitis C virus (HCV) is a pathogen of global importance and nearly 200 million people are chronically infected with HCV. HCV is an enveloped single-stranded RNA virus, which is characteristic of the formation of the host membrane associated replication complex. Previous functional studies have already established that the human ER-anchored VAPB protein acts as a host factor to form a complex with HCV NS5A and NS5B, which may be established as a drug target. However, there is lacking of biophysical characterization of the structures and interfaces of the complex, partly due to the dynamic nature of the complex formation and dissociation, which is extensively involved in intrinsically-disordered domains. Here by an integrated use of domain dissection and NMR spectroscopy, for the first time we have successfully deciphered that the HCV NS5B utilizes its auto-regulatory C-linker to bind the VAPB-MSP domain to form a dynamic complex. This finding implies that the NS5B C-linker is capable of playing dual roles by a switch between the folded and disordered states. Interestingly, our previous and present studies together reveal that both HCV NS5A and NS5B bind to the MSP domains of the dimeric VAP with significantly overlapped interfaces and similar affinities. The identification that EphA2 and EphA5 bind to the MSP domain with higher affinity than EphA4 provides a biophysical basis for further exploring whether other than inducing ALS-like syndrome, the HCV infection might also trigger pathogenesis associated with signalling pathways mediated by EphA2 and EphA5. Hepacivirus genus in the Flaviridae family. The genome of HCV is positive sense single ~9.6 kb long RNA and encodes ~3000 residue polyprotein, which is subsequently processed by viral and cellular proteases into 10 mature structural and nonstructural regulatory proteins on the rough endoplasmic reticulum (ER). Nonstructural proteins, which coordinate the intracellular processes of the virus life cycle, include P7 ion channel, NS2 protease, NS3 serine protease and helicase, NS4A, NS4B, NS5A proteins and NS5B RNA-dependent RNA polymerase (RdRp) [Hepatitis C virus (HCV), first discovered in 1989 . Nearly HCV infection induces distinct alteration of membranes which form sponge-like inclusions, called as “membranous webs”. Studies have suggested that these membranous webs constitute the sites for RNA replication, on which replication proteins and viral RNA localize –7. On thRecently, NS5B, the core component of HCV replication complex, has emerged as a key target for the development of small molecules that can selectively inhibit the replication as mammalian cells lack an RdRp equivalent. NS5B contains 591 residues, in which the catalytic domain over residues 1–531 is connected to a membrane inserting sequence 571–591 with a linker over residues 531–570 . In 1999Due to a high rate of mutation for viral proteins during the life cycle, targeting host-viral protein interaction interfaces for development of antiviral drugs has become increasingly attractive in recent years. Previous functional studies have identified the involvement of human vesicle-associated membrane protein-associated proteins (VAPs) in HCV replication through interaction with NS5A and NS5B –23. BrieTherefore, delineation of high-resolution structures and interfaces of the VAPs-NS5A/NS5B interactions represents an essential step to facilitate further drug development by targeting their interfaces. The VAP family includes VAPA, VAPB and VAPC, out of which VAPB is composed of three domains : an N-teIn the present study, by the same approach ,33, we aTo study the interaction between NS5B and VAPB, we have dissected both VAPB and NS5B into different combinations of domains. For human VAPB, here we used the same dissected proteins which we previously cloned and characterized for mapping the NS5A-VAPB interactions , namely 2+-affinity chromatography followed by Heparin affinity chromatography. On the other hand, the C-linker peptide was cloned into pGEX-4T1 vector with GST-tag. The GST-fused peptide was first purified by affinity chromatography with glutathione-Sepharose 4B beads, and subsequently cleaved to release the C-linker peptide which was purified by reverse-phase (RP) C18 column using HPLC system.All VAPB recombinant proteins were expressed and purified by the same procedures as previously described . Three r1H one-dimensional NMR spectra of NS5B(1–570) proteins are also similar, both of which have several very up-field peaks  and 15N (~19 ppm) spectral dispersions. More