Extended Cox regression analysis showed that IR-only herds had 2.7 times the hazard of a subsequent incident compared with negative-testing herds in year one , and that this difference in the hazard reduced by 63% per year. After 2.7 years the difference had disappeared. The supplementary analysis supported these findings showing that IR only herds still had a greater hazard of a subsequent incident after the IR re-test, but that the effect was reduced. This emphasizes the importance of careful decision making around the management of IR animals and indicates that re-testing alone may not be sufficient to reduce the risk posed by IR only herds in England and Wales.Bovine tuberculosis (TB) is an important animal health issue in many parts of the world. In England and Wales, the primary test to detect infected animals is the single intradermal comparative cervical tuberculin test, which compares immunological responses to bovine and avian tuberculins. Inconclusive test reactors (IRs) are animals that demonstrate a positive reaction to the bovine tuberculin only marginally greater than the avian reaction, so are not classified as reactors and immediately removed. In the absence of reactors in the herd, IRs are isolated, placed under movement restrictions and re-tested after 60 days. Other animals in these herds at the time of the IR result are not usually subject to movement restrictions. This could affect efforts to control TB if undetected infected cattle move out of those herds before the next TB test. To improve our understanding of the importance of IRs, this study aimed to assess whether median survival time and the hazard of a subsequent TB incident differs in herds with only IRs detected compared with negative-testing herds. Survival analysis and extended Cox regression were used, with herds entering the study on the date of the first whole herd test in 2012. An additional analysis was performed using an alternative entry date to try to remove the impact of IR retesting and is presented in the  Mycobacterium bovis occurs throughout the world, being particularly prevalent in Africa and South America. In Europe, countries that had not achieved Officially Bovine Tuberculosis Free Status (OTF) status in 2016 included Bulgaria, Croatia, Cyprus, Greece, Ireland, Italy, Portugal, Romania, Spain, and the United Kingdom (Bovine tuberculosis (TB) caused by In England, Defra's strategy for achieving OTF status for England published in 2014 saw the regionalisation of control measures to take account of the spatial heterogeneity of incidence risk . The oveWales has tested all herds annually since 2008, and in 2016, the TB incidence rate in Wales was 7.0 per 100 herd years at risk  test, which is based upon injection of bovine and avian tuberculins alongside one another in the skin of the neck. Cattle infected with bacteria . Howeverbacteria , the senbacteria , 10.M. bovis at post mortem, compared with between 0.13 and 0.22% of animals with a negative SICCT test.Inconclusive reactors (IRs) to the skin test are defined in England and Wales as animals that demonstrate a reaction to the bovine tuberculin that is less than 4 mm larger than an avian reaction under standard interpretation of the test, or less than 2 mm larger than an avian reaction under severe interpretation. In 2015, there were 2,785 herds in England in which only IRs were detected and which went on to have a re-test, and 21% of these herds had positive reactors  at the re-test . AnimalsA change in policy for the management of IRs was introduced in England in November 2017. The policy now requires that all IRs in the HRA and Edge Area with a negative result on re-testing must remain restricted for life to the holding in which they were identified. This also applies to IRs in infected herds in the LRA. In comparison, the Welsh eradication programme aims to remove IRs detected in chronically infected herds, under specific circumstances, alongside any reactors. These proactive approaches to managing the risks of IRs are appropriate in light of current knowledge, yet the factors associated with the fate of IR herds are still not well understood. Analysis of 2016 surveillance data has shown that in the HRA and Edge areas of England, herds with a history of TB had a significantly greater risk of having a confirmed incident at the IR retest . HoweverA retrospective cohort study followed cattle herds in England and Wales between 1st January 2012 and 31st December 2016. Data describing TB testing and incidence for the study period were obtained from the Animal and Plant Health Agency's Sam database. The study population included all unrestricted herds (TB-free) in the high-risk and edge areas of England and Wales that had a whole-herd type test (WHT) in 2012. This included a small number of routine herd tests  which in some cases might not include all animals in the herd. Herd demographic data, information relating to the first WHT in 2012 and the first subsequent incident  were obtained. The number of incidents in the 10 years prior to the 2012 WHT, and the annual rolling county-level incidence at the end of 2012 were also obtained. The dataset was prepared using Microsoft SQL Server 2012 and extracted for cleaning and analysis using Stata 14 .Herds entered the study on the date of their first WHT in 2012. Herds with a positive test result at the first 2012 WHT, or an incident linked to this test, were excluded. The remaining herds were grouped into two cohorts: those with a clear test result at the 2012 WHT (“clear herds”) and those that had only IRs detected (“IR only herds”). The outcome was defined as a subsequent incident  during the follow-up period. Herds were censored either on the date of the test that disclosed an incident or at the end of the study period, whichever was earlier. Herds lost to follow-up due to the closure of the farm contributed time at risk until the date they were archived in Sam. Time was measured in days, but scaled up to years for the analysis.The hypothesis being tested was that the hazard of a subsequent incident is different between herds in which IRs have been detected and herds which test negative.Descriptive analyses were performed to examine the number of herds in each cohort (clear herds or IR only herds), and the number of incidents during the follow-up period. The median survival time in years for each cohort was estimated using the Kaplan-Meier method . Differep < 0.20 in univariable analyses were considered for inclusion in a multivariable model.Cox regression was used to examine the association between first WHT status in 2012 and the hazard of a subsequent incident. Other explanatory variables examined for an association with the hazard of a subsequent incident were herd type, herd size, the season in which the 2012 WHT took place, the number of incidents in the previous 10 years, geographical risk area and annual rolling county-level incidence at the end of 2012. These other explanatory variables were then individually added to a model with first WHT status in 2012 to assess whether they resulted in a change in the hazard ratio for the primary exposure. Herd size, the number of incidents in the previous 10 years and county-level incidence were analyzed as both continuous and categorical variables, and those that resulted in the greatest change in the hazard ratio for first WHT status in 2012 were used in the analysis. Efron's method for dealing with ties was used since there were a large number of tied events in the dataset due to the large number of herds and the resolution of the temporal unit (days). All variables associated with the hazard of a subsequent incident with a The multivariable analysis was performed in a stepwise manner with the variable first WHT status in 2012 (“clear” or “IR only”) forced into the model as the primary exposure variable. The outcome variable was occurrence of a subsequent incident. Confounders were then sequentially added to the model in a forward stepwise manner, starting with the variable that resulted in the greatest change in the hazard ratio for first WHT status in the univariable analysis. An interaction between herd type and location was considered. The likelihood ratio test and Akaike's Information Criterion (AIC) were used to compare models . Model fp < 0.05 was taken as evidence against the null hypothesis that the hazards were proportional. In addition, graphs of the scaled Schoenfeld residuals over time were plotted for each variable to look for nonlinear relationships between the residuals and time or influential outliers. Interactions between each of the variables and log time were assessed by extending the model to include time varying coefficients using the tvc command in Stata. Model fit could not be assessed using the Cox-snell and deviance residuals after the inclusion of the time-varying coefficients, so models were assessed using the likelihood ratio test and AIC.To test the assumption of proportional hazards, a log-minus-log survival plot was generated for first WHT status adjusted for variables included in the final model. The correlation between the Schoenfeld residuals of each variable and transformed time was assessed using the Chi-squared test. A An additional analysis was performed using the date of the first subsequent clear herd test after the first WHT as the entry date, thereby excluding herds that were disclosed as infected at the IR retest. The purpose of this was to try to remove the impact of the IR retesting and ensure that all herds were starting out on comparable testing regimes. The results of this analysis are presented in the p < 0.001)  tested negative (clear), and 3,311 (11%) only had IRs (IR only) at the first WHT in 2012. Overall, 30% of herds went on to have a subsequent incident within the follow-up period. A greater percentage of IR only herds went on to have a subsequent incident compared with clear herds (63 and 27% respectively) (Z-test to compare two proportions: Z-test to compare two proportions: p < 0.001). The median number of skin test reactors was lower among incidents disclosed by an IR retest than among incidents disclosed by other tests . However, the median numbers of IRs and reactors to the gamma interferon test was zero among incidents disclosed by an IR retest and among incidents disclosed by other tests.The percentage of herds that suffered a subsequent incident was greater among herds with three or more incidents in the 10 years prior to the 2012 WHT, dairy