Warfarin and similar vitamin K antagonists have been the standard therapy for patients with mechanical or biological valve prosthesis and atrial fibrillation (AF). Even with the appropriate use of therapy, some studies have reported that there is a high incidence of thromboembolic events, 1%-4% per year. Furthermore, a bleeding risk is significant, ranging from 2% to 9% per year, according to some studies.The objective of our study was to examine the effect of dabigatran etexilate versus dose-adjusted warfarin for the prevention of intracardiac thrombus in persistent or permanent AF at least 3 months after aortic and/or mitral bioprosthesis replacement.Dabigatran versus warfarin after bioprosthesis valve replacement for the management of atrial fibrillation postoperatively (DAWA) is a phase 2, prospective, open label, randomized exploratory pilot study. The main variable to be observed in this study is intracardiac thrombus. From August 2013 to April 2015, 100 patients, at least 3 months after aortic and/or mitral bioprosthesis replacement and permanent or persistent AF postoperatively, who match eligibility criteria will be selected from Ana Nery Hospital in Salvador-Bahia with a follow-up of three months. Patients were randomly assigned in a 1:1 ratio to receive either dabigatran etexilate or warfarin.Although the present study has no statistic power to proof non-inferiority, it is expected that the dabigatran etexilate group will be protected as well as the warfarin group from intracardiac thrombus, without increasing the bleeding rates, since we are using safer doses (110 mg bid). The lack of necessity of monitoring INR is also another factor that contributes to a better adherence to the new drug and it can make all the difference in the manner of doing anticoagulation for patients with similar clinical characteristics.The study is in the recruitment phase. It is possible that dabigatran etexilate is as effective as warfarin in preventing the emergence of intracardiac thrombus in patients with AF and mitral and/or aortic bioprosthesis.Clinicaltrials.gov NCT01868243; http://clinicaltrials.gov/ct2/show/NCT01868243 (Archived by WebCite at http://www.webcitation/6OABiuasd). Valvular heart disease affects over 100 million people worldwide. Its prevalence is rising due to the high incidence of rheumatic disease in developing countries and the growing impact of degenerative valve disease in elderly populations, a consequence of population ageing . An estiWarfarin and similar vitamin K antagonists (VKA) have been the standard therapy for patients with a prosthetic heart valve and atrial fibrillation (AF). Even with the appropriate use of therapy, the incidence of thromboembolic events is still substantial, 1%-4% per year. Furthermore, bleeding risk is significant, ranging from 2% to 9% per year -5. VKA hDabigatran etexilate is the prodrug of dabigatran, a direct thrombin (factor IIa) inhibitor. After administration, it is rapidly converted by serum esterase to the active moiety, dabigatran, which is a nonpeptide, potent, competitive, and reversible inhibitor of thrombin. The pharmacokinetics and pharmacodynamics of dabigatran allow fixed dose administration without coagulation monitoring .P=.001; and RR=0.91; 95% CI 0.74-1.11; P=.34, respectively) [The US Food and Drug Administration (FDA) approved dabigatran on October 19, 2010, for the prevention of stroke and systemic embolism in patients with nonvalvular AF . The Ranctively) . The conNevertheless, there are no studies in humans evaluating the efficacy and safety of dabigatran in patients with AF and mitral and/or aortic bioprosthetic valve. Among patients with mechanical heart valves, the randomized phase II study to evaluate the safety and pharmacokinetics of oral dabigatran etexilate in patients after heart valve replacement (RE-ALIGN) was terminated early because the dabigatran etexilate treatment arm had significantly more thromboembolic events  and major bleeding  than did the warfarin treatment arm. These bleeding and thromboembolic events were reported in patients who were initiated on dabigatran etexilate postoperatively within 3 days after mechanical bileaflet valve implantation, and in patients whose valves had been implanted more than 3 months previously .With this gap in mind, considering the complicated management of VKAs, the investigators of this study chose to conduct an open randomized controlled pilot trial to assess the efficacy and safety of dabigatran etexilate compared with warfarin in patients with persistent or permanent AF after bioprosthetic mitral and/or aortic replacement (DAWA).DAWA is a phase 2, prospective, open label randomized pilot study. The main variable to be observed in this study is intracardiac thrombus. There are no formal primary or secondary clinical efﬁcacy or safety outcomes because it is a pilot study. Mortality and morbidity events  will be evaluated in an exploratory manner and are considered as further endpoints in this trial. The inclusion and exclusion criteria are outlined in The study will be performed in accordance with the ethical principles that have been laid down in the Declaration of Helsinki. They are consistent with the International Conference on Harmonization/Good Clinical Practice, and applicable regulatory requirements in Brazil where it was approved unreservedly by the local ethics and research committee´s under protocol number 14284813.9.0000.0045. A data monitoring committee will monitor patient safety and treatment efficacy every 2 months.Age from 18 to 64 years at entryPatients with mitral and/or aorthic valve bioprosthesis for at least 3 months postoperativelyThere is 12-lead electrocardiogram documented AF on the day of screening or randomization; or a 24-hour Holter electrocardiogram recording showing AF episodes postoperativelyBrain computed tomography scan without hemorrhage or findings of acute cerebral infarction on the last 2 days of screeningExclusion of atrial thrombus or valve prosthesis thrombosis by transesophageal echocardiograph on the last 2 days of screeningWritten, informed consentPrevious hemorrhagic strokeIschemic stroke in the last 6 monthsSevere renal impairment (creatinine clearance rates < 30 ml/min)Active liver disease (any etiology)Concomitant use of any antiplatelet Increased risk of bleeding Uncontrolled hypertensionGastrointestinal hemorrhage within the past yearAnemia (hemoglobin level <10 g/dL) or thrombocytopenia (platelet count < 100 × 109/L)Active infective endocarditisPregnant or lactating womenProspectively, from August 2013 to April 2015, 100 consecutive patients between 18 and 64 years old, at least 3 months after mitral and/or aortic bioprosthesis valve replacement, documented AF postoperatively, and who match the eligibility criteria are being recruited from Ana Nery Hospital in Salvador-Brazil after obtention of informed consent.For the allocation of the participants, a computer generated list of random numbers including 1 to 100 was used . FollowiDabigatran etexilate will be supplied as capsules containing 110 mg, which should be taken twice daily without the need of INR monitoring. All the patients randomized to use dabigatran etexilate will remain with that drug for the duration of the study. Any patients who used warfarin previously will do a drug washout, followed by an immediate introduction of dabigatran etexilate once the INR < 2.5.The patients assigned to warfarin will require close coagulation monitoring to achieve the target INR . Therefore, it will be necessary to follow a protocol of monitoring and dosage adjustment of this drug to ensure the safety and optimization of its use since each patient responds differently to the same doses. The warfarin dose adjustment algorithm was made according to the evidence-based guideline of the American College of Chest Physicians, and several other studies ,13-18. DThe primary endpoint will be the appearance of an intracardiac thrombus in an esophageal echocardiogram to be held at the end of the follow-up. Other probable endpoints are the composite of stroke (ischemic or hemorrhagic), systemic embolism , and prosthesis valve thrombosis. The safety endpoints will be any bleeding event (major or minor), elevated liver enzymes, or hepatic function abnormalities.A thromboembolic event involving the central nervous system was defined as a sudden, focal neurological deficit of presumed vascular origin lasting 24 hours to 7 days  or enduring more than 7 days (stroke), as confirmed by computed tomographic or magnetic resonance scan imaging and evaluated by a skilled physician. A peripheral embolism was diagnosed when there was a sudden onset of arterial occlusion in the extremities (with or without cyanosis) and with reported absence of pulse, or sudden abdominal pain requiring urgent intervention . One of the criteria in the list below defined a major bleeding event . All oth-1(1.24 mmol L-1) or more, or leading to transfusion of two or more units of whole blood or red cells.Major bleeding criteria: (1) fatal bleeding, (2) symptomatic bleeding in a critical area or organ, such as intracranial, intraspinal, intraocular, retroperitoneal, intraarticular or pericardial, or intramuscular with compartment syndrome, and/or, (3) bleeding causing a fall in hemoglobin level of 20 g LAny patients with bleeding on dabigatran etexilate or warfarin therapy will be immediately hospitalized and screened for the severity of bleeding . The management of these complications will follow current guidelines and review articles -18.All participants will have telephone visits scheduled weekly. After that period, study visits will be scheduled monthly. The telephone number of all the researchers will also be available to the patients. At any time, in any phase of the study, the patient will have the full right to request exclusion from the study.Electrocardiography and laboratory tests  will be performed monthly to monitor any changes that indicate bleeding or coagulopathy. Before the randomization and after the follow-up period, patients will undergo a brain computed tomography without contrast to exclude recent ischemic or previous hemorrhagic cerebrals events, and a transesophageal echocardiogram to check prosthesis function (including peak and mean gradient), and to check left atrial thrombus.During the follow-up, if any unfavorable outcome with patients in the study is evidenced, an emergency meeting with the ethics committee will be held to evaluate the discontinuation of the study, regardless of their stage of recruitment. Other than that, every 2 months there will be a meeting with the same group with the intention of observing the progress of the study and the outcomes observed in each patient.t test for independent populations or related populations, as appropriate. The qualitative and categorical variables will be presented as percentages and their comparisons will be made by χ2 test (chi-square) or the Fisher exact test when indicated.The SPSS 17.0 (SPSS Inc) will be used to perform statistical analysis of the collected data. The primary analysis will be performed according to the intent-to-treat principle. A safety analysis will be performed on all patients treated regardless of any protocol violations. The quantitative variables will be described as mean and standard deviation. The mean comparison will be performed by the Student The use of drugs such as acetylsalicylic acid, clopidogrel, and other antiplatelet agents will not be allowed during the study period. The same applies to antiarrhythmic drugs that interact with dabigatran etexilate, such as quinidine.Although the present study has no statistic power to proof non-inferiority, it is expected that the dabigatran etexilate group will be protected as well as the warfarin group from intracardiac thrombus, without increasing the bleeding rates, since we are using safer doses (110 mg bid). The lack of necessity of monitoring INR is also another factor that contributes to a better adherence to the new drug and it can make all the difference in the manner of doing anticoagulation for patients with similar clinical characteristics. Enrollment for this study started in July 2013 and is expected to conclude in April 2015. Final results are expected in September 2015. The study is in the recruitment phase.Anticoagulant treatment reduces the incidence of death and cardioembolic events in patients with AF or a prosthetic heart valve, and the incidence of death and recurrences in patients with venous thromboembolism . WarfariRecently, direct thrombin inhibitors and factor Xa inhibitors have been added to the armamentarium for anticoagulation in AF. Dabigatran is an oral, reversible, direct competitive inhibitor of thrombin, which prevents the conversion of ﬁbrinogen to ﬁbrin within the coagulation cascade, thereby inhibiting thrombus formation . The ass