specifically, the peptide contains 40 residues plus two extra N-terminal Gly-Ser residues from the cleavage of the GST-fusion protein, in which there are 6 Gly and 3 Pro residues. As the HSQC peak of the N-terminal Gly is usually undetectable due to the fast exchange of its amide protons with water, and 3 Pro residues have no amide proteins, there should be 38 backbone HSQC peaks in the HSQC spectrum. However, although HSQC peaks of 5 Gly residues within the NS5B C-linker peptide are all detectable and well-separated  proteins but found no significant perturbation. These results clearly reveal that HCV NS5B binds to the MSP domain of human VAPB protein, completely consistent with previous biological studies [Previously, we have cloned and shown that the NS5B(1–570) with a C-terminal His-tag was activity in binding the human VAPC protein  and DDX5ublished –27, we t studies ,23,24.15N-labeled MSP domain by different NS5B proteins. The C-His-tagged NS5B(1–570) only induced slight shifts of several HSQC peaks of the MSP domain  at which the shifts of the peaks are almost saturated. However, the C-linker peptide alone appears to have less ability to provoke the disappearance of the MSP peaks than the N-His-tagged NS5B(1–570), probably because the presence of the very large catalytic domain might provide additional binding residues, or/and trigger radical dynamics of the MSP domain on μs-ms time scale.We thus generated the recombinant NS5B C-linker peptide which is highly disordered in solution . HoweverWith the well-established procedure to obtain the dissociation constants (Kd) by fitting the data of HSQC titrations, which we have previously utilized to quantify the NS5A-MSP  and NS5B2+-NTA affinity chromatography followed by FPLC size exclusion chromatography as we previously described [Previously, the human MSP domain has been biologically identified to be cleaved and subsequently secreted to serve as a ligand of the ligand binding domain (LBD) of Eph receptors, and furthermore it was shown that the interaction between EphA4 and VAPB-MSP domain is involved in ALS ,30,31. Hescribed ,31,35–3815N-labeled MSP domain with the unlabelled Eph LBDs. As previously we have extensively characterized the interaction of the MSP domain with EphA4 LBD by ITC, NMR and modelling [15N-labeled MSP domain  and for EphA5 at 1:6 (MSP:EphA2). On the other hand, the HSQC titrations reveal that EphA2  and EphAWe also obtained the Kd values for significantly shifted residues induced by binding with EphA2 and EphA5, which are presented in RNA viruses such as HCV are characteristic of the formation of the host membrane associated replication complexes –23,39,40In the present study, by use of the domain dissection followed by NMR characterization, for the first time we have successfully deciphered that the HCV NS5B binds to the MSP domain of the human VAPB mostly by its C-linker. This finding is interesting as in the NS5B(1–570) structure with a close conformation of the active site –15, the Previously the MSP domain has been functionally identified to act as an endogenous inhibitor for the ephrin-binding domain of Eph receptor family , which iIn summary, for the first time we have successfully deciphered that the HCV NS5B utilizes its C-linker to bind the MSP domain of the human VAPB to form a dynamic complex. This finding implies that NS5B C-linker achieves dual roles by a conformational/dynamic switch between the folded state acting as an enzymatic auto-inhibitor, and disordered state ready for dynamically binding the host factor VAPB to initiate RNA synthesis. The identification that EphA2 and EphA5 bind the MSP domain with higher affinity than EphA4 offers clues for further addressing whether other than inducing ALS-like syndrome, the HCV infection might also trigger pathological consequences associated with signalling pathways mediated by EphA2 and EphA5.The DNA fragments encoding the human VAPB(1–195), MSP(1–125) and CCD(152–195) domains were amplified from HeLa cell cDNA library with designed primers as previously described . All theDNA fragments encoding the ephrin binding domain of Eph receptors  were cloned into pET 32a (Novagen) as we previously described ,31,33–38Escherichia coli BL21 (DE3) star (Invitrogen) competent cells. For the expression of recombinant protein, transformed cells with respective plasmids were grown in Luria-Bertani (LB) medium with 100 μg/ml ampicillin at 37°C to reach the absorbance of 0.6 at 600 nm and subsequently induced with respective optimized IPTG concentrations.After