herds, and increased with herd size  that fell before the date of the first WHT in 2012 and they were not tested again within the follow-up period. This left 30,593 herds under observation. There were 9,326 herds with a subsequent incident, which occurred at a median follow-up time of 1.8 years (range: 0.02–4.9), while 21,267 herds were censored at a median follow-up time of 4.5 years (range: 0.03–5.5). There were 3,705 herds lost to follow-up because the business closed down. More clear herds were lost to follow-up (13.1%) than IR only herds (3.8%).The median survival time among IR only herds was over half that observed for clear herds. Median survival time was also reduced among herds with more than 200 animals, dairy herds, and herds with 3 or more incidents in the previous 10 years (Table p = 0.04).There was a difference in the survival functions of the clear and IR only cohorts Figure  and thisA Cox regression was performed to assess the hazard of a subsequent incident within the two cohorts. There were strong associations between each of the explanatory variables and the hazard of subsequent incidents in the univariable analysis Table . Factorsp < 0.05 for all variables except local incidence, indicating that the proportional hazards assumption had been violated. The log-minus-log plot illustrated a change in the ratio of hazards around 60 days, which correlated with the timing of IR retests. This indicated that an analysis of the time to a subsequent incident may not be appropriate given the differences in follow-up testing between the cohorts, and that time varying coefficients should be included to model interactions between the explanatory variables and time.The initial multivariable Cox regression model included first WHT status in 2012, herd size, the number of incidents in the 10 years before the first WHT in 2012, herd type, county-level TB incidence and geographical risk area. The plot of the Cox-Snell residuals Figure  indicateThe final extended Cox regression model contained first WHT status, herd size, recent history of TB, herd type, local incidence and geographical risk area, and included interactions between time and first WHT status, herd size, TB history, risk area and herd type. The relative hazard of having a subsequent incident was 2.7 times greater among herds that were IR only at the 2012 WHT compared with herds that had a clear test result  Table . The intUnderstanding the level of infection that could be present among IRs is important for directing control measures. In Ireland, Clegg et al.  found thThe number of incidents in the 10 years prior to the study was consistently associated with an increase in the hazard of a subsequent incident. This is in agreement with other studies where TB history has been identified as a risk factor for future incidents –17. HerdDairy herds located within areas subject to badger culling in England were shown to have a greater risk of TB than beef herds in the same areas . It has Increased county-level incidence was associated with an increased hazard of a subsequent incident, and herds in the edge area of England and in Wales had a reduced hazard compared with herds in the high risk area of England. Olea-Popelka et al.  and GreeThe TB testing regime in England and Wales is determined by factors such as location, animal movements and disease history. As such, it varies considerably between herds across both cohorts. However, there are also structural differences in the data due to the TB control policy. IRs have a subsequent test following disclosure of IRs, which does not take place in herds where all the cattle tested negative to the whole herd test. This increases the probability of IR-only herds having a subsequent incident compared with herds that tested clear, since increased testing increases the chances of detecting disease. This is further complicated by the fact that animals that have a second IR test result at the follow up test will automatically be classified as reactors. This means that there is a bias toward detecting cases within the IR only cohort. Unfortunately, the structure of the data did not allow the analysis of individual test data for each herd to explore the impact of this further. Instead, the time-varying coefficients were included to model how the relative hazard of a subsequent incident amongst IR only herds compared with clear herds varied over time. A reduction in the hazard ratio over time was observed, which indicates that the hazard for IR only herds becomes comparable to that of clear herds after around two and a half years. If the effect of re-testing was the only reason that IR only herds had a greater hazard of a subsequent incident, then we would expect the hazard ratio to reach 1.0 after the 60 days retest. The fact that it takes over 2 years to reach 1.0 suggests that the hazard of a subsequent TB incident is still higher among IR only herds than herds that tested negative to a whole herd test once the effect of re-testing has been removed.An additional analysis was performed to try to remove the impact of the IR re-testing by ensuring that all herds were starting out on comparable testing regimes, and the results of this analysis are presented in the There is potential for the misclassification of IRs due to the imperfect test for TB. The influence of disease prevalence on the predictive value of the test also introduces the potential for misclassification across risk areas. For example, the low positive predictive value of the test when prevalence is low means that IRs in the low-risk areas may be false positives, while the low negative predictive value of the test when prevalence is high means that IRs in high-risk areas may be false negatives. Even if perfect classification were possible, the nature of IRs is that their infection status is uncertain. They may be uninfected animals that have been exposed to other mycobacteria, or they may be infected animals that do not respond adequately to the test due to factors such as immunosuppression or co-infection . This unThe finding that the hazard of a subsequent incident reduces over time among IR only herds indicates that the policy in England and Wales for dealing with IRs is having an effect. However, these herds still appear to be at greater risk of having an incident after the IR re-testing regime. This could reflect that the testing is not removing all potentially infected animals from the herd, or there may be other factors which put these herds at a greater risk of having a TB incident that we have yet to understand. This is important information for both policy makers in England and Wales, and those in other countries looking to learn from the English and Welsh experience in tackling bovine TB. The evidence from this analysis suggests that the new policy decision in England, restricting IRs with a negative re-test to the herd in which they were detected for life, should help reduce any residual risk associated with an IR for disease spread. This approach has been implemented in Ireland since 2012  followinThe present study has shown that the hazard of a subsequent TB incident is greater among IR only herds than herds that tested negative to a whole herd test, and that the hazard ratio decreases over time, but remains greater than 1.0 after the IR re-testing regime. This emphasizes the importance of careful decision making around the management of IR animals and indicates that re-testing alone may not be sufficient to reduce the risk posed by IR only herds. Further characterisation of IRs is needed to determine whether the differences observed here are related to management or biological factors. This may be best achieved through an animal-level analysis so that the risk of retaining individual IR animals in a herd in England and Wales can be understood. Our findings correlate with the Irish findings, indicating that the risks of IRs are unlikely to be country and context specific. This provides further evidence of the risk that IRs pose for the spread of TB, which can support the development of policies in other countries relating to the management of IRs.LB designed the study, performed the analysis, and drafted the manuscript in part fulfillment of the requirements for the degree of Master of Science in Veterinary Epidemiology at the Royal Veterinary College, University of London. AP generated the dataset and edited the manuscript. DP and SD provided advice on study design and analysis, made additions to the text, and edited the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


It was found that the high flow stress corresponded to the low temperature and high strain rate, which showed DRX steady state curve during the hot compression. The hot deformation average activation was 263.17 kJ/mol, which was obtained by the analysis of the hyperbolic constitutive equation and the Zener-Hollomon parameter. From observation of the microstructure, it was found that kink deformation of long period stacking ordered (LPSO) phase was one of the important coordination mechanisms of hot deformation at low temperature. The processing map with the strain of 0.5 was established under the basis of dynamic material model (DMM); it described two high power dissipation domains: one appearing in the temperature range of 370–440 °C and the strain rate range of 0.001–0.006 s−1, the other appearing in the temperature range of 465–500 °C and strain rate range of 0.001–0.05 s−1, in which dynamic recrystallization (DRX) mainly ocurred. The highest degree of DRX was 18% from the observation of the metallographic.Mg-Gd-Y-Zn-Zr Mg alloys show excellent performance in high-end manufacturing due to its strength, hardness and corrosion resistance. However, the hot deformation and dynamic recrystallization (DRX) behaviors of Mg-13.5Gd-3.2Y-2.3Zn-0.5Zr were not studied. For this article, hot compression behavior of homogenized high rare-earth (RE) content Mg-13.5Gd-3.2Y-2.3Zn-0.5Zr (wt%) alloy was investigated by using the Gleeble-3500D thermo-simulation test machine under the temperature of 350–500 °C and the strain rate of 0.001–1 s The requirements of lightweight structure and energy saving make magnesium alloy become the material selection direction of many important structural parts at present; however, the restriction of poor mechanical properties, especially the high temperature performance, affect the development of traditional magnesium alloys ,2,3.97Zn1Y2 alloy was studied by Matsuda et al. [The alloys