The cell achieves DNA double-strand break (DSB) repair in the context of chromatin structure. However, the mechanisms used to expose DSBs to the repair machinery and to restore the chromatin organization after repair remain elusive. Here we show that induction of a DSB in human cells causes local nucleosome disassembly, apparently independently from DNA end resection. This efficient removal of histone H3 from the genome during non-homologous end joining was promoted by both ATM and the ATP-dependent nucleosome remodeler INO80. Chromatin reassembly during DSB repair was dependent on the HIRA histone chaperone that is specific to the replication-independent histone variant H3.3 and on CAF-1 that is specific to the replication-dependent canonical histones H3.1/H3.2. Our data suggest that the epigenetic information is re-established after DSB repair by the concerted and interdependent action of replication-independent and replication-dependent chromatin assembly pathways.DOI:http://dx.doi.org/10.7554/eLife.15129.001 Decades of studies have emphasized the critical importance of chromatin components, whose nature and spatial organization regulate cellular function and identity, including DNA repair . DNA douWithin the cell, eukaryotic DNA is packaged into the nucleoprotein structure known as chromatin. The nucleosome is the primary level of chromatin structure, with about 146 bp of DNA wrapped around an octamer of histones, which includes two molecules each of histones H2A, H2B, H3 and H4 . Due to Upon generation of DSBs, the local chromatin structure is altered at many different levels, including histone post-translational modifications, chromatin relaxation, histone exchange, histone mobilization and histone removal from the DNA . The lasChromatin disassembly and reassembly also appear to occur during DSB repair in mammalian cells. Displacement of histones H2B and H3 was apparent during DSB repair around DSBs that were generated by introduction of the I-PpoI and HO homing enzymes into mammalian cells . Using tThe mechanism by which chromatin is disassembled and reassembled during DSB repair is unclear. In yeast, the H3-H4 histone chaperone Asf1 is required for chromatin assembly after HR repair, but this function is due to the role of Asf1 in promoting acetylation of histone H3 on lysine 56 . NucleolInsights that may be relevant to chromatin disassembly and reassembly during DSB may be provided by the chromatin dynamics during transcription, replication and UV damage repair. The histone chaperone CAF-1 deposits newly-synthesized H3/H4 onto the DNA following DNA replication and nucleotide excision repair (NER) in vitro and in cells . AnotherIn this study, we set out to delineate nucleosome dynamics during DSB repair in human cells. We found that DSBs lead to complete nucleosome disassembly around the DNA ends, restricted to within 750 bp from DNA ends. Unexpectedly the chromatin disassembly is independent of DNA end resection because the repair occurred during NHEJ and during MRE11 inhibition. ATM and INO80 facilitate histone disassembly during DSB repair. Meanwhile, chromatin reassembly after repair required both the HIRA-mediated replication-independent pathway and the CAF-1-mediated replication-dependent pathway, suggesting that they occur in a coordinated manner to reestablish the chromatin structure after DSB repair.SLCO5A1 gene was about 50% cleaved in the cell population, as determined by PCR over the I-PpoI site using flanking primers  and ATR (ATM- and Rad3-related) are the central sensor kinases in the DNA damage checkpoint. Whereas ATM is primarily activated by blunt-ended DSBs, activation of ATR is mostly triggered by ssDNA lesions . To deteTo determine whether ATR may have a role in triggering chromatin disassembly that is only revealed in the absence of ATM, we inhibited both ATM and ATR . The resNucleosome disassembly is mediated by histone chaperones in concert with ATP-dependent nucleosome remodelers. All our efforts to identify histone chaperones involved in chromatin disassembly during DSB repair to date have failed to find the responsible histone chaperones (data not shown). Therefore, we turned our attention to the ATP-dependent remodelers, especially the ones that are known to be phosphorylated by ATM in response to DSBs. Budding yeast Fun30 promotes DNA end resection and chromatin disassembly around DSBs . Its mamThe remodeling complex INO80 (Inositol requiring 80) was previously shown to bind DSBs and assist DSB repair in yeast . In addiGiven that ATM phosphorylates INO80 , we wereOur previous work in yeast indicated that the histone chaperone ASF1 is required for chromatin assembly after DSB repair via HR . We knocHere we have shown that nucleosome disassembly and reassembly around DSBs is a highly regulated and coordinated part of the cellular response to DSB damage in mammalian cells, even during repair pathways that do not involve DNA resection. Repair of DSBs by NHEJ was accompanied by the apparent complete disassembly of nucleosomes adjacent to the break, spanning up to 1500 bp around the break. We found that chromatin disassembly around the DSB is a checkpoint-stimulated response to breaks involving an ATP-dependent chromatin remodeler. Meanwhile, HIRA-mediated assembly of H3.3 and CAF-1 mediated assembly of H3.1 occur after DSB repair in an interdependent manner, suggesting that coordinated mechanisms exist to accurately reestablish the epigenetic information carried by the chromatin structure after DNA repair .cis , suggesting that CAF-1 is required for chromatin assembly after DSB repair without ongoing DNA synthesis. It is unlikely that these results are due to indirect effects of CAF-1 knockdown, for example on cell cycle progression, because the defect in chromatin reassembly was localized specifically to the region around the DSB. Furthermore, all the cells would not have had a chance to progress through S phase within the short time course of cutting and repair that occurred in our experiments. The role of CAF-1 in chromatin assembly after DSB repair is not due to an indirect effect on HIRA levels, because no change in HIRA protein level was seen upon knockdown of CAF-1. In agreement with our findings, a recent study found specific recruitment of both the Hir complex and CAF-1 to meiotic DSBs in yeast . This reIn conclusion, we propose that immediately following the induction of DSBs in mammalian cells, histone disassembly occurs on both sides of the break. This step is tightly regulated as only about 4 nucleosomes are disrupted on each side of the DNA break, presumably for efficient recruitment of the NHEJ repair machinery. ATM and histone remodelers such as INO80 actively participate in the histone disassembly. After DSB repair, histones are reassembled back to the repaired DNA regions to restore their local chromatin structures, and this step requires functional coordination between histone chaperones ASF1A, CAF-1 and HIRA.HEK293T cell lines were maintained in DMEM containing 10% FBS. The cell lines were obtained from ATCC and were tested regularly for mycoplasma contamination. The procedure for induction of DSBs by I-PpoI was as described . BrieflyGIPZ Lentiviral shRNA constructs (Thermo scientific) corresponding for each target gene were used to generate stable knockdown cells. Production of lentivirus and transfection of HEK293T cell were carried out according to the manufacturer's instructions (Thermo scientific). The efficiency of knockdown for each target gene was confirmed by western blotting. The antibodies used were: RAD51 (abcam), KU70 , SMARCAD1 (abcam), HIRA (active motif), INO80 (abcam), ASF1A (abcam), ASF1B (abcam), CAF1-p150 (abcam), hGAPDH , β-actin (abcam).Histone H3 Chromatin immunoprecipitation (ChIP) was performed as previously described . In addiSLCO5a1 fragments were detected using a radiolabelled SLCO5a1 probe (primer sequences used for amplifying this probe are listed below).Extracted genomic DNA from HEK293T cell was digested with PstI-EcoRV. DNA samples were resolved by a 1% agarose gel, and transferred to a nylon membrane. The uncut and cut Western analysis of I-PpoI was performed using an antibody against HA-tag .Primers used for ChIP, PCR and southern probes: In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been favorably evaluated by Kevin Struhl (Senior editor) and three reviewers, one of whom, Jerry Workman, is a member of our Board of Reviewing Editors.Thank you for submitting your article "Nucleosome disassembly during NHEJ in human cells, followed by concerted HIRA- and CAF-1-dependent chromatin reassembly" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:This is nice paper that assists in resolving the critical factors that contribute to double strand break (DSB) repair. In particular, the requirements for chromatin remodeling and histone chaperones are demonstrated in reconstructing the chromatin environment during induction of DSBs and repair. The authors utilize an inducible system to create site-specific DSB in mammalian cells. Through multiple lines of evidence  DNA end resection is not evident during repair or nucleosome (de)assembly. Nevertheless, nucleosome eviction is still observed and found to be dependent on ATM and the INO80 chromatin remodeler. In the absence of this activity, repair is deficient. Histone chaperones are then needed to reassemble the chromatin surrounding DNA breaks. The logic of the manuscript is concise and the data largely convincing.Essential revisions:1) A major concern is whether the apparent loss of histones next to the break might be an artifact of the break itself. If the ChIPed DNA fragments are sheared to on average 500 base pairs then a ChIP signal could be seen from histones bound on either side of the primers within 500 bps. However, if you cut next to the primers with the targeted nuclease then the ChIP signal can only come from histones bound within 500 base pairs of the other side (i.e. bound on one side but not both sides). Hence an artificial apparent drop in histone cross linking. The authors need to test or convincingly deal with this possibility.2) At times it is difficult to discern significant differences in H3 occupancy after DSB formation between wildtype and mutant cell lines. p-values should be calculated when authors suggest significant alterations.3) Not all of the panels have error bars. The nature of the assay is not robust, measuring less than 2 fold changes. Thus the statistics are important and error bars are needed.4) The connection between ATM and INO80 function in nucleosome disassembly is not particularly strong. Are the authors suggesting that ATM regulates INO80 to facilitate nucleosome disassembly? If so can a more direct assay be performed, such as shINO80 knockdown in the presence and absence of ATM inhibitor to assess epistatic or added effects.5) Most experiments in this manuscript used only one shRNA to knock down target protein. The authors should include at least one more shRNA to exclude off-target effects. This is an important issue as the effect of knockdown of some genes on nucleosome disassembly assembly is small (maximum 2 fold). Alternatively, it is a good idea to reintroduce the protein to see whether the defects can be rescued by the effects.6) In 7) I suspect that nucleosome disassembly/assembly and repair efficiency depends on the cell cycle. The effect of INO80 knockdown. KU80 and Rad51 on cell cycle should be analyzed.8) It is hard to imagine