73 research outputs found
Efficacy and safety of the combination of reduced duration prophylaxis followed by immuno-guided prophylaxis to prevent cytomegalovirus disease in lung transplant recipients (CYTOCOR STUDY): an open-label, randomised, non-inferiority clinical trial.
INTRODUCTION:
Prolonged use of antivirals to prevent the development of cytomegalovirus (CMV) disease in lung transplant patients has been shown to have significant side effects, for which alternatives are being sought to reduce their use. The monitoring of cell immunity against CMV could be an alternative as it has shown to be useful in identifying transplant patients at low risk of infection, who could benefit from shorter prophylaxis. The aim of the CYTOCOR study is to demonstrate that the combination of a reduced prophylaxis strategy with subsequent CMV-specific immunological monitoring would allow CMV infection to be controlled in lung transplant patients as effectively as the usual strategy (prophylaxis followed by pre-emptive therapy), while reducing the side effects of antivirals due to the shorter duration of prophylaxis.
METHODS AND ANALYSIS:
Phase III randomised, open, multicentre, parallel, non-inferiority clinical trial to study the efficacy and safety of the combination of a prophylaxis strategy up to month +3 post-transplant followed by immuno-guided prophylaxis using the QuantiFERON-CMV technique up to month +12 post-transplant to prevent CMV disease in CMV-seropositive lung transplant recipients. This strategy will be compared with a combination of a usual prophylaxis strategy up to month +6 post-transplant followed by pre-emptive therapy up to month +12. To study the incidence of CMV disease, patients will be followed up to 18 months post-transplantation. A total of 150 patients are expected to be recruited for the study.
ETHICS AND PUBLIC DISSEMINATION:
The clinical trial has been approved by the Research Ethics Committees and authorised by the Spanish Agency of Medicines and Medical Devices (AEMPS).If the hypothesis of this clinical trial is verified, the dissemination of the results could change clinical practice by increasing knowledge about the safety and efficacy of discontinuing valganciclovir prophylaxis in lung transplant recipient
COVID-19 Clinical Profile in Latin American Migrants Living in Spain: Does the Geographical Origin Matter?
COVID-19; Latin America; SeverityCOVID-19; Amèrica Llatina; GravetatCOVID-19; América Latina; GravedadThe aim of this study was to describe and compare the clinical characteristics of hospitalized patients with COVID-19 pneumonia according to their geographical origin. This is a retrospective case-control study of hospitalized patients with confirmed COVID-19 pneumonia treated at Vall d’Hebron University Hospital (Barcelona) during the first wave of the pandemic. Cases were defined as patients born in Latin America and controls were randomly selected among Spanish patients matched by age and gender. Demographic and clinical variables were collected, including comorbidities, symptoms, vital signs and analytical parameters, intensive care unit admission and outcome at 28 days after admission. Overall, 1080 hospitalized patients were registered: 774 (71.6%) from Spain, 142 (13.1%) from Latin America and the rest from other countries. Patients from Latin America were considered as cases and 558 Spanish patients were randomly selected as controls. Latin American patients had a higher proportion of anosmia, rhinorrhea and odynophagia, as well as higher mean levels of platelets and lower mean levels of ferritin than Spanish patients. No differences were found in oxygen requirement and mortality at 28 days after admission, but there was a higher proportion of ICU admissions (28.2% vs. 20.2%, p = 0.0310). An increased proportion of ICU admissions were found in patients from Latin America compared with native Spanish patients when adjusted by age and gender, with no significant differences in in-hospital mortality.Isabel Campos-Varela’s research activity is funded by grant PI19/00330 from Instituto de Salud Carlos III. CIBERehd is supported by Instituto de Salud Carlos III. The work was independent of all funding. This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors
Towards a TILLING platform for functional genomics in Piel de Sapo melons
Background
The availability of genetic and genomic resources for melon has increased significantly, but functional genomics resources are still limited for this crop. TILLING is a powerful reverse genetics approach that can be utilized to generate novel mutations in candidate genes. A TILLING resource is available for cantalupensis melons, but not for inodorus melons, the other main commercial group.
Results
A new ethyl methanesulfonate-mutagenized (EMS) melon population was generated for the first time in an andromonoecious non-climacteric inodorus Piel de Sapo genetic background. Diverse mutant phenotypes in seedlings, vines and fruits were observed, some of which were of possible commercial interest. The population was first screened for mutations in three target genes involved in disease resistance and fruit quality (Cm-PDS, Cm-eIF4E and Cm-eIFI(iso)4E). The same genes were also tilled in the available monoecious and climacteric cantalupensis EMS melon population. The overall mutation density in this first Piel de Sapo TILLING platform was estimated to be 1 mutation/1.5 Mb by screening four additional genes (Cm-ACO1, Cm-NOR, Cm-DET1 and Cm-DHS). Thirty-three point mutations were found for the seven gene targets, six of which were predicted to have an impact on the function of the protein. The genotype/phenotype correlation was demonstrated for a loss-of-function mutation in the Phytoene desaturase gene, which is involved in carotenoid biosynthesis.
Conclusions
The TILLING approach was successful at providing new mutations in the genetic background of Piel de Sapo in most of the analyzed genes, even in genes for which natural variation is extremely low. This new resource will facilitate reverse genetics studies in non-climacteric melons, contributing materially to future genomic and breeding studies.González, M.; Xu, M.; Esteras Gómez, C.; Roig Montaner, MC.; Monforte Gilabert, AJ.; Troadec, C.; Pujol, M.... (2011). Towards a TILLING platform for functional genomics in Piel de sapo melons. BMC Research Notes. 4(289):289-299. doi:10.1186/1756-0500-4-289S2892994289The International Cucurbit Genomics Initiative (ICuGI). [ http://www.icugi.org ]González-Ibeas D, Blanca J, Roig C, González-To M, Picó B, Truniger V, Gómez P, Deleu W, Caño-Delgado A, Arús P, Nuez F, García-Mas J, Puigdomènech P, Aranda MA: MELOGEN: an EST database for melon functional genomics. BMC Genomics. 2007, 8: 306-10.1186/1471-2164-8-306.Fita A, Picó B, Monforte A, Nuez F: Genetics of Root System Architecture Using Near-isogenic Lines of Melon. J Am Soc Hortic Sci. 2008, 133: 448-458.Fernandez-Silva I, Eduardo I, Blanca J, Esteras C, Picó B, Nuez F, Arús P, Garcia-Mas J, Monforte AJ: Bin mapping of genomic and EST-derived SSRs in melon (Cucumis melo L.). Theor Appl Genet. 2008, 118: 139-150. 10.1007/s00122-008-0883-3.Deleu W, Esteras C, Roig C, González-To M, Fernández-Silva I, Blanca J, Aranda MA, Arús P, Nuez F, Monforte AJ, Picó MB, Garcia-Mas J: A set of EST-SNPs for map saturation and cultivar identification in melon. BMC Plant Biol. 2009, 9: 90-10.1186/1471-2229-9-90.Mascarell-Creus A, Cañizares J, Vilarrasa J, Mora-García S, Blanca J, González-Ibeas D, Saladié M, Roig C, Deleu W, Picó B, López-Bigas N, Aranda MA, Garcia-Mas J, Nuez F, Puigdomènech P, Caño-Delgado A: An oligo-based microarray offers novel transcriptomic approaches for the analysis of pathogen resistance and fruit quality traits in melon (Cucumis melo L.). BMC Genomics. 