of Mg-Gd-Y system, which is famous for its low density, good corrosion resistance and excellent performance at both ambient temperature and elevated temperature, received more and more attention in automobile applications ,5. In pra et al. , and it a et al. ,15,16.Processing map can effectively describe the hot plastic deformation workability and determine the most reasonable thermal processing parameters, which are important to the hard deformation materials . HoweverIn previous work, the microstructures with LPSO phase analysis were the key points, and mechanical properties of Mg-Gd-Y-Zn-Zr magnesium alloys have also been reported seriously ,19,20. HDMM  processing map is often used to describe the relationship between deformation parameters, microstructure and hot workability during hot deformation ,22,23. Tm alloys ,26,27. Tσ and the strain rate stress K” is the material constant and m is the strain rate sensitivity index. According to the theory of DMM, the thermal deformation material is regarded as a nonlinear energy dissipation unit. During hot deformation, the total dissipated power, P, is converted into two parts, one is the power G consumed by plastic deformation, most of which is transformed into viscoplastic energy, and a small part is stored in the form of crystal distortion energy; the other is the power J consumed by microstructural evolution, such as dynamic recovery (DRV), and DRX etc. Therefore, the total dissipated power is written as follows:The flow stress perature . The folG and J is determined by the index m which is sensitive to the strain rate:The proportion of dissipative power between J as follows:Bring Equation (3) into Equation (2) and get the dissipation power J reaches the maximum value when m = 1.Assuming that the material is in ideal linear dissipation, η, can be written as follows:Define . Prasad  considerThe magnesium alloy of Mg-13.5Gd-3.2Y-2.3Zn-0.5Zr (wt%) with 420 mm in diameter was casted by semi-continuous casting. Then, cylindrical samples with the size of Φ8 mm × 12 mm were machined from the Mg alloy ingot. The eutectic phase transition temperature of the as-cast magnesium alloy was calculated to be 523 °C  and graphite sheet were used as lubricant before compression and placed between the indenter and the sample, which was used to reduce the deformation friction  with the parameter of diffraction angle from 25° to 85° and scanning speed of 5°/min. Then, the microstructures of the compressed specimens were observed by optical microscope  with the magnification range of 50–500. The scanning electron microscopy  was used to observed the phase morphology with the voltage of 20 kV. Meanwhile, the energy dispersive X-ray spectrometer  and electron backscattered diffraction  were operated to define the phase atomic ratio and grain orientation at 20 kV, title angle of 70°, and working distance of 15 mm. Last, the EBSD data were processed by the TSL OIM software .12RE1Zn1 and Mg5 are the constituent of the target Mg alloy. 12RE1Zn1. In addition, the chemical equation of the bright phase 3# is Mg-11.35Gd-4.32Y-2.10Zn and the stoichiometry is close to Mg5. In the previous work, the approximate chemical composition of 14H LPSO structure in Mg96.5ZnlGd2.5 alloy is Mg-11Zn-8Gd (at.%), and its Zn/Gd atom ratio is about 1.17:1 [5 phases and the increase of Mg12RE1Zn1.The initial microstructure, as-homogenized microstructure and the XRD patterns of Mg-13.5Gd-3.2Y-2.3Zn-0.5Zr alloy are depicted in t 1.17:1 ,30. At lThe variations of stress with strain of the homogenized alloys at the temperatures of 350 °C, 400 °C, 450 °C and 500 °C and strain rates 0.001/s, 0.01/s, 0.1/s and 1/s are presented in The hot deformation microstructures are illustrated in According to the comparison of Microstructure of the compressed specimens at the temperature of 450 °C is shown in For investigating the hot workability behavior of Mg-13.5Gd-3.2Y-2.3Zn-0.5Zr alloy, it is significant to study the constitution equation , which iThe deformation of metal materials at high temperatures is a process determined by thermal activation, satisfying the Arrhenius Equation :(8)ε˙==Aσ at low stress level (ασ < 0.8), high stress level (ασ > 1.2) and the whole stress range can be expressed as follows [Q is the DRX activation energy (kJ/mol), T is the absolute temperature (K), R is gas constant (8.314 J/mol·K) and A , α, β and n are the general constants that are related to the materials, with α = β/n1 [σ is the peak stress or steady stress (MPa).The relationship between strain rate  follows :(9)ε˙=Aσα = β/n1  and σ isThe logarithm of Equation (9) and Equation (10) can be obtained as follows:n and β, respectively. The calculating data can be obtained by the slope of the curves in n1 = 7.954 and β = 0.075, respectively, so Q is influenced by deformation parameters such as temperature and strain rate. The dislocation density increases with the strain increasing and the work hardening makes the deformation difficult, so the greater activation energy is needed. While at a high temperature, the dislocation is easy to slip and climb and the dynamic recrystallization is produced which makes the activation energy reduce accordingly. When the strain is high, the dislocation density increases rapidly and the dynamic recrystallization is low, so the slip of the dislocation requires a larger deformation activation energy. The average linear slope of Q = 263.17 kJ/mol.shown in c is 5.60The larger the activation energy, the more difficult the deformation is; the dynamic precipitation , pinningZ) [Thermal deformation conditions are usually described by temperature compensated Zener-Hollomon (Z) .(13)Z=εσ and Z is as follows:According to the definition of hyperbolic sine function, it can be seen that the relation between Q can be obtained as follows:From Equation (16), the deformation activation energy n and A can be calculated as 3.897 × 1017 s−1. The constitutive equation of the homogenized Mg-13.5Gd-3.2Y-2.3Zn-0.5Zr alloy can be obtained as follows:α, n and Q to Equation (16), the constitutive equation of homogenized Mg-13.5Gd-3.2Y-2.3Zn-0.5Zr alloy at elevated temperature can be expressed by:Furthermore, substitute the value of −1) and domainII (465–500 °C/0.001–0.05 s−1) with the value of about 44%.−1 is the optimum stable parameter for homogenized Mg-Gd-Y-Zn-Zr alloy.Based on the discussion above, both stability and instability domains are shown in −1. The black regions represent the block-shaped LPSO phases without the sufficient confidence index (CI) and the blue regions shown in −1 a considerable one.−1. Based on true stress-strain curves, the constitutive equation, the processing map, and deformation of RUE to verify the parameters, the conclusions are as follows:(1)The homogenized alloy exhibits the typical dynamic recrystallization behavior characteristics. The flow stress increases with the decrease of temperature and the increase of strain rate. Meanwhile, the true stress-strain curves tell that the high strain rate and low temperature make a high work hardening rate.(2)The constitutive equation of the homogenized alloy is (3)LPSO kink deformation becomes an important mean to coordinate deformation when it is difficult to start the sliding system of magnesium alloy during deformation at low temperature. From the further observation of the microstructure evolution, the DRX softening enhances with the increase of temperature which makes the slip system easy to slide. Meanwhile, the flow instability and the stress concentration become serious and the micro-cracks are produced at the intersection of kinks where the lump LPSO phases gather.(4)−1 and 465–500 °C/0.001–0.05 s−1, respectively, which correspond to the peak power dissipation of 44%. From the observation of compressed specimens, the optimum condition for hot plastic deformation is 465–500 °C/0.001–0.05 s−1.According to the processing map, dynamic recrystallization behavior with the strain of 0.5 occurs at two high power dissipation zones: 370–440 °C/0.001–0.006 sIn this research, the hot deformation behavior of homogenized Mg-13.5Gd-3.2Y-2.3Zn-0.5Zr alloy via hot compression tests has been studied at the temperature from 350 °C to 500 °C and the strain rate range of 0.001–1 s


CDK5, an atypical member of the CDK family, play a significant role in the tumorigenesis of multiple organ, but CDK5 and its substrates in genesis and development of HCC is still unclear.Expression of CDK5 in HCC tumor and paired adjacent noncancerous tissues from 90 patients were measured by Western blotting, immunohistochemistry, and real-time PCR. The role of CDK5 in cell function and tumorigenesis was explored in HCC cell lines, ex vivo xenografts and diethylnitrosamine induced HCC model. Furthermore, comparative phosphoproteomic screening identified the oncoprotein TPX2 as a new substrate of CDK5. We also identified the effect of CDK5/P25 interaction blocker tamoxifen on HCC cell growth and migration.CDK5 was increased in HCC tisues and the level of CDK5 was correlated with the severity of HCC based on patient recurrence and 5-year fatality rate. Exogenously expressed CDK5 but not kinase-dead CDK5 promoted proliferation, migration, and invasion of HCC cells. Functional ablation of CDK5 significantly inhibited the exacerbation of HCC cells. Xenograft implantation of HCC cells overexpressing CDK5 promoted tumorigenesis, and genetic knockdown of CDK5 reduced HCC growth and metastasis in vivo. More importantly, heterozygous knockout CDK5 (Cdk5+/−) attenuated HCC tumorigenesis induced by diethylnitrosamine. CDK5-mediated phosphorylation of TPX2 at serine 486 promoted its protein stability. TPX2 silence could restore HCC cell migration capability with overexpression CDK5. Treatment with tamoxifen inhibited cell growth and migration of HCC, demonstrating the role of active CDK5 in HCC.Our results suggest activation of CDK5 is associated with HCC tumorigenesis. CDK5-mediated phosphorylation and stabilization of TPX2 promotes hepatocellular proliferation and tumorigenicity.The online version of this article (10.1186/s13046-019-1297-6) contains supplementary material, which is available to authorized users. Hepatocellular carcinoma (HCC), with more than 700,000 new cases annually, is the third most common cause for cancer death worldwide , 2. DespAbnormal expression and activation of cyclin-dependent kinases (CDKs) contribute to tumorigenesis of certain types of cancers , 5. AmonIn this study, we found that the expression of CDK5 