that knockdown CAF-1 and HIRA affect nucleosome assembly similar after DNA repair. If this is the case, one would expect to detect H3.1 and H3.3 at break sites similarly. Essential revisions:1) A major concern is whether the apparent loss of histones next to the break might be an artifact of the break itself. If the ChIPed DNA fragments are sheared to on average 500 base pairs then a ChIP signal could be seen from histones bound on either side of the primers within 500 bps. However, if you cut next to the primers with the targeted nuclease then the ChIP signal can only come from histones bound within 500 base pairs of the other side (i.e. bound on one side but not both sides). Hence an artificial apparent drop in histone cross linking. The authors need to test or convincingly deal with this possibility.It is true that introducing a DSB could lead to a decrease of the potential DNA fragments that can be ChIPed down. However, this is not the reason for the observed histone level decrease for the following reasons. The sonicated fragment size is generally about 500 bps in our assays, while the closest primer set from the break end is centered around 200bps away. Given that our replicon size is about 100-120bps, this means that the closest primer end in our assay is still about 140-150 bps away from break end. Even if that statistical counting indeed has an effect, the effect should be no more that 25%. In addition, we also detect 50% decrease at 500 bps away, as well as at 750 away. These two sites should not be affected by that statistical model. Moreover, we show that certain conditions (knockdown of INO80 and ATM inhibition) lead to no histone removal at specific time points that have efficient cutting. If the apparent histone loss is an artifact of the break itself, these results would have never have been obtained. In addition, the fact that knockdown of the histone chaperones ASF1, CAF-1 and HIRA all have effective DNA repair, yet there is no return of the histones by ChIP, shows that this signal is not an artifact of the break itself reducing the ChIPability of the flanking DNA. If it were, the ChIPed signal would have returned in the ASF1, CAF-1 and HIRA knockdowns upon DNA repair. The approach and interpretation of histone ChIP around a break that we use is the norm in the field, and is also used by the Soutoglou and Kastan labs.2) At times it is difficult to discern significant differences in H3 occupancy after DSB formation between wildtype and mutant cell lines. p-values should be calculated when authors suggest significant alterations.p values have now been calculated for the knockdown cell lines and inhibitors, and significantly different time points from the control cells are indicated.3) Not all of the panels have error bars. The nature of the assay is not robust, measuring less than 2 fold changes. Thus the statistics are important and error bars are needed.The only data that did not previously have error bars was the experiments using the ATR and MRE11 inhibitors, both of which showed no change from the wild type / no drug control. As such, we were not making statements of novel roles for these proteins from these particular data.In addition, all experiments included the analysis of two DNA regions of equal distance to the 5’ and 3’ of the IPpoI site, that showed highly consistent results, strikingly so for the MRE11 inhibitor experiments. In the case of the MRE11 inhibitor experiments, we also performed the ChIP at both 200bp and 500bp away at both 5’ and 3 ‘to the IPpoI site and saw the identical result. The analysis of four different regions itself indicates the reproducibility of the effect and could be considered more meaningful than analyzing the same region multiple times. But as requested by the reviewers, we have now repeated the ATR inhibitor analyses two more times to provide error bars. Unfortunately, we were not able to do this for the MRE11 inhibitor experiments, given that they were provided in limited quantities by a colleague from my previous institution, so were not readily available, in addition to the time limitations and large amounts of other additional experiments that were needed for this revision.4) The connection between ATM and INO80 function in nucleosome disassembly is not particularly strong. Are the authors suggesting that ATM regulates INO80 to facilitate nucleosome disassembly? If so can a more direct assay be performed, such as shINO80 knockdown in the presence and absence of ATM inhibitor to assess epistatic or added effects.As requested, we have now combined INO80 knockdown with ATM inhibition, and found that there is no synergistic increase. This is consistent with ATM modifying INO80 to promote chromatin disassembly, but far from proves it. We have included the new data and discussed it in the text accordingly.5) Most experiments in this manuscript used only one shRNA to knock down target protein. The authors should include at least one more shRNA to exclude off-target effects. This is an important issue as the effect of knockdown of some genes on nucleosome disassembly assembly is small (maximum 2 fold). Alternatively, it is a good idea to reintroduce the protein to see whether the defects can be rescued by the effects.These are good points, and we have now repeated the critical findings of the paper with additional shRNAs, to show that the results are not off target effects. The data are now included in the revised manuscript.6) In In 7) I suspect that nucleosome disassembly/assembly and repair efficiency depends on the cell cycle. The effect of INO80 knockdown. KU80 and Rad51 on cell cycle should be analyzed.Our data show that in asynchronous cells, the repair pathway that is used to repair the I-PpoI sites that we examine is NHEJ. NHEJ occurs efficiently throughout the cell cycle, but it is likely that there are differences in nucleosome disassembly/assembly pathways used through the cell cycle. Accordingly, as requested, we have examined the effects on INO80, KU80 and Rad51 knockdown on the cell cycle and find no significant alteration in the proportion of cells in G1, S, or G2/M. This data is now included as 8) It is hard to imagine that knockdown CAF-1 and HIRA affect nucleosome assembly similar after DNA repair. If this is the case, one would expect to detect H3.1 and H3.3 at break sites similarly.In agreement with our findings, a paper a few months ago from Haico van Attikum’s group  indeed shows incorporation of H3.1 and H3.3 at sites of double strand breaks, using SNAP labeling of newly-synthesized histones. We have now cited this paper.


Additional long-range linkage information is typically used to orient, order, and link contigs into larger structures referred to as scaffolds. Due to library preparation artifacts and erroneous mapping of reads originating from repeats, scaffolding remains a challenging problem. In this paper, we provide a scalable scaffolding algorithm (SILP2) employing a maximum likelihood model capturing read mapping uncertainty and/or non-uniformity of contig coverage which is solved using integer linear programming. A Non-Serial Dynamic Programming (NSDP) paradigm is applied to render our algorithm useful in the processing of larger mammalian genomes. To compare scaffolding tools, we employ novel quantitative metrics in addition to the extant metrics in the field. We have also expanded the set of experiments to include scaffolding of low-complexity metagenomic samples.Interest in SILP2 achieves better scalability throughg a more efficient NSDP algorithm than previous release of SILP. The results show that SILP2 compares favorably to previous methods OPERA and MIP in both scalability and accuracy for scaffolding single genomes of up to human size, and significantly outperforms them on scaffolding low-complexity metagenomic samples.Equipped with NSDP, SILP2 is able to scaffold large mammalian genomes, resulting in the longest and most accurate scaffolds. The ILP formulation for the maximum likelihood model is shown to be flexible enough to handle metagenomic samples. De novo genome assembly is one of the best studied problems in bioinformatics. Interest in the problem has been renewed in the past decade due to rapid advances in high-throughput sequencing (HTS) technologies, which have orders of magnitude higher throughput and lower cost compared to classic Sanger sequencing. Indeed, top-of-the-line instruments from Illumina and Life Technologies are currently able to generate in a single run billions of reads with an aggregate length of hundreds of gigabases, at a cost of mere cents per megabase. However, most HTS technologies generate relatively short reads, significantly increasing the computational difficulty of the assembly problem. Despite much work on improved assembly algorithms for HTS shotgun reads -6, de noTo increase the utility of such fragmented assemblies, additional long-range linkage information is typically used to orient, order, and link contigs into larger structures referred to as scaffolds. Although long-range linkage information can be generated using a variety of technologies, including Sanger sequencing of both ends of cloned DNA fragments of up to hundreds of kilobases, Pacific Biosciences reads of up to tens of kilobases , and optAlgorithms based on explicit statistical models are currently gaining popularity in the area of genome assembly , with noScalability of our algorithm, referred to as SILP2, is achieved by adopting a non-serial dynamical programming (NSDP) approach . Rather Compared to the preliminary version of the algorithm published in , referreGiven a set of contigs C and a set of read pairs R, the scaffolding problem asks for the most likely orientation of the contigs along with a partition of the contigs into ordered sets connected by read pairs of R. The main steps of the SILP2 algorithm are as follows , where each node i ε V represents a contig and each edge  ε E represents all read pairs whose two individual reads are mapped to the contigs i and j, respectively. Each read in a pair is aligned either to the forward or reverse strand of corresponding contig sequence, and this results in 4 possible configurations for a read pair  i ε V as well as choosing for each edge  ε E one of the four bidirections that is concordant with the orientations of i and j. A common way to reduce an inference problem to an optimization problem is to seek a feasible solution with maximum likelihood. Let each observation, i.e., aligned read pair r ε R, have a probability pr of being correct. Any feasible contig orientation O = O(C) either agrees or disagrees with the read pair r. Let RO be the set of read pairs agreeing with O. Assuming independence of observations, the likelihood of an orientation O can be written asand hence its log-likelihood is over all contig orientations O.Mapping probability estimation. If pr 's are assumed to be the same for all read pairs, then the objective (1) reduces to maximization of the number of read pairs that agree with the contig orientation O. We consider the following factors that reduce the probability pr that read pair r is aligned correctly:Overlap with repeats. As noted above, only pairs for which both reads map uniquely to the set of contigs are used for scaffolding. Still, a read that fully or partially overlaps a genomic repeat may be uniquely mapped to the incorrect location in case repeat copies are collapsed. We preprocess contigs to annotate repeats from known repeat families and by recording the location of multimapped reads. An estimate of the repeat-based mapping probability 1. Contig coverage dissimilarity. Although sequencing coverage can have significant departures from uniformity due to biases introduced in library preparation and sequencing, the average coverage of adjacent contigs is expected to be similarly affected by such biases . If the two reads of r map to contigs i, respectively j, the coverage-based mapping probability of r, i − coveragej coverage|/(i + coveragejcoverage).2. r. Mismatches and indels in read alignments, that can be caused by sequencing errors or polymorphisms in the sequenced sample, can easily be incorporated in the estimation of mapping probabilities.Note that factors such as repeat content of the sequenced genome and sequencing depth will determine how informative repeat-based and coverage-based mapping probabilities are. Depending on these factors, either Integer linear program. Our integer linear program maximizes the log-likelihood of scaffold orientation using the following boolean variables:i for each contig i, with Si equal to 0 if the contig's orientation remains the same and Si = 1 if the contig's orientation is flipped w.r.t. default orientation in the final scaffold.