2009, 10: 467-10.1186/1471-2164-10-467.Blanca JM, Cañizares J, Ziarsolo P, Esteras C, Mir G, Nuez F, Garcia-Mas J, Pico B: Melon transcriptome characterization. SSRs and SNPs discovery for high throughput genotyping across the species. Plant Genome. 2011, 4 (2): 118-131. 10.3835/plantgenome2011.01.0003.González VM, Benjak A, Hénaff EM, Mir G, Casacuberta JM, Garcia-Mas J, Puigdomènech P: Sequencing of 6.7 Mb of the melon genome using a BAC pooling strategy. BMC Plant Biology. 2010, 10: 246-10.1186/1471-2229-10-246.Moreno E, Obando JM, Dos-Santos N, Fernández-Trujillo JP, Monforte AJ, Garcia-Mas J: Candidate genes and QTLs for fruit ripening and softening in melon. Theor Appl Genet. 2007, 116: 589-602.Essafi A, Díaz-Pendón JA, Moriones E, Monforte AJ, Garcia-Mas J, Martín-Hernández AM: Dissection of the oligogenic resistance to Cucumber mosaic virus in the melon accession PI 161375. Theor Appl Genet. 2009, 118: 275-284. 10.1007/s00122-008-0897-x.Comai L, Henikoff S: TILLING: practical single-nucleotide mutation discovery. Plant J. 2006, 45: 684-94. 10.1111/j.1365-313X.2006.02670.x.Cooper JL, Till BJ, Laport RG, Darlow MC, Kleffner JM, Jamai A, El-Mellouki T, Liu S, Ritchie R, Nielsen N, et al: TILLING to detect induced mutations in soybean. BMC Plant Biol. 2008, 8 (1): 9-10.1186/1471-2229-8-9.Dalmais M, Schmidt J, Le Signor C, Moussy F, Burstin J, Savois V, Aubert G, de Oliveira Y, Guichard C, Thompson R, Bendahmane A: UTILLdb, a Pisum sativum in silico forward and reverse genetics tool. Genome Biol. 2008, 9: R43-10.1186/gb-2008-9-2-r43.Dierking EC, Bilyeu KD: New sources of soybean meal and oil composition traits identified through TILLING. BMC Plant Biol. 2009, 9: 89-10.1186/1471-2229-9-89.Perry J, Brachmann A, Welham T, Binder A, Charpentier M, Groth M, Haage K, Markmann K, Wang TL, Parniske M: TILLING in Lotus japonicus identified large allelic series for symbiosis genes and revealed a bias in functionally defective ethyl methanesulfonate alleles toward glycine replacements. Plant Physiol. 2009, 151 (3): 1281-1291. 10.1104/pp.109.142190.Caldwell DG, McCallum N, Shaw P, Muehlbauer GJ, Marshall DF, Waugh R: A structured mutant population for forward and reverse genetics in Barley (Hordeum vulgare L.). Plant J. 2004, 40 (1): 143-150. 10.1111/j.1365-313X.2004.02190.x.Henikoff S, Bradley JT, Comai L: TILLING. Traditional mutagenesis meets functional genomics. Plant Physiol. 2004, 135: 630-636. 10.1104/pp.104.041061.Wu JL, Wu C, Lei C, Baraoidan M, Bordeos A, Madamba MR, Ramos-Pamplona M, Mauleon R, Portugal A, Ulat VJ, et al: Chemical- and irradiation-induced mutants of indica rice IR64 for forward and reverse genetics. Plant Mol Biol. 2005, 59 (1): 85-97. 10.1007/s11103-004-5112-0.Slade AJ, Fuerstenberg SI, Loeffler D, Steine MN, Facciotti D: A reverse genetic, nontransgenic approach to wheat crop improvement by TILLING. Nat Biotechnol. 2005, 23: 75-81. 10.1038/nbt1043.Till BJ, Cooper J, Tai TH, Colowit P, Greene EA, Henikoff S, Comai L: Discovery of chemically induced mutations in rice by TILLING. BMC Plant Biol. 2007, 7: 19-10.1186/1471-2229-7-19.Xin Z, Wang ML, Barkley NA, Burow G, Franks C, Pederson G, Burke J: Applying genotyping (TILLING) and phenotyping analyses to elucidate gene function in a chemically induced sorghum mutant population. BMC Plant Biol. 2008, 8: 103-10.1186/1471-2229-8-103.Dong C, Dalton-Morgan J, Vincent K, Sharp P: A modified TILLING method for wheat breeding. Plant Genome. 2009, 2: 39-47. 10.3835/plantgenome2008.10.0012.Sestili F, Botticella E, Bedo Z, Phillips A, Lafiandra D: Production of novel allelic variation for genes involved in starch biosynthesis through mutagenesis. Mol Breeding. 2010, 25: 145-154. 10.1007/s11032-009-9314-7.Watanabe S, Mizoguchi T, Aoki K, Kubo Y, Mori H, Imanishi S, Yamazaki Y, Shibata D, Ezura H: Ethylmethanesulfonate (EMS) mutagenesis of Solanum lycopersicum cv. Micro-Tom for large-scale mutant screens. Plant Biotech. 2007, 24: 33-38. 10.5511/plantbiotechnology.24.33.Elias R, Till BJ, Mba Ch, Al-Safadi B: Optimizing TILLING and Ecotilling techniques for potato (Solanum tuberosum L). BMC Res Notes. 2009, 2: 141-10.1186/1756-0500-2-141.Piron F, Nicolaı M, Minoıa S, Piednoir E, Moretti A, Salgues A, Zamir D, Caranta C, Bendahmane A: An induced mutation in tomato eIF4E leads to immunity to two Potyviruses. PLoS ONE. 2010, 5 (6): e11313-10.1371/journal.pone.0011313.Himelblau E, Gilchrist EJ, Buono K, Bizell C, Mentzer L, Vogelzang R, Osborn T, Amasino RM, Parkin IAP, Haughn : Forward and reverse genetics of papid cycling Brassica oleracea. Theor Appl Genet. 2009, 118: 953-961. 10.1007/s00122-008-0952-7.Stephenson P, Baker D, Girin T, Perez A, Amoah S, King GJ, Østergaard L: A rich TILLING resource for studying gene function in Brassica rapa. BMC Plant Biol. 2010, 10: 62-10.1186/1471-2229-10-62.Pitrat M: Melon (Cucumis melo L.). Handbook of Crop Breeding Vol I. Vegetables. Edited by: Prohens J, Nuez F. 2008, New York:Springer, 283-315.Dahmani-Mardas F, Troadec Ch, Boualem A, Leveque S, Alsadon AA, Aldoss AA, Dogimont C, Bendahman A: Engineering Melon Plants with Improved Fruit Shelf Life Using the TILLING Approach. PLoS ONE. 2010, 5: e15776-10.1371/journal.pone.0015776.Nieto C, Piron F, Dalmais M, Marco CF, Moriones E, Gómez-Guillamón ML, Truniger V, Gómez P, Garcia-Mas J, Aranda MA, Bendahmane A: EcoTILLING for the identification of allelic variants of melon eIF4E, a factor that controls virus susceptibility. BMC Plant Biol. 2007, 7: 34-10.1186/1471-2229-7-34.Qin G, Gu H, Ma L, Peng Y, Deng XW, Chen Z, Qu LJ: Disruption of phytoene desaturase gene results in albino and dwarf phenotypes in Arabidopsis by impairing chlorophyll, carotenoid, and gibberellin biosynthesis. Cell Res. 2007, 17: 471-482. 10.1038/cr.2007.40.Codons Optimized to Deliver Deleterious Lesions (CODDLe). [ http://www.proweb.org/input ]Lasserre E, Bouquin T, Hernández JA, Bull J, Pech JC, Balague C: Structure and expression of three genes encoding ACC oxidase homologs from melon (Cucumis melo L.). Mol Gen Genet. 1996, 251 (1): 81-90.Giovannoni JJ: Fruit ripening mutants yield insights into ripening control. Curr Opin Plant Biol. 2007, 10: 1-7. 10.1016/j.pbi.2006.11.012.Davuluri GR, van Tuinen A, Mustilli AC, Manfredonia A, Newman R, Burgess D, Brummell DA, King SR, Palys J, Uhlig J, Pennings HMJ, Bowler C: Manipulation of DET1 expression in tomato results in photomorphogenic phenotypes caused by post-transcriptional gene silencing. Plant J. 2004, 40: 344-354. 10.1111/j.1365-313X.2004.02218.x.Wei S, Li X, Gruber MI, Li R, Zhou R, Zebarjadi A, Hannoufa A: RNAi-mediated suppression of DET1 alters the levels of carotenoids and sinapate esters in seeds of Brassica napus. J Agric Food Chem. 2009, 57 (12): 5326-5333. 10.1021/jf803983w.Wang TW, Zhang CG, Wu W, Nowack LM, Madey E, Thompson JE: Antisense suppression of deoxyhypusine synthase in tomato delays fruit softening and alters growth and development DHS mediates the first of two sequential enzymatic reactions that activate eukaryotic translation initiation factor-5A. Plant Physiol. 2005, 138: 1372-1382. 10.1104/pp.105.060194.Ng PC, Henikoff S: SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003, 31 (13): 3812-3814. 