was significantly increased in HCC and that enhanced CDK5 expression was directly correlated with decreased survival, higher tumor recurrence, and vascular invasion. We then demonstrated that CDK5 promoted HCC progression of HCC in vitro and in vivo by xenograft implantation or diethylnitrosamine (DEN)-induced HCC tumorigenesis models. Mechanistic investigation indicated that CDK5 phosphorylates and stabilizes TPX2 to promote HCC. Since CDK5 activity is vital for hepatocellular carcinoma tumorigenesis, drugs that target CDK5 kinase activity may be a potential curative treatment for HCC. Tamoxifen (TMX), which is an endocrine treatment for breast cancer, has been reported as a new inhibitor of CDK5 kinase activity by interrupting the association between CDK5 and its activator p35/p25 . The admAntibodies against CDK5 (C-8), p35 (C-19), and TPX2 were purchased from Santa Cruz Biotechnology . Anti-β-actin, anti-GFP, anti-Rb, and pRb-Ser807/Ser811 antibodies were obtained from Cell Signaling Technology . Anti-ki67 antibodies and the CDK5 inhibitor roscovitine were acquired from Genetex and Cell Signaling Technology, respectively. TMX was purchased from Sigma. Lentivirus of CMV-EGFP-3FLAG-CDK5, CMV-EGFP-3FLAG-kinase-dead-CDK5, and control were obtained from Neuron Biotech (Shanghai). TPX2 was amplified by PCR and inserted into GFP-C3 to generate GFP-C3-TPX2 vector. GFP-TPX2-S486A and GFP-TPX2-S486D mutations were generated using a site-directed mutagenesis kit following the instruction manual (Stratagene).Human liver tumor tissues and respective adjacent non-tumor tissues of 90 patients with detailed pathological data and follow-up information were obtained from Zhongshan Hospital of Xiamen University. All samples were collected by hepatectomy from 2010 to 2013. This study was approved by the ethics committee of Zhongshan Hospital of Xiamen University, and written consent was obtained from all patients involved.Paraffin-embedded tissue sections (10-μM thick) were immunostained. The tissue sections in paraffin were rehydrated through incubations in xylene and then an alcohol gradient from 100 to 70%. The antigen was retrieved by heating in boiling temperature for 10 min using citrate antigen retrieval solution. The primary antibodies were incubated at 4 °C overnight. CDK5 (Santa Cruz) was used at 1:150. CDK5 was incubated with secondary goat antirabbit IgG (Life Technologies) at room temperature for 1 h and then washed three times with PBS. All slides were analyzed by two individuals trained in IHC, and interpretations were confirmed by a pathologist. Briefly, the CDK5 immunoreactivity score was determined by multiplying the CDK5 staining intensity  and the percentage of Cdk5-positive cells . The result was considered positive when the product of the two scores was more than 4.2 in DMEM supplemented with 10% heat-inactivated FBS and Pen/Strep.Human HCC cell lines HepG2, Hep3B, sk-Hep1, QGY7701, SMMC7721, Huh7, MHCC97h, and LM3 were purchased from Shanghai Cell Bank . All cells were cultured at 37 °C in a humidified atmosphere of 5% COTo generate CDK5 knockdown stable cell lines, a target set of shRNA sequences directed against human CDK5 was used. Cells were transfected with DNA constructs by TurboFect (Invitrogen) according to the manufacturer’s protocol and were selected with the corresponding antibiotic puromycin at 1 μg/mL (Sigma) 48 h after transfection.For the construction of CDK5 overexpression stable clones, EGFP-WT-CDK5 and a dominant-negative CDK5 containing a D144N mutation were created using PCR. Two hundred ninety three T-packaging cells were used for lentivirus production. The supernatant containing lentivirus was harvested to transducer and Huh7 cell lines. Resistant clones were selected in the presence of puromycin at 1 μg/mL (Sigma).Harvested cells were homogenized in ice-cold NP-40 lysis buffer with protease inhibitor mix. The samples were centrifuged at 12,000×g for 12 min at 4 °C. The supernatant was collected and total protein levels were measured using the micro BCA protein assay kit (Thermo Fisher Scientific). For western blotting, the lysates were separated with SDS-PAGE and electrophoretically transferred onto nitrocellulose membranes. The membranes were blocked with 5% nonfat milk in TBST and probed with primary antibodies overnight, followed by treatment with secondary antibodies and ECL western blotting detection reagents. For immunoprecipitation, the cell lysates were incubated with corresponding antibody at 4 °C for 4 h, followed by overnight incubation with protein G. The beads were washed five times with ice-cold NP-40 lysis buffer, and the bound proteins were analyzed using SDS-PAGE and immunoblotting analysis.3 cells per well) and cultured for 14 days. Subsequently, the cells were fixed with absolute ethyl alcohol for 15 min and stained with 1.0% crystal violet for 10 min. The number of colonies formed was counted in 10 different fields. 1.0 × 105 cells were seeded into 24-well plate. The cells were divided into 7 groups, each group 3 wells, cultured for one week. Then collected and counted the number of cells of each group daily. The number of cells in 7 days was plotted as cell growth curve to determine the absolute cell growth rate. The stable transfected SMMC-7721 cells (shRNA and control) were starved for 24 h in serum-free media, and 2 × 105 cells were plated into the upper chamber with 8-mm pores . DMEM containing 10% FBS was placed in the lower chamber. For migration assay, cells were stained with crystal violet (Sigma) after incubation for 24 h. For invasion assay, the upper chambers were coated with Matrigel (BD Biosciences) and stained after 48 h. A total of 5 fields were counted for each filter. The experiments were performed three times independently.Cells were seeded into 6-cm tissue culture dishes  was added into the media for the indicated times. The cells were harvested and subjected to immunoblot analysis with antibodies against TPX2, Cdk5, and GAPDH. HEK293T cells transfected with GFP-TPX2-WT, GFP-TPX2-S496A, and GFP-TPX2-S486D were treated with CHX (100 μg/mL) and subjected to immunoblot analysis with antibodies against GFP and GAPDH.6) were subcutaneously injected into the right flanks of 6-week-old male nude mice. Huh7 cells infected with Cdk5 lentivirus and selected with puromycin were injected into nude mice as the above method. The diameters of tumors were measured every 4 days using calipers. Mice were sacrificed 60 days after injection or when tumor reached a static size. The tumors were weighed and statistically analyzed, and the livers were collected.Cdk5 stable knockdown SMMC7721 cells and control cells . Mice were sacrificed after 9 to 10 months, and tumors larger than 1 mm in diameter on the liver surface were counted. Tumors larger than 5 mm across were dissected for biochemical and molecular analyses. All animal procedures in this study were approved by the Institutional Animal Care and Use Committee of Xiamen University.Cdk5 heterozygous knockout mice (cdk5 +/−) and wild-type mice of 8–10 weeks of age were subjected to a 2/3 partial hepatectomy (PH). The procedure was performed as described previously . Mice weE. coli by affinity chromatography. A substrate (1 μg) was added into kinase assay buffer (CST) containing 25 mM Tris-HCl (pH 7.5), 2 mM dithiothreitol (DTT), 5 mM beta-glycerophosphate, 0.1 mM Na3VO4, and 10 mM MgCl2, and incubated with CDK5/p25 kinase and 50 μM ATP-γ-S at 30 °C for 45 min. The samples were alkylated with 2.5 mM PNBM/5% DMSO (Abcam), incubated at room temperature for 1 h, and then subjected to western blotting. Phosphorylated proteins were immunoblotted with an anti-thiophosphate ester antibody.Recombinant GST-TPX2 and GST-TPX2 (S486A) proteins, as well as GST tag protein, were purified from P < 0.05. The different degrees of significance were indicated as follows in the bar graphs: *P < 0.05; **P < 0.01; ***P < 0.001.Clinical parameters were analyzed using the chi-square test. Survival analysis was performed using the Kaplan-Meier method. Student’s t-test or one-way ANOVA was used to determine statistically significant difference between groups. All data were expressed as mean ± SD. Results between groups were considered significant at We examined CDK5 protein levels in HCC tumors and paired adjacent noncancerous tissues from 66 patients by western blotting. We observed that HCC tumor tissues expressed significantly higher levels of CDK5 compared with noncancerous tissues in the majority of patients  were treated with DEN injection. HE staining indicated HCC tumorigenesis in DEN-induced mice  to screen substrates of CDK5 in tumor cells. The oncoprotein TPX2 –27, a keOur previous study showed that CDK5 is related to HCC cell proliferation, migration and invasion, but its mechanism and downstream targets remain unclear. TPX2 has been reported to correlate with tumor migration and invasion , 29. As TPX2 was also upregulated in tumors derived from xenograft by CDK5 overexpression stable HCC Huh7 cells  transgenic mice with DEN-induced tumor model. A decreased tumor number and size were found in Cdk5-deficient mice, which proved our hypothesis in vivo. Furthermore, to eliminate other pathways of CDK5 in cell proliferation, such as cell cycle and DNA damage, chemotherapy and radiation treatment of HCC cells were performed. We found that there was no change of CDK5 expression in HCC cells after radiation treatment. Meanwhile, the inhibition effect of cell proliferation by chemotherapy and radiation treatment was not related to CDK5 expression Additional file 2:Figure S2. CDK5 is associated with HCC cell migration. a The ability of cell motility was compared in shcon and shcdk5 cells by wound healing assay; Light microscopicimages were taken at 0, 24, 72 and 96 h. b Wound-healing assays were performed in GFP,GFP-Cdk5, GFP-CDK5-KD Huh7 cells; Light microscopicimages were taken at 0, 24, 72 and 96 h. (TIF 8749 kb)Additional file 3:Figure S3. HCC cell proliferation and migration were inhibited by roscovitine. a Colony formation assay inSMMC-7721 cells treated with roscovitine concentration gradient of 10 μmol/l,30 μmol/l,50 μmol/l; One Way ANOVA on Ranks:ns-no statistical differences,***p < 0.001, n = 3. b migration (24 h) assays in SMMC-7721 cells after treatment of roscovitine ;One Way ANOVA on Ranks: ***p < 0.001, n = 5. c Protein levels of TPX2 and p-RB in SMMC-7721 cells after treatment of concentration gradient roscovitine; The average of relative TPX2 protein levels are presented in the right panel. (TIF 15418 kb)Additional file 4:Figure S4. CDK5 has no effect on radiation and chemotherapy induced HCC cell death. a Inhibiton effect of oxaliplatin (40 mg/l) in shcon and shcdk5 SMMC-7721 cells by CCK8 assay. b Inhibiton effect of arsenic trioxide  in shcon and shcdk5 SMMC-7721 cells by CCK8 assay. c PARP and Cdk5 protein levels were measured in SMMC-7721 cells after radiation treatment of 6Gy. d-e CCK8 assays in shcdk5 and Cdk5 over-expressed cells compared with control cells after radiation treatment of 6Gy. f Colony formation assay after radiation treatment in shcon and shcdk5 SMMC-7721 cells. (TIF 11506 kb)Additional file 5:Figure S5. CDK5 inhibitor reduces TPX2 protein level. a Treatment of SMMC-7721 and Huh7 cells with tamoxifen by concentration gradient, TPX2 and Cdk5 protein levels were measured by Immunoblotting,TPX2 protein levels arepresented in the right panel.b Similar to a, SMMC-7721 and Huh7 cells were treated with roscovitine by concentration gradient, TPX2 andp-Rb protein levels were measured by Immunoblotting, TPX2 protein levels arepresented in the right panel. (TIF 12532 kb)Additional file 6:Figure S6. Cell counting assay in Huh7 cells transfected with CMV + sicon, CMV + sitpx2, Cdk5 + sicon, Cdk5+ sitpx2, One Way ANOVA on Ranks,*P < 0.05; **P < 0.01;***P < 0.001. (TIF 32 kb)