- a binary variable Sij for each edge  ε E, which equals 0 if none or both ith and jth contigs are flipped, and equals 1 if only one of them is flipped.- a binary variable Sij  which are set to 1 if and only if an edge in state A  is used to connect contigs i and j  enforce agreement between contig orientation variables Si's and edge orientation variables SSince eukaryotic genomes are linear, a valid scaffold orientation should not contain any cycles. The constraints (5) already forbid 2-cycles. Additionally, 3-cycles are forbidden with the constraints shown in Figure S2 in Additional file Non-serial dynamic programming. For large mammalian genomes, the number of variables and constraints is too large for solving the ILP (2)-(5) via standard solvers . As it has been noticed in [All constraints (3-5) as well 3-cycle constraints connect Sticed in , the scaticed in . The solBelow we illustrate the way how the solution is computed in stages through each of which the results of the previous stage are combined to dynamically solve the problem. Obviously, an isolated connected component will not influence other components. Moreover, it has been shown in  that 2-cStill, 2-connected components can be very large, so we look for 2-cuts in order to decompose the graph into significantly smaller 3-connected components. Figure 00 in which the 2-cut nodes i and j are constrained to both have default orientations;(1) the ILP solution sol01 in which the 2-cut nodes i and j are constrained to have opposite orientations.(2) the ILP solution sol00+(sol01-sol00) · Sij or, equivalently, the value sol00 should be added to 01 should be added to The two solutions are combined to solve the ILP for component B. The ILP objective for component B should be updated by adding the term of soli and Sj as in SILP1, ILP is solved only two times for combinations Si = 0 & Sj = 0 and Si = 0 & Sj = 1.The pseudo-code of the SILP2 NSDP algorithm for processing 3-connected components is given in Figure Thinning heuristic. Unfortunately the largest tri-connected component may still induce an ILP too large for CPLEX to solve in a reasonable amount of time. In order to address this problem a thinning heuristic is applied to the scaffolding graph. This scenario can be detected by setting a threshold on the maximum number of contigs allowed in a tri-connected component. When a component exceeds the threshold the number of read pairs necessary to induce an edge is increased by one and decomposition recomputed until there is no component above the threshold.In order to asses the quality and scalability of our scaffolding tool we developed a testing framework which closely mimics real world scaffolding problems. We utilized the Staphylococcus aureus (staph), Rhodobacter sphaeroides (rhodo) genomes and chromosome 14 of HapMap individual NA12878 (chr14) from the GAGE  were scaIn all test cases the read pairs used for scaffolding are aligned against the contigs using bowtie2 . Each reThe three small test cases are used to test both correctness and scalability of the scaffolding tool. In order to test correctness, contigs simulating a draft assembly were created by placing gaps in the genome. The contig and gap sizes were sampled uniformly at random from the collection of all the assemblies used in the GAGE comparison. The procedure to generate the contigs was to alternatively sample with replacement from the set of all contig sizes, and gap sizes. In this way a simulated scaffold can be generated so that the position and relative orientation of all contigs and all gap sizes are known. The orientation of the simulated contigs was randomized to prevent biases.For each genome 10 replicates were created, all subsequent results are the average of the 10 replicates. By creating simulated contigs with no assembly error, the accuracy of subsequent scaffolds can be evaluated exactly. Although the contigs were simulated, real read pairs were aligned against them and used as input. Table S1 in Additional File The NA12878 test case was produced by simply using the contigs created in the SGA  assembleFinally a simulated metagenomics test case was created to explore the feasibility of utilizing SILP2 to scaffold metagenomes. This was created by artificially mixing the staph and rhodo contigs and reads at varying proportions.A natural and common parameter present in all scaffolding algorithms in the bundle size, or the number of read pairs spanning two contigs. This parameter is a natural control of sensitivity and specificity; requiring more support increases specificity at the price of sensitivity and vice-versa. It should be noted that every scaffolding tool tested, including SILP2 does not abide by the set parameter absolutely. Each method raises it in order to ensure efficient operation. The simulated test cases were evaluated at several bundle sizes to asses its effect on accuracy and scalability. The NA12878 test case was only evaluated at the minimum feasible value due to resource constraints.Calculating the accuracy of de novo assemblies or scaffolds is quite difficult. One of the key challenges is deciding on the appropriate measure. In this comparison we elect to present several metrics which will likely have different weight depending on the background and intention of the reader.For the simulated contigs we treat scaffolding as a binary classification problem where methods attempt to predict true adjacencies in the test dataset. The accuracy and sensitivity can be directly measured by computing true positive, and false positive rates. One common summary is MCC, or Mathews Correlation coefficient. This measure assess sensitivity and specificity simultaneously. In the context of scaffolding, this measure illustrates how many correctly ordered and oriented scaffolds were created.An alternative measure, commonly utilized in genome assembly comparison publications ,38 is thFinally the usefulness of a genome can also be measured by the number of identifiable biological features captured. Here we capture this measure by recording the percentage of known genes that are found contiguous in the scaffolds.The MCC metric, as seen in Figure While MCC is natural to a computer scientist its useful to a biologist is lacking because the content of the contigs is ignored. A biologist typically asses a scaffold by the N50, Unfortunately this measure does not reflect the accuracy of the scaffolds and rewards aggressive merging. Using MCC or its constituent components as metrics gives greater clarity to the researcher comparing different tools.The most common metric found in genome assembly and scaffolding is N50. The most recent iteration of benchmark projects have transformed this descriptive number into an accuracy measure by introducing alignment based corrections. Here the scaffolds are aligned against a reference and miss-alignments are interpreted as orientation, or placement errors. We have developed a more efficient implementation of the correcting method developed by . This enThe true N50 value can be determined when using simulated contigs by breaking incorrect scaffolds, this measure is denoted as TPN50. An analog to the TPN50 measure can be obtained by aligning the scaffolds against the known reference. Scaffolds (and contigs) are broken at mis-assembled or mis-scaffolded regions. This post-alignment metrics can be obtained from the assembly evaluation tool called QUAST  and it iUnfortunately the implementation of QUAST required more than 128GB of RAM to evaluate the NA12878 test case, and therefore could not be run. We wrote an alternative implementation of NA50 called ALN50 which is more efficient, but follows a similar framework. Both NA50 and ALN50 are found in Figure First the highest ALN50 is always found at bundle size 3 or 5. If the intent of the assembly is to maximize N50 then clearly no algorithm should be run with bundle size less than 3. However, as it was pointed out in both GAGE and QUAST ,38, N50 Additionally it can be seen that both OPERA and SILP2 have approximately the same TPN50 in the staph and chr14 test cases, however in rhodo, SILP2 clearly out-performs OPERA and MIP at all bundle sizes. It is not clear why SILP2 performs much better on rhodo, and approximately equivalent on the others. For the complete genome SILP2, OPERA and MIP reported an N50 of 26,235, 39,366, 26,235 respectively. This is consistent with the observations from the synthetic data sets.An alternative measure of the completeness of a scaffold is the number of genes aligned against the scaffold. For a given percentage of completeness the number of genes found in the corrected scaffold is an indicator of the usefulness of the genome.As seen in Table One key advantage of SILP2 over other scaffolding tools is its speed and scalability. Table On the staph, rhodo and chr14 datasets, it was observed that SILP2 was quicker at higher bundle sizes and no worse than OPERA or MIP at lower bundle sizes. The NA12878 testcase was extremely challenging for all methods and demonstrated the effect of heuristics on large test cases. It is clear from the reduced runtimes that all 3 methods activate some sort of heuristic at lower bundle sizes. The difference between SILP1 and SILP2 is evident at all bundle sizes.The NA12878 genome was also scaffolded by SILP2 using 20x coverage reads, with a runtime of 18,205 seconds at bundle size 1. Negligible improvement in accuracy over the 2x dataset was observed. From Table Metagenomics is the study of genetic material recovered from heterogeneous mixtures often found in nature. Just like in the de novo assembly of a single genome, the accuracy and size of the scaffolds is critical to subsequent analysis steps. Our ILP based solution is flexible enough to include new constraints and objectives to better serve this challenging scenario.In order to test this hypothesis a simulated metagenomic dataset was created utilizing the staph and rhodo genomes from the GAGE dataset. The simulated contigs used previously were mixed, and both sets of reads were aligned with varying fractions  of staph reads present. Again all three of the major scaffolding tools were tested, however additional weighting scenarios were implemented in SILP2.The runtime, MCC, SCFN50, TPN50 and ALN50 metrics are detailed for each of the compared methods in Table Interestingly all SILP2 variants fare much better than both OPERA, MIP and BAMBUS2 even with no staph reads present (this differs from results in Figure In both SILP2 variants and MIP it is observed that the TPN50 decreases as fewer staph reads are utilized. This is expected since there are fewer opportunities to connect staph contigs and both staph and rhodo contigs are used in the calculation of N50. There is no major differences between the variants of SILP2. The coverage based weight seems to improve MCC at the cost of a slightly lowered TPN50 when compared to no weights.This highly simplified test scenario is not designed to fully explore metagenomic scaffolding, rather to point out an opportunity to further external genome scaffolding algorithms.Scaffolding in an important step in the de novo assembly pipeline. Biologists rely on an accurate scaffold to perform many types of analysis. The larger the scaffold the more useful it will be to them. Recent advances in de novo assemblers has made it feasible to create draft assemblies for large mammalian genomes. We believe the SILP2, coupled with the most recent scalable assemblers will produce the largest and most complete assemblies. This is made possible utilizing non-serial dynamic programming approach to solve our robust ILP. The ILP formulation for the maximum likelihood model is shown to be flexible enough to handle metagenomic samples.The future work includes more thorough experimental validation of SILP2 and comparison BAMBUS2  on metag• ILP - Integer Linear Programming• MCC - Matthew's correlation coefficient• MIP - Mixed Integer Programming• NSDP - Non-serial Dynamic Programming• OGDF - Open Graph Drawing Framework• SQPR - a tree data structure used in graph algorithms to represent the 3-connected components of a graph https://github.com/jim-bo/silp2. This implementation relies on the CPLEX optimization library. The code used for generating most of the reported results, including the implementation of the ALN50 metric, is available at https://github.com/jim-bo/scafathon. The SILP2 source code along with a small test dataset can also be downloaded from http://dna.engr.uconn.edu/software/SILP2.A reference implementation of SILP2 is provided at JL developed and implemented the algorithms, ran the experiments, and wrote result section, HS developed algorithms, participate in writing the paper, and implemented parts of the code, IM and AZ developed algorithms wrote the paper, conceived and supervised implementation.Supplementary figures, methods, and tables are supplied in PDF format.Click here for file