10.1093/nar/gkg509.Guzman P, Ecker JR: Exploiting the triple response of Arabidopsis to identify ethylene-related mutants. The Plant Cell. 1990, 2: 513-523.Henikoff S, Comai L: Single-nucleotide mutations for plant functional genomics. Ann Rev Plant Biol. 2003, 54: 375-401. 10.1146/annurev.arplant.54.031902.135009.Greene EA, Codomo CA, Taylor NE, Henikoff JG, Till BJ, Reynolds SH, Enns LC, Burtner C, Johnson JE, Odden AR, et al: Spectrum of chemically induced mutations from a large-scale reverse genetic screen in Arabidopsis. Genetics. 2003, 164 (2): 731-740.Britt AB: DNA damage and repair in plants. Annu Rev Plant Physiol Plant Mol Biol. 1996, 47: 75-100. 10.1146/annurev.arplant.47.1.75.Truniger V, Nieto C, González-Ibeas D, Aranda M: Mechanism of plant eIF4E-mediated resistance against a Carmovirus (Tombusviridae): cap-independent translation of a viral RNA controlled in cis by an (a)virulence determinant. Plant J. 2008, 56 (5): 716-727. 10.1111/j.1365-313X.2008.03630.x.Gao Z, Johansen E, Eyers S, Thomas CL, Ellis THN, Maule AJ: The potyvirus recessive resistance gene, sbm1, identifies a novel role for translation initiation factor eIF4E in cell-to-cell trafficking. Plant J. 2004, 40 (3): 376-385. 10.1111/j.1365-313X.2004.02215.x.Kang BC, Yeam I, Frantz JD, Murphy JF, Jahn MM: The pvr1 locus in Capsicum encodes a translation initiation factor eIF4E that interacts with Tobacco etch virus VPg. Plant J. 2005, 42 (3): 392-405. 10.1111/j.1365-313X.2005.02381.x.Ruffel S, Gallois J, Lesage M, Caranta C: The recessive potyvirus resistance gene pot-1 is the tomato orthologue of the pepper pvr2-eiF4 genes. Mol Genet Genom. 2005, 274 (4): 346-353. 10.1007/s00438-005-0003-x.Nicaise V, German-Retana S, Sanjuán R, Dubrana MP, Mazier M, Maisonneuve B, Candresse T, Caranta C, LeGall O: The Eukaryotic Translation Initiation Factor 4E Controls Lettuce Susceptibility to the Potyvirus Lettuce mosaic virus1. Plant Physiol. 2003, 132: 1272-1282. 10.1104/pp.102.017855.Esteras C, Pascual L, Saladie M, Dogimont C, Garcia-Mas J, Nuez F, Picó B: Use of Ecotilling to identify natural allelic variants of melon candidate genes involved in fruit ripening. Proceedings Plant GEM8 Lisbon. 2009Levin I, Frankel P, Gilboa N, Tanny S, Lalazar A: The tomato dark green mutation is a novel allele of the tomato homolog of the DEETIOLATED1 gene. Theor Appl Genet. 2003, 106: 454-460.Kolotilin I, Koltai H, Tadmor Y, Bar-Or C, Reuveni M, Meir A, Nahon S, Shlomo S, Chen L, I Levin: Transcriptional profiling of high pigment-2dg tomato mutant links early fruit plastid biogenesis with its overproduction of phytonutrients. Plant Physiol. 2007, 145: 389-401. 10.1104/pp.107.102962
Genome-wide BAC-end sequencing of Cucumis melo using two BAC libraries
<p>Abstract</p> <p>Background</p> <p>Although melon (<it>Cucumis melo </it>L.) is an economically important fruit crop, no genome-wide sequence information is openly available at the current time. We therefore sequenced BAC-ends representing a total of 33,024 clones, half of them from a previously described melon BAC library generated with restriction endonucleases and the remainder from a new random-shear BAC library.</p> <p>Results</p> <p>We generated a total of 47,140 high-quality BAC-end sequences (BES), 91.7% of which were paired-BES. Both libraries were assembled independently and then cross-assembled to obtain a final set of 33,372 non-redundant, high-quality sequences. These were grouped into 6,411 contigs (4.5 Mb) and 26,961 non-assembled BES (14.4 Mb), representing ~4.2% of the melon genome. The sequences were used to screen genomic databases, identifying 7,198 simple sequence repeats (corresponding to one microsatellite every 2.6 kb) and 2,484 additional repeats of which 95.9% represented transposable elements. The sequences were also used to screen expressed sequence tag (EST) databases, revealing 11,372 BES that were homologous to ESTs. This suggests that ~30% of the melon genome consists of coding DNA. We observed regions of microsynteny between melon paired-BES and six other dicotyledonous plant genomes.</p> <p>Conclusion</p> <p>The analysis of nearly 50,000 BES from two complementary genomic libraries covered ~4.2% of the melon genome, providing insight into properties such as microsatellite and transposable element distribution, and the percentage of coding DNA. The observed synteny between melon paired-BES and six other plant genomes showed that useful comparative genomic data can be derived through large scale BAC-end sequencing by anchoring a small proportion of the melon genome to other sequenced genomes.</p
Infection-related and -unrelated malignancies, HIV and the aging population
Funding Information: Conflicts of interest: JR reports personal fees from Abbvie, Bionor, BMS, Boehringer, Gilead, Merck, Janssen, Tobira, Tibotec and ViiV, outside the submitted work. OK has received honoraria, consultancy and/or lecture fees from Abbott, Gilead, GSK, Janssen, Merck, Tibotec and Viiv outside the submitted work. All other authors state no commercial or other associations that may pose a conflict of interest. Funding: Primary support for EuroSIDA is provided by the European Commission BIOMED 1 (CT94-1637), BIOMED 2 (CT97-2713), 5th Framework (QLK2-2000-00773), 6th Framework (LSHP-CT-2006-018632) and 7th Framework (FP7/2007?2013; EuroCoord n? 260694) programmes. Current support also includes unrestricted grants from Janssen R&D, Merck and Co. Inc., Pfizer Inc. and GlaxoSmithKline LLC. The participation of centres in Switzerland was supported by The Swiss National Science Foundation (Grant 108787). The authors have no financial disclosures to make. Author contributions: LS developed the project, analysed the data, and was responsible for writing the manuscript. ?HB and OK contributed to the study design and analysis, interpretation of the data and writing of the manuscript. JL proposed the project and contributed to the study design, ideas for analysis, interpretation of the data and writing of the manuscript. BL, PD, AC, JR, BK, JT and IK contributed to national coordination, study design and writing of the manuscript. AM supervised the project and contributed to the study design and analysis, interpretation of the data and writing of the manuscript. Publisher Copyright: © 2016 British HIV AssociationObjectives: HIV-positive people have increased risk of infection-related malignancies (IRMs) and infection-unrelated malignancies (IURMs). The aim of the study was to determine the impact of aging on future IRM and IURM incidence. Methods: People enrolled in EuroSIDA and followed from the latest of the first visit or 1 January 2001 until the last visit or death were included in the study. Poisson regression was used to investigate the impact of aging on the incidence of IRMs and IURMs, adjusting for demographic, clinical and laboratory confounders. Linear exponential smoothing models forecasted future incidence. Results: A total of 15 648 people contributed 95 033 person-years of follow-up, of whom 610 developed 643 malignancies [IRMs: 388 (60%); IURMs: 255 (40%)]. After adjustment, a higher IRM incidence was associated with a lower CD4 count [adjusted incidence rate ratio (aIRR) CD4 count < 200 cells/μL: 3.77; 95% confidence interval (CI) 2.59, 5.51; compared with ≥ 500 cells/μL], independent of age, while a CD4 count < 200 cells/μL was associated with IURMs in people aged < 50 years only (aIRR: 2.51; 95% CI 1.40–4.54). Smoking was associated with IURMs (aIRR: 1.75; 95% CI 1.23, 2.49) compared with never smokers in people aged ≥ 50 years only, and not with IRMs. The incidences of both IURMs and IRMs increased with older age. It was projected that the incidence of IRMs would decrease by 29% over a 5-year period from 3.1 (95% CI 1.5–5.9) per 1000 person-years in 2011, whereas the IURM incidence would increase by 44% from 4.1 (95% CI 2.2–7.2) per 1000 person-years over the same period. Conclusions: Demographic and HIV-related risk factors for IURMs (aging and smoking) and IRMs (immunodeficiency and ongoing viral replication) differ markedly and the contribution from IURMs relative to IRMs will continue to increase as a result of aging of the HIV-infected population, high smoking and lung cancer prevalence and a low prevalence of untreated HIV infection. These findings suggest the need for targeted preventive measures and evaluation of the cost−benefit of screening for IURMs in HIV-infected populations.publishersversionPeer reviewe