Protein-protein interactions (PPIs) play a crucial role in various biological processes. To better comprehend the pathogenesis and treatments of various diseases, it is necessary to learn the detail of these interactions. However, the current experimental method still has many false-positive and false-negative problems. Computational prediction of protein-protein interaction has become a more important prediction method which can overcome the obstacles of the experimental method. In this work, we proposed a novel computational domain-based method for PPI prediction, and an SVM model for the prediction was built based on the physicochemical property of the domain. The outcomes of SVM and the domain-domain score were used to construct the prediction model for protein-protein interaction. The predicted results demonstrated the domain-based research can enhance the ability to predict protein interactions. Protein commonly consists of one or more submolecule parts, which are termed as domain. Domain is a structural or functional module of protein, and it is usually evolutionarily conserved units. Differential association of domains provides a way to create new functions for organisms . The intDomain-based prediction has provided a new perspective for the study of protein-protein interactions (PPIs). PPIs play a crucial role in biological processes, including immune response, signal transduction, and the occurrence and development of disease. Usually, there are two methods predicting protein-protein interactions, experimental method and computational method. Experimental techniques identifying protein-protein interactions are the earliest research methods, including yeast two-hybrid (Y2H) , tandem Escherichia coli [Wojcik and Schachter have developed an interacted domain pair profile method to predict protein-protein interactions. They applied their method to predict an interaction map of hia coli . Kim et hia coli . Hayashihia coli . Kamada hia coli . Singhalhia coli . Zhang ehia coli .Currently, the features that domain-based methods used just contain the domain co-occurrence relationships or the proportion of an important domain. The domain information is not completely considered. The domain interactions, which are crucial to the understanding of biomolecule interactions, also provide a global view of the protein-protein interaction network. In order to effectively utilize the information of the domain, we proposed a new domain-based method to predict protein-protein interactions.In this paper, we both considered the physicochemical property of domain and the domain-domain interaction score. The physicochemical property of domain was used as the SVM feature to construct the DDI prediction model. Finally, the DDI prediction model is combined with the domain-domain interaction score to construct the PPI prediction model.The flow chart of our method is given in http://www.adhesome.org/) [The positive protein-protein interaction data were collected from the interacting adhesome protein-protein. It can be obtained on the website of The Adhesome: A Focal Adhesion Network (me.org/) , 28. Xiame.org/) , was useme.org/) , 31.http://pfam.xfam.org/). We constructed the corresponding domain-domain pairs. Meanwhile, interacting and noninteracting domain pairs were chosen in the InterDom database (interacting domains http://interdom.lit.ofg.sg/) and 3did database (https://3did.irbbarcelona.org/index.php). The InterDom database had a set of confidence scores of DDIs which used 1.5 as the cutoff of false-positive and nonfalse-positive prediction [We used the protein database mentioned above as our source database to extract the domain of its protein. The domains of protein and sequence information of these domains were obtained from the Pfam database  and ProtComp (https://www.expasy.org/). ProtParam can calculate various physicochemical parameters for a given protein [http://www.softberry.com/berry.phtml?group=programs&subgroup=proloc&topic=protcompan). Thelocation of a protein in a cell has a close relationship to its biological function [The physicochemical property of domain pairs was used as features of our method. The domain and the corresponding sequence information were downloaded from the Pfam database. According to the sequence information of the domain, the physicochemical property of the domain can be obtained with the online tools ProtParam  is the usual technique for classification and regression , 36. In http://www.csie.ntu.edu.tw/∼cjlin/libsvm/) was employed in this work.The software libsvm 3.23 , sensitivity (SN), specificity (SPE), precision (Pre), Matthews correlation coefficient (MCC), and This section is divided into four parts: the first part is the intermediate result of the prediction of the domain-domain interaction, the second part is the result of protein prediction, the third part is the comparison of different methods, and the last part is the limitations of our model.We used the physicochemical property of domain to build the SVM prediction model. To evaluate the robustness of our method and to reduce impact of data independence, fivefold cross validation was used to ensure the reliability of the results. The SVM calculation was run five times. The result of domain-domain interaction prediction is shown in F1 and MCC, can better evaluate the overall performance of the classifier. The average value of F1 was 94.54%, and the MCC was 89.39%. These results show that the domain's physicochemical properties are effective feature information for domain-domain interaction.From λmn represented the Interdom score of m domain and n domain pair and the Smax represented the maximum score of domain-domain in our database.  Pij represented the DDI-predicted label results, which was a probability score that the interacting domain-domain we predicted to the total theoretical domain pairs in a protein pair.  Pij was defined by using the following equation:The domain-domain interaction score in the Interdom database and DDI predicted label results were used to build a protein-protein prediction model. In order to reduce the numerical difference between the domain-domain score, the value was obtained by the following algorithm:Num_predicted was the number of predicted domain pairs with our model for one certain protein pair. Num_DDI was the theoretical number of all domain-domain pairs in the same protein pair.In this section, we assumed that domain-domain interactions were independent . We estiN ∗ N is used to find the optimal parameters A and B. We set the value of N from 0 to 0.6 by 0.1. A total of 49 uniform lattices trained the protein sets. In order to evaluate the results of the training, we set ten thresholds from 0.1 to 0.55, with an interval of 0.05. The values of TP, TN, FP, FN, the false negative rate (fn), the false positive rate (fp), ACC, and SN were calculated. These evaluation indexes are described in detail in Grid algorithm The results of protein-protein interacting possibility were compared by the accuracy and ROC curves with AUC scores. Finally, the parameters A and B with high accuracy and large ACU area were selected. The final equation was as follows:In order to select the optimal threshold, we used formula  to trainX-axis represented different thresholds, and the Y-axis represented the values of fn and fp. The suitable threshold was determined according to two principles: (1) fn and fp should be as small as possible and (2) fn and fp should be as equal as possible. Therefore, we chose 0.26 as the optimal threshold. To obtain a more accurate threshold, we calculated the protein training results of three thresholds that are 0.25, 0.26, and 0.27. We also calculated the AUC (the area under the ROC curve). The results showed the same result in The To demonstrate the prediction performance, we compared our method with other SVM-based methods. In order to compare more accurately, we chose the different studies which not only used Pan's database but also used SVM classifier. The results are shown in As shown in Although the accuracy of our method is acceptable, there are still some limitations for our model to be used widely. For example, the number of our dataset and the physiochemical property are small, and in future work, we plan to test our model on a bigger dataset with more features. For our approach, independent software and online tools development work are still in progress.In this paper, we proposed a new domain-based method to predict protein-protein interaction. We used the domain's physicochemical property and interaction score to construct the protein interaction-predicting model. The predicted result, which achieved a good performance, indicates that our method is relatively successful. The physicochemical property of the domain as features for PPI prediction is of great significance. Applying our approach to large dataset and finding more effective feature information for predicting PPI will be part of our future work. Furthermore, our methods can be used for the prediction of new PPIs, and the result could provide some reference significance for dealing with related bioinformatics problems.