Enzymes, as biological catalysts, form the basis of all forms of life. How these proteins have evolved their functions remains a fundamental question in biology. Over 100 years of detailed biochemistry studies, combined with the large volumes of sequence and protein structural data now available, means that we are able to perform large-scale analyses to address this question. Using a range of computational tools and resources, we have compiled information on all experimentally annotated changes in enzyme function within 379 structurally defined protein domain superfamilies, linking the changes observed in functions during evolution to changes in reaction chemistry. Many superfamilies show changes in function at some level, although one function often dominates one superfamily. We use quantitative measures of changes in reaction chemistry to reveal the various types of chemical changes occurring during evolution and to exemplify these by detailed examples. Additionally, we use structural information of the enzymes active site to examine how different superfamilies have changed their catalytic machinery during evolution. Some superfamilies have changed the reactions they perform without changing catalytic machinery. In others, large changes of enzyme function, in terms of both overall chemistry and substrate specificity, have been brought about by significant changes in catalytic machinery. Interestingly, in some superfamilies, relatives perform similar functions but with different catalytic machineries. This analysis highlights characteristics of functional evolution across a wide range of superfamilies, providing insights that will be useful in predicting the function of uncharacterised sequences and the design of new synthetic enzymes.  •Examining how enzyme function evolves using sequence, structure, and reaction mechanism data.•Quantifying changes in reaction mechanisms reveals how function has diverged in many superfamilies.•Homologous domains frequently use different catalytic residues, which sometimes perform the same enzyme chemistry.•This large-scale analysis has significance in protein function prediction and enzyme design. Enzyme-associated protein domains are found in nearly 70% of the superfamilies in the CATH Functional diversity can arise as a result of selective evolutionary pressures. The duplication of genetic material provides the necessary molecular elements needed to form additional and/or novel functions. Here we consider the divergence of enzyme functions.Early studies of protein families et al.N-Acetylneuraminate Lyase, Crotonase, and Vicinal Oxygen Chelate superfamilies) in which relatives share the same structural fold, or scaffold, but can catalyse different catalytic reactions Large-scale studies of the chemistries performed by different relatives in enzyme superfamilies  function within a superfamily and to examine from a structural perspective how these changes came about. The results of our analysis of 379 domain superfamilies are presented in an Enzyme Commission (EC) exchange matrix a. ConsisTo ascertain if there were significant under- or over-representation of certain changes, we compared the matrix of observed changes to an expectation model that simulates the chances of one function changing to another based on the EC numbers catalogued in FunTree, which also intrinsically takes into account the bias introduced by the sizeable differences in the granularity of the classification system. The ratio of the observed over expected changes is calculated see b. This sThe paucity of inter-class changes suggests that changing overall chemistry is more challenging than changing substrates during evolution. Perhaps it requires many complementary mutations to occur, each of which does not disrupt the enzyme's activity to the point of being deleterious to the fitness of the organism. Alternatively, only a very few residues might be candidates for changing the chemistry, whereas many could change the binding. Also, the order in which mutations occur might be critical We observe that 2994 unique enzymes  fall into 379 CATH domain superfamilies accounting for ~ 56%  of all domain sequences in CATH. This suggests that 2615 enzyme functions  have evolved from another function or from an ancestor with generic functionality, comprising over 87% of all functions. Furthermore, since 1779 of the 2994 EC 4 (59%) are associated with at least two superfamilies, this suggests that more than half of the enzyme functions have arisen in more than one superfamily during evolution. A caveat in this analysis is that some superfamilies in a given fold may be homologous. Prior to each CATH release, we perform HMM–HMM profile comparisons between all superfamily pairs to merge any closely related superfamilies. However, it could be that some close relationships are missed and therefore functions that apparently emerged in two different superfamilies could have in fact emerged in the same superfamily, and our values are over-estimated. Further analysis has shown that 585 of the 1779 EC 4 (~ 33%) associated with more than two superfamilies are from superfamilies within the same fold group.Though the EC numbering system is good for curating enzyme functions, it is not useful for making quantitative comparisons between reaction chemistries. By using EC-BLAST, we can quantify the functional changes observed in the EC exchange matrix by calculating similarities in bond order changes, reaction centres, and substrate/product sub-structures . The figwith changing substrates, we compared the average bond similarity score to the average sub-structure similarity score as calculated by EC-BLAST for each superfamily (To gain an overview of how different superfamilies are changing chemistry erfamily . Each po(i)Similar reactants with very different chemistry a and bA superfamily that has similar reactants but different bond changes is the Vanillyl-Alcohol Oxidase superfamily (CATH ID 1.10.45.10) . The funA superfamily that has similar reactants but different bond changes is the Vanillyl-Alcohol Oxidase superfamily (CATH ID 1.10.45.10) . The function evolves from vanillyl-alcohol oxidase (EC 1.1.3.38), in which three OH bonds and one CH bond are changed plus a change from a double to a single O–O bond to 4-methylphenol dehydrogenase (EC 1.17.99.2), in which one C–O bond is formed plus an R/S change in stereochemistry. The bond changes are therefore completely different. However, the reactants are rather similar, both including a six-membered carbon ring. Both reactions involve a common flavin adenine dinucleotide co-factor, with common steps in the enzyme mechanisms, but although both involve a histidine, this residue is not equivalent in the two proteins and the difference in chemistry occurs due to other residues recruited within the active-site cleft.(ii)Conserved bond order changes with very different reactants cIn contrast, in the Amidase Signature enzyme superfamily (CATH ID 3.90.1300.10), we observe a change from amidase (EC 3.5.1.4) to 6-aminohexanoate-cyclic-dimer hydrolase (EC 3.5.2.12) . Both reIn contrast, in the Amidase Signature enzyme superfamily (CATH ID 3.90.1300.10), we observe a change from amidase (EC 3.5.1.4) to 6-aminohexanoate-cyclic-dimer hydrolase (EC 3.5.2.12) . Both reactions share almost the same bond changes  but the reactants involved are very different. Although five of the seven catalytic residues are conserved, they are mostly located in loop regions, which presumably allow the active site to accommodate very different reactants, yet they perform the same chemistry.Below, we highlight a few specific examples to illustrate the different paradigms we observe:In automatically comparing the bond changes between two reactions, it is possible to catalogue the bond types that have been gained and those that are lost. Again using the phylogenetic trees and ancestral function estimation, it is possible to transverse the trees summarising across all superfamilies the changes in gain/loss of different bond types . The preBy far the most prevalent change in bond type is a change in chirality at a carbon chiral centre [C(R/S)], followed by the making or breaking of an H–O or a C–H bond. The most conserved bond change in two related reactions is the O–H bond change . The mosThe sequences and their functional annotations used in this analysis come from the reviewed section of UniProtKB with varying degrees of explicit experimental characterisation. Only a relatively small proportion has been experimentally validated. However, as part of the manual curation process, functional annotations are corroborated with the existing literature. Some annotations made by means of similarity to existing experimentally validated homologues may be incorrect or only partially correct Ideally, to understand how different functions evolve, catalytic mechanisms should be compared, but unfortunately, these are not well defined for many enzymes. However, we do know which residues in a binding site are conserved and involved in catalysis; thus, here we compare those catalytic residues and explore how they have changed during evolution. Information on catalytic residues was extracted from the CSA database for each CATH functional family, including known catalytic residues and other residues implicated in the chemistry, for example, stabilising an intermediate state. Comparisons of these residues within superfamilies, especially where the function has changed, revealed active-site diversity across a superfamily and determined to what extent changes in catalytic residues are associated with changes in chemistry and/or substrate specificity.A total of 101 (out of the 379) CATH enzyme superfamilies have at least two families with different functions in which one or more of the domains have literature-based catalytic residue annotations. Catalytic residues were compared in terms of both physiochemical similarity and equivalence in the sequence alignment or in three dimensions.P value < 2.2 × 10− 16 using a Welch one-way ANOVA test). This is also accompanied by a greater variation in enzyme function [measured by calculating the average number of different EC numbers  per superfamily in the Rossmann (12 EC 3 on average) or TIM (12 EC 3 on average) fold compared to remaining enzyme superfamilies (5 EC 3 on average)]. These observations are in agreement with recent analyses Nearly 72% of the 101 enzyme superfamilies have at least two functional families with different catalytic residues. A large proportion of functional family pairs  have a CMSS of 5 or less (out of 10). Of these, 71.54% are from superfamilies with either a triosephosphate isomerase (TIM) or a Rossmann fold, which are significantly more diverse than other folds, with median CMSS values of 1.2 and 2.95, respectively see , compareAlthough nearly three-quarters of the superfamilies