Transcriptome characterization and high throughput SSRs and SNPs discovery in Cucurbita pepo (Cucurbitaceae)
Background: Cucurbita pepo belongs to the Cucurbitaceae family. The "Zucchini" types rank among the highest-valued vegetables worldwide, and other C. pepo and related Cucurbita spp., are food staples and rich sources of fat and vitamins. A broad range of genomic tools are today available for other cucurbits that have become models for the study of different metabolic processes. However, these tools are still lacking in the Cucurbita genus, thus limiting gene discovery and the process of breeding.Results: We report the generation of a total of 512,751 C. pepo EST sequences, using 454 GS FLX Titanium technology. ESTs were obtained from normalized cDNA libraries (root, leaves, and flower tissue) prepared using two varieties with contrasting phenotypes for plant, flowering and fruit traits, representing the two C. pepo subspecies: subsp. pepo cv. Zucchini and subsp. ovifera cv Scallop. De novo assembling was performed to generate a collection of 49,610 Cucurbita unigenes (average length of 626 bp) that represent the first transcriptome of the species. Over 60% of the unigenes were functionally annotated and assigned to one or more Gene Ontology terms. The distributions of Cucurbita unigenes followed similar tendencies than that reported for Arabidopsis or melon, suggesting that the dataset may represent the whole Cucurbita transcriptome. About 34% unigenes were detected to have known orthologs of Arabidopsis or melon, including genes potentially involved in disease resistance, flowering and fruit quality. Furthermore, a set of 1,882 unigenes with SSR motifs and 9,043 high confidence SNPs between Zucchini and Scallop were identified, of which 3,538 SNPs met criteria for use with high throughput genotyping platforms, and 144 could be detected as CAPS. A set of markers were validated, being 80% of them polymorphic in a set of variable C. pepo and C. moschata accessions.Conclusion: We present the first broad survey of gene sequences and allelic variation in C. pepo, where limited prior genomic information existed. The transcriptome provides an invaluable new tool for biological research. The developed molecular markers are the basis for future genetic linkage and quantitative trait loci analysis, and will be essential to speed up the process of breeding new and better adapted squash varieties. © 2011 Blanca et al; licensee BioMed Central Ltd.Blanca Postigo, JM.; Cañizares Sales, J.; Roig Montaner, MC.; Ziarsolo Areitioaurtena, P.; Nuez Viñals, F.; Picó Sirvent, MB. (2011). Transcriptome characterization and high throughput SSRs and SNPs discovery in Cucurbita pepo (Cucurbitaceae). BMC Genomics. 12:104-117. doi:10.1186/1471-2164-12-104S1041171
Syntenic relationships between cucumber (Cucumis sativus L.) and melon (C. melo L.) chromosomes as revealed by comparative genetic mapping
<p>Abstract</p> <p>Background</p> <p>Cucumber, <it>Cucumis sativus </it>L. (2n = 2 × = 14) and melon, <it>C. melo </it>L. (2n = 2 × = 24) are two important vegetable species in the genus <it>Cucumis </it>(family Cucurbitaceae). Both species have an Asian origin that diverged approximately nine million years ago. Cucumber is believed to have evolved from melon through chromosome fusion, but the details of this process are largely unknown. In this study, comparative genetic mapping between cucumber and melon was conducted to examine syntenic relationships of their chromosomes.</p> <p>Results</p> <p>Using two melon mapping populations, 154 and 127 cucumber SSR markers were added onto previously reported F<sub>2</sub>- and RIL-based genetic maps, respectively. A consensus melon linkage map was developed through map integration, which contained 401 co-dominant markers in 12 linkage groups including 199 markers derived from the cucumber genome. Syntenic relationships between melon and cucumber chromosomes were inferred based on associations between markers on the consensus melon map and cucumber draft genome scaffolds. It was determined that cucumber Chromosome 7 was syntenic to melon Chromosome I. Cucumber Chromosomes 2 and 6 each contained genomic regions that were syntenic with melon chromosomes III+V+XI and III+VIII+XI, respectively. Likewise, cucumber Chromosomes 1, 3, 4, and 5 each was syntenic with genomic regions of two melon chromosomes previously designated as II+XII, IV+VI, VII+VIII, and IX+X, respectively. However, the marker orders in several syntenic blocks on these consensus linkage maps were not co-linear suggesting that more complicated structural changes beyond simple chromosome fusion events have occurred during the evolution of cucumber.</p> <p>Conclusions</p> <p>Comparative mapping conducted herein supported the hypothesis that cucumber chromosomes may be the result of chromosome fusion from a 24-chromosome progenitor species. Except for a possible inversion, cucumber Chromosome 7 has largely remained intact in the past nine million years since its divergence from melon. Meanwhile, many structural changes may have occurred during the evolution of the remaining six cucumber chromosomes. Further characterization of the genomic nature of <it>Cucumis </it>species closely related to cucumber and melon might provide a better understanding of the evolutionary history leading to modern cucumber.</p
The expanded tomato fruit volatile landscape
[EN] The present review aims to synthesize our present knowledge about the mechanisms implied in the biosynthesis of
volatile compounds in the ripe tomato fruit, which have a key role in tomato flavour. The difficulties in identifiying not
only genes or genomic regions but also individual target compounds for plant breeding are addressed. Ample variability
in the levels of almost any volatile compound exists, not only in the populations derived from interspecific crosses
but also in heirloom varieties and even in commercial hybrids. Quantitative trait loci (QTLs) for all tomato aroma volatiles
have been identified in collections derived from both intraspecific and interspecific crosses with different wild
tomato species and they (i) fail to co-localize with structural genes in the volatile biosynthetic pathways and (ii) reveal
very little coincidence in the genomic regions characterized, indicating that there is ample opportunity to reinforce the
levels of the volatiles of interest. Some of the identified genes may be useful as markers or as biotechnological tools
to enhance tomato aroma. Current knowledge about the major volatile biosynthetic pathways in the fruit is summarized.