Plant LTR-retrotransposons are classified into two superfamilies, Ty1/copia and Ty3/gypsy. They are further divided into an enormous number of families which are, due to the high diversity of their nucleotide sequences, usually specific to a single or a group of closely related species. Previous attempts to group these families into broader categories reflecting their phylogenetic relationships were limited either to analyzing a narrow range of plant species or to analyzing a small numbers of elements. Furthermore, there is no reference database that allows for similarity based classification of LTR-retrotransposons.We have assembled a database of retrotransposon encoded polyprotein domains sequences extracted from 5410 Ty1/copia elements and 8453 Ty3/gypsy elements sampled from 80 species representing major groups of green plants (Viridiplantae). Phylogenetic analysis of the three most conserved polyprotein domains  led to dividing Ty1/copia and Ty3/gypsy retrotransposons into 16 and 14 lineages respectively. We also characterized various features of LTR-retrotransposon sequences including additional polyprotein domains, extra open reading frames and primer binding sites, and found that the occurrence and/or type of these features correlates with phylogenies inferred from the three protein domains.https://repeatexplorer-elixir.cerit-sc.cz/) or using a standalone version of REXdb that can be downloaded seaparately from RepeatExplorer web page (http://repeatexplorer.org/).We have established an improved classification system applicable to LTR-retrotransposons from a wide range of plant species. This system reflects phylogenetic relationships as well as distinct sequence and structural features of the elements. A comprehensive database of retrotransposon protein domains (REXdb) that reflects this classification provides a reference for efficient and unified annotation of LTR-retrotransposons in plant genomes. Access to REXdb related tools is implemented in the RepeatExplorer web server (The online version of this article (10.1186/s13100-018-0144-1) contains supplementary material, which is available to authorized users. Long terminal repeats (LTR) retrotransposons are a very large and diverse group of transposable elements that are ubiquitous in eukaryotes. They are particularly abundant in plant genomes, making up to 75% of nuclear DNA . LTR-retPseudoviridae in the ICTV classification of viruses), Ty3/gypsy (Metaviridae), Bel-Pao (Belpaoviridae), retroviruses (Retroviridae) and endogenous retroviruses  [At present, LTR-retrotransposon are often classified only to superfamily level (the broadest category of LTR-retrotransposon classification), that includes Ty1/copia  –14. Onlyviridae) , 15) havviridae) –18. TherIn spite of the high diversity of their nucleotide sequences, the overall structure of LTR-retrotransposons is highly conserved. A common feature of LTR-retrotransposons is the presence of two direct repeats flanking the central region of the element (these repeats are the 5′ LTR and 3′ LTR). LTRs include sites for transcription initiation and termination and are crucial for element replication. Most LTR-retrotransposons have a primer binding site (PBS) downstream of the 5′ LTR and a polypurine tract upstream of the 3′ LTR. Upon integration LTR-retrotransposons create a target site duplication (TSD) with a characteristic length specific to each family. Intact autonomous elements encode a polyprotein that has at least five protein domains: GAG, protease (PROT), reverse transcriptase (RT), ribonuclease H (RH) and integrase (INT). Cleavage of this polyprotein by PROT domain activity releases separate mature proteins that are necessary for replication and for integration of new retroelement copies into the genome. Some of these protein sequences were found to be sufficiently conserved among all elements within Ty1/copia and Ty3/gypsy superfamilies to use them for phylogenetic analysis –23. ThisArabiopsis thaliana, and classified these into six ancient lineages   and, if Based on the sequence similarity and protein domain order in putative polyprotein sequences, 5410 were classified as Ty1/copia (with the domain order GAG-PROT-INT-RT-RH) and 8453 as Ty3/gypsy (GAG-PROT-RT-RH-INT). In nearly all polyprotein sequences we identified PROT, INT, RT and RH domains  the eORF protein sequences found in Ty1/copia and Ty3/gypsy elements could be divided into 45 and 314 groups, respectively. Only 21.4% of the eORF protein sequences had similarity to various domain types in CDD , the presence, position and orientation of eORFs, and the type of PBS Figs. , 5 and 6Regardless of the type of protein domain and analysis method, Ty3/gypsy phylogenetic trees always included two major lineages we designated as chromovirus and non-chromovirus Fig. , 5 and 6Chromoviruses were classified into six clades named Chlamyvir, Tcn1, Tekay, Reina, Galadriel and CRM, these names match to groups described in previous studies –29, 31 . These cPhyscomitrella patens and Selaginella moellendorffii that were designated Phygy and Selgy respectively  and two species specific clades from ely Fig.  and 5. TPhylogenetic trees inferred from the alignment of INT, RT, RH and concatenated INT-RT-RH domains displayed several discrepancies in their topologies, making it difficult to reconstruct a Ty1/copia phylogeny in plants Fig. . The disIn spite of the discrepancies described above, Ty1/copia retrotransposons could be divided into groups combining elements that clustered together in trees calculated from different protein domains Fig. . PBSs coAll 75,516 polyprotein domain sequences identified in this study were associated with element classification information and used to create a database primarily designed for use within the RepeatExplorer pipeline , 55, henLTR-retrotransposons are likely to have been present in Viridiplantae genomes since their origin approximately 700–1500 million years ago , 57. SucThe hierarchical classification of Ty3/gypsy retrotransposons proposed in this study was supported not only by the phylogenies inferred from the analysis of three polyprotein domains but also by a combination of features characteristic of individual clades. These results are consistent with partial phylogenies in previously published studies Table . On the Although LTR-retrotransposons were primarily classified based on the phylogeny of RT, RH and INT domains, certain sequence and structural features were highly characteristic of some groups of elements. These features are not only classification criteria but also reflect important biological distinctions between individual groups of elements.Chromodomains were found in 94% of chromoviruses but none were found in any other group of LTR-retrotransposons included in this study, suggesting that the presence of this domain can be considered a highly reliable classification feature. Chromodomains are assumed to provide chromoviruses with targeting preferences , 48, 49 The presence of two RH domains is a unique feature of the Tat lineage. Like all other LTR-retrotransposons Tat elements possess an RH domain following the RT domain but they also have an additional RH domain, referred to as aRH, which occur in the polyprotein at three different positions Figs. .Large proportions of elements in some lineages of LTR-retrotransposons were found to possess eORFs, however, unlike the polyprotein, putative protein sequences of these eORFs were highly divergent and possessed no conserved domains common to most elements of the same lineage. For example, although 74% of SIRE elements possessed eORF-3’F, the putative protein sequences could be divided into 19 groups that share no or very little mutual similarity . This suggests that these eORFs either evolved very fast or have been acquired independently from different sources, raising the question whether they have any function. Although the applicability of protein sequences encoded by the eORFs for classification of LTR-retrotransposons is limited, some of them do posses domains that are specific for a significant proportion of elements of given lineage. The most prominent of these are the plant mobile domain (pfam10536), Transposase_28 (pfam04195) and Athila ORF-1 (pfam03078) that were found in 57, 23 and 16% of Ogre, Retand and Athila elements respectively . In oformans , 21 theiIn this study we showed that, despite their enormous DNA diversity, plant LTR-retrotransposons can be reliably classified using phylogenetic approaches into a small number of groups. Our proposed classification relies on phylogenetic analysis of the RT, RH, and INT domain sequences but in many cases is strongly supported by structural and sequence features. These include the presence and position of extra domains in the polyprotein, presence, position and orientation of eORFs, and the types of PBS. These features reflect biologically important distinctions among individual groups of elements and emphasize the need for the more detailed classification. Our database of protein domain sequences from classified elements is the most comprehensive dataset of its kind, representing a suitable reference for a unified classification of LTR-retrotransposons in plants. Since the database has a simple structure and is open for use and improvements by the scientific community we expect it to be continuously developed as new sequence data, especially from under-represented taxa of non-seed plants, becomes available.Genomic DNA sequence data were downloaded from Phytozome  and DendProtein domains were identified using iterative searches for similarity to our in-house database of protein domains and to protein domain sequences deposited in conserved domain database  and exaMultiple sequence alignments were calculated using muscle  and editAdditional file 1:Information about LTR-retrotransposon sequences included in the study. (XLS 9823 kb)Additional file 2:A comparison of all protein domains identified in this study with CDD. (PDF 59 kb)Additional file 3:Sequences of all polyprotein domains in FASTA format. Individual types of domains are distinguished by a prefix which is followed by a name of DNA sequence of the complete element. For example Ty1-RT__REXdb_ID3879 is a protein sequence of RT domain from Ty1/copia element whose entire DNA sequence name is REXdb_ID3879. Information about sources of DNA sequences and classification of complete elements is provided in the Additional file Additional file 4:Similarity of eORFs to CDD sequences. (PDF 23 kb)Additional file 5:Summary of features characteristic of individual groups of LTR-retrotransposons. (XLS 17 kb)Additional file 6:Unrooted neighbor-joining trees inferred from alignments of concatenated alignments of RT-RH-INT (a), and separate alignments of RT (b), RH (c), and INT (d) sequences. Note that chromovirus and non-chromovirus lineages are clearly distinguished in all four trees. Individual clades shown in the Fig. Additional file 7:Sequence logos of CHD chromodomains. Note that the chromodomain sequences are highly divergent both between and within individual groups of chromoviruses. Three sites corresponding to the aromatic cage motif found in HP1-like chromodomains  are mark