showed changes in their catalytic residues in some functional families, we found that 40 out of the 101 superfamilies examined (39.6%) have at least one completely conserved catalytic residue found in equivalent positions in the sequence in all their functional families see . These rA change in enzyme function can be dramatic, that is, a change in the chemistry performed and in the substrate. Whilst changes in catalytic residues usually result in changes in enzyme function see , in mostPerhaps most interesting are the functional families found in 16 of the superfamilies, which have different catalytic residues yet perform the same enzyme chemistry on the same substrateTo examine the link between catalytic machinery and chemistry further, we also used EC-BLAST to determine whether a change in catalytic machinery was accompanied by a change in the reaction mechanism. EC-BLAST uses reaction mechanism information from IUBMB. We examined the bond change for 228 pairs of functional families for which there was sufficient information  has four functional families with the same reaction mechanisms  but different catalytic machineries. Relatives in all four families have the same aldehyde lyase enzymatic activity and their catalytic residues co-locate in the same active site at the top of the beta barrel. Two of their three catalytic residues are found in loops, with the third residue in a beta strand, except for one family whose both the two catalytic residues are in beta strands. Although the catalytic residues occur in different positions in the sequence, the spatial sites of residues having similar chemical properties and catalytic roles are close in the structure see . AlthougThe top-left quadrant in l-lactase dehydrogenase  and spinach glycolate oxidase (GOX) enzymes are two functional families from the same superfamily, where function changes are occurring within the same domain. FCB is a dehydrogenase (EC 1.1.2.3) whereas GOX is an oxidase (EC 1.1.3.15). Both are flavoprotein enzymes that catalyse the oxidation of different l-alpha-hydroxy acids. All relatives in the superfamily bind a flavin co-factor and have six conserved active-site residues cYeast P value of 2.77E-11) and in the mainly beta class .Although previous studies have examined the location of catalytic residues et al.P value of 6.64E-06). However, we found no significant difference between the mean normalised values of catalytic residues in coil regions for superfamilies in the innovable folds and all other alpha/beta class enzyme superfamilies , suggesting that many members of these alpha/beta class superfamilies may also be considered innovable.A total of 91% (343) of the 379 enzyme superfamilies in this study are diverse in their substrate specificity . Since a large proportion of these functional diverse enzyme superfamilies  are alpha/beta, the high proportion of catalytic residues in loops in these folds lends some support to the hypothesis in Dellus-Gur As many others before us have observed, we find that the evolution of enzyme function is extremely complex. However, by being able to take a broad view across a large and wide range of enzyme containing domain superfamilies, we are able to demonstrate some shared aspects. By bringing together classical analysis of relationships between sequence and structure with new qualitative measures of similarities of function, we can observe how some superfamilies are able to change chemistry, sub-substrate specificity, or combinations of the two. By performing detailed structural analysis of active-site residues, we can determine whether these changes occur due to modifications in the catalytic machinery and identify relatives that appear to diverge and then converge again to perform similar functions, whilst others are able to adapt their function without major changes to the active site.As with previous studies, we demonstrate that diverse relatives are more likely to be performing the same or similar chemistries on different substrates. However, dramatic changes in chemistry are observed. For nearly half the available superfamilies, at least one common catalytic residue was found in all relatives supporting the view that there is a tendency to conserve the chemistry. Some extreme cases of divergence in catalytic machinery may reflect the need to fine-tune the active-site residue repertoire to activate different substrates or stabilise different transition states. Alternately, cases where no similarity in catalytic machinery is observed may suggest very diverse evolutionary routes that converge on the same function or routes whereby divergence from a common catalytic machinery, perhaps resulting in a loss in efficiency in a particular relative, is followed by further mutations in different positions within the active site, giving rise to a different residue environment that has the ability to perform the same chemistry.The observations that we report here are crucial to understanding the molecular basis of function evolution and furthering function prediction methods for the plethora of uncharacterized sequences and in the application of the development of novel synthetic enzymes in biotechnology.The protocol for generating multiple sequence alignments, phylogenetic trees, and associated changes in function is based on that used in the construction of FunTree In order to avoid the problems associated with aligning very diverse relatives, FunTree derives phylogenetic trees using a multiple sequence alignment that is guided by multiple structure alignment of structurally coherent relatives. Structurally coherent relatives are defined as those that superpose within 9 Å RMSD. CATH identifies structurally similar groups (SSGs) comprising relatives within a superfamily clustering with a threshold of 9 Å RMSD. Structural representatives from across the superfamily were selected from CATH functional families. Functional families are identified within each superfamily using a novel agglomerative clustering method that groups sequences sharing similar sequence patterns that relate to specificity determining positions in the family Compared to previous work that used representatives of sequence clusters at 35% sequence identity, building up the alignment from representatives of functionally coherent clusters of domain sequences permitted more sequences to be included in the alignment and reduced the number of SSGs representing a domain superfamily.Phylogenetic trees for 379 structurally defined enzyme superfamilies defined by the CATH classification were generated using the CSA The enzyme functional annotations, combined with the phylogenetic tree, were used to infer the ancestral function at each node in the tree using the discrete ancestral character estimation algorithm with an equal rates model as implemented in the APE  The protein domains at the leaves in each tree were annotated with EC numbers A summaryThe CSA stores information on catalytic site residues derived from the literature and also from homology searches, and it defines them as a residue (1) with direct involvement in the catalytic mechanism, (2) affecting another residue or water molecule directly involved in the catalytic mechanism, (3) that stabilises a transition-state intermediate, and (4) that exerts an effect on a substrate/co-factor aiding catalysis. Residues involved in ligand binding are excluded unless they are involved in one of the above four functions Structural domains in functional families were annotated with CSA functional residues that had literature-based evidence. A functional family representative was chosen, by selecting the structural domain annotated with the most CSA functional residues.A subset of the 379 CATH version 3.5 enzyme superfamilies was created containing 101 superfamilies with CSA data for two or more functional families in order to make comparisons between at least two sets of experimentally validated catalytic sites in a superfamily.To compare the catalytic residues between two relatives, we pairwise aligned all functional family representative domains within each superfamily in the dataset with SSAP  The structural location of catalytic residues was examined using all the 379 superfamilies in the original dataset. The secondary structure of each catalytic residue was assigned using the DSSP programme and the BioPerl DSSP module The proportion of catalytic residues in each domain examined was calculated in each of these three assigned categories and normalised by the proportion of all residues in each of the categories [see Eq. (1) below].Eq. (1) is the NP of catalytic residues in each secondary structure category examined.Ccategory represents the number of catalytic residues in a particular secondary structure category, Ctotal represents the total number of catalytic residues, Rcategory represents the total number of residues in a particular secondary structure category, and Rtotal represents the total number of residues.For a given domain, The Wilcoxon rank-sum test in R was used to assess whether there was a statistically significant difference between the distributions of normalised values for catalytic residues in coil regions for superfamily members in each of the three major CATH classes .et al. To explore whether catalytic residues preferentially occur in the coil regions of innovative or functionally diverse superfamily members, we used the Wilcoxon rank-sum test to compare the distributions of catalytic residue proportions between “innovable” and “all other” superfamilies. The innovable superfamilies were defined as those belonging to the four folds described by Dellus-Gur A summary of changes involving oxidoreductases. All EC numbers in FunTree represented as nodes in a network ordered by EC class. Each change in function associated with a change to/from an oxidoreductase (as highlighted in the EC exchange matrix top right) is shown as an edge in the network (top left). The edges in the networks in the bottom row show the bond change, reaction centre, and sub-structure similarities, respectively, coloured using a grey scale where white is zero similarity and black is exactly the same.A summary of changes involving transferases. All EC numbers in FunTree represented as nodes in a network ordered by EC class. Each change in function associated with a change to/from an transferase (as highlighted in the EC exchange matrix top right) is shown as an edge in the network (top left). The edges in the networks in the bottom row show the bond change, reaction centre, and sub-structure similarities, respectively, coloured using a grey scale where white is zero similarity and black is exactly the same.A summary of changes involving hydrolases. All EC numbers in FunTree represented as nodes in a network ordered by EC class. Each change in function associated with a change to/from an hydrolase (as highlighted in the EC exchange matrix top right) is shown as an edge in the network (top left). The edges in the networks in the bottom row show the bond change, reaction centre, and sub-structure similarities, respectively, coloured using a grey scale where white is zero similarity and black is exactly the same.A summary of changes involving lyases. All EC numbers in FunTree represented as nodes in a network ordered by EC class. Each change in function associated with a change to/from a lyase (as highlighted in the EC exchange matrix top right) is shown as an edge in the network (top left). The edges in the networks in the bottom row show the bond change, reaction centre, and sub-structure similarities, respectively, coloured using a grey scale where white is zero similarity and black is exactly the same.A summary of changes involving isomerases. All EC numbers in FunTree represented as nodes in a network ordered by EC class. Each change in function associated with a change to/from an isomerase (as highlighted in the EC exchange matrix top right) is shown as an edge in the network (top left). The edges in the networks in the bottom row show the bond change, reaction centre, and sub-structure similarities, respectively, coloured using a grey scale where white is zero similarity and black is exactly