Finally, and based on recent reports, it is stressed that conjugation to other metabolites such as sugars seems
to play a key role in the modulation of volatile release, at least in some metabolic pathways.We wish to thank the Metabolomics facility at the IBMCP for technical assistance. AG was supported by grants from MinECO and FECYT. This work was facilitated by the European-funded COST action FA1106 QualityFruit.Rambla Nebot, JL.; Tikunov, Y.; Monforte Gilabert, AJ.; Bovy, A.; Granell Richart, A. (2014). The expanded tomato fruit volatile landscape. Journal of Experimental Botany. 65(16):4613-4623. doi:10.1093/jxb/eru128S461346236516Abegaz, E. G., Tandon, K. S., Scott, J. W., Baldwin, E. A., & Shewfelt, R. L. (2004). Partitioning taste from aromatic flavor notes of fresh tomato (Lycopersicon esculentum, Mill) to develop predictive models as a function of volatile and nonvolatile components. Postharvest Biology and Technology, 34(3), 227-235. doi:10.1016/j.postharvbio.2004.05.023Alba, J. M., Montserrat, M., & Fernández-Muñoz, R. (2008). Resistance to the two-spotted spider mite (Tetranychus urticae) by acylsucroses of wild tomato (Solanum pimpinellifolium) trichomes studied in a recombinant inbred line population. Experimental and Applied Acarology, 47(1), 35-47. doi:10.1007/s10493-008-9192-4Baldwin, E. A., Goodner, K., & Plotto, A. (2008). Interaction of Volatiles, Sugars, and Acids on Perception of Tomato Aroma and Flavor Descriptors. Journal of Food Science, 73(6), S294-S307. doi:10.1111/j.1750-3841.2008.00825.xBaldwin, E. A., Goodner, K., Plotto, A., Pritchett, K., & Einstein, M. (2004). Effect of Volatiles and their Concentration on Perception of Tomato Descriptors. Journal of Food Science, 69(8), S310-S318. doi:10.1111/j.1750-3841.2004.tb18023.xBaldwin, E. A., Scott, J. W., Shewmaker, C. K., & Schuch, W. (2000). Flavor Trivia and Tomato Aroma: Biochemistry and Possible Mechanisms for Control of Important Aroma Components. HortScience, 35(6), 1013-1022. doi:10.21273/hortsci.35.6.1013Bender, G., Hummel, T., Negoias, S., & Small, D. M. (2009). Separate signals for orthonasal vs. retronasal perception of food but not nonfood odors. Behavioral Neuroscience, 123(3), 481-489. doi:10.1037/a0015065Bezman, Y., Mayer, F., Takeoka, G. R., Buttery, R. G., Ben-Oliel, G., Rabinowitch, H. D., & Naim, M. (2003). Differential Effects of Tomato (Lycopersicon esculentumMill) Matrix on the Volatility of Important Aroma Compounds†. Journal of Agricultural and Food Chemistry, 51(3), 722-726. doi:10.1021/jf020892hButtery, R. G., Seifert, R. M., Guadagni, D. G., & Ling, L. C. (1971). Characterization of additional volatile components of tomato. Journal of Agricultural and Food Chemistry, 19(3), 524-529. doi:10.1021/jf60175a011Buttery, R. G., Takeoka, G., Teranishi, R., & Ling, L. C. (1990). Tomato aroma components: identification of glycoside hydrolysis volatiles. Journal of Agricultural and Food Chemistry, 38(11), 2050-2053. doi:10.1021/jf00101a010Buttery, R. G., Teranishi, R., Flath, R. A., & Ling, L. C. (1989). Fresh Tomato Volatiles. ACS Symposium Series, 213-222. doi:10.1021/bk-1989-0388.ch017Buttery, R. G., Teranishi, R., Ling, L. C., Flath, R. A., & Stern, D. J. (1988). Quantitative studies on origins of fresh tomato aroma volatiles. Journal of Agricultural and Food Chemistry, 36(6), 1247-1250. doi:10.1021/jf00084a030Carrari, F., Baxter, C., Usadel, B., Urbanczyk-Wochniak, E., Zanor, M.-I., Nunes-Nesi, A., … Fernie, A. R. (2006). Integrated Analysis of Metabolite and Transcript Levels Reveals the Metabolic Shifts That Underlie Tomato Fruit Development and Highlight Regulatory Aspects of Metabolic Network Behavior. Plant Physiology, 142(4), 1380-1396. doi:10.1104/pp.106.088534Causse, M., Friguet, C., Coiret, C., Lépicier, M., Navez, B., Lee, M., … Grandillo, S. (2010). Consumer Preferences for Fresh Tomato at the European Scale: A Common Segmentation on Taste and Firmness. Journal of Food Science, 75(9), S531-S541. doi:10.1111/j.1750-3841.2010.01841.xCausse, M. (2002). QTL analysis of fruit quality in fresh market tomato: a few chromosome regions control the variation of sensory and instrumental traits. Journal of Experimental Botany, 53(377), 2089-2098. doi:10.1093/jxb/erf058Chen, G., Hackett, R., Walker, D., Taylor, A., Lin, Z., & Grierson, D. (2004). Identification of a Specific Isoform of Tomato Lipoxygenase (TomloxC) Involved in the Generation of Fatty Acid-Derived Flavor Compounds. Plant Physiology, 136(1), 2641-2651. doi:10.1104/pp.104.041608Du, X., Finn, C. E., & Qian, M. C. (2010). Bound Volatile Precursors in Genotypes in the Pedigree of ‘Marion’ Blackberry (RubusSp.). Journal of Agricultural and Food Chemistry, 58(6), 3694-3699. doi:10.1021/jf9034089Floss, D. S., & Walter, M. H. (2009). Role of carotenoid cleavage dioxygenase 1 (CCD1) in apocarotenoid biogenesis revisited. Plant Signaling & Behavior, 4(3), 172-175. doi:10.4161/psb.4.3.7840Gardner, H. W., Grove, M. J., & Salch, Y. P. (1996). Enzymic Pathway to Ethyl Vinyl Ketone and 2-Pentenal in Soybean Preparations. Journal of Agricultural and Food Chemistry, 44(3), 882-886. doi:10.1021/jf950509rGoff, S. A. (2006). Plant Volatile Compounds: Sensory Cues for Health and Nutritional Value? Science, 311(5762), 815-819. doi:10.1126/science.1112614González-Mas, M. C., Rambla, J. L., Alamar, M. C., Gutiérrez, A., & Granell, A. (2011). Comparative Analysis of the Volatile Fraction of Fruit Juice from Different Citrus Species. PLoS ONE, 6(7), e22016. doi:10.1371/journal.pone.0022016Goulet, C., Mageroy, M. H., Lam, N. B., Floystad, A., Tieman, D. M., & Klee, H. J. (2012). Role of an esterase in flavor volatile variation within the tomato clade. Proceedings of the National Academy of Sciences, 109(46), 19009-19014. doi:10.1073/pnas.1216515109Granell, A., & Rambla, J. L. (2013). Biosynthesis of Volatile Compounds. The Molecular Biology and Biochemistry of Fruit Ripening, 135-161. doi:10.1002/9781118593714.ch6Guadagni, D. G., Buttery, R. G., & Okano, S. (1963). Odour thresholds of some organic compounds associated with food flavours. Journal of the Science of Food and Agriculture, 14(10), 761-765. doi:10.1002/jsfa.2740141014Hemmerlin, A., Hoeffler, J.