the sequences were confirmed by DNA sequencing analysis, plasmids were transformed into 2+-affinity chromatography (Qiagen) while GST-fused NS5B(531–570) was purified by affinity chromatography with glutathione-Sepharose 4B beads (Pharmacia Biotech) under native conditions. Further purification of His-tagged proteins was achieved with Heparin Sepharose HiTrap HP column . GST-tagged NS5B(531–570) was cleaved with thrombin and then the released C-linker peptide was purified by HPLC on a reverse-phase C18 column (Vydac).All the VAPB proteins were expressed and purified as we previously described . For purEscherichia coli Rosetta-gami (DE3) cells (Novagen). Transformed cells were grown in LB media and protein was purified under native conditions using affinity chromatography followed by thrombin cleavage to remove the His-tag. Cleaved Eph proteins were further purified with HPLC size exclusion chromatography using HiLoad 16/60 Superdex 200 column .Plasmids containing the ligand binding domain of 6 Eph receptors were transformed into 15NH4)2SO4 for 15N-labeling, or (15NH4)2SO4/13C-glucose for 15N/13C-labeling. The purity of all protein samples was checked by the SDS-PAGE gel and their molecular weights were verified by a Voyager STR matrix-assisted laser desorption ionization time-of-flight-mass spectrometer (Applied Biosystems). The concentration of protein samples was determined by the spectroscopic method in the presence of denaturant [The production of the isotope-labeled VAPB and NS5B domain/fragment proteins for NMR studies followed a similar procedure except that the bacteria were grown in M9 medium with the addition of  at 25°C as we described previously  at a pro1H one-dimensional or 1H-15N NMR two-dimensional HSQC characterization.All NMR samples were prepared in 10 mM phosphate buffer at pH 6.8. NMR data were collected at 25°C on an 800-MHz Bruker Avance spectrometer equipped with a shielded cryoprobe. Protein samples at a concentration of 100 μM were used for 1H-15N HSQC spectra of 15N- labeled VAPB proteins were acquired at a protein concentration of 50 μM in the absence or presence of the unlabeled NS5B/Eph proteins at different molar ratios in 10 mM phosphate buffer at pH 6.8. More specifically, for characterizing the interactions of the MSP domain with the NS5B C-linker peptide or human Eph receptors, a series of HSQC spectra of the 15N-labeled MSP domain at a protein concentration of 50 μM were collected in 10 mM phosphate buffer at pH 6.8, with gradual addition of the C-linker peptide or Eph receptors with a ratio increment of 0.5 until the shift of HSQC peaks were mostly saturated [1H)2+(Δ15N)2/5)1/2 [For NMR titration experiments, two-dimensional aturated . By supeaturated –27. The )2/5)1/2 ,33. The )2/5)1/2 ,33 to ob


Calderas are collapse structures related to the emptying of magmatic reservoirs, often associated with large eruptions from long-lived magmatic systems. Understanding how magma is transferred from a magma reservoir to the surface before eruptions is a major challenge. Here we exploit the historical, archaeological and geological record of Campi Flegrei caldera to estimate the surface deformation preceding the Monte Nuovo eruption and investigate the shallow magma transfer. Our data suggest a progressive magma accumulation from ~1251 to 1536 in a 4.6 ± 0.9 km deep source below the caldera centre, and its transfer, between 1536 and 1538, to a 3.8 ± 0.6 km deep magmatic source ~4 km NW of the caldera centre, below Monte Nuovo; this peripheral source fed the eruption through a shallower source, 0.4 ± 0.3 km deep. This is the first reconstruction of pre-eruptive magma transfer at Campi Flegrei and corroborates the existence of a stationary oblate source, below the caldera centre, that has been feeding lateral eruptions for the last ~5 ka. Our results suggest: 1) repeated emplacement of magma through intrusions below the caldera centre; 2) occasional lateral transfer of magma feeding non-central eruptions within the caldera. Comparison with historical unrest at calderas worldwide suggests that this behavior is common. Defining and understanding the shallow transfer of magma at volcanoes is crucial to forecast eruptions, possibly the ultimate goal of volcanology. This is particularly challenging at felsic calderas experiencing unrest, which typically includes significant changes in seismicity, deformation and degassing rates. In fact, caldera unrest is particularly frequent, affects wide areas and its evidence is often complicated by the presence of a