the same.A summary of changes involving ligases. All EC numbers in FunTree represented as nodes in a network ordered by EC class. Each change in function associated with a change to/from an ligase (as highlighted in the EC exchange matrix top right) is shown as an edge in the network (top left). The edges in the networks in the bottom row show the bond change, reaction centre, and sub-structure similarities, respectively, coloured using a grey scale where white is zero similarity and black is exactly the same.Comparing bond order similarities by EC class. All EC numbers in FunTree represented as nodes in a network ordered by EC class. Each change in function associated with a change to/from each EC class is shown in each of the networks as an edge. The edge colour shows the reaction centre similarity score using a grey scale where white is zero similarity and black is exactly the same.Comparing reaction centre similarities by EC class. All EC numbers in FunTree represented as nodes in a network ordered by EC class. Each change in function associated with a change to/from each EC class is shown in each of the networks as an edge. The edge colour shows the reaction centre similarity score using a grey scale where white is zero similarity and black is exactly the same.Comparing sub-structure similarities by EC class. All EC numbers in FunTree represented as nodes in a network ordered by EC class. Each change in function associated with a change to/from each EC class is shown in each of the networks as an edge. The edge colour shows the sub-structure similarity score using a grey scale where white is zero similarity and black is exactly the same.Summary of Vanillyl-Alcohol Oxidase superfamily (CATH ID 1.10.45.10). (a) Overall reaction diagrams with sub-structures identified by SMSD coloured for the two reactions found in the superfamily: vanillyl-alcohol oxidase (EC 1.1.3.38) and 4-methylphenol dehydrogenase (EC 1.17.99.2). (b) A summary table of bond changes for each reaction.Summary of Amidase Signature enzyme superfamily (CATH ID 3.90.1300.10) reactions. (a) Overall reaction diagrams with sub-structures identified by SMSD coloured for two of the reactions found in the superfamily: amidase (EC 3.5.1.4) and 6-aminohexanoate-cyclic-dimer hydrolase (EC 3.5.2.12). (b) A summary table of bond changes for each reaction. (c) A summary table of conservation of catalytic residues in the sequences of the other enzymes in the superfamily, with a tick indication conservation and a cross indication that it is not conserved.Conservation of bond types between changes in function. The top 10 cumulative counts of bond types that remain the same between changes in function across all the changes observed in FunTree. The inset shows the distribution of the top 20 bond changes across all known reactions.Reaction centre. A first-order reaction centre is defined as the atoms involved in the bond change and those atoms directly connected to them. The reaction centre is highlighted in grey and the atoms that make up the reaction centre are highlighted in red.Flowchart of catalytic residue similarity analysis. The steps taken in calculating catalytic residue similarity values for all pairs of functional families in each superfamily analysed.Summary of specificity compared to overall reaction chemistry for each superfamily. An overall description of specificity compared to overall reaction chemistry is provided with to the CATH superfamily pages for further exploration of functional changes.The following are the supplementary data related to this article.


Traditionally, some teenagers and young adults with diabetes have not engaged well at diabetes appointments, giving rise to concerns about long-term health risks. We considered that apps might help this group of patients to improve preparation for, and therefore engagement at their appointments. Although there are already many apps for young people with type 1 diabetes (YPD), we thought that by supporting YPD themselves to develop apps, the resulting products would have greater “authenticity” and relevance.To test the feasibility of an online competition to (1) recruit and support YPD to develop apps (mobile or Internet based) to help prepare for clinic appointments, and (2) for these apps to be tested and rated by YPD.The “Diabetes App Challenge” was a United Kingdom (UK) national competition, run between June and October 2012 for teams including at least one YPD (aged 16-25) to pilot the design and development of apps for use by other YPD prior to clinic appointments. The competition was advertised by social media, email, AdWords and postings on the Diabetes UK website. Registrants for the competition were supported via email and discussion forum. After app development, other YPD were invited (November 2012-February 2013) to trial the apps, choose and use one prior to a clinic appointment, and review their experiences.P=.02). Just over half  said they would use their chosen app again and 4/5  would recommend it to a friend.Of 56 people (including 28 YPD) who expressed interest in the competition, 6 teams (14 people) developed and submitted an app. Two apps aimed to facilitate agenda setting in clinic consultations, 2 enabled data logging and 2 helped insulin dose calculation. Of 135 YPD who registered to trial the apps, 83 (61.5%) took part . Agenda setting apps were considered most useful for preparing for and setting the focus of clinic appointments (This competition to engage YPD in developing and reviewing apps proved successful. App designers and testers saw a need for a range of functions. However, this may, in part, reflect a lack of detailed knowledge of all existing apps and be limited by the technical skills of YPD. App competitions appear worth applying to other patient groups, but future competitions should include a review stage and perhaps focus on ideas for app design for subsequent professional implementation. There is widespread interest in harnessing the potential of apps to promote better self-care of young people with type 1 diabetes (YPD). However, websites and apps are likely to be most popular if they really engage and interest patients in terms of both style and content , and proMany YPD demonstrate poor blood glucose control , which iThe objective of this study was to evaluate a new way to engage YPD in designing and producing apps to improve engagement at diabetes clinic appointments. The aim of the Diabetes App Challenge was to test the feasibility of using a UK national online “competition” to (1) recruit and support YPD to design and develop apps to help set the focus for diabetes consultations, and (2) recruiting other YPD to test these apps.th May 2012) by the Cornwall & Plymouth National Research Ethics Service Committee of the National Health Service (NHS).Ethical approval for the study was granted  a UK competition in which YPD and teammates (“developers”) developed an app; and (2) YPD (“reviewers”) were invited to test and review the submitted apps. We could not predict how many apps would be submitted but anticipated up to 10 entries and had one app developed before the competition via a student project. This app was available (1) as an example for other developers, and (b) as one entrant for the competition and for review. In stage two, our target was to recruit up to 200 reviewers.Developer teams had to include at least one person aged 16-25 with type 1 diabetes living in the UK. Various online methods were used to raise awareness of the competition. Interested parties were directed to the project website for participant information, consent, and registration . MethodsFollowing expression of interest by email from YPD without app developing experience, and from app developers without diabetes, an email “match-making” service was offered to facilitate the creation of appropriate teams by the first author (EA). Teams were given links to useful resources, tips and suggestions, and were offered technical support through a website forum.The developers’ challenge was to create smartphone apps or websites that would be useful in preparing YPD for clinic appointments and help set the focus of the consultation. Applicants were shown the example of the first entrant website You + Your Diabetes , createdSubmitted apps were reviewed by the project team for suitability and accuracy before offering to YPD reviewers in stage two. Developers maintained and updated their apps through stage two and were able to monitor feedback from reviewers in the forum.The target audience was initially people aged 16-22 with type 1 diabetes living in the UK and with clinic appointments due within the 4 month recruitment period (Mid November – Mid February 2013). However, from mid-December, due to initially lower than expected registrations the upper age limit was extended from 22 to 25.Using similar methods to raise awareness as in stage 1, those previously made aware of the project were contacted with updates of stage 2. In addition, 50 university and 54 GP surgeries were emailed and others contacted by social media. Interested parties were directed to the project website which included information, consent, and registration for potential reviewers .Following completion of a baseline questionnaire, those registered were given login access to the website and discussion forum where links to the apps were located. YPD were asked to (1) examine and try the apps on offer, (2) choose one, and (3) use it in preparation for their upcoming clinic appointment . RegistrAs well as involving YPD in the development and review of apps, a small group comprising 4 YPD were involved in developing the research project to help ensure it was relevant to other YPD. They helped write and review participant consent forms to ensure accessibility, helped design the Diabetes App Challenge website, created videos to provide further information and were consulted throughout the duration of the project.For developers, website registration forms collected demographic data. After participation in the competition, feedback questions regarding competition experience were sent by email and other forum and email communication was collected for content analysis. Those who did not submit an app to the competition (“non-developers”) were followed up by email questionnaire to establish reasons for this and to learn for future competition delivery. For this feedback, non-developers were offered each a 20 GBP Amazon voucher.For reviewers, the website registration form requested (1) demographic data, (2) next appointment due date, (3) if they had missed or considered missing a clinic appointment and (4) “before-after" questions about satisfaction and confidence (piloting for a subsequent study). After app use, the website follow-up form requested information about the app they used including (1) initial attraction to that app, (2) ease of use, (3) perceived usefulness of the app in preparing for and focusing during their clinic appointment, (4) intentions to use the app again and recommend to a friend, (5) helpfulness of app features, and (6) follow-up questions. Additional follow-up questions via email included (1) importance placed on YPD-created apps and (2) further qualitative feedback on the Diabetes App Challenge experience.Descriptive responses to open-ended questions (email and online questionnaire) were analyzed using an inductive method of conventional content analysis to identify and summarize response meanings , and repSix teams (6 YPD and 8 teammates) submitted a completed app to the competition comprising two match-made teams, two self-made teams and two teams of one YPD each . Teams were located across England. The 6 YPD had a mean age of 20.33 (SD 3.27) and a mean of 8.75 years diabetes duration (SD 7.36) and the 8 teammates had a mean age of 21.50 (SD 2.73). Half of developers, both YPD and teammates, were computer science university students (7/14), 2 were in computer science employment (14%), 4 were students in other subjects (29%) and 1 in unknown employment (7%).In total 56 people registered interest to develop an app. Excluding enquiries with no further interest and offers of support from people without diabetes or technical skills, there were 23 teams of potential developers. These included 9 match-made teams, 11 teams of one YPD and 3 self-made teams. Nineteen teams continued corresponding with EA and 8 teams described plans to develop an app. Of those, 25% who expressed initial interest submitted apps .Of the 42 potential developers, a third (15/42) were recruited from emails to clinicians, universities, and others, 7 from Diabetes UK, 4 from Facebook/Twitter, 2 were known contacts of the project, 1 from Google AdWords. A third (13/42) could not be traced to the original advertising source.Nineteen (68%) of the 28 potential developers who did not submit an app responded to email follow-up. The reasons for not completing an app were lack of time or other commitments (11/19), communication or conflict of ideas within match-made teams (6/19), realization that their design already existed (1/19), and app coding difficulties (1/19). Although incomplete or just ideas, seven made reference to their app plans, including four data-logging, two notes/ agenda setting, and one diabetes game.The 6 submitted apps were, Diabetes Logger , DiabeteAcross the course of the project EA sent an average of 43 emails to each developer . Developers sent EA 12 emails each . Two teams requested support regarding formula accuracy of insulin dose calculations, and one team technical support regarding coding. The most common difficulty cited for developers was time, mostly limited by university assignments or employment. Other difficulties included design and technical skills and team communication.YPD developers took part in the competition to make it easier for others to manage their appointments and condition, as well teammates gained app project experience .