Hepeviridae family. There are at least 20 million HEV infections annually and 60,000 HEV-related deaths worldwide. HEV can cause up to 30% mortality in pregnant women and progress to liver cirrhosis in immunocompromised individuals and is, therefore, a greatly underestimated public health concern. Although a prophylactic vaccine for HEV has been developed, it is only licensed in China, and there is currently no effective, non-teratogenic treatment. HEV encodes three open reading frames (ORFs). ORF1 is the largest viral gene product, encoding the replicative machinery of the virus including a methyltransferase, RNA helicase, and an RNA-dependent RNA polymerase. ORF1 additionally contains a number of poorly understood domains including a hypervariable region, a putative protease, and the so-called ‘X’ and ‘Y’ domains. ORF2 is the viral capsid essential for formation of infectious particles and ORF3 is a small protein essential for viral release. In this review, we focus on the domains encoded by ORF1, which collectively mediate the virus’ asymmetric genome replication strategy. We summarize what is known, unknown, and hotly debated regarding the coding and non-coding regions of HEV ORF1, and present a model of how HEV replicates its genome.Hepatitis E virus (HEV) is a small quasi-enveloped, (+)-sense, single-stranded RNA virus belonging to the  Hepeviridae family [Orthohepevirus, and are primarily transmitted through contaminated water sources or through the consumption of undercooked, infected meat derived from swine, deer, or wild boar [Hepatitis E virus (HEV) is a positive-sense, 5′-capped, single-stranded RNA virus of the e family . The vire family . The HEVild boar .Acute hepatitis from HEV is generally self-limiting in healthy patients, and symptoms  tend to resolve approximately 1 month post-infection . HoweverIn immunocompromised patients, chronic HEV is first treated by reducing immunosuppressive therapy where applicable (effective in ~70% of patients), and if this is unsuccessful, ribavirin monotherapy is used ,9,10. AdIn this review, we focus on the mechanisms of HEV genomic replication, starting from uncoating after the virus has entered the host cytoplasm to the process of asymmetric genomic replication and translation of viral proteins from subgenomes. We also cover, in detail, the previously published literature on open reading frame 1 (ORF1) of HEV which encodes the replicative machinery of the virus, as well as the 5′ non-coding and junctional regions flanking ORF1.HEV is organized into three ORFs. ORF1 is the largest, comprising ~5 kB of the virus and encoding the enzymes required for genomic replication including the methyltransferase (Met), RNA helicase (Hel), a putative papain-like cysteine protease (PCP), and the RNA-dependent RNA polymerase (RdRp) a. The geThe (+)-sense HEV genome is capped at the 5′ end and polyadenylated at the 3′ end, and can therefore be translated directly by host ribosomes . After vAfter HEV was identified as non-A, non-B hepatitis in 1983, research into the functional domains of the virus began . With thalphavirus-like’ supergroup of RNA viruses [The genomic RNA of HEV is known to be capped, based on binding assays to monoclonal antibodies and competitive binding experiments . The reg viruses ,25,26,27Though sequence homology with other viruses initially suggested that the methyltransferase domain was located from nucleotides 26 to 240, the experimentally validated domain required for capping stretches over half of ORF1, encompassing the methyltransferase, X domain, putative protease, Y domain, and HVR domains, terminating within the helicase domain ,20. TherSeveral studies have shown that patients with acute viral hepatitis (AVH) and acute liver failure (ALF) caused by HEV were infected with virus containing mutations in various domains of ORF1, including in the methyltransferase domain. Mutations in this region can have pro- or antiviral effects. In one study, it was found that the D29N and V27A mutations in the methyltransferase domain of genotype 1 HEV led to an increase in viral load, and were identified in patients experiencing ALF but not in those experiencing the relatively less severe symptoms of AVH (GenBank accession no: AF459438) . ConversUltimately, though the methyltransferase domain is one of the better understood regions of HEV, questions still remain as to whether the protein is a discrete, functional unit of a processed polyprotein, or if it is one functional region of a large multifunctional protein.The X domain  and Y domains of HEV are, at this time of writing, enigmatic to say the least. As with other domains of HEV ORF1, the functions of the X and Y domains were initially deduced based on sequence alignments with other viruses . Since tThe HEV X domain is also known as the ‘macro domain’ because it exhibits weak sequence homology to human macro domain-containing proteins, which are ADP ribose-binding molecules . Mono ancis interactions with the methyltransferase and ORF3 proteins. The HEV X domain shows high sequence homology to the active site of the coronavirus (CoV) cellular X domain-associated macro domain protein/ADP ribose-1”-monophosphatase (CoV Appr-1”-pase), and mutations in the putative catalytic site of the HEV X domain at N809A, H812L, G816A, G816V, G817A, or G817V severely reduce or completely abrogate viral replicative ability based on experiments using a reporter replicon of the SAR55 strain of genotype 1 HEV (GenBank accession no. AF444002) [Other suggested functions of the HEV X domain include a role in viral replication and F444002) . A yeastF444002) . FurtherF444002) . InteresF444002) ,35.To date, there is very little known about the Y domain of HEV outside of the fact that it possesses sequence conservation of several motifs within this region across all known HEV genotypes, and shares sequence homology across several motifs with other known viruses. Specifically, in silico analysis suggests a putative palmitoylation site at residues C336–C337, and an alpha helix segment stretching from residues L410 to E416 (both motifs conserved across known HEV genotypes) that is predicted to bind the cytoplasmic membrane [Not much is known about the clinical relevance of the X and Y domains of HEV, but a few studies have thus far shed some light on their importance in pathology. One such study analyzed HEV quasispecies in two groups of solid organ transplant patients; one of these groups went on to establish chronicity and the other group cleared the infection. Between these two groups, there was greater sequence heterogeneity in the HVR region of HEV and within the X domain in the group that developed chronic infections when compared to the group who cleared in infection, suggesting a role in the severity of pathogenesis dictated by the composition of these regions .There is also some evidence suggesting the involvement of the X domain in cellular iron transport. Based on studies using a yeast two-hybrid system, the HEV macro domain protein interacts with the light chain of human ferritin . FurtherOnce again, the presence of macro domains is conserved across the alpha-like supergroup of positive sense RNA viruses, including coronaviruses, rubella virus, HEV, and mouse hepatitis virus (MHV). MHV, a coronavirus, induces high levels of inflammatory cytokines and is known to induce acute viral hepatitis in mice. Strikingly, a recombinant MHV strain A59 with a single amino acid substitution within the macro domain enzymatic core N1348A, encoded by the virus, not only led to slightly reduced titers when introduced to mice, but it did not induce liver disease and induced much lower levels of the inflammatory cytokine IL-6 . While tThe putative protease region of HEV and its function(s) are still under debate. The region was first identified as a putative protease based on sequence alignment with rubella virus and, since then, it has been studied in a variety of expression paradigms, leading to directly conflicting results. As it stands, there are two major hypotheses in the HEV field regarding this domain: (1) that this region acts as a true virally encoded protease that processes the HEV polyprotein into discrete functional units; or (2) that this region does not process the viral polyprotein, and if it does harbor proteolytic activity, the targets must be cellular and not viral. The studies supporting each hypothesis are outlined below.Evidence for a cysteine protease that processes ORF1 into nine protein subunits: In silico analysis predicted a papain-like beta barrel fold and identified the proteolytic dyad of this putative papain-like cysteine protease (PCP) as residues C434 and H443 . A putatEvidence for processing of ORF1 into two subunits: Another study utilizing a GFP reporter replicon of the genotype 1 SAR55 strain of HEV showed that site-directed mutagenesis of the following residues in the PCP domain abrogated GFP expression in HUH 7 S10-3 cells, used in the study as a proxy for viral replication: C457A, C459A, C471A, C472A, C481A, C483A, H443L, H497L, and H590L [Evidence for chymotrypsin-like activity of the putative protease: One study found that purified and dialyzed fragments of HEV ORF1 and ORF2 were processed into smaller fragments when incubated with purified protein from the PCP region spanning amino acids 440–610, and that inhibitors to chymotrypsin halted this processing, suggesting that this region harbors a different class of proteolytic activity [Evidence for serine protease cleavage sites within the PCP region: Conversely, a recent study found two conserved putative cleavage sites for cellular thrombin and one putative cleavage site for cellular factor Xa within HEV ORF1, conserved across all HEV genotypes; the factor Xa site was suggested within the PCP domain at amino acid 560, and the thrombin sites in X domain (between 846 and 862 depending on HEV genotype) and in RNA-dependent RNA polymerase (between 1218 and 1235 depending on genotype) . To charSeveral studies suggest that the polyprotein of HEV is processed but disagree