-F., Meyer, O., Tritsch, D., Kagan, I. A., Grosdemange-Billiard, C., … Bach, T. J. (2003). Cross-talk between the Cytosolic Mevalonate and the Plastidial Methylerythritol Phosphate Pathways in Tobacco Bright Yellow-2 Cells. Journal of Biological Chemistry, 278(29), 26666-26676. doi:10.1074/jbc.m302526200Howe, G. A., Lee, G. I., Itoh, A., Li, L., & DeRocher, A. E. (2000). Cytochrome P450-Dependent Metabolism of Oxylipins in Tomato. Cloning and Expression of Allene Oxide Synthase and Fatty Acid Hydroperoxide Lyase. Plant Physiology, 123(2), 711-724. doi:10.1104/pp.123.2.711Ilg, A., Beyer, P., & Al-Babili, S. (2008). Characterization of the rice carotenoid cleavage dioxygenase 1 reveals a novel route for geranial biosynthesis. FEBS Journal, 276(3), 736-747. doi:10.1111/j.1742-4658.2008.06820.xKlee, H. J. (2010). Improving the flavor of fresh fruits: genomics, biochemistry, and biotechnology. New Phytologist, 187(1), 44-56. doi:10.1111/j.1469-8137.2010.03281.xKlee, H. J., & Giovannoni, J. J. (2011). Genetics and Control of Tomato Fruit Ripening and Quality Attributes. Annual Review of Genetics, 45(1), 41-59. doi:10.1146/annurev-genet-110410-132507Klee, H. J., & Tieman, D. M. (2013). Genetic challenges of flavor improvement in tomato. Trends in Genetics, 29(4), 257-262. doi:10.1016/j.tig.2012.12.003Koeduka, T., Fridman, E., Gang, D. R., Vassao, D. G., Jackson, B. L., Kish, C. M., … Pichersky, E. (2006). Eugenol and isoeugenol, characteristic aromatic constituents of spices, are biosynthesized via reduction of a coniferyl alcohol ester. Proceedings of the National Academy of Sciences, 103(26), 10128-10133. doi:10.1073/pnas.0603732103Kovács, K., Fray, R. G., Tikunov, Y., Graham, N., Bradley, G., Seymour, G. B., … Grierson, D. (2009). Effect of tomato pleiotropic ripening mutations on flavour volatile biosynthesis. Phytochemistry, 70(8), 1003-1008. doi:10.1016/j.phytochem.2009.05.014Kochevenko, A., Araújo, W. L., Maloney, G. S., Tieman, D. M., Do, P. T., Taylor, M. G., … Fernie, A. R. (2012). Catabolism of Branched Chain Amino Acids Supports Respiration but Not Volatile Synthesis in Tomato Fruits. Molecular Plant, 5(2), 366-375. doi:10.1093/mp/ssr108KURODA, H., OSHIMA, T., KANEDA, H., & TAKASHIO, M. (2005). Identification and Functional Analyses of Two cDNAs That Encode Fatty Acid 9-/13-Hydroperoxide Lyase (CYP74C) in Rice. Bioscience, Biotechnology, and Biochemistry, 69(8), 1545-1554. doi:10.1271/bbb.69.1545Lê, S., & Ledauphin, S. (2006). You like tomato, I like tomato: Segmentation of consumers with missing values. Food Quality and Preference, 17(3-4), 228-233. doi:10.1016/j.foodqual.2005.08.001Lengard, V., & Kermit, M. (2006). 3-Way and 3-block PLS regressions in consumer preference analysis. Food Quality and Preference, 17(3-4), 234-242. doi:10.1016/j.foodqual.2005.05.005Lewinsohn, E., Sitrit, Y., Bar, E., Azulay, Y., Meir, A., Zamir, D., & Tadmor, Y. (2005). Carotenoid Pigmentation Affects the Volatile Composition of Tomato and Watermelon Fruits, As Revealed by Comparative Genetic Analyses. Journal of Agricultural and Food Chemistry, 53(8), 3142-3148. doi:10.1021/jf047927tLiavonchanka, A., & Feussner, I. (2006). Lipoxygenases: Occurrence, functions and catalysis. Journal of Plant Physiology, 163(3), 348-357. doi:10.1016/j.jplph.2005.11.006Mageroy, M. H., Tieman, D. M., Floystad, A., Taylor, M. G., & Klee, H. J. (2011). A Solanum lycopersicum catechol-O-methyltransferase involved in synthesis of the flavor molecule guaiacol. The Plant Journal, 69(6), 1043-1051. doi:10.1111/j.1365-313x.2011.04854.xMaloney, G. S., Kochevenko, A., Tieman, D. M., Tohge, T., Krieger, U., Zamir, D., … Klee, H. J. (2010). Characterization of the Branched-Chain Amino Acid Aminotransferase Enzyme Family in Tomato. Plant Physiology, 153(3), 925-936. doi:10.1104/pp.110.154922Marilley, L. (2004). Flavours of cheese products: metabolic pathways, analytical tools and identification of producing strains. International Journal of Food Microbiology, 90(2), 139-159. doi:10.1016/s0168-1605(03)00304-0Marlatt, C., Ho, C. T., & Chien, M. (1992). Studies of aroma constituents bound as glycosides in tomato. Journal of Agricultural and Food Chemistry, 40(2), 249-252. doi:10.1021/jf00014a016Mathieu, S., Cin, V. D., Fei, Z., Li, H., Bliss, P., Taylor, M. G., … Tieman, D. M. (2008). Flavour compounds in tomato fruits: identification of loci and potential pathways affecting volatile composition. Journal of Experimental Botany, 60(1), 325-337. doi:10.1093/jxb/ern294Matsui, K. (2006). Green leaf volatiles: hydroperoxide lyase pathway of oxylipin metabolism. Current Opinion in Plant Biology, 9(3), 274-280. doi:10.1016/j.pbi.2006.03.002Matsui, K., Kurishita, S., Hisamitsu, A., & Kajiwara, T. (2000). A lipid-hydrolysing activity involved in hexenal formation. Biochemical Society Transactions, 28(6), 857-860. doi:10.1042/bst0280857Matsui, K., Ujita, C., Fujimoto, S., Wilkinson, J., Hiatt, B., Knauf, V., … Feussner, I. (2000). Fatty acid 9- and 13-hydroperoxide lyases from cucumber1. FEBS Letters, 481(2), 183-188. doi:10.1016/s0014-5793(00)01997-9Mita, G., Quarta, A., Fasano, P., De Paolis, A., Di Sansebastiano, G. P., Perrotta, C., … Santino, A. (2005). Molecular cloning and characterization of an almond 9-hydroperoxide lyase, a new CYP74 targeted to lipid bodies*. Journal of Experimental Botany, 56(419), 2321-2333. doi:10.1093/jxb/eri225Moummou, H., Tonfack, L. B., Chervin, C., Benichou, M., Youmbi, E., Ginies, C., … van der Rest, B. (2012). Functional characterization of SlscADH1, a fruit-ripening-associated short-chain alcohol dehydrogenase of tomato. Journal of Plant Physiology, 169(15), 1435-1444. doi:10.1016/j.jplph.2012.06.007Nagegowda, D. A. (2010). Plant volatile terpenoid metabolism: Biosynthetic genes, transcriptional regulation and subcellular compartmentation. FEBS Letters, 584(14), 2965-2973. doi:10.1016/j.febslet.2010.05.045Negoias, S., Visschers, R., Boelrijk, A., & Hummel, T. (2008). New ways to understand aroma perception. Food Chemistry, 108(4), 1247-1254. doi:10.1016/j.foodchem.2007.08.030Noordermeer, M. A., Veldink, G. A., & Vliegenthart, J. F. . (1999). Alfalfa contains substantial 9-hydroperoxide lyase activity and a 3Z