“I have had problems in the past with showing my BG results to consultants and have had problems recording them”“there is absolutely no point whatsoever in going to a diabetic clinic appointment at a hospital without an accurate record of blood sugar etc. as there is really very little anyone can do for you without it”“keeping track of lots of data was a real pain, and having to do so to make the consultations useful, quite time consuming”“The main reason for me to want to make this app was in the hope that it would help someone with their new diagnosis”“I was motivated by the challenge of deigning an app for people like myself, who have type 1 in the hope that in some way it would make there life better of easier”Of the 135 YPD reviewer registrants, 83 (62%) took part in trialling and reviewing an app. Reviewers’ mean age was 18.98 (SD 2.58), 55% were female, and mean years since diagnosis was 7.08 (SD 5.05) ranging from 2 months to over 20 years. Fifty-one (62%) had attended a clinic appointment within the last 3 months, 27 (33%) within 4-8 months, 4 (5%) over 9 months ago. Twelve (14%) had missed, and 19 (23%) had considered missing clinic appointments at some time because they did not think it was worth attending, while 47 (57%) had never considered it.Reviewers were made aware of the Diabetes App Challenge through (1) Diabetes UK (22/83), (2) Twitter (14/83), (3) Facebook (13/83), (4) word of mouth from friend or family (6/83), (5) email, (8/83), (6) hospital (5/83), (7) newspaper (4/83), (8) doctor’s surgery/ letter (5/83), (9) online search (4/83), (10) diabetes discussion forum (1/83), and (11) university news (1/83).Reviewers looked at an average of 3 apps each before making a selection (based on self-report and tracking logs). The three most popular apps chosen by reviewers each offered a different function: Diabetes Logger (n=25)m a data recording app; You + Your Diabetes (n=24), a notes/ agenda setting app; and Insulin Calc (n=17), an insulin dose calculator app .F2,80=5.72, P=.01). Comments from 61/83 reviewers reflect these scores.Over half of reviewers  thought their chosen app was useful or very useful for preparing for or setting the focus of their clinic appointment. Notes/ agenda setting apps were considered more useful  for clinic appointments than data logging  and insulin dose calculator  (P=.52) nor recommend to a friend (P=.40). Overall, reviewers indicated that the apps were worth trialling but a few felt improvements or amendments were needed before regular use.Just over half of reviewers intended to use the app they had chosen again  and most intended to recommend the chosen app to a friend . No significant differences were found between app functions and intention to use again . Most reviewers  thought their chosen app was easy or very easy to use. This varied from 100% for two apps (You + Your Diabetes and T1NDA) to 33% (27/83) for another. Reviewers’ felt the easiest to use apps were self-explanatory and simple to understand. The other apps were also considered easy to use but with some suggestions to improve the user-interface.Across the apps, there was a significant positive correlation between ease of use and usefulness  setting targets and viewing trends, (2) ease of recording and tracking data, and (3) data storage in one mobile location without need for logbook or pen/ paper; for the insulin dose calculation apps (1) simplicity and ease of use, (2) accuracy and trust of calculator, and (3) all in one calculation (carbs and insulin); for the notes/ agenda setting apps (1) the topic prompts to identity and remember what to discuss at appointment, (2) simple layout and ease of use, and (3) ability to document and review notes.Of the 83 reviewers, 34 (41%) responded to additional follow-up. Most of these  felt it was important or very important that the apps were created by YPD. In additional comments  much importance was placed on app design (not necessarily development) by diabetic peers because of a mutual understanding of the needs, condition and experiences in order for the apps to offer the most accurate features and details. Two reviewers felt that apps created by like-minded people were reassuring . A few mentioned the importance of this age group designing the apps from their perspectives; however for other reviewers age was not important as older people with diabetes experience similar issues. A few felt no importance for the apps to be designed by YPD as long as the needs were met, it worked well and looked good, and YPD feedback shaped the design.The most important finding of the Diabetes App Challenge was confirmation of the feasibility of recruiting YPD through an online competition in a relatively short space of time, and with optional support, to develop their own apps to improve preparation for diabetes appointments. We had thought that an online competition would be quicker, more cost effective, and involve larger numbers of YPD, than methods based on a user-panel informing the design of professionally developed app ,26. We tThe need for YPD, and not just professionals, to be involved in app design and development was emphasised by the partly unexpected range of apps submitted. Originally, we had not anticipated data recording or insulin dose calculation apps as among the tools to engage YPD in preparation for clinic appointments. Although notes and agenda setting items were featured within most of the submissions, only one of the five other apps (excluding the student example) had consultation agenda setting as a principal function. However, this might be because the YPD who designed these apps considered technical issues to be paramount in being able to engage fully at their appointments. In support of this, some reviewers commented that being able to show the doctor their results on a mobile, and others that helping them deal with the problem of calculating insulin doses, gave them more control and so empowered them in the consultation.Another significant finding was that the user-developer method we employed was considered important by two-thirds of reviewers. The direct “bottom up” process of peer innovation  was valued, although some felt a more “professional” interface was needed.The study also provided useful information about how to advertise and recruit for a competition. The most effective methods of advertising the competition were university computer science department emails and Diabetes UK online, whereas paid online advertising was considered expensive and ineffective, costing GBP 1700, and resulted in only one potential developer recruited.A range of unexpected findings, challenges and limitations were also evident in this study. A variety of apps already existed for recording blood glucose, help with carbohydrate and calorie calculations , and we The apps that were produced may also have represented the “art of the possible”, since technical ability was cited as a potential limitation to what could be produced. For example, this may have accounted for a lack of any social media element to the apps. YPD may also have been more adventurous in their ideas if others with greater expertise and resources were to create the apps. Therefore, perhaps professional developer collaborations, or competitions in which YPD just submit ideas for design, rather than actually implement apps, could be the best solution in a future competition.A probable limitation on the number of apps submitted was the time of year in which the competition took place. The study was scheduled to coincide with the UK summer term and holidays with the intention to “capture” students with available time and interest. However, many students still cited university commitments as reasons for non-participation or withdrawal. Our timescale was also limited by the funding and ethical approval, but a competition run earlier in the year may have attracted greater numbers.We successfully recruited a large number of reviewers, and while we failed to reach the target of 200 reviewers in the time available, we think our pilot study clearly confirms the feasibility of this approach. The main time constraint was the requirement to test apps prior to the next booked diabetes clinic appointment. Without this fixed requirement, and by recruiting over a longer period, we would have been able to recruit our target of 200 YPD to test apps.Diabetes UK and social media platforms Twitter and Facebook were most effective for raising awareness to reviewers. Reviewer participants were self-selected, indicating pre-interest in their diabetes management, yet over a third had previously missed or considered missing a clinic appointment. “Did not attend” rates vary from one clinic to another and over time  making iReviewers chose evenly between the 3 main functions of the 6 apps which were suited to different YPD needs for (1) remembering what to ask at appointments, (2) simplifying insulin dose calculations, and (3) easier observation of blood glucose trends. As anticipated in the context of the design specification, notes/ agenda setting apps were perceived as most useful for clinic appointment focus and preparation, in particular, their category prompts for stimulating reflection about areas of concern and reminders to raise issues at the appointment. Despite a large market of diabetes-specific apps (via iTunes and Google Play) none that prioritise this function appeared to be available in 2013 . Some inLastly, the online user-review method enabled larger scale remote recruitment, comparable to online usability testing, a common method of assessing the user experience of websites and apps . The anoThis pilot study confirmed the feasibility of engaging YPD in a competition to design and test apps to enhance preparation for clinic appointments. A range of needs were identified in the apps that were designed and some of our preconceptions about likely app functions were challenged. This study strongly supports the idea that YPD should be involved in designing apps for use by YPD, but it may be more appropriate for the primary role of the patients to be to advise on design rather than implementation. It will be particularly important to determine whether competitive app design and evaluation could engage more hard to reach YPD who are at highest risk from poor control of diabetes, as opposed to more self-selected enthusiasts who engaged with this project.