on the class of protease that is encoded by this region. These studies are summarized in this section.While the studies listed above implicate the polyprotein as being processed over the course of the HEV replication cycle, few utilize biologically relevant systems that accurately mimic HEV infection, and none were conducted in the context of a natural infection cycle. Conversely, studies looking at ORF1 protein function and localization did not find evidence of polyprotein processing. One such study concluded that in vitro translation of ORF1 protein did not harbor intrinsic proteolytic activity when the protein was purified; subsequent in vitro expression of proteins in HeLa or HUH7 and pulse-chase experiments with radioactive methionine did not show processing, and suggest that the ORF1 polyprotein localizes to endoplasmic reticulum membranes . Other sAny study relying on (over)expression of the PCP, or any ORF1 subunit for that matter, will ultimately have to prove that such domain taken outside the context of the ORF1 polyprotein is still functioning properly. Otherwise, the relevance of any data will be very difficult to determine. Ultimately, the function of the putative protease domain is still as enigmatic as ever, and future studies will hopefully be able to shed more unambiguous light on the functions of this region of the HEV replicase.The hypervariable region (HVR) of HEV is located in ORF1 directly downstream of the putative papain-like cysteine protease (PCP) domain. It is bound by the conserved sequences TLYTRTWS and RRLLXTYPDG at the N- and C- termini respectively, however, the intervening sequence contains the most divergence of any region in the virus, earning it the name ‘hypervariable region’ . AlthougAmino acid sequence identity of the HVR differs up to 71% across HEV genotypes. Intra-genotypically, it differs up to 31% among genotype 1 isolates, 41% among genotype 3 isolates, 46% among genotype 4 isolates, and 30% between the only two available avian HEV isolates . The HVRThe most commonly proposed function for the HEV HVR is that it plays a structural role as a flexible hinge between adjoining ORF1 regions . This isThere is also evidence suggesting that the HVR influences host tropism. HVR sequence divergence is >2-fold greater for HEV zoonotic genotypes 3 and 4 than for human genotype 1, suggesting a potential association between sequence heterogeneity and the number of hosts . FurtherFinally, the HVR is known to be essential for viral replication and, despite its great sequence heterogeneity, it exerts this effect in a genotype-specific manner. Deletions in the HVR or swapping HVR sequences between strains of HEV from different genotypes both result in major reductions in viral replication efficiency . The speMultiple analyses of HEV isolates from chronically infected patients have revealed that the HVR can acquire insertions over time, either from other regions of the viral genome, or from human genes ,57. It iEMBO), which make up an NTP-binding motif. The A site contains a run of hydrophobic residues followed by a conserved GxxxxGKS/T site (where x represents any amino acid), and the B site begins with a run of hydrophobic amino acids followed by an asparagine. The Walker A site is thought to be involved in directly binding beta and gamma phosphates of NTPs, while the B site chelates Mg2+ of the Mg–NTP complex. The HEV helicase falls under superfamily 1, which possesses seven conserved motifs arranged in a co-linear fashion . Motif VI is thought to bind nucleic acids due to the high number of basic residues, namely arginine [Helicases are enzymatically capable of unwinding RNA duplex structures, a process that is coupled with NTP hydrolysis and responsible for the observed NTPase activity in most, if not all, of the helicases described to date (reviewed in ). RNA hearginine .Multiple studies have been published in the past several decades aimed at mechanistically understanding and mapping the function of the HEV helicase. Enzyme-linked immunosorbent assays (ELISAs) have shown that the HEV helicase possesses NTPase activity and is capable of hydrolyzing ATP . DeletioEscherichia coli and found that this protein hydrolyzes all rNTPs efficiently, but exhibits a preference for dATP and dCTP [Further, a study utilizing a radioactive phosphate assay revealed that the aforementioned HEV helicase domain ranging from amino acids 960 to 1204 from genotype 1 HEV exhibits 5′ NTPase activity, suggesting that this activity is essential during RNA cap formation . The samand dCTP .Renilla luciferase. For example, the A1213V and V1213A point mutations respectively reduce replication of the genotype 1 SAR55 and genotype 3 SHEV replicon strains. Additionally, the S605P mutation within the X domain combined with an I978V mutation in the helicase domain have a cumulative negative effect on viral replication [Other mutations made in the helicase domain of HEV genotype 3 have varying effects on viral replication in a reporter replicon system expressing lication .In patients with fulminant hepatic failure caused by genotype 1 HEV, it is common to see the following mutations in the helicase region: L1110F and V1120I . These mAdditionally, a study aimed at finding novel inhibitors to this virally encoded protein domain via virtual screening demonstrated that the saturation mutagenesis producing synonymous mutations within the helicase domain did not affect in vitro-transcribed RNA synthesis, suggesting non-conservation of the genome, and that the nucleotide sequences therein are dispensable at the transcriptional level .As with most RNA viruses (retroviruses excluded), HEV encodes an RdRp that synthesizes sense and antisense RNA transcripts using antisense and sense viral RNA templates, respectively. In the Burma reference strain of HEV, the RdRp spans nucleotides 1249–1671 (GenBank accession M73218), and it is located downstream of the RNA helicase gene across all genotypes. The HEV RdRp is phylogenetically classified in supergroup III, along with the RdRps from rubella virus and beet necrotic yellow vein virus . UnfortuHEV employs an asymmetric genomic replication mechanism which is thought to occur in the endoplasmic reticulum. The sense viral RNA is first transcribed into an antisense intermediate RNA strand which is subsequently used as a template to transcribe both a full-length sense RNA genome to be packaged into progeny virions as well as a shorter subgenomic RNA (sgRNA) that is used as a template to translate the ORF2 and ORF3 proteins. The HEV RdRp binds to the 3′ UTR of the sense strand to produce the antisense intermediate strand and to the 5′ UTR of the antisense strand to produce the full-length sense RNA genome. The RdRp also binds to a subgenomic promoter (SgP) spanning a 44 nt region from the 3′ end of the ORF1 to the transcriptional start site (TSS) of ORF3 ,70 and aViral RdRps often interact with other viral or host proteins that can complement RdRp activity, serve as scaffolds for the viral replicase complex, or modulate RdRp activity to influence levels of transcription. Yeast two-hybrid screening has shown that the RdRp self-interacts, a characteristic shared by many (+)-sense strand RNA viruses such as poliovirus and hepatitis C virus; however, it is not known whether these interactions amount to dimer formation or higher-order oligomers ,74,75. TThe HEV RdRp has also been shown to interact with several host and immune factors. It binds the host interferon-induced protein IFIT1, with the proposed function that it sequesters IFIT1 to inhibit its anti-translational activity . RdRps fSeveral mutations in the RdRp region have been correlated with adverse clinical outcomes. A study in North India analyzing clinical isolates from pregnant patients with genotype 1 HEV infection found that C1483W and N1530T point mutations in the RdRp were correlated with high viral loads and poor clinical outcomes (Reference strain: GenBank ID AF459438) . AdditioThe RdRp is also an attractive therapeutic target. Ribavirin, the only existing treatment for chronic HEV infection, is a nucleoside analog that inhibits RdRp activity and is highly effective in certain patient subpopulations . In vitrcis-acting regulatory elements (CREs) that play roles during genomic replication: the 3′ non-coding region (NCR) and the subgenomic promoter (SgP). Both the 3′ NCR and the SgP likely contain secondary structures and sequences that are highly conserved across diverse HEV genotypes [The HEV genome contains two known enotypes ,84. Thesenotypes ,86. A nuHEV, which contains a (+)-sense single-stranded RNA genome, requires transcription of a complementary antisense template RNA as a key step in genomic replication. Initiation of antisense RNA transcription requires binding of the RdRp or replicase complex to the 3′ end of the sense strand; therefore, this region plays a critical and early role in replication of the viral genome. Studies have confirmed that two stem loop structures located at nucleotides 7089–7163 and 7173–7194 (Ref: AF076239) as well as the 3′ poly-A tail are critical for interaction with the RdRp, and that the two stem loops are conserved across diverse HEV genotypes . MutatioThe subgenomic promoter (SgP) is a conserved sequence located at nucleotides 5080–5132 (Ref: Burma M73218) which, on the antisense template RNA, is critical for synthesis of the (+)-sense subgenomic RNA (sgRNA) ,88,89. TElectrophoretic mobility shift assays have shown that the RdRp exhibits a higher binding affinity to the 3′ NCR than SgP, however, further studies are required to fully understand how RdRp interactions with these target sites are regulated . UnfortuHEV is a globally prevalent pathogen causing a heavy clinical burden in diverse geographical and patient populations. Since the first infectious clone for HEV was created in 1991 [Box 1Which host factors are essential for HEV RNA replication?Does HEV replication lead to membrane rearrangements similar to other (+) RNA viruses?Does ORF1 polyprotein get processed? If so, how?Does the PCP region contain protease activity? If so, against what targets?What is the role of the HVR? How do insertions in this region confer cell culture adaptation?What is the role of the Y domain in the HEV replication cycle?What is the structure of the ORF1 polyprotein, or structures of ORF1-encoded proteins (if processed)?What are the kinetics and levels of transcription of antisense, full-length (+)-sense, and sgRNAs; and what are the mechanisms regulating expression of these elements?What are the components of the replicase complex for HEV? Does the RdRp self-oligomerize?