hydrothermal system: as a result, forecasting any eruption and vent-opening sites within an existing caldera is very difficultIn historical times only two felsic restless calderas have erupted: Campi Flegrei and Rabaul7810124Despite the restless activity of Campi Flegrei, the recent unrest episodes did not culminate in eruption, so that any possibility to define the pre-eruptive shallow transfer of magma  at Campi Flegrei remains elusive. Indeed, this definition is a crucial step in order to identify and understand pre-eruptive processes, and thus to make any forecast. To fill this gap, we focused on the last eruption of 1538, reconstructing its pre-eruptive deformation pattern. For this, we exploited the unique historical, archaeological, geological and long-term geodetic record of the caldera to carefully determine the height variations (and related errors) of 20 selected sites along its coastline . The detIn this paper a completely original data set is provided on the height variations within the Campi Flegrei caldera in the last 2000 years, with the only exception for the previously known vertical displacements at site 30 . While oThe integrated analysis of geomorphological, sedimentological, paleontological, archaeological and historical data allowed a detailed and quantitative reconstruction of the evolution of the ground displacements predating the Mt. Nuovo eruption along the coastline of the Pozzuoli Bay . A repreth century, as suggested by historical and urban planning sources, archaeological evidence and geological data : we therefore use this year to distinguish the long-term caldera deformation from the short-term deformation preceding the eruption, from 1536 to 1538, reconstructed from several sources almost coeval with the eruption18192021After the eruption, all the recovered deformation data show a generalized renewal of the subsidence, with maximum values in the Pozzuoli area.The nature of the data  makes it difficult to precisely infer the amount and extent of horizontal deformation that accompanied the vertical deformation. However, records of ground tilt offer an additional constraint on the deformation field. To this aim, tilt changes between 1536 and 1538 have also been reconstructed .Our reconstruction shows that between 1251 and 1536 a general cumulative uplift affected the inner caldera, with a maximum value of 14 m in Pozzuoli . The larWe model the caldera’s crust as a homogenous, isotropic, elastic half space. Once we include the data uncertainty in our inversion model, our relatively simple approach allows us to get results that can be compared with those of more complex, numerical models. Therefore, while being aware of the limitations of our models , we also emphasize that our models provide a first-order analysis with an estimated and acceptable error23We did not attempt to model any contribution to the deformation field from the Campi Flegrei hydrothermal system or from structural discontinuities associated with the caldera. The nature, extent, and permeability of the pre-1538 hydrothermal system are highly uncertain, so any attempt to model the effect of magma accumulation on it would have introduced a set of largely unconstrained variables. Therefore, any modelling considering the role of the hydrothermal system would have just introduced a higher set of non-constrained variables. Similar considerations also hold in considering any pre-existing discontinuity in the modelling: our general knowledge and data on the subsurface of Campi Flegrei are still too limited to include a reliable and univocal analysis taking into account for pre-existing fractures.Another limit of our analysis is that elastic deformation models have very similar near-field vertical deformation for a range of source geometries3  explains the large uplift at four sites close to Monte Nuovo (3) is consistent with the volume of pyroclastic ejecta from the eruptionThe inversion of the deformation data suggests that the best-fit source for the 1400–1536 uplift is a radially symmetrical intrusion , bathymetric (>50 m on average) and density  preceding the 1538 eruption is based on precise information on height variations at twenty sites along the Campi Flegrei coastline  derived The twenty measurement sites of vertical deformation were selected for their proximity <100 m) to the benchmarks of the levelling network of the Osservatorio Vesuviano; this allowed us to subtract from our calculations the post-1905  before the 1538 AD eruption. Sci. Rep.6, 32245; doi: 10.1038/srep32245 (2016).