:2E
-enal isomerase. FEBS Letters, 443(2), 201-204. doi:10.1016/s0014-5793(98)01706-2Ortiz-Serrano, P., & Gil, J. V. (2007). Quantitation of Free and Glycosidically Bound Volatiles in and Effect of Glycosidase Addition on Three Tomato Varieties (Solanum lycopersicumL.). Journal of Agricultural and Food Chemistry, 55(22), 9170-9176. doi:10.1021/jf0715673Ortiz-Serrano, P., & Gil, J. V. (2010). Quantitative Comparison of Free and Bound Volatiles of Two Commercial Tomato Cultivars (Solanum lycopersicumL.) during Ripening. Journal of Agricultural and Food Chemistry, 58(2), 1106-1114. doi:10.1021/jf903366rOrzaez, D., Medina, A., Torre, S., Fernández-Moreno, J. P., Rambla, J. L., Fernández-del-Carmen, A., … Granell, A. (2009). A Visual Reporter System for Virus-Induced Gene Silencing in Tomato Fruit Based on Anthocyanin Accumulation. Plant Physiology, 150(3), 1122-1134. doi:10.1104/pp.109.139006Piombino, P., Sinesio, F., Moneta, E., Cammareri, M., Genovese, A., Lisanti, M. T., … Grandillo, S. (2013). Investigating physicochemical, volatile and sensory parameters playing a positive or a negative role on tomato liking. Food Research International, 50(1), 409-419. doi:10.1016/j.foodres.2012.10.033Rick, C. M., Uhlig, J. W., & Jones, A. D. (1994). High alpha-tomatine content in ripe fruit of Andean Lycopersicon esculentum var. cerasiforme: developmental and genetic aspects. Proceedings of the National Academy of Sciences, 91(26), 12877-12881. doi:10.1073/pnas.91.26.12877Sánchez, G., Besada, C., Badenes, M. L., Monforte, A. J., & Granell, A. (2012). A Non-Targeted Approach Unravels the Volatile Network in Peach Fruit. PLoS ONE, 7(6), e38992. doi:10.1371/journal.pone.0038992Simkin, A. J., Schwartz, S. H., Auldridge, M., Taylor, M. G., & Klee, H. J. (2004). The tomato carotenoid cleavage dioxygenase 1 genes contribute to the formation of the flavor volatiles β-ionone, pseudoionone, and geranylacetone. The Plant Journal, 40(6), 882-892. doi:10.1111/j.1365-313x.2004.02263.xSinesio, F., Cammareri, M., Moneta, E., Navez, B., Peparaio, M., Causse, M., & Grandillo, S. (2010). Sensory Quality of Fresh French and Dutch Market Tomatoes: A Preference Mapping Study with Italian Consumers. Journal of Food Science, 75(1), S55-S67. doi:10.1111/j.1750-3841.2009.01424.xSpeirs, J., Lee, E., Holt, K., Yong-Duk, K., Steele Scott, N., Loveys, B., & Schuch, W. (1998). Genetic Manipulation of Alcohol Dehydrogenase Levels in Ripening Tomato Fruit Affects the Balance of Some Flavor Aldehydes and Alcohols. Plant Physiology, 117(3), 1047-1058. doi:10.1104/pp.117.3.1047Tadmor, Y., Fridman, E., Gur, A., Larkov, O., Lastochkin, E., Ravid, U., … Lewinsohn, E. (2002). Identification ofmalodorous, a Wild Species Allele Affecting Tomato Aroma That Was Selected against during Domestication. Journal of Agricultural and Food Chemistry, 50(7), 2005-2009. doi:10.1021/jf011237xTandon, K. S., Baldwin, E. A., Scott, J. W., & Shewfelt, R. L. (2003). Linking Sensory Descriptors to Volatile and Nonvolatile Components of Fresh Tomato Flavor. Journal of Food Science, 68(7), 2366-2371. doi:10.1111/j.1365-2621.2003.tb05774.xTieman, D., Bliss, P., McIntyre, L. M., Blandon-Ubeda, A., Bies, D., Odabasi, A. Z., … Klee, H. J. (2012). The Chemical Interactions Underlying Tomato Flavor Preferences. Current Biology, 22(11), 1035-1039. doi:10.1016/j.cub.2012.04.016Tieman, D. M., Loucas, H. M., Kim, J. Y., Clark, D. G., & Klee, H. J. (2007). Tomato phenylacetaldehyde reductases catalyze the last step in the synthesis of the aroma volatile 2-phenylethanol. Phytochemistry, 68(21), 2660-2669. doi:10.1016/j.phytochem.2007.06.005Tieman, D., Taylor, M., Schauer, N., Fernie, A. R., Hanson, A. D., & Klee, H. J. (2006). Tomato aromatic amino acid decarboxylases participate in synthesis of the flavor volatiles 2-phenylethanol and 2-phenylacetaldehyde. Proceedings of the National Academy of Sciences, 103(21), 8287-8292. doi:10.1073/pnas.0602469103Tieman, D. M., Zeigler, M., Schmelz, E. A., Taylor, M. G., Bliss, P., Kirst, M., & Klee, H. J. (2006). Identification of loci affecting flavour volatile emissions in tomato fruits. Journal of Experimental Botany, 57(4), 887-896. doi:10.1093/jxb/erj074Tieman, D., Zeigler, M., Schmelz, E., Taylor, M. G., Rushing, S., Jones, J. B., & Klee, H. J. (2010). Functional analysis of a tomato salicylic acid methyl transferase and its role in synthesis of the flavor volatile methyl salicylate. The Plant Journal, 62(1), 113-123. doi:10.1111/j.1365-313x.2010.04128.xTikunov, Y. M., de Vos, R. C. H., González Paramás, A. M., Hall, R. D., & Bovy, A. G. (2009). A Role for Differential Glycoconjugation in the Emission of Phenylpropanoid Volatiles from Tomato Fruit Discovered Using a Metabolic Data Fusion Approach. Plant Physiology, 152(1), 55-70. doi:10.1104/pp.109.146670Tikunov, Y., Lommen, A., de Vos, C. H. R., Verhoeven, H. A., Bino, R. J., Hall, R. D., & Bovy, A. G. (2005). A Novel Approach for Nontargeted Data Analysis for Metabolomics. Large-Scale Profiling of Tomato Fruit Volatiles. Plant Physiology, 139(3), 1125-1137. doi:10.1104/pp.105.068130Tikunov, Y. M., Molthoff, J., de Vos, R. C. H., Beekwilder, J., van Houwelingen, A., van der Hooft, J. J. J., … Bovy, A. G. (2013). NON-SMOKY GLYCOSYLTRANSFERASE1 Prevents the Release of Smoky Aroma from Tomato Fruit. The Plant Cell, 25(8), 3067-3078. doi:10.1105/tpc.113.114231Tzin, V., Rogachev, I., Meir, S., Moyal Ben Zvi, M., Masci, T., Vainstein, A., … Galili, G. (2013). Tomato fruits expressing a bacterial feedback-insensitive 3-deoxy-d-arabino-heptulosonate 7-phosphate synthase of the shikimate pathway possess enhanced levels of multiple specialized metabolites and upgraded aroma. Journal of Experimental Botany, 64(14), 4441-4452. doi:10.1093/jxb/ert250Ursem, R., Tikunov, Y., Bovy, A., van Berloo, R., & van Eeuwijk, F. (2008). A correlation network approach to metabolic data analysis for tomato fruits. Euphytica, 161(1-2), 181-193. doi:10.1007/s10681-008-9672-yVancanneyt, G., Sanz, C., Farmaki, T., Paneque, M., Ortego, F., Castanera, P., & Sanchez-Serrano, J. J. (2001). Hydroperoxide lyase depletion in transgenic potato plants leads to an increase in aphid performance. Proceedings of the National Academy of Sciences, 98(14), 8139-8144. doi:10.1073/pnas.141079498Vogel, J. T., Tan, B.-C., McCarty, D. R., & Klee, H. J. (2008). The Carotenoid Cleavage Dioxygenase 1 Enzyme Has Broad Substrate Specificity, Cleaving Multiple Carotenoids at Two Different Bond Positions. Journal of Biological Chemistry, 283(17), 11364-11373. doi:10.1074/jbc.m710106200Vogel, J. T., Tieman, D. M., Sims, C. A., Odabasi, A. Z., Clark, D. G., & Klee, H. J. (2010). Carotenoid content impacts flavor acceptability in tomato (Solanum lycopersicum). Journal of the Science of Food and Agriculture, 90(13), 2233-2240. doi:10.1002/jsfa.4076Walter, M. H., Floss, D. S., & Strack, D. (2010). Apocarotenoids: hormones, mycorrhizal metabolites and aroma volatiles. Planta, 232(1), 1-17. doi:10.1007/s00425-010-1156-3Zanor, M. I., Rambla, J.-L., Chaïb, J., Steppa, A., Medina, A., Granell, A., … Causse, M. (2009). Metabolic characterization of loci affecting sensory attributes in tomato allows an assessment of the influence of the levels of primary metabolites and volatile organic contents. Journal of Experimental Botany, 60(7), 2139-2154. doi:10.1093/jxb/erp086Zhang, B., Chen, K., Bowen, J., Allan, A., Espley, R., Karunairetnam, S., & Ferguson, I. (2006). Differential expression within the LOX gene family in ripening kiwifruit. Journal of Experimental Botany, 57(14), 3825-3836. doi:10.1093/jxb/erl151Zorrilla-Fontanesi, Y., Rambla, J.-L., Cabeza, A., Medina, J. J., Sánchez-Sevilla, J. F., Valpuesta, V., … Amaya, I. (2012). Genetic Analysis of Strawberry Fruit Aroma and Identification of O-Methyltransferase FaOMT as the Locus Controlling Natural Variation in Mesifurane Content. Plant Physiology, 159(2), 851-870. doi:10.1104/pp.111.18831
Development and Validation of a Risk Score for Chronic Kidney Disease in HIV Infection Using Prospective Cohort Data from the D:A:D Study
Ristola M. on työryhmien DAD Study Grp ; Royal Free Hosp Clin Cohort ; INSIGHT Study Grp ; SMART Study Grp ; ESPRIT Study Grp jäsen.Background Chronic kidney disease (CKD) is a major health issue for HIV-positive individuals, associated with increased morbidity and mortality. Development and implementation of a risk score model for CKD would allow comparison of the risks and benefits of adding potentially nephrotoxic antiretrovirals to a treatment regimen and would identify those at greatest risk of CKD. The aims of this study were to develop a simple, externally validated, and widely applicable long-term risk score model for CKD in HIV-positive individuals that can guide decision making in clinical practice. Methods and Findings A total of 17,954 HIV-positive individuals from the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study with >= 3 estimated glomerular filtration rate (eGFR) values after 1 January 2004 were included. Baseline was defined as the first eGFR > 60 ml/min/1.73 m2 after 1 January 2004; individuals with exposure to tenofovir, atazanavir, atazanavir/ritonavir, lopinavir/ritonavir, other boosted protease inhibitors before baseline were excluded. CKD was defined as confirmed (>3 mo apart) eGFR In the D:A:D study, 641 individuals developed CKD during 103,185 person-years of follow-up (PYFU; incidence 6.2/1,000 PYFU, 95% CI 5.7-6.7; median follow-up 6.1 y, range 0.3-9.1 y). Older age, intravenous drug use, hepatitis C coinfection, lower baseline eGFR, female gender, lower CD4 count nadir, hypertension, diabetes, and cardiovascular disease (CVD) predicted CKD. The adjusted incidence rate ratios of these nine categorical variables were scaled and summed to create the risk score. The median risk score at baseline was -2 (interquartile range -4 to 2). There was a 1: 393 chance of developing CKD in the next 5 y in the low risk group (risk score = 5, 505 events), respectively. Number needed to harm (NNTH) at 5 y when starting unboosted atazanavir or lopinavir/ritonavir among those with a low risk score was 1,702 (95% CI 1,166-3,367); NNTH was 202 (95% CI 159-278) and 21 (95% CI 19-23), respectively, for those with a medium and high risk score. NNTH was 739 (95% CI 506-1462), 88 (95% CI 69-121), and 9 (95% CI 8-10) for those with a low, medium, and high risk score, respectively, starting tenofovir, atazanavir/ritonavir, or another boosted protease inhibitor. The Royal Free Hospital Clinic Cohort included 2,548 individuals, of whom 94 individuals developed CKD (3.7%) during 18,376 PYFU (median follow-up 7.4 y, range 0.3-12.7 y). Of 2,013 individuals included from the SMART/ESPRIT control arms, 32 individuals developed CKD (1.6%) during 8,452 PYFU (median follow-up 4.1 y, range 0.6-8.1 y). External validation showed that the risk score predicted well in these cohorts. Limitations of this study included limited data on race and no information on proteinuria. Conclusions Both traditional and HIV-related risk factors were predictive of CKD. These factors were used to develop a risk score for CKD in HIV infection, externally validated, that has direct clinical relevance for patients and clinicians to weigh the benefits of certain antiretrovirals against the risk of CKD and to identify those at greatest risk of CKD.Peer reviewe
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